Hypusination of the translation factor eIF5A regulates mitochondrial tRNA processing to promote prostate cancer aggressiveness

Domain: biology
Published: 2026-03-13
Editorial outcome: major_revision

Abstract
Protein synthesis plays a central role in cancer development and progression. eukaryotic initiation factor 5A (eIF5A), a translation factor activated by hypusination, is implicated in tumorigenesis, however, its mode of action is still unclear. We find that hypusinated eIF5A (eIF5Ahyp) promotes metastasis and tumor growth in prostate cancer (PCa) by supporting mitochondrial metabolism and translation. eIF5Ahyp controls the subcellular localization of Mitochondrial Ribonuclease P Protein 3 (MRPP3) mRNA encoding a protein essential for mitochondrial tRNA (mt-tRNA) maturation. We show that eIF5Ahyp regulates the nuclear export of MRPP3 mRNA, its expression, thereby promoting mt-tRNA maturation. Our findings establish that MRPP3 enhances mitochondrial metabolism and supports PCa metastasis. Importantly, its expression restores mitochondrial translation and tumor growth inhibited by the downregulation of eIF5Ahyp. Together, we uncover a critical role for eIF5Ahyp in mitochondrial protein synthesis and highlight its broader implications in coordinating the expression of nuclear and mitochondrial genomes, linking hypusination to cancer progression.

Introduction
Cancer cell growth and tumor progression are fundamentally driven by increased protein synthesis and metabolic reprogramming, two closely interconnected processes1. The translation factor eukaryotic initiation factor 5A (eIF5A) plays a crucial role in this context, being involved in the initiation, elongation and termination of translation for a specific subset of proteins2. There are two known highly homologous (91%) isoforms of eIF5A: eIF5A and eIF5A2 encoded by two different genes located on two different chromosomes. However, eIF5A2 expression is weak in the prostate 3. One of the defining features of both isoforms of eIF5A is that they undergo hypusination, a unique and highly conserved post-translational modification essential for its activity4. This modification, dependent on the polyamine spermidine, is catalyzed by two enzymes: deoxyhypusine synthase (DHPS) and the deoxyhypusine hydroxylase (DOHH).

Polyamines play an important role in cell proliferation, apoptosis, protein and nucleotide synthesis5. Previous studies, including our own, have demonstrated that polyamines are essential for metastasis in prostate cancer (PCa)6,7, and their levels are significantly elevated in PCa tissues compared to benign prostatic hyperplasia (BPH) or normal prostate tissues7. These findings point to the polyamine/hypusination axis as a central player in PCa progression. Yet, despite the established link between hypusinated eIF5A (eIF5Ahyp) and neoplasia, the underpinning mechanisms of its pro-tumorigenic actions remained elusive. According to the GLOBOCAN study, PCa is the second most diagnosed cancer and the fifth leading cause of cancer death among men worldwide 8. Removal of the prostate (prostatectomy) and radiotherapy are treatments for localized tumors. For more advanced PCa, anti-androgen treatments and/or chemotherapy (Docetaxel) are prescribed. However, patients quickly develop resistance, leading to fatal outcomes. Therefore, there is a critical need to discover therapies that target new molecular pathways.

Emerging evidence suggests that tumor cells hijack the translation machinery to selectively promote the expression of oncogenic proteins, thereby fueling cancer progression9. mRNA translation is an energy-intensive process, consuming 30 to 50% of the cell's energy, primarily supplied by mitochondria10. Recent evidence highlights eIF5A’s role in mitochondrial activity in macrophages polarization and senescence11,12. However, the implications of hypusination in mitochondrial metabolism in cancer progression have yet to be understood.

Mitochondria possess their own genome, consisting of 2 ribosomal RNAs, 22 tRNAs, and 13 encoding proteins which are essential components of the mitochondrial respiratory chain13. The genome is transcribed as a single polycistronic unit, requiring precise post-transcriptional modifications to generate functional and mature RNAs. These processes are controlled by nuclear-encoded proteins and require accurate coordination between the nuclear and mitochondrial genome to maintain mitochondrial function and integrity14. In this study, we show that eIF5Ahyp mediates the nuclear-mitochondrial dialogue by regulating the expression of the mitochondrial ribonuclease P protein 3 (MRPP3), a nuclear-encoded endonuclease essential for the maturation of mitochondrial tRNAs (mt-tRNA). Our data reveal that both eIF5Ahyp and its modifying enzyme DHPS are upregulated in PCa tumors, and elevated DHPS expression correlates with poor prognosis. Conversely, depletion of eIF5Ahyp suppresses PCa cell aggressiveness, reduces the growth of patient-derived tumoroids and limits metastasis in vivo. Mechanistically, we demonstrate that eIF5Ahyp regulates mitochondrial activity and the maturation of mt-tRNA through the downregulation of MRPP3. Consistent with the role of eIF5Ahyp, we identify MRPP3 as a pro-oncogenic factor that drives tumor growth and progression.

Results
eIF5Ahyp and DHPS are upregulated in human PCa.
To determine the role of eIF5Ahyp in PCa, we carried out an in-depth bioinformatic analysis using several public RNA and proteomic databases and assessed hypusination in patient samples. Analysis of the CamCaP Study Group dataset (GSE70770)15, which includes benign and tumor tissues from 259 patients, revealed that the key regulators of hypusination: DHPS, DOHH, EIF5A and EIF5A2 were significantly overexpressed in tumor tissues compared to normal tissues (Fig. 1a,b). Consistent with the major role of polyamines in PCa, genes encoding enzymes involved in polyamine metabolism such as, the ornithine decarboxylase 1 (ODC1), spermidine synthase (SRM) and spermine synthase (SMS) were also significantly upregulated in tumors (Fig. 1a,b). We further analyzed the expression of DHPS, DOHH, EIF5A and EIF5A2 using single-cell RNA sequencing (scRNA-seq) data from Heidegger et al. 16. Integrated analysis of tumor and normal samples (Fig. 1c and Supplementary Fig. 1a-e) revealed a significant increase in the expression of EIF5A (p=6x10-5), DOHH (p=1.8x10-6), and DHPS (p<2.2x10-16) within tumoral epithelial cells compared to normal epithelial cells (Fig. 1d). Further analysis of four databases (TCGA, Grasso, Lapointe and Varambally) 17-19 showed a correlation between the expression of the genes of the hypusination module (eIF5A1, eIF5A2, DHPS and DOHH) (Supplementary Fig. 1f), however, only DHPS was consistently and significantly upregulated in PCa (Supplementary Fig.1h). Remarkably, patients with high levels of DHPS also showed significantly higher expression of DOHH and EIF5A (Supplementary Fig. 2e). These findings demonstrate that genes within the hypusination module—particularly DHPS—are upregulated in primary PCa.

Since PCa is dependent on androgens, expression analysis of the hypusination genes and AR was performed, but no significant correlation was found between hypusination genes and AR hallmark genes signature (Supplementary Fig.1g).

To determine if hypusination plays a role in PCa metastasis, we used Cancertool 20, a web-based platform for cancer gene expression analysis. DHPS was consistently overexpressed with the progression of the disease from primary tumors to metastases (Fig. 1e, Supplementary Fig.1h). Interestingly, our analysis of lymph node involvement (N) and distant metastasis (M), using the OncoDB online database, confirmed the rise in DHPS levels as the disease progressed (Fig. 1f,g and Supplementary Fig. 2a,b). We then analyzed the expression of the hypusination mRNAs in a database of metastatic castration prostate cancer patients (mCRPC), the most advanced form of PCa 21. Our results showed a significant increase in DHPS mRNA levels in neuroendocrine prostate cancer—a rare but highly aggressive subtype of PCa compared to adenocarcinoma—whereas DOHH, EIF5A, and EIF5A2 levels remained unchanged (Supplementary Fig. 2c). Finally, high DHPS mRNAs levels are associated with lower overall survival in prostate cancer patients based on the TCGA database (Supplementary Fig. 2d). All together, our data show that DHPS overexpression is associated with metastatic PCa and poor prognosis.

We then analyzed the protein levels of DHPS, DOHH, and eIF5A in a proteomic database that includes 306 patients with adenocarcinoma 22. Interestingly, the three proteins were significantly more expressed in tumoral than normal tissue (Supplementary Fig. 2f). To reinforce the relevance of our findings to human pathology, we assessed eIF5Ahyp, total eIF5A and DHPS protein levels by immunoblotting in the tumoral and adjacent normal tissues from PCa patients at our local hospital (CHU Nice) (Table 1 and Fig. 1h). Both eIF5Ahyp and DHPS were significantly elevated in tumors tissues (p = 0.0045 and p = 0.021, respectively) while eIF5A did not increase (Fig. 1i,j; Supplementary Fig. 2g). Similarly, we found that eIF5Ahyp, eIF5A and DHPS were significantly more expressed in PCa tumors than prostate tissue from patients with BPH (Supplementary Fig. 2h,i). Collectively, our results show that hypusination of eIF5A and DHPS levels were upregulated in PCa and associated with metastasis.

Inhibition of eIF5Ahyp suppresses tumor growth and PCa aggressiveness in different PCa models.
To characterize the pro-tumorigenic role of eiF5Ahyp in PCa, we employed two approaches to inhibit eIF5Ahyp: knockdown (KD) of DHPS using IPTG-inducible shRNA and pharmacological inhibition with GC7, a competitive inhibitor of DHPS, in three PCa cell lines (LNCaP, DU145 and PC3) (Supplementary Fig. 3a). Both DHPS knockdown and GC7 treatment led to significant reduction in cell proliferation, migration and invasion, as observed in Boyden chamber assays (Supplementary Fig. 3b,c). Notably, these interventions induced cell cycle arrest at the G0/G1 phase (Supplementary Fig. 3d) without causing apoptosis (Supplementary Fig. 3e).

To further validate these findings, we tested the effects of eIF5Ahyp inhibition on three patient-derived tumoroids (MSK-PCa1, MSK PCa3 and MSK-PCa4)23. We verified by cytometry and immunoblot that both GC7 and the downregulation of DHPS decreased eIF5Ahyp (Fig. 2a, Supplementary Fig. 3f,g) and observed that it induced a significant decrease in tumoroid growth as well as tumoroids formation capacities (Fig. 2b, Supplementary Fig. 4a). In contrast, GC7 had a minimal impact on the proliferation of organoids derived from normal prostate tissue (Supplementary Fig. 4b). To analyze the effects of the inhibition of eIF5Ahyp on cell division in 3D, we set up the fluorescence ubiquitin cell cycle indicator (FUCLCI)-based system in tumoroids. This technique allows the tracking of cell division in live cells within their endogenous environment with high spatiotemporal resolution24. We observed that GC7 treatment decreased cell division and increased cell cycle arrest within the 3D tumoroids (Fig. 2c). Additionally, GC7 significantly inhibited cell invasion, reducing the ability of tumoroid cells to migrate out of a soft collagen matrix by 60%, showing that eIF5Ahyp is associated with invasion in cancer cells (Fig. 2d).

We further evaluated the role of eIF5Ahyp in tumor growth in vivo using xenograft experiments. DU145 and PC3 cell lines, either expressing control shRNA (shCtl) or shDHPS, or treated with a vehicle or GC7 (10 mg/kg, i.p.), were implanted in mice. Both strategies with the two cell lines resulted in a significant reduction in tumor volume and weight (Fig. 2e and Supplementary Fig. 4c-f). These results were validated in RM-1 cells, a mouse prostate cancer cell line, injected subcutaneously in syngeneic C57Bl6J mice (Fig. 2f and Supplementary Fig. 4g,h). Altogether, our data clearly show that eIF5Ahyp is required for PCa cell proliferation and tumor growth.

To determine the effects on metastasis, we used an orthotopic xenograft model in which PC3 cells expressing luciferase were injected directly into the prostate of mice, following established protocols25,26. This model allows the cancer cells to grow within their native microenvironment, enabling the development of primary tumors and the formation of distant metastases. The injected cells were either transfected with controls shRNA (shCtl) or shRNA targeting DHPS (shDHPS) to inhibit eIF5Ahyp. After 50 days, DHPS and eIF5Ahyp were significantly decreased in prostate tumors (Supplementary Fig. 4i) and tumor progression was assessed using the bioluminescent signal in animals. Remarkably, total luminescence was significantly reduced in mice injected with shDHPS cells, indicating lower tumor and metastasis burden (Fig. 2g). Further imaging of organs commonly invaded by metastatic cells (kidney, spleen, liver, lung and digestive track) revealed luminescent cells at distant sites, confirming metastatic spread (Supplementary Fig. 4j). While metastasis was observed in nearly all mice injected with shCtl cells, only 2 out of 7 mice injected with shDHPS cells developed metastases in the liver, spleen and kidney, and just 1 out of 7 showed metastatic spread to the digestive tract. Notably, none of the mice injected with shDHPS cells had lung metastases (Fig. 2h). Taken together, our results suggest that eIF5Ahyp is essential for promoting tumor growth and PCa metastasis.

eIF5Ahyp controls mitochondrial metabolism in PCa cells.
Building on previous studies linking eIF5Ahyp to mitochondrial metabolism11, we performed metabolite profiling of DHPS KD, GC7 treated cells and controls counterparts of DU145 cells. Of the 308 metabolites measured by LC-MS/MS, the steady-state levels of 71 metabolites showed significant changes in response to DHPS depletion (p<0.05) with six intermediates of the TCA cycle (citrate, aconitate, α-ketoglutarate, succinate, fumarate and malate) significantly decreased upon eIF5Ahyp inhibition (Fig. 3a, b and Table 2). Consistent with the metabolic effects of DHPS silencing, a reduction in TCA cycle intermediates was also confirmed in cells treated with GC7 (Supplementary Fig. 5a-d). To assess whether the activity of the TCA cycle was affected by eIF5Ahyp, we employed a stable isotope-tracing approach by using [13C ]-glucose (Fig. 3c). As expected, the inhibition of eIF5Ahyp, significatively decreased the abundance of aconitate (M+2), α-ketoglutarate (M+2), succinate (M+2), fumarate (M+2) and malate (M+2) in both cell lines with a more pronounced effect in DU145 (Fig. 3d, Supplementary Fig. 5e). Altogether, these results demonstrate that eIF5Ahyp maintains TCA cycle activity in PCa cells.

To determine if the decrease in eIF5Ahyp affects mitochondrial respiration, we measured the oxygen consumption rate (OCR) and extracellular acidification rate (ECAR) in PCa cells treated with GC7 or knockdown for DHPS. Although ECAR remained unchanged (Supplementary Fig. 5f,g), eIF5Ahyp inhibition impaired basal respiration, the maximum respiratory capacity and ATP production in DU145, LNCaP and PC3 cells (Fig. 3e, f, and Supplementary Fig.5h). Similar effects were observed in patient-derived tumoroids, where inhibition of eIF5Ahyp decreased OCR without significantly affecting ECAR (Supplementary Fig. 5i,j). Importantly, in line with our previous results showing that mitochondria adapt their shape and structure in response to energetic stress27, the effect of eIF5Ahyp inhibition were not due to a decrease in mitochondrial content (Supplementary Fig. 5k), but were associated with mitochondrial fragmentation and cristae disorganization; a hallmark of energetic stress28 (Fig. 3g,h).

In conclusion, our findings demonstrate that eIF5Ahyp is critical for maintaining mitochondrial metabolism and integrity in PCa cells.

eIF5Ahyp supports MRPP3 expression and mitochondrial t-RNA maturation.
Given the role of eIF5Ahyp in mRNA translation, we examined whether hypusination influences protein synthesis. Using a puromycin incorporation assay, we demonstrated that both GC7 and DHPS knockdown reduced the synthesis of nascent proteins in PCa cells and patient-derived tumoroids, indicating inhibited mRNA translation (Supplementary Fig. 6a-c). To further explore this, we conducted a polysome fractionation assay to examine the association of ribosomes with mRNA. Polysomes (actively translated mRNA, with two or more ribosomes, and monosomes, mRNA with one ribosome) were separated by zonal ultra-centrifugation on sucrose gradient according to their molecular weight and shape, and the different fractions were quantified as described previously29. We observed that GC7-treated cells exhibited a substantial decrease in polysomes and an increase in the 40S, 60S, and 80S ribosomal subunits, suggesting a global reduction in protein translation (Fig. 4a). A proteomic analysis identified significant downregulation of 439 proteins and upregulation of 85 proteins upon DHPS depletion in DU145 cells (Fig. 4b). Similar trends, with less protein affected, were seen in LNCaP cells, where 161 proteins were downregulated and 30 upregulated (Supplementary Fig. 6d).

