Adaptation to cystine limitation stress confers a targetable lipid metabolism vulnerability in pancreatic ductal adenocarcinoma

Domain: chemistry
Published: 2025-12-31
Editorial outcome: major_revision

Abstract
Cystine/cysteine is critical for antioxidant response and sulfur metabolism in cancer cells and is one of the most depleted amino acids in the micro-environment of pancreatic ductal adenocarcinoma (PDAC). The effects of cystine limitation stress (CLS) on PDAC progression are poorly understood. Here we report that adaptation to CLS (CLSA) promotes PDAC cell proliferation and tumor growth through translational upregulation of the oxidative pentose phosphate pathway (OxPPP). OxPPP activates the de novo synthesis of nucleotides and fatty acids to support tumor growth. On the other hand, CLSA-mediated lipidomic reprogramming depends on triacylglycerides synthesis and lipid droplet formation to mitigate lipotoxicity. Through drug screening, we identify lomitapide as an inhibitor of CLSA PDAC tumor growth and a potent sensitizer of chemotherapy. Lomitapide inhibits triacylglycerides synthesis to interfere with CLSA and chemotherapy-induced lipidomic reprogramming. Taken together, we demonstrate that CLSA promotes PDAC tumor growth through metabolic reprogramming and lomitapide could be used to target the dysregulated lipid metabolism in PDAC.

Introduction
Pancreatic ductal adenocarcinoma (PDAC) is a highly aggressive cancer with a 5-year survival rate less than 13%. The PDAC tumor microenvironment is characteristically nutrient deprived due to desmoplasia, poor vascularization, and hyperactive cancer metabolism1,2. Plasticity in cancer metabolism is critical for cancer cells to overcome nutrient limitation stress and to support tumor growth and progression1. However, the roles of nutrient limitation stress in PDAC tumor growth and progression remained incompletely understood.

Cystine (Cys2) and cysteine (Cys) are important amino acid nutrients for the antioxidant response and sulfur metabolism3,4. In the oxidative environment in the blood, Cys is oxidized into Cys2. SLC7A11, the functional subunit of the Cys2/glutamate antiporter system xc−, is responsible for cystine uptake3,5. In the cell, Cys2 is reduced to Cys and used for the synthesis of essential sulfur metabolites, such as glutathione (GSH) and iron-sulfur clusters (Fe-S)6. Although Cys2 and Cys are non-essential amino acids, cancer cells depend on exogenous Cys2 for antioxidant response and survival4,7. Cys2 deprivation induces ferroptosis, a type of iron and lipid peroxidation-dependent cell death in pancreatic cancer and other cancers7–12. Intriguingly, Cys2 and Cys are among the most depleted amino acids in the PDAC tissue and tumor interstitial fluid13,14. It is unclear how PDAC cells adapt to the chronic Cys2 limitation stress (CLS) and how such adaptation affects PDAC tumor growth and progression.

Cancer cells upregulate anabolic metabolism, such as de novo synthesis of nucleotides and fatty acids (FA), to support cancer cell proliferation and tumor growth15. The oxidative pentose phosphate pathway (OxPPP) provides ribose-5-phosphate (R5P) for the de novo synthesis of nucleotides16 and NADPH for de novo FA synthesis17,18. glucose-6-phosphate dehydrogenase (G6PD), 6-phosphogluconolactonase (PGLS), and phosphogluconate dehydrogenase (PGD) are the three enzymes in the OxPPP, which use glucose-6-phosphate (G6P) as precursor for the synthesis of R5P and the reduction of NADP+ to NADPH16. G6PD catalyzes the rate limiting step of OxPPP and is upregulated in many cancer types, including PDAC19.

While the upregulation of lipogenesis provides lipids to support membrane synthesis during cancer cell proliferation, the accumulation of excess FA could lead to lipotoxicity and cell damage20–22. To protect cells from lipotoxicity, excess FA is esterified by diacylglycerol O-acyltransferase 1 and 2 (DGAT1 and 2) into triacylglycerides (TG) and stored in the lipid droplets (LD)22,23. LD accumulation correlates with tumor aggressiveness and therapy resistance in many cancer types24. In addition to serving as lipid storage organelles, LDs are crucial for cell survival under stress. Stress factors such as ER stress, acidosis, and chemotherapeutic agents can promote lipolysis and/or lipogenesis23,25. The storage of excess FA, polyunsaturated fatty acids, lipid peroxidation products, and acyl-ceramides in LD allows cells to avoid stress-induced lipotoxicity and cell death26. There are recent reports indicating that DGAT1/2 inhibitors could be used to inhibit tumor growth and improve the efficacy of chemotherapy and radiotherapy in colorectal cancer, melanoma, and glioblastoma20,27. However, the roles of LD in PDAC remain poorly understood28.

Here, we investigated the effects of chronic CLS in PDAC. We found that adaptation to CLS (CLSA) promotes PDAC cell proliferation, ferroptosis resistance, and tumor growth. CLSA PDAC cells translationally upregulate OxPPP enzymes to promote biosynthesis of NADPH, nucleotides, and FAs. Through screening of a metabolism-focus drug library, we identified that lomitapide could potently induce lipotoxicity in CLSA PDAC by suppressing TG synthesis, LD formation, and increasing toxic lipid species. Our data further showed that the FOLFIRINOX chemotherapy regimen induces lipidomics reprogramming and lomitapide could target FOLFIRINOX-induced LD formation to increase therapeutic efficacy. In patient-derived xenograft models and the KrasLSL-Kras G12D/+; Trp53LSL− R172H/+; Pdx1-Cre (KPC) engineered mouse model, lomitapide inhibited PDAC tumor growth and robustly improved the efficacy of FOLFIRINOX regimens. Our data shed new light on the role of nutrient stress in PDAC progression and showed that lomitapide could be used to exploit stress-induced vulnerability in PDAC lipid metabolism.

Results
Adaptation to cystine limitation stress promotes PDAC cell proliferation, ferroptosis resistance, and tumor growth
To determine whether PDAC cells might be subjected to CLS, we determined the levels of Cys and Cys2 in PDAC and para-tumor normal pancreatic tumor tissue from C57BL/6 mice orthotopically implanted with a PDAC line derived from the KPC (KrasLSL-G12D; Trp53LSL-R172H; Pdx1-Cre) model. The levels of Cys and Cys2 in tumor tissues were approximately 90% (for Cys) to 50% (for Cys2) lower when compared to para-tumor normal pancreatic tissues (Fig. 1A). Similarly, we observed 60% and 75% decrease in the levels Cys and Cys2, respectively, in patient PDAC tissues when compared to para-tumor normal pancreas control in a cohort of 11 PDAC patients (Fig. 1B). We further used Mass spectrometry imaging (MS imaging) to compare the spatial distribution of Cys and Cys2 in tumor tissues from the KFC (KrasLSL-G12D; Trp53fl/fl; Pdx1-Cre) spontaneous PDAC model. Our data showed that Cys levels and Cys/Cys2 ratios were decreased in pancreatic intraepithelial neoplasia (PanIN) and further decreased in carcinoma regions when compared to normal pancreatic tissues (Figs. S1A and 1C). Taken together, our data suggest that PDAC cells are subjected to chronic CLS during tumorigenesis and progression.

Most cell culture media (e.g., DMEM or RPMI) contain 200µM Cys2, which is significantly higher than Cys2 levels in the human plasma (25–50µM)29. Cells cultured in vitro have higher demand for Cys2 due to direct exposure to ambient O2. As shown in Fig. S1B, decreasing Cys2 concentrations to 50µM or lower in MiaPaCa-2 media led to increased phosphorylation of eIF2α and the upregulation of ATF4 protein levels, which suggested the induction of the integrated stress response by CLS. As expected, acute reduction of Cys2 from 200µM to 50 or 25µM led to lipid peroxidation and ferroptosis-like cell death in PDAC cells in 72h (Fig. S1C–E). In colony formation assay, Cys2 limitation inhibited colony formation (Fig. S1F). Approximately 5 to 30 percent of PDAC cells were able to adapt to CLS at 25µM and resume cell growth and proliferation after 3–4 weeks exposure to CLS (Figs. S1F, G and 1D, E). Supplementation with 5% BSA in Cys2 limited media (25µM Cys2) not only had no rescue effect, but paradoxically further inhibited colony formation (Fig. S1F). The proportion of PDAC cells adapted to 50µM CLS was much higher (Fig. S1F). Here we use CLSA-25 and CLSA-50 to refer to PDAC cells adapted to 50 or 25µM Cys2 limitation stress, respectively. Culturing PDAC cells in CLS-25 media (25µM Cys2) reduced the intracellular Cys levels by approximately 75% to 90% in 24–48h (Fig. 1F). Although Cys level modestly recovered in CLSA-25 MiaPaCa-2 and PANC-1 cells after 4-week adaptation, it was still ~50–60% lower than naïve control cells. No recovery of intracellular Cys was observed in CLSA-25 Pan02 and KPC cells (Fig. 1F). Interestingly, CLSA PDAC cells proliferate much faster than parental cells, despite severe reduction of intracellular Cys (Figs. 1G and S1H). After 4-week adaptation, the ATF4 levels in CLSA cells were no longer elevated, which indicated that CLSA cells overcame integrate stress response despite lower intracellular Cys (Fig. S1I). CLSA-25 cells had increased ability to uptake FITC-Cys2 (Fig. S1J). Consistent with this observation, when cultured in Cys2 replete media, the intracellular Cys levels in CLSA cells were much higher than control cells (Fig. S1K). However, there was no increase in SLC7A11 abundance in CLSA cells (Fig. S1I). Doxycycline-induced chronic knockdown of SLC7A11 (for 4 weeks) also increased cell proliferation (Fig. 1H). Given the considerable interest in using Cys2 deprivation agents as potential cancer therapeutics, we asked whether CLS induced by pharmacological genetically SLC7A11 inhibitors might have similar pro-proliferation effects on PDAC cells. We previously reported that imidazole ketone erastin (IKE) induced ferroptosis in PDAC cell lines and patient-derived organoids (PDOs)30. As shown in Fig. 1I, PDAC organoids adapted to IKE-induced CLS (CLSA-I, for inhibitor induced CLSA) also grew faster than naïve control PDOs.

GPX4 is the sole GSH peroxidase responsible for scavenging lipid peroxide and preventing ferroptosis. As shown in Fig. 1J, K, the IC50 of RSL-3 in CLSA-25 cells and CLSA-I PDOs increased dramatically by ten to 500-fold when compared to their respective naïve controls. CLSA-50 cells and SLC7A11 chronic knockdown cells also developed RSL-3-induced ferroptosis resistance, although to a lesser extent when compared to CLSA-25 cells (Figs. 1J and S1L). In addition to the GSH-GPX4 axis, CoQ10 and BH4 have been reported to be potent suppressors of lipid peroxidation and ferroptosis31–34. Interestingly, CLSA PDAC cell were more sensitive to FSP1 inhibitor (iFSP1) and DHFR inhibitor (methotrexate) (Fig. S1M, N), which indicated increased reliance of these alternative anti-ferroptosis pathways in CLSA PDAC cells.

To understand the potential mechanisms underlying CLSA-mediated ferroptosis resistance, we investigated the protein levels of major regulators of ferroptosis resistance in GPX4 and CoQ10 including GPX4, FSP1, DHODH, COQ2, COQ6, and COQ9. As shown in Fig. S1O, P, there was little change in GPX4, COQ6, and COQ9 levels. However, FSP1 levels were downregulated, while COQ2 was modestly upregulated in CLSA PDAC cells. To determine the role of the CoQ10 pathway, we used iFSP1, brequinar (BQR), and COQ2 shRNA to suppress the ubiquinol recycling (through FSP1 and DHODH inhibition) and CoQ10 synthesis (through COQ2 knockdown). COQ2 knockdown almost completely, and iFSP1 or BQR treatment partially, overcame RSL-3-induced ferroptosis resistance in CLSA PDAC cells (Fig. S1Q). Taken together, our data indicated that the ferroptosis resistance in CLSA PDAC cells was at least partially dependent on the CoQ10 anti-ferroptosis axis.

To determine whether CLSA-mediated PDAC cell proliferation and ferroptosis resistance depends on continuous CLS pressure, we cultured CLSA MiaPaCa-2 cells in Cys2 replete (200µM) media for 4 weeks. As shown in Fig. S1R, S, even after 4 week culture in Cys2 replete conditions, the CLSA cells maintain elevated cell proliferation and ferroptosis resistance. These data indicated that CLSA phenotypes, once established, are relatively stable.

To determine whether CLSA affects tumor growth, we implanted CLSA Pan02 and KPC cells and their naïve control cells orthotopically into the pancreas of C57BL/6 mice. Mice implanted with CLSA-50 Pan02 cells grew modestly larger tumors, with increased numbers of liver metastases when compared to the control group (Fig. 1L–N). The liver metastasis incident increased from 30% in control to 90% in CLSA-50 group (Fig. 1M, N). In the KPC xenograft experiment, the growth of orthotopically implanted CLSA-25 KPC tumors was dramatically faster than control tumors, although no metastasis was detected in either group (Fig. 1O, P). Similarly, orthotopically implanted CLSA-I PDOs developed larger tumors when compared to naïve control (Fig. 1Q, R). Taken together, our data showed that CLSA promotes PDAC cell proliferation, ferroptosis resistance, and tumor growth.

To determine whether nutrient limitation of other amino acids might induce adaptations like CLSA, we cultured MiaPaCa-2 cells in media containing reduced amounts of glutamine (400µM), tryptophan (10µM), or arginine (2µM), respectively. These amino acids and concentrations were selected based on previous reports showing their depletion in PDAC13,35. MiaPaCa-2 cells were able to proliferate in Trp-limited media, but not in Glu- or Arg-limited conditions for 2 weeks (Fig. S1T). BSA supplementation allowed PDAC cell adaptation to glutamine limitation (Fig. S1U), as previously reported14. However, Glu-limitation adapted cells (in the presence of 5% BSA) proliferates lower than naïve control (Fig. S1V). Although MiaPaCa-2 cells could proliferate under Trp limitation conditions for 2 weeks (Fig. S1T), most cells stopped proliferating after 2 weeks (Fig. S1V, W), which could not be rescued by BSA supplementation (Fig. S1W). Therefore, our data suggested that CLS induced a unique adaptation mechanism in PDAC to promote cell proliferation and tumor growth.

CLSA cells downregulate iron sulfur cluster synthesis to promote glycolysis
A major function of Cys is to be used for GSH synthesis, which is required for antioxidant response and ferroptosis resistance. Acute Cys limitation (25µM) markedly reduced GSH levels by fifty to ninety percent in PDAC cells (Fig. S2A), which is consistent with the induction of ferroptosis by acute CLS. However, GSH levels in CLSA-25 PDAC cells were comparable to their naïve control cells (Fig. S2A), despite little to no recovery in intracellular Cys. To understand the effects of CLSA on Cys metabolism, we used 15N2, 13C6-cystine to label Cys metabolites in MiaPaCa-2 cells. Control or CLSA-25 cells were incubated with 200µM (for control) or 25µM (for CLSA-25) 15N2, 13C6-Cys2 for 0, 2, or 4h. The fractional labeling of M+4 Cys reached 68% at 2h and plateau after that in the control group (Fig. 2A). The M+4 Cys fractions in CLSA-25 group were 54% and 38% at 2 and 4h, respectively. Despite lower fractional labeling of M+4 Cys in CLSA-25 cells, the fractional labeling of GSH and GSSG levels in the two groups were similar (Fig. 2B), which suggested faster turnover of GSH/GSSG in CLSA-25 cells.

We noted that the labeling of M+4 Alanine was reduced in CLSA-25 cells by 80% to 90% after 4 or 2h labeling, respectively (Fig. 2C). Alanine is a by-product of Cys desulfurase NFS1, which uses Cys as substrate for the synthesis of Fe-S36. Fe-S is a critical co-factor for oxidoreductases such as aconitase (ACO) and mitochondrial respiratory complexes I, II and III36. We confirmed that the activities of ACO1 and ACO2 were markedly reduced in CLSA-25 PDAC cells (Fig. 2D). The protein levels of NDUFS1, a Fe-S binding subunit in complex I, was downregulated in all the CLSA-25 PDAC cells. The downregulation of Fe-S proteins in complex II (SDHB) and complex III (RISKE) was also observed in CLSA MiaPaCa-2 cells (Fig. 2E). The downregulation of respiratory complex proteins was not due to global suppression of mitochondria biogenesis, since there was no significant difference in mitochondria mass between control and CLSA cells (Fig. S2B). The upregulation of TFRC, IRP2 in CLSA cells was consistent with the notion that downregulation of the Fe-S synthesis activates Iron Starvation Response (Fig. 2F). Interestingly, ISCU and NFS1, two core components of the iron-sulfur cluster assembly complex, were significantly downregulated in CLSA PDAC cells (Fig. 2F). Mitochondria stress test and glycolysis stress test showed that CLSA cells markedly downregulated mitochondrial oxygen consumption rates (OCR) while upregulating extracellular acidification rate (ECAR) (Fig. 2G, H). Glucose uptake was also dramatically upregulated in CLSA cells (Fig. S2C). Our data suggested that by downregulating Fe-S synthesis, CLSA cells promote a switch from mitochondrial oxidative phosphorylation to glycolytic metabolism. The suppression of Fe-S assembly could be due to the decreased abundance of iron-sulfur assembly complex, the lower intracellular Cys, or the combination of both.

Interestingly, the steady-state labeling of Cys, GSH, GSSG, and CoA all decreased in CLSA-25 cells after 24h incubation with 15N2, 13C6-Cys2 (Fig. S2D), which suggested that CLSA-25 cells might enhance their ability to obtain Cys from alternative sources. Since CSE was upregulated in CLSA MiaPaCa-2 (Fig. S2E), we used 13C-Serine as tracer to investigate the effects of CLSA on de novo Cys synthesis through the transsulfuration pathway. Despite approximately 30% labeling of cystathionine by 13C-Serine, the M+1 Cys was less than 1% in naïve and undetectable in CLSA MiaPaCa-2 cells (Fig. S2F). Although there was 20-30% labeling of M+1 GSH (Fig. S2F), this was likely due to conversion of 13C-Serine to 13C-Glycine, which is subsequently used for GSH synthesis. These observations are similar to findings reported by the DeNicola’s group37 and suggest that transsulfuration pathway is unlikely a major source of Cys in either naïve or CLSA cells.

