Supplementary Figure S10. TR-107 downregulates the expression of essential mitochondrial proteins. Colorectal cancer cells (A) LoVo, (B) NCI-H508, (C) LS 174T, and (D) RKO were treated with vehicle control (0.1% DMSO) or TR-107 (50 nmol/L) for 24 hours. Immunoblot (N=3) was performed for various mitochondrial regulatory and metabolic proteins. (E-H) Band densitometry analysis was conducted to quantify relative protein expression and normalized to β-actin control. Densitometry was measured with ImageJ and analyzed with GraphPad Prism as described in Materials and Methods. Data are presented as mean ± SD values (N=3). *, P < 0.05; **, P < 0.01; ***, P < 0.001; ****, P < 0.0001.

The basal-like molecular subtype of pancreatic ductal adenocarcinoma (PDAC) is highly lethal and therapy resistant. A better understanding of the underlying molecular mechanisms driving this aggressive tumor subtype is necessary for the development of effective therapies. Notably, upregulation of keratin 17 (K17) in cancer is associated with poor patient outcome and the basal-like PDAC subtype. In this study, we identified a critical dependency of basal-like PDACs on de novo pyrimidine biosynthesis, driven by intramitochondrial K17. Mechanistically, K17 translocated into the mitochondrial intermembrane space via a mitochondrial localization signal recognized by the translocase of outer mitochondrial membrane 20. In the mitochondria, K17 bound to and stabilized dihydroorotate dehydrogenase, the rate-limiting enzyme of de novo pyrimidine biosynthesis, by preventing its ubiquitination-mediated degradation. Blocking the entry of K17 into the mitochondria sensitized cancer cells to gemcitabine, a pyrimidine analogue and standard chemotherapeutic agent. In animal studies, pharmacologic inhibition of dihydroorotate dehydrogenase combined with gemcitabine treatment decreased tumor growth and doubled survival in mice bearing K17+ but not K17- PDAC. These findings define a mitochondrial role for K17 in driving pyrimidine biosynthesis and uncover a metabolic vulnerability in K17+ basal-like PDACs that can be therapeutically targeted. SIGNIFICANCE:Targeting the mitochondrial role of keratin 17 in pyrimidine biosynthesis represents a promising strategy to sensitize basal-like pancreatic cancer to gemcitabine and improve outcomes in this lethal subtype.

Supplementary Figure 10: The combination of gemcitabine and brequinar treatment inhibits K17+ cells in vivo. A-B. Tumor volume of mice bearing L3.6 K17 and K17 KO tumors, treated with indicated drugs. C-D. Fold change of tumor volume (normalized to saline controls on day 0) of mice bearing L3.6 K17 and K17 KO tumors, treated with indicated drugs. E-G. Fold change of tumor volume (normalized to K17 tumors on day 0) of mice bearing L3.6 WT and K17 KO tumors, treated with indicated drugs. Two-way ANOVA followed by Šídák's test. *P<0.05, **P<0.01 H-J. The survival of mice bearing L3.6 WT and K17 KO tumors, treated with indicated drugs. Dots are censored points.

Supplementary Figure 9: Gemcitabine combined with brequinar, but not FCCP or Gboxin, effectively inhibits K17+ cells in vitro. A-B. The IC50 values of gemcitabine (A) and brequinar (B) in KPC SE (EV, K17, and mMLS-K17) cell line models. Mean ± SD, n = 4, One-way ANOVA followed by Tukey’s test. C. Cell viability following treatment of gemcitabine and brequinar in KPC SE (EV, K17, and mMLS-K17) cell line models. Cells were treated with gemcitabine alone or gemcitabine plus brequinar for 48 hours. Data is normalized to EV groups. Mean ± SD, n = 4, Two-way ANOVA followed by Šídák's test. D-G. Fold change of IC50 values of brequinar in K17+ (D-E) or K17− (F-G) cell line models with or without exogenous dC. Mean ± SD, n = 3–4, One-way ANOVA followed by Dunnett's test. H-I. Combination treatment of brequinar and gemcitabine in KPC (H) and PANC-1 (I) K17 SE cell line models. The synergy distribution is indicated by colors. J-K. Combination treatment of gemcitabine and FCCP (J) and gemcitabine and Gboxin (K) in L3.6 K17 LFO and KPC K17 SE cell line models. The synergy distribution is indicated by colors. *P<0.05, **P<0.01, ***P<0.001, ****P<0.0001.