Pathway enrichment analysis of the downregulated proteins highlighted disrupted mitochondrial translation and function as key processes affected by eIF5Ahyp depletion (Supplementary Fig. 6e). We performed polysome sequencing (Supplementary Fig.6f) and integrated the data with the proteomic study to identify common pathways using Gene Set Enrichment Analysis (GSEA). We found that 26 pathways were commonly regulated (Fig. 4c). Notably, 11 of the top 15 pathways were associated with mitochondrial metabolism, including the mitochondrial protein-containing complex (Fig. 4d). To validate the role of hypusination in mitochondrial mRNA translation, we measured mitochondrial translation in cells treated with either vehicle, GC7, or chloramphenicol, a known inhibitor of mitochondrial protein synthesis. Consistent with chloramphenicol's effects, GC7 treatment significantly decreased mitochondrial translation (Supplementary Fig. 6g). Supporting these findings, data from the Heidegger single-cell RNA seq (scRNA-seq) patient database revealed a positive correlation between high DHPS and EIF5A expression and genes involved in mitochondrial translation in epithelial prostatic cells (Supplementary Fig. 6h-k). This establishes a clear link between eIF5Ahyp and mitochondrial translation. In agreement with these results, our proteomic analysis further identified the downregulation of the family of the Pentatricopeptide repeat (PPR) proteins in DU145 and LNCaP cells upon eIF5Ahyp depletion (Fig. 4b, Supplementary Fig. 6d). PPR proteins are essential RNA-binding proteins involved in mitochondrial RNA processing and translation30. Given its essential role as a regulator of mitochondrial RNA maturation and function, both in vitro and in vivo, MRPP3 emerged as a key target, 31,32. MRPP3 was one of the most significantly downregulated proteins following eIF5Ahyp inhibition, with a Log fold change of -2.99 in DU145 cells (Supplementary Fig. 7a).

Furthermore, we found that MRPP3 protein levels significantly correlate with the expression of DHPS, DOHH, eIF5A and A2 in the Sun proteomic database that includes 306 patients (Supplementary Fig. 7b). To confirm these findings, we validated the downregulation of MRPP3 protein levels in DU145, LNCaP and the three patient-derived tumoroids following GC7 treatment or DHPS KD (Fig. 4e and Supplementary Fig. 7c). To study the role of MRPP3 in the effects of eIF5Ahyp on mitochondrial translation, we overexpressed it in cells treated with GC7 (Supplementary Fig. 7d). Interestingly, elevated MRPP3 levels rescued the downregulation of mitochondrial translation induced by the inhibition of eIF5Ahyp (Fig. 4f) demonstrating that eIF5A regulates mitochondrial translation through MRPP3. To reinforce the link between eIF5Ahyp, MRPP3 and TCA cycle, we demonstrated that overexpression of MRPP3 partially reversed the inhibition of isocitrate Dehydrogenase (NAD(+)) 3 Catalytic Subunit Alpha (IDH3A), Succinate Dehydrogenase Complex Flavoprotein Subunit A (SDHA) and Dihydrolipoamide Dehydrogenase (DLD), three enzymes implicated in the regulation of the TCA cycle 11 (Fig. 4g).

MRPP3 functions as the catalytic enzyme of the RNaseP protein complex that regulates the maturation of mitochondrial tRNA (mt-tRNA)32 (Fig. 4h). To study the function of MRRP3 in the context of low hypusination level, the amount of immature tRNA was quantified in DU145 cells and tumoroids. Consistent with the decrease of MRPP3 caused by eIF5Ahyp inhibition, we observed a 2.7- and 8.2-fold increase in unprocessed mt-tRNAVal and mt-tRNAIle, respectively, following GC7 treatment (Fig. 4i). Additionally, we sorted dividing and arrested cells from FUCCI-expressing tumoroids (Fig. 2c) and quantified the relative amount of immature tRNA. Decreased Ki67 expression in GC7-treated and arrested cells confirmed their reduced proliferation (Supplementary Fig. 7e), and these cells also exhibited increased levels of immature mt-tRNAVal and mt-tRNAIle (Fig. 4j). To independently assess tRNA maturation, we analyzed pre-RNA cleavage by RNA-seq. A defect in the processing of mt-tRNA can be detected by the analysis of the reads in the region spanning the mitochondrial tRNA and mRNA sequences as previously described by Münch and Harper31. When tRNA processing is malfunctioning, sequence reads from the contiguous mRNA can extend into tRNA resulting in an increase of reads. Interestingly, we observed a significant increase in the reads spanning the regions between tRNA and ND2, COX1 and COX2 mRNA indicating an accumulation of immature mt-tRNA when eIF5A was inhibited (Fig. 4k). Altogether, our results show that eIF5Ahyp inhibition reduces MRPP3 expression and mt-tRNA maturation resulting in the decrease of mitochondrial translation.

eIF5Ahyp controls the nuclear export of MRPP3 mRNA.
We next aimed to investigate how hypusination regulates the expression of MRPP3. eIF5A is a nucleocytoplasmic shuttle protein and a RNA binding protein33,34. Furthermore, MRPP3 mRNA contains the sequence motif AAAUGU necessary for the binding to eIF5A as described by Xu et al.35. Thus, we postulated that eIF5A binds to MRPP3 mRNA and exports it to the cytosol to be translated. Using a RIP-qPCR assay we validated the binding of eIF5A to MRPP3 mRNA in DU145 and PC3 cells (Fig. 5a). In accordance with previous studies 36, we also showed that eIF5A binds to c-MYC mRNA but not RPLP0, GAPDH mRNA. Then, we examined whether hypusination interferes with the cellular localization of eIF5A in PCa cells by immunofluorescence. Similarly to our positive control leptomycin B, a potent inhibitor of nuclear export 37, the treatment with GC7 or the KD of DHPS significantly increased the amount of eIF5A in the nucleus compared to control cells (Fig. 5b,c). This result suggests, as previous described 38, that hypusination is required to target eIF5A in the cytoplasm. To demonstrate that eIF5A hypusination directly interferes with the transfer of MRPP3 mRNA in the cytosol, we performed cellular fractionation and quantified MRPP3 mRNA by q-PCR in the nuclear and cytosolic fractions of DU145 cells treated with GC7. To exclude an effect on the transcription of MRPP3, we first analyzed MRPP3 mRNA expression and showed that GC7 and leptomycin B did not affect MRPP3 mRNA levels (Fig. 5d). In accordance with the role of eIF5A in the nuclear-cytosolic transfer, GC7 led to the accumulation of MRPP3 and c-MYC mRNA in the nucleus whereas RPLP0 mRNA was not affected (Fig. 5e), showing that hypusination is required for the nuclear export of MRPP3 mRNA. Of note, leptomycin B increased MRPP3, RPLP0 and c-MYC mRNA in the nucleus and it also decreased the expression of MRPP3 and c-MYC, suggesting that nuclear export is a general mechanism that controls the expression of both proteins (Supplementary Fig. 8a). Importantly, we also observed that both immature mt-tRNAVal and mt-tRNAIle were significantly increased upon leptomycin B treatment (Supplementary Fig. 8b). Altogether, our results show that eIF5Ahyp regulates MRPP3 expression through the nuclear export of its mRNA.

MRPP3 is a pro-oncogenic protein that regulates mitochondrial function and PCa metastasis.
To investigate the role of MRPP3 in PCa cell metabolism and tumorigenesis, we generated DU145 and PC3 cell lines with stable knockdown of MRPP3 (shMRPP3) (Supplementary Fig. 9a) and conducted steady state metabolomics and Seahorse analysis to assess mitochondrial function. Similarly to the inhibition of eIF5Ahyp, the downregulation of MRPP3, significatively decreased the abundance of citrate (M+2), α-ketoglutarate (M+2), fumarate (M+2) and malate (M+2) (Fig. 6a, Supplementary Fig. 9b). In addition, silencing of MRPP3 decreased basal respiration, oxygen consumption, maximum respiratory capacities and ATP production in both cancer cell lines, indicating impaired mitochondrial function (Fig. 6b). Finally, downregulation of MRPP3 caused drastic changes in mitochondrial morphology, including increased circularity and disorganized cristae structure (Supplementary Fig. 9c, d). These findings establish MRPP3 as a central regulator of TCA cycle as well as mitochondrial activity and integrity in PCa cells.

Next, we examined whether the alterations of metabolism caused by MRPP3 silencing translated to changes in tumor growth and aggressiveness. In vitro, MRPP3 knockdown significantly reduced migration and invasion capabilities of PC3 and DU145 cells (Supplementary Fig. 9e). Consistent with these results, MRPP3 depletion led to a significant decrease in the growth of patient-derived tumoroids, highlighting its role in supporting tumor cell viability and expansion (Fig. 6c). To determine if MRPP3 has a pro-tumoral role in vivo, we performed subcutaneous injections of PCa cells. Remarkably, MRPP3 downregulation significantly decreased the tumor growth of both DU145 and PC3 in a xenograft model and RM-1 in syngeneic mice (Fig. 6d,e and Supplementary Fig. 9f-h). Since MRPP3 expression rescued mitochondrial translation after the inhibition of eIF5Ahyp (Fig. 4f), we examined whether it could overcome the anti-migratory and anti-invasive effects of low eIF5Ahyp in vitro. Indeed, exogenous expression of MRPP3 restored the migratory and invasive capacities of DU145 treated with GC7 (Supplementary Fig. 9i,j). We next validated the contribution of MRPP3 in eIF5A effects in vivo. Notably, the expression of MRPP3 in DU145 cells, which have low levels of eIF5Ahyp, restored tumor growth in a xenograft model (Fig. 6f,g, Supplementary Fig. 10a). Similarly, MRPP3 overexpression counteracted partially the anti-tumoral effects resulting from the downregulation of DHPS in the RM-1 syngeneic model (Supplementary Fig. 10b-d) demonstrating that eIF5Ahyp plays a role in neoplasia through MRPP3. To further characterize the role of MRPP3 in PCa, we analyzed the formation of metastasis after injection of PC3-Luc cells expressing shMRPP3 in the prostate. Monitoring luminescence allowed us to track tumor spread, and inhibition of MRPP3 led to a significant reduction in total luminescence, indicating lower tumor burden (Fig. 6h). Moreover, metastasis analysis showed that only 1 out of 8 mice injected with cells depleted for MRPP3 developed metastases at two sites (spleen and digestive tract), while 100% control (shCtl)-injected mice exhibited widespread metastasis in the liver, spleen, and kidney (Fig. 6i, Supplementary Fig. 10e). To implement these results, MRPP3 expression was analyzed in clinical samples from our local cohort of PCa patients. MRPP3 was significantly upregulated in tumor tissues compared to adjacent normal tissues, further supporting its role as a pro-tumorigenic factor (Fig. 6j,k). Similarly, we found that MRPP3 is significantly more expressed in PCa tumors than prostate tissue from patients with Benign Prostate Hyperplasia (BPH) (Supplementary Fig. 10f). Interestingly, the analysis of Sun's proteomic database confirmed that MRPP3 is overexpressed in tumors 22 (Supplementary Fig. 10g). Of note, while we did not find a correlation between MRPP3 and DHPS or eIF5Ahyp in our cohort, Sun’s database revealed a correlation between the expression of MRPP3, DHPS, and eIF5A (Supplementary Fig. 7b).

In conclusion, our data demonstrate that MRPP3 is a protein driving the pro-oncogenic effects of eIF5A. It maintains mitochondrial function and controls tumor progression in PCa (Fig. 7). These findings highlight MRPP3 as a potential therapeutic target, with its inhibition offering a promising strategy to disrupt cancer cell metabolism and limit metastatic spread.

Methods
Ethical statement
The study utilized human prostate tissue samples obtained from PCa patients who gave informed written consent before undergoing radical prostatectomy at the CHU Hospital of Nice in 2023. This research was performed in accordance with the declaration of Helsinki and it was approved by the French national ethics committee under the CODECOH number DC2022-4966.

Mice were fed a standard chow diet (Cat#A04, Safe) and housed in a temperature-controlled room under a 12-h light–dark cycle under pathogen-free conditions. Experimental protocols were validated by the National Animal Care and Use Committee and the regional ethics commission (Ciepal Azur) and the French ministry of research under the reference: APAFIS#C41336-20230208 100 1830 v7, following the European regulation on the protection of animals used for scientific purposes (UE directive 2010/63/EU.

Statistics, reproducibility and data analysis.
All experiments were performed at least three independent times unless stated. Statistical analyses were performed with GaphPad Prism version 9.0 using appropriate test: two-tailed Student’s T test, Mann-Whitney or ANOVA as indicated in the figure legends. No statistical method was used to predetermine sample size. Allocation of samples and mice was random in all experiments. The investigators were not blinded during experiments outcome assessment. Not all replications were successful due to technical problems in some experiments.

Patients samples were analyzed by two pathologists to isolate the normal tumor tissue from the prostatectomy. For animal experiments, 6 to 10 mice were used as indicated in each figure legend. For the experiments with GC7, mice were randomly distributed in the control or treated group. All data are available upon request to the corresponding author.

Patients
At diagnosis, the patients' ages ranged from 54 to 77 years, their clinical characteristics are described in Table 1.

Cell culture and cell lines
DU145 (cat# HTB-81), LNCaP (cat#CRL-174 0), and PC3 (cat#CRL-1435) are human PCa cell lines purchased from ATCC. RMI-1 (cat#CRL-3310) is a mouse prostate cancer cell line from ATCC. The cells are used at low passage after purchase and tested monthly for mycoplasma contamination. Cells are passed whenever they reach 70% confluence. DU145 and PC3 cells are cultured in DMEM medium (Gibco), LNCaP cells are cultured in RPMI1640 medium (Gibco). Culture medium is supplemented with 10% FBS (Dutscher) and 1% penicillin/streptomycin (100 U/mL and 100 μg/ml respectively (Gibco). Cells are incubated at 37°C with 5% CO2. For the inhibition of eIF5Ahyp cells were treated with GC7 (N‐guanyl‐1,7‐diaminoheptane synthesized by AtlanChim Pharma, Nantes, France and Sigma-Aldrich) at 40µM for 24h in all the experiments.

To generate cell lines and tumoroids that express IPTG-inducible shDHPS, we infected the cells with lentivirus containing plasmid pLKO-puro-IPTG-3xLacO which holds: Clone TRCN0000330717, ref seq NM_001930 (Sigma-Aldrich) and then the cells were selected with puromycin 1µg/ml for 1 week, to inhibit DHPS the cells were induced with IPTG 250µM for 5 days.

We also generated cell lines and tumoroids expressing shCtl, shMRPP3 and shDHPS by infecting them with lentiviruses containing the plasmids: (pLV[shRNA]-EGFP/Neo-U6>Scramble_shRNA), (pLV[shRNA]-EGFP:T2A:Neo-U6>hPRORP[shRNA#1](VB900138-9190phn),(pLV[shRNA]-EGFP:T2A:Neo-U6>hDHPS[shRNA#1] (VB900141-4950rcu) and we selected resistant clones with Geneticin 400µg/ml (Gibco) for 3 weeks. . To overexpress MRPP3 protein, we inset the MRPP3 coding sequence (addgene plasmid #67866) into FUmGW plasmid (addgene plasmid #22479) and selected resistant cells with 300 µg/ml zeocin (Thermofisher) for 4 weeks.

Patient-derived prostate cancer tumoroids
Patient-derived tumoroid MSK-PCa1 (AR-, Syp-), MSK-PCa3 (AR+, Syp-), MSK-PCa4 (AR-, Syp+) and normal prostate organoids (AR+, Syp-) are obtained through a collaboration with Yu Chen's laboratory (MSKCC, New York) and were maintained in the culture medium as described previously23, the culture medium was refreshed every 3 days and the tumoroids are passaged every 2 weeks.

To measure the size of the tumoroids, 10000 cells per well were seeded in a 24 well plate. After one week of growth, the tumoroids were treated for another week with GC7 at 80µM, or IPTG (500µM) to induce the expression of shDHPS, the medium containing the treatment was replaced every 3 days, and at the end of the treatment the tumoroids are fixed with 4% PFA for 20min on ice. The tumoroids and organoids were imaged with microscope (EVOS) and the size was measured using Cell Profiler software. The number of tumoroids measured for Fig. 2b is as follow: for MSK-PCa1, 3474 (Ctl) and 3778 (GC7); 1477 (shDHPS-) and 1964 (shDHPS+); for MSK-PCa3, 1743 (Ctl) and 1212 (GC7); 1520 (shDHPS-) and 1890 (dhDHPS+); and for MSK-PCa4, 3,167 (Ctl) and 3,260 (GC7); 3167 (dhDHPS-) and 3260 (shDHPS+). For Fig. 6c: 1379 (Ctl) and 932 (GC7).