It has been previously reported that cancer cells could acquire amino acids through micropinocytosis14,38. CLSA PDAC cells significantly increased micropinocytosis uptake of FITC-dextran, which could be blocked by EIPA (Fig. S2G, H). Therefore, micropinocytosis of extracellular proteins could potentially serve as an alternative source of Cys in CLSA PDAC cells.

Metabolic reprogramming in CLSA cells activates PPP metabolism and nucleotide synthesis
To understand the CLSA-induced metabolic reprogramming, we performed metabolomics screening using control and CLSA-25 PDAC cells (Figs. 3A and S3A–D). Metabolic set enrichment analysis (MSEA) showed that Warburg effects, Glycolysis, Pentose phosphate pathway (PPP), and nucleotide metabolisms (both Purine and Pyrimidine) were among the most overrepresented metabolic pathways in CLSA-25 MiaPaCa-2 and/or PANC-1 cells (Fig. 3A).

Nucleotides are critical building blocks required for the synthesis of rRNA, mRNA, and DNA in proliferating cells15. PPP is a glycolysis shunt pathway that provides R5P and PRPP (Phosphoribosyl pyrophosphate), which are essential precursors for the synthesis of both purine and pyrimidine nucleotides15,39. CLSA-25 cells have increased levels of multiple ribonucleotides and deoxyribonucleotides (Figs. 3B and S3E, F). To determine whether CLSA activates PPP and de novo nucleotide synthesis, we used [U-13C]-glucose and LC-MS/MS to analyze the effects of CLSA on the glucose entry into glycolysis and PPP metabolism (Fig. 3C–E). As shown in Fig. 3D, E, CLSA increased glucose flux into glycolytic metabolites (Fig. 3E), PPP metabolites (R5P, PRPP), and nucleotides (IMP, UMP) (Fig. 3E). Our data suggested that CLSA-mediated metabolic reprogramming promotes glycolysis, PPP, and de novo nucleotide synthesis to support cancer cell proliferation and tumor growth.

OxPPP is translationally upregulated in CLSA PDAC cells to promote nucleotides and NADPH synthesis
G6PD and transketolase (TKT) are the first and rate limiting enzymes for the oxidative and reductive PPP, respectively. Given the importance of de novo nucleotide synthesis in cell proliferation, we evaluated the effects of a G6PD inhibitor (G6PDi1) and a TKT inhibitor (Oxythiamine) on the proliferation of CLSA 25 and naïve PDAC cells. As shown in Fig. S4A, B, G6PDi1 abrogated CLSA-mediated cell proliferation in MiaPaCa-2 and PANC1 cells, while Oxythamine had no effect. CLSA PDAC cells were also more sensitive to G6PDi1-induced cell death (Fig. S4C). To determine whether OxPPP might be upregulated by CLSA, we evaluated the protein abundance of G6PD, PGLS, and PGD in CLSA-25 PDAC cells and CLSA-I PDOs. As shown in Fig. 4A, B, G6PD protein levels were increased in all the CLSA-25 cells and CLSA-I PDOs when compared to their naïve controls. The protein levels of PGLS and PGD were also upregulated in CLSA cells and PDOs except for MiaPaCa-2 (for PGLS) and Capan-2 (for PGD) (Fig. 4A, B). Similar upregulation of OxPPP proteins was observed after doxycycline-induced SLC7A11 knockdown in PANC-1 and MiaPaCa-2 cells for 4 weeks (Fig. S4D). Moreover, the upregulation of OxPPP proteins in CLSA-25 MiaPaCa-2 cells did not depend on the continuous presence of CLS (Fig. S4E).

To determine whether CLS in the PDAC patient tumor microenvironment might also lead to PPP upregulation, we stained G6PD and PGD in PDAC tissues and paired para-tumor normal tissue from 18 patients. As shown in Fig. 4C, D, the protein levels of G6PD and PGD were robustly upregulated in PDAC tissues when compared to paired para-tumor pancreatic tissues. To investigate whether OxPPP upregulation might contribute to PDAC progression, we evaluated the abundance of G6PD in PDAC tissues from a cohort of 100 patients. As shown in Table S1, G6PD high patients had larger tumor size, more advanced TNM stages, and higher incidence of lymph node metastasis (Table S1). G6PD high patients also had lower overall survival (OS) and relapse free survival (RFS) (Fig. S4F), which indicates a critical role for OxPPP in PDAC tumor growth and progression.

Next, we investigated the mechanism underlying CLSA-mediated OxPPP upregulation in PDAC. We found no significant changes in the mRNA transcript levels of the three OxPPP genes (G6PD, PGLS, and PGD) in CLSA-25 cells (Fig. S4G). G6PD is a very stable protein, with no detectable degradation even after 12–24h cycloheximide (CHX) treatment (Fig. S4H). Therefore, we hypothesized that OxPPP enzymes might be translationally regulated in CLSA PDAC cells. We used L-Azidohomoalanine (AHA) to label newly translated proteins in CLSA-25 and naïve MiaPaCa-2 and PANC-1 cells40. The labeled peptides were tagged using a biotin-alkyne click-chemistry probe. After pull-down with streptavidin, the abundance of AHA-labeled G6PD, PGLS, and PGD was determined by Western blotting. The levels of newly translated G6PD and PGD were two to fivefold higher in CLSA MiaPaCa-2 and PANC-1 cells when compared to control (Fig. 4E). AHA-tagged PGLS only increased in CLSA-25 PANC-1 cells, but not in MiaPaCa-2 cells (Fig. 4E).

To further investigate the translational regulation of PPP enzymes, a sucrose gradient polysome profiling experiment was carried out (Fig. 4F, G). Polysome profiles showed an overall shift of mRNA into heavier polysomes in CLSA-25 MiaPaCa-2 cells (Fig. 4F), which indicated upregulation of translational initiation. The peak distribution of G6PD and PGD mRNA shifted from fraction 3 in control cells to fraction 6 and 4, respectively, in CLSA-25 cells, which indicated that the number of ribosomes associated with those mRNAs was higher in CLSA-25 cells compared with control cells. In contrast, the peak distribution of PGLS and GAPDH mRNA shifted toward lighter fractions, which is consistent with AHA labeling results in MiaPaCa-2 (Fig. 4G). The shift toward heavier polysomes for the G6PD and PGD mRNAs suggests that OxPPP is translationally upregulated in CLSA cells.

To investigate the role of OxPPP in CLSA-mediated phenotypes, we used RNAi to knockdown G6PD in PDAC cells (Fig. S4I). Both nucleotide levels (Fig. 4H, I) and NADPH/NADP+ ratios (Fig. 4J) were increased in CLSA-25 PDAC cells, which was suppressed by siRNA depletion of G6PD (Figs. 4H–J and S4J). G6PD siRNA also inhibited the CLSA-mediated increase in ferroptosis resistance and cell proliferation (Fig. S4K, L). The siRNA results were confirmed with doxycycline-induced knockdown of G6PD (Fig. S4M–O). To determine whether activation of OxPPP is sufficient to mediate CLSA phenotypes, we overexpressed G6PD in naïve PDAC cells (Fig. S4P). G6PD overexpression increased resistance to RSL3- and iFSP1-induced ferroptosis in PDAC cells (Fig. S4Q, R), while cell proliferation was not affected by ectopic G6PD (Fig. S4S). Taken together, our data suggested that the activation of OxPPP is at least partially responsible for CLSA-mediated nucleotide synthesis, cell proliferation, and ferroptosis resistance.

CLSA PDAC cells are hypersensitive to the lipid metabolism drug lomitapide
To investigate whether CLSA could expose exploitable metabolic vulnerabilities, we performed a drug screening using a metabolism-focus library of more than 800 compounds (Table S2). Seventy-six compounds showed more than 70% inhibition of cell viability in CLSA group (Fig. 5A). Among the most effective drugs were glycolysis/glucose uptake inhibitors (e.g., PFK158, BAY-876) and nucleotide synthesis inhibitors (e.g., Leflunomide, Pemetrexed acid) (Figs. 5A and S5A), which are consistent with upregulation of glycolysis and nucleotide synthesis in CLSA cells. Approximately 30% of the positive hits were compounds targeting lipid metabolism, including many FDA-approved drugs for cardiovascular diseases (e.g., Lomitapide, Mevastatin) and type II diabetes (e.g., Troglitazone, Pioglitazone) (Figs. 5A and S5A). Considering the excellent safety profiles of lipid metabolism drugs, several drugs within this group, along with Denifanstat (FASN inhibitor) and A939572 (SCD1 inhibitor), were further investigated in naïve and CLSA PDAC cells (Figs. 5B and S5B). Among these drugs, lomitapide showed excellent efficacies toward CLSA PDAC cells and PDOs with IC50 in the high nanomolar to low micromolar range (Fig. 5B, C). Lomitapide-induced cell death in control and CLSA PDAC cells could be partially rescued by pan-caspase inhibitor zVAD-fmk and RIPK1 inhibitor necrostatin-1, but not by ferrostatin-1 (Fig. S5C). Moreover, lomitapide treatment had no effect on lipid peroxidation in either control or CLSA PDAC cells (Fig. S5D). Therefore, lomitapide-induced cell death in PDAC cells likely involved apoptosis and necroptosis, but not ferroptosis.

Lomitapide is an orphan drug approved by the FDA for the treatment of homozygous familial hypercholesterolemia (HoFH)41. Developed as an inhibitor for microsomal triacylglycerides transfer protein (MTTP), lomitapide inhibits the transfer of TG to ApoB in hepatocytes and enterocytes to suppress the secretion of ApoB-containing lipoprotein into the bloodstream41,42. As shown in Fig. 5D–F, orthotopically implanted CLSA-25 MiaPaCa-2 xenograft grew faster than naïve control tumors. The CLSA-25 group was more sensitive to the anti-tumor effect of lomitapide and treatment with 10mg/kg lomitapide completely abrogated the CLSA effects on promoting tumor growth (Fig. 5D–F).

Lomitapide induces lipotoxicity by suppressing triacylglycerides synthesis and LD formation
In an effort to determine the mechanism underlying lomitapide cytotoxicity, we found no detectable protein levels of MTTP in naïve or CLSA PDAC cells (Fig. S5E). Therefore, we performed targeted lipidomics screening to investigate the effect of lomitapide treatment on lipid metabolism in MiaPaCa-2 cells. As shown in Figs. 5G and S5F–J, lomitapide treatment (1µM) significantly decreased the levels of TG and cholesterol ester (CE) while increasing the levels of free fatty acids (FFA) and acyl-carnitines (CAR), two toxic lipid species. The levels of phospholipids (PL) and lyso-phospholipids (LPL) were also increased after lomitapide treatment (Fig. S5G, H). TLC analysis (Figs. 5H, I and S6A, B) showed that lomitapide treatment decreased TG levels in PDAC cells in a dose-dependent manner, while the levels of DG were not affected. LD staining and confocal imaging indicated that lomitapide robustly inhibited LD formation in PDAC cells (Fig. 5J, K). It is interesting to note that when compared to DGAT1 inhibitor (DGAT1i) A922500 and DGAT2 inhibitor (DGAT2i) PF-06424439, lomitapide was able to achieve larger reduction of TG levels at much lower concentrations (Fig. S6A, B). Immunofluorescence staining of MiaPaCa-2 xenograft tumor sections showed CLSA increased Perilipin 2 (PLIN2, LD marker) staining by approximately twofold (Fig. S6C). Lomitapide treatment decreased PLIN2 staining intensity in both control and CLSA tumors by approximately twofold (Fig. S6D). Our data indicated that lomitapide treatment reduced LD levels in cell culture and xenograft tumor models. Given recent reports implicating LD in ferroptosis resistance43,44, we tested the effects of lomitapide on PDAC cell sensitivities to RSL-3 induced ferroptosis. As shown in Fig. S6E, lomitapide (0.5µM) decreased RSL-3 IC50 by two to four fold and 15 to 40-fold in naïve and CLSA PDAC cells, respectively. Therefore, although lomitapide doesn’t induce ferroptosis as a single agent, it could potentially be used to sensitize PDAC cells to ferroptosis.

To understand the mechanism by which lomitapide regulates TG, we used oleic acid-alkyne (OA-alkyne), a click-chemistry fatty acid probe, to evaluate the effects of lomitapide treatment on de novo TG synthesis. MiaPaCa2 and PANC-1 cells were pre-treated with various concentrations of lomitapide for 2h and then pulsed with OA-alkyne. After 30min labeling, the lipids were extracted, labeled with 3-azido-7-hydroxycoumarin through click-chemistry reaction, and the OA-alkyne labeled lipids were resolved through TLC. As shown in Fig. 5L, M, lomitapide inhibited de novo TG synthesis with an IC50 of approximately 0.5µM. Accompanying the dose-dependent decrease in OA-labeled TG, the free, unincorporated OA levels were increased in lomitapide treated PDAC cells (Fig. 5L, M). When [U-13C]-OA was used as tracer, lomitapide inhibited 13C-OA incorporation into neutral lipids, while the labeling of free OA or OA in polar lipids are not affected (Fig. S6F). TG synthesis is essential for cells to neutralize FFA-induced lipotoxicity22. Therefore, we determined the effects of lomitapide treatment on sensitivity to palmitate-induced lipotoxicity in PDAC cells. As shown in Fig. 5N, co-treatment with 0.5µM lomitapide reduced palmitate IC50 in CLSA MiaPaCa-2 and CLSA PANC-1 cells from 168µM and 125µM to 10µM to 35µM, respectively, which suggests that lomitapide treatment increases lipotoxicity sensitivity in PDAC cells.

The inhibition of TG synthesis and accumulation of FFA in lomitapide-treated PDAC cells is reminiscent of similar phenotypes in DGAT1 and DGAT2 knockout mice45. Therefore, we investigated the effects of lomitapide on DGAT activities following a previously reported protocol46. As shown in Fig. S6G, microsomal membranes isolated from mouse liver were able to synthesize TG using dioleyl glycerol (DOG) and NBD-palmitoyl-CoA as substrate. Using this assay, we determined that lomitapide could inhibit DGAT activation with an apparent IC50 of approximately 1µM (Fig. 5O). It has been previously reported that lomitapide could be processed and degraded by cytochrome P45041, which is enriched in the microsomal membrane used for the in vitro DGAT activity assay. Pre-incubation of lomitapide with microsomal membranes (from mouse liver, naïve or CLSA-25 MiaPaCa-2 cells) for 1h or longer completely abrogated its inhibition of DGAT activities (Fig. S6H). Therefore, the inhibitory effect of lomitapide on DGAT activity in this in vitro assay is likely underestimated.

To determine whether the inhibition of DGAT1 and 2 might be responsible for the cytotoxicity of lomitapide, we used siRNA to deplete DGAT 1 and 2 in MiaPaCa-2 and PANC-1 cells. As shown in Fig. S6I–K, DGAT1 or 2 knockdowns significantly reduced the LD staining in control and CLSA-25 PDAC cells. Moreover, CLSA-25 PDAC cells were more sensitive to DGAT1 or 2 siRNA induced cell death than naïve control cells (Fig. 5P). Taken together, our data suggested lomitapide inhibits TG synthesis and LD formation at least in part by targeting DGAT activities in PDAC cells, and CLSA cells are hypersensitive to lomitapide-induced lipotoxicity, likely due to CLSA-mediated activation of lipogenesis.

CLSA promotes lipogenesis and lipid droplet formation in PDAC
Since CLSA PDAC cells are hypersensitive to lipid metabolism drugs, we speculated that CLSA might affect lipid metabolism in PDAC. Notably, OxPPP has been implicated in promoting lipogenesis in adipocytes and cancer cells17,47. NADPH, along with malonyl-CoA, is required for de novo fatty acid synthesis by fatty acid synthase and suppression of OxPPP inhibits lipogenesis in cancer cells17,18. We used targeted lipidomics and untargeted lipidomics screening to examine the effect of CLSA on lipid metabolism changes in PANC-1 and MiaPaCa-2 cells, respectively. (Figs. 6A, B and S7A–D). Interestingly, TG was the most upregulated lipid species in both CLSA-25 lines when compared to their naïve controls (Fig. 6A, B). We confirmed through thin layer chromatography (TLC) that TG was upregulated in CLSA-25 PANC-1 and MiaPaCa-2 cells (Fig. 6C, D). Confocal microscopy indicated that CLSA promotes LD formation (Fig. 6E–G).

Lipase activity assay showed that there was no change in the activities of ATGL, the major lipase in TG lipolysis (Fig. S8A), in CLSA PDAC cells, which suggested that the elevated TG and LD in the adapted cells were not due to inhibition of lipolysis. G6PD overexpression (OE) in naïve MiaPaCa-2 and PANC-1 cells was sufficient to increase TG and LD levels (Fig. S8B–E). Conversely, G6PD knockdown in CLSA PDAC cells significantly decreased TG levels (Fig. 6H, I). These data suggested that CLSA promotes lipogenesis and LD formation through activation of the OxPPP. To further critically investigate this notion, we used 13C-glutamine labeling to determine the effects of CLSA and G6PD inhibition (with G6PDi1) on de novo FA synthesis. As shown in Fig. 6J, K, 13C-labeled palmitate (PA, C16:0) and stearate (SA, C18:0) were increased in CLSA-25 PANC-1 cells when compared to naïve control cells, especially those species with more than 8 13C atom incorporations (M+x, x≥8). These results indicated the activation of de novo FA synthesis in CLSA PDAC cells. The inhibition of the OxPPP pathway with G6PDi1 suppressed de novo PA and SA synthesis and largely abrogated the effects of CLSA-25, especially in PA and SA species with greater than 12 13C atom incorporations (M+x, x≥12). Taken together, our data strongly indicated that CLSA-25 promotes de novo lipid synthesis in an OxPPP-dependent manner.

