Abstract 3068: Identify targetable molecular drivers of chemotherapy resistance in gastroesophageal adenocarcinoma
Bibliographic record
Abstract
Abstract Introduction: Gastroesophageal adenocarcinoma (GEA) is one of the most lethal malignancies worldwide. Even with the standard-of-care chemotherapy, 40% of the patients are innately resistant and half of the initial responders develop acquired resistance. The molecular mechanisms underlying the development of resistance in GEA remain largely unknown. Methods: 30 GEA patients who received chemotherapy were included in this cohort. Both pre-and post-treatment primary tissues were collected to generate patient-derived organoids (PDOs). 29 PDOs were treated with chemotherapeutic agents and the cell viability was measured. We also evaluated the correlation between ex-vivo drug responses of PDOs and in-patient clinical responses. Data obtained from whole-exome (WES) and RNA sequencing of the primary tumor and their PDOs were analyzed to identify targetable molecules associated with chemo-resistance. Results: After treatment, the cell viability of the PDOs obtained from chemo-resistant patients was significantly higher than that of chemo-sensitive patients. The variant allele frequency of the PDOs recapitulated their parental tumors. WES of one patient tumor revealed an increased copy number of EGFR, and their PDOs showed high sensitivity to an EGFR inhibitor in the subsequent drug screens. Furthermore, 40% of chemo-sensitive patients had mutations in one or more genes belonging to the adhesion G protein-coupled receptors (GPCRs) family. The adenylate cyclase-activating G protein-coupled receptor signaling pathway was found to be significantly activated only in chemo-sensitive patients. Single-cell RNA sequencing of pre-and post-treatment tissue revealed a broadly shifted transcriptome in epithelial cells. Patients with upregulated cell stemness genes including CTNNB1, MYC, ETS2, and KLF4 had disease recurrence 6 months post-surgery, while patients with unaltered or downregulated stemness genes remain disease-free 18 months until today. Conclusion: Our PDOs not only reflected the genetic profile of primary tumors but also recapitulated patient responses to chemotherapy. Genomic analysis revealed that mutations in a few GPCR genes might have a role in increased sensitivity to chemotherapy. In addition, the transcriptomic analysis showed stemness genes were associated with disease recurrence. Our GEA PDO platform allows the identification and the subsequent verification of resistant-conferring targets, providing insight for novel therapeutic combinations. Funding: This project is supported by the Cancer Research Society (CCS), and the Department of Defence (DoD), USA. Citation Format: Mingyang Kong, Swneke Bailey, Veena Sangwan, Lorenzo Ferri. Identify targetable molecular drivers of chemotherapy resistance in gastroesophageal adenocarcinoma [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 3068.
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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 | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".