High-fat diet (HFD) intake has been linked to an increased risk of pancreatic ductal adenocarcinoma (PDAC), a lethal and therapy-resistant cancer. However, whether and how specific dietary fats drive cancer development remains unresolved. Leveraging an oncogenic Kras -driven mouse model that closely mimics human PDAC progression, we screened a dozen isocaloric HFDs differing solely in fat source and representing the diversity of human fat consumption. Unexpectedly, diets rich in oleic acid - a monounsaturated fatty acid (MUFA) typically associated with good health - markedly enhanced tumorigenesis. Conversely, diets high in polyunsaturated fatty acids (PUFAs) suppressed tumor progression. Relative dietary fatty acid saturation levels (PUFA/MUFA) governed pancreatic membrane phospholipid composition, lipid peroxidation, and ferroptosis sensitivity in mice, concordant with circulating PUFA/MUFA levels being linked to altered PDAC risk in humans. These findings directly implicate dietary unsaturated fatty acids in controlling ferroptosis susceptibility and tumorigenesis, supporting potential "precision nutrition" strategies for PDAC prevention.

Supplementary Figure 1: K17 upregulates nucleotide-related pathways. A. Unbiased TCGA data analysis using primary PDAC tumor samples. K17 mRNA levels correlate with normalized enrichment scores (NES); Spearman correlation and P-values are shown. NES values were compared between previously established high and low K17 groupings using the Wilcoxon rank-sum test. The top 17 pathways with the highest enrichment scores and P-values are shown. B-C. Human PANC-1 PDAC cells are transduced to stably express either empty vector (EV) or human K17 (K17) as a stable expression (SE) model. By Immunofluorescence, K17 is shown in green, and the nucleus is indicated by DAPI stain in blue. Scale bar = 100 μm. D. Metabolomic analyses in PANC-1 K17 SE cell line model. Data are shown in heatmaps with n = 5 per group. Two-way ANOVA followed by Šídák's test. Statistical significance between groups is indicated. E-G. Metabolomic analyses in K17 LOF (E) and SE (F-G) cell line models. Relative levels of glycolysis, TCA cycle, and PPP were shown with n = 5 per group. Two-way ANOVA followed by Šídák's test. *P<0.05, **P<0.01, ***P<0.001.

Supplementary Figure 6: Mitochondrial-localized K17 interacts with DHODH and increases its level. A-E. Western blots of whole cell lysates (WCL), cytosolic and mitochondrial subcellular fractions of K17, DHODH, COX IV, and β-actin/α-tubulin in L3.6 (A) and BxPC-3 (B) K17 LOF cell line modes, KPC (C) and PANC-1 (D) K17 SE cell line models, and L3.6 K17-rescue cell line models (E). F-H. Western blots showing immunoprecipitation of K17 with DHODH, TOM20, and COX IV in cytosolic and mitochondrial fractions from BxPC-3 (F) K17 LOF, or KPC (G) and PANC-1 (H) K17 SE cell line models. An input control of fraction lysates is included. I. Immunofluorescent images of K17 (red), TOM 20 (green), and nucleus (blue) in KPC K17 SE cell line models captured by super-resolution confocal microscopy. J. Bar graph indicates the co-localized area of K17 and TOM20. Mean ± SD, n = 10, Welch’s t-test. K. Cell proliferation of L3.6 KO and KPC cells expressing EV, K17, or mMLS-K17 determined by crystal violet staining. n = 6. L. Western blots of WCL, cytosolic and mitochondrial fractions showing K17, DHODH, TOM40, COX IV, and α-tubulin following the limited digestion assay in K17 LOF and SE cell line models. M. Western blots demonstrating immunoprecipitation of K17 and its interaction with DHODH in whole-cell lysates from human PDAC patient-derived organoids. Note that organoid hF44 shows higher K17 levels with detectable DHODH.