Since G6PD overexpression promotes TG synthesis and LD formation, we further determined the effects of OxPPP activation on lomitapide sensitivity. As shown in Fig. S8F, G6PD overexpression reduced the lomitapide IC50 by approximately twofold, which indicated that activation of OxPPP was sufficient to sensitize PDAC cells to lomitapide.

To determine whether LD formation is upregulated in PDAC, we performed LD staining in PDAC tissue cryosections from 30 patients. LD staining in PDAC patient tissues and paired para-tumor normal tissues revealed dramatic increase in LD formation in tumor tissues (Figs. 6L, M and S8G). PLIN2 was also upregulated in PDAC tissues when compared to paratumor normal (Fig. S8H). In PDAC tissues, LD almost exclusively colocalized with CK19 positive PDAC cells, but not with α-SMA positive cancer-associated fibroblast cells (Fig. S8G). LD levels in PDAC patient tissues significantly correlated with G6PD staining intensities (Fig. S8I, J). Taken together, our data indicated that OxPPP upregulation in CLSA PDAC promotes lipogenesis and LD formation.

Lomitapide inhibits chemotherapy-induced LD-formation and TG synthesis and sensitizes PDAC tumors to modified FOLFIRINOX in PDX and KPC models
TG synthesis and LD formation are critical for cells to avoid stress-induced lipotoxicity21,23. Targeted lipidomics analysis of MiaPaCa-2 cells treated with modified FOLFIRINOX (mFOLFIRINOX)48 chemotherapy showed that mFOLFIRINOX treatment induced dramatic lipidome reprogramming that increased TG levels (especially the levels of TG containing long chain FA and PUFAs) while reducing the levels of PL and LPL (Figs. 7A, B and S9A–E). This observation is consistent with the notion that chemotoxic stress induces lipolysis and stores excess FFA in TG and LD to mitigate lipotoxicity21,23. We confirmed that mFOLFIRINOX treatment increased TG and LD levels (Figs. 7C and S10A, B). mFOLFIRINOX-induced TG synthesis and LD formation was abrogated by lomitapide treatment (Figs. 7C and S10A, B). Co-treatment of PDOs with mFOLFIRINOX and 200nM lomitapide synergistically reduced mFOLFIRINOX IC50 by approximately two to fivefold in control or CLSA-I PDOs, respectively (Figs. 7D and S10C). Chemo-sensitization effects of lomitapide could be observed at a concentration as low as 50nM (Figs. 7D and S10C). Similar chemo-sensitization effects were observed when lomitapide was combined with the Abraxane/Gemcitabine chemotherapy regimen (Fig. S10D). The knockdown of DGAT1 or DGAT2 also dramatically increased chemo-sensitivity (Fig. S10E). Conversely, inhibition of TG lysis with ATGL inhibitor decreased chemosensitivity (Fig. S10F, G). Taken together, our data suggested that lomitapide sensitizes PDAC to chemotherapy by targeting DGAT-mediated TG synthesis and LD formation.

To determine whether lomitapide could be used to improve the efficacy of FOLFIRINOX therapy, we used PDX models derived from two PDAC patients (Fig. 7E). NSG mice bearing PDX tumor fragments were administered with vehicle control, lomitapide, mFOLFIRINOX or the combination treatment when the tumor size reached 3mm in diameter (Fig. 7E). As shown in Fig. 7F, G, mFOLFIRINOX treatment inhibited the tumor growth in PDX-1 and PDX-2 mice by 52% and 16%, respectively. Lomitapide treatment alone inhibited PDX-1 and PDX-2 growth by 40% and 35%, respectively. When combined with mFOLFIRINOX, the inhibition of tumor growth was further enhanced to 78% and 77% (Figs. 7F, G and S10H). The inhibitory effects of single and combination treatments on tumor growth were confirmed with positron emission tomography scan using 18F-fluorodeoxyglucose as tracer (Figs. 7H, I and S10I).

To further evaluate the chemo-sensitization effects of lomitapide, we tested the effects of lomitapide and mFOLFIRINOX treatments in the genetically engineered KPC (LSL-KrasG12D/+; LSL-Trp53R172H/+; Pdx1-Cre) PDAC model. The PDAC tumor formation in KPC mice was monitored by ultrasound imaging. Mice were randomly assigned into one of the four treatment groups (vehicle, lomitapide, mFOLFIRINOX, or combination) after confirmation of tumorigenesis. The mice were treated for 4 weeks, and the tumor growth was monitored through ultrasound during this period. After stopping treatment at week 4, the mice were further monitored for survival. As shown in Fig. 7J–L, after 4 weeks of treatments, lomitapide and mFOLFIRINOX reduced KPC tumor volume by 23% and 43%, respectively. The combination treatment reduced tumor size by 78% (Fig. 7J, K). As a monotherapy, lomitapide improved the median survival from 52 days (in control group) to 70 days (p=0.04). The median survival in the mFOLFIRINOX group was 65 days (p=0.20). The combination treatment further increased the median survival to 121 days (p=0.001) (Fig. 7L). Therefore, lomitapide could inhibit tumor growth and improve animal survival in KPC model as a single agent. When combined with mFOLFIRINOX, lomitapide robustly increased the chemotherapy efficacy and prolonged animal survival. Importantly, although mFOLFIRINOX treatment modestly reduced the body weight of KPC mice, lomitapide treatment, alone or in combination with mFOLFIRINOX, had no additional effects on weight loss (Fig. S10J). These data indicated that lomitapide and its combination with mFOLFIRINOX were well tolerated in mice.

PLIN2 staining of tumor tissues collected from KPC mice showed that mFOLFIRINOX increased LD levels, which could be inhibited by lomitapide (Fig. 7M, N). LD staining in PDX tissue cryosections showed that mFOLFIRINOX treatment significantly increased LD levels, which could be inhibited by lomitapide (Fig. S10K–L).

Taken together, our data suggested that lomitapide has potent chemo-sensitization effects, potentially through inhibiting TG synthesis, LD formation, and enhancing chemotherapy-induced lipotoxicity.

Methods
Antibodies, key reagents, and inhibitors
Information for antibodies, key reagents, and inhibitors are included in Tables S3 and S4, respectively.

Cell culture
The PDAC cell lines (MiaPaCa-2, PANC-1, SW-1990, Capan-2) were obtained from the ATCC. KPC cells were derived from Kraslsl-KrasG12D/+; Trp53R172H/+; Pdx1-Cre (KPC) genetically engineered mouse model. Pan02 cell was a gift from Dr. Shari Pilon-Thomass (Moffitt Cancer Center). All ATCC cell lines were characterized or authenticated by the ATCC using short tandem repeat profiling and passaged in our laboratory for fewer than 6 months before use. All cell lines used were free of microbial (including mycoplasma) contamination. We routinely perform test for mycoplasma contamination in the lab at least monthly. All pancreatic cells were cultured in DMEM medium supplemented with 10% fetal bovine serum and 1% Penicillin-Streptomycin and maintained at 37°C in a humidified 5% CO2 incubator.

Induction of CLSA
CLSA-25 and CLSA-50 cell culture media were prepared by supplementing pyruvate, glutamine, methionine, and cystine-free DMEM media (Gibco, 21013-024) with 1mM Sodium Pyruvate, 4mM glutamine, 200µM L-Methionine, and 25µM L-cystine (for CLSA 25) or with 50µM L-cystine (for CLSA 50). To induce CLSA, PDAC cells were cultured in indicated L-cystine limited media supplemented with 10% FBS and 1% Penicillin-Streptomycin for 4 weeks. The media were changed every other day during this period. After 4 week adaptation, cells were frozen and stored in liquid nitrogen. After recovery from liquid nitrogen cell were cultured in their respective induction media and used for experiments within 6 passages.

Patient derived organoid (PDOs) culture
PDO were derived from 2 patients (both male and 65–75 years old) and cultured following a previously described protocol30. To induce CLSA-I PDO, two PDOs were cultured in medium containing 0.5µM IKE for 4 weeks. For PDO xenografts, CLSA-I or control PDOs were digested into single cells using TrypLE Express and then neutralized with Human Complete Feeding Medium contained Human Wash Medium with BSA (Advanced DMEM/F-12, 10mM HEPES, 1× GlutaMAX Supplement, 100µg/ml Primocin, and 0.1% BSA). 1×105 of PDO cells were resuspended into Matrigel and injected orthotopically into pacreas. The growth of tumors were monored through MRI scan using 9.4T MR scanner (Bruker BioSpec 94/30 USR) at Multimodality Preclinical Molecular Imaging Center in Tianjin Medical University General Hospital. The tumor volume was calculated with the formula: volume = length × width × width/2.

Treatment of PDAC cells and PDOs with modified FOLFIRINOX (mFOLFIRINOX)
mFOLFIRINOX Treatment of PDAC cells and PDO cultures were carried out as previously described. The mFOLFIRINOX cocktail consisted of 5-FU, SN-38 (metabolic product of Irenocan responsible for its inhibitory activity toward DNA topoisomerase I) and oxaliplatin at a 2:1:2 ratios. The indicated mFOLFIRINOX concentrations were the concentrations of 5-FU and oxaliplatin.

Cell proliferation assay
1×105 Cells per well were seeded onto a 12-well plate in triplicate. The media were changed every two days. At indicate time points, the cells were fixed with 10% formalin for 15 min and stained with 0.5mL 10% crystal violet solution for 20 min with shaking. After staining, the cells were washed with water for five times and dried overnight. The crystal violet staining was solubilized with 1ml 10% acetic acid absorbance at OD 590nm was determined with a plate reader.

Cell viability assay
1×104 cells per well were seeded onto 96-well plates (Corning, 3610) and treated with different drugs at indicated concentrations for two to three days. Cell viabilities were tested using CellTiter-Glo Cell Viability Assay (Promega, G7572) and recorded as relative luminescence units using FlexStation 3 (Molecular Devices).

2-NBDG Glucose uptake assay
PDAC cells were seeded at 2×105 cells/well in a 12 well plate. The cells were incubated with 500µL of culture medium containing 50µM 2-NBDG and incubated at 37°C for 2h. The reaction was terminated by washing the cells twice with ice-cold PBS. The cell was re-suspended through trypsinization and analyzed through flow cytometry using the excitation/emission at 467/542nm.

Mitochondria stress test and glycolysis stress test
Oxygen consumption rate (OCR) and extracellular acidification rate (ECAR) were determined using Seahorse XFe24 Extracellular Flux Analyzer (Agilent Seahorse Bioscience) following protocols recommended by the manufacturer. Cells were seeded on XFe24 cell culture microplates (2.5×105 cells/well). Cells were maintained in a XF DMEM assay medium (Agilent, 103575-100) in a non-CO2 incubator for 30 min before the assay. The XF Cell Mito Stress Test Kit (Agilent, 103015-100), was used for the OCR assay. XF Glycolysis Stress Test Kit was used for the ECAR assay (Agilent, 103020-100). For mitochondria stress test, the baseline recording was followed by sequential injection the following reagent to the final concentration: 1.5µM oligomycin, 1µM FCCP, and 0.5µM rotenone/antimycin A. For glycolysis stress test, the baseline recording was followed by sequential injection the following reagents: 10mM D-glucose, 1µM oligomycin, and 50mM 2-DG. At the end of the experiment, the cells in each well were lysed with RIPA buffer and the protein concentrations were determined through BCA assays. The ECAR and OCR data were normalized against total protein amount in each well.

RNA interference and other constructs
The knockdowns of G6PD, DGAT1, and DGAT2 was achieved using the 27mer duplexes DsiRNA system from IDT. The targeting sequences are listed in Table S4. pLX304-G6PD was constructed by subcloning the human G6PD cDNA into pLX304 vector through Gateway subcloning. The lentiviral particles were packaged in HEK293 cells using the PEI transfection method, and concentrated as previously described57. After selection with blasticidine, the surviving cells were pooled together and used for assays. siRNA and shRNA target sequences were included in Table S5.

Tet-inducible knockdown of SLC7A11 and G6PD
For inducible knockdown of SLC7A11 and G6PD, shRNA sequence targeting the two genes (see Table S4) were cloned into the pLVX-H1-TetOne-Puro vector and lentivirus particles were prepared as described in the previous section. After viral particle infection and selection with puromycin, the expression of shRNA were induced by treating cells with 1–100ng/ml doxycycline for 4–7 days (for acute knockdown) or 4 weeks (for chronic knockdown of SLC7A11).

Western blotting
Cells were lysed in SDS-NP40 buffer (50mM Tris, pH 8.0, 150mM NaCl, 1% NP40, 1% SDS, 1mM protease inhibitors cocktail) on ice for 1 min. Cells were scraped from the plate and sonicated briefly three times. Then lysates were centrifuged at 20,000×g, 4°C for 10 min. 20-40µg proteins were separated by SDS-PAGE and transferred onto PVDF membrane. The membranes were incubated in blocking buffer (5% (w/v) nonfat dry milk in Tris-buffered saline, 0.05% Tween 20 (TBS-T)) for 30 min at room temperature and incubated with primary antibodies for 20 h at 4°C, followed by incubation with secondary antibodies for 60 min at room temperature. Antibody information are listed in Supplementary Table S3.

Reverse transcription-polymerase chain reaction
1×106 cells were washed with ice-cold PBS and total RNA was extracted using RNeasy kit (Qiagen, Cat# 74106). 1µg RNA was used for the reverse transcription using High-Capacity cDNA Reverse Transcription Kit (Thermo Fisher Scientific, 4368814). cDNA was diluted 1:10 then used for qPCR with ABI qPCR master mix (Thermo, Cat# 4367659). Each RT-PCR experiment was performed independently at least three times. The PCR primers used are listed in Supplementary Table S6.

L-Azidohomoalanine (AHA) labeling of OxPPP enzymes
7×106 cells on a 10 cm dish were rinsed twice with 5ml 1× PBS and incubated with L-Met free DMEM medium for 1h in 37°C, 5% CO2 incubator. After 1h, L-AHA were added to the final concentration of 1mM. After 1h labeling with AHA, cells were lysed. To label newly-synthesized proteins, lysate was mixed with 2× click-chemistry reaction buffer (2mM Copper Sulfate, 20µM Biotin-Alkyne, 2mM TCEP in 1× PBS) and incubated for 60 min at room temperature with shaking. The reaction was terminated by adding TCA to the final concentration of 10% and incubated on ice for 30 min. After 10,000×g centrifugation at 4°C 10 min, the precipitate was washed with 1ml ice-cold acetone for 3 times, and air-dried at room temperature for 30 min. The pellet was re-dissolved in 500µl RIPA buffer with proteinase inhibitor cocktail and sonicated for 10s on ice 3 times. The biotin-labeled proteins were precipitated with 40µl NeutrAvidin resin and affinity-purified OxPPP enzymes were detected with Western blotting using antibodies for G6PD, PGLS, PGD, and with GAPDH as control.

Polysome profiling
1×107 cells were treated with CHX (100µg/ml) in the cell culture media for 2 min and the cells were placed on ice. After removal of media, the cells were washed twice with ice-cold 1× PBS/CHX (100µg/ml). Cells were scraped in 600µl Polysome Buffer (50mM HEPES, pH 7.4, 250mM KCl, 5mM MgCl2, 250mM sucrose) containing 1% Triton ×-100, 1.3% NaDOC, 100µg/ml CHX, 0.1U/µl SUPERase. In RNAase inhibitor (AM2694, Invitrogen). After 10 min lysis at 4°C with rocking, the lysates were centrifuged at 3000×g for 15 min at 4°C. 600μL supernatant was loaded to a sucrose gradient (20%–47%, w/w) and centrifuged in a Beckman SW41Ti rotor at 34,000 rpm for 160 min at 4°C. After centrifugration, 8 fractions were collected from each. The RNA from each fraction was extracted using TRlzol (15596018, Invitrogen) and used for qPCR analysis.

LC-MS/MS analysis of NEM-cysteine, GSH, dNTP, and NADP+/NADPH
NEM-cysteine. The measurement of NEM-derivatized cysteine in pancreatic cancer cells was carried out following our previously reported protocol30. Human samples were obtained from 11 PDAC patients (age 48–69, 7 male and 4 female). For preparation of human and mouse tissue samples, 10mg PDAC or para-tumor normal tissues were immersed in 10µl NEM Tissue Buffer (25mM N-Ethylmaleimide, 10mM Ammonium Formate, pH 7.0) spiked with 10µM NEM-15N, 13C3-Cysteine as interior control) and homogenized with a glass Dounce tissue homogenizer on ice. The homogenate was centrifuged at 20,000 rpm, 4°C for 5 min and 5μL supernatant were diluted in 45µl NEM Tissue Buffer and used for LC-MS/MS analysis.

GSH. 2×105 cells in 12-well plate (70% confluency) were washed with ice-cold 1× PBS three times and the residual PBS was thoroughly removed. 225µl ice-cold 0.1% formic acid and 25µl [13C2, 15N] GSH (1µg/ml in 0.1% formic acid) was added to the well. The cells were scrapped into a 1.5ml Eppendorf tube. Cells were vortexed for 15s, snap-frozen in liquid nitrogen for 1 min and thawed in a room temperature water bath. After three freeze-thaw cycle, cells were centrifuged at 13,000×g for 3 min and the supernatant were collected for LC-MS/MS analysis.

dNTP. 1×106 cells (in 6-well plate) were washed with ice-cold PBS and residual PBS was removed. 490µl ice-cold 80% MeOH spiked with 10µl 100nM [13C10, 15N5]-dATP (646237, Sigma) internal standard were added and cells were scrapped into a 1.5mL tube. After vortex, the lysates were centrifuged at 21,130×g, 4°C for 10 min. The supernatant was transferred to a new tube and mixed with 1ml 50mM NH4Ac, pH 4.5 and used for subsequent SPE. Oasis WAX 1cc, 30mg, 30µm cartridge (Waters, Milford, MA, USA) was used for SPE. The cartridge was activated with 1ml methanol, and equilibrated with 1ml ddH2O prior to sample loading. After the samples loading by gravity, the cartridge was washed by 1mL 50mM NH4Ac, pH 4.5, and 1mL 0.5% (25% NH4OH) in methanol. The analytes were finally eluted with 1ml buffer containing 80% methanol, 15% water, and 5% (25% NH4OH). The eluent was dried by Speed-vac and reconstituted with 50µl reconstitution solution for LC-MS/MS analysis.

