Targeting tRNA-dependent tyrosine usage unveils a metabolic vulnerability in hepatocellular carcinoma

Domain: chemistry
Published: 2026-03-06
Editorial outcome: major_revision

Abstract
Cancer cells reprogram translation and metabolism to fuel tumorigenesis. Here, we show that hepatocellular carcinoma (HCC) paradoxically maintains low tyrosine levels despite increased uptake and reduced metabolism, redirecting tyrosine to translation via MYC-driven upregulation of tyrosyl-tRNA synthetase 1 (YARS1) and tRNA-TyrGUA. Restricting tyrosine translation availability (RTTA) via dietary limitation, YARS1/tRNA-TyrGUA ablation, tyrosine degradation (TAL), or YARS1 inhibition (tyrosinol) disturbs this adaptation, leading to the mitigation of tumorigenesis and extension of survival. Mechanistically, RTTA reduces tyrosine codon-dependent translation of mitochondrial complex I subunit NDUFB8 and lipid regulator SCD1, causing complex I misassembly, oxidative phosphorylation failure, and lipid peroxidation-induced ferroptosis. Genome-wide CRISPR screening identifies that loss of GPX4 and BCL2 by genetic manipulation or pharmacological treatment enhances the ability of RTTA to inhibit hepatocellular carcinogenesis. Our findings establish RTTA as a therapeutic strategy targeting tyrosine dependency and highlight combinatorial targeting of translation-metabolism crosstalk and ferroptosis pathways in liver cancer.

Introduction
Reprogramming of amino acid utilization pathways to optimise catabolic and anabolic processes, thus promoting cancer cell proliferation and preventing cell death, constitutes a common hallmark of tumorigenic metabolic plasticity1–4. Specifically, oncogene-driven rewiring of amino acid flux involves fine-tuning between catabolism and protein synthesis due to the increased mRNA translation requirements and the reprogramming of mRNA translation, conferring a demand for specific amino acids5,6. However, a deep understanding of how these two features coordinate in cancer pathogenesis to maintain amino acid utilisation balance is still lacking.

Tyrosine, a large neutral amino acid, is a non-essential amino acid that can be converted from phenylalanine via phenylalanine hydroxylase in vivo7,8. In mammals, some L-type amino acid transport systems, including SLC7A5 and SLC43A1, are responsible for transporting diverse neutral amino acids from the extracellular matrix into the intracellular space, including tyrosine, phenylalanine, leucine, histidine, tryptophan, valine, isoleucine, and alanine9,10. The lysosomal amino acid transporter protein SLC38A9 is required to efficiently transport neutral amino acids back into the intracellular amino acid pool after protein degradation in lysosomes11. In hepatocytes, tyrosine can be degraded, mediated by a five-enzyme cascade (TAT-HPD-HGD-GSTZ1-FAH), to generate fumaric acid and acetoacetate in addition to its role as a constituent unit of proteins12. Consequently, when there is an inborn functional deficiency of hepatic tyrosine catabolic enzymes, tyrosine and its downstream metabolites accumulate in the body, which significantly affects newborn survival and childhood development, i.e., tyrosinemia13,14. Clinically, long-term tyrosine-restricted diets are established for disease management in these patients, demonstrating the feasibility of tyrosine-restricted diets in HCC patients.

In this study, we found that HCC cells hijack tyrosine uptake and degradation to shunt tyrosine towards protein synthesis, representing a critical adaptation in response to hepatocellular carcinogenesis, thereby remodelling the balance of tyrosine utilisation. Restriction of tyrosine translation availability through dietary intervention, genetic manipulation, or pharmacological inhibition disturbs this delicate balance, which then impairs oxidative phosphorylation and triggers ferroptosis, ultimately alleviating tumorigenesis and potentiating cancer therapy combined with sorafenib or venetoclax, which represents a potential therapeutic window for patients with liver cancer.

Results
HCC hijack tyrosine uptake and degradation to preserve oncogenic tyrosine levels
To determine whether amino-acid levels were changed in HCC, targeted metabolomics on tumour and normal liver tissues obtained from human and mouse sources was performed, of which the mouse liver tumours were isolated from H11LNL-Myc; Alb-cre;Alb-cre mice (hereafter referred to as Myc/Alb-cre). In this mouse model, hepatocyte-specific overexpression of MYC sequentially drove the development of hepatomegaly and multiple high-grade tumours in the mouse liver within 12 weeks of age15. Irrespective of whether the tissues were from humans or mice, tyrosine was the most significantly decreased amino acid in the tumour compared to the normal liver (Fig. 1a, b). Our observations were consistent with the previous metabolomics results in human HCC patients (n=130) and mTOR-hyperactivation-driven HCC mouse model1,16. Meanwhile, tumour tyrosine levels were negatively correlated with tumour diameter (Fig. 1c). We also isolated interstitial fluid from liver tumours of different sizes to measure tyrosine concentration. The results showed no significant correlation between tumour size and tyrosine levels in the tumour interstitial fluid, indicating that tumour size did not affect local tyrosine availability (Supplementary Fig. 1a). Therefore, we speculated whether high levels of tyrosine favour liver tumorigenesis.

To identify the role of tyrosine in hepatocellular carcinogenesis in vivo, we established three mouse HCC models, including a MYC overexpression-driven HCC model, a DEN treatment-induced HCC model, and an intrahepatic injection model of human HCC cells to validate the effect of tyrosine levels on HCC development. Mice were fed diets containing 0% or 500% of the normal tyrosine levels in the standard diet (tyrosine 100%). Surprisingly, we found that restriction of dietary tyrosine intake (Tyr 0% diet, hereafter referred to as TR diet) led to a significant decrease in characteristic hepatomegaly, liver-to-body weight ratio, tumour burdens, and diameters relative to the standard diet (Tyr 100% diet) (Fig. 1d–f). This phenomenon was opposite to the supplementation of dietary tyrosine intake (Tyr 500% diet) (Supplementary Fig. 1b–d). Remarkably, the TR diet prolonged the survival time in tumour-bearing mice, while the tyrosine-supplemented diet shortened the survival time of these mice (Fig. 1g). Moreover, at 9 weeks of age after tumours had already developed in Myc/Alb-cre mice, tyrosine-restricted diets were applied to evaluate their impact on established tumorigenesis. Results also demonstrated that restriction of dietary tyrosine intake (Tyr 0% diet) significantly inhibited liver tumour development compared to the standard diet (Tyr 100% diet) (Supplementary Fig. 1e–g). These findings indicate that tyrosine-restricted diets exert significant therapeutic efficacy against HCC development during tumour initiation and establishment. Tyrosine restriction mainly reduced the tyrosine levels in the liver, with minimal effects on other amino acids (Supplementary Fig. 1h). To consolidate the above findings, we also determined whether low tyrosine abundance inhibits cancer cell growth in vitro. Consistent with in vivo effects, tyrosine restriction (Tyr 0%) substantially reduced cell viability and induced cell cycle arrest, along with increasing the ratio of early and late apoptotic cells compared with the standard medium (Tyr 100%) (Supplementary Fig. 2a–g), whereas tyrosine supplementation promoted tumour proliferation (Supplementary Fig. 2h–j). Together, these results indicated that tyrosine abundance is critical for tumorigenicity.

Moreover, to evaluate the systemic consequences of tyrosine-deficient diets in mice, wild-type mice were fed with a 10-week tyrosine-deficient diet to assess tyrosine restriction effects on body and organ weights and food intake. The results demonstrated that tyrosine restriction increased total body weight and fat mass, along with an increase in liver weight (Supplementary Fig. 3a, b). No significant differences were observed in the weight of other organs or in daily food intake (Supplementary Fig. 3b, c). Concurrently, the levels of alanine aminotransferase (ALT), aspartate aminotransferase (AST), triglyceride (TG), total cholesterol (TC), creatinine (CREA), creatine kinase (CK), and lactate dehydrogenase (LDH), established biomarkers for liver, kidney, and myocardial injury, were measured. Tyrosine-deficient diets induced liver injury in mice, whereas no significant effects on kidney and heart functions (Supplementary Fig. 3d). Furthermore, tyrosine-deficient mice showed the lipid droplet accumulation in liver, whereas no pathological changes or tissue injury were observed in other organs (Supplementary Fig. 3e). Moreover, given tyrosine’s role as a dopamine precursor, we evaluated depression-like behaviours using the tail suspension test (TST), a method for assessing depressive states in mice. No significant behavioural differences were observed between the two groups after 10 weeks of diet intervention (Supplementary Fig. 3f). These findings indicate that tyrosine deprivation induces lipid droplet accumulation in wild-type mice, consistent with previous studies that combined dietary deprivation of tyrosine and methionine with an HFD diet disrupts lipid metabolism17.

Next, we speculated whether the low levels of tyrosine in HCC tissues were due to reduced tyrosine uptake or increased tyrosine metabolism. To investigate this hypothesis, tyrosine transport was measured by an ex vivo assay using 3H-tyrosine and an in vitro assay using 13C-tyrosine. These assays confirmed that tyrosine uptake was upregulated in HCC (Fig. 1h and Supplementary Fig. 4a). However, 13C-tyrosine metabolic tracing assay in primary hepatocytes isolated from normal or HCC mouse livers revealed a decreased conversion of tyrosine to its downstream metabolites, including fumarate and citrate, in primary cancer cells compared with primary normal hepatocytes (Supplementary Fig. 4b, c). Consistently, the downstream metabolites of tyrosine were also decreased in HCC tissues (Supplementary Fig. 4d). These results suggested that the rapid influx of tyrosine to its downstream metabolites did not occur, despite increased uptake in HCC. Consistent with our observations, transcriptomic and proteomic analyses of HCC datasets (The Cancer Genome Atlas (TCGA) and The Clinical Proteomic Tumour Analysis Consortium (CPTAC)) also showed that the levels of tyrosine transporters such as SLC7A5, SLC43A1, and SLC38A9 were increased in tumour tissues compared with adjacent normal tissues, whereas the levels of tyrosine metabolism proteins such as TAT, HPD, HGD, FAH, and GSTZ1 were decreased in HCC samples (Fig. 1i, Supplementary Fig. 4e, f, and Supplementary Fig. 5a–g). Gene set enrichment analysis (GSEA) also indicated that the tyrosine metabolism pathway was downregulated in HCC tissues and cells (Supplementary Fig. 5b, e, and g). Finally, we validated the upregulation of tyrosine transporters and loss of tyrosine metabolism proteins in tumours by Western blotting and immunohistochemistry (Fig. 1j, k, Supplementary Fig. 4g, h, and Supplementary Fig. 5h, i). Furthermore, we found that SLC7A5 transporter inhibitor (JPH203) treatment resulted in a significantly reduction tyrosine uptake in liver cancer cells to further corroborate the upregulation of tyrosine uptake in HCC (Supplementary Fig. 4i). Moreover, based on the TCGA dataset, upregulation of tyrosine transporters and loss of tyrosine metabolism genes were associated with a worse prognosis for HCC patients, with the most significant effects reflecting the protective role of tyrosine in tumorigenesis (Fig. 1l). Thus, our findings indicated that liver tumours increase tyrosine uptake and reduce tyrosine metabolism to compensate for another intracellular pathway that consumes tyrosine (Fig. 1m).

MYC fuels tyrosine translation availability via YARS1 in HCC
In addition to undergoing metabolism, another primary consumption of intracellular tyrosine is its role as a building block in protein synthesis. We presumed that the diversion of tyrosine utilisation, i.e., reduced tyrosine metabolism in HCC tissues, was attributed to accommodating the high requirements of the tumour proteome (Fig. 2a). To validate this hypothesis, an ex vivo isotopic tracer method using 3H-tyrosine confirmed that both the total amount and the relative proportion of tyrosine incorporated into protein synthesis were indeed increased in liver cancer compared to normal liver (Fig. 2b, c). Consistent with this observation, the tRNA-TyrGUA, a tyrosine cognate isoacceptor tRNA, exhibited the most marked elevation among all tRNAs in HCC relative to normal tissues by tRNA RT-qPCR (after tRNA de-modification) and Northern blotting (Fig. 2d and Supplementary Fig. 6a). In contrast, the expression of another tRNA-TyrAUA isoacceptor did not change, which was associated with the low distribution of its cognate TAT codon in the human transcriptome (Fig. 2d and Supplementary Fig. 6a, b). Moreover, tyrosyl-tRNA synthetase 1 (YARS1) expression was upregulated in HCC and correlated with poor survival among HCC patients (Fig. 2e, f and Supplementary Fig. 6c–f). Subsequently, in-depth analysis of amino acid and codon enrichment in proteins with translation upregulated and downregulated in HCC patients further confirmed that the content of tyrosine and its cognate TAC codon was significantly increased in translation-upregulated proteins (unchanged at mRNA levels but increased at protein levels) as compared with translation-downregulated proteins (unchanged at mRNA levels but decreased at protein levels) (Fig. 2g, h). Taken together, our findings indicated that unmetabolized tyrosine is utilised in protein synthesis, promoting tumorigenicity and progression.

Moreover, to further identify that the increased translational utilisation of tyrosine is a specific feature of liver tumour progression, the uptake of tyrosine, lysine, and alanine between tumour tissues and normal tissues was measured. We found that while the uptake rates of both tyrosine and lysine were significantly elevated in tumour tissues compared to normal tissues, only tyrosine exhibited a significantly higher incorporation ratio into protein synthesis within HCC (Supplementary Fig. 6g). We also found that lysine-tRNA ligase (KARS1) and alanine-tRNA synthetase (AARS1), responsible for lysine and alanine translational utilisation, respectively, were significantly downregulated in tumour tissues (Supplementary Fig. 6h). Correspondingly, the levels of tRNA-LysCUU showed a significant decrease and the levels of tRNA-Ala remained unchanged (Supplementary Fig. 6i), implying that an increase in amino acid uptake, alongside elevated levels of aminoacyl-tRNAsynthetases and cognate isoacceptor tRNA, is essential for promoting translational utilisation of amino acids.

Gene amplification of MYC is observed across multiple human cancer types, explicitly accounting for 11.56% of HCC patients18. MYC hyperactivation or overexpression, alone or in combination with other oncogenic mutations, drives active translation, thus increasing total protein production in many malignancies, contributing to its ability to regulate tRNA and ribosome biogenesis19–22. Here, we found MYC potently bound to the promoter of YARS1 in multiple human and mouse cells by analysing the chromatin immunoprecipitation (ChIP)-sequencing database (Supplementary Fig. 7a, b). Indeed, ChIP and luciferase reporter assays also confirmed that a conserved element within the YARS1 promoter was responsible for its interaction with MYC (Fig. 2i and Supplementary Fig. 7c). Notably, the expression of YARS1 exhibited the most marked reduction among all aminoacyl-tRNA synthetases after knocking down MYC in SNU398 cells, indicating that tyrosine translational utilisation, for which YARS1 is responsible, plays a critical role in increased mRNA translation requirements in hepatocellular carcinoma (Supplementary Fig. 7d). Furthermore, MYC knockdown also decreased the protein levels of YARS1 (Fig. 2j). Consistent with these findings, a positive correlation was observed between the mRNA levels of MYC and YARS1 (Supplementary Fig. 7e, f). We also found that only the expression levels of TAT and FAH were negatively correlated with MYC expression, indicating that the reduced levels of tyrosine metabolic genes are not fully dependent on MYC expression (Supplementary Fig. 7g). Collectively, these results showed a direct link for oncogenic MYC signalling in increasing the expression of YARS1, which identifies a role that oncogenic transcriptional programmes fulfil requirements in protein synthesis in cancer cells by upregulating aminoacyl-tRNA synthetase biogenesis in HCC.

To assess the functional contribution of tyrosine translation bioavailability in developing HCC, we first explored the results from the published genome-wide HCC screen dataset based on the Cancer Dependency Map (DepMap) project. Among all aminoacyl-tRNA synthetases, YARS1 ranked as the second cell-survival-dependent gene in multiple HCC cell screens. In contrast, the tyrosine metabolism gene set, especially TAT, exhibited a cell-survival-independent pattern, i.e., knocking out the tyrosine metabolism gene set promoted HCC survival, which is also consistent with previous reports23–25 (Supplementary Fig. 7h, i). This result suggests that targeting tyrosine translation bioavailability represents a vulnerability in liver cancer, wherein improving the translation utilisation of tyrosine enhances cell fitness, whereas its disruption impairs cell fitness.

Moreover, to further illustrate that tyrosine dependency is a common feature of liver tumorigenesis, the expression levels of YARS1 were first evaluated. We found that YARS1 expression was upregulated in the DEN-induced mouse liver tumour model (Supplementary Fig. 8a). Next, wild-type mice were injected with the plasmids of myr-AKT and NRASG12V via hydrodynamic tail-vein injection to induce HCC tumorigenesis, together with feeding a tyrosine-modified diet. The results demonstrated that tyrosine restriction also significantly attenuated the progression of AKT/NRASG12V-driven HCC (Supplementary Fig. 8b–d). Furthermore, we found that hepatocellular carcinoma’s dependence on tyrosine was determined by its protein synthesis activity. Specifically, tumour cells exhibiting higher protein synthesis activity showed greater inhibition of cell growth upon tyrosine restriction. We measured protein synthesis activity, the expression levels of MYC, YARS1, and the tyrosine metabolism gene set in seven HCC cell lines and one normal hepatic cell line (THLE-2). The results revealed that HCC lines demonstrated higher protein synthesis activity, elevated YARS1 expression, and reduced tyrosine metabolism gene set compared to normal hepatocytes (Supplementary Fig. 8e). Tyrosine restriction was less effective at inhibiting cell proliferation of the cell lines with low-proteinsynthesis activity (THLE-2 or HEPG2), compared to those with high protein synthesis activity (SNU398 or PLCPRF5) (Supplementary Fig. 8f). Moreover, we found that overexpressing MYC in SNU449 cells with low-protein synthesis activity to enhance protein synthesis activity, increased the inhibitory effect of tyrosine restriction, whereas MYC knockdown in SNU398 cells with high protein synthesis activity to reduce protein synthesis activity, decreased this inhibitory effect of tyrosine restriction (Supplementary Fig. 8g). Collectively, these results demonstrate that tyrosine dependency in HCC cells is primarily governed by global protein synthesis activity rather than being exclusively restricted to MYC-driven carcinogenesis.

Moreover, we found that knocking down YARS1 or tRNA-TyrGUA reduced the fitness of HCC cells (Supplementary Fig. 9a–p). Next, control or YARS1-depleted HCCLM3 cells were implanted in the BALB/c nude mouse liver. Consistent with in vitro effects, YARS1 depletion reduced tumour burdens and tumour diameters, which in turn prolonged the survival time of tumour-bearing mice (Fig. 2k–m). Furthermore, we injected adeno-associated virus 8 (AAV8) into Myc/Alb-cre mice at one month of age to specifically knock down YARS1 in hepatocytes. Similar to our previous results, Myc/Alb-cre mice injected with AAV8-shYARS1 developed significantly fewer tumours with smaller diameters and an extended survival time of tumour-bearing mice (Fig. 2n–p and Supplementary Fig. 9q). Taken together, the presented experiments demonstrated that liver cancer is sensitive to the deletion of YARS1 and tRNA-TyrGUA-mediated limitation of tyrosine translation availability.

RTTA decreases the translation of NDUFB8 and SCD1 in liver cancer
To demonstrate whether the limitation of tyrosine is sufficient to reduce tyrosine translation bioavailability, we validated it through two approaches. First, after the restriction of tyrosine or YARS1 depletion either in vitro or in vivo, the charged tRNA-TyrGUA levels were reduced (Supplementary Fig. 10a, b). Second, upon sensing decreased levels of tRNA-TyrGUA charging, YARS1 underwent nuclear translocation (Supplementary Fig. 10c, d)26,27. Thus, we integrated the transcriptomics, translatomics, proteomics, and metabolomics of tyrosine-limited culture (Tyr 0%) and normal culture (Tyr 100%) to systematically elucidate the mechanism that underlies the effects of restriction of tyrosine translation availability in HCC (Supplementary Fig. 10e). First, the quality of our ribosome-profiling was assured, characterised by the nucleotide length and trinucleotide periodicity distribution of coding sequences in ribosome-protected fragments (Supplementary Fig. 10f, g). Our results also revealed that tyrosine deprivation and YARS1-knockdown did not change global translation efficiency (Supplementary Fig. 10h–j). Of note, by integrative analysis of matched transcriptomic and translatomics data, we found the content of tyrosine and its codon was higher in translation-downregulated protein (unchanged at mRNA levels but reduced at translation levels) compared to translation-upregulated protein (unchanged at mRNA levels but increased at protein levels) upon tyrosine deprivation treatment (Fig. 3a, b), which also suggested that translation defects were observed at tyrosine-enriched transcripts. Next, by combinatorial analysis of matched transcriptomic and proteomics data or translatomics and proteomics data, we defined the tyrosine translational sensitive signature upon tyrosine restriction as candidates with the following characteristics: (1) unchanged at the RNA levels, (2) downregulated at translation efficiencies, (3) reduced at protein levels, (4) enriched in tyrosine and its codon (Fig. 3c–e). In this tyrosine signature, we mainly focused on two proteins as the most prominent translational targets of tyrosine restriction: NADH dehydrogenase [ubiquinone] 1 beta subcomplex subunit 8, mitochondrial (NDUFB8) and acyl-CoA desaturase 1 (SCD1), due to proteomics and metabolomics results showing that tyrosine restriction affected oxidative phosphorylation and unsaturated fatty acid metabolism (Fig. 3f). Indeed, mRNAs encoding SCD1 and NDUFB8 showed significantly decreased translation in tyrosine-restricted conditions, with minimal changes in the mRNA transcription, whereas the translation of NDUFB1 with low tyrosine codon content remained unchanged (Fig. 3g). We also found that tyrosine restriction showed a higher frequency of ribosomal footprints at the TAC codon in the SCD1 and NDUFB8 transcript, with predominant A-site stalling rather than P-site stalling (Supplementary Fig. 10k). Footprint accumulation density analysis further revealed that tyrosine restriction showed a higher P-site accumulation at the codon immediately preceding the 5’ end of the TAC codon in the SCD1 transcript, confirming that tyrosine deprivation leads to A-site stalling of ribosomes at the TAC codon in the SCD1 transcript (Supplementary Fig. 10l). However, no significant footprint accumulation density difference was observed in the NDUFB8 transcript, potentially due to insufficient number of RPFs aligned to this transcript (Supplementary Fig. 10l).

As further support for the above observation, we found proteins reduced upon tyrosine deprivation were enriched in pathways associated with the electron transport chain (ETC), including mitochondrial respiratory chain complex I assembly, proton motive force-driven mitochondrial ATP synthesis, oxidative phosphorylation and NADH dehydrogenase (ubiquinone) activity (Supplementary Fig. 11a–c). Thus, we found that the expression of mitochondrial proteins (especially NDUFB8) enriched in tyrosine (Fig. 3e), along with several of those that were translationally reduced in tyrosine-limited conditions, was generally reduced upon tyrosine restriction, thereby impairing the mitochondrial proteostasis. Moreover, proteins upregulated upon tyrosine deprivation were clustered in the hallmarks of metabolic processes, including ferroptosis, aminoacyl-tRNA biosynthesis, amino acid metabolism, autophagy, etc (Supplementary Fig. 11c). Interestingly, ferroptosis suppressors such as GPX4 and SLC7A11 were significantly elevated in tyrosine-limited culture (Tyr 0%) (Supplementary Fig. 11d), a phenomenon explained by integrated stress response (ISR) and metabolomics results. First, we observed significant activation of the GCN2-eIF2α-ATF4 axis upon tyrosine restriction, as shown by increased phosphorylation levels of GCN2 and eIF2α, and elevated protein levels of ATF4, indicating that ISR is activated to respond to tyrosine translation limitation and reestablish physiological homeostasis (Supplementary Fig. 11e). Next, we found that the intracellular levels of tyrosine were reduced after tyrosine limitation (Supplementary Fig. 11f). However, while tyrosine restriction enhanced the cellular capacity to convert phenylalanine to tyrosine, this increased conversion was insufficient to compensate for tyrosine consumption, ultimately resulting in a significant decrease in intracellular tyrosine levels (Supplementary Fig. 11g, h). Importantly, we noticed that metabolites increased upon tyrosine deprivation were enriched in pathways associated with the unsaturated fatty acids, including biosynthesis of unsaturated fatty acids, arachidonic acid metabolism, linoleic acid metabolism, and alpha-linolenic acid metabolism (Supplementary Fig. 11i, j). In agreement with this finding, monounsaturated fatty acids (MUFAs) represented by palmitoleic acid (C16:1) and oleic acid (C18:1) were decreased upon tyrosine deprivation, whereas polyunsaturated fatty acids (PUFAs), including linoleic acid (C18:2), arachidonic acid (C20:4) and adrenic acid (C22:4) showed an increasing trend (Supplementary Fig. 11i). These changes maybe attributed to downregulation of SCD1, as well as elevated extracellular fatty acid uptake following SCD1 reduction, and ISR activation-induced PUFA accumulation28–33. Given that PUFAs are more prone to peroxidation, which can trigger ferroptosis34, our results also validated that tyrosine deprivation could effectively induce the formation of oxidised lipid species, with long-chain oxidised phosphatidylethanolamines being the most prominent (Supplementary Fig. 11k). We consistently observed greater lipid peroxidation upon RTTA treatment, using the probe C11 BODIPY 493/503 (Supplementary Fig. 12a–f). On the other hand, increased PUFAs were further validated with lipid droplet accumulation after RTTA treatment (Supplementary Fig. 12g–j) to sequester and store excess PUFAs into lipid droplets, where they are protected against lipid peroxidation35. Thus, tyrosine restriction reduces the tyrosine codon-dependent translation of SCD1, resulting in a reduced generation of MUFAs, thereby leading to lipid peroxidation and ferroptosis, despite the cells’ attempt to counteract ferroptosis by increasing the expression of GPX4 and SLC7A11.

