Prevalence and Prognostic Significance of PIK3CA Mutation and CNV Status and Phosphorylated AKT Expression in Patients With Cervical Cancer Treated With Primary Surgery
Bibliographic record
Abstract
Currently, there are limited and conflicting reports on the prognostic utility of PIK3CA and associated pathway markers for cervical cancers treated with primary surgical management. Moreover, current studies are lacking complete characterization of adjuvant treatment with RT and/or chemotherapy. We aimed to document the prevalence, clinicopathologic, adjuvant treatment details, and prognostic value of PI3K/AKT pathway mutations and copy number variation and phosphorylated AKT status in patients with cervical cancers treated with primary surgery. A clinicopathologic review was performed on a retrospective cohort of 185 patients with cervical cancer, treated with primary surgery at a single tertiary institution. Next-generation sequencing and digital PCR was used to determine PI3K/AKT pathway mutational status and PIK3CA copy number variation, respectively, and fluorescent immunohistochemistry measured phosphorylated AKT expression. In all, 179 of 185 (96.8%) of tumors were successfully sequenced; 48 (26.8%) were positive for PI3K/AKT pathway mutations-the majority (n=37, 77.1%) PIK3CA mutations. PIK3CA mutation was associated with pathologically positive lymph nodes [12 (32%) vs. 22 (16%); P =0.022] and indication for postoperative chemoradiotherapy [17 (45.9%) vs. 32 (22.5%); P =0.004]. On multivariable analysis, PIK3CA status was not associated with overall survival ( P =0.103) or progression-free survival ( P =0.240) at 5 yrs, nor was PIK3CA copy number variation status. phosphorylated AKT ≤ median significantly predicted for progression-free survival [multivariable hazard ratio 0.39 (0.17-0.89; P =0.025)] but not overall survival ( P =0.087). The correlation of PIK3CA with pathologic positive lymph node status yet lack of association with survival outcomes may be due to the use of adjuvant postoperative therapy. PIK3CA assessment before radical hysterectomy may help identify patients with a higher risk of node-positive disease.
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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 | 0.002 |
| 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) | 0.001 | 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".