Pancreatic ductal adenocarcinoma (PDAC) is the most lethal common cancer (5-year survival ∼13%), emerging through years-to-decades progression involving chronic fibro-inflammatory injury and precursor transformation processes including ADM and PanIN. KRAS-driven acinar-to-ductal metaplasia (ADM) is among the earliest experimentally tractable and potentially interceptable events; KRAS (mutated in >90% of PDAC) has remained difficult to therapeutically target, particularly for prevention; emerging KRAS inhibitors are developed for treatment of established malignancy rather than early interception. We aimed to prioritize KRAS-axis interception candidates via AI-guided network analysis of TCGA-PAAD restricted to a curated KRAS-driven ADM/PanIN-initiation mechanism module.
The 38-gene module (n=183 TCGA-PAAD samples; 37 genes available, PRSS2 absent) spans KRAS-MAPK, RTKs, TGF-β/SMAD, ECM, inflammation, transcription, tumor suppressors, and ductal/acinar genes from canonical pancreatic-cancer-progression biology, linking established-tumor transcriptomes to early-interception biology. A stability-selected Spearman-correlation network served as the network backbone (PCMCI+/NOTEARS extensions ongoing), paired with patient-level bootstrap filtering (B=200 resamples; ≥70% retention). A composite Interception Score I(v) = α·CB + β·Σ|w| + γ·U + δ·R integrating betweenness centrality, summed edge-weight influence, druggability (literature-curated drug-target prior), and bootstrap robustness ranked candidate interception nodes (unoptimized weights; tuning ongoing).
Spearman correlation yielded a 37-node, 248-edge network baseline; bootstrap resampling (B=200) evaluated 856 distinct candidate edges, of which 194 (22.7%) achieved ≥70% retention, defining the stable subgraph used for scoring. The Interception Score placed 7 KRAS-axis genes among the top-10 candidates: ERBB2 (0.953), KRAS (0.743), ERBB3 (0.742), MAPK1 (0.708), EGFR (0.675), MAP2K2 (0.605), and BRAF (0.589). Inflammation (IL6, 0.755), TGF-β/SMAD2 (0.726), and ECM/MMP2 (0.638) also ranked highly, recapitulating PDAC initiation mechanisms (stromal-epithelial crosstalk; inflammatory-fibrotic priming). ERBB2 (HER2), a clinically druggable RTK with approved inhibitors in other malignancies, emerged as the top-ranked candidate, supporting evaluation of HER2-axis signaling for interception in molecularly selected PDAC subsets. These findings align with canonical PDAC biology, supporting biological plausibility prior to formal weight optimization and external validation.
AI-guided network analysis of TCGA-PAAD prioritizes biologically coherent KRAS-axis and stromal-inflammatory candidates with clinically available HER2-, EGFR-, MEK-, BRAF-, and KRAS-pathway inhibitors, supporting hypothesis generation for future pancreatic cancer interception studies. Stage-resolved analysis, causal-inference extensions, and sex-/age-stratified validation are ongoing.
Jianfu Li, Yingyun Yang, Michael Wallace, Cui Tao, Yan Bi. AI-Driven Network-Based Discovery on TCGA-PAAD Identifies KRAS-Axis Drug-Repurposing Targets for Pancreatic Cancer Interception [abstract]. In: Proceedings of AACR Drug Discovery and Development (AACR D3) Conference; 2026 Jul 21-24; Boston, MA. Philadelphia (PA): AACR; Clin Cancer Res 2026;32(14_Suppl):Abstract nr A029.
Jianfu Li, Yingyun Yang, Michael B. Wallace et al.· Clinical Cancer Research· 0 citations
Early-onset pancreatic cancer (EOPC; age <50 y at diagnosis) is rare (≈1.3/100,000), biologically distinct, and germline-enriched (BRCA1/2, PALB2, ATM, CDKN2A, Lynch). Despite NCCN and CAPS Consortium recognition, its pre-diagnostic electronic health record (EHR) trajectory is uncharacterized. We sought reproducible signatures to guide subtype-aware surveillance for this under-screened young-adult population, where conventional guidelines do not apply.
We assembled an EOPC cohort from Mayo Clinic (3 sites, 2001–2023; n=169 EOPC, n=3,162 older-onset PDAC), identified by ICD-10 C25.0–C25.3, C25.7, C25.9 or ICD-9 157.x with age <50 at first diagnosis. For each patient, 3-year pre-diagnostic trajectories of 10 routine laboratory analytes (bilirubin, CA 19-9, CEA, lipase, amylase, glucose, HbA1c, ALT, AST, alkaline phosphatase) were summarized over 30/90/180/365-day windows (mean, slope, delta; 1,706 features total; 131 retained at ≥10% non-zero). Features were winsorized (1–99 pct), standardized, and projected onto 15 PCA components capturing 81.7% variance. K-means clustering (k=2–6, min cluster fraction ≥10%) was assessed by silhouette and 100-resample bootstrap Adjusted Rand Index (ARI). Cluster signatures were compared against the older-onset PDAC cohort projected into the same component space.
Two reproducible pre-diagnostic clusters emerged (k=2; silhouette 0.469; bootstrap ARI 0.440). Cluster A: "occult prodrome" (87.0%; n=147; mean age 44.9 y) showed no clear signal across the 10 monitored analytes, with all analyte z-scores near zero through the 3-year window. Cluster B: "metabolic-biliary active" (13.0%; n=22; mean age 44.4 y) was characterized by elevated mean HbA1c (z=+1.08), rising bilirubin slope (z=+0.54), and rising ALT/alkaline phosphatase slopes (z=+0.51 each), consistent with combined diabetic-onset and biliary-obstructive prodrome. The two-cluster structure reproduced in older-onset Mayo PDAC at 87.3% / 12.7%, nearly identical to the EOPC distribution, indicating a fundamental pre-diagnostic dichotomy of pancreatic cancer rather than an age-specific phenomenon. The dominant occult phenotype across age strata indicates that lab-trajectory–anchored surveillance can only address the active minority and motivates complementary genetic-, demographic-, or imaging-anchored pathways for the occult majority.
EOPC pre-diagnostic trajectories partition into a dominant occult prodrome (∼87%) without detectable signal in the 10 routine labs evaluated and a minority metabolic-biliary active prodrome (∼13%) with combined diabetic and obstructive features. The high occult prevalence motivates germline-guided active surveillance for genetically at-risk young adults rather than symptom-driven workup, anchoring next-generation surveillance trial designs in rare and hereditary pancreatic malignancies. External validation in independent institutional cohorts (Mayo Clinic Platform / MERCI, or comparable EHR networks) is the planned next step.
Jianfu Li Li, Yingyun Yang, Wallace MIchael, Yan Bi. Pre-diagnostic clinical-trajectory signatures of early-onset pancreatic cancer [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: Breaking Barriers in the Fight against Rare Cancers; 2026 Jul 18-20; Philadelphia, PA. Philadelphia (PA): AACR; Cancer Res 2026;86(14_Suppl):Abstract nr A046.
Jianfu Li, Yingyun Yang, Wallace MIchael et al.· Cancer Research· 0 citations