NADP+/NADPH. 1×106 cells in 6-well plate were washed with ice-cold PBS and extracted with 0.4ml 80% MeOH pre-chilled to −20°C. The plates are transferred to −80°C for 15 min and cells were scrapped into a 1.5ml tube. After centrifugation at 15,000×g for 10 min at 4°C, the supernatant was used directly of LC-MS/MS analysis.

LC-MS/MS. All LC-MS/MS analysis were carried out using Sciex QTRAP 6500+ mass spectrometry coupled with a Sciex EXion HPLC separation system. The multiple reaction monitoring mode (MRM) was used to analyze and quantify metabolites. All peaks were integrated and quantified by Sciex OS 3.0 software.

Normalization. For mouse or human tissues, the tissue weight was used for normalization. For cell culture samples, the total protein amounts from three separate replicates were determined through BCA assay and used for normalization.

Lipase activity assay
Lipase activities were determined using Lipase Microplate Assay Kit from Absin (abs580082). Briefly, 5×106 cells were trypsinized and harvested through centrifugation. 1ml Assay buffer was added to the cell pellet. After sonication, the cell lysates were centrifuged at 16,000×g at 4°C for 40 min. The lipase activity in the supernatant was determined through a colorimetric assay according to the manufacturer’s instruction.

Aconitase activity assay
Aconitase activity in cell lysates was measured using the Aconitase Activity Assay Kit (Sigma Aldrich, MAK337) according to the manufacturer’s instructions. Cytosolic aconitase (ACO1) and mitochondrial aconitase (ACO2) activities were determined by monitoring the conversion of citrate to isocitrate at 565nm. Protein-normalized enzymatic activity was expressed as µM/min per milligram of protein.

C11 BODIPY Lipid peroxidation assay
Cell were treated as indicated and incubated with 2mM C11-BODIPY 581/591 (Beyotime, S0043M) for 1h. Excess C11-BODIPY was removed by washing the cells twice with PBS. Lipid peroxidation was immediately detected by an automatic microplate spectrophotometer (Synergy H1, BioTek Instruments, Vermont, USA). The signals from both non-oxidized C11 (excitation 581nm/emission 591nm) and oxidized C11 (excitation 488nm/emission 510nm) were determined.

FITC-cystine uptake assay
FITC-cystine uptake was performed as previously described30. 3×105 cells were plated onto 6 well plate for overnight. The cells were incubated with fresh medium containing 5µM FITC-cystine (SCT047, Sigma). After 30 min incubation in a 37°C CO2 incubator, the cells were trypsinized and washed with ice-cold PBS (with 1% FBS) twice and used for flow cytometry analysis.

EdU staining
Cells (2×105/well) were seeded in 6-well plates and cultured overnight to allow attachment and recovery of normal growth status. Subsequently, EDU labeling, fixation, and permeabilization were performed according to the manufacturer’s protocol (APExBIO, Cat# K1175). Flow cytometry data were acquired using a Beckman Coulter flow cytometer with an excitation wavelength of 488nm, and analyzed with FlowJo software (v10.0).

Cell proliferation assay
1×105 Cells per well were seeded onto a 12-well plate in triplicate. The cell culture medium was refreshed every two days. At indicate time points, the cells were fixed with 10% formalin for 15 min and stained with 0.5ml 10% crystal violet solution for 20 min with shaking. After staining, the cells were washed with ddH2O for five times and dried overnight. The crystal violet staining was solubilized with 1ml 10% acetic acid absorbance at OD 590nm was determined with a plate reader.

Colony formation assay
3×103 cells were suspended in 3mL indicated culture and seeded into 6 well plate. The medium was replaced every three days. After 10–14 days, the colonies were visualized through Crystal Violet staining.

High throughput drug screening
Cells were seeded onto 96-well plates at an optimal density in their respective medium incubated at 37°C in a 5% CO2 environment for 16h. Following incubation, compounds from a metabolic disease focus library (L5200, TOPSCIENCE) were added to the cells at a final concentration of 5μM (with DMSO serving as the vehicle control). After incubation with the compounds for 48h, cell viability was measured using the CCK-8 assay. Compounds that significantly inhibited cell viability (more than 70% inhibition) in MiaPaCa-2-CLSA cells were identified as potential hits.

Patients tissue specimens
For NEM-cysteine experiment, de-identified tissues were obtained from 11 patients (age 48–69 years old, 7 male and 4 female). For lipid droplet and PLIN2 staining, tissues were obtained from 30 PDAC patients (age 45–72, 19 male and 11 female). For PDO cultures, tissues were obtained from 2 male PDAC patients (65–75 years old). For PDX experiments, tissues were derived from 2 patients (1 male and 1 female, age 55–75 years old). For G6PD IHC staining, tumor samples and para-tumor normal tissues were obtained from 100 patients (age 29–81, 57 male, 43 female) with PDAC treated at the Tianjin Cancer Hospital from 2014 to 2018. All patients underwent radical pancreaticoduodenectomy with R0 margins confirmed by two pathologists. None of the patients had received chemotherapy or radiotherapy at the time of sample collection. All patients were treated with systemic gemcitabine-based chemotherapy after operation for six cycles after surgery. No radiotherapy was given before or after surgery. Postoperative follow-up of patients were conducted every 3 months initially. OS was defined as the time interval from the date of surgery to that of death due to any cause or that of the last follow-up. RFS was calculated from the date of surgery to that of local recurrence or metastasis. Local recurrence or metastasis was diagnosed by radiological examination (contrast-enhanced CT or MRI scanning). All patients provided written informed consent. The study protocols were approved by the Ethics Committee of the Tianjin Cancer Institute and Hospital.

Animal husbandry
All experimental mice were housed in a specific pathogen-free (SPF) environment. The ambient temperature was 21–23°C, with 45% humidity and the mice had ad libitum access to water and food. The feed used was produced by Sibeifu Company (product code: SPF-F02-003). Light cycles in the mouse rooms were 12 light/12 dark.

Orthotopic xenograft and bioluminescence imaging (BLI)
The orthotopic PDAC xenograft and BLI imaging were carried out following previously reported procedures30,58,59 according to IACUC protocols approved by the IACUC committee at the Tianjin Cancer Hospital. Briefly, Luciferase-labeled PDAC cells (1×105 for KPC and Pan02 cells, 1×106 for MiaPaCa-2 cells) were resuspended in 20µl Matrigel (diluted in DMEM media) and orthotopically injected into carefully exposed pancrease of 6–7 weeks old female mice (C57BL/6J for KPC and Pan02 cells, BALB/c Nude mice for MiaPaCa-2 cells). The wound was closed with suture and wound clip. Non-invasive BLI imaging was carried out using Xenogen IVIS 200 1 week after the surgery to monitored the orthotopic tumor growth. At the end of the experiment, liver were inspected for visible metastatic lessions and ex vivo BLI imaging was carried out to monitor liver metastasis.

PDX model experiments
The experimental protocol was approved by the Ethics Committee of Tianjin Medical University Cancer Institute and Hospital, following the NIH Guide for the Care and Use of Laboratory Animals. Pathogen-free NSG mice (6–7 weeks old, female) were used for the primary tumor xenograft (PDX) model. Tumor specimens were collected from pancreatic cancer patients who underwent surgical resection, and the tissues were transplanted into 8-week-old NSG mice under a sterile environment. After three successful passages, the PDX tumor was excised and cut into 2mm fragments and inoculated into NSG mice. Once the transplanted tumors reached 3mm, mice were randomly assigned into 4 groups (6 mice per group) to receive different treatments. The treatment groups included: (A) vehicle control (saline), (B) mFOLFIRINOX (Oxaliplatin: 10mg/kg, intravenous injection once weekly; 5-FU: 10mg/kg, intraperitoneal injection once weekly; Irinotecan: 5mg/kg, intraperitoneal injection once weekly), as previously described60, (C) Lomitapide treatment at 10mg/kg via daily oral gavage, and (D) combination therapy with mFOLFIRINOX plus Lomitapide. Tumor size was measured weekly using calipers, and the tumor volume was calculated with the formula: volume = length × width × width/2. At the end of the experiment, tumors were harvested from the mice for further processing and analysis.

For PET-CT scan, mice were fasted for 6h prior to the experiment but had free access to water. Before the injection of the imaging agent, the mice were weighed, and 18F-FDG was administered via the tail vein at a dosage of 5µCi/g, with the injection time recorded. One hour after the tail vein injection of the 18F-FDG tracer, a micro-PET/CT scan was performed. The mice were anesthetized using isoflurane gas and positioned prone on the small animal PET/CT bed, with infrared beams used to center the scanning field. Static imaging was then conducted, starting with the PET scan followed by the CT scan, for a total duration of approximately 10 min. The CT and PET images were transmitted to the IRIS workstation for image reconstruction and fusion. The equipment we used is the French Inviscan small animal imaging system, IRIS PET/CT, and the 18F-FDG radioactive tracer was provided by the Molecular Imaging and Nuclear Medicine Department of Tianjin Cancer Hospital.

KPC mouse model
KPC mice (C57BL/6Smoc-Krasem4(LSL-G12D); Trp53em4(R172H); Pdx1-cre mice, 8 weeks old, male) were purchased from Shanghai Model Organisms Center. The development of pancreatic cancer in these mice were monitored by ultrasound scans (Canon Aplio i800, Japan). Mice with tumor volumes of 20–60mm³ were randomly assigned into four groups: (A) vehicle control (saline), (B) mFOLFIRINOX, (C) Lomitapide, and (D) combination therapy with mFOLFIRINOX plus Lomitapide and treated as described above. The treatments continued for 4 weeks, during which the tumor volume was monitored biweekly via ultrasound scans. The survival of mice continued to be monitored after stopping the treatment.

IHC analysis
Sections of formalin-fixed, paraffin-embedded tumors were subjected to IHC analysis for G6PD and PGD as using a DAB (3,3′-diaminobenzidine) substrate kit (Maixin) according to the manufacturer’s instructions. Sections were incubated with anti-G6PD (sc-373886, Santa Cruz Biotechnology, at 1:200 dilution) or anti-PGD (sc-398977, Santa Cruz Biotechnology, at 1:200 dilution), anti-ATF4 (10835-1-AP, Proteintech, at 1:200 dilution) or anti-PLIN2 (Abcam, ab52356, at 1:100 dilution) antibodies overnight at 4°C. After wash, the sections were stained with a secondary antibody for 30 min at room temperature. PBS was substituted for each primary antibody as a negative control. Five random fields were examined under a light microscope. Immunoreactivity was scored according to the estimated percentage of positive tumor cells as described previously. IHC staining results were blindly and independently performed by two pathologists who were blinded to the clinical data. Staining intensity was scored 0 (negative), 1 (low), 2 (medium), and 3 (high). The H-score was calculated according to the formula: H-score = (0× percentage of 1+ cells) + (1× percentage of 1+ cells) + (2× percentage of 2+ cells) + (3× percentage of 3+ cells), yielding a total score ranging from 0 to 300. Expression levels were classified based on the H-score as follows: 0 (negative, −), 1–100 (weak expression, +), 101–200 (moderate expression, ++), and 201–300 (strong expression, +++). Antibodies used in IHC staining can be found in Supplementary Table S2.

Lipid droplets staining
For the staining of LD in tissues, we subjected fresh cancer/cancer-adjacent tissues from patients or mouse tumor fragments to rapid freezing, followed by embedding in OCT compound and sectioning. These sections were stored at −20°C. Prior to staining, the sections were gradually thawed at 4°C for 20 min, then permeabilized with ice-cold acetone for 20 min. Afterward, sections were blocked with 3% BSA for 30 min. Subsequently, BODIPY™ 493/503 NHS ester (succinimidyl ester) dye was added at a final concentration of 5μM for the staining of adiposomes. The sections were incubated at room temperature for 60 min, washed three times with PBS, and counterstained with DAPI. For quantitation, The average LD numbers per cell from 5 random fields (20x objective) were counted.

For lipid droplet staining in cells, 3×105 cells were seeded onto a 3.5cm glass bottom cell culture dish (50% confluency). The glass bottom was coated with 0.2% gelatin as previously described61. Cells were stained with 1.5μl LipidSpotTM-488 dye diluted in 1ml cell culture medium in a 37°C CO2 incubator for 30 min. After staining, the cells were washed with 1× PBS and fixed with 4% paraformaldehyde for 10 min, washed with 1× PBS twice and counterstained with DAPI. The LD were imaged with Leica SP8 laser scanning confocal microscope equipped with an 63× oil immersion objective.

Thin layer chromatography (TLC)
5×106 cells in a 10 cm dish were washed with 1× PBS twice and harvested with a cell scrapper. The cell pellets were wash with 1× PBS twice and the lipids were extracted with 750μL methanol:choloroform (4:1, v/v). After centrifugation at 13,300 rpm for 5 min at room temperature, the supernatant was mixed with 600µl 0.1% aqueous acetic acid and 300µl chloroform and vortexed for 10s. The mixture was centrifuged at 13,300 rpm for 5 min and the lower organic phase was transferred to a glass vessel and dried under nitrogen. The dried lipids were reconstituted in chloroform and loaded onto Silica gel 60 TLC plate (1.11845.0001, Merck). The TLC plates were developed using hexane/diethyl ether/acetic acid 60:40:1 (v/v/v). The lipids were visualized using iodine vapor and imaged with a scanner.

Oleate-Alkyne tracing
8×106 MiaPaCa-2 cells were pretreated with 2µM lomitapide or vehicle (DMSO) in regular growth media (DMEM plus 10% FBS) for 2h. After 2-h pretreatment, cells were incubated with growth media supplemented with 10µM with vehicle control or 2µM lomitapide, respectively, for 6h. The cells were then washed with ice-cold PBS and harvested using a cell scraper. 1/10 of the cells were used for protein assay (BCA method) and normalization. The remaining cells were lysed with 1ml 50% MeOH, 0.05M HCl and vortexed for 10s. 0.5ml chloroform was added and vortexed vigorously to extract lipids. After 16,000×g centrifugation for 5 min at 4°C, the lower organic phase was added to a glass vial. The upper aqueous phase was extracted with 0.5ml chloroform again and the two organic phase extractions were combined and used for SPE separation using STRATA NH2 column (500mg, 55µm, 70A, 8B-S009-HBJ, Phenomenex) following a previously reported protocol43,69. The column was preactivated with 4ml hexane, followed by 4ml chloroform/isopropanol (2:1 v/v) and then 4ml hexane again. The MiaPaCa-2 lipid extracts were loaded. Neutral lipids, FFA, and polar lipids were eluted using 4ml chloroform/isopropanol (2:1 v/v), 8ml diethyl ether/acetic acid (100:2, v/v), and 4ml methanol, respectively. After elution, the lipids were dried under nitrogen flow, saponified and used for LC-HRMS analysis (see 13C5, 15N2-glutamine tracing for de novo fatty acid synthesis).

DGAT activity assay
DGAT activity assay was performed using 1,2 dioleoyl-sn-glycerol (DOG, D0138, Sigma) and NBD-palmitoyl CoA (810705P, Avanti Polar Lipids) as substrate and crud miccrosomal membrane isolated from mouse liver following a previously reported protocol46. 5µg liver membrane (in 50µl buffer containing 50mM Tris-HCl, pH 7.6, 250mM sucrose) was incubated with 150µl reaction master mix (20µl 1M Tris-HCL, pH 7.6, 1µl 1M MgCl2, 10µl 4mM DOG, 10µl 12.5mg/ml FFA-free BSA, 10µl 500µM NBD-palmitoyl CoA and 99µl ddH2O) with or without lomitapide, mixed by vortexing and incubated at 37°C for 10 min with shaking. The reaction was terminated by the addition of 750µl methano/chloroform 4:1 v/v followed by vortexing. After 17,000×g centrifugation at room temperature for 5 min, the 400µl lower organic phase was transferred to a glass tube, dried with SpeedVac. After reconstituion in chloroform, the NBD-labeled lipids were resolved through TLC as previously described.

Metabolomics and lipidomics screening
Metabolomics screening was performed through LC-MS/MS as previously described63,64. The MSEA analysis was performed using Metaboanalyst 5.0. Untargeted lipidomics screening was performed with assistance from Dr. John Asara (BIDMC Mass Spectrometry Core) following previously their published protocols65. Briefly, 7×106 cells were washed with PBS and harvested with a cell scraper in a 12 ml glass tube. After centrifugation (1000×g, 5 min at room temperature), the cells were resuspended in 200µl PBS. 10% cells were saved for protein assay and normalization. The remaining cells were extracted with 4ml chloroform:methanol (2:1, v/v). After 30 min incubation on a orbital shaker at room temperature, 400µl ddH2O was added and the samples were vortexed for 1 min. The samples were allowed to stand for 10 min and centrifuged at 2200×g for 15 min. The lower phase was collected and dried under a nitrogen stream and used for untarged metabolomics screening using a relative quantitative positive/negative ion switching method as previously described65.

