DOI: 10.5281/zenodo.18501690
title: Supplementary Material for "Glycolysis-stratified coordination of fatty acid and glutamine metabolism in pancreatic ductal adenocarcinoma""

description: Update in this version: Supplementary files updated to include a revised metabolite-inference heatmap (glycolysis strata × metabolite-defined state concordance) and updated CPTAC-PDAC proteomics validation using enzyme/meta-correlation (r_meta) with permutation-tested Δr_meta = r_meta(High) − r_meta(Low) and BH-FDR (q).

Supplementary Material for Glycolysis-stratified coordination of fatty acid and glutamine metabolism in pancreatic ductal adenocarcinoma

Contents:- A Graphical Abstract

This Zenodo repository contains all supplementary figures, tables, and source data referenced in the manuscript, including transcriptomic analyses (S1-S2), metabolite-inference analyses (S3-S5), a schematic of fatty-acid families and representative enzymes (S6), and proteomic validation (S7).

S1 – Predictive Modeling of GLN ActivityS1 Fig. Elastic-Net out-of-fold predictions for GLN activity by glycolysis grouping. S1 Table. Cross-validated performance metrics (R² and RMSE) by grouping. S1 Data. Out-of-fold predicted vs. observed GLN activity by sample.

S2 – FA Family DefinitionsS2 Table. Curated mapping of fatty-acid (FA) pathways/enzymes to functional families used in transcriptomic analyses.

S3 – Inferred Metabolite ActivitiesS3 Fig. Principal component analysis (PCA) of inferred metabolite activities across PDAC samples. S3 Table. Raw and z-scored inferred metabolite activity scores for 13 metabolites.

S4 – Metabolite State ComparisonsS4 Fig. Heatmap showing concordance between glycolysis strata (Low/Medium/High) and metabolite-defined metabolic states (sample counts). 

S4 Table. One-way ANOVA and Kruskal–Wallis statistics comparing metabolite activities across phenotypes.

S5 – Mapping and Final State LabelsS5 Table. Metabolite–gene mapping with +1/−1 directionality assignments used to compute weighted metabolite activity scores. S5 Data. Final metabolite-defined metabolic state labels for all PDAC samples.

S6 – FA Chain-length Schematic and CPTAC Proteome CharacteristicsS6 Fig. Schematic mapping representative enzymes and pathways across fatty-acid chain-length classes (MCFA, LCFA, VLCFA) and two example lipid families (glycerophospholipids, sphingolipids).S6 Table. Descriptive statistics for the CPTAC PDAC tumor proteome (MD_abundance_tumor matrix), including number of tumors (n = 140), total proteins (11,662), per-protein missingness distribution, and the number of proteins retained after filtering to ≥70% observed values (7,993).

S7 – Proteomic Validation of FA–GLN Coordination (CPTAC-PDAC Cohort)S7 Fig. Proteomics validation of glycolysis-state differences in FA–GLN coupling using enzyme/meta-correlation (r_meta) across tertiles.S7 Table. Family-level r_meta values by glycolysis tertile (Low/Medium/High) computed from protein-level Spearman correlations summarized in Fisher-z space.S8 Table. Δr_meta = r_meta(High) − r_meta(Low) with permutation p-values (B=5,000) and BH-FDR q-values.

Contact: Contact: Correspondence available upon request.
description: Update in this version: Supplementary files updated to include a revised metabolite-inference heatmap (glycolysis strata × metabolite-defined state concordance) and updated CPTAC-PDAC proteomics validation using enzyme/meta-correlation (r_meta) with permutation-tested Δr_meta = r_meta(High) − r_meta(Low) and BH-FDR (q).