To further support our sequencing results that translation of tyrosine-rich NDUFB8 and SCD1 is more sensitive to tyrosine limitation, we first developed reporters expressing luciferase infusion with SCD1 (8.73%, tyrosine), NDUFB8 (9.17%, tyrosine) or NDUFB1 (1.72%, tyrosine), which are proteins that have different tyrosine codon frequencies. We found that the translation of the SCD1-Luc reporter and either the NDUFB8-Luc reporter was more sensitive to RTTA treatment than that of the NDUFB1-Luc reporter (Fig. 3h and Supplementary Fig. 13a, b). Moreover, compared to transfection of WT reporter constructs for NDUFB8 or SCD1, the relative luciferase activities in SNU398 cells transfected with MUT reporter constructs (mutating TAC to TAT) were increased under tyrosine-free or YARS1-knockdown conditions (Supplementary Fig. 13c–e). We also found that compared to overexpression of WT plasmids for NDUFB8 or SCD1, overexpression of MUT plasmids (mutating TAC to TAT) for NDUFB8 or SCD1 effectively improved the impaired mitochondrial complex I function induced by tyrosine restriction (Supplementary Fig. 13f) and alleviated tyrosine restriction-induced elevation in lipid peroxidation (Supplementary Fig. 13g, h). These findings indicate that restricting tyrosine translation availability has a greater translation inhibition effect on TAC-rich transcripts than on TAT-rich transcripts. Next, the reduced translation of SCD1 and NDUFB8 mediated by RTTA treatment was confirmed by ribosome immunoprecipitation assay using RPL22-Flag expressing SNU398 cells (Supplementary Fig. 13i–k). Indeed, YARS1 expression was significantly and positively correlated with NDUFB8 or SCD1 in HCC patients (Supplementary Fig. 13l). Thus, these findings further supported that tyrosine codon-dependent translation is regulated by tyrosine and YARS1 along with tyrosine cognate tRNA-TyrGUA.

Furthermore, to further authenticate the functional consequences of translational reduction of NDUFB8 and SCD1 in impairing ETC activity and inducing ferroptosis, blue native-PAGE and SDS-PAGE assays were conducted to assess the assembly profiles of the ETC complexes and the expression levels of SCD1. We found that RTTA treatment could specifically reduce the complex I assembly and the expression of SCD1 in vitro and in vivo (Fig. 3i, j, and Supplementary Fig. 14a, b). We also found that tyrosine supplementation could increase the protein expression of SCD1 and NDUFB8 in vitro and in vivo (Supplementary Fig. 14c, d), but tyrosine restriction had minimal impact on NDUFB8 and SCD1 protein levels in adjacent normal liver tissues of tumour-bearing mice (Supplementary Fig. 14e). Additionally, we selected tryptophan and serine to investigate their deprivation impacting on NDUFB8 and SCD1 expression. While the frequency of tryptophan in NDUFB8 and SCD1 ranked similarly to tyrosine, tyrosine deprivation induced a significantly greater reduction in protein levels than tryptophan deprivation, while serine deprivation showed no significant impact on these two protein levels (Supplementary Fig. 14f, g), indicating that tyrosine availability exerts more profound translational control than the availability of tryptophan and serine in liver cancer. Similarly, we found that RTTA treatment led to defective complex I activity with little effect on other ETC complexes in vitro and in vivo, as evaluated by enzyme catalytic activity (Fig. 3k, l and Supplementary Fig. 15a, b). Consistently, RTTA treatment reduced OCR with a significant decrease in the maximal respiration capacity due to a defective mitochondrial function caused by complex I misassembly (Fig. 3m and Supplementary Fig. 15c, d). Impaired oxidative phosphorylation was also associated with the generation of cytotoxic mitochondrial ROS (Mito-ROS)36, as measured by an increased Mito-ROS following tyrosine restriction and knocking down of YARS1 and tRNA-TyrGUA (Supplementary Fig. 15e–g).

In addition, given that functional defects in the respiratory chain complexes and ferroptosis can both impair the morphology and structure of mitochondria, limiting tyrosine diet and knocking down YARS1 and tRNA-TyrGUA in vitro and in vivo consistently showed severe ferroptosis and respiration defect characteristics, including mitochondrial atrophy, an increase in mitochondrial membrane density and cristae width, cristae disorganisation and extensive lipid droplet formation, suggesting morphology and structural abnormalities that reflect mitochondrial defects (Fig. 3n and Supplementary Fig. 16a–j). Of note, related pathologic changes, including reduced cell proliferation (characterised by Ki-67), increased cell apoptosis (characterised by TUNEL), and increased lipid peroxidation (characterised by 4-HNE), again indicated that restricting tyrosine translation availability resulted in defective function of mitochondria and lipid peroxidation (Fig. 3o and Supplementary Fig. 16k–n). Overall, these findings provide evidence that targeting tyrosine translation bioavailability either through tyrosine limitation or knocking down YARS1 and tRNA-TyrGUA leads to a reduction in the tyrosine codon-dependent translation of NDUFB8 and SCD1, resulting in defective assembly of mitochondrial complex I and lipid peroxidation.

Genome-wide CRISPR screening identifies factors that enhance the efficacy of tyrosine-restricted therapy
According to our proteomics results, we found that multiple proteins and pathways were upregulated following tyrosine restriction, such as GPX4 and SLC7A11 in the ferroptosis pathway and YARS1 in the aminoacyl-tRNA synthetase pathway, indicating that such genetic interactions might impinge on the anti-tumour efficacy of tyrosine restriction. Therefore, a whole-genome CRISPR–Cas9 loss-of-function screen was conducted to systematically elucidate the underlying mechanism of tyrosine dependence in HCC (Fig. 4a). By analysing sgRNAs depleted in the tyrosine-deprived condition compared with the normal condition, we identified YARS1 as the strongest negatively hit gene in the tyrosine-deprived group throughout the time course (Fig. 4b, c). This result indicated that loss of YARS1 was synthetically lethal when combined with tyrosine restriction on the one hand, and again validated our previous hypothesis that intracellular tyrosine in HCC was preferentially shunted in the direction of protein synthesis rather than metabolised as a ketogenic and glycogenic amino acid on the other hand. Specifically, we noted that sgRNAs targeting SLC7A5 were decreased after tyrosine restriction. In contrast, sgRNAs targeting tyrosine metabolism genes such as TAT and HGD were enriched, confirming the necessity of maintaining intracellular tyrosine levels in HCC cells (Fig. 4b, c).

Moreover, our finding of a decrease in sgRNAs targeting ferroptosis suppressors such as GPX4 and SLC7A11 following tyrosine restriction corresponded to their upregulated protein expression, again suggesting that tumour cells increase the expression of ferroptosis suppressors to scavenge lipid peroxidation caused by tyrosine restriction (Fig. 4b, c). Of note, BCL2, which inhibits mitochondrial damage-induced apoptosis37, was also identified as the top negatively selected gene in our screen, further supporting our previous results that impaired function and structural abnormalities of mitochondria induced cell apoptosis upon tyrosine deprivation, thus depletion of BCL2 improved the therapeutic effects with tyrosine restriction (Fig. 4b, c). Surprisingly, depletion of multiple genes encoding mitochondrial respiratory chain complex proteins was beneficial for HCC cells to adapt to complex I deficiency under tyrosine-restricted conditions (Fig. 4b), which is consistent with previous observations that mitochondrial complex I dysfunction can be alleviated by deletion of pathway-intrinsic proteins5,38. Notably, a large-scale overlap was found between negatively selected genes and genes with elevated protein levels upon tyrosine limitation, further revealing a homoeostatic feedback loop in which these candidates, whose depletion impaired cell fitness in the tyrosine-deprived condition, were elevated to resist tyrosine restriction (Fig. 4d). Collectively, our results suggested that these positive and negative genetic interactions are crucial for understanding the mechanistic underpinnings of tyrosine dependency in HCC and again indicate that HCC cells require more tyrosine to maintain increased protein synthesis.

Furthermore, several of the most negatively selected genes, such as GPX4, SLC7A11, and BCL2, were selected to corroborate our loss-of-function screen. We found that knockdown of either GPX4, SLC7A11 or BCL2 could remarkably improve the efficacy of dietary tyrosine modulation and YARS1 depletion in decreasing HCC cell fitness (Supplementary Fig. 17a–f). Consistently, pharmacological inhibition of GPX4 and BCL2 by their inhibitors RSL3 and venetoclax could also effectively enhance the inhibition effect of tyrosine restriction and YARS1 depletion (Fig. 4e, f, and Supplementary Fig. 17g, h). We also tested Erastin, a small molecule inhibitor of SLC7A11, and found that it could improve the therapeutic effect of tyrosine deprivation and YARS1 depletion (Fig. 4g and Supplementary Fig. 17i). Importantly, Sorafenib, a multikinase inhibitor for the treatment of advanced HCC patients, also demonstrated an improved therapeutic effect with tyrosine restriction and YARS1 depletion, which was attributed to its treatment-induced ferroptosis39–41 (Fig. 4h and Supplementary Fig. 17j). Moreover, knockdown of GPX4 or BCL2 in YARS1-knockdown tumour cells showed an enhanced therapeutic effect, characterising by a reduced tumour volume (Supplementary Fig. 18a, b), thereby validating that restricting tyrosine translation availability combined with ferroptosis-induced or apoptosis-induced models hold excellent therapeutic efficacy in reducing hepatocellular carcinogenesis. Furthermore, to confirm that restricting tyrosine translation availability suppresses tumorigenesis through inducing ferroptosis, rescue experiments were conducted both in vitro and in vivo. Treatment with ferroptosis inhibitor (Fer-1) significantly reversed the reduction of cell proliferation caused by tyrosine deprivation or YARS1-knockdown (Supplementary Fig. 18c, d), and mitigated YARS1-knockdown-induced tumour regression (Supplementary Fig. 18e–g). These findings collectively confirm that restricting tyrosine translation availability triggers tumour cell ferroptosis. Meanwhile, we found that depletion of NDUFB8 or SCD1 reduced the proliferation of HCC cells and inhibited tumour development (Supplementary Fig. 18h–k), thereby indicating that restricting tyrosine translation availability reduced HCC tumorigenesis and progression by decreasing the expression of NDUFB8 or SCD1. As expected, our in vivo HCC mouse model studies showed that both tyrosine restriction and YARS1 depletion combined with sorafenib or venetoclax showed an enhanced therapeutic effect, characterised by a reduced tumour burden and tumour diameter and extended survival time in Myc/Alb-cre mice (Fig. 4i–m, and Supplementary Fig. 18l–n). Thus, our results suggested that dietary tyrosine modulation and YARS1 depletion combined with targeted therapies (e.g., sorafenib and venetoclax) hold excellent therapeutic efficacy in reducing hepatocellular carcinogenesis.

Moreover, to establish the direct causality between MYC-YARS1-NDUFB8 or SCD1, we first examined ETC complex function and lipid peroxidation upon MYC knockdown. We found that MYC depletion reduced the expression of YARS1, NDUFB8, and SCD1 (Supplementary Fig. 19a), thereby inhibiting mitochondrial complex I enzyme activity (Supplementary Fig. 19b) and promoting lipid peroxidation (Supplementary Fig. 19c, d). Subsequently, we investigated whether YARS1 overexpression could rescue the defective effects in MYC-knockdown cells. Results demonstrated that YARS1 overexpression effectively improved the impaired mitochondrial complex I function induced by MYC deficiency (Supplementary Fig. 19e), while alleviating MYC knockdown-induced elevation in lipid peroxidation (Supplementary Fig. 19f, g). Meanwhile, the lipid peroxidation levels were partially restored by re-expressing SCD1 in the YARS1-knockdown cells (Supplementary Fig. 19h, i) and the downregulation of complex I activity was reversed by expressing NDUFB8 back into YARS1-knockdown cells (Supplementary Fig. 19j). Similarly, we demonstrated that supplementation with oleic acid and palmitoleic acid (hereafter referred to as MUFA) effectively alleviated ferroptosis triggered by tyrosine restriction, YARS1-knockdown, or MYC knockdown, as evidenced by decreased lipid peroxidation levels (Supplementary Fig. 19k–m). Furthermore, SCD1 knockdown also resulted in increased lipid peroxidation (Supplementary Fig. 19n). Collectively, these findings indicate that MYC facilitates the translation of NDUFB8 and SCD1 by enhancing YARS1 transcription, thereby promoting mitochondrial complex assembly and ferroptosis resistance.

Tyrosine ammonia-lyase (TAL) exhibit potent therapeutic efficacy by degrading tyrosine in HCC
A long-term tyrosine-restricted diet in patients with tyrosinemia represents the feasibility of this dietary intervention in HCC patients42. Nevertheless, this restrictive diet poses challenges in terms of patient adherence. Thus, an approach superior to dietary intervention is to catalyse amino acids into non-toxic, readily metabolisable products through the action of an enzyme43. Clinically, L-asparaginase is widely used in the treatment of patients with acute lymphoblastic leukaemia due to its aminohydrolase function that catalyses the degradation of asparagine to ammonia and aspartic acid, thereby reducing the protein synthesis availability of asparagine44. Thus, phenylalanine/tyrosine ammonia-lyases (PAL/TALs) that convert the non-oxidative deamination of phenylalanine into cinnamic acid or tyrosine into coumaric acid (Fig. 5a), respectively, represent a potential therapeutic strategy for HCC45. Considering these enzymes with dual activity of catalysing phenylalanine/tyrosine, TAL derived from Flavobacterium johnsoniae, with the lowest catalytic activity for phenylalanine, was chosen to reduce the interference and consequence of phenylalanine degradation46. The dissociation constants (Kd) for FjTAL-tyrosine (5.88 μM) and FjTAL-phenylalanine (no binding), along with enzyme catalytic activity assay, further confirmed that FjTAL efficiently degraded tyrosine, with a minimal effect on phenylalanine (Fig. 5b and Supplementary Fig. 20a, b).

Subsequently, we found that FjTAL treatment significantly inhibited the cell growth/survival in multiple HCC cells, as evaluated by half-maximal inhibitory concentration (IC50) values around 0.4–0.7 μM (Fig. 5c). Similar to tyrosine restriction and YARS1 depletion, FjTAL treatment could effectively reduce cell proliferation, induce cell apoptosis, and synergistically increase the anti-tumour efficacy of sorafenib or venetoclax in HCC cells (Supplementary Fig. 20c–n). As expected, FjTAL treatment also reduced tyrosine translation bioavailability, thereby decreasing the translation of SCD1 and NDUFB8 (Supplementary Fig. 21a–d). Defective mitochondrial function was further validated upon FjTAL treatment, characterised by reduced complex I formation and enzyme catalytic activity, downregulated OCR, and increased production of Mito-ROS (Fig. 5d, e, and Supplementary Fig. 21e, f). Similarly, FjTAL treatment also induced the formation of lipid droplets and increased lipid peroxidation in HCC cells (Fig. 5f, g, and Supplementary Fig. 21g–j), and Fer-1 treatment reduced the levels of lipid oxidation induced by TAL treatment (Supplementary Fig. 21k, l). In line with this, electron microscopy-based morphometric analysis also showed mitochondria morphology and structural abnormalities following FjTAL treatment (Supplementary Fig. 21m, n).

To further consolidate the anti-tumour efficacy of FjTAL in vivo, we administered a single intraperitoneal injection of different doses of FjTAL to tumour-bearing Myc/Alb-cre mice. The amino acid profile of FjTAL-treated liver tissue at a dosage of 50 mg/kg revealed the most pronounced and the longest-lasting reduction in tyrosine (Supplementary Fig. 21o). In contrast, the other amino acids showed little change after FjTAL treatment (Supplementary Fig. 21o). Consistently, after we treated tumour-bearing Myc/Alb-cre mice three times a week for 1 week with low-dose FjTAL (10 mg/kg), medium-dose FjTAL (25 mg/kg), or high-dose FjTAL (50 mg/kg), only the high-dose treatment group revealed reduced levels of tRNA-TyrGUA charging and an increase in the nuclear translocation of YARS1, indicating a significant inhibition of tyrosine translation availability (Supplementary Fig. 21p, q). Of note, our in vivo mouse HCC model studies also showed that while FjTAL treatment alone could remarkably reduce the weight ratio of liver/body, tumour burden, and tumour diameter, and prolong survival time in Myc/Alb-cre mice, its combination with sorafenib or venetoclax displayed an improved therapeutic efficacy (Fig. 5h–k). Consistent with the in vitro observation, FjTAL-treated tumours showed a defective mitochondrial function and severe ferroptosis phenotype, characterised by reduced complex I formation and enzyme activity, decreased expression of SCD1, and impaired morphology and structure of mitochondria (Fig. 5l, m, and Supplementary Fig. 21r). Finally, histopathological examination revealed reduced cell proliferation, increased cell apoptosis and lipid peroxidation, preferentially in FjTAL-treated tumours, indicating that therapeutic degradation of tyrosine by FjTAL treatment can antagonise hepatocellular carcinogenesis through impairing oxidative phosphorylation and inducing ferroptosis (Fig. 5n, o).

YARS1-mediated tyrosine aminoacylation in liver tumorigenesis can be inhibited by tyrosinol
In addition to limiting tyrosine uptake or pharmacologically degrading tyrosine, we propose an additional strategy to block the translational utilisation of tyrosine, i.e., the use of the structural analogue tyrosinol to competitively occupy the pocket of tyrosine-binding YARS126,47, thereby reducing YARS1-catalysed tyrosine binding to tRNA (Fig. 6a). The Kd for tyrosine-YARS1 and tyrosinol-YARS1 reached 22.6 μM and 40.2 μM, respectively, indicating a similar affinity to YARS1 (Fig. 6b). We also found that tyrosinol could reduce the binding capacity of YARS1 to tyrosine (Supplementary Fig. 22a). Moreover, the amino acid profiling in liver tissues from Myc/Alb-cre mouse treated with tyrosinol demonstrated that tyrosinol treatment had minimal effects on amino acid levels compared to the control group (Supplementary Fig. 22b). Thus, chemical inhibition of YARS1 by tyrosinol reduced the fitness of HCC cells and synergistically improved the therapy efficacy of sorafenib or venetoclax in HCC cells (Supplementary Fig. 22c–n). Consistently, tyrosinol treatment prevented tyrosine aminoacylation, supported by a reduced tRNA-TyrGUA charging and increased YARS1 nuclear translocation (Supplementary Fig. 22o, p), thereby inhibiting the translation of NDUFB8 and SCD1 (Fig. 6c, d). As a functional consequence of the reduced translation of NDUFB8 and SCD1, we also observed defective mitochondrial function and lipid peroxidation, leading to mitochondrial structural and morphological abnormalities (Fig. 6e–g and Supplementary Fig. 23a–f), and Fer-1 treatment reduced the levels of lipid oxidation induced by tyrosinol treatment (Supplementary Fig. 23g, h).

Subsequently, we attempted to define whether the results obtained from human cancer cells could be translated to mouse tumours. Pharmacokinetic studies in mice revealed that when given orally at a dosage of 500 mg/kg, the duration of tyrosinol in the liver was approximately 24 hours (Supplementary Fig. 24a). We chose the tyrosinol dose (500 mg/kg/d) based on a pilot study of different doses of tyrosinol (250 or 500 mg/kg/d), which showed a reduced tyrosine aminoacylation and increased YARS1 nuclear translocation at the dosage of 500 mg/kg per day (Supplementary Fig. 24b–d). Moreover, to evaluate the safety profile of tyrosinol in mice, we found that tyrosinol treatment (repeated dosing of 500 mg/kg/d for 4 weeks, oral gavage) did not result in any significant tissue weight changes (Supplementary Fig. 24e). The levels of ALT, AST, CREA, CK, and LDH were also unchanged upon tyrosinol treatment (Supplementary Fig. 24f). Furthermore, no apparent pathological differences or tissue injury were observed after tyrosinol treatment (Supplementary Fig. 24g). Additionally, we examined the impact on the aminoacylation of the other two aromatic amino acids (phenylalanine and tryptophan) after tyrosinol treatment. Results demonstrated that the charged tRNA-PheGAA and tRNA-TrpCCA levels remained unchanged upon tyrosinol treatment (Supplementary Fig. 24h), indicating that tyrosinol treatment does not have potential off-target effects in vivo. As observed in vitro, tyrosinol treatment alone could significantly reduce liver-to-body-weight ratio, tumour burdens and tumour diameters and prolong the survival time in the tumour-bearing mice, while its combination with sorafenib or venetoclax showed an improved anti-tumour efficacy (Fig. 6h–j). Similarly, defective mitochondrial function and severe ferroptosis phenotype preferentially occurred in tyrosinol-treated tumours (Fig. 6k–n and Supplementary Fig. 24i, j). Thus, our findings showed that suppressing YARS1 with tyrosinol, both alone and in combination with sorafenib or venetoclax, uncovers attractive therapeutic options for treating HCC patients.

Methods
Patient tissues and ethics
Informed consent was obtained from all patients in this study. No compensation was provided. Due to the limited samples available, sex and gender were not considered in the study design. This study was conducted following both the Declarations of Helsinki and Istanbul and received approval from the Ethics Committee of the Fifth Medical Centre of the Chinese PLA General Hospital. HCC tissues and adjacent liver tissues were sourced from the Fifth Medical Centre of the Chinese PLA General Hospital. The patient data were supplied in Supplementary data 6. HCC data from TCGA, CPTAC, and CNCB (the China National Centre for Bioinformation) were used for analysis.

Animals and ethics statement
All animal experiments were approved by the Animal Ethics Committees of Inner Mongolia Medical University and Beijing University of Chemical Technology and performed in accordance with the guidelines of the National Institutes of Health (NIH). The maximal tumour size permitted by the ethics committee was 2500 mm3, and the maximal tumour size was not exceeded in this study. Male C57BL6/J and 4-week-old male BALB/c nude mice were provided by Beijing Vital River Laboratory Animal Technology Co., Ltd (China). Alb-cre and H11LNL-Myc (H11-CAG-loxp-STOP-loxp-MYC) strains, based on C57BL/6J background, were purchased from Shanghai Model Organisms Centre, Inc. Myc/Alb-cre mice were generated by crossing H11LNL-Myc and Alb-cre mice. Animals were housed in individually ventilated cages (IVC) within a specific pathogen-free (SPF) grade system at 22°C with a 12-hour light/dark cycle and free access to water and food. The animals used in the experiments were randomly assigned to groups. In the subcutaneous tumour model, tumour growth was monitored at regular intervals, and mice were euthanized when tumour volume approached 2500 mm3, mice lost 20% of body weight, or tumours exhibited ulceration. In vivo experiments, including spontaneous and orthotopic liver tumour models, were terminated at predefined endpoints when (a) tumours exceeded 2 cm in diameter, (b) mice lost 20% of body weight, or (c) mice showed signs of severe distress such as lethargy or impaired mobility. Survival time was recorded in all experiments.

Animal experiments
Male mice only were used in the different models to avoid the influence of sex and oestrogen. For the HCC mouse model, Myc/Alb-cre transgenic mice spontaneously develop HCC within 12 weeks of age. The orthotopic HCC model induced by diethylnitrosamine (DEN) (Sigma, Cat# N0676) treatment was established following the protocol described in previous reports21. Briefly, 14-day-old male mice received an intraperitoneal injection of DEN at a dosage of 25 mg/kg. Regarding the intrahepatic injection model of human HCC cells, 4-week-old male nude mice were anaesthetised, and their livers were placed ex vivo through a subcostal incision. Then, 50 μL of PBS containing 1×106 cells was injected into both the left and right lobes of the liver. After bleeding from the left and right lobe wounds was stopped with sterile cotton swabs, the livers were placed back into the abdominal cavity, and the incisions were sutured. Animals were sacrificed after the indicated time points and treatments. Then, livers were photographed and weighed. Tumour numbers were counted by visual assessment, and tumour diameters were measured using calliper. Liver tissues were stored at −80°C after being frozen in liquid nitrogen for further analysis.

For the tyrosine-modified diet experiments, mice were fed different tyrosine-modified diets for the durations shown in the articles. Special diets with varying levels of tyrosine were purchased from Xie Tong Bio-engineering (Yangzhou) Co., Ltd (China). The diet of tyrosine 100% corresponds to the concentration of tyrosine (0.4%, wt/wt) contained in the standard diet (Cat. No. A100021B). The tyrosine-restricted diet (tyrosine 0% diet) contained 0% tyrosine, and the tyrosine-supplemented diet (tyrosine 500% diet) contained 2% tyrosine. Differences in protein/nitrogen content were modulated by adjusting the proportional concentration of glutamate.

For AAV administration, AAV particles including AAV8-shNC, AAV8-shYARS1-1, and AAV8-shYARS1-2 were purchased from GenePharma (China). AAV particles were injected into four-week-old Myc/Alb-cre mice by tail-vein injection at 1×1012 genome copies (GC) in PBS per mouse. shRNA sequences were listed in Supplementary data 1.