Invasion assay with tumoroids
To study invasion, tumoroids cultured for a two-week period were transferred into a 2mg/ml collagen matrix at pH7. After 48h tumoroids were fixed with 8% PFA solution on ice for 4h, then permeabilized with a 0.5% PBS triton solution. The tumoroids are labelled with DAPI (Sigma-Aldrich) and phalloidin (Thermofisher) and imaged using a Nikon confocal microscope. The number of tumoroids counted for the invasion assay in Fig. 2D is as follows: 54 (Ctl) and 60 (GC7).

Cytometry analysis of tumoroids
Tumoroids were treated 24 hours with 80µM GC7 or 6 days with 500µM IPTG to induce the shDHPS before analysis. Treated or untreated tumoroids were recovered on ice and after dissociation, fixed and permeabilized with Cytofix/cytoperm solutions (BD biosciences). After saturation with 3% BSA the cells were labelled with primary antibody hypusine (ProteoGenix), MRPP3 (Abcam), then the corresponding secondary antibody (Thermofisher). The cells are then analyzed with VYB cytometer (Miltenyi Biotec).

FUCCI reporter system in tumoroids.
To investigate the cell cycle in tumoroids, the Fucci reporter system was generated. Tumoroides were infected with lentivirus to express the plasmid pBOB-EF1-FastFUCCI-Puro (Addgene Plasmid #86849). After selection for 1 month with puromycin 1µg/ml, the tumoroids were treated with GC7 80µM for 48h then imaged with a Nikon spinning disk microscope, or dissociated with TrypLE Express (Gibco), then analyzed through the VYB cytometer (Miltenyi Biotec) to determine the proportion of Green and mKO2 cells. We also used an Aurora cell sorter to separate green proliferative cells from red arrested cells and extracted RNA from each condition for Mt-RNA processing analysis.

RNA isolation and RT-qPCR
Total RNA was extracted on ice using TRIzol reagent (Invitrogen). One microgram of RNA was reverse transcribed into cDNA using the reverse transcription system (Promega). Then, the cDNA is diluted 100-times, and primers (Eurofins) (sequences in supplementary material) are used at a concentration of 500nM in a final volume of 10µL. Fast SYBR Green Master Mix (Thermofisher) is added, and the plate was read using a StepOnePlus System (Applied Biosystems) for qPCR analysis.

Animal experiments
For xenograft experiments, PCa cells (2.106 cells) were injected subcutaneously into 5-week-old male nude mice (strain: Rj:NMRI-Foxn1nu/Foxn1nu) mice (Janvier). Mice were injected daily with 100µL of PBS or GC7 (10mg/mL/kg/day), and tumor size was measured twice a week. Tumor volume was determined using the following equation (π/6) × A × B² (A = larger tumor diameter, B = smaller tumor diameter), as previously described55. The maximum tumor size permitted by our ethics committee is 1 cm³; however, none of the tumors in this study reached that limit. The experiments were concluded based on predefined timelines and humane endpoints, in compliance with EU Directive 2010/63/EU. Experiments for the DU145 model were terminated after 28 to 31 days, for the PC3 model after 20 to 25 days, and for the RM-1 model after 10 days, following prior assessments of tumor growth.

For the orthotopic prostate xenograft, PC3 cells expressing the Luciferase gene and shCtl, shDHPS or shMRPP3 (7. 105 cells) were mixed with Matrigel (Corning) in a 1:1 ratio and injected into the anterior lobe of the prostate of 6-week-old male NOD-SCIDγ mice (Envigo). Abdominal incisions were reclosed with sutures. Animals were monitored once week for 50 days using a photon imager (Biospace Optima System system). For Biospace analysis the animals were injected with luciferin (Revvity) (1.5mg/mouse). At the end of the experiments the size of the tumors was monitored, prostate, lungs, kidneys, liver, spleen and digestive tract were harvested and analyzed. We decided to end the experiment after 50 days, based on our previous studies using the same model, when metastasis appeared25.

In vitro migration and invasion assays
Migration and invasion assays were carried out as previously detailed6. Cells deprived of serum for 24h were plated onto transparent PET inserts with 8.0µm pores (Corning). For invasion assays, Boyden chamber inserts were coated with extracellular matrix (Sigma-Aldrich) that was diluted at a ratio of 1:10. The bottom surface of the transwells was immersed in medium containing 10% FBS and fibronectin (10µg/ml) (Santa Cruz). After 6h for migration assays and 24h for invasion assays, the upper surface of the Boyden chamber was gently wiped clean with a cotton swab. Cells that migrated through the insert were then fixed, stained with DAPI (2mg/ml), imaged using an EVOS microscope (Life Technologies) and counted using ImageJ.

Cell cycle analysis
Cells were cultured at a density of 2.105 cells/well in 6-well culture plates, they were trypsinized and fixed with 70% ethanol. After treatment with 100 µg/mL RNase (Invitrogen), cells were incubated with propidium iodide (32µg/ml) for 30min at 4°C and analyzed using the MACSQuant® Analyzer 10 flow cytometer (Miltenyi Biotec).

Electron microscopy
This experiment was carried out as reported27. Cells were fixed using 1.6% glutaraldehyde in 0.1 M phosphate buffer (pH 7,4) at room temperature (RT) and subsequently at 4°C for 16h. After washing with sodium cacodylate buffer 0.1M (pH: 7,4), samples were processed for 1h at RT with 1% osmium tetroxide and 1% potassium ferricyanide in 0.1M sodium cacodylate buffer (pH: 7,4). Cells were then washed with distilled water, dehydrated with ethanol and embedded in epoxy resin. Thin sections of 80µM are contrasted with lanthanides (Gadolinium 5%, Samarium 5%) and observed with a transmission electron microscope JEM1400 (JEOL) with Morada CCD camera (Olympus SIS). Mitochondrial circularity was measured and analyzed using Image J. In Fig. 3h, the number of mitochondria analyzed is as followed: Ctl (n=295), GC7 (n=416), shDHPS- (n=271) and shDHPS+ (n=203).

Analysis of mitochondrial protein synthesis
Cells seeded in 150mm dishes at 80% of confluence and treated with puromycin (20µg/ml) for 20min. As a positive control, cells are treated with 100µg/ml chloramphenicol (Sigma-Aldrich), a mitochondrial translation inhibitor, for 24h. Cells were then rinsed with PBS, scrapped and mitochondria extracted using the mitochondrial extraction kit (Thermofisher) following the manufacturer's instructions. Isolated mitochondria were fixed with 2% PFA and permeabilized with 0.1% saponin buffer (Sigma-Aldrich) for 5min at 4°C. Saturation was performed using 3% FBS for 30min. Mitochondria were then stained with anti-puromycin antibody (Sigma-Aldrich) followed by the incubation with anti-mouse secondary antibody (Thermofisher). TOM22 coupled antibody (Miltenyi) was used for additional staining. Fluorescence was analyzed using the Aurora cytometer. Anti-TOM22 coupled antibody (Miltenyi) was used for additional staining. Fluorescence was analyzed using the Spectra Aurora flow cytometer (Cytek) equipped with 5 lasers.

Protein synthesis assay.
To measure protein synthesis, 2µg/ml puromycin is added to the DU145 culture medium and 50µg/ml puromycin is added to DU145 cells expressing plKO shdhps, for 15min and a positive control is also performed with cycloheximide (10µg/ml) which inhibits protein synthesis, added 20min before the addition of puromycin. The cells were then washed with PBS on ice and the proteins were extracted. An immunoblot was carried out by migrating 20µg of protein, and the anti-puromycin antibody was applied (Sigma-Aldrich).

Immunofluorescence
For immunofluorescence assay, cells were fixed with 4% PBS/PFA for 15min and then permeabilized with 0.2% triton solution for 5 minutes. Cells were then saturated with 1% PBS/BSA for 45min and incubated with primary antibody anti-eIF5A (Bdbiosciences), anti-tom20 (BD Transduction Laboratories) (1/300) overnight at 4°C and coupled secondary antibody (1/400) (Life Technologies) for 1h. Nuclei were labelled using Dapi (Sigma-Aldrich) and images were taken using a Nikon A1R confocal microscope. Mitochondrial branch length was measured using the Mitochondria Analyzer plugin in Fiji (version 1.54f). In Fig. 3B, the number of branchs analyzed is as follow: Ctl (n=21), GC7 (n=20), shDHPS- (n=21) and shDHPS (n=29. Colocalization analysis was performed using the JaCoP plugin in Fiji to assess the degree of overlap between fluorescent signals.

Immunoblotting
Immunoblots were conducted as described previously6. Cells were lyzed using RIPA lysis buffer (Thermo Fisher) complemented with protease inhibitors (Mini-complete, noEDTA, Roche). Protein quantification was done using a BCA assay. Proteins were denatured with Laemmli buffer and 20µg of protein was loaded on the SDS-PAGE gel. The proteins were then transferred overnight at 4°C to a polyvinylidene difluoride (PVDF) membrane (Millipore). The membrane was blocked with 3% BSA for 1h, followed by incubation with primary antibodies anti-hypusine (ProteoGenix), anti-eIF5A (Bd Biosciences), anti-DHPS (Bethyl Laboratories), anti-ERK2 (Santa Cruz), anti-HSP90 (Santa Cruz), anti-MRPP3 (Abcam). After rinsing, the membranes were incubated with secondary antibodies anti-rabbit or anti-mouse conjugated to a horseradish peroxidase (Promega). ECL (Millipore) was used for detection on a Syngene PXi imager. All uncropped immunoblots are provided in the Source Data file.

RNA-seq
Cells cultured in a 6-well plate were detached in 1X PBS, resuspended cells were centrifuged at 1500 rpm for 5min, then the supernatant was discarded, and the cell pellet was collected. The sample was immediately frozen in − 80℃ and shipped to BGI (Hong Kong) along with adequate dry ice to be analyzed. The data were analyzed using different platforms. Coverage data across the tRNA region and gene body were normalized by the total number of reads, followed by conversion to Counts per Million (CPM) for each condition (Control, GC7). This normalization accounts for differences in sequencing depth, allowing for comparison across samples. The pSlot compares coverage trends across these genomic regions.

Polysome profiling
DU145 Cells were seeded at 106 cells/1 0cm dish, treated with 40µM CG7 48h later (D0) during 24h. At the end of this treatment, cells were treated 10min with emetin (Sigma-Aldrich) 25µg/ml, washed twice with PBS, and harvested by trypsination. Cytoplasmic lysates were prepared by incubation of cells 10min in hypotonic buffer (10mM Tris-HCl pH 7.4, 0.5mM MgCl , 10mM KCl, 1X CompleteTM EDTA free protease inhibitor (Roche) and 10U/mL RNAseOutTM (Invitrogen). Cells are disrupted by shaking in presence of ceramic beads (10sec at 4500rpm in a Precellys Evolution homogenizer). Nuclei were pelleted by centrifugation at 750 g for 5min at 4°C, and mitochondria were pelleted by centrifugation at 12,000 g for 10min at 4°C. The protein content of the cytosolic extract was measured by Bradford assay and samples containing 2mg protein were loaded on top of 15–50% sucrose gradients poured using the Gradient Master (Serlabo Technologies). After ultracentrifugation at 250 000g during 105min at 4°C on a SW41 Beckman rotor, fractions of 700µl each were collected from each gradient while 254nm absorbance profiles were generated using an ISCO UA-6 detector.

Polysome sequencing
RNA sequencing: RNA extractions were sequenced on an Illumina Novaseq6000 machine with a paired-end protocol. Libraries were prepared with the TruSeq mRNA kit.
RNA-seq Preprocessing: Raw sequencing reads were aligned on the human genome (GRCh38) using STAR (v2.7.8a), with the annotation of known genes from gencode v37. Gene expression levels were then quantified using Salmon (1.4.0) and the annotation of protein coding genes from gencode v37.
Differential expression analyses & Candidates Deregulated Genes selection: Differential expression analyses were conducted on untreated and treated samples using DESeq2 (v1.40.2), with independent processing of the POLY and CYTO cohorts. Genes lacking adjusted p-values due to low coverage were excluded, and log2 fold changes were corrected using the APEGLM shrinkage method (apeglm v1.22.1). A significance threshold (adjusted p < 0.05) and a log2FC cutoff of 1 were applied for both cohorts. Genes were categorized based on significance and direction of expression changes, distinguishing shared (BOTH_DOWN/UP) or cohort-specific (CYTO_DOWN/UP or POLY_DOWN/UP) regulation.
To better identify genes with non-parallel expression changes between CYTO and POLY, we applied a three-step filtering approach. Genes significantly associated with treatment in at least one cohort were retained. A ratio of mean expression changes in POLY vs. CYTO (thresholds >2 or <0.5) was used to detect gene expression inflation or deflation. Finally, a t-test (p < 0.05) assessed the significance of differences in expression changes between POLY and CYTO. Genes were classified as TRANSLA when changes were driven mainly by translation, BUFFER when transcriptional changes were counteracted by translation, and STAB when expression was not statistically different between transcriptional and translational levels. All these analyses were performed in R v4.3.1.
Bioinformatics Analysis: Sequencing was performed by the Cancer Genomics Platform (CRCL), RNA-seq quality controls and pre-processing were handled on the Gilles Thomas Bioinformatics platform (CRCL-CLB). RNA-seq Analyses were conducted collaboratively between the Gilles Thomas Bioinformatics Platform and the RibosOMICS Platform (CRCL).

Proteomic analysis
The cell pellets were lysed in RCIPA buffer and 15ug of protein samples were stacked on NuPAGE™ in a single band to perform trypsin digestion before mass spectrometry analysis using an Orbitrap Fusion Lumos Tribrid Mass Spectrometer (ThermoFisher Scientific, San Jose, CA) in data-independent acquisition mode (DIA). Protein identification and quantification was processed using the DIA-NN 1.8 algorithm 56 and DIAgui package (https://github.com/marseille-proteomique/DIAgui 57.

Nuclear-Cytoplasmic Fractionation
The fractionation was performed as previously described58. Cells were harvested, washed with PBS, and centrifuged 400rcf. They were then resuspended in 0.1% NP-40 supplemented with RNAsine (Promega), which lyses the cytoplasmic membrane, allowing the collection of the cytoplasmic fraction. The lysate was centrifuged at 10000rcf to pellet the nuclei. The supernatant, containing the cytoplasmic fraction, was collected, and the nuclei were washed three times with 0.1% NP-40. Following this, approximately 50 passes through a 30G syringe were performed to ensure proper nuclear lysis. RNA was then isolated using TRIzol (Invitrogen).

RIP-qPCR
Cells from two 10cm dishes were harvested, washed with PBS, and lysed using an RNase-free lysis buffer (50mM Tris, 100mM NaCl, 0.1% SDS, 0.5% sodium deoxycholate, 5mM NaF, 5mM sodium pyrophosphate, 1% NP40, complemented with protease inhibitors). After 30min of gentle agitation, the lysate was centrifuged at 14,000g for 15min. The supernatant was collected, and the protein concentration was measured using a BSA assay. Protein G beads (MedChemExpress) were washed twice with the lysis buffer, and 30µl of beads were added to the lysate for 30min at 4°C to eliminate non-specific binding proteins. After centrifugation, the supernatant was collected, and 1% of it was set aside as input for analysis.
eIF5A was immunoprecipitated using 10µg of anti-eIF5A antibody (BD Biosciences) and 100µl of Protein G beads overnight. In parallel, a control immunoprecipitation was performed using an anti IgG antibody (Sigma-Aldrich) to account for non-specific binding. The next day, the beads were recovered by centrifugation and washed five times with a high-salt RNase free buffer (50mM Tris, 300mM NaCl, 0.1% SDS, 0.5% sodium deoxycholate, 5mM NaF, 5mM sodium pyrophosphate, 1% NP40, complemented with protease inhibitors). RNA was then isolated from the beads using TRIzol. The isolated RNA was subjected to RT-qPCR to analyze the enrichment of specific RNA molecules, following the protocol provided by Thermo Fisher Scientific.

