It Is All in the Genes: A Story of Unexpected Survival in a 67-Year-Old Male with Metastatic Pancreatic Cancer
Bibliographic record
Abstract
Background. We describe a case report of a 67-year-old male with PDAC who experienced an exceptional survival outcome during systemic therapy and its implications in precision medicine. We hypothesize that his outcomes are attributable, in part, to a germline BRCA2 deletion and somatic GNAS substitution. Methods. Retrospective single-patient chart review was performed at the London Regional Cancer Program, as well as a structured literature search spanning all years in PubMed of BRCA and GNAS mutations in pancreatic cancer. Results. The case described herein represents a 67-year-old male who survived over 27 months after third-line treatment with gemcitabine, docetaxel, and capecitabine (GTX) chemotherapy for metastatic PDAC after progression on gemcitabine and Abraxane and then on FOLFIRINOX. His survival far exceeded the median overall survival metrics. Genetic testing revealed a pathogenic heterozygous germline BRCA2 6643delT p.(Tyr2215Thrfs ∗ 14) frameshift mutation and somatic GNAS 2531 G > A p.(Arg844His) mutation. Conclusions. This case highlights the urgent need to expand our knowledge of cancer biology to advance personalized cancer treatment and therapy development.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.005 |
| 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".