Supplementary Figure 4: K17 drives gemcitabine resistance by increasing intracellular deoxycytidine. A-B. Dose response curves of K17-negative cells treated with gemcitabine and individual nucleosides. C-D. Dose response curves of K17-positive cells treated with gemcitabine and individual nucleosides. E-F. Fold change of cell proliferation in K17-negative cells treated with individual nucleosides. Crystal violet staining. n = 4. G-H. Fold change of cell proliferation in K17-positive cells treated with individual nucleosides. Crystal violet staining. n = 4. I-K. Cell proliferation of KPC, L3.6, and PANC-1 cell line models determined by WST-1 assay. n = 3. L-N. Cell cycle progression between K17-positive and K17-negative cells in KPC, L3.6, and PANC-1 cell line models. n = 3. O. The deoxycytidine/gemcitabine ratio is shown upon gemcitabine treatment, as determined by LC-MS/MS in PANC-1 K17 SE cell line model. Mean ± SD, n = 3, Welch’s test. P. 13C-glucose metabolic flux analysis in K17 LOF and SE cell line models to measure glucose, glucose 6-phosphate (G6P), and lactate flux. Mean ± SD, n = 3, Two-way ANOVA followed by Šídák's test. Q. The mRNA level of enzymes involved in nucleoside transporter was analyzed by qRT-PCR in KPC, L3.6, and PANC-1 cell line models. n = 3. SLC29A1 encodes ENT1, and SLC29A2 encodes ENT2. R. Western blots of ENT1 and ENT2 protein levels in L3.6, BxPC-3, KPC, and PANC-1 cell line models. S. Quantification showing fold change of ENT1/α-tubulin and ENT2/α-tubulin in isogenic cell line models. *P<0.05, **P<0.01, ***P<0.001.

Supplementary Figure 8: Mitochondrial K17 stabilizes DHODH by blocking its ubiquitination. A-J. Western blots for ubiquitin in WCL and mitochondrial fractions following DHODH immunoprecipitation in K17 LOF (A-D), SE (E-H), and rescue (I-J) cell line models. IgG immunoprecipitation controls are included. The input control of WCL and mitochondria fraction lysates are included (B, D, F, H, J). Bar graphs show quantification of the DHODH ubiquitination fold change across the isogenic cell line models. n = 3. Welch’s t-test. #P = 0.061. K-N. Quantification of DHODH degradation determined by CHX and MG132 assay in K17 LOF (K), SE (L-M), and rescue (N) cell line models. n = 3. Two-way ANOVA followed by Šídák's test. O. Metabolomic analyses in KPC cells expressing EV, K17, or mMLS. Data are shown as heatmaps with n = 4 per group. Two-way ANOVA followed by Tukey's test. Statistical significance between groups is indicated. P. Intracellular CTP levels measured by mass spectrometry in K17 LOF and SE cell line models. Mean ± SD, n = 3. Welch’s t-test. *P<0.05, **P<0.01.

Supplementary Figure 5: No significant difference in genes involved in pentose phosphate pathway and pyrimidine biosynthesis between K17+ and k17− cells. A-B. The expression of genes involved in the pentose phosphate pathway (GO0006098) for KPC (A) and L3.6 (B) cell lines. C-D. The expression of genes involved in the pyrimidine biosynthesis pathway (GO0006221) for KPC (C) and L3.6 (D) cell lines.

Supplementary Table 1. Identification of potential drugs for targeting nucleotide metabolism. Abbreviations are shown as follow. DHODH: dihydroorotate dehydrogenase, CAD: carbamoyl-phosphate synthetase 2, aspartate transcarbamoylase, and dihydroorotase, UMPS: uridine monophosphate synthetase, CDA: cytidine deaminase, CNT2: concentrative nucleotide transporter 2, DPYD: dihydropyrimidine dehydrogenase, PPAT: phosphoribosyl pyrophosphate amidotransferase, DHFR: dihydrofolate reductase, RNR: ribonucleotide reductase, HPRT: hypoxanthine-guanine phosophoribosyltransferase, TS: thymidylate synthase, GART: glycinamide ribonucleotide transformylase. Selected drugs for testing drugs are bolded. Based on our previous study, response (%) In K17-positive cells lower than 30 are consider not responsive.

Supplementary Figure 7: Mitochondrial K17 stabilizes DHODH. A-D. Western blot images of DHODH half-life determined by cycloheximide (CHX) chase assay in whole cell lysate (WCL) and mitochondria of L3.6 K17 LOF cell line modes (A), KPC and PANC-1 K17 SE cell line models (B-C), and L3.6 K17-rescue cell line models (D).

