High CDCP1 Expression Reflects Immune and Stromal Remodeling and Oncogenic Signaling in Pancreatic Ductal Adenocarcinoma
Bibliographic record
Abstract
Background: CUB domain-containing protein 1 (CDCP1) is implicated in pancreatic ductal adenocarcinoma (PDAC) prognosis, but its relationship to the tumor microenvironment (TME) and oncogenic signaling remains incompletely defined. We hypothesized that CDCP1 expression is associated with hallmark cancer signaling pathways and transcriptionally inferred TME remodeling in PDAC. Methods: We analyzed transcriptomic and clinical data from 214 PDAC cases (The Cancer Genome Atlas (TCGA), n = 145; GSE62452, n = 69). Patients were stratified into high CDCP1 and low CDCP1 groups based on the top tertile of expression. Immune and stromal components of the TME were quantified using the xCell algorithm. Gene Set Enrichment Analysis (GSEA) with Hallmark gene sets was used for pathway enrichment. Results: T cells, adipocytes, and fibroblasts, suggesting an immune-excluded and stromally depleted TME. It also correlated with increased homologous recombination deficiency scores, mutation burden, and single-nucleotide variants. CDCP1 expression correlated with CDKN2A mutation but was only weakly associated with KRAS, TP53, and SMAD4 alterations. GSEA showed consistent enrichment of proliferative (E2F, MYC, G2M, p53) and protumorigenic (transforming growth factor-β, hypoxia, glycolysis) pathways in high CDCP1 tumors across both datasets. Conclusion: CDCP1 defines a transcriptionally distinct PDAC subtype characterized by immune evasion, stromal depletion, and genomic instability. These findings highlight CDCP1 as a potential therapeutic target and biomarker reflecting interplay between oncogenic signaling and the TME.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".