PIK3CA Mutation as Potential Poor Prognostic Marker in Asian Female Breast Cancer Patients Who Received Adjuvant Chemotherapy
Bibliographic record
Abstract
Background: The prognostic relevance of the PIK3CA mutation together with PD-L1, c-Met, and mismatch repair deficiency (dMMR) have not been fully investigated in Asian women with breast cancer (BC) who have undergone postoperative adjuvant chemotherapy. Methods: We analyzed PIK3CA mutations via peptide nucleic acid (PNA)-mediated real-time PCR assay, PD-L1/c-Met expression via immunohistochemistry (IHC), and microsatellite instability (MSI) status using PCR and IHC, in 191 resected BCs from 2008 to 2011. The Cancer Genome Atlas (TCGA) dataset for the involvement of the PIK3CA mutation with PD-L1/c-Met/MMR was explored. Results: The PNA clamp-mediated assay was able to detect the PIK3CA mutation in 1% of the mutant population in the cell line validation. Using this method, the PIK3CA mutation was found in 78 (49.4%) of 158 samples. c-Met and PD-L1 positivity were identified in 31.4 and 21.8% of samples, respectively, which commonly correlated with high histologic grade and triple-negative subtype. MSI/dMMR was observed in 8.4% of patients, with inconsistency between MMR IHC and the MSI PCR. The PIK3CA mutation exhibited a poor prognostic association regarding recurrence-free survival (RFS) in both overall and triple-negative BCs. In subgroup analyses, the PIK3CA-mutated tumors showed poorer RFS than the PIK3CA-wildtype within the c-Met-positive, MSS, triple-negative, or age onset <50 years subgroups, which showed a similar trend of association in TCGA data. Conclusions: PIK3CA mutation together with c-Met or dMMR/MSI status might be relevant to poor prognosis in BC subsets, especially in Asian women.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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 teacher head, 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".