Adenosine diphosphate (ADP) ribosylation (ADPr) regulates multiple stress responses, yet substrates in the apoptotic machinery remain elusive. We show that a single, DNA damage-induced ADPr event controls proapoptotic PIDDosome (PIDD1/RAIDD/caspase-2) formation in response to unresolved interstrand DNA cross-links (ICL). ADPr targets conserved E783 in the PIDD1 death domain (DD); is catalyzed by poly(ADP-ribose) polymerase 4 (PARP4), a phylogenetically orphan PARP of previously unknown function; is reversed by the ribosylhydrolase activity of PARP14; and is triggered by Ataxia Telangiectasia and RAD3-related (ATR) phosphorylation-induced, PIAS1-mediated SUMOylation of the PIDD1 DD, which enables PARP4 docking. PIDD1 ADPr is dispensable for the recruitments of RAIDD and caspase-2 but essential for the dimerization of the caspase. Hence, denying E783 ADPr spares the onset of PIDDosome assembly but blocks its completion, thus eliminating caspase-2 activation and ensuing apoptosis. Conversely, removal of PARP14 forces apoptosis, even in cells with tolerable damage. The data identify PARP4 as an ICL response effector and illuminate a three-step modification sequence of the PIDD1 DD that conducts PIDDosome assembly from initiation to completion.

Supplementary Figure 3: Targeting upregulated nucleotide metabolism by inhibiting de novo pyrimidine synthesis in K17-expressing PDAC (A-H), and nucleoside addition promotes gemcitabine resistance of pancreatic cancer cells (I-L). A-B. Kaplan–Meier curves of patients with upregulated pyrimidine (A) or purine (B) salvage pathways, further stratified based on K17 status. Log-rank P-values are reported. The TCGA analysis included 44 cases each from the low and high K17 expression groups. C. Kaplan–Meier curves which stratify TCGA PDAC patients relative to the mRNA of their GSEA scores for nucleotide metabolism. D-H. CyQUANT IC50 values or relative index of KPC cells with or without K17 expression to Brequinar (D-E, note: CyQUANT relative index: 0.09 in EV cells; 0.06 in K17 cells), Tetrahydrouridine (F), Azathioprine (G), and 6-Mercaptopurine (H), were shown. Welch’s test. n = 4. *P<0.05. I. Fold change in intracellular nucleoside levels following treatment with individual exogenous nucleosides in L3.6 and KPC cell line models, measured by mass spectrometry. NC, no-treatment control. n = 3. Two-way ANOVA followed by Dunnett's test compared with NC. J-M. Representative microscope images of KPC and L3.6 cell line models treated with DMSO or gemcitabine at indicated supplementation with each nucleoside (40x).

Supplementary Figure S6. Washout of TR-107 treatment suggests an irreversible inhibition of CRC cell viability. (A) HCT116 cells were treated in a 96-well plate format with vehicle control (0.1% DMSO) or indicated concentrations of TR-107 for 2, 4, 6, 8, 12, 24, and 72 hours. At each time point, wells were washed out twice with fresh media and replaced with fresh media lacking treatment up until 72 hours. Cell viability was assessed for all treatment durations after 72 hours. Data are presented as mean ± SD values (N=6). *, P < 0.05; **, P < 0.01; ***, P < 0.001; ****, P < 0.0001. (B) Western blot analysis of HCT116 cells after 24 hours of treatment with washout and 72 hours with no washout. HCT116 cells were treated with vehicle control (0.1% DMSO) or TR-107 10 nmol/L, 50 nmol/L, 1 μmol/L. Immunoblot was performed for ClpX, mtTFA, and β-actin as loading control.

Activation and proliferation of parietal epithelial cells (PECs), located along the inner rim of Bowman's capsule, drives disease progression in subtypes of glomerulonephritis and focal segmental glomerulosclerosis. In examining the mechanisms contributing to PEC activation two established mouse models were utilized in this study, nephrotoxic serum nephritis (transient model) and podocyte-specific Klf4 knockout (progressive model). A role for transcription factor FRA2 (Fosl2) was uncovered through single nuclear multiomic approaches relating to the regulation of PEC transcriptional/chromatin dynamics. Co-immunoprecipitation followed by mass spectrometry assessed the FRA2 protein interactome in cultured PECs, revealing a potential role for FRA2 in alternative splicing. Fosl2 expression was then blunted through CRISPR-Cas9 gene editing in cultured PECs, revealing reduced proliferative capacity and the downregulation of myofibroblast markers. In-vivo genetic lineage tracing of PECs after nephrotoxic serum revealed PEC-to-myofibroblast trans-differentiation events. Finally, immunostaining of human kidney biopsies with varied subtypes of glomerulonephritis confirmed Fosl2 expression in activated PECs within crescentic lesions, with single cell deconvolution strategies assigning PEC-skewed proportion ratios to bulk RNA-seq patient data from the NEPTUNE consortium. These results suggest that FRA2 (Fosl2) directs a conserved molecular program of PEC-specific responses in subtypes of glomerulonephritis and focal segmental glomerulosclerosis.