For FjTAL treatment, eight-week-old Myc/Alb-cre mice were administered a single intraperitoneal injection of FjTAL at different dosages to evaluate the efficacy of the FjTAL treatment. At the indicated time points, liver tissues were collected for HPLC-MS analysis to examine the degradation efficacy of amino acids. In other FjTAL-treated experiments, mice received FjTAL by intraperitoneal injection every 2 days until sacrificed.

For tyrosinol (Sigma, Cat# 469998) treatment, tyrosinol was dissolved in PBS, and mice received tyrosinol by oral gavage at a concentration of 500 mg/kg per day.

For Sorafenib or Venetoclax treatment, drugs were dissolved in vehicle (5% (v/v) DMSO, 40% (v/v) PEG300, 5% (v/v) Tween-80 in 0.9% (w/v) NaCl). Each mouse received oral gavage at 30 mg/kg per day.

Cell lines and cell culture
Human HCC cell lines that underwent short-tandem repeat testing and were confirmed free of mycoplasma contamination, including SNU398, SNU449, PLCPRF5, and HCCLM3, were obtained from Bena Culture Collection (China). A stable YARS1-knockdown HCC cell line was generated using a lentiviral vector. All cell lines were cultured in high-glucose containing DMEM medium supplemented with 10% FBS (Vazyme, Cat# F101-01) and 1% streptomycin–penicillin (VivaCell, Cat# C3420-0100). For experiments involving the restriction of tyrosine, cells were cultured in a high-glucose DMEM medium that only lacked tyrosine (tyrosine 0% compared to standard medium). Primary mouse hepatocytes from 6-to-8-week-old mice were isolated and cultured, as previously reported53. EBSS and type Ⅳ collagenase (Sigma, Cat# C5138) were briefly perfused through the portal vein to digest liver tissue. Hepatocytes were isolated using Percoll buffer (Sigma, Cat# P1644) and cultured in DMEM medium. Cells were cultured at 37°C with 5% CO2.

Plasmids
The promoter sequence of YARS1 was cloned into the pGL4.10 plasmid to generate the luciferase reporter vector YARS1-WT-Luc. A mutant construct of the luciferase reporter YARS1-mutant-Luc was generated as previously reported21. The pLKO.1-shYARS1 vector was homemade, and shRNA sequences were listed in Supplementary Data 1.

Transfection, lentiviral transduction, and generation of stable cell lines
For siRNA or shRNA-mediated knockdown, cells were transfected with 50 nM siRNAs or 1.5 μg shRNA-targeting plasmids using Lipofectamine 2000 (Invitrogen, Cat# 11668500), both from GenePharma (China), in Opti-MEM, according to the manufacturer’s instructions. For lentivirus packaging, HEK293T cells were co-transfected with shRNA-targeting vectors and the helper vectors psPAX2 and pCMV-VSVG using Lipofectamine 3000 (Invitrogen, Cat# L3000150). The cell supernatants containing lentiviruses were collected and concentrated 48h after transfection. Low-density (20%) HCCLM3 cells were infected with the concentrated supernatant in the presence of 5 μg/mL polybrene (Beyotime, Cat# C0351) for 24 hours. Infected cells were placed under puromycin selection at a 1 mg/mL concentration for 1 week to obtain stable cell lines.

Drug treatment
For drug treatment, (1S,3R)-RSL3 (MCE, Cat# HY-100218A), Erastin (MCE, Cat# HY-15763), Sorafenib (MCE, Cat# HY-10201), and Venetoclax (MCE, Cat# HY-15531) were used to improve the anti-tumour efficacy with restriction of tyrosine translation availability. Drugs were dissolved in DMSO. Cells were treated with drugs as indicated in the figures for 48h in combination with either tyrosine-restricted medium, shRNA-mediated knockdown, FjTAL-treated medium, or medium containing tyrosinol.

RNA extraction, cDNA synthesis, and RT-qPCR
Total RNA extraction was performed using TRIZOL (Invitrogen, Cat# 15596018CN) as previously reported21. cDNA was synthesised via reverse transcription using 3 μg of RNA as a template with the HiScript III Reverse Transcription Kit (Vazyme, Cat# R323). Real-time PCR was performed with ChamQ SYBR qPCR Master Mix (Vazyme, Cat# Q412) using an ABI 7500 Sequence Detection System. Primer sequences for quantitative PCR analysis are listed in Supplementary Data 1.

tRNA qPCR
Total RNA was extracted using TRIZOL, with integrity and purity confirmed via the A260/A280 ratio. Total tRNA quantification was performed using a tRNA quantification kit (Arraystar, AS-FS-004). Briefly, purified RNA was treated with demethylase AlkB to remove methylation. Following RNA purification via chloroform extraction, purified RNA served as a template for reverse transcription using the MLV reverse transcriptase kit (Invitrogen, Cat# 28025013) according to the manufacturer’s protocols. tRNA quantification was then performed by RT-qPCR according to the manufacturer’s specifications. Primer sequences for tRNA quantification were provided in Supplementary Data 1.

Northern blot for detecting tRNA
The tRNA Northern blot was performed using a Northern blot kit (Beyotime, Cat# R0220), according to the manufacturer’s protocol. A total of 500 ng of trizol-extracted RNA was mixed with 2× RNA native loading buffer (Beyotime, Cat# R0221), heated at 65°C for 15 minutes, and then loaded into a 15% urea polyacrylamide gel (Beyotime, Cat# R0232S). The gel was electrophoresed in TBE buffer at 200V for 40 minutes. The RNAs were transferred to a nylon membrane at 60V for 1 hour and then crosslinked with the membrane under UV radiation at 120 mJ/cm2 for 30–45s. The membrane was pre-hybridised with hybridising solution for 2 hours, then a 10 pmol/mL RNA probe labelled with biotin was added for an additional 2 hours of hybridisation. Following hybridisation, the membrane was washed twice with low-salt buffer and twice with high-salt buffer, then blocked with blocking buffer at 37°C for 15 minutes. The membrane was incubated with a blocking buffer containing Streptavidin-HRP conjugate at a 1:2000 dilution for 15 minutes, followed by two washes with a balanced buffer. Detection was achieved using the ECL detection solution according to the manufacturer’s guidance. All probe sequences were listed in Supplementary Data 1.

Northern tRNA charging assay
The tRNA aminoacylation assay was performed as previously reported54. Cells were resuspended in 0.3 M sodium acetate buffer (pH 4.7) containing 10 mM EDTA, mixed with phenol-chloroform-isoamyl alcohol (pH 4.7), vortexed, and centrifuged at 22,000×g for 25 min at 4°C. RNA was precipitated with 100% ethanol, resuspended in 0.3 M acetate buffer (pH 4.5), precipitated with 100% ethanol again and dried. RNA was redissolved in acetate buffer (pH 4.5), mixed with 2× RNA loading buffer (pH 4.5), loaded onto a 15% urea polyacrylamide gel (pH 4.5), and then subjected to electrophoresis at 40V for 6h in 0.3 M acetate buffer (pH 4.5). Membrane transfer proceeded in the buffer containing 10 mM Tris-acetate (pH 7.8), 5 mM sodium acetate and 0.5 mM EDTA at 40V for 2h. Subsequent steps followed the Northern blot procedure.

Immunoblot analysis
Tissues were homogenised in lysis buffer (50 mM Tris, pH 7.8, 0.5 M NaCl, 2 mM EDTA, 2 mM EGTA, 1% Triton X-100, 0.25% Deoxycholate, 1 mM NaF and 1 mM Na3VO4) supplemented with protease inhibitors (Roche, Cat# 46931320001) using a homogeniser (IKA) and subsequently lysed for 30 min at 4°C. Cells were lysed with 1 mL lysis buffer (50 mM Tris, pH 7.4, 150 mM NaCl, 1 mM EDTA, 1% Triton X-100, 1 mM NaF, 1 mM Na3VO4) supplemented with protease inhibitors for 30 min at 4°C. After centrifugation at 13,000×g at 4°C for 10 min, protein concentration was quantified using the Bradford or BCA assay, depending on the lysis buffer used. For immunodetection, equal amounts of total protein lysate were boiled and resolved thereafter by SDS-PAGE and transferred to nitrocellulose membrane, blocked with milk, and incubated with indicated diluted primary antibodies. The signal was detected using Pierce™ ECL Western Blotting Substrate (Thermo Scientific, Cat# 32209). The antibodies used in this article were shown as follows: anti-SLC7A5 (Proteintech, Cat# 28670-1-AP), anti-SLC38A9 (Proteintech, Cat# 21871-1-AP), anti-SLC43A1 (Proteintech, Cat# 10444-1-AP), anti-TAT (Thermo fisher, Cat# PA5-26541), anti-HPD (Proteintech, Cat# 67552-1-Ig), anti-HGD (Proteintech, Cat# 16465-1-AP), anti-GSTZ1 (Proteintech, Cat# 14889-1-AP), anti-FAH (Proteintech, Cat# 14928-1-AP), anti-YARS1 (Thermo fisher, Cat# PA5-53883), OXPHOS antibody cocktail (anti-NDUFB8 (Proteintech, Cat# 14794-1-AP), anti-SDHB (Proteintech, Cat# 10620-1-AP), anti-UQCRC1 (Proteintech, Cat# 10620-1-AP), anti-MTCO2 (Proteintech, Cat# 55070-1-AP), anti-ATP5A1 (Proteintech, Cat# 14676-1-AP)), anti-SCD1 (Proteintech, Cat# 28678-1-AP), anti-4-HNE (JaICA, Cat# MHN-20P), anti-Histone H3 (CST, Cat# 4499) and anti-β-Actin (TransGen Biotech, Cat# HC201-01). Horseradish peroxidase-conjugated anti-rabbit IgG (LABLEAD, Cat# RN0100), anti-mouse IgG (LABLEAD, Cat# MN0100) was employed as secondary antibodies.

Blue native-PAGE
The BN-PAGE was performed to detect the assembly of mitochondrial respiratory complexes as previously reported55. Human cancer cells were collected, washed with cold PBS and resuspended in PBS containing digitonin (6 mg/mL) (Beyotime, Cat# ST1272) and protease inhibitors. After lysing the cells on ice for 15 min, 1 mL cold PBS was added to the samples, followed by centrifugation at 10,000×g for 5 min at 4°C to collect mitochondrial pellets. For liver tissues, the tissues were homogenised in MOPS buffer (440 mM sucrose, 20 mM MOPS, 1 mM EDTA, 0.2 mM PMSF and protease inhibitors) using a homogeniser and then lysed for 10 min on ice. After centrifugation at 10,000×g for 10 min, enriched mitochondrial fractions were collected. Pellets were resuspended in 100 μL buffer (1 M aminocaproic acid, 50 mM Bis–Tris/HCl, pH 7.0) supplemented with 20 μL dodecyl maltoside (10% w/v) and protease inhibitors, vortexed, and then incubated on ice for 5 minutes before the lysates were centrifuged at 20,000×g for 20 min to collect solubilized mitochondrial complexes in the supernatant. Protein concentration was measured using the BCA assay. Then, equal amounts of lysates were mixed with 2× blue native-PAGE Sample Buffer (Beyotime, Cat# P0761) and loaded onto a 3–12% blue native precast gel (Beyotime, Cat# P0546) at 4°C. Samples were electrophoresed in cathode buffer Ⅰ at 40V for 4h and subsequently in cathode buffer II at 40V for 2h until excess blue dye migrated out of the gels. Stripping buffer (100 mM 2-mercaptoethanol, 2% SDS, 62.5 mM Tris-HCl, pH 6.7) was used to wash the gel at 50°C for 30 minutes to remove G250 and expose antigen epitopes, followed by transfer of proteins to nylon membrane. Subsequent steps followed Western Blot procedures.

Flow cytometric detection of cell apoptosis, cell cycle, lipid ROS, and mitochondrial ROS
Cell death was measured using the Annexin-V FITC kit (Beyotime, Cat# C0162). Cells were washed in PBS, resuspended in annexin-V binding buffer and incubated with staining buffer containing annexin-V-FITC and propidium iodide (PI) for 30 min at 4°C. For cell cycle analysis, cells were washed in PBS, fixed with 70% ethanol, and incubated with staining buffer containing PI and RNase A for 30 min at room temperature. Mitochondrial reactive oxygen species (ROS) were assessed by staining cells with MitoSOX Red (MCE, Cat# HY-D1055). Lipid peroxidation was evaluated using BODIPY 581/591 C11 (Thermo Scientific, Cat# D3861) for cell staining. Flow cytometry was performed using a CytoFLEX (Beckman) instrument, and data were analysed with CyteExpert software (Beckman). Excitation/absorption wavelengths were as follows: annexin-V FITC (488 nm/525 nm, FITC channel, 488 nm laser, 525/40 BP), PI (488 nm/585 nm, PE channel, 488 nm laser, 585/42 BP), MitoSOX Red (510 nm/580 nm, PE channel, 488 nm laser, 585/42 BP), and BODIPY 581/591 C11 (500 nm/510 nm, FITC channel, 488 nm laser, 525/40 BP). Gating strategies for flow cytometry analysis were provided in Supplementary Fig. 26.

3H tyrosine uptake and tracing
For ex vivo uptake, normal liver freshly isolated from H11LNL-Myc mouse or tumour tissues freshly isolated from Myc/Alb-cre mouse were incubated in tyrosine-deficient DMEM medium containing 2 μCi L-[ring 3,5-3H]-Tyrosine (American Radiolabelled Chemicals, Inc. Cat# ART0195) at 37°C for 30 min. Tissues were washed thrice with cold PBS and subsequently lysed with SOLVABLE (PerkinElmer, Cat# 6NE9100). To assess tyrosine translation utilisation, normal liver or tumour tissues were incubated in tyrosine-deficient DMEM medium containing 10 μCi 3H-Tyrosine at 37°C for 1h. Tissues were washed thrice with cold PBS and subsequently homogenised in lysis buffer using a homogeniser. For ribosome extraction, ribosome pellets were isolated using a ribosome extraction kit (BestBio, Cat# BB-36061) according to the manufacturer’s protocol. For protein extraction, the lysate was centrifuged at 4°C for 30 min, the supernatant was retained, and trichloroacetic acid was added to the supernatant to precipitate protein. Intracellular 3H tyrosine was quantified by using a scintillation counter (PerkinElmer).

13C tyrosine uptake and metabolic flux analysis
Primary mouse hepatocytes isolated from H11LNL-Myc mouse or Myc/Alb-cre mouse were cultured in tyrosine-deficient DMEM medium containing 250 μM L-Tyrosine (ring-13C6) (Cambridge Isotope Laboratories, Cat# CLM-1542-PK) at 37°C for 12h or 48h to analyse in vitro uptake or metabolic flux of 13C tyrosine, respectively. Then, cells were collected and mixed with 80% methanol, sonicated for 1 min in an ice-water bath, followed by placing on dry ice for 1 min. Samples were stored at −80°C for 30 min, thawed at 4°C for 10 min, vortexed for 1 min and centrifuged at 16,000×g at 4°C for 10 min. The supernatants were gently dried with nitrogen. Then, samples were reconstituted with 50% ACN containing internal standards for testing by UHPLC-HRMS platform.

Ultimate 3000 Liquid Chromatography System equipped with a Waters Amide column (100 mm×2.1 mm, 1.7 μm). The injection volume was 5 μL. The flow rate was 0.3 mL per minute. The mobile phase composition consisted of (A) 10 mM ammonium acetate aqueous solution and (B) 10 mM ammonium acetate in 90% acetonitrile aqueous solution. A linear gradient elution mode was employed for the separation of metabolites, with the following gradient profile: Starting at 95% B and maintained for 0.5 minutes, linearly decreasing to 65% B over 7 minutes and held for 1 minute, further linearly decreasing to 50% B at 8 minutes and held for 1 minute, then linearly increasing to 95% B at 9.1 minutes and held for 2.9 minutes, returning to the initial gradient at 9.1 minutes and equilibrating until 12 minutes. The metabolites were ionised, and mass spectrometry data were collected using an Orbitrap Fusion Tribrid mass spectrometer. Negative ion mode ionisation (HESI-) of the metabolites was performed using a heated electrospray ionisation source. The main parameters of the ion source were set as follows: spray voltage at 2500 V, capillary temperature at 325°C, and needle heater temperature at 300°C. The sheath gas flow rate was 30 (arbitrary units, the same below), and the auxiliary gas flow rate was 10 (arbitrary units). The S-Lens RF was set to 60 (arbitrary units). The first-order mass spectrometry scan range was from mass-to-charge ratio (m/z) 70–800. Raw mass spectral data were preprocessed using Xcalibur software (version 4.0.27.19). Data were displayed by the ratio of labelled metabolites to all metabolites.

Amino acid profiling of liver tissues from HCC patients and mice
Amino acid profiling was carried out by targeted metabolomics. Snap-frozen liver samples with no significant difference in weight between groups were added into 80% methanol containing 0.1% formic acid and the internal standard succinic acid-2,2,3,3-d4, homogenised with two stainless steel beads using a grinder and sonicated for 10 min in an ice-water bath, followed by standing at −20°C for 20 min. After centrifugation at 16,000×g at 4°C for 10 min, the supernatants were added into mixed internal standard and subsequently concentrated. Pyridine solution containing methoxamine hydrochloride was added to the samples, and the oximation reaction was carried out for 60 min at 37°C in a shaking incubator. Then, BSTFA derivatization reagent, hexane and internal standards were added into the samples, and the reaction was carried out at 70°C for 60 min before GC-MS analysis. GC-MS analysis was performed using a TSQ9000 triple-quadrupole mass spectrometer with MRM scan type.

Mitochondrial respiration
Oxygen consumption rates (OCRs) were measured to assess mitochondrial respiration using Seahorse XFe96 Analyzer (Agilent). Cells were plated in XFe96 Cell Culture Microplates (Agilent, Cat# 102416-100) and cultured in DMEM until confluence, after which the medium was switched to Seahorse XF Base Medium (Agilent, Cat# 102353-100) supplemented with glucose, L-glutamine, and sodium pyruvate for OCR measurement. OCR was measured beginning with basal (baseline), and then was treated with oligomycin (Abcam, Cat# ab141829), 4-(trifluoromethoxy)phenylhydrazone (FCCP) (Sigma, Cat# C2920), and rotenone (Sigma, Cat# R8875). The results were expressed in pmol/min and normalised to the cell number.

Expression and purification of FjTAL and YARS1
The coding sequence of FjTAL or YARS1 was cloned into the pET22b-(+) vector, and the recombinant vector was transformed into BL21 (DE3). The transformed strains were revived and streaked onto TB agar plates containing ampicillin to select for transformants. Selected strains were expanded in TB medium with ampicillin at 37°C overnight. Isopropyl-β-D-thiogalactopyranoside (IPTG) with a concentration of 0.4 mM was added to induce protein expression of FjTAL for 22h at 25°C. Correspondingly, IPTG at 0.4 mM concentration induced the protein expression of YARS1 for 16h at 18°C. The cells were disrupted by ultrasonication, and the supernatant was collected and purified via a Ni-affinity column, followed by concentration to yield a protein concentrate. The concentrate was stored at −80°C after identification through molecular sieving.

Pyrophosphate production assay
All enzymatic reactions were conducted in 50 mM HEPES (pH 7.5), 25 mM KCl, 2 mM MgCl₂, 4 mM ATP, 300 nM YARS1, protein substrates, tyrosine or tyrosinol at 37°C for 1h. Pyrophosphate (PPi) production was quantified using the fluorogenic PPi sensor from the PhosphoWorks™ Fluorimetric Pyrophosphate Assay Kit (Enhanced Selectivity) (AAT Bioquest, Cat# 21614), according to the manufacturer’s instructions.

Whole-genome CRISPR screen and analysis
The Brunello library, comprising 76,441 sgRNAs targeting 19,114 genes, was used to perform genome-wide CRISPR screening56. Lentiviruses carrying Cas9 expression vectors were used to transduce the SNU398 cell line, establishing a stable SNU398 cell line expressing Cas9 protein (SNU398-Cas9). This SNU398-Cas9 cell line was then transduced with the Brunello library at a low MOI (0.3) for 24 hours, followed by culture in fresh DMEM supplemented with puromycin for 72 hours. After puromycin selection for 7 days, cells were harvested and divided into two groups, cultured in DMEM with or without tyrosine for either 2 days or 3 days. Genomic DNA was extracted and used as a template to amplify the sgRNA insertion region via PCR, guided by sgRNA barcode sequences, to generate the library. Following NGS deep sequencing on the Illumina platform, sgRNA abundance was quantified using Bowtie2, and essentiality β score per gene was calculated by using the MLE algorithm of MAGECK software. Candidate genes were identified and listed.

Cell viability and clone formation
Cell viability was tested using 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyl-2H-tetrazolium bromide (MTT) assay following the manufacturer’s instructions. MTT was added to the medium at a final concentration of 5 μg/mL for an incubation of 4h, and the medium was replaced with DMSO. The absorbance of the solution at 570 nm was measured using a microplate reader. For the clonogenic growth assay, after being treated as indicated and cultured for a total of 12 days, cells were fixed with 4% formaldehyde, stained with crystal violet solution, photographed and quantified using ImageJ.

ChIP assay and Ch-IP datasets
Ch-IP assays were carried out using an EZ-CHIPTM Assay Kit (Sigma, Cat# 17-371) according to the manufacturer’s instructions. Briefly, SNU398 cells were crosslinked with 1% formaldehyde for 20 min at 37°C, after which crosslinking reactions were quenched with 0.125 M glycine for 5 min at room temperature. The fixed cells were resuspended and lysed in SDS buffer (50 mM Tris-HCl, pH 8.0, 5 mM EDTA, 1% SDS, 100 mM NaCl) supplemented with protease inhibitors and broken by sonication to obtain DNA fragments of ~200–500 bp. The supernatant was then incubated with 4 μg anti-MYC antibody or IgG overnight at 4°C followed by adding Protein G magnetic beads into the immune complexes with a 2-h co-incubation at room temperature. After washing, elution and de-crosslinking, immunoprecipitated DNA and input DNA (fraction reserved from the sonication step) were purified and used for PCR analysis. Data were presented as a percentage of input DNA for each condition. By mining the data from the Cistrome Data Browser datasets, the MYC-binding region of the YARS1 promoter was found, as indicated in the figures.

Luciferase reporter assay
SNU398 cells were seeded into 24-well plates. After 24h, cells were transfected with 50 nM siRNAs or scramble siRNA control and co-transfected with the luciferase reporter and the luciferase internal control reporter phRL-TK. Cells were harvested for measurement of reporter activity using the Dual-Luciferase Reporter Assay System (Promega, Cat# E1910) 48h post-transfection. The internal control Renilla luciferase activity was used to normalise the luciferase activity.

Reporter assay
Reporters expressing luciferase infusion with either NDUFB8, SCD1 or NDUFB1, as indicated in the figures, were generated by gene synthesis from GeneWiz (China). SNU398 cells transfected with these reporter constructs were subjected to tyrosine restriction, FjTAL treatment, tyrosinol treatment, YRAS1 knockdown or tRNA-TyrGUA knockdown for 48h. Then, cells were collected and lysed to measure the activity of luciferase and Renilla luciferase using the Dual-Luciferase Reporter Assay System according to standard protocols. The geometric means of luciferase activities were normalised to the internal control of Renilla luciferase activities.

Ribosome immunoprecipitation
Ribosome immunoprecipitation was performed based on previous reports and a Magna RIP™ kit (Sigma-Aldrich, Cat# 17-371)57. Briefly, cells transfected with Flag-RPL22 plasmid were subjected to tyrosine translation utilisation restriction treatment. Then, cells were treated with CHX (100 μg/mL) for 30 min at 37°C, followed by lysis in lysis buffer (150 mM KCl, 10 mM MgCl2, 1% NP-40, 0.5 mM DTT, 100 μg/mL CHX, 20 mM HEPES KOH (pH 7.3), protease inhibitors, and 10 μL/mL RNasin and Superasin) for 15 min on ice. After centrifugation at 20,000×g for 10 min at 4°C, the supernatants were incubated with Flag affinity gels (Sigma-Aldrich, Cat# A220) overnight at 4 °C and subsequently the immune complexes were washed extensively. Then, immunoprecipitated RNA and input RNA (fraction reserved from the incubation step) were eluted in elution buffer containing 10% SDS and proteinase K and purified using the RNA Clean and Concentrator columns Kit (Zymo Research Corp, Cat# R1017). Immunoprecipitated RNA was reverse-transcribed, followed by RT-qPCR to quantify gene enrichment. Data are presented as a percentage of the input RNA.

