PIK3CA Mutated Colorectal Cancers Without KRAS, NRAS and BRAF Mutations Possess Common and Potentially Targetable Mutations in Epigenetic Modifiers and DNA Damage Response Genes
Bibliographic record
Abstract
BACKGROUND/AIM: Despite therapeutic advancements, metastatic colorectal cancer is usually fatal, necessitating novel approaches based on the molecular pathogenesis to improve outcomes. Some colorectal cancers have no mutations in the extended RAS panel (KRAS, NRAS, BRAF) genes and represent a special subset, which deserves particular therapeutic considerations. MATERIALS AND METHODS: The genomic landscape of colorectal cancers from publicly available genomic series was interrogated, using the cBioportal platform. Colorectal cancer cohorts with cancers devoid of KRAS/NRAS or BRAF mutations were evaluated for the presence of mutations in the catalytic sub-unit alpha of kinase PI3K, encoded by the gene PIK3CA. RESULTS: PIK3CA mutations in the absence of KRAS/NRAS/BRAF mutations were observed in 3.7% to 7.6% of colorectal cancers in the different series examined. Patients with all four genes in wildtype configuration (quadruple wild type) represented 32.2% to 39.9% of cases in the different series examined. Compared with quadruple wild type cancers, triple (KRAS/NRAS/BRAF) wild type/PIK3CA mutated cancers had a higher prevalence of high TMB cases and additional mutations in colorectal cancer associated genes except for mutations in TP53. Mutations in genes encoding for epigenetic modifiers and the DNA damage response (DDR) were also more frequent in triple wild type/PIK3CA mutated cancers. The prognosis of the two groups was comparable. CONCLUSION: Colorectal cancers with PIK3CA mutations in the absence of KRAS/NRAS/BRAF mutations have frequently mutations in epigenetic modifiers and DDR response genes, which may provide opportunities for targeting. These mutations are present in a smaller subset of quadruple wild type cancers.
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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 | 0.001 |
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".