Targeted quantitative lipidomics assay was performed with assistance from Metware Bio (Woburn, MA). For lomitapide treatment, CLSA-25 MiaPaCa-2 cells were treated with 1µM lomitapide for 24h. For mFOLFIRINOX treatment, 1×107 naïve MiaPaCa-2 cells were treated with mFOLFIRINOX cocktail consists of 5-FU (8µM), Oxaliplatin (8µM), and SN-38 (4µM) for 24h. For PANC-1 targeted lipidomics, 1×107 CLSA-25 or naïve control cells were used. Cells were harvested using a cell scrapper. The cell pellets were resuspended in 100µl ddH2O containing proteinase inhibitors. 50µl cell suspensions were used for lipid extraction, while the remaining samples were used for protein assay and the total protein amounts in each sample was used for normalization. The data acquisition instruments consisted of Ultra Performance Liquid Chromatography (Nexera LC-40, Shimadzu) equipped with Thermo Accucore™ C30 (2.6μm, 2.1mm × 100mm i.d.) column and tandem mass spectrometry (MS/MS) (Triple Quad 6500+, AB/SCIEX). Liquid phase conditions: Mobile phase: A phase was acetonitrile /water (60/40, V/V) (0.1% formic acid added, 10mmol/L ammonium formate); B phase was acetonitrile /Isopropyl alcohol (10/90, V/V) (0.1% formic acid added, 10mmol/L ammonium formate); Gradient program: 80:20 (V/V) at 0 min, 70:30 (V/V) at 2 min, 40:60 (V/V) at 4 min, 15:85 (V/V) at 9 min, 10:90 (V/V) at 14 min, 5:95 (V/V) at 15.5 min, 5:95 (V/V) at 17.3 min, 80:20 (V/V) at 17.5 min, 80:20 (V/V) at 20 min; Flow rate: 0.35ml/min; Column temperature: 45°C; Injection volume: 2μL. Mass spectrometry conditions: LIT and triple quadrupole (QQQ) scans were acquired on a triple quadrupole-linear ion trap mass spectrometer (QTRAP), QTRAP® 6500+ LC-MS/MS System, equipped with an ESI Turbo Ion-Spray interface, operating in positive and negative ion mode and controlled by Analyst 1.6.3 software (Sciex). The ESI source operation parameters were as following: ion source, turbospray; source temperature 500°C; ion spray voltage (IS) 5500 V (Positive), −4500 V (Negative); Ion source gas 1 (GS1), gas 2 (GS2), curtain gas (CUR) were set at 45, 55, and 35 psi, respectively. Instrument tuning and mass calibration were performed with 10 and 100 μmol/L polypropylene glycol solutions in QQQ and LIT modes, respectively. QQQ scans were acquired as MRM experiments with collision gas (nitrogen) set to 5 psi. DP and CE for individual MRM transitions was done with further DP and CE optimization. A specific set of MRM transitions were monitored for each period according to the lipids eluted within this period.

13C6, 15N2-cystine tracing
Cystine isotopologue tracing was performed following a previously described protocol66 with modifications. Cystine, methionine, and glutamine free DMEM media (Gibco, 21013-024) were supplemented with 400µM (for control group) or 50µM (for CLSA-25 group) 13C6, 15N2-cysteine, 100µM methionine, 4mM glutamine and 10% dialyzed FBS and stored at 4°C for 48h for the oxidation of cysteine to cystine. 7×106 control or CLSA-25 MiaPaCa-2 cells were pre-conditioned in the same medium containing 12C, 14N-cystine for 12h. After pre-conditioning, cells were labeled with their respective media containing isotopologue cystine for indicated time (2, 4, or 24h). The metabolites were extracted with 2ml 80% MeOH. After centrifugation, the supernatant was dried under nitrogen flow and analyzed through LC-MS/MS as previously described67.

13C6-glucose tracing to glycolysis and PPP/nucleotide metabolites
13C6-glucose tracing was performed as we described previously with modifications63,68. 7×106 control or CLSA-25 MiaPaCa-2 cells were incubated with DMEM medium (Life Technology, D98002710) containing 200µM (for control group) or 25µM cystine (for CLSA-25 group), 10mM 13C6-glucose, and 10% dialyzed FBS for indicated time (from 0 to 360min). After extraction with 80% methanol and centrifugation, the supernatant was collected and dried using SpeedVac and re-dissolved in 50μL of methanol/water (50/50) for LC-MS/MS analysis as previously described68.

13C5, 15N2-glutamine tracing for de novo fatty acid synthesis
1×106 PANC-1 cells on a 6 cm dish was washed with PBS and incubated with isotopic labeling media containing 4mM 13C5, 15N2-glutamine containing 200µM (for control cells) or 25µM (for CLSA-25 cells) L-Cys2 and dialyzed FBS. After 24-h incubation, cells were washed with 1× PBS twice and scrapped into a 1.5ml tube on ice. The cells were centrifuged at 500×g at 4°C for 3 min and the cell pellets were vortexed in 1ml 50% methanol with 0.05M HCl for 10s. 500µl choloroform was added to each tube and vortexed vigorously to extract lipids. After 16,000×g centrifugation for 5 min, the lower organic phase was transferred into a glass vial. The upper aqueous phase was extracted with choloroform again and the organic phase was combined and dried under nitrogen flow. The dried lipids were reconstituted in 90% methanol solution containing 0.3M KOH and incubated in a 2ml glass vial at 80°C for 1h. After saponification, the 100µl formic acid was added to the reaction and the mixture was extracted with 900µl hexane twice. The hexane extracts were combined and dried under nitrogen flow. After reconstitution in 50µl methanol/chloroform 4:1 v/v, the saponified fatty acids were used for mass spectrometry analysis. The LC/MS system consisted of a Dionex Ultimate 3000 XRS pump (Thermo Scientific, San Jose, CA), a Dionex Ultimate 3000 XRS open autosampler (Thermo Scientific, San Jose, CA), a Dionex Ultimate 3000 RS column compartment (Thermo Scientific, San Jose, CA), and an Exactive Plus orbitrap mass spectrometer (Thermo Fisher Scientific, San Jose, CA). Data was collected using Xcalibur 3.0.63 software (Thermo Scientific, San Jose, CA) and analyzed using FreeStyle 1.8.63.0 software (Thermo Scientific, San Jose, CA). A binary gradient of solvent A: 97/3 water/methanol with 10mM tributylamine and 15mM acetic acid (pH 4.5) and solvent B: 100% methanol was as follows: 80 to 99% B from 0 to 20 min, remaining at 99% B from 20 to 40 min, from 99% B to 80% B to 41 min, and remaining steady at 80% B to 50 min. The separation was performed on a Luna C8(2) reversed-phase column (150×2.0mm, 3μm particle size, 100Å pore size, Phenomenex, Torrance, CA). The flow rate was 200μL/min, the autosampler temperature was 5°C, injection volume 10μL, and column temperature 25°C. The mass spectrometer was operated in negative mode. The electrospray settings were set as follows sheath gas flow rate 45 (arbitrary units), auxiliary gas flow rate 10 (arbitrary units), sweep gas flow rate 2 (arbitrary units), spray voltage 2.5 kV, capillary temperature 250°C, S-lens RF level 50, and auxiliary gas temperature 400°C. The mass spectrometer resolution was set to 140,000 and the automatic gain control was set to 3×106 with a maximum injection time of 100ms. The scan range was 200–400 m/z from 0 to 20 min and 300 to 575 m/z from 20 to 50 min.

[1-13C]-L-Serine tracing to transsulfuration
L-Cystine and L-Serine Free DMEM high glucose Media was supplemented with 400µM [1-13C]-L-Serine, and 400µM (for control cells) or 50µM (for CLSA-25 cells) L-Cysteine and 10% FBS. [1-13C]-L-Serine and L-Cysteine were added to the Media 48h before test. Cell were pre-conditioned in medium containing 10% FBS and 12C-serine for 12h in 10 cm dish (7×106 cells per dish). Cells were washed twice with 1× PBS and incubated with their respective media containing 400µM [1-13C]-L-Serine for 4h. The cells were then washed with ice-cold PBS for three times and lysed in 2ml 80% MeOH in −80°C freezer for 15 min. The cells were harvested through scraping. After 17,000×g centrifugation at 4°C for 20 min, the supernatant was transferred to a new tube and dried with nitrogen flow and used for LC-MS/MS analysis.

[U-13C]-OA tracing
8×106 MiaPaCa-2 cells were pretreated with 2µM lomitapide or vehicle (DMSO) in regular growth media (DMEM plus 10% FBS) for 2h. After 2-h pretreatment, cells were incubated with growth media supplemented with 10µM with vehicle control or 2µM lomitapide, respectively, for 6h. The cells were then washed with ice-cold PBS and harvested using a cell scraper. 1/10 of the cells were used for protein assay (BCA method) and normalization. The remaining cells were lysed with 1ml 50% MeOH, 0.05M HCl and vortexed for 10s. 0.5ml chloroform was added and vortexed vigorously to extract lipids. After 16,000×g centrifugation for 5 min at 4°C, the lower organic phase was added to a glass vial. The upper aqueous phase was extracted with 0.5ml chloroform again and the two organic phase extractions were combined and used for SPE separation using STRATA NH2 column (500mg, 55µm, 70A, 8B-S009-HBJ, Phenomenex) following a previously reported protocol43,69. The column was preactivated with 4ml hexane, followed by 4ml chloroform/isopropanol (2:1 v/v) and then 4ml hexane again. The MiaPaCa-2 lipid extracts were loaded. Neutral lipids, FFA, and polar lipids were eluted using 4ml chloroform/isopropanol (2:1 v/v), 8ml diethyl ether/acetic acid (100:2, v/v), and 4ml methanol, respectively. After elution, the lipids were dried under nitrogen flow, saponified and used for LC-HRMS analysis (see 13C5, 15N2-glutamine tracing for de novo fatty acid synthesis).

Matrix-assisted laser desorption/ionization (MALDI)-mass spectrometry imaging (MSI) of cysteine and cystine in mouse pancreas
Mouse pancreas samples (approximately 3×3mm) were harvested from 8-weeks old KFC mice (KrasLSL-G12D; Trp53fl/fl; Pdx1-Cre) and immersed immediately in isopentane placed on top of dry ice. The frozen samples were cryosectioned at a thickness of 7μm using a Leica CM1950 cryostat. Tissue sections were mounted onto indium tin oxide (ITO)-coated glass slides for MALDI-MSI and onto standard glass slides for histological analysis. A MALDI matrix solution consisting of 1,5-diaminonaphthalene (5.6mg/mL in 5% HCl and 50% ethanol) was applied to the ITO-mounted sections using the HTX M3+ automated sprayer under the following conditions: flow rate of 20μL/min, 25 passes, 10 psi liquid nitrogen sheath gas, and a spraying velocity of 1200mm/min. MALDI-MSI was conducted using a Thermo Q Exactive HF-X Orbitrap mass spectrometer integrated with a UV-laser MALDI source (Spectroglyph LLC)70. Data acquisition was performed in negative ion mode across an m/z range of 100–1000 with a spatial resolution of 20μm. Adjacent serial sections of the mouse pancreas were fixed in 4% formaldehyde post-sectioning and stained with hematoxylin and eosin (H&E) stain, processed in University of Texas Health Science Center at San Antonio (UTHSA). Autofluorescence (AF) images of pre-MSI sections and brightfield images of H&E-stained sections were acquired using a Zeiss Axioscan 7 digital slide scanner equipped with a 20× objective lens. Please refer to the protocols.io for detailed procedures at Zhang et al.71.

Cysteine and cystine annotations from MSI were executed using METASPACE, a software with false discovery rate control72. To confirm molecular identity, tandem mass spectrometry (MALDI-MS/MS) was performed on frozen mouse pancreas sections targeting the cysteine and cystine precursor ion. The resulting fragment ion m/z values were verified by Human Metabolome Database spectral library73. The spatial distribution of cysteine and cystine in frozen mouse pancreas sections was analyzed using Bruker SCiLS Lab software. MALDI-MSI datasets for each sample were imported into SCiLS, and corresponding pre-MSI AF images were registered to the total ion current (TIC) image using a two-point alignment method. H&E-stained images from adjacent serial sections were subsequently overlaid onto the AF images. Regions of interest (ROI, Normal, PanIN & ADM, Tumor, and Lymphocytes) from mouse pancreas were defined based on H&E-stained images by a pancreatic cancer pathologist. Ion intensity data corresponding to cysteine (m/z 120.0125) and cystine (m/z 239.0166) were extracted for each pixel within the ROI following TIC normalization. Mean ion intensity values for cysteine and cystine were calculated by averaging pixel-level intensities within the ROI.

Drug treatments synergy analysis
The Zero Interaction Potency (ZIP) score analysis was performed using SynergyFinder74 to determine the synergistic effects between Lomitapide and mFOLFIRINOX treatments. ZIP score > 10 indicates synergistic effects between the two treatments.

Material availability
All unique/stable reagents generated in this study are available from the lead contact with a completed materials transfer agreement.

Statistics and reproducibility
Statistical data analysis was performed using Graphpad Prism 10. The continuous outcome variables were compared using two-tailed two-sample t-test (paired or unpaired). For non-continuous variables, Mann–Whitney U test was used. For multiple comparisons, one-way ANOVA with Dunnett’s or Sidak’s multiple comparison test were used. For tumor growth curves and cell proliferation curves, two-way ANOVA with Tukey’s multiple comparison test were used. Categorical variables were analyzed using Fisher’s exact test of Chi square test. Survival analysis was performed using Kaplan–Meier’s method. No statistical method was used to predetermine sample size. No data were excluded from the analyses. For cell-based experiments, western blotting, immunostaining, and FACS, data collection was conducted blindly. Measurement for cell viability, FACS, photo capture, and histological analysis were performed by different individuals who were blinded to the experimental groups. Mass spectrometry analysis was blinded prior to analysis.

Ethical considerations
All animal experiments were performed with approval from the Animal Ethical and Welfare Committee (AEWC) at the Tianjin Medical University Cancer Institute and Hospital (Approval No.: 2023086). The following humane endpoints were used for mouse euthanasia: a single tumor volume of ≥2000mm³; persistent tumor surface ulceration and infection that showed no improvement after local care (e.g., sterile disinfection); deterioration of the mice’s general condition, such as a body weight loss of ≥20% within one week accompanied by emaciation, rough and unkempt fur, and loss of skin elasticity; refusal to eat or drink for 24 consecutive hours with signs of dehydration (e.g., sunken eye sockets, dry nasal mucosa, and cold limbs); and abnormal movement and behavior, including persistent huddling and inactivity, unresponsiveness to stimuli, or the presence of ataxia (unsteady gait, stumbling) and paralysis.

The research using de-identified human samples (organoids, PDXs, and patient tissue specimens) complies with all relevant ethical regulations. In accordance with the requirements of the Ethics Committee of Tianjin Medical University Cancer Institute and Hospital, China, and the recognized ethical guidelines of the Declaration of Helsinki, all patients provided written informed consent for the use of their specimens and disease-related information in future research (Approval No.: EK20220153). The patients are not compensated.