Immunohistochemistry and immunostaining assessment
For immunohistochemistry staining, the formalin-fixed paraffin-embedded liver samples from HCC patients and mice were cut into sections of 3 μm, deparaffinized, rehydrated in graded alcohols, heated at 95°C for 30 minutes in 1 mM EDTA buffer (pH 8.0) to retrieve antigen and blocked endogenous peroxidases and non-specific binding sites using 4% hydrogen peroxide and 5% milk, respectively. Primary antibody was incubated with the sections overnight at 4°C, followed by washing the sections with PBS and adding secondary antibodies with a 30 min co-incubation at room temperature. The positive cells were visualised using DAB chromogen. One-step TUNEL apoptosis assay kit (Beyotime, Cat# C1088) was used to detect apoptotic cells in the liver sections from the mouse according to the manufacturer’s protocol. Briefly, after being deparaffinized, rehydrated in graded alcohols and washed in PBS, the sections were incubated with 20 μg/mL DNase-free proteinase K for 20 min at 37°C. After an extensive washing step (four times PBS), the 50 μL detection solution for each sample, containing 5 μL TdT enzyme and 45 μL fluorescent labelling solution, was used in the reaction for 1h at 37°C in the dark. The nuclei were visualised with DAPI (Beyotime, Cat# P0131). Representative images were recorded using a Nikon fluorescence microscope system. For the immunoreactivity evaluation of specimens from the patient, an H-score method was used to precisely quantify the immunolabelled cells by experienced pathologists as previously described58. Briefly, staining intensity of cells was divided into four categories: no positive staining (scored 0), low staining intensity (scored 1), moderate staining intensity (scored 2) and strong staining intensity (scored 3). Immunoreactivity scores of patients were calculated according to the following formula: H-score = 100 ⅹ (% cells with score 1 × 1 + % cells with score 2 × 2 + % cells with score 3 × 3), ranging from 0 to 300. For the immunoreactivity assessment of Ki-67 staining, the Ki-67-positive cells were quantified by computerised counts (Image-Pro Plus 6). The TUNEL or 4-HNE positive cells were visually counted by experienced pathologists.

Transmission electron microscopy
Cultured cells and freshly isolated liver tissues were fixed in 0.15 M sodium cacodylate buffer (pH 7.4) supplemented with 2.5% glutaraldehyde, and 2 mM CaCl2 for 2h at 4°C and post-fixed in 1% osmium tetroxide overnight at 4°C and 1% potassium ferricyanide for 12h at room temperature. Then, samples were stained in 1% aqueous uranyl acetate for 1 hour at 4°C in the dark, dehydrated in graded acetones and finally embedded in EMbed 812 (Electron Microscopy Sciences). Ultrathin sections (70 nm) were cut using a diamond knife (Diatome) in an ultramicrotome (Leica EM UC7), placed on copper grids and stained with uranyl acetate and lead citrate. Sections were photographed on a JEM 1400 transmission electron microscope operated at 120 kV. Morphometric analysis of maximal cristae width was performed by using Image-pro plus 6 on at least 15 randomly selected mitochondria per group.

Pharmacokinetic studies
A single oral dose of tyrosinol was administered to 8-week-old male Myc/Alb-cre mice. Liver tissues were collected at the indicated time points, extracted with 50% methanol and shaken for 1h before centrifuging at 16,000×g for 10 min at 4°C. LC-MS analysis was performed on the UPLC I-Class chromatography coupled to a XEVO TQ-S Micro triple-quadrupole mass spectrometer with SRM scan type. Target Lynx software was used for the quantitative analysis. Phoenix WinNonlin software (version 8.1) was used to calculate the pharmacokinetic parameters through non-compartmental pharmacokinetic analysis with the linear/log trapezoidal rule.

Oil red O staining assay
HCC cells were seeded in six-well plates, then treated as indicated in the figures. Staining was performed according to the instructions of the Oil Red O Stain Kit (Solarbio, Cat# G1262). Briefly, cells were washed with PBS three times and subsequently fixed in 4% paraformaldehyde for 20 min at room temperature. After being rinsed with 60% isopropanol for 10–20s until the stroma was clear, cells were soaked in a newly prepared Oil Red O solution for 20 min before staining with Mayer hematoxylin solution for 1 min. Representative images were recorded using a Nikon fluorescence microscope system, and lipid droplet intensity was assessed with Image-pro plus 6 software.

Cellular fractionation
Cellular fractionation was performed as previously described21. In brief, cells were harvested, and 1/4 of the cells were removed as whole cell lysate (WCL). The remaining cells were lysed in lysis buffer containing 20 mM HEPES, pH 7.9, 10 mM KCl, 1.5 mM MgCl2, 0.5 mM dithiothreitol and protease inhibitors for 30 min on ice, and then NP-40 (0.3% final concentration) was added to the lysates. The lysates were swirled for 25s and centrifuged at 200×g for 10 min at 4°C to separate the cytoplasmic fraction (Cytoplasm) and the nuclear pellet (Nucleus). The precipitates were resuspended with solution 1 (0.25 M sucrose, 10 mM MgCl2), then added onto solution 2 (0.88 M sucrose, 0.05 mM MgCl2) and centrifuged at 3500×g for 10 min to obtain the purified nuclear fraction.

Isothermal titration calorimetry (ITC) binding assay
The binding affinity of FjTAL with tyrosine or phenylalanine and YARS1 with tyrosine or tyrosinol was measured using a MicroCal PEAQ-ITC calorimeter. Briefly, all proteins and compounds were dissolved in the working buffer (20 mM HEPES, pH 8.0 and 200 mM NaCl). The titration was performed with 19 successive injections of tyrosine or phenylalanine at 300 μM concentration, with a 120s interval between each injection, into the cell solution containing FjTAL at 10 μM concentration at 50×g at 25°C. Correspondingly, tyrosine or tyrosinol with a concentration of 500 μM was titrated into YARS1 at 25 μM concentration. The Origin software was used for baseline correction, integration and isotherm curve fitting to a single-site binding model to calculate the equilibrium dissociation constant (Kd) values of binding reactions.

Mitochondrial complex activity
The activities of mitochondrial complex I-V from cells or liver tissues were tested using mitochondrial complex activity assay kit (Solarbio, Cat# BC0515, Cat# BC3235, Cat# BC3245, Cat# BC0945 and Cat# BC1440), respectively, according to the manufacturer’s instructions.

Single-cell RNA-seq and analysis
The single-cell RNA-seq (scRNA-seq) cohort was obtained from the Cancer Single-cell Expression Map (CancerSCEM) at the China National Centre for Bioinformation (CNCB). Raw data were sourced from the following datasets in the GEO database: GSE107747, GSE202642, GSE242889, GSE233405, and GSE155481. Analysis was conducted using the Seurat v5.2.1 R package. Hepatocyte and hepatocellular carcinoma cell clusters were extracted from CancerSCEM-LIHC (n=10). Cell clusters were defined using the SingleR package, with hepatocellular carcinoma cells and hepatocyte clusters identified based on MYC expression levels. The Dimplot and Featureplot were generated using SCpubr and Nebulosa R packages.

RNA sequencing and data analysis
mRNAs were enriched from total RNA using Oligo dT magnetic beads, followed by fragmentation and synthesis of first and second-strand cDNA. Terminal repair, poly-A addition, adapter ligation, fragment selection, amplification, and purification prepared the library for sequencing on SURFSeq 5000 (GeneMind). Raw reads underwent quality control and filtration before being mapped to the GRCh38/hg38 genome using HISAT2. The feature Counts tools from Subread software filtered non-uniquely mapped and unqualified reads, generating an RNA-seq count matrix. Differential expression gene (DEG) analysis was executed by the DEseq2 (V1.42.1) R packages based on the count matrix. The visualisation of the results of DEGs analysis (Volcano plot) was generated using ggplot2 R package, and the DEGs list was established by setting the log2Foldchange threshold at 1 and p value < 0.05. Data are shown in Supplementary Data 2.

Tandem mass tag-labelled (TMT) quantitative proteomics and analysis
Total proteins were extracted, quantified using BCA assay, digested into peptides and labelled with TMT. These TMT-labelled peptides were fractionated via reversed-phase chromatography on an Agilent 1100 HPLC system and analysed by LC-MS. All analyses were performed by a Q-Exactive mass spectrometer (Thermo, USA) equipped with a Nanospray Flex source (Thermo, USA). Proteome Discoverer (v.2.4) was used to search all the Q-Exactive raw data thoroughly against the sample protein database. Database search was performed with Trypsin digestion specificity. Alkylation of cysteine was considered a fixed modification during database searching. For the protein quantification method, the labelling method was selected. A global false discovery rate (FDR) was set to 0.01, and protein groups considered for quantification required at least two peptides. After peptide quality control and median normalisation, a protein expression level matrix was generated. Inter-group differential protein analysis was conducted using the rstatix (version 0.7.2) R package with a mean-based differential analysis approach. A volcano plot of differential proteins was created using the ggplot2 R package. Data are shown in Supplementary Data 3.

Ribosome profiling (Ribo-seq) and data analysis
Cells were collected and washed with ice-cold PBS containing cycloheximide, then snap-frozen in liquid nitrogen. The frozen cell pellets were lysed using ice-cold lysis buffer containing 150 mM Tris-HCl, 10 mM NaCl, 1% Triton X-100, 0.5 mM DTT, 1% NP–40, 100 μg/mL CHX and DNase. The supernatant was treated with RNase, and urea gels were used to isolate ribosome-protected fragments (RPFs). The library was successfully prepared and sequenced using the SURFSeq 5000 platform (GeneMind). The clean reads were obtained by filtering the raw reads, mapped to the GRCh38/hg38 genome, human rRNA sequences, human tRNA sequences, and human CDS or cDNA sequences. Sequencing quality was assessed by RPFs distribution analysis performed using the genomic alignments R package and riboWaltz. Ribo-seq read count matrix was generated using feature counts software by counting the number of reads mapping to the ORF of protein-coding genes. Normalisation and differential translation analysis were performed using the DEseq2 R package. Visualisation of differential translation genes (volcano plot) was generated using the ggplot2 R package. The genome visualisation was performed using the integrative genomics viewer (IGV, version 2.18.4) based on BAM files of each sample mapped to GRCh38/hg38 genome. Data are shown in Supplementary Data 4.

Metabolomics analysis using GC-MS and LC-MS, and data processing
SNU398 cells were seeded in 15-cm plates in tyrosine-restricted medium or normal medium. After 2 days, a total of 1×10⁸ cells were harvested from each group to generate four technical replicates. Then, pre-cooled methanol-water (V:V=4:1) and chloroform were added to the cells, followed by sonication for 20 min in an ice-water bath and standing at −40°C overnight. After being centrifuged at 16,000×g for 10 min at 4°C, 2/3 of the supernatant was removed for LC-MS detection, and the remaining supernatant was used for GC-MS. To perform LC-MS, the dried supernatants were reconstituted with methanol-water (V:V=1:4), and mixed with the internal standard (0.1 mg/mL), vortexed for 30s, sonicated for 3 min in an ice-water bath, and then stood for 2 hours at −40°C. After being centrifuged again at 16,000×g for 10 min at 4°C, the supernatant was aspirated with a syringe, filtered using a 0.22 μm organic-phase pinhole filter, and stored at −80°C for LC-MS analysis. The procedure of GC-MS analysis was described above in amino acid profiling. LC-MS analysis was done by Waters ACQUITY UPLC I-Class plus and Thermo QE system. GC-MS analysis was performed using an Agilent 8890-5977B quadrupole instrument time-of-flight mass spectrometer.

Progenesis QI v3.0 software (Nonlinear Dynamics, Newcastle, UK) was used to pre-process the raw data for baseline filtering, peak identification, integration, retention time correction, peak alignment and normalisation. MS-DIAL software was used to perform qualitative and quantitative analysis of small molecules from GC-MS data collected in Full Scan mode. The identification of compounds was based on multiple dimensions such as RT (retention time), exact mass number, secondary fragments, and isotope distribution. Identification analysis was performed using the Human Metabolome Database (HMDB), Lipidmaps (v2.3), METLIN database, and LuMet Animal 3.0 local database. Data are shown in Supplementary Data 5.

Data mining of genome-wide CRISPR screens
Screen results from the DepMap project (DepMap Public 24Q2+ Score Chronos), visualised through ggplot2 R package were used to identify the dependencies of YARS or tyrosine metabolism-related gene sets in HCC cell lines.

Multi-omics analysis and visualisation
The GSEA analysis based on the KEGG and GO database was performed by clusterProfiler (V4.10.1) R package, and GSEA plot was generated by ggplot2 R package and enrichplot R package. Combination analysis of TCGA with CPTAC, RNA-seq with proteomics, RNA-seq with Ribo-seq, and proteomics with Ribo-seq was performed based on the results of differential analysis of each omics (log2FoldChange) and visualised by ggplot2 R package.

Codon and amino acid frequency analysis
The complete CDS sequences of the human genome were retrieved from the NCBI CCDS database. After filtering all sequences lacking an ATG initiation codon, codon counts for all 64 codon types across CDS sequences were quantified using Biostrings R package. Then, the percentage distribution of each codon within individual CDS sequences was calculated to generate a codon frequency matrix. Subsequently, the amino acid counts and frequency matrix for all 20 amino acids were generated according to the codon table and codon count matrix. Based on the codon and amino acid frequency matrix, we ranked all CDS from high to low based on the frequency of each codon and amino acid, and generated codon TAC and tyrosine frequency distribution curve of all human genome CDS using ggplot2. Next, the differential codons and amino acids of target gene sets screened from multi-omics were calculated based on differential value (log2FoldChange) and codons and amino acids frequency matrix, and the differential codons and amino acids heatmap was generated by ggplot2.

Statistical and reproducibility
All results were shown as the mean ± standard deviation, and the data were from at least three independent experiments unless specifically stated. The statistical analyses were performed using GraphPad Prism 10 or the corresponding R packages. GraphPad Prism 10 software was used for mouse survival studies to generate a survival curve and perform statistical significance analysis. Kaplan–Meier survival curves were generated from RNA sequencing gene expression data and the outcome of 330 hepatocellular carcinomas and analysed for statistical significance using the R software package. An unpaired two-tailed Student’s t test was used to analyse the data for two-group comparisons. ANOVA analysis was used to compare multiple groups as described in the figure legends.

Reporting summary
Further information on research design is available in the Nature Portfolio Reporting Summary linked to this article.

Data availability
The proteomic and metabolome data generated in this study have been deposited in the CNCB database under accession codes OMIX010875 and OMIX010876. The proteomic and metabolomic data are also available under accession code IPX0014937000 in the Integrated Proteome Resources. The RNA-seq and Ribo-seq data generated in this study have been deposited in the CNCB database under accession code HRA012185. The HCC single-cell transcriptome data used in this study are available in the Gene Expression Omnibus (GEO) database under accession codes GSE202642, GSE242889, and GSE155481. The raw data of RNA-seq, Ribo-seq, proteomic, and metabolomic data are available under open access. The sequences of primers, shRNA, and probes used in this article are supplied in Supplementary Data 1. The data from transcriptomics, translatomics, proteomics, and metabolomics are supplied in Supplementary Data 2–5, respectively. The raw numbers for charts and graphs are available in the Source Data file. Source data are provided with this paper.