Primer sequences used for RIPq-PCR and qPCR.
(mt)pre-tRNAVal fw ACGAGCTCTAAGTGTACTGGAAA; (mt)pre-tRNAVal rv GGGCAAGTTAAGTTGAAAT; (mt)pre-tRNAIle fw GCGAATTCAATCTCCAGCA; (mt)pre-tRNAIle rv GAAATAAGGGGGTTTAAGC; GAPDH mRNA fw CCCACTCCTCCACCTTTGAC GAPDH mRNA rv CCACCACCCTGTTGCTGTA; 18S rRNA fw CATTCGAACGTCTGCCCTATC; 18S rRNA rv CGTCACCCGTGGTCACCAT; Mrpp3 fw GGAAGCACATGCTAAGACGGAG; Mrpp3 rv GTGCAGTGTGGCATACAGAAGG
RPLP0 fw TGGTCATCCAGCAGGTGTTCGA; RPLP0 rv ACAGACACTGGCAACATTGCGG
Myc fw CCTGGTGCTCCATGAGGAGAC; Myc rv CAGAECTCTGACCTTTTGCCAGG; Ki67 fw GAAAGAGTGGCAACCTGCCTTC; Ki67 rv GCACCAAGTTTTACTACATCTGCC.

Metabolite profiling via LC-MS.
Metabolomic analysis was performed as previously described 6. Cells from three 10cm dishes at 70% confluence were refreshed with serum-free medium overnight. Metabolites were extracted using 4ml of 80% methanol. The samples were centrifuged for 5min at 3000rcf to pellet the insoluble material. Two additional extractions were performed on the insoluble pellet using 0.5ml of 80% methanol, followed by centrifugation for 5min at 16,000g at 4°C. The 5ml extracted metabolites were pooled and dried under nitrogen gas using an N-EVAP system (Organomation Associates, Inc). The dry pellet was resuspended in 20µl of HPLC-grade water for mass spectrometry, and 7µl of the suspension was injected into a 5500 QTRAP triple quadrupole mass spectrometer (AB/SCIEX) coupled to a Prominence UFLC HPLC System (Shimadzu) for the analysis of 300 endogenous water-soluble metabolites via selected reaction monitoring for steady-state analysis of the samples. We used Metaboanalyst 6.0 to carry out the analyses.

Stable isotope tracing analysis
For 13C6 glucose tracing, cells were cultured in triplicates in 10cm dish. After being washed with PBS, glucose-free DMEM supplemented with 10% dialyzed FBS, and containing the tracer (13C -D-glucose) at a 25mM final concentration (Sigma-Aldrich), was added for 2h. Cells were washed with PBS and rapidly fixed with cold 80% methanol. The cell suspension in methanol was collected and centrifuged at 21,000 rcf for 5min at 4°C. The supernatant was collected, and the cell pellet resuspended with 500µl of methanol solution. It was centrifuged again at 21,000rcf for 5min at 4°C. The supernatants collected were dissolved in 8M urea (10mM Tris, pH 8.0) at 60°CS. The samples were then dried using a nitrogen gas apparatus (N-EVAP) and subjected to LC-MS analysis.

Prostate tumor database analysis
We analyzed transcriptomic data from the GSE70770 databases of normal and tumor human prostate tissue, and used Phantasus software v1.11.0 (https://artyomovlab.wustl.edu/phantasus) 59 to perform differential expression, analysis of polyamine pathway genes in different normal and tumor samples. We used the CANCERTOOL Website to analyze DHPS expression in different prostate cancer databases 20.

Glycolysis and mitochondria respiration
Oxygen consumption rate (OCR) was measured in real time using the Seahorse XF96 Extracellular Flux Analyzer (Agilent) following the instructions of the manufacturer. Prior to the assay, cells were starved of glucose for 1h, then glucose (10mM), oligomycin (1µM), 2,4-Dinitrophenol (DNP, 10µM) and a mixture of rotenone and antimycin A (1µM each) were added sequentially added at specific time points during the assay. After each experiment, the protein content was quantified for standardization. No significant variation was observed in protein levels.
To measure the OCR on patients derived from tumoroids, approximately 150 tumoroids were plated in 10µl of Matrigel matrix (Corning) per well in a 96-well plate. After 48h, the tumoroids medium is changed to a glucose-free medium for 1h and then injected successively to obtain a final concentration of 20mM glucose, 4µM oligomycin, 40µM DNP, 4µM Antimycin and 4µM Rotenone.

Single cell data analysis
Single-cell RNA sequencing data from the GSE193337 dataset 16 were analyzed with RStudio (version 4.3.1) and SCeurat (version 5.0). Cell-type annotation was performed using the scType Cell Marker Database. Four patient datasets were integrated for the analysis. Epithelial cells were identified as a result of merging subclusters corresponding to club cells, basal cells, and other epithelial subtypes. A threshold for dividing the epithelial cells into DHPS-high and DHPS-low subclusters was set based on DHPS gene expression, with a cutoff of <1.2. We have performed pathway enrichment analysis using the fgsea package.

Schematic illustrations.
All the schematic illustrations were created in BioRender.