The postantibiotic effect (PAE) is the persistent suppression of microbial growth following the removal of antimicrobial therapy. In general, antibiotics that generate a PAE are dosed less frequently, and thus, the PAE has important implications for dosing regimens. PAEs can arise through several mechanisms, including the extended occupancy of the drug target following drug elimination, and the correlation between drug-target residence time and PAE provides insight into target vulnerability. To assess the vulnerability of Escherichia coli leucyl-tRNA synthetase (ecLeuRS), which is an essential enzyme in protein synthesis, the time-dependent inhibition of the enzyme was studied by the benzoxaborole class of compounds that inhibit LeuRS by forming a stable LeuRS-tRNALeu-benzoxaborole adduct. Preincubation of epetraborole with ecLeuRS resulted in a decrease in the IC50 value for enzyme inhibition from 38 to 3 nM, consistent with the slow formation of the final enzyme-inhibitor complex, and similar shifts in IC50 were observed for three other benzoxaboroles. The benzoxaboroles generated short PAEs (<1 h) in E. coli, however, the PAE values of AN3334 and epetraborole increased from 0.88 to 1.70-3 h when a sub-MIC concentration of the aminoglycoside tobramycin was included in the media. pSILAC revealed that the synthesis rate of ecLeuRS was reduced 1.6-fold in the presence of sub-MIC tobramycin, reinforcing the role that protein turnover plays in target vulnerability.

The ability of Candida albicans to resist stressful conditions in the host and grow invasively into tissues contributes to the virulence of this human fungal pathogen. Plasma membrane subdomains known as the MCC (membrane compartment of Can1) or eisosomes are important for these processes. MCC/eisosome domains are furrow-shaped invaginations of the plasma membrane that are about 250 nm long and 50 nm deep. To identify proteins that localize to these domains, a proximity labeling method was used in which the TurboID variant of the BirA biotin ligase was fused to Sur7 and Lsp1, 2 proteins that localize to eisosomes and are important for virulence. This resulted in biotinylation of nearby proteins, permitting their identification. Analysis of 19 candidate proteins by tagging with the green fluorescent protein identified 7 proteins that detectably overlapped with MCC/eisosomes. Deletion mutant analysis showed that one of these, a poorly studied protein known as Ker1, was important for hyphal growth in liquid culture, invasive growth into agar medium, and resistance to stress caused by copper and cell wall perturbing agents. Altogether, these approaches identified novel MCC/eisosome proteins and show that TurboID can be applied to better define the molecular mechanisms of C. albicans pathogenesis and aid in discovery of targets for novel therapeutic strategies.

The postantibiotic effect (PAE) is the delay in bacterial regrowth following antibiotic removal. It has important implications for dosing regimens since drugs that have extended activity following their elimination can be dosed less frequently, widening the therapeutic window. While the PAE has been associated with target vulnerability and the rate of target turnover, little is known about the genetic components that modulate the PAE. Here, we developed a high-throughput assay to screen the Escherichia coli Keio collection of ∼4000 deletion strains, identifying genes that enhance the PAE for CHIR-090, an inhibitor of UDP-3-O-(R-3-hydroxymyristoyl)-N-acetylglucosamine deacetylase (LpxC). This screen revealed approximately 400 gene knockouts that enhanced the PAE of CHIR-090. The list of PAE enhancers was enriched for genes involved in transmembrane transport and outer membrane synthesis. Notably, deletion of the rfaE gene, which is involved in lipopolysaccharide (LPS) biosynthesis, increased the PAE of the LpxC inhibitors CHIR-090 and LPC-058 by 2 and 3 h, respectively. Consistent with this phenotype, cotreatment of wild-type E. coli with an RfaE inhibitor increased the PAE of CHIR-090 or LPC-058 by 1 h. To probe the mechanism of this interaction, we measured the rate of LpxC turnover and found that knocking out rfaE extended the half-life of LpxC by 2-fold, suggesting that disrupting RfaE increases the stability of LpxC, increasing target vulnerability and enhancing the PAE of LpxC inhibitors.