Peer review rounds
[{"round": 1, "reviewer_comments": {"reviewer_1": "This manuscript by Li Y, Li Z et al., titled \"Adaptation to Cystine Limitation Stress Confers a Targetable Lipid Metabolism Vulnerability in Pancreatic Ductal Adenocarcinoma (PDAC),\" explores the connection between cysteine limitation adaptation and lipid reprogramming in PDAC.\nWhile many individual aspects such as cyst(e)ine depletion, ferroptosis, oxPPP, and lipid reprogramming are already recognized features of PDAC and might initially seem to lack novelty, the innovative aspect of this study lies in its integration of these elements and the proposal of a new drug combination (LOMITAPIDE) with mFOLFIRINOX chemotherapy. The authors also used a multifaceted approach in multiple PDAC models.\nTherefore, I consider this study to be of significant relevance to the scientific community and the readership of Nature Communications. However, several major and minor concerns, listed below, need to be addressed before it can be considered for publication.\nMajor Concerns\n1. The starting point of CLSA seems mainly to be attributed to adaptation to a decreased uptake of cystine, as pointed out with the use of IKE and by comparison with the para-tumor content of cyst(e)ine. However, it’s unclear whether in this context there is an impaired SLC7A11 gene expression over time or rather due to usage of cysteine by other pathways beyond GSH. The authors should confirm the most salient results of the manuscript using inducible loss- and gain-of-function of SLC7A11. Is there a loss of SLC7A11 in PDAC patients that can account for a worse prognosis or resistance to chemotherapy? Or is there a role of the pancreas microenvironment in the sequestration of cyst(e)ine?\n2. Even though mass spectrometry was performed in tumors and para-tumor samples, Figure 1 is missing the Cys2 quantification and the ratio. It would be more relevant and convincing to show Cys and Cys2 spatial distribution in tumor and non-tumor areas via MALDI-MS imaging with a corresponding H&E staining.\n3. It would be beneficial to have images of CLSA occurring over time in Figure 1C and Supplementary Figure 1, not just at the endpoint. Is CLSA reversible or a permanent event?\n4. C11-BODIPY should be expressed as ratiometric values (Green/Red) and not as %high. Please revise Supplementary Figure 1 accordingly. Additionally, these methods and others are missing in the methods section.\n5. As cyst(e)ine and GPX4 operate on the same axis of ferroptosis regulation, it is not surprising that CLSA PDAC cells become co-resistant to the inhibition of both. What about other pathways regulating ferroptosis? It’s known that cancer cells resistant to the cyst(e)ine/GPX4 pathway can be vulnerable to inhibition of other independent pathways such as FSP1i and DHFR, which are also tightly connected with oxPPP and nucleotide metabolism/synthesis. The authors should show whether these contribute to the phenotype of CLSA in PDAC.\n6. From PDAC orthotopic model experiments, CLSA PDAC cells seem to maintain the more aggressive phenotype shown in vitro. This again suggests a cell-autonomous and permanent adaptation of the PDAC cells even when there is plenty of cyst(e)ine in the pancreas microenvironment. This point is connected to comment number 1 and needs to be dissected with orthogonal loss- and gain-of-function approaches.\n7. Supplementary Figure 1: Can cyst(e)ine and Trp deprivation be rescued by BSA? The text says 2-4 weeks, the legend says 2 weeks, and panel J says days instead of weeks—what is the timepoint? The authors should consolidate the results and explain why certain results are missing or are not consistent.\n8. In Figure 2A, the authors find a decrease in the M+4 cysteine derived from labeled cystine; however, the M+0 fraction of cysteine and all other metabolites in Supplementary Figure 2C is increased. The authors suggested briefly that this could be due to additional sources of cysteine, but none of these possibilities were tested or shown. This is particularly relevant as some PDAC cell lines used in this study have a baseline good expression of the transsulfuration pathway genes. Even though PDAC and other cancers seem to rely mainly on cyst(e)ine uptake, the upregulation of the transsulfuration pathway can contribute to the CLSA phenotype. This hypothesis is also corroborated by the ATF4 upregulation (a regulator of the CSE gene) and by the absolute absence of labeling of HTAU and TAU. Authors need to show a C13-serine tracing in vitro and in vivo, with and without CLSA. Also, protein levels of the main components of the de novo synthesis and uptake of cyst(e)ine should be shown in all conditions. Refer to PMID: 36862034 for guidelines regarding this point.\n9. The authors state that CLSA cells have a decrease in the labeled alanine coming from cysteine as a byproduct of the Fe-S cluster pathway. This is linked to a decreased activity of both ACO1 and ACO2 activity (these methods are missing), as well as to Fe-S formation and impaired mitochondrial respiration. Two points require attention: What’s the impact on the mitochondrial mass? And what’s the role of iron metabolism in this phenotype? Key components of the Fe-S pathways such as ISCU and CISD1 are not taken into consideration. It is also unclear why the authors chose H3 as a housekeeping control in Figure 2D.\n10. MSEA analysis in Figure 3A should show the significant sets that are up and down in CLSA conditions. Also, a heatmap or volcano plot for all the significant metabolites at steady-state should be reported at least in the Supplementary section.\n11. G6PD mRNA levels need to be assessed in multiple cell lines. Also, it’s unclear whether the CHX assay was run in CLSA or control cells. siRNA-mediated knockdown of G6PD should be confirmed with inducible shRNA.\n12. The authors state that “G6PD overexpression increases ferroptosis resistance.” However, they are just targeting the xCT/GPX4 pathway, which is only one of the pathways. This comment relates to comment #5: The authors need to check other ferroptosis pathways. Also, they should explain why G6PDi or KD induce only a partial rescue of the CLSA-induced phenotype (this is valid also for results in Figure 5J, K).\n13. Lipidome analysis in Figure 5 should include a more thorough analysis, including double bonds and carbon length analysis for all the relevant classes. Also, PC, PE, and PS significantly change in CLSA, but they are not taken into consideration. As these lipids can be both synthesized and stored in LD, they can play a role in the phenotype that is neglected now. Also, they should use an LD-enriched fraction and perform lipidomics on that to prove the relevant differentially regulated lipids are confined there. The same criticism is valid for lipidomics in Figures 6 and 7.\n14. Whenever LDs are accumulating, this could indicate also a decreased lipolysis, which is not taken into consideration. Specific lipase activities should be measured in all conditions to consider the effect of lipolysis in the CLSA phenotype. Lipase inhibitors should also be used to test this hypothesis. The same is valid for the in vivo experiments in Figures 6 and 7.\n15. Panel L in Figure 5 needs a corresponding H&E to evaluate the result. It would be more informative to see tumor and para-tumor areas together on the same slide.\n16. The 800-drug screen focused on metabolism is nice. However, the lack of a full table and the raw data renders the evaluation of these results difficult. In other words, the authors really need to prove in the most unbiased way that Lomitapide is the best candidate drug to be used. Also, the plausible target of Lomitapide, MTTP, seems to be missing in PDAC cells—which cells are we looking at in Supplementary Figure 6B? Control or CLSA? Also, by implying that Lomitapide targets DGAT, the authors point to potential off-target effects of the drug. There are several other lipid synthesis inhibitors (e.g., FASN, SCD inhibitors) that are available and FDA-approved, which produce a phenotype like Lomitapide but are proven to be very on-target and less promiscuous than Lomitapide. The authors should consider using other inhibitors of the same pathways to corroborate their conclusions.\n17. Lipidomics of Lomitapide-treated versus control is again neglecting other relevant classes such as PE, PC, and LPC that significantly change. In Figure 6G, PL are not even represented, which seems odd. Refer to comment 13.\n18. Regarding Supplementary Figure 6J, K—Microsomal analysis should be done using microsomes isolated from isogenic control and CLSA cells +/- treatments or DGAT.\n19. In all in vivo studies, including the one in Figure 6, I miss the confirmation of the lipidomic profile seen in vitro. This is especially relevant because the cells are implanted in a cyst(e)ine-replete environment, and we don’t know if the phenotype is maintained post-implantation and treatment. Also, it would be relevant to have confirmation that the drug is on-target and that it reaches the tumors. What’s the overall toxicity and the effect on the general systemic metabolism in animals?\n20. Fig 6 J-K It would be cool to use a fluorescent-azide and use click chemistry to show incorporation of OA-alkyne into LD stained with a different color.\n21. General lipid incorporation con be altered in ctrl vs CLSA conditions. Authors need to test this aspect. Also, a general MS analysis with a traceable OA should be used to measure the incorporation of OA in lipids other than TG.\n22. Figure 7- Synergy of Lom +FOLFIRINOX should be showed in a synergy matrix.\n23. In all the in vivo experiments, what is the contribution of ferroptosis? Is ferroptosis the eventual mechanism triggering tumor regression/inhibition?\nMinor Concerns\n24. In general, the results discussion is at points abrupt and should be elaborated more (e.g. “These findings implicated the involvement of other metabolic pathways in addition to OxPPP and G6PD”-which ones?). The authors should include possible limitations too. The discussion is mostly a summary of the results without much elaboration and integration with existing literature. Most of the discussion should be used in the results instead. General statements such “according to the expression patterns of”, or “modulates”, render the readability a bit confusing and jeopardize the results. I advise to revise the text and to better guide the reader though the figures with tangible variables that are the same in both text and figure. The authors should also make sure they use a proper scientific terminology (e.g. “expression” refers to genes and not to proteins)\n25. Methods, figure legends and figures are sloppy in several points and need to be extensively revised and implemented. Some methods are missing, some others are lacking details (e.g normalization, timepoints etc). Figure legends do not provide a comprehensive explanation of the panels and miss important details, hindering a proper evaluation of the results. Some figures and legends are mislabeled. Quantification is missing in multiple panels (e.g LD quantification). Labels of graphs are sometimes missing or not immediate and complicate their interpretation (e.g. Log 2 FC of what?; Fold Change of what?; Expression in PDAC cells (which ones? Ctrl or CLSA)", "reviewer_2": "The present study investigates how pancreatic ductal adenocarcinoma (PDAC) cells adapt to chronic cystine limitation—an environmental stress common in the nutrient‐deprived PDAC microenvironment. The authors show that cells which adapt to cystine limitation (termed “CLSA” cells) not only maintain glutathione synthesis despite low cystine levels but also undergo metabolic reprogramming. Key features of this reprogramming include a translational upregulation of the oxidative pentose phosphate pathway (OxPPP) (notably increased levels of G6PD, PGD, and PGLS), which fuels enhanced nucleotide synthesis and lipogenesis. The increased lipogenesis leads to higher triacylglyceride (TG) production and lipid droplet (LD) formation—a process that helps the cells mitigate lipotoxicity while promoting proliferation and ferroptosis resistance. A drug screen identified lomitapide, an FDA‐approved lipid metabolism drug, as a potent inhibitor of TG synthesis (likely via DGAT inhibition) in these adapted cells. Lomitapide not only induces lipotoxicity in CLSA cells but also sensitises PDAC cells and patient‐derived models to chemotherapy (FOLFIRINOX), leading to improved anti-tumor efficacy in xenograft and genetically engineered mouse models. Overall, the study was well conducted and of broad interest. I only have a few remarks the authors might wish to address:\n1) The authors report the activation of ATF4 at 24 hours upon cysteine limitation. Is the basal activation of ATF4 maintained in the CLSA cells? Expanding on this, does this generate a long-standing dependence on ATF4 activity, and ultimately, is the constitutive activation of ATF4 the causative event leading to increased dependency on TG synthesis? Finally, does the ATF4 activation also observed in the tumor samples? This could add molecular depth to some of the observations reported by the authors.\n2) The aspect describing the increase ferroptosis resistance of CSLA is not worked out in detail. A better characterization, including evaluating the expression of GPX4, SLC7A11, FSP1, for example, would be of interest. Along these lines, to what extent is the PUFA/MUFA ratio changed in the different phospholipid classes. Also, can the inhibition of LD restore the ferroptosis sensitivity in these cells? A recent preprint (https://www.biorxiv.org/content/10.1101/2025.01.06.631537v1 )has hinted at a role of FSP1 in preserving TG and inhibiting ferroptosis within lipid droplets, perhaps this is worth discussing in line with the present observations.\nMinor points:\n-Line 127 and Line 129, starting with “Although..” are duplicated.\n-The word “reprograming” is used in several places; the standard spelling is “reprogramming.”\n-Line 121 - “ferroptosis-like cell death in PDAC cells in in 72 hours” contains a duplicate “in.” It should read “in 72 hours.”\n-Line 448 - In the Discussion section, “miroenvironment” appears instead of “microenvironment.”", "reviewer_3": "The article by Li et al. studies the adaptation to Cystine Limitation Stress (CLS) in PDAC. By using cell lines, patient-derived organoids, patient samples, and diverse mouse models, the authors demonstrate that adaptation to CLS promotes tumor growth by activating the oxidative pentose phosphate pathway via increased translation. CLSA induces lipid reprogramming and de novo lipid synthesis, resulting in triacylglyceride (TG) synthesis and accumulation in lipid droplets to mitigate lipotoxicity. The compound Lomitapide inhibits TG synthesis, interfering with lipid reprogramming and enhancing FOLFIRINOX chemotherapy both in vitro and in vivo.\nI have thoroughly reviewed this manuscript and must commend the authors on the excellent quality of work presented. The research is insightful, well-structured, and contributes significantly to the field. The methodology is sound, and the conclusions drawn are both logical and impactful.\nHowever, there are a few minor corrections and suggestions that I would like to point out:\n1. Is LD staining increased in patients with high G6PD expression? These data would significantly strengthen the story, fully supporting the in vivo/in vitro data presented here on the connection between high oxPPP and increased de novo lipid synthesis.\n2. Considering that the patients used for survival analysis (Table S1) were treated with gemcitabine-based therapies, it would be important to determine if lomitapide sensitizes to gemcitabine or gemcitabine/abraxane on top of mFOLFIRINOX, at least using in vitro assays.\n3. There are a few typographical errors throughout the text.\n4. The statistical analysis methodology must be justified and included in the Materials and Methods section."}, "author_response": "We would like to thank the three reviewers for their many constructive critiques and valuable suggestions. We have performed extensive new experiments and thoroughly revised the manuscript to address to the comments, as detailed in the following point-by-point response.\nPoint-by-point response to reviewer comments\nReviewer 1\nThis manuscript by Li Y, Li Z et al., titled \"Adaptation to Cystine Limitation Stress Confers a Targetable Lipid Metabolism Vulnerability in Pancreatic Ductal Adenocarcinoma (PDAC),\" explores the connection between cysteine limitation adaptation and lipid reprogramming in PDAC.\nWhile many individual aspects such as cyst(e)ine depletion, ferroptosis, oxPPP, and lipid reprogramming are already recognized features of PDAC and might initially seem to lack novelty, the innovative aspect of this study lies in its integration of these elements and the proposal of a new drug combination (LOMITAPIDE) with mFOLFIRINOX chemotherapy. The authors also used a multifaceted approach in multiple PDAC models.\nTherefore, I consider this study to be of significant relevance to the scientific community and the readership of Nature Communications. However, several major and minor concerns, listed below, need to be addressed before it can be considered for publication.\nReviewer #1 (Remarks to the Author):\nMajor Concerns\n1. The starting point of CLSA seems mainly to be attributed to adaptation to a decreased uptake of cystine, as pointed out with the use of IKE and by comparison with the para-tumor content of cyst(e)ine. However, it’s unclear whether in this context there is an impaired SLC7A11 gene expression over time or rather due to usage of cysteine by other pathways beyond GSH. The authors should confirm the most salient results of the manuscript using inducible loss- and gain-of-function of SLC7A11.Is there a loss of SLC7A11 in PDAC patients that can account for a worse prognosis or resistance to chemotherapy? Or is there a role of the pancreas microenvironment in the sequestration of cyst(e)ine?\nResponse: Our western blotting results showed that treatment with 25 uM modestly reduced SLC7A11 protein levels at 7 days and after 4 weeks adaptation (Fig. S1I). However, despite reduction in SLC7A11 protein levels, the CLSA PDAC cells increased FITC-cystine uptake activities by 20-50% (Fig. S1J). Consistent with this observation, CLSA cells had much higher (approximately 4-fold higher) intracellular cysteine when cultured in cystine replete medium (200 uM cystine) (Fig. S1K) according to LC-MS/MS quantitation of NEM-Cysteine. The mechanism underlying the increased cystine uptake is unclear.\nFollowing the suggestion of this reviewer, we used tet-on shRNA to knockdown SLC7A11 in PDAC cells (knockdown efficiency shown in Fig. S4D). As shown in Fig. S4D, although acute knockdown of SLC7A11 (doxycycline, 5 days) had no effect on the protein levels of OxPPP enzymes, the protein levels of G6PD, PGD and PGLS increased after 4 weeks dox-induction (100ng/ml). Chronic SLC7A11 knockdown (4 weeks) also induced adaptation that promoted cell proliferation and ferroptosis resistance (Fig. 1H and S1L). Taken together, our results showed that CLS (induced by either depletion of environmental cystine or by genetic depletion of its transporter) could induce adaptions that activate OxPPP and promote cell proliferation, ferroptosis resistance.\nTo determine whether there is a loss of SLC7A11 in PDAC, we used IHC to compare the expression of SLC7A11 in 60 PDAC tissues and paired para-tumor normal pancreatic tissues (Fig. R1A). Our data showed that there was no difference in SLC7A11 in PDAC vs normal tissues. Analysis of survival data from TCGA PDAC dataset (kmplot.com) also showed that there was no significant correlation between SLC7A11 transcript levels and patient survival (Fig. R1B).\nFigure R1, A, representative IHC staining micrograph (left) and quantitation (right) showing the expression of SLC7A11 in PDAC tissues and paired normal tissues from PDAC patients. B, the correlation between SLC7A11 mRNA transcript levels and PDAC patient overall survival in the TCGA PDAC patient cohort. Data were from kmplot.com. C, representative IHC staining of CDO1 in human liver tissues, PDAC tissues and paired normal pancreas tissues.\nTo determine whether the tumor microenvironment plays a role in cystine sequestration, we used IHC to examine the expression of CDO1, the enzyme responsible for cysteine catabolism. As shown in Figure R1C, although normal pancreatic islet cells had weak CDO1 staining, the pancreatic acinar cells in normal tissues, cancer cells and stromal cells in PDAC tissues were negative for CDO1 expression. Taken together, our data suggested that the cysteine/cystine depletion in the tumor microenvironment was likely not engaged in the active cystine/cysteine catabolism.\nThe lower intracellular cysteine in PDAC tissues could be due to a combination of factors such as increased consumption (due to hyperactive redox flux in cancer cells) and decreased supply (due to desmoplasia and defective vasculatures). In our MS imaging experiment, tumor infiltrating lymphocytes in PDAC tumor tissues had higher levels of Cys than cancer cells (Fig. 1C, Fig. S1A). It remained unclear whether these tumor infiltrating lymphocytes in PDAC tissues compete with cancer cells for cystine to induce CLS.