Peer review rounds
[{"round": 1, "reviewer_comments": {"reviewer_1": "This manuscript analyzed the effect of hypusination on the development of prostate cancer. In silico analysis highlights that genes encoding for the enzyme associated with polyamine and hypusine biosynthesis are increased in tissues from prostate cancer. This was confirmed at the protein level. Migration and invasion of established prostate cancer cell lines and tumoroids are reduced by DHPS knockdown or DHPS inhibition by GC7. These treatments also decreased cell division and increased cell cycle arrest of tumoroids. Further, development of xenografts of DU145 and PC3 human cell lines was impaired by shDHPS or GC7. Immunodeficient mice receiving an orthoptic injection of human PC3 cells with shDHPS in the prostate exhibit reduction of growth and metastasis compared to control animals. A metabolomics and a proteomics investigation in cells +/- shDHPS revealed that hypusination supports the TCA and mitochondrial metabolism in prostate cancer cells, notably by supporting the translation of the PPR protein MRPP3. Then, the authors confirmed that MRPP3 was regulated by hypusination through well-designed targeted approaches. Last, silencing of MRPP3 dampens mitochondrial activity and growth and metastasis of prostate cancer cells. Importantly, overexpression of MRPP3 in cells with low levels of EIF5A-Hyp restores tumor growth in the xenograft model. Overall, this paper is well written and the role of hypusine/MRPP3 pathway on the growth of prostate cancer cells is supported by numerous complementary experiments. However, further experiments are required to verify the phenotypes associated with the molecular tools used by the authors, notably the overexpression of MRPP3 gene in cells with DHPS silencing. Here are my comments: Major 1/In Fig. 1b, please be more specific about the gene EIF5A. Is it EIF5A1 or EIF5A2? By the way, it should be indicated in the introduction that EIF5A is encoded by two genes. Please, include a column for the average fold-change in this figure. 2/ It is not clear to me why the authors used ERK2 as house-keeping protein in Fig. 1e. This should be explained and/or supported by the literature. The densitometry of EIF5A-hyp/EIF5A should be performed to determine whether the level of hypusination is mainly due to increased EIF5A level of the activity of DHPS. 3/ Apoptosis of prostate cancer cell lines should be included in the paper (see line 151). 4/ To anticipate a putative therapeutic approach using GC7, it is critical to determine whether GC7 and/or shDHPS affect the growth of organoids derived from normal epithelial prostate tissue. 5/ For Fig. 2b, what was the concentration of GC7? I do not quite understand the quantification: The tumor size is relative to what? To my opinion, this figure should depict the mean of the size all counted organoids. There is no rationale to compare one specific organoid in GC7-treated well to another specific organoid in the control group. Please explain more clearly this analysis. Moreover, on Line 155, the authors states that the number of tumoroid is reduced; this is not shown/quantify. In the contrary, there were more tumoroids quantified in the GC7/shDHPS-treated groups. Last, the fact that hypusine synthesis is more reduced by gene silencing than by GC7 but that tumoroid size is more decreased by GC7 compared to shDHPS is concerning. This should be discussed. 6/ Please, indicate when the GC7 treatment began in Extended Data Fig. 2g? 7/ The level of EIF5A-Hyp should be investigated in the tumors in both xenograft models (GC7, shDHPS). 8/ It is essential to demonstrate whether hypusination affects the TCA cycle in prostate cancer cells directly through the translation of enzymes involved in this pathway or indirectly, through a PPR-dependent effect on mitochondria? 9/ The hypusine consensus sequence is AAAUGU sequence, not AAAGUG (line 283). 10/ Why the translocation of MYC mRNA to the cytoplasm is inhibited by GC7 (fig. 5e) if MYC mRNA is not a target for EIF5A-Hyp (Fig. 5a)? Is MYC involved in prostate cancer? Is MYC found in the proteomic analysis? 11/ The authors clearly showed that hypusination regulates MRPP3 translation. When they overexpress the gene encoding for MRPP3, the phenotype associated with DHPS silencing is reversed. However, if DHPS is knockdown, the level of MRPP3 protein should be still low since the machinery for its translation is reduced, even if the gene is more expressed. Do the authors think that overexpressing a gene can counteract a reduction of hypusination? Please, show MRPP3 protein levels in the tumors of the different groups. 12/ The paper would be greatly improved using a syngeneic model of prostate cancer. Minor comments: 13/ The schema of biosynthesis of EIF5A-Hyp in Fig. 1a is not accurate. DHPS uses spermidine and the Lys50 of EIF5A as substrate. Same remark for Extended Data Fig. 2b. 14/ In the abstract and Introduction (lines 47 and 68), put the abbreviation in parenthesis after the complete name of the protein. 15/ In general, remove the P value from the text since they are shown in the figures. 16/ Line 939: do not capitalize Primary. 17/ Please, describe the epidemiology, etiology, and disease progression of prostate cancer as a first paragraph of the introduction. 18/ Fig. 1h should appear before Fig. 1e, since it is a transcriptomic analysis. 19/ Describe more specifically Fig. 2a in the Results section. Why the authors did not use a western blot? At which time point was performed the analysis of EIF5A-hyp level? 20/ The legend of Fig. 6f needs revision. 21/ Fig. 5b should be included in the Extended Data. It is already known that hypusination is required for nuclear translocation. 22/ In Fig. 6f, I suggest writing ‘EV + shCtl’, ‘MRPP3 + shDHPS’, etc… instead of ‘EV shCtl’, ‘MRPP3 shDHPS’, etc… 23/ The last paragraph of the Discussion should be developed. Define RBP. What are the clinical implications of their discovery about the essential role of hypusination in prostate cancer. 24/ Include a paragraph about Statistics in the Methods section", "reviewer_2": "In the present work Kahi and colleagues propose that the polyamine-regulated EIF5A protein promotes prostate cancer growth and metastasis by regulating the nuclear export and localization of MRPP3 mRNA, which encodes a protein essential for mitochondrial tRNA (mt-tRNA) maturation. Through loss of function studies, they show that the inhibition of hypEIF5A and MRPP3 impair mitochondrial metabolism and translation, thus establishing a connection between this translation factor, mitochondrial function and cancer aggressiveness. The translation factor EIF5A has been previously shown to regulate translation of protein involved in autophagy, polyamine homeostasis, mitochondrial metabolism or cell proliferation/viability. The findings presented herein add further complexity to the mode of action of this protein and further emphasize the potential value of targeting hypusination for therapeutic purposes. Overall, the paper is well written, the story is original and supported by several elegant and solid experimental approaches. The following points should be addressed to improve the quality of the manuscript: - In very recent Nature paper from the Fendt group (DOI https://doi.org/10.1038/s41586-024-08335-7) it was shown that hypusinated EIF5A regulates cancer metastasis in response to aspartate content in the TME. By stimulating NMDA receptors, asp was shown to increase intracellular calcium content, leading to CREB-mediated induction of DOHH transcription, increased EIF5A hypusination and consequent translation of TGFbeta targets involved in metastasis. It would be worth to try to connect the present findings with those from the Fendt group. Is the mechanism described here only applicable to prostate cancer? Are there potential overlapping steps? - Figure 1: there are two members of EIF5A proteins: EIF5A1 and EIF5A2. Since previous studies have shown that EIF5A2 is upregulated in some cancers and involved in metastasis, including prostate cancer metastasis (https://doi.org/10.1038/s41420-021-00764-x ), analysis of EIF5A2 should be conducted along with that of EIF5A1. Also, please normalize the levels of hypEIF5A to total EIF5A rather than ERK2 and show the OS also for EIF5A1 and 2. - Figure 2: can the authors provide evidence of the effect of DHPS inhibition on cell proliferation (i.e. BrDU staining or cell proliferation rate) in their cell lines? In addition, since in figure 2g it is difficult to visualize the metastases quantified in Figure 2h (same also in Figs 6g and 6h), can the authors show the luminescence on the explanted organs? - Figure 3: can the authors show the whole list of the 71 metabolites identified by MS in a table? - Figure 4: Most of the experiments in this figure are conducted with GC7. A previous paper from the Kahana group (DOI 10.1074/jbc.M110.106419) showed different polysomal profiles in response to GC7 (inhibition of initiation) compared to EIF5A knockdown (inhibition of elongation). This should be addressed. Also, a table with the list of proteins identified by MS would be helpful. - Figure 5: GC7 treatment is shown to increase the nuclear enrichment of MRPP3 and C-MYC, suggesting that hypusination may regulate their shuttling. However, while MRPP3 mRNA is shown to associate with EIF5A, MYC mRNA seems to be slightly enriched although not significantly. This result is somehow puzzling, authors may increase the number of replicates in Fig. 5a to see if statistical significance can be reached or delete the C-MYC data or provide an explanation for the observed discrepancy. Is C-MYC content regulated by GC7 as previously shown (doi: 10.1038/s41419-020-03174-6)? - A graphical abstract would be helpful.", "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": "In this manuscript, Kahi et al. address the role of the eIF5A hypusination in prostate cancer (PCa). They propose that this axis is upregulated in PCa. At the mechanistic level, the authors proposed a model for which eIF5A-hyp regulates translation through the control of the nuclear export of MRPP3 mRNA that controls mitochondrial metabolism, a critical step for tumor growth. The manuscript builds on previously published data supporting the role of eIF5A-hyp in mitochondrial metabolism and translation in other cancer types. However, there are major weaknesses that reduce the potential impact of this study in the field of PCa. The main concern is the lack of a proper interrogation of the human relevance of this axis in PCa in the context of the current knowledge. There is no clear identification of which prostate tumors depend on eIF5A and are, therefore, vulnerable to the inhibition of this pathway. Is eIF5A-hyp relevant in primary PCa, or in CRPC? Is it more critical just in metastasis? Is there any connection with the androgen receptor status? The experimental approach mixes different cell lines and models without considering these critical variables in PCa. Furthermore, the experiments lack proper controls to show that tumors without upregulation of the eIF5A-hyp are not sensitive to its inhibition. Similarly, there is no strong rationale for identifying MRPP3 as the primary target downstream. The data presented in this study are too preliminary, do not have the robustness required to demonstrate the proposed model, and the quality of the manuscript does not reach the expected level for its publication in Nature Communications. Specific points: Fig. 1 and Extended Fig. 1. The data of these Figures show the expression of different components of the eIF5A hypusination pathway using several public datasets but in a scattered manner, independently analyzing different components in each dataset. Is there a correlation between DHPS, EIF5A and DOHH mRNA levels in the datasets of Figs. 1b, 1h and Ext Fig. 1c (TCGA)? How is the expression of EIF5A and DOHH in Fig. 1h? A more thorough investigation, including analysis of public datasets with CRPC samples split by adenocarcinoma or neuroendocrine, needs to be included. In Figs. 1c,d and Ext Fig. 1a,b: violin and UMAP plots for the expression of DHPS, EIF5A and DOHH in the different cell populations need to be shown. Ext. Fig. 1c: How are low vs high DHPS patients defined? What is the expression of EIF5A and DOHH in those patients? Are EIF5A levels predictors of poor survival as concluded (but not shown) in the results section of Fig. 1? According to Figs. 1b and 1c, EIF5A levels are upregulated in tumors compared to normal samples. However, there is no clear upregulation of EIF5A levels in Fig. 1e (not quantified). This discrepancy needs to be addressed. Fig. 2 and Extended Fig. 2. The in vitro cell systems used to investigate the role of eIF5A needs to be better characterized from the point of view of eIF5A hypusination to be able to show a direct dependency. What are the levels of eIF5A-hyp and DHPS in the different cell lines and prostate tumoroids? All the prostate lines used are prostate cancer cell lines and need to be compared to a normal prostate cell line. Western blots of Ext Fig. 2a,b needs to be run all together and with a normal cell line. Similarly, the tumoroids used represent a diverse biology mimicking different PCa subtypes. MSK-PCa1 is an AR-/Syp-, MSK-PCa3 is AR+, and PCa4 is AR-/Syp+. How is the eIF5A hypusination axis in the different subtypes? Is there any correlation with the response to inhibition of the pathway and the specific activation of this axis in a particular subtype? The proper control of knock-down of shDHPS and GC7 on eIF5A-hyp on tumorids needs to be shown by WB. Based on the FACS data, there is no correlation between the degree of inhibition of hypusination by GC7 and shDHPS in the different tumoroids and the impact on tumoroid size. Fig. 3 and Extended Fig.3. Why do LNCaP cells respond very differently from DU145 in OCR with almost no effect of shDHPS on maximal respiration if both cell lines are equally sensitive to inhibition of DHPS in terms of growth and invasion? Similar to the functional assays described in Fig.2, to demonstrate the dependency on eIF5A-hyp, a proper control showing that the effect is selective to those cell lines overexpressing eIF5A is required. Fig. 4 and Extended Fig. 4. Sequencing of the polysome profiling is required to identify the specific changes in translation. Translation changes cannot be directly inferred from the proteomic studies. Integrating ribosomal profiling and proteomic is necessary. Is there a correlation between the levels of increased translation and eIF5A-hyp in the different cell models? Is there a correlation between mitochondrial translation and eIF5A-axis in the same dataset analyzed in Fig. 1 and Ext Fig. 1? The increased translation linked to eIF5A-hyp needs There is no proper rationale for selecting MRPP3 as the main target of eIF5A. If MRPP3 is downstream of eIF5A, why does MRPP3 overexpression induce eIF5A-hyp (Fig. Ext 4h)? Is there a correlation at the protein levels of eIF5A-hyp/DHPS and MRPP3 in the tumor samples of Fig. 1e? There is no correlation between the downregulation of MRPP3 with GC7 in PCa3 (Fig. Ext. 4g) and the different functional readouts in the other Figures for this model. Fig. 6 and Extended Fig. 6. There is a disconnect between data on OCR comparing shDHPS (Fig. 3e) and shMRPP3 (Fig. 6a). If shMRPP3 is mimicking shDHPS, they should have similar effect. The in vivo experiments of Fig. 6e and f show similar tumor weights for the control group when the tumor volume is less than half at the endpoint in Fig. 6f as compared to Fig. 6e. How is that possible? Regarding the potential human relevance for MRPP3, the data of Fig. 6i is totally insufficient. To demonstrate that MRPP3 is the relevant target downstream of eIF5A in prostate cancer, it is critical to show the correlation of MRPP3 with eIF5A-hyp and DHPS in the same human samples in a proper cohort including advanced PCa since the authors aim to demonstrate its potential role in metastasis. In general, the quality of the data needs attention. Samples should be run together, and the quality of the immunofluorescence should be improved. There is no clear definition of whether the data represents biological or technical replicates."}, "author_response": "Dr Frédéric Bost INSERM U1065 Centre Méditerranéen de Médecine Moléculaire 151 route de St Antoine de Ginestière 06200 NICE France frederic.bost@univ-cotedazur.fr Nice, July 15th, 2025 Dear Reviewers, Thank you for reviewing our manuscript entitled “eIF5A hypusination regulates MRPP3 expression and mitochondrial tRNA processing to promote Prostate cancer aggressiveness\". We sincerely thank you for your relevant, useful, and constructive comments. We have addressed all of them to the best of our ability and the answers to specific points are addressed below in detail. Sincerely yours, Of note, modifications in the text are highlighted in red. ANSWERS TO THE REVIEWERS: Reviewer #1: We thank the reviewer for the positive feedback on our work, particularly noting that “the paper is well-written and the role of the hypusine/MRPP3 pathway in the growth of prostate cancer cells is supported by numerous complementary experiments.” The reviewer suggested additional experiments and provided valuable insights to enhance our manuscript. 1/In Fig. 1b, please be more specific about the gene EIF5A. Is it EIF5A1 or EIF5A2? By the way, it should be indicated in the introduction that EIF5A is encoded by two genes. Please, include a column for the average fold-change in this figure. ANSWER: We added the expression of eIF5A1 and A2 to figure 1b, however, as previously shown (Clement et al. 2006, PMID: 16519677) we confirm that eIF5A2 is very weakly expressed in prostate cancer cells. We also addressed the issue of the two isoforms of eIF5A : “There are two known highly homologous (91%) isoforms of eIF5A: eIF5A and eIF5A2 encoded by two different genes located on two different chromosomes. However, eIF5A2 expression is weak in the prostate (Clement, 2006 PMID: 4406228).” Finally, as requested, we added a column with the average fold-change and included the data obtained with both isoforms in the new Fig.1b, Ext Data Fig. 1d-j., Ext Data Fig. 2a-d. 2/ It is not clear to me why the authors used ERK2 as house-keeping protein in Fig. 1e. This should be explained and/or supported by literature. The densitometry of EIF5A-hyp/EIF5A should be performed to determine whether the level of hypusination is mainly due to increased EIF5A level of the activity of DHPS. ANSWER: We and others have used ERK2 as a loading control in previous articles (Kaminski et al. PMID: 31064849, Mizrachy-Schwartz et al. PMID: 17622357, Antherieu et al. PMID: 17503468). This kinase is ubiquitously and robustly expressed. As requested by the reviewer, we included the densitometry for eIF5Ahyp/eIF5A and confirmed the increase of hypusination in tumors (New Fig. 1j). 3/ Apoptosis of prostate cancer cell lines should be included in the paper (see line 151). ANSWER: The results of the Annexin V assay that monitors apoptosis in cells treated with GC7 and cells expressing shDHPS have been added to the new version of the manuscript (Extended Data Fig. 3e). They show that the inhibition of hypusination does not induce apoptosis. 4/ To anticipate a putative therapeutic approach using GC7, it is critical to determine whether GC7 and/or shDHPS affect the growth of organoids derived from normal epithelial prostate tissue. ANSWER: We performed experiments on normal human prostate organoids (Gao et al . PMID 4237931) with GC7 and we found that: “GC7 had minimal impact on the proliferation of organoids derived from normal prostate tissue (Extended Data Fig. 4b).” 5/ For Fig. 2b, what was the concentration of GC7? I do not quite understand the quantification: The tumor size is relative to what? To my opinion, this figure should depict the mean of the size all counted organoids. There is no rationale to compare one specific organoid in GC7-treated well to another specific organoid in the control group. Please explain more clearly this analysis. Moreover, on Line 155, the authors states that the number of tumoroid is reduced; this is not shown/quantify. In the contrary, there were more tumoroids quantified in the GC7/shDHPS-treated groups. Last, the fact that hypusine synthesis is more reduced by gene silencing than by GC7 but that tumoroid size is more decreased by GC7 compared to shDHPS is concerning. This should be discussed. ANSWER: We added the concentration of GC7 used for the treatment of tumoroids in the legend of Fig. 2a. We were not clear regarding the presentation of this figure and what we analyzed. Firstly, we present in the figure 2 the effects of the inhibition of hypusination on the growth of established tumoroids. We have analyzed the size of “n” tumoroids (the n indicated in the bar graph corresponds to the number of tumoroids measured) and we compared the mean of the size of the tumoroids treated with GC7 or expressing shDHPS to the size of control tumoroids at the end of the experiment. Besides, we did not explain the protocol very well, to clarify this issue we implemented the material and methods section (page 26): “To measure the size of the tumoroids, 10000 cells per well were seeded in a 24 well plate. After one week of growth, the tumoroids are treated for another week with GC7 at 80µM, or IPTG (500µM) to induce the expression of shDHPS, the medium containing the treatment is replaced every 3 days, and at the end of the treatment the tumoroids are fixed with 4% PFA for 20min on ice. The tumoroids are imaged with microscope (EVOS) and the size was measured using Cell.Profiler software. Between 1212 and 3778 were analyzed depending on the treatment and the tumoroids (Fig. 2b)”. In addition, we added a scheme in the new Figure 2 that summarizes the protocol. Regarding the differential effects of GC7 vs shDHPS: tumoroids were allowed to develop until day 8 without treatment before the addition of GC7 or IPTG (that induce the shRNA). The action of GC7 is more rapid than the downregulation of DHPS by IPTG, which may explain why GC7's effects are more pronounced over a period of 7 days of action. Secondly, the reviewer is right we did not include the effects of the inhibition of hypusination on the capacity to give tumoroids. Thus, we conducted an additional experiment in which GC7, or ITPG (to induce shDHPS) were added on day 0 (at the seeding). The results are shown in Extended Data Fig. 4a, we demonstrated that : “The treatment with GC7 and induction of shDHPS significantly decreased tumoroids formation capacities (Fig. 2b, Extended Data Fig. 4a).” 