Predictive and Prognostic Analysis of PIK3CA Mutation in Stage III Colon Cancer Intergroup Trial
Bibliographic record
Abstract
BACKGROUND: Somatic mutations in PIK3CA (phosphatidylinositol-4,5-bisphosphonate 3-kinase [PI3K], catalytic subunit alpha gene) activate the PI3K-AKT signaling pathway and contribute to pathogenesis of various malignancies, including colorectal cancer. METHODS: We examined associations of PIK3CA oncogene mutation with relapse, survival, and treatment efficacy in 627 stage III colon carcinoma case subjects within a randomized adjuvant chemotherapy trial (5-fluorouracil and leucovorin [FU/LV] vs irinotecan [CPT11], fluorouracil and leucovorin [IFL]; Cancer and Leukemia Group B 89803 [Alliance]). We detected PIK3CA mutation in exons 9 and 20 by polymerase chain reaction and pyrosequencing. Cox proportional hazards model was used to assess prognostic and predictive role of PIK3CA mutation, adjusting for clinical features and status of routine standard molecular pathology features, including KRAS and BRAF mutations and microsatellite instability (mismatch repair deficiency). All statistical tests were two-sided. RESULTS: Compared with PIK3CA wild-type cases, overall status of PIK3CA mutation positivity or the presence of PIK3CA mutation in either exon 9 or 20 alone was not statistically significantly associated with recurrence-free, disease-free, or overall survival (log-rank P > .70; P > .40 in multivariable regression models). There was no statistically significant interaction between PIK3CA and KRAS (or BRAF) mutation status in survival analysis (P(interaction) > .18). PIK3CA mutation status did not appear to predict better or worse response to IFL therapy compared with FU/LV therapy (P(interaction) > .16). CONCLUSIONS: Overall tumor PIK3CA mutation status is not associated with stage III colon cancer prognosis. PIK3CA mutation does not appear to serve as a predictive tumor molecular biomarker for response to irinotecan-based adjuvant chemotherapy.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".