\n2. Even though mass spectrometry was performed in tumors and para-tumor samples, Figure 1 is missing the Cys2 quantification and the ratio. It would be more relevant and convincing to show Cys and Cys2 spatial distribution in tumor and non-tumor areas via MALDI-MS imaging with a corresponding H&E staining.\nResponse: New Cys2 and Cys/Cys2 ratios data are provided in Fig. 1B. We have also performed MS imaging to determine the Cys, Cys2, Cys/Cys2 ratios in regions corresponding to PDAC tissues, normal tissues and PanIn/ADM. Our data (Fig. 1C and Fig. S1A) showed that Cys and Cys/Cys2 ratios were decreased in PanIN/ADM and further decreased in PDAC regions when compared to normal pancreatic tissue regions. Cys2 levels, however, was not significantly different between normal, PanIN and PDAC in MS imaging experiment.\n3. It would be beneficial to have images of CLSA occurring over time in Figure 1C and Supplementary Figure 1, not just at the endpoint. Is CLSA reversible or a permanent event?\nResponse: To obtain the colony formation assay results in supplementary Figure 1 and Fig. 1C, it is necessary to grow the cells undisturbed for approximately two weeks to allow each single cell to form colonies. At earlier time points the colony will be too small for visualization. To determine the intermediate effect of CLSA on PDAC cell proliferation, we used EdU to label the proliferating cells (cells in S phase) after 25 uM Cystine treatment for 0-4 weeks. As shown in Fig. 1E, CLS-25 treatment for 3 days markedly reduced EdU positive cells by approximately 80% in PDAC cells. The proportion of EdU positive cells gradually recover after 1 week culture in 25 uM Cystine medium and exceed the control cells by week 3- week 4 (Fig. 1E).\nTo determine whether CLSA phenotypes are transient or stable, we cultured CLSA cells in cystine replete medium (200 uM) for 4 weeks. As shown in Fig. S1R-S1S and S4E, after 4 week culture in the Cys2-replete media, the cell proliferation, ferroptosis resistance and G6PD expression in CLSP MiaPaCa-2 cells remained elevated when compared to naïve control MiaPaCa-2, which suggested that CLSA is a very stable phenotype, and that the maintenance of these phenotypes didn’t require the continuous presence of CLS.\n4. C11-BODIPY should be expressed as ratiometric values (Green/Red) and not as %high. Please revise Supplementary Figure 1 accordingly. Additionally, these methods and others are missing in the methods section.\nResponse: C11-BODIPY results in the original manuscript were determined using flow cytometry using flow cytometry as we described in a previous publication1. Following the suggestion of this reviewer, we measured C11-BODIPY green-red ratios using fluorescence plate reader and the results were used to replace the flow cytometry results in this revised manuscript (Fig. S1D).\n5. As cyst(e)ine and GPX4 operate on the same axis of ferroptosis regulation, it is not surprising that CLSA PDAC cells become co-resistant to the inhibition of both. What about other pathways regulating ferroptosis? It’s known that cancer cells resistant to the cyst(e)ine/GPX4 pathway can be vulnerable to inhibition of other independent pathways such as FSP1i and DHFR, which are also tightly connected with oxPPP and nucleotide metabolism/synthesis. The authors should show whether these contribute to the phenotype of CLSA in PDAC.\nResponse: As suggested by this reviewer, we tested the effect of CLSA on sensitivities to FSP1 inhibitor iFSP1 and DHFR inhibitor (methotrexate). As shown in Fig. S1M and S1N, CLSA decreased the IC50 of FSP1i from 16.5 uM and 7.9 uM in control MiaPaCa-2 cells and PANC-1 to 1.2 uM and 0.7 uM in their respective CLSA-25 cells (Fig. S1M). CLSA also increased sensitivities to DHFRi, but to a smaller extent (Fig. S1N). Therefore, as suggested by this reviewer, while CLSA increased resistance to ferroptosis inducers targeting cystine/GPX4 pathway, CLSA cells were more vulnerable iFSP1/DHFRi inhibition.\n6. From PDAC orthotopic model experiments, CLSA PDAC cells seem to maintain the more aggressive phenotype shown in vitro. This again suggests a cell-autonomous and permanent adaptation of the PDAC cells even when there is plenty of cyst(e)ine in the pancreas microenvironment. This point is connected to comment number 1 and needs to be dissected with orthogonal loss- and gain-of-function approaches.\nResponse: Indeed, as suggested by this reviewer, CLSA phenotypes are stable and not dependent on the continuous presence of CLS, as indicated by responses to comment 3.\n7. Supplementary Figure 1: Can cyst(e)ine and Trp deprivation be rescued by BSA? The text says 2-4 weeks, the legend says 2 weeks, and panel J says days instead of weeks—what is the timepoint? The authors should consolidate the results and explain why certain results are missing or are not consistent.\nResponse: 2-4 weeks was the time required for PDAC cells to adopt stable adaptation in their nutrient-limited media. The 2 weeks in the legend of colony formation assays were the time needed for colony formation. In these assays naïve control cells or adapted cells were plated in their respective media and cultured undisturbed for 2 weeks to allow the formation of colonies from single cells. The panel J was a cell proliferation assay where naïve or adapted cells were plated on day 0 and their cell proliferation were evaluated over the course of days. Therefore the inconsistency in time course indicated by this reviewer was due to the nature of different experiments and assays.\nNew BSA rescue data are included in Fig. S1F and S1W. Supplementation with 5% BSA not only had no rescue effect on MiaPaCa2 colony formation in cystine limitation Figure R2, 3x103 MiaPaCa-2 cells per well were plated onto a 6 well plate and cultured in control DMEM or Trp-limited (10 uM Trp) media for 14 days. Colonies were stained with crystal violet. condition, but paradoxically further inhibited colony growth. In Trp-limited media PDAC cells was able to maintain cell proliferation for 2 weeks. Similar to 25 uM cystine limitation, including 5% BSA in the Trp-limited media inhibited MiaPaCa-2 cell colony formation (Fig. R2). After 2 weeks, MiaPaCa-2 cells grew in Trp-limited media stopped proliferating. Supplementation with 5% BSA had no rescue effect (Fig. S1W).\nWe must admit that we are puzzled by the inhibitory effects of BSA supplementation in Cystine- and Trp-limited media. However, these experiments have been repeated by three different individuals (Qin Li, Yunzhan Li and Zekun Li) in three different locations (Penn State College of Medicine, Tianjin Cancer Hospital and China Pharmaceutical University) using different batches of BSA and cell culture media and similar results were achieved. Therefore, the inhibitory effect of 5% BSA supplementation in Cys2 and Try limited conditions are highly repeatable and the underlying mechanisms will need to be investigated in the future.\n8. In Figure 2A, the authors find a decrease in the M+4 cysteine derived from labeled cystine; however, the M+0 fraction of cysteine and all other metabolites in Supplementary Figure 2C is increased. The authors suggested briefly that this could be due to additional sources of cysteine, but none of these possibilities were tested or shown. This is particularly relevant as some PDAC cell lines used in this study have a baseline good expression of the transsulfuration pathway genes. Even though PDAC and other cancers seem to rely mainly on cyst(e)ine uptake, the upregulation of the transsulfuration pathway can contribute to the CLSA phenotype. This hypothesis is also corroborated by the ATF4 upregulation (a regulator of the CSE gene) and by the absolute absence of labeling of HTAU and TAU. Authors need to show a C13-serine tracing in vitro and in vivo, with and without CLSA. Also, protein levels of the main components of the de novo synthesis and uptake of cyst(e)ine should be shown in all conditions. Refer to PMID: 36862034 for guidelines regarding this point.\nResponse: Gina DeNicola’s group reported in PMID: 36862034 that cancer cells (including PDAC cells) had little to no detectable de novo synthesis of cysteine through transsulfuration pathway in cell culture or in vivo, despite expression of CBS and CSE. We confirmed the expression of CBS and CSE in PDAC cells and CSE expression was elevated in CLSA MiaPaCa-2 cells (Fig. S2E). However, when C13-serine was used as tracer, there was only less than 1% labeling of cysteine in control MiaPaCa-2 cells and no detectable labeling in CLSA cells (Fig. S2F). We observed a modest increase in the labeling of cystathionine by 13C-serine (Fig. S2F) in CLSA cells (from 27% to 35%). Although there was 20-30% labeling of GSH, fractional labeling decreased in CLSA cells (15%) when compared to control cells (32 %). The lack of cysteine labeling suggested that the GSH labeling by C13-serine was likely due to the conversion of C13-serine into C13-glycine. Our results were consistent with results reported by the DeNicola group and suggested that the transsulfuration pathway is unlikely to be a significant source of cysteine in control or CLSA PDAC cells.\nIt has been previously reported that nutrient limitation promotes macropinocytosis. Therefore, we used fluorescent-labeled dextran to examine the effects of CLSA on micropinocytosis. As shown in Fig.S2G-S2H, we observed significant increase in micropinocytosis in CLSA PDAC cells. Therefore, cysteine uptake from micropinocytosis could potentially account for the increased in M+0 cysteine and other sulfur metabolites in the stable state tracing data in Fig. S2D.\n9. The authors state that CLSA cells have a decrease in the labeled alanine coming from cysteine as a byproduct of the Fe-S cluster pathway. This is linked to a decreased activity of both ACO1 and ACO2 activity (these methods are missing), as well as to Fe-S formation and impaired mitochondrial respiration. Two points require attention: What’s the impact on the mitochondrial mass? And what’s the role of iron metabolism in this phenotype? Key components of the Fe-S pathways such as ISCU and CISD1 are not taken into consideration. It is also unclear why the authors chose H3 as a housekeeping control in Figure 2D.\nResponse: Flow cytometry analysis of Mitotracker Green staining in control and CLSA PDAC cells indicated that there was no significant difference in mitochondrial mass between naïve and adapted PDAC cells (Fig. S2B). Western blotting analysis of TFRC, IRP1, IRP2, ISCU and NFS1 showed upregulation of TFRC and IRP2, which indicated upregulation of the iron starvation response (Fig. 2F). Interestingly, ISCU and NFS1, two core components of the ISC assembly complex, were also downregulated in CLSA cells (Fig. 2F). These data are consistent with the critical roles of Fe-S in the regulation of iron starvation response. Furthermore, the downregulation of ISCU and NFS1 in CLSA cells would likely contribute to the suppression of Fe-S synthesis in CLSA cells.\nBoth tubulin and histone 3 were used as loading control in the original Fig. 2D Western blotting. We have now included Tubulin in addition to Histone H3 in the revised figure (Fig. 2E).\nAconitase activity assay method is now included in the revised Materials and Methods.\n10. MSEA analysis in Figure 3A should show the significant sets that are up and down in CLSA conditions. Also, a heatmap or volcano plot for all the significant metabolites at steady-state should be reported at least in the Supplementary section.\nResponse: MSEA analysis has been performed on upregulated metabolites and downregulated metabolites (Fig. S3B, S3D). In addition, volcano plot of all the significantly changed metabolites were included in Fig. S3A, S3B.\n11. G6PD mRNA levels need to be assessed in multiple cell lines. Also, it’s unclear whether the CHX assay was run in CLSA or control cells. siRNA-mediated knockdown of G6PD should be confirmed with inducible shRNA.\nResponse: We confirmed that, similar to MiaPaCa-2 cells, CLSA had little effect on the G6PD, PGLS and PGD mRNA levels in CLSA PANC1 cells (Fig. S2G). The CHX assay was performed in naïve control MiaPaCa-2 and new data in CLSA25 MiaPaCa-2 cells showed similar results (Fig.S2H). We also confirmed that inducible shRNA depletion of G6PD abrogated CLSA-mediated ferroptosis resistance and cell proliferation (Fig.S2M-S2O).\n12. The authors state that “G6PD overexpression increases ferroptosis resistance.” However, they are just targeting the xCT/GPX4 pathway, which is only one of the pathways. This comment relates to comment #5: The authors need to check other ferroptosis pathways. Also, they should explain why G6PDi or KD induce only a partial rescue of the CLSA-induced phenotype (this is valid also for results in Figure 5J, K).\nResponse: As suggested by this reviewer, we tested the effects of G6PD overexpression on iFSP1. As shown in Fig. S4R, ectopic expression of G6PD in naïve MiaPaCa-2 cells and PANC-1 cells also increase resistance to iFSP1 (IC50 increased from 4.8 uM to 9.6 uM in PANC-1 and 11.1 uM to 30.9 uM in MiaPaCa-2).\nThe partial rescue effect of G6PDi1 or G6PD knockdown in some assays are likely due to metabolic changes in other pathways. We have included the following paragraph in the discussion:\nThe metabolic reprogramming in CLSA PDAC was in part due to suppression of Fe-S synthesis and translational activation of the OxPPP. While genetic or pharmacological inhibition of G6PD abrogated the CLSA-mediated tumor cell proliferation and ferroptosis resistance, ectopic expression of G6PD could only partially recapitulate some of the CLSA phenotypes (e.g. ferroptosis resistance, lipogenesis), but not others (e.g. cell proliferation). These findings implicated the involvement of other metabolic pathways in addition to OxPPP during CLSA. A common adaptation response to chronic amino acid deprivation stress is the compensatory activation of the mTORC1, which promotes both nucleotide and lipid synthesis. The potential role of mTORC1 in CLSA will need to be further investigated in the future.\n13. Lipidome analysis in Figure 5 should include a more thorough analysis, including double bonds and carbon length analysis for all the relevant classes. Also, PC, PE, and PS significantly change in CLSA, but they are not taken into consideration. As these lipids can be both synthesized and stored in LD, they can play a role in the phenotype that is neglected now. Also, they should use an LD-enriched fraction and perform lipidomics on that to prove the relevant differentially regulated lipids are confined there. The same criticism is valid for lipidomics in Figures 6 and 7.\nResponse: The lipidomics data from MiaPaCa2 control and CLSA cells in Figure 5 was untargeted / non-quantitative and not suitable for detailed analysis. Therefore, we performed new targeted/quantitative lipidomics experiment using PANC1 control and CLSA cells (Fig. 6A). Using these new data, we performed double bonds and carbon length analysis in major lipid classes (FFA, PC, PE, PI, PS, PG, TG) and data are shown in Fig. S7. Our data showed that like MiaPaCa2 cells, TG was also prominently upregulated in CLSA cells. Interestingly, PC and Cer, two lipid classes downregulated in CLSA MiaPaCa2 cells were upregulated in CLSA PANC-1, which indicated that CLSA-induced lipidomic changes of different lipid species could be context dependent.\nSimilar analysis have been performed for targeted lipidomics data in the original figures 6 (lomitapide treatment) and 7 (FOLFIRINOX treatment).\nAlso, they should use an LD-enriched fraction and perform lipidomics on that to prove the relevant differentially regulated lipids are confined there.\nResponse: This appeared to be a misunderstanding of our view. We believed that the lipidomics reprogramming in CLSA cells are global and not limited to TG or lipid droplets. Our de novo FA synthesis assay using 13C-glutamine as tracer was examining FA synthesis in the whole lipidome, not limited to TG or LD. In fact, it is well established that FA flux among different lipid classes is intricately connected. Blocking FA flux into one lipid subclass (e.g. TG synthesis) would likely result in increasing FA flux to other subclass (e.g. acyl-CoA, acyl-carnitine, PL etc). The reason that we focused on TG and LD in this manuscript was because our mechanistic studies showed that lomitapide inhibits TG synthesis and LD formation. We agree with this reviewer, lipidomics changes in other lipid classes could have important implications for CLSA phenotypes and PDAC progression. However, due to immense complexity of lipidomes, the context dependent changes in different lipid subclasses (as shown in the new lipidomics screening in PANC1 cells) and the scope of the current study, we choose to focus on the global lipogenesis in general instead of changes in different subclasses.\nTo better reflect our rationale to focus on TG and LD, we have reorganized Figure 5 and 6. Most of the data in the original Figure 6 are now presented in Figure 5 and the original Figure 5 are now Figure 6 in the revised manuscript.\n14. Whenever LDs are accumulating, this could indicate also a decreased lipolysis, which is not taken into consideration. Specific lipase activities should be measured in all conditions to consider the effect of lipolysis in the CLSA phenotype. Lipase inhibitors should also be used to test this hypothesis. The same is valid for the in vivo experiments in Figures 6 and 7.\nResponse: As suggested by this reviewer, we performed ATGL lipase activity assay using cell lysates from control and CLSA MiaPaCa-2 and PANC1 cells. Our new data showed that the lipase activity in control and CLSA PDAC cells were not statistically significant (Fig. S8A). ATGL inhibitor itself had little cytotoxicity in either control or CLSA PDAC cells (Fig. S10F). When combined with gemcitabine, ATGL inhibitor decreased (instead of increased) the sensitivities of gemcitabine chemotherapy in control and CLSA PDAC cells (Fig. S10G). Therefore, our data suggested that the accumulation of TG and LD in CLSA PDAC cells were not due to inhibition of lipolysis and ATGL inhibition would not an effective approach to increase chemosensitivity. Given these observations, we didn’t test the ATGLi in animal models.\n15. Panel L in Figure 5 needs a corresponding H&E to evaluate the result. It would be more informative to see tumor and para-tumor areas together on the same slide.\nResponse: Panel L has been replaced with data showing H&E staining and LD staining on serial sections of PDAC tissues and para-tumor normal tissues (revised Fig. 6L). Frozen PDAC tissues and para-tumor normal tissues in our tissue banks are small in sizes and it is rare to have both normal and cancer tissues on the same block. However, we were able to identify large paraffin blocks that contain both normal and cancer tissues. Paraffin blocks are not suitable for staining with lipid droplet fluorescent dye (BODIPY 493/503 or LipidSpot), due to the use of organic solvents in sample preparation. Therefore, we used immunofluorescence staining of PLIN2 as a marker for LD. Our PLIN2 staining results showed that LD was upregulated in PDAC tissues when compared to para-tumor normal tissues (Fig. S8H).\n16. The 800-drug screen focused on metabolism is nice. However, the lack of a full table and the raw data renders the evaluation of these results difficult. In other words, the authors really need to prove in the most unbiased way that Lomitapide is the best candidate drug to be used. Also, the plausible target of Lomitapide, MTTP, seems to be missing in PDAC cells—which cells are we looking at in Supplementary Figure 6B? Control or CLSA? Also, by implying that Lomitapide targets DGAT, the authors point to potential off-target effects of the drug. There are several other lipid synthesis inhibitors (e.g., FASN, SCD inhibitors) that are available and FDA-approved, which produce a phenotype like Lomitapide but are proven to be very on-target and less promiscuous than Lomitapide. The authors should consider using other inhibitors of the same pathways to corroborate their conclusions.\nResponse: The summary of the 800 drug screening results were shown in Fig 5A and we have now included the data for this panel in the corresponding source data file. As shown in the source data table, lomitapide was the number 3 most effective drugs in the drug screening and the number 1 among the FDA approved drugs. To the best of our knowledge, there is no FDA approved FASN or SCD1 inhibitors for the treatment of cancer or other diseases. Orlistat is an FDA-approved gastric and pancreatic lipase inhibitor that was reported to have potential FASN inhibitory activities. However, like lomitapide, this is also a repurposed drug instead of a FASN-specific inhibitor. In our manuscript, we did identify through drug screening and validate other FDA-approved lipid metabolism drugs such as mevastatin and darapladib (Fig. 5B). However these drugs were less effective than lomitapide.\nAs suggested by this reviewer we tested FASN and SCD1 inibitors Denifanstat and A939572 (both were tested in clinical trials) in MiaPaCa2 cells. As shown in Fig. S5B, CLSA PDAC cells were more sensitive to denifastat (IC 50: 66.5 uM and 14.6 uM for naïve and CLSA MiaPaCA2 cells; 30.7 uM and 7.5 uM for naïve and CLSA PANC1 cells). A939572 had little effect on PDAC cell viability even at 100 uM and the IC50s were not determined.