6/ Please, indicate when the GC7 treatment began in Extended Data Fig. 2g? ANSWER: We indicated with an arrow on the graph when GC7 was added in the new Extended Data Fig. 4 e,g (Former Fig. 2g). 7/ The level of EIF5A-Hyp should be investigated in the tumors in both xenograft models (GC7, shDHPS). ANSWER: As requested by the reviewer we have quantified the level of eIF5Ahyp in the vivo experiments to validate the specific effects of our intervention on tumor growth (Ext Data Fig. 4, d, f, h ,I, Ext Data Fig. 9g,h, Ext Data Fig. 10a,d). 8/ It is essential to demonstrate whether hypusination affects the TCA cycle in prostate cancer cells directly through the translation of enzymes involved in this pathway or indirectly, through a PPR-dependent effect on mitochondria? ANSWER: In the new figure 4g, we show that the inhibition of hypusination inhibits the expression of mitochondrial enzymes that regulate the TCA cycle. In this experiment, we demonstrate that the expression of MRPP3 partially reverses the inhibition induced by GC7, thus, we show that there is a direct link between Hypusination-MRPP3 and expression of TCA cycle enzymes. These new results are included in the new version: “To reinforce the link between eIF5Ahyp, MRPP3 and TCA cycle, we demonstrated that overexpression of MRPP3 partially reversed the inhibition of isocitrate Dehydrogenase (NAD(+)) 3 Catalytic Subunit Alpha (IDH3A), Succinate Dehydrogenase Complex Flavoprotein Subunit A (SDHA) and Dihydrolipoamide Dehydrogenase (DLD), three enzymes implicated in the regulation of the TCA cycle {Puleston, 2019, PMID: 34216540} (Fig. 4g).” 9/ The hypusine consensus sequence is AAAUGU sequence, not AAAGUG (line 283). ANSWER: Thanks for noting this mistake, we changed it with the right sequence. 10/ Why is the translocation of MYC mRNA to the cytoplasm inhibited by GC7 (fig. 5e) if MYC mRNA is not a target for EIF5A-Hyp (Fig. 5a)? Is MYC involved in prostate cancer? Is MYC found in the proteomic analysis? ANSWER: The hypusinated form of eIF5A promotes MYC translation in colorectal cancer (Coni et al. 2023, PMID: 33303756), as mentioned in the discussion of the manuscript. Previous research has shown that eIF5A binds to MYC mRNA in colon cancer cells, which is why we used it as a positive control in our study. In the updated version of Figure 5a, we included additional experiments in DU145 and PC3 cell lines to demonstrate that, similar to colorectal cancer cells, eIF5A is associated with MYC mRNA. Furthermore, we demonstrate that GC7 slightly decreased c-MYC expression but to a less extend than MRPP3 MRPP3 (Ext Data Fig. 8a). Interestingly, leptomycin B an inhibitor of Exportin 1 (XPO1) that participates in the nuclear-to-cytoplasmic transport of MYC mRNA in hepatocarcinoma cells (Deutzman et al. 2024) also slightly inhibited c-MYC expression in PCa cells. Yes, MYC is overexpressed in prostate cancer and we now mention in the discussion that MYC plays an important role in this cancer. 11/ The authors clearly showed that hypusination regulates MRPP3 translation. When they overexpress the gene encoding for MRPP3, the phenotype associated with DHPS silencing is reversed. However, if DHPS is knockdown, the level of MRPP3 protein should be still low since the machinery for its translation is reduced, even if the gene is more expressed. Do the authors think that overexpressing a gene can counteract a reduction of hypusination? Please, show MRPP3 protein levels in the tumors of the different groups. ANSWER: The reviewer's insightful remark is correct. Indeed, we observed that under conditions where MRPP3 is overexpressed, the inhibition of hypusination (either by GC7 or shDHPS) reduces MRPP3 expression. However, this reduction remains higher in cells treated with GC7 or shDHPS alone (Fig. 4g and Extended data Fig. 7d, 9j, 10a,d). So, the translation machinery may be inhibited but not sufficiently to counteract MRPP3 mRNA gene overexpression. We have added the expression of MRPP3 in the mice tumors (New Ext Data Fig. 10a). 12/ The paper would be greatly improved using a syngeneic model of prostate cancer. ANSWER: The reviewer is right, the demonstration of the role of eIF5A hypusinated in a syngeneic model reinforces our conclusion. Thus, we performed in vivo experiments doing allograft injection of RM-1 cells (ATCC ref# CRL-3310) a murine prostate cancer cell line in C57Bl6J immunocompetent mice. RM-1 have been previously used in vivo in several studies, for example by Zhou et al. (PMID: 38569039), Chen et al. (PMID: 30841425), Liu et al. (PMID: 36046655), Xu et al. (PMID : 30841931), Yang et al. (PMID : 39127402) or Krzastek et al. (PMID : 29943070). Using this syngeneic model, we did an experiment with GC7, with RM-1 cells expressing shDHPS, RM-1 cells expressing shMRPP3 and a rescue experiment with MRPP3 expressing plasmid. We demonstrated that the treatment with GC7 as well as the downregulation of DHPS or MRPP3 inhibit tumor growth, furthermore, we confirmed that MRPP3 overexpression counteracted partially the anti-tumoral effects resulting from the downregulation of DHPS in the RM-1 syngeneic model (Fig. 2f, Fig. 6e, Ext Data Fig. 4g,h 10b-d). Minor comments: 13/ The scheme of biosynthesis of EIF5A-Hyp in Fig. 1a is not accurate. DHPS uses spermidine and the Lys50 of EIF5A as substrate. Same remark for Extended Data Fig. 2b. ANSWER: The reviewer is right and we have corrected the scheme in the new version of Fig. 1a., we also modified the scheme in Extended Data Fig.3a (previously 2b). 14/ In the abstract and Introduction (lines 47 and 68), put the abbreviation in parenthesis after the complete name of the protein. ANSWER: We did the modifications accordingly. 15/ In general, remove the P value from the text since they are shown in the figures. ANSWER: We removed the p value in the text when they are indicated in the figures. 16/ Line 939: do not capitalize Primary. ANSWER: The change is done. 17/ Please, describe the epidemiology, etiology, and disease progression of prostate cancer as a first paragraph of the introduction. ANSWER: As requested we added a paragraph on PCa in the introduction: “According to the GLOBOCAN study, PCa is the second most diagnosed cancer and the fifth leading cause of cancer death among men worldwide {Bray, 2024 #3269}. Removal of the prostate (prostatectomy) and radiotherapy are treatments for localized tumors. For more advanced PCa, anti-androgen treatments and/or chemotherapy (Docetaxel) are prescribed. However, patients quickly develop resistance, leading to fatal outcomes. Therefore, there is a critical need to discover therapies that target new molecular pathways.” 18/ Fig. 1h should appear before Fig. 1e, since it is a transcriptomic analysis. ANSWER: We did the modifications accordingly. 19/ Describe more specifically Fig. 2a in the Results section. Why the authors did not use a western blot? At which time point was performed the analysis of EIF5A-hyp level? ANSWER: The reviewer is right, we did not comment this figure in the results, thus, we added a sentence in the new version of the manuscript. In addition to cytometry analysis, we present in the new version immunoblots of the expression of eIF5A hypusinated and DHPS in the tumoroids. We added this new sentence to the results section: “We verified by cytometry and immunoblot that both GC7 and the downregulation of DHPS decreased eIF5Ahyp (Fig. 2a, Extended Data Fig. 3f,g).”. However, we must emphasize that tumoroids are 3D structures; thus, analysis using Western blotting will average the signal, unlike cytometry, which performs individual cell analysis. Furthermore, we need a lot of tumoroids to obtain a sufficient amount of protein to perform a Western blot. The levels of eIF5Ahyp were analyzed 24 hours after the addition of GC7 and 6 days after the addition of IPTG for shDHPS. This information has been added to the Materials and Methods section: “Tumoroids were treated 24 hours with 80µM GC7 or 6 days with 500µM IPTG to induce the shDHPS before cytometry analysis.” 20/ The legend of Fig. 6f needs revision. ANSWER: We have re-written the legend of the figure 6 f in the new version: “DU145 cells expressing shCtl or shDHPS were stably transfected with empty vector (EV) or MRPP3 expressing plasmid and subcutaneously injected in nude mice (n=8 per group). Graphs represent the follow-up of the tumor volume and the tumor weight. Pictures of the tumors from the four cell lines are taken at the end of the experiment.” 21/ Fig. 5b should be included in the Extended Data. It is already known that hypusination is required for nuclear translocation. ANSWER: We agree with the reviewer that it is known that hypusination is required for nuclear translocation, however, we think that it is important to show these results in the main figures, because it is the main mechanisms explaining how eIF5A regulates MRPP3 expression. 22/ In Fig. 6f, I suggest writing ‘EV + shCtl’, ‘MRPP3 + shDHPS’, etc… instead of ‘EV shCtl’, ‘MRPP3 shDHPS’, etc… ANSWER: As requested by the reviewer, we did the modifications in the new Figure 6. 23/ The last paragraph of the Discussion should be developed. Define RBP. What are the clinical implications of their discovery about the essential role of hypusination in prostate cancer. ANSWER: In the new version of the manuscript, we defined RBP and added the following paragraph: “In conclusion, our results reveal that the RBP (RNA binding protein) function of eIF5A controls MRPP3 expression and PCa metastasis. This provides a new molecular basis for developing novel therapies targeting mitochondrial function in advanced PCa, for which few therapeutic options are available.” 24/ Include a paragraph about Statistics in the Methods section ANSWER: Thanks for this suggestion, we added the following paragraph: “All experiments were performed at least three independent times unless stated. Statistical analyses were performed with GaphPad Prism version 9.0 using appropriate test: Student’s t test, Mann-Whitney or ANOVA.” REVIEWER # 2 We would like to thank the Reviewer for their careful review of our manuscript and for their positive feedback, stating that \"Overall, the paper is well written, the story is original, and it is supported by several elegant and solid experimental approaches.\" We have taken the constructive suggestions into consideration to improve our manuscript and hope that the revisions will meet her/his expectations. Below are our answers: - In very recent Nature paper from the Fendt group (DOI https://doi.org/10.1038/s41586-024-08335-7) it was shown that hypusinated EIF5A regulates cancer metastasis in response to aspartate content in the TME. By stimulating NMDA receptors, asp was shown to increase intracellular calcium content, leading to CREB-mediated induction of DOHH transcription, increased EIF5A hypusination and consequent translation of TGFbeta targets involved in metastasis. It would be worth to try to connect the present findings with those from the Fendt group. Is the mechanism described here only applicable to prostate cancer? Are there potential overlapping steps? ANSWER: We thank the reviewer for mentioning this interesting paper published in Nature after the submission of our manuscript (Doglioni et al. January 2025). This article demonstrates that aspartate triggers a molecular cascade that activates CREB, which in turn induces the expression of DOHH mRNA and protein. The increased expression of DOHH enhances hypusination, thereby promoting lung metastasis. Doglioni et al. also demonstrated that Aspartate promotes the N-methyl-d-aspartate (NMDA) receptor activity and this is required for DOHH expression in breast cancer cells metastasis. We analyzed the expression of DOHH and GRIN2D (encoding for NMDA) mRNA and we found no significant modification of their expression in primary tumors (PT) vs metastasis (META) in our PCa orthotopic model (Data for reviewers only below). This result has been added to the new version of the manuscript in the discussion: “More recently, Doglioni et al. demonstrated that Aspartate promotes the N-methyl-d-aspartate (NMDA) receptor activity, and this is required for DOHH mRNA expression in breast cancer cells metastasis. We analyzed the expression of DOHH and NMDA (Grin2d) in primary tumors and the metastasis of PCa orthotopic xenografts and did not find significant changes in mRNA expression (Data shown) suggesting that this mechanism may not be implicated in PCa.” - Figure 1: there are two members of EIF5A proteins: EIF5A1 and EIF5A2. Since previous studies have shown that EIF5A2 is upregulated in some cancers and involved in metastasis, including prostate cancer metastasis (https://doi.org/10.1038/s41420-021-00764-x ), analysis of EIF5A2 should be conducted along with that of EIF5A1. Also, please normalize the levels of hypEIF5A to total EIF5A rather than ERK2 and show the OS also for EIF5A1 and 2. ANSWER: This is an issue also raised by Reviewer #1, we have added the expression data for eIF5A and eIF5A2 to Figure 1B and other analysis included the data obtained with both isoforms in the new Fig.1b, Ext Data Fig. 1d-j., Ext Data Fig. 2a-d. Consistent with previous findings (Clement et al., 2006, PMID: 16519677), we confirm that eIF5A2 is very weakly expressed in prostate cancer cells. Additionally, we have included a sentence in the introduction discussing the two isoforms of eIF5A. We thank the reviewer for bringing to our attention the study by Zheng et al. It is important to note that this study used an antibody that was marketed at the time as specific for eIF5A2. After the publication of this study the supplier posted this note : “This product was previously published with the name Anti-eIF5A2 antibody [EPR7411-6]. Following in-house testing that showed reactivity to both recombinant Human eIF5A protein (ab87457) and recombinant Human eIF5A2 protein (ab99140), the name was updated in January 2021 to Anti-eIF5A2 + eIF5A antibody [EPR7411-6]. Consequently, the specificity of this antibody for eIF5A2 is not guaranteed. Nevertheless, the findings of the publication align with our current manuscript, demonstrating that eIF5A plays an important role in prostate cancer.” In the new Figure 1j the expression of eIF5Ahyp has been normalized to eIF5A . - Figure 2: can the authors provide evidence of the effect of DHPS inhibition on cell proliferation (i.e. BrDU staining or cell proliferation rate) in their cell lines? In addition, since in figure 2g it is difficult to visualize the metastases quantified in Figure 2h (same also in Figs 6g and 6h), can the authors show the luminescence on the explanted organs? ANSWER: As requested by the reviewer the effects of DHPS inhibition (with GC7 and shDHPS) on LNCaP, DU145 and PC3 proliferation were added to the new version of the manuscript (Extended Data Fig. 3 b,c). We have included the luminescence of the organs from the mice injected with ShCT, shDHPS and shMRPP3 in the new version of the manuscript (Extended Data Fig. 4j and Extended Fig. 10e). - Figure 3: can the authors show the whole list of the 71 metabolites identified by MS in a table? ANSWER: We added a new table (Table 2) with the list of the 71 metabolites modified upon the downregulation of DHPS as requested by the reviewer. - Figure 4: Most of the experiments in this figure are conducted with GC7. A previous paper from the Kahana group (DOI 10.1074/jbc.M110.106419) showed different polysomal profiles in response to GC7 (inhibition of initiation) compared to EIF5A knockdown (inhibition of elongation). This should be addressed. Also, a table with the list of proteins identified by MS would be helpful. ANSWER: The reviewer pointed out a paper published in JBC in 2010 demonstrating that GC7 inhibits eIF5A initiation and elongation whereas depletion of eIF5A inhibits elongation only (Landau et al. 2010). We addressed this question in the discussion: “Studies conducted by Kahana's group revealed that GC7 inhibits both initiation and elongation, whereas shRNA targeting eIF5A specifically inhibits elongation {Landau, 2010 #3273}. This discrepancy may be due to the off-target effects of GC7. However, eIF5A has been involved in all stages of translation. It regulates initiation {Ivanov, 2018 #3275} and more specifically the fidelity of star codon initiation {Manjunath, 2019 #3210}, but it also plays a crucial role in the elongation and termination phases {Schuller, 2017 #3086; Pelechano, 2017 #2848}. In our study, we downregulated DHPS and utilized GC7. Notably, both interventions exhibited similar effects on PCa cells and tumor growth, and they similarly influenced MRPP3 expression, minimizing potential but still possible off-target effects of GC7.” The list of proteins identified by MS are available on PRIDE (accession number PXD058627) as indicated in the new version of the manuscript. We also included the accession number for the RNA Seq in the material and method section. - Figure 5: GC7 treatment is shown to increase the nuclear enrichment of MRPP3 and C-MYC, suggesting that hypusination may regulate their shuttling. However, while MRPP3 mRNA is shown to associate with EIF5A, MYC mRNA seems to be slightly enriched although not significantly. This result is somehow puzzling, authors may increase the number of replicates in Fig. 5a to see if statistical significance can be reached or delete the C-MYC data or provide an explanation for the observed discrepancy. Is C-MYC content regulated by GC7 as previously shown (doi: 10.1038/s41419-020-03174-6)? In response to the reviewer comments, we increased the number of replicates in Figure 5a and we performed the experiment in additional PCa cell line (PC3). We demonstrated that in both DU145 and PC3 c-MYC mRNA associated with eIF5A (New figure 5a), consequently, we observed a slight inhibition of c-MYC protein levels in cells treated with GC7 (Ext Data Fig. 8a). - A graphical abstract would be helpful. ANSWER: Thanks for the suggestion. We added a graphical abstract to the revised version of the manuscript (Fig. 7). REVIEWER # 3 The reviewer 3 co-reviewed the article with another reviewer as part of the Early Career Researchers program. REVIEWER #4 We thank the reviewer for carefully reading our manuscript and for the constructive comments made. One of the major concerns was the clinical relevance of our work for the pathology of PCa: “ The main concern is the lack of a proper interrogation of the human relevance of this axis in PCa in the context of the current knowledge. There is no clear identification of which prostate tumors depend on eIF5A and are, therefore, vulnerable to the inhibition of this pathway. Is eIF5A-hyp relevant in primary PCa, or in CRPC? Is it more critical just in metastasis?” Thanks to this suggestion, we have strengthened this issue in the new version of the manuscript by conducting in-depth analysis on previously analyzed databases, but also new databases including proteomic data and neuroendocrine PCa. Our analysis demonstrates that it is primarily the expression of DHPS that increases during PCa progression and metastasis. Additionally, we would like to emphasize that the polyamine-hypusination axis is highly relevant, particularly since the prostate is one of the organs with the highest concentrations of polyamines. This point is addressed in both the introduction and discussion sections of the article: “Polyamines play an important role in cell proliferation, apoptosis, protein and nucleotide synthesis{Casero, 2018 #2634}. Previous studies, including our own, have demonstrated that polyamines are essential for metastasis in PCa (Kaminski et al., 2019; Zabala-Letona et al., 2017), and their levels are significantly elevated in PCa tissues compared to benign prostatic hyperplasia or normal prostate tissues (Zabala-Letona et al., 2017). These findings point to the polyamine/hypusination axis as a central player in PCa progression.”