267. IDENTIFYING CANCER-ASSOCIATED FIBROBLAST POPULATIONS DRIVING THERAPY RESISTANCE IN GASTROESOPHAGEAL ADENOCARCINOMA
Bibliographic record
Abstract
Abstract Background Peri-operative docetaxel-based triplet chemotherapy is the standard-of-care treatment for advanced gastroesophageal adenocarcinoma (GEA). However, most patients recur due to innate or acquired resistance. Although distinct populations of cancer-associated fibroblasts (CAFs) within the tumor microenvironment play important roles in conferring chemoresistance in other cancer types, this paradigm has not been extensively studied in GEA. We aim to characterize CAF heterogeneity in a well-annotated cohort of GEA patients, identifying potential biomarkers and targets to overcome chemoresistance. Methods Immunofluorescence and flow cytometry assays were performed to validate previously reported CAF markers from the literature in primary patient fibroblasts. To identify specific CAF markers for GEA, an atlas was developed using single-cell RNA sequencing (scRNA-seq) data obtained from 46 GEA patient samples, including 28 patients with longitudinal samples over the docetaxel-based triplet chemotherapy treatment trajectory. Differential and gene ontology analyses were performed to characterize distinct CAF subpopulations and identify dynamic CAF markers across treatment timepoints, while correlating with in-patient treatment response to chemotherapy. In parallel, tumor organoid-CAF co-cultures were established for subsequent in vitro drug testing with standard-of-care chemotherapy. Results CAF markers (VIM, FAP, PDPN, and S100A4) were found to be differentially expressed in fibroblasts isolated from good and poor pathological-response tumours. Analysis of scRNA-seq data reveals two main subpopulations of CAFs: myofibroblast CAFs (myCAFs) and inflammatory CAFs (iCAFs). Two markers, CCL20 and CHRDL1, were identified as differentially expressed between good and poor pathological responders in iCAFs, while nine markers, including ISG20 and C20orf27, were differentially expressed between clinical partial responders and poor responders. Dynamic CAF markers, including STAG2 and HAT1, were differentially expressed across treatment timepoints and were associated with pathological or clinical response. Conclusions GEA CAFs demonstrate extensive heterogeneity and comprise two major subpopulations. Several CAF markers were found to be associated with patient chemotherapy pathological or clinical response to chemotherapy, either in the chemonaïve setting or in the context of changes over the course of therapy. These putative biomarkers will be further validated and investigated, both in additional samples and in co-culture settings, to gain a better understanding of their clinical relevance and targeting potential.
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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 | 0.001 |
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".