\nWe would also like to respectfully point out that although inhibitions of lipid synthesis (by targeting FASN and SCD1) could potentially inhibit TG synthesis and LD formation, the mechanisms of action are different from DGAT inhibitors. Lipid synthesis inhibitors would not be effective in targeting TG/LD due to elevated lipid/FA uptake or lipolysis. On the other hand, inhibitors targeting DGAT would be effective in targeting TG/LD from de novo FA synthesis, lipid uptake or lipolysis alike.\n17. Lipidomics of Lomitapide-treated versus control is again neglecting other relevant classes such as PE, PC, and LPC that significantly change. In Figure 6G, PL are not even represented, which seems odd. Refer to comment 13.\nResponse: In the original Figure 6G, we didn’t include PL in the volcano plot because we intended to emphasize increases in toxic lipid species (FA and CAR). Including PL would mask FA and CAR on the plot. Following the suggestion of this reviewer, we have replotted the data, to include PC, PE, LPC and other major lipid classes in several different volcano plots (Fig. 5G, Fig. S5F-S5I). In addition, we have performed carbon length and double bond analysis (Fig. S5J).\n--\n18. Regarding Supplementary Figure 6J, K—Microsomal analysis should be done using microsomes isolated from isogenic control and CLSA cells +/- treatments or DGAT.\nResponse: New experiments using microsomes isolated from control and CLSA cells were perfomred. Similar to liver microsome experiments, lomitapide could inhibit DGAT activities in PDAC cell microsome and pre-incubation reduced or abrogated the inhibitory activities of lomitapide toward DGAT activity (Fig. S6H).\n19. In all in vivo studies, including the one in Figure 6, I miss the confirmation of the lipidomic profile seen in vitro. This is especially relevant because the cells are implanted in a cyst(e)ine-replete environment, and we don’t know if the phenotype is maintained post-implantation and treatment. Also, it would be relevant to have confirmation that the drug is on-target and that it reaches the tumors. What’s the overall toxicity and the effect on the general systemic metabolism in animals?\nResponse: Our new immunofluorescence staining using PLIN2 antibody confirmed that CLSA MiaPaCa2 xenograft tumors had more LD than control tumors and lomitapide treatment reduced LD staining (Fig. S6C-S6D). We used PLIN2 staining because these tumor samples were preserved via FFPE and not suitable for LipidSpot or BODIPY 493/503 staining. In the previous submission, we showed LipidSpot LD staining in tumor tissues harvested from PDX models and our results showed that chemotherapy increased LD staining, which could be inhibited by lomitapide treatment (Fig. S10K-S10L). Our new PLIN2 staining in FFPE samples from KPC model showed similar results to PDX experiments (Fig. 7M).\nAs an FDA-approved drug, the toxicity and side effects of lomitapide have been extensively characterized in pre-clinical animal studies and clinical trials. The real-world evaluations of the safety and efficacy of long-term lomitapide therapy among HoFH patients have also been extensively documented in the literature2-4 . Overall, long term administration lomitapide therapy was found to be safe among patients and the dose that we used in animal studies were relevant to the dose in patients. Most common adverse events were manageable, mild to moderate gastrointestinal side effects (e.g. diarrhea, nausea etc). Another common side effect is steatosis and increase in liver inflammation; however, most of the liver side effects were observed after long-term lomitapide therapy (19 months or longer) and progression to liver fibrosis was very rare. General effects of lomitapide on systemic metabolism among patients included lower LDL-c and fat accumulation in the liver, due to its inhibition of MTTP.\nIn our animal experiments we observed no weight loss from lomitapide single treatment; when combined with FOLFIRINOX, the combination group had no additional weight loss when compared to FOLFIRINOX group (Fig. S10J). We discuss the side effects of lomitapide in the limitation section of the revised manuscript. Future development of lomitapide-based DGAT inhibitors without MTTP inhibitory effects would be desirable.\n20. Fig 6 J-K It would be cool to use a fluorescent-azide and use click chemistry to show incorporation of OA-alkyne into LD stained with a different color.\nResponse: We did try OA-alkyne labeling in PDAC cells and unfortunately, we were not able to achieve good labeling of LD. This is likely because TG localized to the hydrophobic core of LD and poorly accessible to Cu2+, which is needed to catalyze the click-chemistry reaction. The click-chemistry reaction for extracted lipids (in TLC experiments) happened in organic solvents using [acetonitrile] CuBF as catalyst. Such 4 4 conditions would destroy LD structure and therefore not suitable for microscopy.\n21. General lipid incorporation con be altered in ctrl vs CLSA conditions. Authors need to test this aspect. Also, a general MS analysis with a traceable OA should be used to measure the incorporation of OA in lipids other than TG.\nFigure R3, Control and CLSA-25 MiaPaCa-2 cells were incubated with 10 uM [U-18C] OA for 6 hours. The lipids were extracted and separated into FFA, neutral lipids and polar lipids using a SPE column. The lipids were saponified and used for the analysis of fractional OA labeling through LC-HRMS. Response: Due to the immense complexity of lipidome, it is technically challenging to trace FA incorporation into thousands of different lipid species. Therefore, we used solid phase extraction to separate the lipids into three main categories: neutral lipids (including TG, DG, acyl-ceramides etc), free fatty acids and polar lipids (including phospholipids and lysophospholipids). Using [U-13C]-OA as tracer, we observed increased OA incorporation into polar lipids in CLSA MiaPaCa-2, but not to FFA or neutral lipids. We are including this data in this response letter for the information of this reviewer (Figure R3). The increased incorporation into polar lipids could be due to the elevated cell proliferation (and thus increase in membrane biogenesis). We would like to further investigate this hypothesis in future studies. However, if this reviewer felt it was necessary, we could include the data in the revised manuscript.\nUsing SPE separation and [U-13C]-OA tracing, we also demonstrated in new experiments that lomitapide inhibited OA incorporation into neutral lipids, with no significant effects on incorporation into polar lipids or FFA (Fig. 6F).\n22. Figure 7- Synergy of Lom +FOLFIRINOX should be showed in a synergy matrix.\nResponse: The synergy of lomitapide plus FOLFIRINOX data were The Zero Interaction Potency (ZIP) score analysis was performed using SynergyFinder5 to determine the synergistic effects between Lomitapide and mFOLFIRINOX treatments. Data are shown in Fig. S10C.\nFigure R4, 4HNE IHC staining of PDX-1 tissues harvested from experiments in Figure 7F-7I.\n23. In all the in vivo experiments, what is the contribution of ferroptosis? Is ferroptosis the eventual mechanism triggering tumor regression/inhibition?\nResponse: As shown in Fig.S5C, pan-caspase inhibitor ZVAD and RIPK1 inhibitor Necrostatin-1 could partially rescue, lomitapide-induced cell death, at least in CLSA cell. However, ferrostatin-1 had no effect. C11-Bodipy staining in cell culture (Fig. S5D) and and 4HNE staining of lomitapide-treated PDX-1 tumor sections (Fig. R4) showed that lomitapide treatment had little effect on lipid peroxidation in vitro or in vivo. Taken together our data showed that lomitapide likely induced cell death through a combination of apoptosis and necroptosis, but not ferroptosis. With that said, we have new experiments showing that when combined with RSL-3, lomitapide could increase sensitivity to RSL-3 induced ferroptosis and overcame CLSA-mediated ferroptosis resistance (Fig. S6E).\nMinor Concerns\n24. In general, the results discussion is at points abrupt and should be elaborated more (e.g. “These findings implicated the involvement of other metabolic pathways in addition to OxPPP and G6PD”-which ones?). The authors should include possible limitations too.\nThe discussion is mostly a summary of the results without much elaboration and integration with existing literature. Most of the discussion should be used in the results instead. General statements such “according to the expression patterns of”, or “modulates”, render the readability a bit confusing and jeopardize the results. I advise to revise the text and to better guide the reader though the figures with tangible variables that are the same in both text and figure. The authors should also make sure they use a proper scientific terminology (e.g. “expression” refers to genes and not to proteins)\nResponse: We have revised the discussion section to incorporate the constructive critiques of this reviewer, including providing more detailed discussion of other potential metabolic pathways, adding a new limitation sections, removing or shortening the parts describing or summarizing results, among others. Results section has also been revised to include tangible variables such as IC50 and numerical values. In addition, all references to “protein expression” were revised to “protein abundance” or “protein levels”.\n25. Methods, figure legends and figures are sloppy in several points and need to be extensively revised and implemented. Some methods are missing, some others are lacking details (e.g normalization, timepoints etc). Figure legends do not provide a comprehensive explanation of the panels and miss important details, hindering a proper evaluation of the results. Some figures and legends are mislabeled. Quantification is missing in multiple panels (e.g LD quantification). Labels of graphs are sometimes missing or not immediate and complicate their interpretation (e.g. Log 2 FC of what?; Fold Change of what?; Expression in PDAC cells (which ones? Ctrl or CLSA)\nResponse: Methods and Figure legends have been revised to include additional details (such as normalization and timepoints) and to improve clarity. All the LD staining have been quantified. The figures and legends have been checked multiple rounds to correct for mistakes and to improve clarity.\nReviewer #2 (Remarks to the Author):\nThe present study investigates how pancreatic ductal adenocarcinoma (PDAC) cells adapt to chronic cystine limitation—an environmental stress common in the nutrient‐deprived PDAC microenvironment. The authors show that cells which adapt to cystine limitation (termed “CLSA” cells) not only maintain glutathione synthesis despite low cystine levels but also undergo metabolic reprogramming. Key features of this reprogramming include a translational upregulation of the oxidative pentose phosphate pathway (OxPPP) (notably increased levels of G6PD, PGD, and PGLS), which fuels enhanced nucleotide synthesis and lipogenesis. The increased lipogenesis leads to higher triacylglyceride (TG) production and lipid droplet (LD) formation—a process that helps the cells mitigate lipotoxicity while promoting proliferation and ferroptosis resistance. A drug screen identified lomitapide, an FDA‐approved lipid metabolism drug, as a potent inhibitor of TG synthesis (likely via DGAT inhibition) in these adapted cells. Lomitapide not only induces lipotoxicity in CLSA cells but also sensitises PDAC cells and patient‐derived models to chemotherapy (FOLFIRINOX), leading to improved anti-tumor efficacy in xenograft and genetically engineered mouse models. Overall, the study was well conducted and of broad interest. I only have a few remarks the authors might wish to address:\n1) The authors report the activation of ATF4 at 24 hours upon cysteine limitation. Is the basal activation of ATF4 maintained in the CLSA cells? Expanding on this, does this generate a long-standing dependence on ATF4 activity, and ultimately, is the constitutive activation of ATF4 the causative event leading to increased dependency on TG synthesis? Finally, does the ATF4 activation also observed in the tumor samples? This could add molecular depth to some of the observations reported by the authors.\nResponse: As we shown in Fig. S1I, although ATF4 levels remained upregulated at up to 7 days after CLS exposure, its levels in CLSA cells return to levels comparable to those in control cells after 4 week adaptation. These data suggested that CLSA cells were able to overcome ISR despite marked reduction in intracellular cysteine. These observations are also consistent with the data showing global upregulation of mRNA translation, since ISR in general suppress global translation.\nWe performed IHC staining of ATF4 in PDAC tissues and paired paranormal tissues. Our data showed that there was no difference in ATF4 staining between cancer and normal tissues (Figure R5). Taken together, our data suggested that ATF4 or ISR are unlikely to be responsible for CLSA phenotypes, including the dependency on TG synthesis.\nFigure R5, Representative IHC images (A) and H score quantitation (B) of ATF4 staining intensities in the PDAC tissues and para-tumor normal tissues from 60 PDAC patients.\n2) The aspect describing the increase ferroptosis resistance of CSLA is not worked out in detail. A better characterization, including evaluating the expression of GPX4, SLC7A11, FSP1, for example, would be of interest.\nResponse: We have previously investigated the effects of CLSA on multiple proteins involved in ferroptosis resistance (FSP1, COQ2, SLC7A11 etc) and these data are now included in this revised manuscript (Fig. S1O). In summary, we found that FSP1 was paradoxically downregulated in CLSA PDAC cells, but COQ2, the rate limiting enzyme in de novo CoQ10 synthesis, was upregulated. CLSA PDAC cells were also more sensitive to inhibitors targeting the CoQ10 pathway (iFSP1). SLC7A11 was downregulated in CLSA cells (Fig. S1I), but the cystine uptake activity was upregulated (Fig. S1J and S1K, please also see response to reviewer 1, comment 1).\nFSP1/DHODH inhibition or COQ2 knockdown could at least partially overcame ferroptosis resistance in CLSA cells (Fig. S1Q).\nAlong these lines, to what extent is the PUFA/MUFA ratio changed in the different phospholipid classes. Also, can the inhibition of LD restore the ferroptosis sensitivity in these cells? A recent preprint (https://www.biorxiv.org/content/10.1101/2025.01.06.631537v1 )has hinted at a role of FSP1 in preserving TG and inhibiting ferroptosis within lipid droplets, perhaps this is worth discussing in line with the present observations.\nResponse: As suggested by this reviewer, we analyzed the C18:2/C18:1/C18:0 ratios, as well as the levels of C20:4, C22:4 and C22:6 in major lipid classes in naïve and CLSA PANC-1 cells and the new data are shown in Fig. S7. Overall, we found that ferroptosis-promoting PUFAs (C20:4, C22:4 and C22:6) were increased (instead of decreased) in major lipid classes. Therefore, the ferroptosis resistance in CLSA PDAC cells was likely not due to changes in PUFA levels in the lipidome.\nWe also discussed the bioRxiv preprint suggested by this reviewer and tested the effects of lomitapide, alone or in combination with RSL-3 in naïve and PDAC cells. Our new data showed that lomitapide treatment by itself didn’t induce lipid peroxidation or ferroptosis (Fig. S5C, S5D). Lomitapide-induced cell death could be rescue by inhibitors for apoptosis and necroptosis, but not by ferrostatin-1 (Fig. S5C, S5D). However, when combined with RSL-3, lomitapide could sensitize PDAC cells (naïve or CLSA) to RSL3 and largely overcame CLSA-mediated ferroptosis resistance (Fig. S6E). These data are largely in line with recent evidence implicating a role for LD in ferroptosis resistance.\nMinor points:\n-Line 127 and Line 129, starting with “Although..” are duplicated.\n-The word “reprograming” is used in several places; the standard spelling is “reprogramming.”\n-Line 121 - “ferroptosis-like cell death in PDAC cells in in 72 hours” contains a duplicate “in.” It should read “in 72 hours.”\n-Line 448 - In the Discussion section, “miroenvironment” appears instead of “microenvironment.”\nResponse: These typos and mistakes have been corrected in the revised manuscript. Thank you!\nReviewer #3 (Remarks to the Author):\nThe article by Li et al. studies the adaptation to Cystine Limitation Stress (CLS) in PDAC. By using cell lines, patient-derived organoids, patient samples, and diverse mouse models, the authors demonstrate that adaptation to CLS promotes tumor growth by activating the oxidative pentose phosphate pathway via increased translation. CLSA induces lipid reprogramming and de novo lipid synthesis, resulting in triacylglyceride (TG) synthesis and accumulation in lipid droplets to mitigate lipotoxicity. The compound Lomitapide inhibits TG synthesis, interfering with lipid reprogramming and enhancing FOLFIRINOX chemotherapy both in vitro and in vivo.\nI have thoroughly reviewed this manuscript and must commend the authors on the excellent quality of work presented. The research is insightful, well-structured, and contributes significantly to the field. The methodology is sound, and the conclusions drawn are both logical and impactful.\nHowever, there are a few minor corrections and suggestions that I would like to point out:\n1. Is LD staining increased in patients with high G6PD expression? These data would significantly strengthen the story, fully supporting the in vivo/in vitro data presented here on the connection between high oxPPP and increased de novo lipid synthesis.\nResponse: To address this question, we evaluated the levels of G6PD and LD levels in 30 patients. As shown in Fig. S8I-S8J, the expression levels of G6PD significantly correlated with LD levels, which is consistent with our in vitro data showing that activation of OxPPP could contribute to LD accumulation.\n2. Considering that the patients used for survival analysis (Table S1) were treated with gemcitabine-based therapies, it would be important to determine if lomitapide sensitizes to gemcitabine or gemcitabine/abraxane on top of mFOLFIRINOX, at least using in vitro assays.\nResponse: As suggested by this reviewer, we tested the effect of lomitapide on PDAC cell sensitivities to Abraxane/Gemcitabine. Our data showed that lomitapide treatment sensitized PDAC cells to Abraxane/Gemcitabine treatments in naïve and CLSA PDAC cells (Fig. S10D).\n3. There are a few typographical errors throughout the text.\nResponse: The revised manuscript has been checked for typos and grammar mistakes.\n4. The statistical analysis methodology must be justified and included in the Materials and Methods section.\nResponse: A statistical method section has been added."}, {"round": 2, "reviewer_comments": {"reviewer_1": "I commend the authors for such a thorough and extensive revision!\nWell done! In my opinion, the manuscript is now suitable for publication in Nature Communications\nA few minor comments/suggestions:\n1) I found both the BSA supplementation and the OA incorporation results very interesting and I definitely suggest to investigate these mechanisms in the future studies.\n2) Lomitapide seems to be potent regardless of CLSA, so I would probably highlight this in the discussion\n3) I spotted a few typos: lines 409 (\"Taking\" instead of \"Taken\"); 433 (FIg); 458, 576 (\"Lipidomics\" instead of \"Lipidome\")\n4) There are 2 reference sections-all references should be together\n5) Suppl Fig. 9 panel E misses the color legend", "reviewer_2": "The authors have sufficiently addressed my concerns.\nI would only avoid stating that the resistance cells upregulate Coq biosynthesis proteins since the effect observed is only marginal.", "reviewer_3": "No further comments"}, "author_response": "Point by point response\nReviewer #1 (Remarks to the Author):\nI commend the authors for such a thorough and extensive revision!\nWell done! In my opinion, the manuscript is now suitable for publication in Nature Communications\nA few minor comments/suggestions:\n1) I found both the BSA supplementation and the OA incorporation results very interesting and I definitely suggest to investigate these mechanisms in the future studies.\nResponse: We thank the reviewer for their thoughtful suggestions.\n2) Lomitapide seems to be potent regardless of CLSA, so I would probably highlight this in the discussion\nResponse: The discussion has been modified according to the suggestion.\n3) I spotted a few typos: lines 409 (\"Taking\" instead of \"Taken\"); 433 (FIg); 458, 576 (\"Lipidomics\" instead of \"Lipidome\")\n4) There are 2 reference sections-all references should be together\n5) Suppl Fig. 9 panel E misses the color legend\nResponse: All the mistakes have been corrected.\nReviewer #2 (Remarks to the Author):\nThe authors have sufficiently addressed my concerns.\nI would only avoid stating that the resistance cells upregulate Coq biosynthesis proteins since the effect observed is only marginal.\nResponse: We have changed the wording “increase” to “moderately increase” following the suggestion of this reviewer."}]

Decision letter