Peer review rounds
[{"round": 1, "reviewer_comments": {"reviewer_1": "This manuscript presents an extensive mechanistic study on how HCC reprograms tyrosine metabolism to support tumorigenesis by favoring translation over catabolism. The study reveals that MYC driven upregulation of YARS1 and tRNA-Tyr-GUA shunts tyrosine toward protein synthesis, particularly in translation of mitochondrial complex I subunit NDUFB8 and the lipid regulator SCD1. Tyrosine restriction via dietary limitation, enzymatic degradation (TAL), or inhibition of YARS1 (tyrosinol) impairs oxidative phosphorylation and promotes ferroptosis, resulting in reduced tumor burden and increased survival in mouse HCC models. The authors also identify synergistic vulnerabilities via CRISPR screening, highlighting GPX4 and BCL2 inhibition as effective combinatorial strategies. This is a compelling study that uncovers a non-obvious metabolic vulnerability in HCC by targeting translational tyrosine dependency. However, further additional evidence is required to clarify mechanisms and strengthen causal links\nMajor comments:\n1. Given that the central claim is that tyrosine availability fuels tumorigenesis, a direct quantitative comparison (tumor weight, number, size) between 100% and 500% tyrosine diet groups would strengthen this claim. The data presented in fig 1d-f highlight the impact of dietary tyrosine modulation. While the 0% tyrosine diet robustly reduces tumor burden, the reported increase in tumor burden with 500% tyrosine supplementation is mentioned but not fully quantified or statistically interrogated in the main figure panels.\n2. Although fig. 2 provides evidence for increased protein incorporation of 3H-tyrosine in HCC and upregulation of YARS1 and tRNA-Tyr-GUA, there is no direct assessment of global protein synthesis under tyrosine-free conditions to determine if tyrosine restriction broadly suppresses translation or specifically affects tyrosine-rich transcripts. An O-propargyl-puromycin (OPP) assay would allow quantification of nascent protein synthesis under tyrosine-free vs. control conditions. This could confirm that global translation remains largely intact and would support the claim that only tyrosine-dependent translation is compromised.\n3. The ribosome profiling data in fig. 3 suggest that translation of tyrosine rich transcripts like NDUFB8 and SCD1 is impaired under tyrosine restriction, but the resolution of codon specific stalling (especially at the A or P site) is not reported. Ribosome stalling at tyrosine codons would directly demonstrate codon specific translation stress. Precise mapping of ribosome footprints could reveal whether stalled ribosomes accumulate at Tyr codons in these transcripts, and whether the stalling occurs at the A or P sites, thus validating mechanistic specificity. This reviewer suggests to re-analyze Ribo-seq data with higher resolution A- and P-site mapping around TAC codons in NDUFB8 and SCD1 transcripts. Also, generating cumulative plots showing footprint pileups at Tyr codons under tyrosine-replete vs. tyrosine-deprived conditions in NDUF8 and SCD1 transcripts might be very informative.\n4. The luciferase reporters for NDUFB8 and SCD1 translation rely on the native sequence. However, the specificity of RTTA to the TAC codon (vs. TAT) is assumed but not tested. Given that tRNA-Tyr-GUA decodes TAC codons and not TAT, mutating TAC to TAT in the reporter constructs could test codon specificity. If translation inhibition persists with TAT-only reporters, this may suggest off-target or broader effects, whereas rescue would confirm specific targeting of TAC codons via tRNA-Tyr-GUA.\nMinor comments:\n1.Given the relatively high in vivo dosage of tyrosinol (500 mg/kg), a toxicity and specificity profile is warranted. Are other aminoacyl-tRNA synthetases affected?\n2. While ITC data suggest that tyrosinol binds YARS1 with similar affinity as tyrosine, no kinetic data (competitive inhibition or IC50 for aminoacylation) are presented.", "reviewer_2": "This manuscript presents a comprehensive study investigating how HCC cells rewire tyrosine metabolism to favour protein translation rather than catabolism, ultimately supporting tumourigenesis. The authors demonstrated that, rather than being catabolized, tyrosine is preferentially diverted toward protein synthesis in HCC. This reprogramming is facilitated through MYC-dependent upregulation of YARS1 and its cognate tRNA, tRNA-TyrGUA. The integration of multi-omics data and functional studies both in vitro and in vivo across human and murine models convincingly show that tyrosine availability is critical for tumour growth and that restricting tyrosine (via diet or enzymatically) or inhibiting YARS1 impairs tumour progression. The authors provide a compelling rationale for targeting tyrosine utilization as a therapeutic approach in liver cancer. This study will be of broad interest to readers of Nature Communications, particularly those interested in cancer metabolism and translational oncology. While the conclusions are largely supported by the data, several conceptual and mechanistic aspects would benefit from clarification or additional experimentation. For example, the role of the integrated stress response (ISR), which is notably absent from the discussion despite its relevance in amino acid sensing.\nSpecific comments:\n1. Figure 1D-F : Systemic effects of tyrosine-deficient diets. It is unclear whether the systemic consequences of tyrosine-deficient diets were controlled for. Were there differences in food intake, body weight (lean mass/fat mass), or signs of hepatic dysfunction. Given that tyrosine is also an important precursor to several neurotransmitters, including data from healthy, wild-type animals subjected to these diets would be beneficial and bolster any translational relevance.\n2. Are tyrosine-restricted diets administered prior to tumour initiation, or after tumours are established? It would be important to evaluate whether dietary intervention would still be effective when tumours are already present or larger.\n3. Since phenylalanine is a precursor to tyrosine, how do the authors explain the apparent complete depletion of Tyr under ‘0% tyrosine’ conditions in vitro ( is there no tyrosine biosynthesis or is this insufficient to meet the demands of the cells)? Stable isotope tracing experiments with phenylalanine may help explain this.\n4. Figure 1I-J: please include isotopologue abundances in addition to fractional enrichment in the 13C-Tyr tracing data.\n5. Are the observed Tyr dependencies a general feature of liver tumourigenesis, or specifically driven by MYC dysregulation? Authors mention that 11.56% of HCC patients observe MYC amplification, but the cell lines used (SNU398, SNU449, and Huh7) do not have MYC amplification. Correlating Tyr sensitivity with MYC expression would address this- does MYC KD reduce tyrosine dependency or rescue effects of tyrosine depletion?\n6. Figure 2O-2Q show that some HCC cell lines are highly dependent on YARS1. Do these correspond to MYC-high models? Does YARS1 correlate with MYC expression levels or general translation rates?\n7. Is the reduction in tyrosine metabolic genes in HCC cells and tumours MYC-dependent?\n8. If YARS1 is knocked down, can the observed mitochondrial and lipid peroxidation defects be rescued by re-expressing SCD1 or NDUFB8?\n9. ISR Pathway : the authors make no mention to the ISR which is canonically activated in response to AA limitation via GCN2/eif2a/ATF4. This is a key mechanistic gap, especially since uncharged tRNAs are canonical activators of GCN2, several markers observed (e.g. SLC7A5, SLC7A11, oxidative stress response genes) are known ATF4 target genes, and proteins upregulated upon tyrosine deprivation are clustered in hallmarks that are common to amino acid restriction (autophagy, L-amino acid transport etc). The ISR could influence lipid metabolism and ferroptosis, potentially confounding the attribution to SCD1 downregulation. Have the authors assessed ISR activation in response to tyrosine depletion or YARS1 KD? This pathway should be acknowledged.\n10. Fatty acid metabolism and link to ferroptosis: fatty acid composition is known to change under metabolic stress or ISR activation. Can the authors uncouple the effects of tyrosine depletion on MUFA/PUFA balance from its protenogenic role in SCD1 synthesis? Would MUFA supplementation rescue ferroptosis induced by tyrosine depletion, MYC KD, or YARS1 KD? Does SCD1 KD alone recapitulate the lipid peroxidation phenotypes?\n11. Figure S1L/S1N and S1A/S1C: Does the proliferation increase with tyrosine supplementation correlate with increased protein expression of SCD1 and NDUFB8?\n12. Figure 1I: the 12-hour labelling time is relatively long to assess amino acid uptake. The increase in M+6 Tyr could be due to decreased catabolism rather than increased uptake. Use of transporter inhibition (eg. JPH203 for SLC7A5) or transporter KD would clarify this mechanism.\n13. Figure 1C: tumour size negatively correlates with Tyr concentration. Can authors measure tyrosine levels in tumour interstitial fluid to confirm that this doesn’t reflect local tyrosine availability?\n14. Line 70-71: The statement that “low levels of tyr favour liver tumourigenesis” seems contradictory given that later data show increased tyrosine uptake and that tyrosine supplementation boosts HCC proliferation. Should reframe to clarify that tumours have an increased requirement for tyrosine.\n15. Figure 2B/2C , Lines 126-128: The enrichment of tyrosine codons in translationally upregulated proteins may reflect general increases in protein synthesis. Would this not also be true for other amino acids? Is this increased utilization of tyrosine for protein synthesis tyrosine-specific or a global phenomenon associated with tumour progression?\n16. In Figure 3 the effect of the tyrosine-deficient diet on specific proteins is evaluated in tumour cell lines and is also shown for tumours. Are those effects tumour-specific, i.e. are the levels of SCD1 and NDUF8 affected by Tyr-deficient diet in the adjacent liver tissue of tumour-bearing mice? They do have tissues so would be important to see of NDUF8 and SCD1 are also affected in normal livers.\n17. Would the expression of NDUF8 and SCD1 proteins also be affected if any other amino acids are depleted?\n18. The increase in PUFA levels upon tyrosine deprivation is surprising. Do authors have a plausible explanation?\n19. Were tyrosine levels measured with FjTAL treatment?\nGeneral comment: a lot of panels should be moved to supplemental or additional information to make main figures less crowded and the main points more concise.", "reviewer_3": "I co-reviewed this manuscript with one of the reviewers who provided the listed reports. This is part of the Nature Communications initiative to facilitate training in peer review and to provide appropriate recognition for Early Career Researchers who co-review manuscripts.", "reviewer_4": "This study explores hepatocellular carcinoma's metabolic plasticity, focusing on how HCC cells reprogram tyrosine uptake and use to promote translation rather than catabolism. It presents extensive data integrating metabolomics, transcriptomics, proteomics, ribosome profiling, CRISPR screening, and in vivo models. The idea that tyrosine translation availability (RTTA) is a vulnerability in HCC and can be targeted is potentialy clinically relevant. The concepts appear to be novel, however, despite the comprehensive data, several weaknesses diminish the mechanistic insights and translational impact.\nMajor Concerns\n1. The genome-wide CRISPR screen is used as a central aspect to identify synthetic vulnerabilities in the RTTA context. However, the changes observed are modest, and the study subsequently relies largely on pharmacological inhibitors (e.g., venetoclax, RSL3, erastin, sorafenib) to support claims. The reliance on small-molecule inhibitors with pleiotropic effects makes it difficult to attribute synergy specifically to RTTA-related pathways. As such, validation using genetic loss-of-functon(knockout/knockdown) models for key hits (e.g., GPX4, SLC7A11, BCL2) is essential. Rescue experiments with ferroptosis inhibitors (e.g., ferrostatin-1, β-mercaptoethanol) would help confirm the ferroptotic mechanism.\n2. Sorafenib is a multi-kinase inhibitor with broad targets beyond ferroptosis. Venetoclax also has complex effects on apoptosis. Without genetic proof, the observed synergy between tyrosine restriction and these agents may reflect unrelated drug effects rather than specific mechanistic interactions with RTTA. For this, it would be relevant to include in vivo experiments with genetically defined ferroptosis-sensitive models, such as Xct (SLC7A11) or GPX4 deficient cells (important to note that these cells cannot growth in vitro without β-mercaptoethanol or ferrostatin-1 respectively – but in the presence of these agent knockout cells can be generate and implanted in vivo). These experiments would provide strong mechanistic validation that RTTA acts via ferroptosis.\n3. The study convincingly shows reduced tyrosine metabolism and increased translation, but the direct causality between MYC → YARS1 → translation of ETC components and ferroptosis is not fully established. Would experiments using codon-recoding of NDUFB8/SCD1 reduce tyrosine dependence? This experiments while challenging could strengthen the link between codon usage bias and ferroptotic outcomes.\nMinor Concerns\n• The dietary intervention (TR diet) is intriguing, but patient feasibility is uncertain. A discussion of nutritional safety, systemic effects, and whether restriction selectively affects tumor cells versus normal hepatocytes is necessary.\n• Tyrosinol and TAL enzyme approaches are promising, but off-target metabolic effects remain underexplored. More profiling of systemic amino acid metabolism would be important before translational claims.\n• Figures: Several panels are highly data-dense. Consider streamlining or moving supportive proteomic/transcriptomic heatmaps to Supplementary Figures.", "reviewer_5": "The manuscript titled “Targeting tRNA-dependent tyrosine usage unveils a metabolic vulnerability in hepatocellular carcinoma” described tyrosine charging to tRNA and its subsequent utilization for protein translation as a metabolic dependency for the tumorigenesis of HCC and demonstrated that limiting the availability of tyrosine for translation attenuates tumorigenesis. Specifically, the authors reported that free tyrosine levels are significantly reduced in human and mouse HCC tumors compared to normal tissues and that this reduction in tyrosine levels is attributed to MYC-dependent increased tyrosine charging to form tRNA-TyrGUA, which is needed for protein translation.\nTo demonstrate the dependence of HCC on the availability of tyrosine charging and its subsequent translation, the authors showed that limiting tyrosine translation availability—via dietary limitation, YARS1/tRNA-TyrGUA ablation, tyrosine degradation (TAL), or YARS1 inhibition (tyrosinol)—leads to impaired oxidative phosphorylation and ferroptosis and attenuation of tumor progression in several mouse models. Mechanistically, the authors showed that restriction of tyrosine translation availability reduces tyrosine codon-dependent translation of mitochondrial complex I subunit NDUFB8 and lipid regulator SCD1, causing complex I misassembly, oxidative phosphorylation failure, and lipid peroxidation-induced ferroptosis.\nBased on these findings, the authors concluded that tRNA-dependent tyrosine usage is a metabolic vulnerability of HCC that can be exploited for therapeutic treatment. While there are some issues with the interpretation of the data and some claims made are not well-founded, the authors have compilled relevant data to support their claims, and the discovery of the role of tRNA-dependent tyrosine usage in HCC is rather novel and potentially important. If the authors could address some of the flaws in the current version of the manuscript, the manuscript should be at the level of Nature Communications.\nMajor Flaws and Issues:\n1. One of the problems reading through the manuscript and figures is that the authors crammed too many data points into each figure. For example, to describe the effects of various treatments on tumor growth, the authors used non-liver body weight (body weight minus liver weight) to show that treatments did not have an impact on non-liver body weight. These data are probably not necessary to include in the main figures. I would suggest the authors move less relevant figures to the supplement to avoid overwhelming the figures and readers (this makes some figures barely eligible such as Figures 1C, 3E, 3I, 3K, and 3L).\n2. One of the major claims in the manuscript is that restricting tRNA-dependent tyrosine usage attenuates HCC tumorigenesis and progression by reducing codon-dependent translation of mitochondrial complex I subunit NDUFB8 and lipid regulator SCD1. This would imply that disrupting the expression and/or activity of NDUFB8 and SCD1 could similarly affect HCC tumorigenesis and progression as restricting tRNA-dependent tyrosine usage. Could the authors provide data to test this hypothesis?\n3. As a follow-up, what makes the translation of NDUFB8 and SCD1 more susceptible to tyrosine restriction? Given that tyrosine is an amino acid required for synthesizing all tyrosine-containing proteins, it is reasonable to assume that proteins with high tyrosine content in their sequences would be more likely to be affected by tyrosine restriction. Could the authors survey protein databases to identify proteins with a high percentage of tyrosine and determine whether NDUFB8 and SCD1 are among them? That piece of data would strengthen the argument made in the manuscript.\n4. The authors created three HCC mouse models to demonstrate the efficacy of tyrosine restriction (Figures 1D–F). However, in the figure legends, the authors did not provide a clear indication of which mouse model was used in subsequent figures (e.g., Figures 1M, 2E), making it hard to interpret the data. Please specify the mouse models used in the figure legends.\n5. In Figure 2, the authors claimed that the upregulation of YARS is driven by MYC overexpression. Given that MYC is only responsible for driving a fraction of HCC tumors, it is assumed that this observation is likely specific to MYC-dependent HCC. Is YARS also upregulated in DEN-induced HCC mouse models?\n6. In Figure 3, the authors stated that restriction of tyrosine translation availability leads to impaired oxidative stress and ferroptosis. However, the data provided in Figure 3 showed that, while limiting tyrosine upregulates several ferroptosis suppressors such as GPX4 and SLC7A11, it did not directly induce ferroptosis, as the authors have not tested whether ferroptosis inhibitors could rescue the cell death or measured whether tyrosine limitation induces lipid peroxidation. The data provided can only support a claim that tyrosine limitation increases ferroptosis sensitivity rather than leading to ferroptosis. Therefore, the authors need to tone down their claims that limiting tyrosine leads to ferroptosis.\n7. In Figure 4, the authors showed that a genome-wide CRISPR screen under tyrosine restriction identified a list of genes, including anti-apoptotic protein BCL2 and anti-ferroptosis proteins SLC7A11 and GPX4, which synergize with tyrosine restriction to promote cell death upon knockout. The authors further validated that pharmacological inhibition of BCL2 or ferroptosis induction using SLC7A11 inhibitors or GPX4 inhibitors could synergize with dietary tyrosine limitation and YARS1 depletion to promote HCC cell death in vitro and attenuate HCC tumor growth in vivo. These data are largely consistent with those provided in Figure 3, showing that tyrosine restriction promotes ferroptosis sensitivity. However, Figure 3 is titled as “Restriction of tyrosine translation availability leads to impaired oxidative stress and ferroptosis” and was allocated to show that tyrosine restriction promotes ferroptosis sensitivity. Thus, it would make more sense to rearrange and consolidate these ferroptosis-related data into one figure. It would take some effort to rearrange and adjust the text accordingly, but it would significantly improve the manuscript’s logical flow.\n8. In Figures 4, 5, and 6, the authors showed some representative images of liver tumors (4I, 4L, 5N, and 6N) after treatment. Some of these liver tumors appeared completely tumor-free, yet the survival of the mice from these treatment groups (4K, 4N, 5P, and 6P) was extended but not completely protected. While this may sound like nitpicking and fastidious criticism, it does make readers question how representative these tumor images are. I would recommend selecting more representative and realistic images to avoid being nitpicked.\n9. The authors used TEM images of livers to show that cristae formation was severely affected by tyrosine limitation via dietary limitation, YARS1/tRNA-TyrGUA ablation, tyrosine degradation (TAL), or YARS1 inhibition (tyrosinol) and quantified maximal cristae width to show that these treatments lead to mitochondrial defects. While these images are on the same scale based on the scale bar, the mitochondrial size and electron density vary significantly. For example, in Figure 6S, the tyrosinol group showed clearly smaller and more electron-dense mitochondria compared to the control-treated ones. These images are not quite comparable in scale, making it difficult to quantify maximal cristae width. I would recommend selecting more comparable images as representative images.\n10. In several figures (Figures 5K–L, 6J–K), the authors showed that in HCC cell lines, tyrosine degradation (TAL) or YARS1 inhibition (tyrosinol) increases lipid peroxidation, suggesting that these treatments induce ferroptosis. It would be more convincing if the authors could also test whether ferrostatin or an iron chelator could attenuate the lipid oxidation induced by these treatments."}, "author_response": "Response to Reviewers’ comments\nReviewer #1 (Remarks to the Author); expert in translation regulation:\nThis manuscript presents an extensive mechanistic study on how HCC reprograms tyrosine metabolism to support tumorigenesis by favoring translation over catabolism.\nThe study reveals that MYC driven upregulation of YARS1 and tRNA-Tyr-GUA shunts tyrosine toward protein synthesis, particularly in translation of mitochondrial complex I subunit NDUFB8 and the lipid regulator SCD1. Tyrosine restriction via dietary limitation, enzymatic degradation (TAL), or inhibition of YARS1 (tyrosinol) impairs oxidative phosphorylation and promotes ferroptosis, resulting in reduced tumor burden and increased survival in mouse HCC models. The authors also identify synergistic vulnerabilities via CRISPR screening, highlighting GPX4 and BCL2 inhibition as effective combinatorial strategies.\nThis is a compelling study that uncovers a non-obvious metabolic vulnerability in HCC by targeting translational tyrosine dependency. However, further additional evidence is required to clarify mechanisms and strengthen causal links.\nResponse: We appreciate the constructive comments from the reviewer, which will help us further strengthen our manuscript. We have carefully revised the manuscript according to the Reviewer’s comments and provided point-by-point responses as follows.\nMajor comments:\n1. Given that the central claim is that tyrosine availability fuels tumorigenesis, a direct quantitative comparison (tumor weight, number, size) between 100% and 500% tyrosine diet groups would strengthen this claim. The data presented in fig 1d-f highlight the impact of dietary tyrosine modulation. While the 0% tyrosine diet robustly reduces tumor burden, the reported increase in tumor burden with 500% tyrosine supplementation is mentioned but not fully quantified or statistically interrogated in the main figure panels.\nResponse: We appreciate the reviewer’s insightful comments. The quantitative comparisons (including tumor weight, number, and size) between the 100% and 500% tyrosine diet groups are presented in Figures S1B-S1D of the revised manuscript, due to space limitations (please also see Response Figure 1-1). In the three models (MYC overexpression-driven HCC model, DEN treatment-induced HCC model, and intrahepatic injection model of human HCC cells), dietary tyrosine supplementation (Tyr 500% diet) led to a significant increase in characteristic hepatomegaly, liver-to-body weight ratio, tumor burdens, and diameters relative to the standard diet (Tyr 100% diet), indicating that tyrosine supplementation promotes liver cancer development. The related description has been added to the revised manuscript (Page 4, Lines 83-84).\nResponse Figure 1-1. (A) A diagram depicting the in vivo assessment of tumorigenesis by tyrosine in Myc/Alb-cre mice (top), C57BL/6J mice treated by DEN (middle), and BALB/c nude mice with HCCLM3 cells intrahepatic injection (bottom). (B) Photographs of the liver from the tumor-bearing mice fed either a normal diet (Tyr 100%) or a tyrosine-supplemental diet (Tyr 500%), including Myc/Alb-cre mice (top), C57BL/6J mice (middle), and BALB/c nude mice (bottom). (C) The body weight excluding liver weight, liver to body weight ratio, tumor number, and maximum tumor diameter of the tumor-bearing mice fed tyrosine-modified diet were shown, including Myc/Alb-cre mice (top) (n = 7), C57BL/6J mice (middle) (n = 7), and BALB/c nude mice (bottom) (n = 5).\n2. Although fig. 2 provides evidence for increased protein incorporation of 3H-tyrosine in HCC and upregulation of YARS1 and tRNA-Tyr-GUA, there is no direct assessment of global protein synthesis under tyrosine-free conditions to determine if tyrosine restriction broadly suppresses translation or specifically affects tyrosine-rich transcripts. An O-propargyl-puromycin (OPP) assay would allow quantification of nascent protein synthesis under tyrosine-free vs. control conditions. This could confirm that global translation remains largely intact and would support the claim that only tyrosine-dependent translation is compromised.\nResponse: We thank the Reviewer for this great question. To evaluate whether tyrosine restriction broadly suppresses translation, we first analyzed our ribosome-profiling data. As shown in Response Figure 1-2 A (corresponding to the revised manuscript Figure S10H), the empirical cumulative distribution of translation efficiency for 5188 genes in SNU398 cells cultured in control media revealed a weak shift in the curve relative to tyrosine-restricted media, indicating that global translation efficiency remained unchanged under tyrosine restriction. Next, the O-propargyl-puromycin (OPP) assay also showed that restricting tyrosine translation availability via tyrosine-free or YARS1 knockdown did not change nascent protein synthesis (Response Figure 1-2 B and C, corresponding to the revised manuscript Figure S10I and S10J). These results consistently indicate that global translation remains largely intact under tyrosine restriction conditions. The related description has been added to the revised manuscript (Page 11, Lines 273-275).\nResponse Figure 1-2. (A) The empirical cumulative distribution of translation efficiency for 5188 genes in SNU398 cells cultured in control and tyrosine-restricted media. (B and C) Representative images of in vitro OPP incorporation show unchanged nascent protein synthesis in the indicated cells. DAPI, 4,6-diamidino-2-phenylindole.\n3. The ribosome profiling data in fig. 3 suggest that translation of tyrosine rich transcripts like NDUFB8 and SCD1 is impaired under tyrosine restriction, but the resolution of codon specific stalling (especially at the A or P site) is not reported. Ribosome stalling at tyrosine codons would directly demonstrate codon specific translation stress. Precise mapping of ribosome footprints could reveal whether stalled ribosomes accumulate at Tyr codons in these transcripts, and whether the stalling occurs at the A or P sites, thus validating mechanistic specificity. This reviewer suggests to re-analyze Ribo-seq data with higher resolution A- and P-site mapping around TAC codons in NDUFB8 and SCD1 transcripts. Also, generating cumulative plots showing footprint pileups at Tyr codons under tyrosine-replete vs. tyrosine-deprived conditions in NDUF8 and SCD1 transcripts might be very informative.\nResponse: Thanks for your professional advice. To obtain higher precision RPF sequence alignment information, we strictly restricted the read length range (25-34nt) during sequence filtering and realigned the RPFs to the genome with base-pair precision using STAR. After precisely locating the P-sites and A-sites of all RPFs mapping to the CDS sequences (SCD transcript: ENST00000370355 and NDUFB8 transcript: ENST00000299166), we calculated the relative positions of all these ribosomal footprints represented by RPFs with respect to the nearest TAC codons on the transcripts, and plotted ribosomal footprint accumulation around TAC codons. Additionally, we analyzed the frequency of RPFs exhibiting P-site stalling and A-site stalling at TAC codons in both transcripts.\nBased on the reanalysis results of Ribo-seq raw data, tyrosine restriction resulted in a higher frequency of ribosomal footprints at the TAC codon relative to normal conditions, with predominant A-site stalling observed rather than P-site stalling (Response Figure 1-3 A and B, corresponding to the revised manuscript Figure S10K. The data in the figure sourcing from the Response Table 1 and 2). Footprint accumulation density analysis further revealed that in the SCD1 transcript, the tyrosine-restricted group showed a higher frequency of ribosomal footprints with P-site accumulation at the codon immediately preceding the 5’ end of the TAC codon, confirming that tyrosine deprivation leads to A-site stalling of ribosomes at TAC codons (Response Figure 1-3 C, corresponding to the revised manuscript Figure S10L). No significant difference in footprint accumulation density was observed in the NDUFB8 transcript, potentially due to an insufficient number of RPFs aligned to this transcript (Response Figure 1-3 D, corresponding to the revised manuscript Figure S10L). The related description has been added to the revised manuscript (Page 12, Lines 293-302).\nResponse Figure 1-3. (A and B) The frequency of ribosome footprint stalling at TAC codon and the A-site and P-site stalling frequency at TAC codon in the SCD1 and NDUFB8 transcripts. (C and D) The accumulation plot of ribosome footprint around TAC codon ±12nt in the SCD1 (C) and NDUFB8(D) transcripts.