Pancreatic adenocarcinomas without KRAS, TP53, CDKN2A and SMAD4 mutations and CDKN2A/CDKN2B copy number alterations: a review of the genomic landscape to unveil therapeutic avenues
Bibliographic record
Abstract
BACKGROUND: Pancreatic adenocarcinoma is one of the cancers with the worst prognosis. The current treatment paradigm based on combination chemotherapy has improved survival over the last decade, but the disease is still fatal in most cases. New therapies exploiting the increasing understanding of the molecular pathology of the disease are needed. Although the disease presents with few recurrent molecular alterations, these represent opportunities for targeted treatments to be developed. However, a minority of cases are devoid of these common alterations. A description of the molecular landscape of this sub-set of pancreatic adenocarcinoma could uncover other molecular lesions present in them that could serve as therapeutic targets. METHODS: The sub-set of pancreatic cancers without the common alterations in KRAS, TP53, CDKN2A and SMAD4 has been examined from published and publicly available pancreatic cancer cohorts for determination of their clinical and molecular characteristics. The cBioportal platform was used for this evaluation and the OncoKB knowledgebase was used for determination of the functional significance of discovered mutations. RESULTS: About 5% to 10% of pancreatic adenocarcinomas present without the usual molecular alterations that characterize the disease. These cases tend to be genomically stable and have low prevalence of microsatellite or chromosome instability. Molecular alterations that are observed in pancreatic cancers in lower frequencies than the four most prevalent alterations, such as DNA Damage Response and epigenetic modifier mutations, are still observed in the sub-set without the common alterations and may be pathogenically relevant. CONCLUSIONS: Despite the absence of most frequent pancreatic cancer alterations in a sub-set of pancreatic adenocarcinomas, this sub-set possesses other alterations in frequencies similar to the rest of pancreatic cancers. Putative targeting of alterations present is discussed and can serve as the basis for targeted therapies 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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.004 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".