. “Since polyamines are elevated in prostate (Devens et al, 2000 #2829) the study of hypusination is highly relevant.” Below are our answers to the specific points raised by the reviewer: Specific points: Important Note: As requested by the reviewer 1 and 2 we have analyzed the expression of EIF5A and EIF5A2 and we added a paragraph on these two isoforms in the introduction: “There are two known highly homologous (91%) isoforms of eIF5A: eIF5A1 and eIF5A2 encoded by two different genes located on two different chromosomes. However, eIF5A2 expression is weak in the prostate {Clement, 2006 #3162}.” Fig. 1 and Extended Fig. 1. The data of these Figures show the expression of different components of the eIF5A hypusination pathway using several public datasets but in a scattered manner, independently analyzing different components in each dataset. Is there a correlation between DHPS, EIF5A and DOHH mRNA levels in the datasets of Figs. 1b, 1h and Ext Fig. 1c (TCGA)? ANSWER: We performed correlation analysis for DHPS, DOHH, EIF5A and EIF5A2 mRNA using the databases TCGA, Lapointe, Grasso and Varambilly as requested by the reviewer and the conclusion is included in the results section : “In TCGA and Grasso databases, a correlation was observed between eIF5A, DHPS and DOHH expression (Extended Data Fig. 1j), however, eIF5A and DOHH were not significantly associated with PCa (Extended Data Fig.1g-i).”. Of note, we also performed a correlation analysis with the Sun proteomic database and we found that the expression of eIF5A, DHPS and DOOH are significantly correlated (Extended Fig. 7b). How is the expression of EIF5A and DOHH in Fig. 1h? ANSWER: We have included in the new version the expression levels of DOHH, EIFE5A and EIF5A2 from Grasso et al., Lapointe et al., Varambally et al. in the Extended Data Fig. 1 g-i. A more thorough investigation, including analysis of public datasets with CRPC samples split by adenocarcinoma or neuroendocrine, needs to be included. In Figs. 1c,d and Ext Fig. 1a,b: violin and UMAP plots for the expression of DHPS, EIF5A and DOHH in the different cell populations need to be shown. ANSWER: We analyzed the expression of the different genes in a database of patients with neuroendocrine cancers (Beltran et al.), in metastasis and Lymph nodes (OncoDB). These data are included in the new version of the manuscript in the result section: “The increase in DHPS during disease progression was confirmed through our analysis of lymph node involvement (N) and the presence of distant metastasis (M), utilizing the online database resource OncoDB. (Fig. 1f,g and Extended Data Fig. 2a,b). DHPS mRNA was also significantly increased in neuroendocrine PCa, a rare but more aggressive form of PCa {Beltran, 2016 #3272} while, we did not find a significant increase in the levels of DOHH, EIF5A, or EIF5A2 (Extended Data Fig. 2c).” Also, we added the UMAP dot plots of the expression of DHPS, DOHH, EIF5A1 and EIF5A2 in the different cell population (New Extended Data Fig.1a-f ). Ext. Fig. 1c: How are low vs high DHPS patients defined? What is the expression of EIF5A and DOHH in those patients? Are EIF5A levels predictors of poor survival as concluded (but not shown) in the results section of Fig. 1? ANSWER: Data were obtained using GEPIA website (GEPIA (Gene Expression Profiling Interactive Analysis), an interactive web server for analyzing RNA sequencing from the TCGA database (Tang et al. 2017, PMID: 28407145). Genes with higher absolute log2 fold change (|log2FC|) values and lower q-values than pre-set thresholds are considered differentially expressed. Expression levels categorized as \"low-level\" are those below the median value. Conversely, \"high-level\" expression refers to levels above the median value. We analyzed the expression of DOHH, EIF5A1 et EIF5A2 in the patients with low DHPS and high DHPS as requested and we found that except for EIF5A2 the expression of DOHH and EIF5A is correlated with the expression level of DHPS. The results was added in the Extended Data Fig. 2e. The analysis of the overall survival for DOHH, eIF5A1 et eIF5A2 was added to the new version of the manuscript, only DHPS levels are associated with a poor survival (Extended Data Fig. 2d). The reviewer is right our sentence: “Collectively, these clinical analyses demonstrate that eIF5Ahyp and DHPS are upregulated in PCa and are associated with poor prognosis.” is not correct since we don’t know if eIF5A hypusinated is associated with a poor survival. From our analysis, only DHPS expression is associated with poor survival. Thus, we modified our sentence for: “Collectively, our results show that hypusination of eIF5A and DHPS levels are upregulated in PCa and associated with advanced stages of the disease.” According to Figs. 1b and 1c, EIF5A levels are upregulated in tumors compared to normal samples. However, there is no clear upregulation of EIF5A levels in Fig. 1e (not quantified). This discrepancy needs to be addressed. ANSWER: The reviewer is right, EIF5A mRNA is upregulated in Tumor prostate tissue (Fig. 1b). As requested by the reviewer, we quantified eIF5A proteins in our tumor samples vs normal adjacent tissue (Extended data Fig. 2g) and found that there is no significant modification of eIF5A protein expression in tumor vs normal adjacent tissue. This result is not surprising since the expression of mRNA does not always match with the expression of the protein. The key finding in our study is that the hypusinated form of EIF5A (activated form) is elevated in tumors. We also added new immunoblots comparing eIF5Ahyp, eIF5A and DHPS expression in PCa and BPH patients. We show that: “eIF5Ahyp, eIF5A and DHPS were significantly more expressed in PCa tumors than prostate tissue from patients with BPH (Extended Data Fig. 2h,i)”. This result suggests that within the same biopsy (patient), eIF5A is not upregulated, however, it is more expressed in tumor tissue compared to normal (BPH) from different patients. Fig. 2 and Extended Fig. 2. The in vitro cell systems used to investigate the role of eIF5A needs to be better characterized from the point of view of eIF5A hypusination to be able to show a direct dependency. What are the levels of eIF5A-hyp and DHPS in the different cell lines and prostate tumoroids? All the prostate lines used are prostate cancer cell lines and need to be compared to a normal prostate cell line. Western blots of Ext Fig. 2a,b needs to be run all together and with a normal cell line. Similarly, the tumoroids used represent a diverse biology mimicking different PCa subtypes. MSK-PCa1 is an AR-/Syp-, MSK-PCa3 is AR+, and PCa4 is AR-/Syp+. How is the eIF5A hypusination axis in the different subtypes? Is there any correlation with the response to inhibition of the pathway and the specific activation of this axis in a particular subtype? The proper control of knock-down of shDHPS and GC7 on eIF5A-hyp on tumorids needs to be shown by WB. Based on the FACS data, there is no correlation between the degree of inhibition of hypusination by GC7 and shDHPS in the different tumoroids and the impact on tumoroid size. ANSWER: As requested by the reviewer we assessed eIF5A hypusination and DHPS levels on the same immunoblot in the different cancer cell lines (LNCaP, DU145, PC3) and added a normal prostate epithelial cell line (P69) (Plymate et al. PMID: 8855827). We also performed an immunoblot for the tumoroids MSKPCa1, 3 and 4 and normal prostate organoid (Gao et al. PMID: 25201530) (Extended Data Fig. 3 a,g). DHPS levels are similar between the different cancer cell lines and tumoroids, while we observed a lower expression in P69 and normal organoids (Extended Data Fig. 3 a,g). The levels of hypusination do not vary significantly between the cell lines and the tumoroids. The reviewer is right the tumoroids mimic different PCa subtypes with different status for AR expression, this was included in the new version of the material and methods. Independently of the status of the tumoroids they respond similarly to GC7 (Extended Data Fig. 3 a,g), while shDHPS induces a stronger effect than GC7. However, it is worth noting that the timing differs: GC7 is applied for 24 hours, whereas we prepared the lysates 5 days after the addition of IPTG induction. This timing difference is one reason why it is challenging to compare the effects of a drug with those of a genetic approach using an inducible system. Additionally, several other factors may explain the divergences of the biological responses between GC7 and shDHPS: i) the off-target effects of GC7 compared to a targeted genetic approach. ii) differences in the doubling times of the tumoroids (Gao et al., 2016). iii) immunoblotting on 3D structures provide valuable information about protein expression, however, it is important to recognize that the signal represents an average and may not capture the full complexity and heterogeneity of the sample. That is why we used cytometry to have a complementary technique that can help to interpret the results more accurately. Fig. 3 and Extended Fig.3. Why do LNCaP cells respond very differently from DU145 in OCR with almost no effect of shDHPS on maximal respiration if both cell lines are equally sensitive to inhibition of DHPS in terms of growth and invasion? Similar to the functional assays described in Fig.2, to demonstrate the dependency on eIF5A-hyp, a proper control showing that the effect is selective to those cell lines overexpressing eIF5A is required. ANSWER: The reviewer is right LNCaP cells are less responsive to the inhibition of hypusination than DU145 cells in the Seahorse experiments as well as in the steady state metabolomic. We performed additional experiments and found that the inhibition of eiF5Ahyp has more pronounced effects in DU145 than LNCaP in 13C glucose tracing experiments and but also in the puromycin incorporation assay (Extended Data Fig. 5e and 6a,b). Our hypothesis is that DU145 cells are more dependent on translation than LNCaP cells and, consequently, more sensitive to translation inhibitors, which specifically affect their metabolism. Indeed, our proteomic analysis shows that GC7 regulates the expression of a greater number of proteins in DU145 cells than in LNCaP cells (see data not shown below). Previous studies from Hsieh's group (Liu et al., PMID 31366581) have shown that the androgen receptor acts as a negative regulator of protein synthesis. This is confirmed by our observation that LNCaP cells, organoids, and MSK-PCa3 tumoroids, which are all AR-positive, display lower levels of translation than AR negative cells (Extended Fig. 6b). Proteomic analysis of the number of proteins regulated by GC7 in LNCaP and DU145. In blue downregulated proteins and in red upregulated proteins. This specific issue is commented in the discussion of the new version of the manuscript: “We observed that AR-positive cells, including LNCaP, normal organoids, and MSK-PCa3 tumoroids, exhibit lower levels of translation. This confirms the findings of Liu et al., which demonstrate that AR acts as a negative regulator of protein synthesis {Liu, 2019 #3276}. Furthermore, inhibiting hypusination in these cells had a less pronounced effect on metabolism. This suggests that cells with low translation levels may be less sensitive to hypusination inhibition, an effect that impacts more specifically cell metabolism.” Fig. 4 and Extended Fig. 4. Sequencing of the polysome profiling is required to identify the specific changes in translation. Translation changes cannot be directly inferred from the proteomic studies. Integrating ribosomal profiling and proteomic is necessary. Is there a correlation between the levels of increased translation and eIF5A-hyp in the different cell models? Is there a correlation between mitochondrial translation and eIF5A-axis in the same dataset analyzed in Fig. 1 and Ext Fig. 1? The increased translation linked to eIF5A-hyp needs . ANSWER: As requested by the reviewer we have performed a polysome sequencing and integrated the data with the results of the proteomic study. The conclusion was added to the new version of the manuscript: “We performed polysome sequencing (Extended data Fig.6f) and integrated the data with the proteomic study to identify common pathways using Gene Set Enrichment Analysis (GSEA). We found that 26 pathways were commonly regulated (Fig. 4c). Notably, 11 of the top 15 pathways were associated with mitochondrial metabolism, including the mitochondrial protein-containing complex (Fig. 4d).” We conducted a puromycin incorporation assay using normal and prostate cancer cell lines, as well as tumoroids and normal organoids (Extended Data Fig. 6a-c). We observed that translation was lower in LNCaP, normal organoids, and MSK3 (all three of which are AR+). There is no proper rationale for selecting MRPP3 as the main target of eIF5A. If MRPP3 is downstream of eIF5A, why does MRPP3 overexpression induce eIF5A-hyp (Fig. Ext 4h)? Is there a correlation at the protein levels of eIF5A-hyp/DHPS and MRPP3 in the tumor samples of Fig. 1e? There is no correlation between the downregulation of MRPP3 with GC7 in PCa3 (Fig. Ext. 4g) and the different functional readouts in the other Figures for this model. The rational for selecting MRPP3 is explained in more details in the new version : “Among the PPR proteins, MRPP3 emerged as a key target, given its essential role as a regulator of mitochondrial RNA maturation and function, both in vitro and in vivo{Münch, 2016 #3169;Rackham, 2016 #3189}. MRPP3 was one of the most significantly downregulated proteins following eIF5Ahyp inhibition, with a Log fold change of -2.99 in DU145 cells 2 (Extended data Fig. 7a). Furthermore, we found that MRPP3 protein levels significantly correlate with the expression of DHPS, DOHH, eIF5A and A2 in the Sun proteomic database that includes 306 patients (Extended data Fig. 7b).” We did not find a correlation between the expression of MRPP3 and DHPS or eIF5Ahyp in our tumor samples, likely due to the small number of patients. We agree with the reviewer that in the previous Extended Data Figure 4h, eIF5Ahyp shows a slight increase upon MRPP3 expression. However, this observation was not replicated in other in vitro experiments (Fig. 4g and Extended Data Figure 9j). It is true that the decrease in MRPP3 expression is slight but significant in the MSK-PCa3 tumoroids treated with GC7, while its effects on their growth and formation are similar to those seen in other tumoroids. Our hypothesis is that even a minor reduction in MRPP3 can impact their phenotype. Fig. 6 and Extended Fig. 6. There is a disconnect between data on OCR comparing shDHPS (Fig. 3e) and shMRPP3 (Fig. 6a). If shMRPP3 is mimicking shDHPS, they should have similar effect. The in vivo experiments of Fig. 6e and f show similar tumor weights for the control group when the tumor volume is less than half at the endpoint in Fig. 6f as compared to Fig. 6e. How is that possible? Regarding the potential human relevance for MRPP3, the data of Fig. 6i is totally insufficient. To demonstrate that MRPP3 is the relevant target downstream of eIF5A in prostate cancer, it is critical to show the correlation of MRPP3 with eIF5A-hyp and DHPS in the same human samples in a proper cohort including advanced PCa since the authors aim to demonstrate its potential role in metastasis. ANSWER: The reviewer is correct; shMRPP3 induces a weak but still significant inhibition of OXPHOS compared with the effects of shDHPS (Fig. 6b). One hypothesis to explain this discrepancy is that the remaining level of MRPP3 is sufficient to maintain a relatively high level of OXPHOS. Another hypothesis might be that the shMRPP3 used in this study is constitutive, allowing cells to adapt to the downregulation of MRPP3, whereas the shDHPS is inducible. To further characterize the role of MRPP3 in PCa cell metabolism we performed a steady-state metabolomic study (Fig. 6a), and we showed that similarly to shDHPS, the downregulation of MRPP3 led to significant decrease of 4 intermediates of the TCA cycle (citrate, α-ketoglutarate, fumarate and malate). This result demonstrates that despite the weak effect on OCR, the downregulation of MRPP3 inhibits TCA cycle. We added this new result in the revised version : “Similarly to the inhibition of eIF5Ahyp, the downregulation of MRPP3, significatively decreased the abundance of citrate (M+2), α-ketoglutarate (M+2), fumarate (M+2) and malate (M+2) (Fig. 6a).” The in vivo experiments of Fig. 6e and f show similar tumor weights for the control group when the tumor volume is less than half at the endpoint in Fig. 6f as compared to Fig. 6e. How is that possible? The reviewer is correct; however, we noted that the tumors were filled with liquid, likely due to necrosis. During sampling, this liquid drained away, resulting in a reduced weight. To confirm the rescuing effects of MRPP3, we conducted the same experiment using a syngeneic model and RM-1 cells. The results of this new experiment are shown in (Extended Data Figure 10b-d) . We found that overexpression of MRPP3 partially rescued the anti-tumoral effect of shDHPS. We added more patients to our study and confirmed that MRPP3 expression is significantly higher in PCa compared with BPH (Extended Data Fig. 10f). However, as previously mentioned, we did not find a significant correlation between the expression of MRPP3 and DHPS or eIF5Ahyp in our tumor samples, likely due to the limited number of patients. Interestingly, in the Sun proteomic database, which includes 306 patients, MRPP3 protein levels are elevated in tumors (Extended Data Fig. 10f), and its expression significantly correlates with the expression of DHPS, DOHH, eIF5A1, and A2 (Extended Data Fig. 7b). This specific point was added to the result section: “Similarly, we found that MRPP3 is significantly more expressed in PCa tumors than prostate tissue from patients with Benign Prostate Hyperplasia (BPH) (Extended Data Fig. 10f). Interestingly, the analysis of Sun's proteomic database confirmed that MRPP3 is overexpressed in tumors {Sun, 2024 #3274} (Extended Data Fig. 10g). Of note, this database also revealed a correlation between the expression of MRPP3, DHPS, and eIF5A (Extended Data Fig. 7b).” Dear reviewers, Please find below the response to the reviewer’s questions. Reviewer’s comments appear in green bold italics; our responses follow, prefaced by “>>” and the new figures presented here could be added to a revised version. I thank the authors for their efforts during the revision to address my previous comments, and I appreciate the additional experiments and new analyses included in the revised manuscript. However, most of my major concerns remain only partially (at most) addressed. As I mentioned in my previous review, the paper falls short in identifying which prostate tumors depend on eIF5Ahyp and in linking the response to targeting this pathway, either pharmacologically with inhibitors or through genetic manipulation with shRNA, to specific patterns of expression or dependencies. - Although the revised version includes expanded expression analyses from TCGA and other public datasets, including neuroendocrine PCa, the new data do not provide a cohesive picture of the human relevance of the eiF5Ahyp axis or its expression across different stages or subtypes of PCa. The expression and dependency of this pathway in primary versus metastatic disease, AR-positive versus AR-negative tumors, or castration-resistant prostate cancer (CRPC) remain largely unexplored, and the results differ among the datasets analyzed, precluding reaching more definitive conclusions. >> In the revised version, we clearly and explicitly demonstrate that DHPS expression progressively increases across the disease stages—from Normal to Primary Tumors and finally to Metastasis (Fig. 1e)—in three independent databases. This trend is also confirmed in lymph node samples according to the OncoDB database (Fig. 1g). Furthermore, in ext. Fig. 2c, we included the dataset from Beltrán et al., which features castration-resistant prostate cancer (CRPC) cases, further divided into adenocarcinoma and neuroendocrine subtypes, as initially requested by the reviewer (“A more thorough investigation, including analysis of public datasets with CRPC samples split by adenocarcinoma or neuroendocrine, needs to be included”). In the present updated version, we included data examining the relationship between AR activity and the hypusination pathway: 1) We assessed the correlation between AR—based on the AR signaling score defined by Bluemm et al. (PMID: 29017058) —and the hypusination pathway genes (DHPS, DOHH, EIF5A1, and EIF5A2). Our analysis of four databases revealed no significant correlation between these two pathways (NEW Extended Data Fig. 1f). 2) Using our proteomic data, we assessed the enrichment of the androgen response hallmark in GC7-treated LNCaP cells (AR positive cells). Our findings indicate that hypusination inhibition does not significantly impact the androgen response pathway (Figure R1). Fig. R1: Enrichment plot for the hallmark of androgen response in LNCaP cells treated with GC7. 3) We also analyzed the expression of AR in LNCaP cells and the inhibition of hypusination with GC7 or inducible expression of shDHPS did not affect the expression of AR (Figure R2). Fig. R2: Immunoblot of DHPS, eIF5Ahyp, AR and HSP90 (loading control) of LNCaP cell lysates treated with GC7 or expressing shDHPS. 