\nTable.1 The transcript of SCD1 (ENST00000370355)\nA-site P-site\nA-site P-site total stalling stalling\nSample\nstalling stalling RPFs frequency frequency\n(100%) (100%)\nTyr 0%_1 22 11 1077 2.04 1.02\nTyr 0%_2 13 12 1479 0.88 0.81\nTyr 100%_1 41 39 6707 0.61 0.58\nTyr 100%_2 39 56 5466 0.71 1.02\nTable.2 The transcript of NDUFB8 (ENST00000299166)\nA-site P-site\nA-site P-site total stalling stalling\nSample\nstalling stalling RPFs frequency frequency\n(100%) (100%)\nTyr 0%_1 6 1 315 1.90 0.32\nTyr 0%_2 7 7 355 1.97 1.97\nTyr 100%_1 6 5 1254 0.48 0.40\nTyr 100%_2 10 6 936 1.07 0.64\n4. The luciferase reporters for NDUFB8 and SCD1 translation rely on the native sequence. However, the specificity of RTTA to the TAC codon (vs. TAT) is assumed but not tested. Given that tRNA-Tyr-GUA decodes TAC codons and not TAT, mutating TAC to TAT in the reporter constructs could test codon specificity. If translation inhibition persists with TAT-only reporters, this may suggest off-target or broader effects, whereas rescue would confirm specific targeting of TAC codons via tRNA-Tyr-GUA.\nResponse: We appreciate the reviewer’s thoughtful point. As the reviewer suggested, we mutated TAC to TAT in the reporter constructs, as shown in the schematic diagram (Response Figure 1-4 A, corresponding to the revised manuscript Figure S13C). The Relative luciferase activity was higher in SNU398 cells transfected with the MUT reporter constructs (for NDUFB8 or SCD1) than in those with the WT constructs, under tyrosine-free conditions or upon YARS1 knockdown (Response Figure 1-4 B and C, corresponding to the revised manuscript Figure S13D and S13E), indicating that restricting tyrosine translation availability has a greater translation inhibition effect on TAC-rich transcripts than TAT-rich transcripts. The related description has been added to the revised manuscript (Page 14, Lines 355-359).\nResponse Figure 1-4. (A) Graphic illustration of the indicated reporter expressing luciferase infusion with either SCD1 or NDUFB8 with a different TAC codon frequency. RLuc serves as an internal control. (B and C) Relative luciferase activities in SNU398 cells transfected with the indicated reporters and cultured in tyrosine-modified mediums (B) or relative luciferase activities in SNU398 cells transfected with the indicated reporters together with YARS1 shRNA (C). Quantification of luciferase activities normalized to Renilla luciferase activities (n = 3).\nMinor comments:\n1. Given the relatively high in vivo dosage of tyrosinol (500 mg/kg), a toxicity and specificity profile is warranted. Are other aminoacyl-tRNA synthetases affected?\nResponse: We appreciate the reviewer’s insightful comments. To evaluate the safety profile of tyrosinol in mice, we first analyzed organ weights upon tyrosinol treatment and found that tyrosinol treatment (repeated dosing of 500 mg/kg/d for 4 weeks, oral gavage) did not result in any significant changes (Response Figure 1-5 A, corresponding to the revised manuscript Figure S24E). Concurrently, the levels of alanine aminotransferase (ALT), aspartate aminotransferase (AST), creatinine, creatine kinase, and lactate dehydrogenase, established biomarkers for liver, kidney, and myocardial injury, were measured. Tyrosinol treatment showed no significant effects on these markers (Response Figure 1-5 B, corresponding to the revised manuscript Figure S24F). Furthermore, no apparent pathological differences or tissue injury were observed after tyrosinol treatment (500 mg/kg/d) (Response Figure 1-5 C, corresponding to the revised manuscript Figure S24G). These results indicate that tyrosinol treatment did not induce tissue injury, consistent with a previous study demonstrating that dietary tyrosinol supplementation (10 g/kg in the chow) caused no differences in physiological indices (Figure S7E-S7H) (Zhao et al, 2023) (PMID: 37071536). The related description has been added to the revised manuscript (Page 22, Lines 603-608). Additionally, we examined the impact on the aminoacylation of the other two aromatic amino acids (phenylalanine and tryptophan) after tyrosinol treatment. Results demonstrated that the charged tRNA-PheGAA and tRNA-TrpCCA levels remained unchanged upon tyrosinol treatment, indicating that tyrosinol treatment does not have potential off-target effects in vivo (Response Figure 1-5 D, corresponding to the revised manuscript Figure S24H). The related description has been added to the revised manuscript (Page 22, Lines 608-613).\nResponse Figure 1-5. (A) Male C57BL/6J mice were treated with vehicle or Tyrosinol. The weight of body, liver, kidney, heart, lung and colon were measured. (B) Serum levels of ALT, AST, CREA, CK and LDH were determined in mice treated with vehicle or tyrosinol. (C) H&E staining of liver, kidney, heart, lung and colon from mice treated with vehicle or tyrosinol. Scale bar 100 µm. (n=5).\n2. While ITC data suggest that tyrosinol binds YARS1 with similar affinity as tyrosine, no kinetic data (competitive inhibition or IC50 for aminoacylation) are presented.\nResponse: We appreciate the reviewer's helpful comments. Aminoacyl-tRNA synthetases (AARSs) produce aminoacylated tRNAs for protein synthesis. As shown in Response Figure 1-6 A, the amino acid is first activated by ATP (blue box). Activated amino acid is then transferred to the tRNA (green box). The full aminoacylation pathway (purple box) is marked by the dissociation of the aminoacyl-tRNA from the enzyme. Thus, the aminoacylation rate can be measured by the formation of PPi. Based on this, the production of PPi is measured via a fluorogenic PPi sensor according to the manual of the PhosphoWorksFluorimetric Pyrophosphate Assay Kit *Enhanced Selectivity* (AAT Bioquest, Cat#21614) (Zong et al, 2024) (PMID: 38653238). The results demonstrated that tyrosinol could reduce the binding capacity of YARS1 to tyrosine, as evidenced by IC50 and the increased K (Response Figure 1-6 B, corresponding to the revised manuscript Figure S22A). The relevant description has been added to the revised manuscript (Page 21, Lines 581-583). The detailed description of the pyrophosphate production assay has also been added to the revised manuscript (Page 37, Lines 986-991).\nResponse Figure 1-6. (A) Aminoacyl-tRNA synthetase aminoacylation pathway. (B) The PPi production assay validates the competitive inhibition of tyrosinol on tyrosine binding to YARS1, as evidenced by the increased K in B (left). The PPi production is measured at a tyrosine concentration of 50 μM under treatment with varying concentrations of tyrosinol to calculate its half-maximal inhibitory concentration (IC50) (right). Data are representative of three independent experiments (n = 3).\nReviewer #2 (Remarks to the Author); expert in liver cancer and metabolism:\nThis manuscript presents a comprehensive study investigating how HCC cells rewire tyrosine metabolism to favour protein translation rather than catabolism, ultimately supporting tumourigenesis. The authors demonstrated that, rather than being catabolized, tyrosine is preferentially diverted toward protein synthesis in HCC. This reprogramming is facilitated through MYC-dependent upregulation of YARS1 and its cognate tRNA, tRNA-TyrGUA. The integration of multi-omics data and functional studies both in vitro and in vivo across human and murine models convincingly show that tyrosine availability is critical for tumour growth and that restricting tyrosine (via diet or enzymatically) or inhibiting YARS1 impairs tumour progression. The authors provide a compelling rationale for targeting tyrosine utilization as a therapeutic approach in liver cancer. This study will be of broad interest to readers of Nature Communications, particularly those interested in cancer metabolism and translational oncology. While the conclusions are largely supported by the data, several conceptual and mechanistic aspects would benefit from clarification or additional experimentation. For example, the role of the integrated stress response (ISR), which is notably absent from the discussion despite its relevance in amino acid sensing.\nResponse: We would like to express our sincere appreciation to you for taking the time to read the manuscript in-depth and for providing valuable constructive suggestions that will help improve our paper. We learned a great deal from the comments and made our best efforts to revise the manuscript accordingly.\nSpecific comments:\n1. Figure 1D-F : Systemic effects of tyrosine-deficient diets. It is unclear whether the systemic consequences of tyrosine-deficient diets were controlled for. Were there differences in food intake, body weight (lean mass/fat mass), or signs of hepatic dysfunction. Given that tyrosine is also an important precursor to several neurotransmitters, including data from healthy, wild-type animals subjected to these diets would be beneficial and bolster any translational relevance.\nResponse: We thank the reviewer for raising this critical point regarding the systemic effects of tyrosine deprivation. In response to this question, we conducted a dedicated study in healthy, wild-type mice fed a diet deficient in tyrosine. Our results indicate that the 10-week tyrosine-deficient diets induce an increase in total body weight and fat mass, along with increased liver weight (Response Figure 2-1 A and B, corresponding to the revised manuscript Figure S3A and S3B). No significant differences were observed in the weight of other organs or in daily food intake (Response Figure 2-1 B and C, corresponding to the revised manuscript Figure S3B and S3C). Concurrently, the levels of alanine aminotransferase (ALT), aspartate aminotransferase (AST), triglyceride (TG), total cholesterol (TC), creatinine (CREA), creatine kinase (CK), and lactate dehydrogenase (LDH), established biomarkers for liver, kidney, and myocardial injury, were measured. Tyrosine-deficient diets increase serum ALT, TC, and TG levels, accompanied by lipid droplet accumulation (Response Figure 2-1 D and E, corresponding to the revised manuscript Figure S3D and S3E), partially consistent with a previous report (Sano et al, 2021) (PMID: 33724516). This report showed that combined dietary deprivation of tyrosine and methionine reduced the intermediate metabolite fumarate, thereby reducing KEAP1 succinylation and suppressing nuclear translocation of NRF2, ultimately disrupting lipid metabolism and exacerbating hepatic steatosis in high-fat diet-induced non-alcoholic fatty liver disease model (Sano et al., 2021) (PMID: 33724516). Furthermore, in our new experiments, no pathological changes or tissue injury were observed in other organs (Response Figure 2-1 D and E, corresponding to the revised manuscript Figure S3D and S3E). We did not observe significant differences between the two diet groups during the short-term intervention period in WT mice (2-week or 4-week feeding). The related description has been added to the revised manuscript (Page 5, Line 102 to Page 6, Line 115).\nMoreover, given tyrosine’s role as a dopamine precursor, we evaluated depression-like behaviors using the tail suspension test (TST), a method for assessing depressive states in mice. No significant behavioral differences were observed between the two diet groups after 10 weeks of intervention (Response Figure 2-1 F, corresponding to the revised manuscript Figure S3F). It was noted that an 8-month tyrosine-deficient diet in our original DEN-induced HCC model resulted in some hair appearing grayish white, due to tyrosine acting as a precursor for melanin (Data not shown). However, short-term dietary restriction did not alter hair color. Notably, another study finds that tyrosine restriction extends lifespan in Drosophila by activating FOXO pathway, demonstrating the multifaceted effects of tyrosine-restricted diets on physiological processes in a context-dependent manner (Kosakamoto et al, 2024) (PMID: 39213345).\nTherefore, for tyrosine restriction diets, it might be safe to apply them intermittently for HCC treatment. Clinical application of tyrosine restriction diets also requires optimization of the intervention time to leverage potential anti-tumor effects while minimizing adverse outcomes. The related description (Page 6, Lines 115-121) and discussion (Page 25, Lines 663-680) have been added to the revised manuscript.\nResponse Figure 2-1. (A and B) Male C57BL/6J mice were fed either a standard diet or a tyrosine-restricted diet for 10 weeks. The weights of the body, lean mass, fat mass, liver, kidney, heart, lung, and colon were measured. (C) The food intake was counted in C57BL/6J mice fed either a standard diet or a tyrosine-restricted diet for 10 weeks. (D) Serum levels of ALT, AST, TG, TC, CREA, CK, and LDH were determined in the indicated mice. (E) H&E staining of liver, kidney, heart, lung, and colon from the indicated mice. Scale bar 100 µm. (F) The tail suspension test was performed on the indicated mice. (n=5).\n2. Are tyrosine-restricted diets administered prior to tumour initiation, or after tumours are established? It would be important to evaluate whether dietary intervention would still be effective when tumours are already present or larger.\nResponse: We appreciate this thoughtful comment. In our study, we used hepatocyte-specific MYC overexpressing mice, a model that reliably induces early-stage hepatocellular carcinoma (HCC) lesions (2–3 mm in diameter) by 7 weeks of age in male mice, with progression to advanced-stage tumors (>1 cm) by approximately 3 months (Mei et al, 2020) (PMID: 32489910). In the original manuscript, a tyrosine-restricted diet is introduced at 6 weeks of age, prior to the tumor initiation. In the revised manuscript, at 9 weeks of age, after tumors have already developed, tyrosine-restricted diets were applied to evaluate their impact on established tumorigenesis. Results also indicated that restriction of dietary tyrosine intake (Tyr 0% diet) led to a significant decrease in characteristic hepatomegaly, liver-to-body weight ratio, tumor burdens, and diameters relative to the standard diet (Tyr 100% diet) (Response Figure 2-2, corresponding to the revised manuscript Figure S1E-1G). These findings indicate that tyrosine-restricted diets exert significant therapeutic efficacy against HCC development during tumor initiation and establishment. The related description has been added to the revised manuscript (Page 5, Lines 87-93).\nResponse Figure 2-2. (A) A diagram depicting the in vivo assessment of tumorigenesis by tyrosine in Myc/Alb-cre mice. (B) Photographs of the liver from the tumor-bearing mice fed either a normal diet or a tyrosine-supplemental diet in Myc/Alb-cre mice. (C) The body weight excluding liver weight, liver to body weight ratio, tumor number, and maximum tumor diameter of the tumor-bearing mice fed a tyrosine-modified diet were shown in Myc/Alb-cre mice (n = 6).\n3. Since phenylalanine is a precursor to tyrosine, how do the authors explain the apparent complete depletion of Tyr under ‘0% tyrosine’ conditions in vitro ( is there no tyrosine biosynthesis or is this insufficient to meet the demands of the cells)? Stable isotope tracing experiments with phenylalanine may help explain this.\nResponse: We thank the Reviewer for this great question. We apologize that the y-axis range in Figure S6K of the original manuscript may lead to misinterpretation of the data. We redraw the figure to better represent the differences, as shown in Response Figure 2-3A (corresponding to the revised manuscript Figure S11F). Based on our metabolomics results, we observed that under ‘0% tyrosine’ conditions in vitro, intracellular tyrosine levels decreased dramatically, but were still maintained at 17499 of tyrosine abundance, possibly due to phenylalanine as a precursor to tyrosine (Response Figure 2-3 A).\nAs noted by the reviewer, phenylalanine serves as a precursor to tyrosine and can be converted to tyrosine within the cell. Analysis of our metabolomics data revealed that phenylalanine levels also decreased significantly by approximately 40% after tyrosine restriction, suggesting a rise in phenylalanine consumption (average phenylalanine abundance: Tyr 100% vs Tyr 0% = 434396 vs 255198) (Response Figure 2-3 B). Furthermore, after treating cells with stable isotope-labeled phenylalanine (13C-phenylalanine) under Tyr 100% conditions or Tyr 0% conditions, we found that although the absolute amount of 13C-tyrosine was lower in the tyrosine-restricted group compared to the control group (average 13C-tyrosine abundance: Tyr 100% vs Tyr 0% = 156437 vs 17165), its relative proportion is higher under tyrosine-restricted conditions (average 13C-tyrosine percentage: Tyr 100% vs Tyr 0% = 18.85% vs 28.15%) (Response Figure 2-3 C, corresponding to the revised manuscript Figure S11G-S11H). These results collectively indicate that cellular capacity to convert phenylalanine to tyrosine is enhanced following tyrosine restriction. However, this increased conversion might still be insufficient to compensate for the consumption of tyrosine, ultimately leading to a significant decrease in intracellular tyrosine levels. A brief description of these findings has also been added to the revised manuscript (Page 13, Lines 322-326).\nResponse Figure 2-3. (A) Revised figure of tyrosine abundance in SNU398 cells cultured in control and tyrosine-restricted media in metabolomics data. (n = 3). The left image is the original manuscript, and the right image is the revised manuscript. (B) Quantification of phenylalanine abundance in SNU398 cells cultured in control and tyrosine-restricted media in metabolomics data. (n = 3). (C) Absolute intracellular tyrosine levels in SNU398 cells treated with 5 µM 13C-phenylalanine for 6 hours under control and tyrosine-restricted conditions (left). Percentage of 13C-tyrosine to total tyrosine between control and tyrosine-restricted conditions (right). (n = 3).\n4. Figure 1I-J: please include isotopologue abundances in addition to fractional enrichment in the 13C-Tyr tracing data.\nResponse: Thanks for your professional advice. We have provided the isotope abundance data for Fig. 1I-1J in the original manuscript, as shown in Response Figure 2-4 (corresponding to the revised manuscript Figure S4A-S4C).\nResponse Figure 2-4. (A) Percentage of 13C-tyrosine to total tyrosine between primary mouse hepatocytes isolated from normal liver and Myc/Alb-cre tumor. The left panel displays data in percentage, and the right panel shows isotopologue abundances. (n = 4). (B and C) The percentage of 13C-fumarate to total fumarate (top) and 13C-citrate to total citrate (bottom) between primary mouse hepatocytes isolated from normal liver and Myc/Alb-cre tumor. The left panel displays data in percentage, and the right panel shows isotopologue abundances. (n = 4).\n5. Are the observed Tyr dependencies a general feature of liver tumourigenesis, or specifically driven by MYC dysregulation? Authors mention that 11.56% of HCC patients observe MYC amplification, but the cell lines used (SNU398, SNU449, and Huh7) do not have MYC amplification. Correlating Tyr sensitivity with MYC expression would address this- does MYC KD reduce tyrosine dependency or rescue effects of tyrosine depletion?\nResponse: We appreciate this thoughtful comment. In our original manuscript, we utilized three distinct mouse HCC models: a MYC overexpression-driven HCC model, a DEN treatment-induced HCC model, and an intrahepatic injection model of human HCC cells, to validate the effect of tyrosine levels on HCC development. Based on our findings (revised manuscript Figure 1), we observed that in all three models, restricting dietary tyrosine intake significantly reduced the development of liver tumors compared to the standard diet, regardless of whether it was associated with MYC amplification. The occurrence of liver cancer induced by DEN is attributed to the formation of methylated macromolecules induced-DNA damage (Schulien & Hasselblatt, 2021) (PMID: 33785162). Moreover, in the revised manuscript, another HCC mouse model has been used to further illustrate whether tyrosine dependency is a common feature of liver tumorigenesis. Mice were injected with the plasmids of myr-AKT and NRASG12V via hydrodynamic tail vein injection to induce HCC tumorigenesis, together with feeding a tyrosine-modified diet (schematic representation provided in the Response Figure 2-5 A). The results demonstrated that tyrosine restriction also significantly attenuated the progression of AKT/NRASG12V-driven HCC (Response Figure 2-5, corresponding to the revised manuscript Figure S8B-S8D). This further supports the notion that tyrosine dependency represents a common characteristic of liver cancer. A brief description has been added to the revised manuscript (Page 9, Lines 224-231).\nFurthermore, as raised by the reviewer in this question and question 6, we found that the hepatocellular carcinoma’s dependence on tyrosine was determined by its protein synthesis activity. Specifically, tumor cells exhibiting higher protein synthesis activity show greater inhibition of cell growth upon tyrosine restriction. We measured protein synthesis activity, the expression of MYC, YARS1, and the tyrosine metabolism gene set in seven HCC cell lines and one normal hepatic cell line (THLE-2). The results revealed that the expression levels of MYC in the four tumor cell lines (SNU398, SNU449, PLCPRF5, and HCCLM3) used in our original manuscript were different. Relative to the expression levels of MYC in THLE-2, SNU449 and PLCPRF5 exhibited similar levels, whereas HCCLM3 and SNU398 showed elevated levels. Notably, these four HCC lines demonstrated higher protein synthesis activity and elevated YARS1 expression compared to normal hepatocytes (Response Figure 2-5 D, corresponding to the revised manuscript Figure S8E). Thus, these four HCC cell lines demonstrated a higher dependence on YARS1 or stronger tyrosine sensitivity, which also explains the reviewer’s comment in question 6, stating that although MYC regulates YARS1 transcription, YARS1 protein levels correlate more strongly with protein synthesis activity. A brief description has also been added to the revised manuscript (Page 9, Line 231 to Page 10, Line 239).\nFurthermore, tyrosine restriction was less effective at inhibiting cell proliferation in the cell lines with low protein synthesis activity (THLE-2 or HEPG2), compared to those with high protein synthesis activity (SNU398 or PLCPRF5) (Response Figure 2-5 E, corresponding to the revised manuscript Figure S8F). Moreover, we found in SNU449 cells with low basal protein synthesis, MYC overexpression increased protein synthesis, thereby potentiating the inhibitory effect of tyrosine restriction (the increased inhibition degree from 37% to 55%), whereas MYC knockdown in SNU398 cells with high protein synthesis activity to reduce protein synthesis activity, decreased this inhibitory effect of tyrosine restriction (the decreased inhibition degree from 63% to 51%) (Response Figure 2-5 F, corresponding to the revised manuscript Figure S8G). These results indicated that MYC overexpression increased the burden on ribosome translation, rendering the cells more susceptible to tyrosine depletion, which resulted in a greater suppression of cell growth upon tyrosine depletion. A similar phenomenon has also been observed in RNA splicing stage that MYC overexpression increases burden on the core spliceosome in human B-cell line P493-6, thus significantly improving anti-proliferative capacity upon splicing factor BUD31 knockdown (Extended Data Figure 10b) (Hsu et al, 2015) (PMID:26331541). Collectively, these results demonstrate that tyrosine dependency in HCC cells is primarily governed by global protein synthesis activity, rather than being specifically tied to MYC-driven oncogenesis. The brief description (Page 10, Lines 239-248) and discussion (Page 25, Lines 672-674) have also been added to the revised manuscript.\nResponse Figure 2-5. (A) A diagram depicting the in vivo assessment of hepatocellular carcinogenesis by tyrosine in C57BL/6J mice injected with the plasmids of myr-AKT and NRASG12V. (B) Photographs of the liver from the tumor-bearing mice fed either a standard diet or a tyrosine-restricted diet. (C) Body weight excluding liver weight, liver to body weight ratio, tumor number, and maximum tumor diameter of the tumor-bearing mice fed a tyrosine-modified diet were shown (n = 6). (D) Immunoblots showing puromycin incorporation and the expression of related proteins in the indicated cells. (E) Relative cell viability of normal liver cell line and HCC cell lines cultured in tyrosine-deficient medium compared to standard tyrosine medium (n = 3). (F) Relative cell viability of SNU449 and SNU398 cell lines cultured in tyrosine-restricted medium, together transfected with the indicated plasmids or siRNAs. (n = 3).\n6. Figure 2O-2Q show that some HCC cell lines are highly dependent on YARS1. Do these correspond to MYC-high models? Does YARS1 correlate with MYC expression levels or general translation rates?\nResponse: We appreciate the reviewer’s insightful comments. In our original manuscript Figure 2O (corresponding to the Response Figure 2-6 A), we analyzed the results from the published genome-wide HCC screen dataset within the Cancer Dependency Map (DepMap) project and found that a subset of HCC cell lines showed high YARS1 dependency. These cell lines did not correspond to MYC-high cell lines, especially SNU739 (Response Figure 2-6 B). Meanwhile, according to data from DepMap, there was no significant correlation between the expression levels of MYC and the perturbation effect score of YARS1 among all liver cancer cell lines tested, indicating that YARS1 dependency in HCC is uncoupled from MYC oncogene expression (Response Figure 2-6 C). As shown in Response Figure 2-5 D and E above, YARS1 protein levels are more closely linked to cellular protein synthesis rates than to MYC-mediated transcriptional regulation.\nResponse Figure 2-6. (A) Gene rank plot showing the dependency of YARS1 and TAT in 12 HCC cell lines from DepMap CRISPR knockout screens. TAT (red) and YARS1 (green) are highlighted. (B) The expression levels of MYC in various HCC cell lines are based on data from the DepMap project. On the left side of the dashed line are the 12 HCC cell lines corresponding to the original manuscript, and on the right side are the other four HCC cell lines. (C) Pearson correlations between MYC expression levels and perturbation effect score of YARS1 based on the DepMap project data.\n7. Is the reduction in tyrosine metabolic genes in HCC cells and tumours MYC-dependent?\nResponse: We appreciate the reviewer’s helpful comments. Analysis of HCC patient RNA data revealed that only the expression levels of TAT and FAH exhibited a significant negative correlation with MYC expression, indicating that the expression reduction of tyrosine metabolic genes was not fully dependent on MYC expression (Response Figure 2-7, corresponding to the revised manuscript Figure S7G). Similarly, as described in response Figure 2-5 D, the reduction of tyrosine metabolic genes was generally correlated with the increased protein synthesis efficiency, rather than with MYC expression in HCC cell lines. The brief description has also been added to the revised manuscript (Page 9, Lines 206-209).\nResponse Figure 2-7. Pearson correlations between tyrosine metabolic genes and MYC RNA in RNA-seq data of TCGA.\n8. If YARS1 is knocked down, can the observed mitochondrial and lipid peroxidation defects be rescued by re-expressing SCD1 or NDUFB8?\nResponse: We appreciate the reviewer's thoughtful point. SCD1, the enzyme that catalyzes the rate-limiting step in monounsaturated fatty acid synthesis, promotes lipid peroxidation when its expression is decreased (Sen et al, 2025; Tesfay et al, 2019) (PMID: 40198901, 31270077). Deficiency of NDUFB8, a core subunit of mitochondrial complex I, impairs complex I enzyme activity (Kami Reddy et al, 2024) (PMID: 39253977). New experiments with YARS1 knockdown have been conducted. We found that the lipid peroxidation levels were partially restored by re-expressing SCD1 in the YARS1 knockdown cells (Response Figure 2-8 A and B, corresponding to the revised manuscript Figure S19H-S19I) and the downregulation of mitochondrial complex I activity was reversed by expressing NDUFB8 back into YARS1 knockdown cells (Response Figure 2-8 C, corresponding to the revised manuscript Figure S19J). The related brief description has been added to the revised manuscript (Page 19, Lines 501-504).\nResponse Figure 2-8. (A and B) SNU398 cells transfected with the indicated shRNAs and constructs were treated with C11-BODIPY probe (1 μM) followed by flow analysis (A) and lipid peroxidation quantification (B). NDUFB8 plasmids were transfected into SNU398 cells together with YARS1 shRNA, and the activities of mitochondrial complex I were analyzed (n = 3).\n9. ISR Pathway : the authors make no mention to the ISR which is canonically activated in response to AA limitation via GCN2/eif2a/ATF4. This is a key mechanistic gap, especially since uncharged tRNAs are canonical activators of GCN2, several markers observed (e.g. SLC7A5, SLC7A11, oxidative stress response genes) are known ATF4 target genes, and proteins upregulated upon tyrosine deprivation are clustered in hallmarks that are common to amino acid restriction (autophagy, L-amino acid transport etc). The ISR could influence lipid metabolism and ferroptosis, potentially confounding the attribution to SCD1 downregulation. Have the authors assessed ISR activation in response to tyrosine depletion or YARS1 KD? This pathway should be acknowledged.\nResponse: We genuinely appreciate your insightful comment. As described by the reviewer, GCN2 is a key cellular sensor of amino acid deprivation. When amino acid availability becomes scarce, GCN2 kinase is activated by direct binding to uncharged tRNAs. Then, GCN2 promotes restoration of amino acid levels by up-regulating ATF4 target genes involved in amino acid biosynthesis and transport (Costa-Mattioli & Walter, 2020; Malnassy et al, 2024) (PMID: 32327570, 38768690). We found that there was not associated with any sign of integrated stress response (ISR) after tyrosine deprivation or YARS1 knockdown for 48h in SNU398 cells (Response Figure 2-9 A), which was also observed in threonine restriction in glioblastoma stem cells (Figure 5i) (Wu et al, 2024) (PMID: 38519786) or VARS knockdown in melanoma cells (Extended Data Figure 5b) (El-Hachem et al, 2024) (PMID: 38849541). However, upon prolonging tyrosine restriction or YARS1 knockdown to 72h, a time point used in our original manuscript to detect the change of transcriptomic and proteomic after tyrosine translation limitation, we observed significant activation of the GCN2-eIF2α-ATF4 axis, as shown by increased phosphorylation levels of GCN2 and eIF2α, and elevated protein levels of ATF4, indicating that integrated stress response is activated to respond to tyrosine translation limitation and reestablish physiological homeostasis (Response Figure 2-9 B, corresponding to the revised manuscript Figure S11E). A brief description has been added to the revised manuscript (Page 12, Lines 317-321).\nThe Integrated Stress Response (ISR) is characterized by the upregulation and activation of ATF4. This response elicits a dichotomous functional outcome: low-level or short-term activation promotes cell survival, whereas prolonged or intense activation drives cell death (Tang et al, 2024) (Wortel et al, 2017) (PMID: 38383612, 28797581). ATF4 directs these opposing cellular fates by regulating a broad set of target genes through complex mechanisms operating at transcriptional, translational, and post-translational levels, and via interactions with other transcription factors. Especially, when considering its involvement in ferroptosis, the ATF4 pathway can either inhibit or promote ferroptosis. Several target genes of ATF4, including HSPA5, SLC7A11, and NUPR1, act as negative regulators of ferroptosis. Conversely, other ATF4 target genes, such as BTG1, DDIT3, CHAC1, and SLC1A5, positively regulate ferroptosis (Tang et al., 2024) (PMID: 38383612). This intricate relationship underscores the complexity of cellular responses to varying stress levels. Thus, although ATF4 serves as a common mediator, the ultimate transcriptional and physiological outcome is determined by the specific cellular context, stress type, and duration of stimulation.\nIn this study, we found that tyrosine restriction activated the ISR, as evidenced by the upregulation of ATF4 expression (Response Figure 2-9 B, corresponding to the revised manuscript Figure S11E). Consistent with the model that ATF4 target gene activation depends on stress severity, cellular context, and stimulus duration, our transcriptomic analysis identified a set of genes induced by ATF4 under this condition. Among these, canonical anti-ferroptotic genes such as SLC7A11 and NUPR1 were upregulated, along with several pro-ferroptotic genes, including BTG1, DDIT3 and CHAC1 (Response Figure 2-9 C). This co-activation of antagonistic target genes indicates that the ISR may play a dual role in mediating cellular responses to tyrosine restriction.\nResponse Figure 2-9. (A and B) Analysis of GCN2-eIF2α-ATF4 signaling cascade in SNU398 cells cultured in tyrosine-modified mediums or transfected with YARS1 shRNA at 48 h (A) or 72 h (B). (C) Transcriptomics data analysis of ATF4 target gene expression in SNU398 cells cultured in tyrosine-modified mediums (n = 3).\n10. Fatty acid metabolism and link to ferroptosis: fatty acid composition is known to change under metabolic stress or ISR activation. Can the authors uncouple the effects of tyrosine depletion on MUFA/PUFA balance from its protenogenic role in SCD1 synthesis? Would MUFA supplementation rescue ferroptosis induced by tyrosine depletion, MYC KD, or YARS1 KD? Does SCD1 KD alone recapitulate the lipid peroxidation phenotypes?\nResponse: Thanks for your professional advice. As a rate-limiting enzyme for monounsaturated fatty acid (MUFA) biosynthesis, SCD1 reduction or inhibition promotes a shift from MUFAs to PUFAs in cellular lipid composition and induces ferroptosis (Bogie et al, 2020; Ding et al, 2023; Glowacka et al, 2024; Schwab et al, 2024; Thurmer et al, 2022; Zhao et al, 2022) (PMID: 32097464, 37805657, 39572570, 39009641, 35624087, 36197994). In high-ZEB1-expressing cancer cells, ZEB1 knockdown represses the expression of enzymes important for MUFA biosynthesis (including SCD1 and FASN), thereby significantly altering the ratio of PUFA/MUFA and inducing ferroptosis (Figure 2c) (Schwab et al., 2024) (PMID: 39009641). In FaDu cancer cells, SCD1 inhibition causes a 3-fold reduction in MUFA levels, and the PUFA/MUFA ratio increases substantially more in the presence of SCD1 inhibitors (Figure 5h-5j) (Glowacka et al., 2024) (PMID: 39572570). Thus, in our original manuscript, we proposed that tyrosine restriction suppressed SCD1 translation in a codon-dependent manner, leading to an imbalance in MUFA/PUFA. Furthermore, as noted by the reviewers, the impact of tyrosine deprivation on the MUFA/PUFA balance may also be mediated through the activation of ISR. Previous study has found that ISR activation significantly alters cellular lipid composition, particularly leading to significant accumulation of PUFAs containing at least three double bonds (20:4, 22:4, 22:5, 24:6) (Supplementary Fig.7f, 7g) (Labbe et al, 2024) (PMID: 39333061). Thus, based on the results from response Figure 2-9 B, i.e., induced ISR activation upon tyrosine deprivation, we propose that the altered intracellular MUFA/PUFA balance may be attributed to a dual mechanism: (i) tyrosine-mediated translation regulation of SCD1, and (ii) ISR activation-driven remodeling of lipid composition under tyrosine restriction. The brief description has also been added to the revised manuscript (Page 13, Lines 334-336).\nSCD1 catalyzes the desaturation of saturated fatty acids, principally stearic acid (18:0) and palmitic acid (16:0), to their Δ9-monounsaturated counterparts, oleic acid (18:1) and palmitoleic acid (16:1) (Thurmer et al., 2022) (PMID: 35624087). Previous studies have found that ferroptosis induced by MUFA deficiency due to SCD1 knockdown can be rescued by MUFA supplementation (Sokol et al, 2025; Zhao et al., 2022) (PMID: 39442523, 36197994). Similarly, we demonstrated that supplementation with oleic acid and palmitoleic acid (hereafter referred to as MUFA) effectively alleviated ferroptosis triggered by tyrosine restriction, YARS1 knockdown, or MYC knockdown, as evidenced by decreased lipid peroxidation levels (Response Figure 2-10 A-C, corresponding to the revised manuscript Figure S19K-S19M). Furthermore, SCD1 knockdown resulted in increased lipid peroxidation (Response Figure 2-10 D, corresponding to the revised manuscript Figure S19N). Thus, these findings suggest that restricting tyrosine availability induces ferroptosis by disrupting the MUFA/PUFA balance, whereas MUFA supplementation significantly alleviates it. The brief description has also been added to the revised manuscript (Page 19, Lines 505-509).\nResponse Figure 2-10. BODIPY493/503 C11 staining in SNU398 cells with the indicated treatment. (A) tyrosine deprivation combined with MUFA treatment, (B) YARS1 knockdown combined with MUFA treatment, (C) MYC knockdown combined with MUFA treatment, (D) SCD1 knockdown. (n = 3).\n11. Figure S1L/S1N and S1A/S1C: Does the proliferation increase with tyrosine supplementation correlate with increased protein expression of SCD1 and NDUFB8?\nResponse: We appreciate this thoughtful comment. The protein levels of SCD1 and NDUFB8 in the samples from Figures S1L/S1N and S1A and S1C of the original manuscript were determined, and the results have been given in the revised manuscript (Figures S14C and S14D). We found that tyrosine supplementation could increase the protein expression of SCD1 and NDUFB8 in vitro and in vivo (Response Figure 2-11, corresponding to the revised manuscript Figure S14C and S14D). A brief description has been added to the revised manuscript (Page 14, Lines 378-380).\nResponse Figure 2-11. (A) SDS-PAGE and immunoblot analysis of protein expression from SNU398 cells cultured in tyrosine-supplemented medium or normal medium for 48 h. (B) SDS-PAGE and immunoblot analysis of liver protein expression from mice fed a tyrosine-modified diet.\n12. Figure 1I: the 12-hour labelling time is relatively long to assess amino acid uptake. The increase in M+6 Tyr could be due to decreased catabolism rather than increased uptake. Use of transporter inhibition (eg. JPH203 for SLC7A5) or transporter KD would clarify this mechanism.\nResponse: Thanks for your professional advice. In our original manuscript, we used two methods to validate the improved tyrosine uptake capacity of liver tumors compared to normal tissues. First, using an ex vivo assay where tissues were treated with 3H-tyrosine for 1 hour, we observed significantly higher tyrosine uptake in tumor tissues compared to normal tissues (Figure 1H of the revised manuscript). Second, as detailed in the original manuscript Figure 1I (current in the revised manuscript Figure S4A), primary hepatocytes were treated with 13C-tyrosine to examine the differences in tyrosine uptake between tumor cells and normal hepatocytes. Furthermore, as suggested by the reviewers, we conducted new experiments using the SLC7A5 transporter inhibitor JPH203. This treatment resulted in a significant reduction in tyrosine uptake in liver cancer cells, further corroborating the upregulation of tyrosine uptake in HCC (Response Figure 2-12, corresponding to the revised manuscript Figure S4I). A brief description has been added to the revised manuscript (Page 6, Line 144 to Page 7, Line 147).\nResponse Figure 2-12. Primary mouse hepatocytes isolated from normal liver and Myc/Alb-cre tumor were treated with JPH203 (1 μM) for 12 h, followed by 13C-tyrosine (5 μM) treatment for 3 h. The abundance of 13C-tyrosine and total tyrosine was analyzed (n = 3).\n13. Figure 1C: tumour size negatively correlates with Tyr concentration. Can authors measure tyrosine levels in tumour interstitial fluid to confirm that this doesn’t reflect local tyrosine availability?\nResponse: We appreciate the reviewer’s helpful comments. We isolated interstitial fluid from liver tumors of different sizes to measure tyrosine concentration. The results showed no significant correlation between tumor sizes and tyrosine levels in the tumor interstitial fluid, indicating that tumor size did not affect local tyrosine availability (Response Figure 2-13, corresponding to the revised manuscript Figure S1A). A brief description has been added to the revised manuscript (Page 4, Lines 70-74).\nResponse Figure 2-13. Pearson correlation between liver tumor diameters and tyrosine levels in interstitial fluid of Myc/Alb-cre mice (n = 10).\n14. Line 70-71: The statement that “low levels of tyr favour liver tumourigenesis” seems contradictory given that later data show increased tyrosine uptake and that tyrosine supplementation boosts HCC proliferation. Should reframe to clarify that tumours have an increased requirement for tyrosine.\nResponse: Thank you for the reviewer’s kind reminder. We have corrected this sentence (“high levels of tyrosine favor liver tumorigenesis”) in the revised manuscript (Page 4, Lines 73-74).\n15. Figure 2B/2C, Lines 126-128: The enrichment of tyrosine codons in translationally upregulated proteins may reflect general increases in protein synthesis. Would this not also be true for other amino acids? Is this increased utilization of tyrosine for protein synthesis tyrosine-specific or a global phenomenon associated with tumour progression?\nResponse: Thanks for this important question. As highlighted by the reviewer, in our original manuscript, we demonstrated that both tyrosine uptake and its incorporation ratio into proteins are significantly higher in HCC tissues compared to normal liver tissues by using an ex vivo isotopic tracer method (Figure 2B and 2C in the current revised manuscript). To investigate whether this is attributed to increased protein synthesis in tumors, we performed an in-depth analysis of amino acid and codon enrichment in proteins with translation upregulated and downregulated in HCC patients (Response 2-14 A, corresponding to the revised manuscript Figure 2H). This analysis revealed that the enrichment levels of only a subset of amino acids and their corresponding cognate codons were elevated (e.g., lysine and tyrosine) within HCC tissue, while others were reduced (e.g., alanine). This indicates that although protein synthesis generally increases during HCC progression, the utilization of some, but not all, amino acids increase; in some cases, it even decreases. This phenomenon has also been observed in melanoma, leukemia, and breast cancer. Specifically, the translational utilization of valine is notably increased in melanoma and leukemia, thereby facilitating mitochondrial oxidative respiration and fatty acid oxidation (El-Hachem et al., 2024; Thandapani et al, 2022) (PMID: 38849541, 34937946). In contrast, in breast cancer, translational utilization of leucine is significantly suppressed, thereby inhibiting the translation of growth-suppressive genes (Passarelli et al, 2022) (PMID: 35288656). These findings suggest that during tumor progression, there is an increased translational utilization of specific amino acids to enhance protein synthesis.\nMoreover, to further identify that the increased translational utilization of tyrosine is a specific feature of liver tumor progression, we compared the uptake differences of tyrosine, lysine, and alanine between tumor tissues and normal tissues. The results showed that while the uptake rates of both tyrosine and lysine were significantly elevated in tumor tissues compared to normal tissues (Response Figure 2-14 B up, corresponding to the revised manuscript Figure S6G), only tyrosine exhibited a significantly higher incorporation ratio into protein synthesis within HCC (Response Figure 2-14 B bottom, corresponding to the revised manuscript Figure S6G). We found that YARS1 and its cognate isoacceptor tRNA-TyrGUA were significantly upregulated in tumors. In contrast, KARS1 (lysine-tRNA ligase) and AARS1 (alanine-tRNA synthetase), responsible for charging lysine and alanine, respectively, were markedly downregulated in tumor tissues compared to normal tissues (Response Figure 2-10 C, corresponding to the revised manuscript Figure S6H). Correspondingly, the levels of tRNA-LysCUU showed a significant decrease, and the levels of tRNA-Ala remained unchanged. These results suggest that enhanced amino acid uptake, coupled with elevated levels of aminoacyl-tRNA synthetases and their cognate tRNAs, is essential for supporting the increased translational utilization of amino acids in tumors (Response Figure 2-10 D, corresponding to the revised manuscript Figure S6I). Collectively, these results demonstrate that the increased consumption of tyrosine for protein synthesis is a key metabolic vulnerability driving liver cancer progression. A brief description has been added to the revised manuscript (Page 8, Lines 177-189).\nResponse Figure 2-14. (A) Compared with normal liver tissues, a graph representing gene levels detected by RNA sequencing (y-axis) and proteomics (x-axis) of HCC tissues. Genes with red dots represent translation upregulation, and genes with blue dots represent translation downregulation in HCC. Genes that met the cut-off criteria (p<0.05, -0.5<log2FC (x-axis)<0.5 and -1<log2FC (y-axis)<1). (B) Relative 3H-amino acids uptake into normal liver and Myc/Alb-cre tumor (up). Percentage of 3H-amino acids in protein to 3H-amino acids uptake in normal liver and tumor tissues (n = 6). (C) The protein expression of aminoacyl-tRNA synthetases in the CPTAC-LIHC database. (D) The RNA levels of the indicated tRNA in matched HCC tissues and normal liver tissues were measured by RT-qPCR (n = 15).\n16. In Figure 3 the effect of the tyrosine-deficient diet on specific proteins is evaluated in tumour cell lines and is also shown for tumours. Are those effects tumour-specific, i.e. are the levels of SCD1 and NDUF8 affected by Tyr-deficient diet in the adjacent liver tissue of tumour-bearing mice? They do have tissues so would be important to see of NDUF8 and SCD1 are also affected in normal livers.\nResponse: Thank you for highlighting this. As detailed in our responses to Reviewer’s questions 5 and 6, tyrosine restriction exerted greater inhibitory effects on tumor cells with high protein synthesis activity than on normal cells exhibiting low protein synthesis activity. Similarly, we observed minimal impact on NDUFB8 and SCD1 protein levels in adjacent normal liver tissues of tumor-bearing mice upon tyrosine restriction, as shown in Response Figure 2-15 (corresponding to the revised manuscript Figure S14E). A related brief description has been added to the revised manuscript (Page 14, Line 380 to Page 15, Line 382).\nResponse Figure 2-15. SDS-PAGE analysis of the adjacent normal liver tissues from tumor-bearing mice fed a tyrosine-modified diet.\n17. Would the expression of NDUF8 and SCD1 proteins also be affected if any other amino acids are depleted?\nResponse: We appreciate the reviewer’s comments. Our analysis of the amino acid composition profiles across the entire proteome revealed that the tyrosine content of NDUFB8 and SCD1 ranks in the top 10 percentiles (102/19110 and 251/19110, respectively) (Response Figure 2-16 A). Additionally, we selected tryptophan (the content of the two proteins ranks in the top 10 percentiles similarly to tyrosine (282/19110 and 1148/19110)) and serine (its content in these two proteins ranks in a much lower percentile (18551/19110 and 13967/19110) (Response Figure 2-16 A, corresponding to the revised manuscript Figure S14F), to investigate the impact of their deprivation on NDUFB8 and SCD1 expression. Tyrosine deprivation induced a significantly greater reduction in protein levels than tryptophan deprivation, while serine deprivation showed no significant impact on these two protein levels (Response Figure 2-16 B, corresponding to the revised manuscript Figure S14G), indicating that tyrosine availability exerts more profound translational control than the availability of tryptophan and serine in liver cancer. A brief description has been added to the revised manuscript (Page 15, Lines 382-389).\nResponse Figure 2-16. (A) The frequencies of tyrosine (left), tryptophan (medium), and serine (right) in the coding sequence (CDS) sorted from high to low. (B) SDS-PAGE analysis of SNU398 (left) or SNU449 (right) cells cultured in amino acid-modified medium for 48 h.\n18. The increase in PUFA levels upon tyrosine deprivation is surprising. Do authors have a plausible explanation?\nResponse: We propose that the elevation of PUFA levels following tyrosine deprivation may be attributed to the following mechanisms. First, previous studies have found that SCD1 catalyzes the formation of MUFAs from SFA acylCoA. Inhibiting SCD1 reduces the content of MUFA and increases the content of PUFA, which can provide a corresponding substrate for fatty acid oxidation (Sen et al, 2023; Tesfay et al., 2019) (PMID: 37029018, 31270077). Moreover, a previous study also showed that cells increase uptake of extracellular lysophospholipids to supplement cellular unsaturated fatty acids in response to SCD1 inhibition (Kamphorst et al.(Kamphorst et al, 2013) (PMID: 23671091). Our study also found that tyrosine deprivation led to an enrichment in the upregulation of the lipid digestion/absorption pathway, as indicated by our proteomics data (Response Figure 2-17). Second, as mentioned in question 10, a previous study has found that ISR activation significantly alters cellular lipid composition, particularly leading to a significant accumulation of PUFAs containing at least three double bonds (20:4, 22:4, 22:5, 24:6)(Labbe et al., 2024) (PMID: 39333061). Our results also found that tyrosine deprivation induces ISR activation (Response Figure 2-9 B). Therefore, the elevation of intracellular PUFA following tyrosine deprivation may be attributed to alterations in fatty acid synthesis due to downregulation of SCD1, as well as elevation of extracellular fatty acid uptake upon SCD1 reduction, and ISR activation-induced PUFA accumulation. A brief description has been added to the revised manuscript (Page 13, Lines 334-336).\nResponse Figure 2-17. KEGG enrichment analysis of differentially expressed proteins under the tyrosine deprivation condition of SNU398 cells. (n = 3).\n19. Were tyrosine levels measured with FjTAL treatment?\nResponse: We really appreciate the reviewer’s comments. As shown in Response Figure 2-18 (corresponding to the revised manuscript Figure S21O), the amino acid profile of FjTAL-treated liver tissue at a dosage of 50 mg/kg revealed the most pronounced and the longest-lasting reduction in tyrosine. In contrast, the other amino acids showed little change after FjTAL treatment. A brief description has been added to the revised manuscript (Page 20, Lines 550-555).\nResponse Figure 2-18. Amino acid profile of FjTAL-treated livers compared to vehicle-treated livers. (n = 2).\nGeneral comment: a lot of panels should be moved to supplemental or additional information to make main figures less crowded and the main points more concise.\nResponse: Thanks a lot for the reviewer’s kind reminder. We have moved some panels from the original figures to the supplementary figures to ensure the main figures are more concise.\nReviewer #3 (Remarks to the Author):\nI co-reviewed this manuscript with one of the reviewers who provided the listed reports. This is part of the Nature Communications initiative to facilitate training in peer review and to provide appropriate recognition for Early Career Researchers who co-review manuscripts.\nResponse: We sincerely appreciate your thorough review and detailed comments on our manuscript.\nReviewer #4 (Remarks to the Author); expert in ferroptosis:\nThis study explores hepatocellular carcinoma's metabolic plasticity, focusing on how HCC cells reprogram tyrosine uptake and use to promote translation rather than catabolism. It presents extensive data integrating metabolomics, transcriptomics, proteomics, ribosome profiling, CRISPR screening, and in vivo models. The idea that tyrosine translation availability (RTTA) is a vulnerability in HCC and can be targeted is potentialy clinically relevant. The concepts appear to be novel, however, despite the comprehensive data, several weaknesses diminish the mechanistic insights and translational impact.\nResponse: We sincerely appreciate your thorough review and detailed comments on our manuscript. As suggested, we have provided a point-by-point response to Reviewer #4’s comments below.\nMajor Concerns\n1. The genome-wide CRISPR screen is used as a central aspect to identify synthetic vulnerabilities in the RTTA context. However, the changes observed are modest, and the study subsequently relies largely on pharmacological inhibitors (e.g., venetoclax, RSL3, erastin, sorafenib) to support claims. The reliance on small-molecule inhibitors with pleiotropic effects makes it difficult to attribute synergy specifically to RTTA-related pathways. As such, validation using genetic loss-of-functon (knockout/knockdown) models for key hits (e.g., GPX4, SLC7A11, BCL2) is essential. Rescue experiments with ferroptosis inhibitors (e.g., ferrostatin-1, β-mercaptoethanol) would help confirm the ferroptotic mechanism.\nResponse: Thank you for your great and constructive suggestions. The moderate change observed in our screening results may be attributed to the short duration of stress induction (tyrosine deprivation). Therefore, in accordance with your constructive suggestion, we combined genetic knockdown with tyrosine restriction in tumor cells. As shown in Response Figure 4-1 A-F (corresponding to the revised manuscript Figure S17A-S17F), knockdown of key genes (GPX4 knockdown in Response Figure 4-1 A and B; SLC7A11 knockdown in Response Figure 4-1 C and D; BCL2 knockdown in Response Figure 4-1 E and F) enhanced the therapeutic efficacy of tyrosine restriction, validating that the synergistic antitumor effects between tyrosine translational restriction and our screening results. A brief description has been added to the revised manuscript (Page 17, Lines 456-459).\nFurthermore, to confirm that restricting tyrosine translation availability suppresses tumorigenesis through inducing ferroptosis, rescue experiments were performed both in vitro and in vivo. Treatment with ferroptosis inhibitor (Fer-1) significantly reversed the reduction of cell proliferation caused by tyrosine deprivation or YARS1 knockdown (Response Figure 4-1 G and H, corresponding to the revised manuscript Figure S18C-S18D), and mitigated YARS1 knockdown-induced tumor regression (Response Figure 4-1 I-K, corresponding to the revised manuscript Figure S18E-S18G). These findings collectively confirm that restricting tyrosine translation availability triggers tumor cell ferroptosis. A brief description has been added to the revised manuscript (Page 18, Lines 473-479).\nResponse Figure 4-1. (A to F) The combination of tyrosine deprivation or YARS1 knockdown with GPX4 (A and B), SLC7A11 (C and D), and BCL2 (E and F) depletion reduced the cell viability of HCC cell lines (n = 3). (G and H) Fer-1 treatment rescued the reduction of proliferation caused by tyrosine restriction (G) and YARS1 knockdown (H) in HCC cells (n = 3). (I to K) Fer-1 treatment in YARS1 knockdown cells rescued tumor growth (n=6 per group). Tumor photograph (I), tumor volumes (J), and tumor weight (K).\n2. Sorafenib is a multi-kinase inhibitor with broad targets beyond ferroptosis. Venetoclax also has complex effects on apoptosis. Without genetic proof, the observed synergy between tyrosine restriction and these agents may reflect unrelated drug effects rather than specific mechanistic interactions with RTTA. For this, it would be relevant to include in vivo experiments with genetically defined ferroptosis-sensitive models, such as Xct (SLC7A11) or GPX4 deficient cells (important to note that these cells cannot growth in vitro without β-mercaptoethanol or ferrostatin-1 respectively – but in the presence of these agent knockout cells can be generate and implanted in vivo). These experiments would provide strong mechanistic validation that RTTA acts via ferroptosis.\nResponse: We thank the Reviewer for this insightful question and valuable advice on the experiments. As suggested by the reviewers, knockdown of GPX4 or BCL2 in YARS1-knockdown tumor cells showed a synergistic therapeutic effect, characterized by a reduced tumor volume (Response Figure 4-2, corresponding to the revised manuscript Figure S18A-S18B), thereby validating that restricting tyrosine translation availability, combined with ferroptosis-induced or apoptosis-induced models, holds remarkable synergistic therapeutic efficacy in suppressing hepatocellular carcinogenesis. A brief description has been added to the revised manuscript (Page 17, Line 468 to Page 18, Line 472).\nResponse Figure 4-2. Knockdown of GPX4 or BCL2 in YARS1 knockdown cells reduced tumor growth (n=6 per group). Tumor photograph (A) and tumor volumes (B).\n3. The study convincingly shows reduced tyrosine metabolism and increased translation, but the direct causality between MYC → YARS1 → translation of ETC components and ferroptosis is not fully established. Would experiments using codon-recoding of NDUFB8/SCD1 reduce tyrosine dependence? This experiments while challenging could strengthen the link between codon usage bias and ferroptotic outcomes.\nResponse: We appreciate the reviewer’s helpful comments. To establish the direct causality between MYC-YARS1- translation of ETC components and ferroptosis, we first examined electron transport chain complex function and ferroptosis upon MYC knockdown. As shown in the Response Figure 4-3 A-G (corresponding to the revised manuscript Figure S19A-S19G), MYC depletion reduced the expression of YARS1, NDUFB8, and SCD1 (Response Figure 4-3 A), thereby inhibiting mitochondrial complex I enzyme activity (Response Figure 4-3 B) and promoting lipid peroxidation (Response Figure 4-3 C and D). Subsequently, we investigated whether YARS1 overexpression could rescue the defective effects in MYC-knockdown cells. Results demonstrated that YARS1 overexpression effectively improved the impaired mitochondrial complex I function induced by MYC deficiency (Response Figure 4-3 E), while alleviating MYC knockdown-induced elevation in lipid peroxidation (Response Figure 4-3 F and G). Collectively, these findings indicate that MYC facilitates the translation of NDUFB8 and SCD1 by enhancing YARS1 transcription, thereby promoting mitochondrial complex assembly and ferroptosis resistance. The related description has been added to the revised manuscript (Page 18, Line 491 to Page 19, Line 501).\nAs suggested by the reviewer, to test the specificity of NDUFB8/SCD1 codon-coding, we first had mutated TAC to TAT in the reporter constructs, as shown in the schematic diagram (Response Figure 4-3 H, corresponding to the revised manuscript Figure S13C). Compared to transfection with WT reporter constructs for NDUFB8 or SCD1, the relative luciferase activities in SNU398 cells transfected with MUT reporter constructs were increased under tyrosine free or YARS1 knockdown conditions (Response Figure 4-3 I and J, corresponding to the revised manuscript Figure S13D-S13E), indicating that restricting tyrosine translation availability had a greater translation inhibition effect on TAC-rich transcripts than TAT-rich transcripts. Next, we found that compared to overexpression of WT plasmids for NDUFB8 or SCD1, overexpression of MUT plasmids (TAC→TAT) for NDUFB8 or SCD1 effectively improved the impaired mitochondrial complex I function induced by tyrosine restriction (Response Figure 4-3 K, corresponding to the revised manuscript Figure S13F), and alleviated tyrosine restriction-induced elevation in lipid peroxidation (Response Figure 4-3 L and M, corresponding to the revised manuscript Figure S13G-S13H). The related description has been added to the revised manuscript (Page 14, Lines 355-365). These results demonstrate that restricting tyrosine translational availability suppresses mitochondrial complex I activity and induces lipid peroxidation in a manner dependent on codon-specific translational repression of NDUFB8 and SCD1 proteins.