4) Finally, we analyzed the RNA-seq data from Sattari et al. (PMID: 37140987), in which AR is downregulated in LNCaP cells. In this context, AR knockdown using siRNA did not affect the expression of DHPS, DOHH, or eIF5A, indicating that AR does not regulate the hypusination module at the mRNA level (Figure R3). Fig. R3: mRNA expression of the indicated genes after AR Knockdown in LNCaP cells (data form Sattari et al. RNAseq). Altogether, our results demonstrate an upregulation of DHPS and hypusination in metastases compared to primary tumors, suggesting that there is a clear dependency of prostate metastasis on hypusination. It is still unclear what drives the increase in eiF5Ahyp and at what level (mRNA, protein, which step, in which stage?). >> Hypusination depends on spermidine levels, and the prostate is among the organs with the highest spermidine concentrations, as highlighted in both the Introduction (lines 78–83 : “Polyamines play an important role in cell proliferation, apoptosis, protein and nucleotide synthesis{Casero, 2018 #2634}. Previous studies, including our own, have demonstrated that polyamines are essential for metastasis in prostate cancer (PCa){Kaminski, 2019 #2629;Zabala-Letona, 2017 #1457}, and their levels are significantly elevated in PCa tissues compared to benign prostatic hyperplasia (BPH) or normal prostate tissues{Zabala-Letona, 2017 #1457}.”) and the Discussion (line 488: “Since polyamines are elevated in prostate {Devens, 2000 #2829} the study of hypusination is highly relevant,”). Notably, expression of most polyamine pathway genes (Fig. 1b), along with DHPS (at both mRNA and protein levels) and hypusinated eIF5A (in patient samples), is elevated in prostate tumors and metastases (Fig. 1c–k). This highlights the pivotal role of the polyamine/hypusination axis in prostate cancer progression. The results from the different datasets and cohorts are scattered, superficially analyzed, and contradictory among them. >> We have restructured the results section of our dataset analysis to enhance clarity, emphasizing that DHPS expression improves as the disease progresses from the primary tumor to metastasis. Additionally, we have revised this section to present the findings in a gene-to-protein framework (as initially requested by reviwer #1): in red in the text from line 144-171. The analysis of the scRNAseq dataset does not add any information. The UMAPs shown without splitting by normal or tumor do not demonstrate that the pathway is increased in tumor samples. The responses of the authors to address the contradictory results presented do not solve these problems. >> We appreciate this comment and agree that our original UMAPs, shown without stratifying by clinical status, were not the most informative way to convey differential pathway activity. To address this concern, we now provide violin plots split by benign tissue Vs. tumor for each major cell class. In epithelial (malignant) cells, the hypusination components DHPS and eIF5A are significantly elevated in tumors relative to benign epithelium, while changes in stromal/immune subsets are modest or absent (Ext. Data Fig.1c-e). This resolves the ambiguity of the unsplit UMAPs and localizes pathway upregulation to the malignant compartment. Moreover, the scRNA-seq analysis is pivotal, as it reveals a cell-level correlation between the hypusination module and the mitochondrial translation signature (Extended Data Fig. 6h–k). This finding strengthens our proposed model connecting eIF5A hypusination to mitochondrial RNA maturation. Moreover, the scRNA-seq analysis is pivotal, as it reveals a cell-level correlation between the hypusination module and the mitochondrial translation signature (Extended Data Fig. 6h–k). This finding strengthens our proposed model connecting eIF5A hypusination to mitochondrial RNA maturation. Similar inconsistencies are seen with the different model systems used in the study (cell lines and prostate tumoroids). First, the data are not robust enough across experiments, and there are still multiple discrepancies. For example, LNCaP cells show similar levels of eiF5Ahyp compared to normal prostate cells (P69) and lower than DU145 or PC3 (at least in the blots with GC7, Ext Fig. 3a). However, they respond to most of the proliferation, migration, and invasion assays better or at least as well (Ext. Fig.3b). Additionally, although normal controls (P69 and normal organoids) have been included for expression analysis and in one experiment for sensitivity to GC7, most experiments do not include controls run in parallel to demonstrate selectivity. While the inclusion of normal prostate organoids as controls for GC7 sensitivity is valuable, a detailed quantification of eIF5Ahyp and DHPS levels across the different PCa subtypes and correlation with sensitivity to GC7 or shDHPS is still missing. Significant discrepancies persist in mitochondrial functional assays across models. >> We respectfully disagree with the reviewer concerning the robustness of our experiments. Across orthogonal perturbations (genetic DHPS knockdown and the DHPS inhibitor GC7), multiple independent experiments, and diverse models (three established PCa lines, three patient-derived tumoroids, and three in vivo settings), we observe directionally consistent effects of eIF5A hypusination inhibition on proliferation, migration, invasion, tumor growth, and metastasis. Concerning the “discrepancies” between basal eIF5Ahyp levels and functional readouts (e.g., LNCaP Vs. P69, DU145, PC3), we agree that basal hypusination does not linearly predict steady-state proliferation, migration, or invasion. eIF5Ahyp is a contributing, but not exclusive, determinant of these phenotypes. Distinct genetic backgrounds, lineage programs (e.g., AR, p53 status), and pathway wiring can yield different baseline behaviors even when eIF5Ahyp levels are comparable. The appropriate test of dependency is perturbation: in all models examined, inhibiting hypusination produces convergent phenotypic consequences. Moreover, we work with metastasis derived cells, even P69 are immortalized cells lines, therefore, it is misleading to assume there is a direct correlation between the levels of hypusination and the biological effects. Mechanistically, our work shows that eIF5Ahyp sustains mitochondrial function by promoting MRPP3 expression and mt-tRNA maturation; when hypusination is reduced, mitochondrial translation and respiration decline, ATP production falls, and invasive/proliferative capacity drops. Thus, lack of a one-to-one correlation between baseline eIF5Ahyp and phenotypic magnitude is expected; what is consistent is the direction and mechanism of the response to eIF5Ahyp inhibition. In this revised version, we have addressed the reviewer’s request by including the quantification of eIF5Ahyp and DHPS from the immunoblots in Extended Data Figure 3a and g. We present here data from proliferation experiments using GC7 on P69 normal epithelial cells. GC7 significantly inhibited proliferation by 40%, though this effect was less pronounced than in LNCaP, DU145, and PC3 cells, which showed inhibition rates of 60%, 83%, and 65%, respectively (Figure R4 and Extended Data Figure 3c). Importantly, P69 cells are immortalized cell lines that exhibit distinct genetic and biological characteristics compared to primary epithelial cells. In this context, patient-derived organoids from normal glands serve as a more representative control for normal cells, and in this model, the inhibitory effect of GC7 is only 6% (Figure R4). Fig. R4: Effects of GC7 on normal cells and organoids. Proliferation assay in P69 immortalized normal prostate cells and patient derived organoid from normal gland. With regard to selectivity for tumor over normal cells, it is noteworthy that GC7 is well tolerated in mice. In line with previous studies (Fang et al., PMID: 29286162; Robbins et al., PMID: 20956533; Cougnon et al., PMID: 40789258 and 33731685), our findings confirm that GC7 does not alter behavior or body weight, even while effectively suppressing tumor growth in vivo. These results indicate that GC7 selectively targets tumor cells with elevated translational activity. Regarding the effects of GC7 on metabolism, we conducted steady-state metabolomic analysis in P69 cells. Our results demonstrate that aconitate is the only metabolite of the TCA cycle significantly downregulated following GC7 treatment (see Figure R5 below), a finding that starkly contrasts with the inhibitory effects observed in cancer cells (LNCaP and DU145) (Ext Data Fig 5a-d). The revised manuscript includes new polysome profiling and proteomic data, which add weight to the involvement of eIF5Ahyp in mitochondrial function. >> We Fig. R5: Steady-State metabolomics in P69 cells treated with GC7 (40µM, 24h). thank the reviewer for raising this point and we fully agree that this experiment is critical, as it directly connects hypusination to mitochondrial metabolism. Nevertheless, the identification of MRPP3 as the primary downstream mediator remains speculative, and the revised version has not provided a stronger rationale. The data do not strongly support, in a robust manner, that MRPP3 is the main target downstream of eIF5Ahyp. >> This criticism is unwarranted, the rationale for the study of MRPP3 is supported by multiple experimental findings from our work and work conducted by other research teams: - Our proteomic and polysome-profiling analyses reveal a disruption in mitochondrial function. Single-cell RNA analysis further supports this finding: epithelial cells with \"high DHPS\" expression exhibit perturbed mitochondrial translation compared to those with \"low DHPS\" (Extended Data Figure 6h,i). This pattern is consistent with TCGA data, where mitochondrial translation is impaired in patients with high DHPS expression relative to those with low expression (Fig. R6). Fig. R6 : Top 15 biological pathways significantly regulated in patients with hight DHPS high DHPS expression in the TCGA database. To validate these observations, we confirmed the inhibition of mitochondrial translation and identified a family of PPR proteins—among the most significantly downregulated following hypusination inhibition—that are known to regulate mitochondrial translation. Notably, MRPP3, a key member of this family, plays an essential role in mitochondrial translation. It is the only PPR protein with a catalytic site capable of cleaving polycistronic mitochondrial RNA, a process critical for mitochondrial RNA maturation and translation regulation. - Experimentally, our data clearly demonstrate both in vitro and in vivo the direct relationship between eIF5Ahyp and MRPP3 in PCa: 1. MRPP3 expression partially rescues the effects of eIF5Ahyp inhibition on mitochondrial translation (Fig. 4f), TCA cycle enzyme activity (Fig. 4g), cell migration and invasion (Extended Data Fig. 9i), and tumor growth in both xenograft and syngeneic models (Fig. 6f, Extended Data Fig. 10b). 2. MRPP3 is consistently overexpressed in PCa tumors, as shown in both our patient samples and proteomic databases (Fig. 6, Extended Data Fig. 10f and g), establishing a direct link between hypusination and MRPP3 in prostate cancer. Furthermore, the analysis of Sun et al. proteomic database showed a correlation between MRPP3, DHPS and eIF5A expression (Ext Data Fig. 7b). - The rationale for focusing on MRPP3 is fully addressed in the first revised version of the manuscript. “Given its essential role as a regulator of mitochondrial RNA maturation and function, both in vitro and in vivo, MRPP3 emerged as a key target, 31,32. MRPP3 was one of the most significantly downregulated proteins following eIF5Ahyp inhibition, with a Log fold 2 change of -2.99 in DU145 cells (Extended data Fig. 7a). Furthermore, we found that MRPP3 protein levels significantly correlate with the expression of DHPS, DOHH, eIF5A and A2 in the Sun proteomic database that includes 306 patients (Extended data Fig. 7b).” To conclude, as noted by reviewer 1: “the role of hypusine/MRPP3 pathway on the growth of prostate cancer cells is supported by numerous complementary experiments” and to our knowledge, this study is the first to demonstrate a role for MRPP3 in cancer. Significant discrepancies persist in mitochondrial functional assays across different models. For instance, oxygen consumption rate phenotypes upon DHPS and MRPP3 depletion are not fully aligned, raising concerns about the consistency of the proposed mechanism. Likewise, there is no correlation between levels of MRPP3 in the different models and the response to shDHPS or GC7 treatments (see Ext. Fig. 7c and Fig.2b as examples, equal reduction in MRPP3 by shDHPS in all tumorids, but different effect on tumor size). >> The discrepancy between the effects of shMRPP3 and shDHPS may arise because shDHPS expression is inducible, whereas shMRPP3 is constitutively expressed. This constitutive downregulation could allow cells to adapt to reduced MRPP3 levels, resulting in a more moderate impact on mitochondrial function. Notably, acute knockdown of MRPP3 using siRNA—thereby preventing cellular adaptation—resulted in significant inhibition of proliferation and a more pronounced effect on mitochondrial respiration similar to that induced by GC7 (Figure R7). Fig. R7 : Effects of siRNAMRPP3 on DU145 cells proliferation and mitochondrial metabolism. a, Immunoblot of MRPP3 in cells transfected with siRNAMRPP3; b, Cell number 72h after siMRPP3 transfection; c, Graphic representation of basal respiration, ATP production in cells transfected with siRNAMRPP3 (red bars). More importantly, the correlation of MRPP3 protein expression with eIF5Ahyp or DHPS levels in human PCa samples is not provided, which reduces the human relevance of the reported findings. >> The reviewer’s point is valid; we initially omitted the correlation analysis for our patient cohort. This has now been included in the revised manuscript (line 428: Of note, while we did not find a correlation between MRPP3 and DHPS or eIF5Ahyp in our cohort,). In our own dataset, we did not observe a correlation between the expression of MRPP3, DHPS, and eIF5Ahyp, likely due to the limited sample size. However, in the revised version initially sent, we highlight that analysis of the proteomic dataset published by Sun et al.—which includes 306 patients—demonstrates a clear and significant correlation among DHPS, eIF5A, and MRPP3 expression (Extended Data Fig. 10g). The quality of the data, particularly immunoblots and immunofluorescence images, remains suboptimal. In summary, despite the revision, the manuscript at this stage still does not provide a significant advance for the PCa field, and it does not meet the expected rigor and quality for publication in Nature Communications. >> We were surprised by this comment, as it was raised by only one reviewer, while the others explicitly noted: “Overall, this paper is well written and the role of hypusine/MRPP3 pathway on the growth of prostate cancer cells is supported by numerous complementary experiments.” (Reviewer #1) and “The findings presented herein add further complexity to the mode of action of this protein and further emphasize the potential value of targeting hypusination for therapeutic purposes. Overall, the paper is well written, the story is original and supported by several elegant and solid experimental approaches.” (Reviewer #2, 3). Furthermore, while we acknowledge that the immunoblots of the patient samples are not perfect, we are certainly willing to provide higher-quality images if required to meet the publication standards. Nice, December 9th, 2025 Answer to the reviewer: Reviewer #4 (Remarks to the Author): “I thank the authors for their thorough and thoughtful response to my previous critique and appreciate the considerable effort they have devoted to strengthening the manuscript. The additional analyses addressing AR signaling, including the lack of correlation between AR activity and hypusination pathway gene expression, and the demonstration that eIF5Ahyp inhibition does not alter AR levels or activity, help to clarify the AR-independence of the hypusination axis. These additions enhance both the mechanistic depth and clinical relevance of the study. I appreciate the authors’ responsiveness and support the publication of the revised manuscript in Nature Communications. Further improvement in the quality of the western blot images would enhance the overall clarity and presentation of the findings.” ANSWER: We sincerely thank Reviewer #4 for their supportive remark regarding the publication of our revised manuscript in Nature Communications. In response, we have enhanced the quality of the Western blot images to the highest possible standard and hope that these improvements are satisfactory. Dr Frédéric Bost"}, {"round": 2, "reviewer_comments": {"reviewer_1": "The authors have responded very precisely to each of my critics. The paper is clearer, very strong, and greatly improved by the syngeneic model. My initial enthusiasm has been strengthen by this revised submission.", "reviewer_2": "The authors have provided thorough and satisfactory responses to all comments. The revisions have substantially improved the manuscript, which is now suitable for publication.", "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": "I thank the authors for their efforts during the revision to address my previous comments, and I appreciate the additional experiments and new analyses included in the revised manuscript. However, most of my major concerns remain only partially (at most) addressed. As I mentioned in my previous review, the paper falls short in identifying which prostate tumors depend on eIF5Ahyp and in linking the response to targeting this pathway, either pharmacologically with inhibitors or through genetic manipulation with shRNA, to specific patterns of expression or dependencies. Although the revised version includes expanded expression analyses from TCGA and other public datasets, including neuroendocrine PCa, the new data do not provide a cohesive picture of the human relevance of the eiF5Ahyp axis or its expression across different stages or subtypes of PCa. The expression and dependency of this pathway in primary versus metastatic disease, AR-positive versus AR-negative tumors, or castration-resistant prostate cancer (CRPC) remain largely unexplored, and the results differ among the datasets analyzed, precluding reaching more definitive conclusions. It is still unclear what drives the increase in eiF5Ahyp and at what level (mRNA, protein, which step, in which stage?). The results from the different datasets and cohorts are scattered, superficially analyzed, and contradictory among them. The analysis of the scRNAseq dataset does not add any information. The UMAPs shown without splitting by normal or tumor do not demonstrate that the pathway is increased in tumor samples. The responses of the authors to address the contradictory results presented do not solve these problems. Similar inconsistencies are seen with the different model systems used in the study (cell lines and prostate tumoroids). First, the data are not robust enough across experiments, and there are still multiple discrepancies. For example, LNCaP cells show similar levels of eiF5Ahyp compared to normal prostate cells (P69) and lower than DU145 or PC3 (at least in the blots with GC7, Ext Fig. 3a). However, they respond to most of the proliferation, migration, and invasion assays better or at least as well (Ext. Fig.3b). Additionally, although normal controls (P69 and normal organoids) have been included for expression analysis and in one experiment for sensitivity to GC7, most experiments do not include controls run in parallel to demonstrate selectivity. While the inclusion of normal prostate organoids as controls for GC7 sensitivity is valuable, a detailed quantification of eIF5Ahyp and DHPS levels across the different PCa subtypes and correlation with sensitivity to GC7 or shDHPS is still missing. Significant discrepancies persist in mitochondrial functional assays across models. The revised manuscript includes new polysome profiling and proteomic data, which add weight to the involvement of eIF5Ahyp in mitochondrial function. Nevertheless, the identification of MRPP3 as the primary downstream mediator remains speculative, and the revised version has not provided a stronger rationale. The data do not strongly support, in a robust manner, that MRPP3 is the main target downstream of eIF5Ahyp. Significant discrepancies persist in mitochondrial functional assays across different models. For instance, oxygen consumption rate phenotypes upon DHPS and MRPP3 depletion are not fully aligned, raising concerns about the consistency of the proposed mechanism. Likewise, there is no correlation between levels of MRPP3 in the different models and the response to shDHPS or GC7 treatments (see Ext. Fig. 7c and Fig.2b as examples, equal reduction in MRPP3 by shDHPS in all tumorids, but different effect on tumor size). More importantly, the correlation of MRPP3 protein expression with eIF5Ahyp or DHPS levels in human PCa samples is not provided, which reduces the human relevance of the reported findings. The quality of the data, particularly immunoblots and immunofluorescence images, remains suboptimal. In summary, despite the revision, the manuscript at this stage still does not provide a significant advance for the PCa field, and it does not meet the expected rigor and quality for publication in Nature Communications."}, "author_response": ""}, {"round": 3, "reviewer_comments": {"reviewer_4": "I thank the authors for their thorough and thoughtful response to my previous critique and appreciate the considerable effort they have devoted to strengthening the manuscript. The additional analyses addressing AR signaling, including the lack of correlation between AR activity and hypusination pathway gene expression, and the demonstration that eIF5Ahyp inhibition does not alter AR levels or activity, help to clarify the AR-independence of the hypusination axis. These additions enhance both the mechanistic depth and clinical relevance of the study. I appreciate the authors’ responsiveness and support the publication of the revised manuscript in Nature Communications. Further improvement in the quality of the western blot images would enhance the overall clarity and presentation of the findings."}, "author_response": ""}]

Decision letter