\nResponse Figure 4-3. (A) SDS-PAGE analysis of protein expression after MYC depletion in SNU398 cells. (B) The activities of mitochondrial complex I-V of SNU398 cells after MYC depletion (n = 3). (C and D) BODIPY493/503 staining in SNU398 cells after MYC depletion (C). Quantification of lipid peroxidation (D) upon MYC depletion (n = 3). (E) The activities of mitochondrial complex I of SNU398 cells transfected with MYC shRNA, together with YARS1 overexpression (n = 3). (F and G) BODIPY493/503 staining in SNU398 cells transfected with MYC shRNA, together with YARS1 overexpression (F). Quantification of lipid peroxidation (G) (n = 3). (H) Graphic illustration of the indicated reporter expressing luciferase infusion with either SCD1 or NDUFB8 with a different TAC codon frequency. RLuc serves as an internal control. (I and J) Relative luciferase activities in SNU398 cells transfected with the indicated reporters and cultured in tyrosine-modified mediums (I) or relative luciferase activities in SNU398 cells transfected with the indicated reporters together with YARS1 shRNA (J). Quantification of luciferase activities normalized to Renilla luciferase activities (n = 3). (K to M) The activities of mitochondrial complex I (K) and BODIPY493/503 staining (L) of SNU398 cells cultured in tyrosine-modified mediums, together with the indicated overexpression vectors. Quantification of lipid peroxidation (M) (n = 3).\nMinor Concerns\n1. The dietary intervention (TR diet) is intriguing, but patient feasibility is uncertain. A discussion of nutritional safety, systemic effects, and whether restriction selectively affects tumor cells versus normal hepatocytes is necessary.\nResponse: We thank the reviewer for raising this critical point regarding the systemic effects of tyrosine deprivation. In response to this question, we conducted a dedicated study in healthy, wild-type mice fed a diet deficient in tyrosine. Our results indicate that the 10-week tyrosine-deficient diet induces an increase in total body weight and fat mass, along with increased liver weight (Response Figure 2-1 A and B, corresponding to the revised manuscript Figure S3A and S3B). No significant differences were observed in the weight of other organs or in daily food intake (Response Figure 2-1 B and C, corresponding to the revised manuscript Figure S3B and S3C). Concurrently, the levels of alanine aminotransferase (ALT), aspartate aminotransferase (AST), triglyceride (TG), total cholesterol (TC), creatinine (CREA), creatine kinase (CK), and lactate dehydrogenase (LDH), established biomarkers for liver, kidney, and myocardial injury, were measured. Tyrosine-deficient diets increase serum ALT, TC, and TG levels, accompanied by lipid droplet accumulation, partially consistent with the previous report (Sano et al., 2021) (PMID: 33724516), whereas no pathological changes or tissue injury were observed in other organs (Response Figure 2-1 D, corresponding to the revised manuscript Figure S3D; Response Figure 2-1 E, corresponding to the revised manuscript Figure S3E). We did not observe significant differences between the two diet groups during the short-term intervention period in WT mice (2-week or 4-week feeding). The related description has been added to the revised manuscript (Page 5, Line 102 to Page 6, Line 115).\nMoreover, given tyrosine’s role as a dopamine precursor, we evaluated depression-like behaviors using the tail suspension test (TST), a method for assessing depressive states in mice. No significant behavioral differences were observed between the two diet groups after 10 weeks of intervention (Response Figure 2-1 F, corresponding to the revised manuscript Figure S3F). It was noted that an 8-month tyrosine-deficient diet in our original DEN-induced HCC model resulted in some hair appearing grayish white, due to tyrosine acting as a precursor for melanin (Data not shown). However, short-term dietary restriction did not alter hair color. Notably, another study finds that tyrosine restriction extends lifespan in Drosophila by activating FOXO pathway, demonstrating the multifaceted effects of tyrosine-restricted diets on physiological processes in a context-dependent manner (Kosakamoto et al., 2024) (PMID: 39213345).\nTherefore, for tyrosine restriction diets, it might be safe to apply them intermittently for HCC treatment. Clinical application of tyrosine restriction diets also requires optimization of the intervention time to leverage potential anti-tumor effects while minimizing adverse outcomes. The related description (Page 6, Lines 115-121) and discussion (Page 25, Lines 663-680) have been added to the revised manuscript.\nResponse Figure 4-4. (A and B) Male C57BL/6J mice fed either a standard diet or a tyrosine-restricted diet for 10 weeks. The weight of the body, lean mass, fat mass, liver, kidney, heart, lung, and colon were measured. (C) The food intake was counted in C57BL/6J mice fed either a standard diet or a tyrosine-restricted diet for 10 weeks. (D) Serum levels of ALT, AST, TG, TC, CREA, CK, and LDH were determined in the indicated mice. (E) H&E staining of liver, kidney, heart, lung, and colon from the indicated mice. Scale bar 100 µm. (F) Tail suspension test was performed on the indicated mice (n=5).\nAs mentioned by the reviewer, we found that hepatocellular carcinoma’s dependence on tyrosine was determined by its protein synthesis activity. Specifically, tumor cells exhibiting higher protein synthesis activity showed greater inhibition of cell growth upon tyrosine restriction. We measured protein synthesis activity, the expression of MYC, YARS1, and the tyrosine metabolism gene set in seven HCC cell lines and one normal hepatic cell line (THLE-2). The results revealed that HCC lines demonstrated higher protein synthesis activity and elevated YARS1 expression compared to normal hepatocytes (Response Figure 4-5 A, corresponding to the revised manuscript Figure S8E). Thus, these HCC cell lines showed a high dependence on YARS1 or stronger tyrosine sensitivity. Furthermore, tyrosine deprivation was less effective at inhibiting cell proliferation of the cell lines with low protein synthesis activity (THLE-2 or HEPG2), compared to those with high protein synthesis activity (SNU398 or PLCPRF5) (Response Figure 4-5 B, corresponding to the revised manuscript Figure S8F). Collectively, these results demonstrate that tyrosine restriction is more sensitive to tumor cells compared to normal cells. The brief description (Page 9, Line 231 to Page 10, Line 241) and discussion (Page 25, Lines 672-674) have also been added to the revised manuscript.\nResponse Figure 4-5. (A) Immunoblots showing puromycin incorporation and the expression of related proteins in the indicated cells. (B) Relative cell viability of normal liver cell line and HCC cell lines cultured in tyrosine-deficient medium compared to standard tyrosine medium (n = 3).\n2. Tyrosinol and TAL enzyme approaches are promising, but off-target metabolic effects remain underexplored. More profiling of systemic amino acid metabolism would be important before translational claims.\nResponse: We appreciate this thoughtful comment. To elucidate the impact of FjTAL treatment on amino acid metabolism in vivo, we administered a single intraperitoneal injection of different doses of FjTAL into tumor-bearing Myc/Alb-cre mice (n=2 each). In the amino acid profile of FjTAL-treated liver tissue at a dosage of 50 mg/kg, tyrosine was the most significantly and persistently reduced amino acid (Response Figure 4-6 A, corresponding to the revised manuscript Figure S21O). The related description has been added to the revised manuscript (Page 20, Lines 550-555).\nMoreover, we detected the amino acid profiling in liver tissues from Myc/Alb-cre mice treated with tyrosinol. The results demonstrated that tyrosinol treatment had minimal effects on hepatic amino acid levels compared to the control group (Response Figure 4-6 B, corresponding to the revised manuscript Figure S22B). Therefore, these findings indicate that neither TAL nor tyrosinol treatment significantly alters the metabolism of other amino acids. The related description has been added to the revised manuscript (Page 21, Lines 583-585).\nResponse Figure 4-6. (A) Amino acid profile of FjTAL-treated livers compared to vehicle-treated livers (n = 2). (A) Amino acid profile of Tyrosinol-treated livers compared to vehicle-treated livers (n = 5).\n3. Figures: Several panels are highly data-dense. Consider streamlining or moving supportive proteomic/transcriptomic heatmaps to Supplementary Figures.\nResponse: Thank you for the reviewer’s kind reminder. We have moved some panels from the original figures to the supplementary figures to ensure the main figures are more concise.\nReviewer #5 (Remarks to the Author); expert in mitochondria:\nThe manuscript titled “Targeting tRNA-dependent tyrosine usage unveils a metabolic vulnerability in hepatocellular carcinoma” described tyrosine charging to tRNA and its subsequent utilization for protein translation as a metabolic dependency for the tumorigenesis of HCC and demonstrated that limiting the availability of tyrosine for translation attenuates tumorigenesis. Specifically, the authors reported that free tyrosine levels are significantly reduced in human and mouse HCC tumors compared to normal tissues and that this reduction in tyrosine levels is attributed to MYC-dependent increased tyrosine charging to form tRNA-TyrGUA, which is needed for protein translation.\nTo demonstrate the dependence of HCC on the availability of tyrosine charging and its subsequent translation, the authors showed that limiting tyrosine translation availability—via dietary limitation, YARS1/tRNA-TyrGUA ablation, tyrosine degradation (TAL), or YARS1 inhibition (tyrosinol)—leads to impaired oxidative phosphorylation and ferroptosis and attenuation of tumor progression in several mouse models. Mechanistically, the authors showed that restriction of tyrosine translation availability reduces tyrosine codon-dependent translation of mitochondrial complex I subunit NDUFB8 and lipid regulator SCD1, causing complex I misassembly, oxidative phosphorylation failure, and lipid peroxidation-induced ferroptosis.\nBased on these findings, the authors concluded that tRNA-dependent tyrosine usage is a metabolic vulnerability of HCC that can be exploited for therapeutic treatment. While there are some issues with the interpretation of the data and some claims made are not well-founded, the authors have compilled relevant data to support their claims, and the discovery of the role of tRNA-dependent tyrosine usage in HCC is rather novel and potentially important. If the authors could address some of the flaws in the current version of the manuscript, the manuscript should be at the level of Nature Communications.\nResponse: We thank Reviewer 5 for the thorough review of our manuscript and very positive comments. We have carefully addressed all questions in the revised manuscript, as detailed below.\nMajor Flaws and Issues:\n1. One of the problems reading through the manuscript and figures is that the authors crammed too many data points into each figure. For example, to describe the effects of various treatments on tumor growth, the authors used non-liver body weight (body weight minus liver weight) to show that treatments did not have an impact on non-liver body weight. These data are probably not necessary to include in the main figures. I would suggest the authors move less relevant figures to the supplement to avoid overwhelming the figures and readers (this makes some figures barely eligible such as Figures 1C, 3E, 3I, 3K, and 3L).\nResponse: Thank you for the reviewer’s kind reminder. We have moved some panels from the original figures to the supplementary figures to ensure the main figures are more concise.\n2. One of the major claims in the manuscript is that restricting tRNA-dependent tyrosine usage attenuates HCC tumorigenesis and progression by reducing codon-dependent translation of mitochondrial complex I subunit NDUFB8 and lipid regulator SCD1. This would imply that disrupting the expression and/or activity of NDUFB8 and SCD1 could similarly affect HCC tumorigenesis and progression as restricting tRNA-dependent tyrosine usage. Could the authors provide data to test this hypothesis?\nResponse: We appreciate the reviewer's helpful comments. As suggested by the reviewer, we found that knockdown of NDUFB8 or SCD1 reduced the proliferation of HCC cells (Response Figure 5-1 A and B, corresponding to the revised manuscript Figure S18H). Next, control, NDUFB8- or SCD1-depleted HCCLM3 cells were implanted in the BALB/c nude mouse. We found that knockdown of NDUFB8 or SCD1 inhibited tumor development, as shown in Response Figure 5-1 C, D, and E (corresponding to the revised manuscript Figure S18I-S18K), thereby indicating that restricting tyrosine translation availability reduces HCC tumorigenesis and progression by decreasing the expression of NDUFB8 or SCD1. The related description has been added to the revised manuscript (Page 18, Lines 479-483).\nResponse Figure 5-1. (A and B) Relative cell viability of HCC cell lines transfected with the plasmids of shNC, shNUDFB8 (A), or shSCD1 (B) (n = 3). (C to E) Depletion of NDUFB8 or SCD1 in HCCLM3 cells reduced tumor growth (n=6 per group). Tumor photograph (C), tumor weight (D), and tumor volumes (E).\n3. As a follow-up, what makes the translation of NDUFB8 and SCD1 more susceptible to tyrosine restriction? Given that tyrosine is an amino acid required for synthesizing all tyrosine-containing proteins, it is reasonable to assume that proteins with high tyrosine content in their sequences would be more likely to be affected by tyrosine restriction. Could the authors survey protein databases to identify proteins with a high percentage of tyrosine and determine whether NDUFB8 and SCD1 are among them? That piece of data would strengthen the argument made in the manuscript.\nResponse: We sincerely appreciate the reviewer’s comments. Our analysis of amino acid composition across the entire proteome revealed that both NDUFB8 and SCD1 exhibit the contents of tyrosine frequencies ranking in the relatively higher percentiles (about the top 10%) (102/19,110 and 251/19,110, respectively) (Response Figure 5-2, corresponding to revised manuscript Figure 3E). Consequently, we defined the tyrosine-translational-sensitive signature under tyrosine restriction as candidates enriched in tyrosine. The relevant description has been added to the revised manuscript (Page 11, Lines 281-285).\nResponse Figure 5-2. The frequency of tyrosine in the coding sequence (CDS) is sorted from high to low.\n4. The authors created three HCC mouse models to demonstrate the efficacy of tyrosine restriction (Figures 1D–F). However, in the figure legends, the authors did not provide a clear indication of which mouse model was used in subsequent figures (e.g., Figures 1M, 2E), making it hard to interpret the data. Please specify the mouse models used in the figure legends.\nResponse: Thank you for the reviewer’s kind reminder. We have added the related mouse model description to the figure legends to provide a clearer explanation of the data (See Page 56, Lines 1477-1480; Page 59, Lines 1491-1494, and Page 59, Lines 1497-1498).\n5. In Figure 2, the authors claimed that the upregulation of YARS is driven by MYC overexpression. Given that MYC is only responsible for driving a fraction of HCC tumors, it is assumed that this observation is likely specific to MYC-dependent HCC. Is YARS also upregulated in DEN-induced HCC mouse models?\nResponse: We appreciate this thoughtful comment. In our original manuscript, we used three mouse HCC models: a MYC overexpression-driven HCC model, a DEN treatment-induced HCC model, and an intrahepatic injection model of human HCC cells to validate the effect of tyrosine levels on HCC development. Based on our research findings, we found that in all three models, restricting dietary tyrosine intake significantly reduced the development of liver tumors compared to a standard diet, regardless of whether it was related to MYC amplification. To further illustrate that tyrosine dependency is a common feature of liver tumorigenesis, the plasmids of myr-AKT and NRASG12V were injected into mice via hydrodynamic tail vein injection to induce HCC tumorigenesis. Concurrently, a tyrosine-restricted diet was administered to assess the impact of tyrosine limitation in this model (schematic representation provided in Response Figure 5-3 A). The results demonstrated that tyrosine restriction also significantly reduced the progression of AKT/NRASG12V-driven HCC (Response Figure 5-3 B and C, corresponding to the revised manuscript Figure S8C-S8D). This further supports the notion that tyrosine dependency represents a common characteristic of liver cancer. The brief description has also been added to the revised manuscript (Page 9, Lines 227-231). Moreover, it was observed that YARS1 expression was upregulated in the DEN-induced mouse liver tumor model (Response Figure 5-3 F, corresponding to the revised manuscript Figure S8A), further suggesting that the susceptibility of liver tumors to tyrosine restriction may be dependent on the level of YARS1-mediated activity in protein synthesis. The brief description has also been added to the revised manuscript (Page 9, Lines 224-227).\nWe also measured protein synthesis activity, the expression of MYC, YARS1, and the tyrosine metabolism gene set in seven HCC cell lines and one normal hepatic cell line (THLE-2). The results revealed that the levels of YARS1 more strongly correlated with protein synthesis activity (Response Figure 5-3 D, corresponding to the revised manuscript Figure S8E). Meanwhile, tyrosine restriction was less effective at inhibiting cell proliferation in the cell lines with low protein synthesis activity (THLE-2 or HEPG2), compared to those with high protein synthesis activity (SNU398 or PLCPRF5) (Response Figure 5-3 E, corresponding to the revised manuscript Figure S8F). Collectively, these results demonstrate that tyrosine dependency in HCC cells is primarily governed by global protein synthesis activity, rather than being specifically tied to MYC-driven oncogenesis. The brief description has also been added to the revised manuscript (Page 9, Line 231 to Page 10, Line 241).\nResponse Figure 5-3. (A) A diagram depicting the in vivo assessment of hepatocellular carcinogenesis by tyrosine in C57BL/6J mice injected with the plasmids of myr-AKT and NRASG12V. (B) Photographs of the liver from the tumor-bearing mice fed either a standard diet or a tyrosine-restricted diet. (C) Body weight excluding liver weight, liver to body weight ratio, tumor number, and maximum tumor diameter of the tumor-bearing mice fed a tyrosine-modified diet were shown (n = 6). (D) Immunoblots showing puromycin incorporation and the expression of related proteins in the indicated cells. (E) Relative cell viability of normal liver cell line and HCC cell lines cultured in tyrosine-deficient medium compared to standard tyrosine medium (n = 3). (F) SDS-PAGE analysis of the proteins from DEN-treated mouse livers.\n6. In Figure 3, the authors stated that restriction of tyrosine translation availability leads to impaired oxidative stress and ferroptosis. However, the data provided in Figure 3 showed that, while limiting tyrosine upregulates several ferroptosis suppressors such as GPX4 and SLC7A11, it did not directly induce ferroptosis, as the authors have not tested whether ferroptosis inhibitors could rescue the cell death or measured whether tyrosine limitation induces lipid peroxidation. The data provided can only support a claim that tyrosine limitation increases ferroptosis sensitivity rather than leading to ferroptosis. Therefore, the authors need to tone down their claims that limiting tyrosine leads to ferroptosis.\nResponse: Thanks for the great constructive suggestions. To confirm the mechanism that restricting tyrosine translation availability suppresses tumorigenesis through inducing ferroptosis, we first tested the levels of lipid peroxidation by using the probe C11 BODIPY 493/ 503. We observed increased lipid peroxidation upon RTTA treatment, as shown by Response Figure 5-4 A-D (corresponding to the revised manuscript Figure S12A-S12F). A brief description has been added to the revised manuscript (Page 13, Lines 340-341).\nMoreover, rescue experiments were conducted both in vitro and in vivo. Treatment with ferroptosis inhibitor (Fer-1) significantly reversed the reduction of cell proliferation caused by tyrosine deprivation or YARS1 knockdown (Response Figure 5-4 E and F, corresponding to the revised manuscript Figure S18C-S18D), concurrently mitigating YARS1 knockdown-resulted tumor regression (Response Figure 5-4 G-I, corresponding to the revised manuscript Figure S18E-S18G). These findings collectively confirm that restricting tyrosine translation availability triggers ferroptosis in tumor cells. A brief description has been added to the revised manuscript (Page 18, Lines 473-479).\nResponse Figure 5-4. (A) BODIPY493/503 staining in HCC cell lines with the indicated treatment. Shown in (A and C) are tyrosine restriction (A) and YARS1 depletion (C), respectively. Quantification of lipid peroxidation (B and D) upon tyrosine restriction (B), and YARS1 depletion (D), respectively (n = 3). (E and F) Fer-1 treatment rescued the reduction of proliferation caused by tyrosine restriction (E) and YARS1 knockdown (F) in HCC cells (n = 3). (G to I) Fer-1 treatment in YARS1 knockdown cells rescued tumor growth (n=6 per group). Tumor photograph (G), tumor volumes (H), and tumor weight (I).\n7. In Figure 4, the authors showed that a genome-wide CRISPR screen under tyrosine restriction identified a list of genes, including anti-apoptotic protein BCL2 and anti-ferroptosis proteins SLC7A11 and GPX4, which synergize with tyrosine restriction to promote cell death upon knockout. The authors further validated that pharmacological inhibition of BCL2 or ferroptosis induction using SLC7A11 inhibitors or GPX4 inhibitors could synergize with dietary tyrosine limitation and YARS1 depletion to promote HCC cell death in vitro and attenuate HCC tumor growth in vivo. These data are largely consistent with those provided in Figure 3, showing that tyrosine restriction promotes ferroptosis sensitivity. However, Figure 3 is titled as “Restriction of tyrosine translation availability leads to impaired oxidative stress and ferroptosis” and was allocated to show that tyrosine restriction promotes ferroptosis sensitivity. Thus, it would make more sense to rearrange and consolidate these ferroptosis-related data into one figure. It would take some effort to rearrange and adjust the text accordingly, but it would significantly improve the manuscript’s logical flow.\nResponse: Thank you for the reviewer’s kind reminder. Due to space constraints in the main figures, we were unable to include many more images. As such, we have carefully rearranged the existing figures to best support the article's logical flow. We have rearranged and consolidated the ferroptosis-related data into a new figure to improve the manuscript’s logical flow (Figure 4, along with its supplementary Figures 17, 18, and 19). Specifically, we have relocated the synergistic therapeutic effects of tyrosine deprivation combined with GPX4 or SLC7A11 knockdown in vitro and in vivo to Supplementary Figures 17 and 18, and transferred the ferroptosis-related results of the MYC-YARS1-SCD1 axis to Supplementary Figure 19. Concurrently, we have revised the title of Figure 3 to “Restriction of tyrosine translation availability reduces the translation efficiency of NUDFB8 and SCD1”.\n8. In Figures 4, 5, and 6, the authors showed some representative images of liver tumors (4I, 4L, 5N, and 6N) after treatment. Some of these liver tumors appeared completely tumor-free, yet the survival of the mice from these treatment groups (4K, 4N, 5P, and 6P) was extended but not completely protected. While this may sound like nitpicking and fastidious criticism, it does make readers question how representative these tumor images are. I would recommend selecting more representative and realistic images to avoid being nitpicked.\nResponse: Thank you for the reviewer’s kind reminder. In response, we have enhanced the clarity of the relevant tumor images (Figures 4I, 4K, 5I, 6H, and S18L in the revised manuscript) and clearly outlined the residual tumor margins using red indicator lines. This revision reveals the minimal residual disease that was present even in the best-responding cases, which may have been overlooked originally. The revised images now better align the visual data with the survival outcomes, reflecting a significant—though not complete—tumor reduction. This adjustment allows for a more realistic representation of the therapeutic efficacy and reduces the risk of misinterpretation.\n9. The authors used TEM images of livers to show that cristae formation was severely affected by tyrosine limitation via dietary limitation, YARS1/tRNA-TyrGUA ablation, tyrosine degradation (TAL), or YARS1 inhibition (tyrosinol) and quantified maximal cristae width to show that these treatments lead to mitochondrial defects. While these images are on the same scale based on the scale bar, the mitochondrial size and electron density vary significantly. For example, in Figure 6S, the tyrosinol group showed clearly smaller and more electron-dense mitochondria compared to the control-treated ones. These images are not quite comparable in scale, making it difficult to quantify maximal cristae width. I would recommend selecting more comparable images as representative images.\nResponse: We appreciate the reviewer’s comments and apologize for the issues with the images. We have replaced the original images with the higher clarity images in the revised manuscript (Figures 3N and 6L).\n10. In several figures (Figures 5K–L, 6J–K), the authors showed that in HCC cell lines, tyrosine degradation (TAL) or YARS1 inhibition (tyrosinol) increases lipid peroxidation, suggesting that these treatments induce ferroptosis. It would be more convincing if the authors could also test whether ferrostatin or an iron chelator could attenuate the lipid oxidation induced by these treatments.\nResponse: Thank you for the reviewer’s constructive suggestions. Considering your advice, we found that Fer-1 (ferrostatin-1) treatment reduced the levels of lipid oxidation induced by TAL (Response Figure 5-5 A and B, corresponding to the revised manuscript Figure S21K and S21L) or tyrosinol treatment (Response Figure 5-5 C and D, corresponding to the revised manuscript Figure S23G and S23H). A brief description has been added to the revised manuscript (Page 20, Lines 545-547 and Page 22, Lines 594-595).\nResponse Figure 5-5. (A) BODIPY493/503 staining in SNU398 cell lines with the indicated treatment. Shown in (A and C) are TAL treatment combined with Fer-1 (A) and tyrosinol treatment combined with Fer-1 (C), respectively. Quantification of lipid peroxidation (B and D) (n = 3).\nReferences\nBogie JFJ, Grajchen E, Wouters E, Corrales AG, Dierckx T, Vanherle S, Mailleux J, Gervois P, Wolfs E, Dehairs J et al (2020) Stearoyl-CoA desaturase-1 impairs the reparative properties of macrophages and microglia in the brain. 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Proc Natl Acad Sci U S A 119: e2203480119\nZhao R, Cai K, Yang JJ, Zhou Q, Cao W, Xiang J, Shen YH, Cheng LL, Zang WD, Lin Y et al (2023) Nuclear ATR lysine-tyrosylation protects against heart failure by activating DNA damage response. Cell Rep 42: 112400\nZong Z, Xie F, Wang S, Wu X, Zhang Z, Yang B, Zhou F (2024) Alanyl-tRNA synthetase, AARS1, is a lactate sensor and lactyltransferase that lactylates p53 and contributes to tumorigenesis. Cell 187: 2375-2392 e2333\nReviewer #1 (Remarks to the Author):\nThe authors have fully addressed all my concerns. I recommend publication of the manuscript\nResponse: We highly thank this reviewer for his/her time and effort, and insightful comments that greatly improved our study.\nReviewer #2 (Remarks to the Author):\nAll of the reviewers' comments have been appropriately addressed.\nResponse: We highly thank this reviewer for his/her time and effort, and insightful comments that greatly improved our study.\nReviewer #3 (Remarks to the Author):\nI co-reviewed this manuscript with one of the reviewers who provided the listed reports. This is part of the Nature Communications initiative to facilitate training in peer review and to provide appropriate recognition for Early Career Researchers who co-review manuscripts.\nResponse: We highly thank this reviewer for his/her time and effort, and insightful comments that greatly improved our study.\nReviewer #4 (Remarks to the Author):\nThe authors have addressed most of my comments -\nBut in Supplementary Figure 18A and B, the animal experiments are performed lacking controls related to BCL2 and GPX4 alone, therefore, it's difficult to claim that this effect is synergistic.\nAside from this, I have nothing to add.\nResponse: We highly thank this reviewer for his/her time and effort, and insightful comments that greatly improved our study. We apologize for any misunderstanding caused by the revised manuscript Figure S18A and S18B. In this experiment, we used two distinct shRNA knockdown plasmid systems: pLKO.1-shNC and pGPU6-shNC. Thus, the experimental groups were designed as follows:\ngroup 1 (shNC): pLKO.1-shNC+pGPU6-shNC\ngroup 2 (shYARS1-1): pLKO.1-shYARS1-1+pGPU6-shNC\ngroup 3 (shYARS1-2): pLKO.1-shYARS1-2+pGPU6-shNC\ngroup 4 (shYARS1-1+shGPX4): pLKO.1-shYARS1-1+pGPU6-shGPX4,\ngroup 5 (shYARS1-2+shGPX4): pLKO.1-shYARS1-2+pGPU6-shGPX4\ngroup 6 (shYARS1-1+shBCL2): pLKO.1-shYARS1-1+pGPU6-shBCL2\ngroup 7 (shYARS1-2+shBCL2): pLKO.1-shYARS1-2+pGPU6-shBCL2\nConsequently, group 1 served as the control for: group 2 and 3, group 2 served as the control for: group 4 and 6, and group 3 served as the control for: group 5 and 7.\nReviewer #5 (Remarks to the Author):\nThe authors have adequately addressed the previous critiques raised in the previous review.\nResponse: We highly thank this reviewer for his/her time and effort, and insightful comments that greatly improved our study."}, {"round": 2, "reviewer_comments": {"reviewer_1": "The authors have fully addressed all my concerns. I recommend publication of the manuscript", "reviewer_2": "All of the reviewers' comments have been appropriately addressed.", "reviewer_3": "I co-reviewed this manuscript with one of the reviewers who provided the listed reports. This is part of the Nature Communications initiative to facilitate training in peer review and to provide appropriate recognition for Early Career Researchers who co-review manuscripts.", "reviewer_4": "The authors have addressed most of my comments -\nBut in Supplementary Figure 18A and B, the animal experiments are performed lacking controls related to BCL2 and GPX4 alone, therefore, it's difficult to claim that this effect is synergistic.\nAside from this, I have nothing to add.", "reviewer_5": "The authors have adequately addressed the previous critiques raised in the previous review."}, "author_response": ""}]

Decision letter