10P PIK3CA mutation and response to neoadjuvant taselisib and endocrine therapy: A biomarker study of the LORELEI trial
Bibliographic record
Abstract
Various predictive biomarkers regarding PI3K inhibitors in patients with estrogen receptor-positive breast cancer (BC) have been identified, including oncogenic alterations in PIK3CA, but the main response and resistance pathways are still unknown. Here we explored the transcriptomic landscape and response to the PIK3CA inhibitor taselisib and endocrine therapy in relation to PIK3CA mutations and treatment in the LORELEI trial (NCT02273973). LORELEI enrolled postmenopausal patients with HR-positive/HER2-negative early BC. Neoadjuvant therapy was given for 16 weeks. RNA sequencing (RNAseq) was performed on baseline tumor biopsies. Gene set and cell type enrichment analyses were performed using fgsea and xCell. Intrinsic subtypes by AIMS were calculated. PIK3CA status was assessed using a ISO15189-validated assay. Overall response rate by centrally assessed breast MRI classified tumors as responders (complete or partial response) and non-responders. RNAseq data were generated for 187 patients (56% of the entire population enrolled in the trial). In total, 78% had T2, 67% N0 and 63% grade 2 tumors, and 64% had invasive ductal carcinoma. There were 81 patients with PIK3CA mutant (MT) and 106 patients with PIK3CA wild-type (WT) tumors, with MT tumors enriched in Luminal A subtypes compared to WT tumors (Fisher’s test, p<0.01). We observed an enrichment of the epithelial mesenchymal transition gene set and the hematopoietic stem cell type in MT tumors, while WT tumors were enriched in proliferation and immune related gene sets. Among the 187 tumors, 77 (41%) were classified as responders and 110 (59%) as non-responders. No difference in PIK3CA mutation-associated gene signature was observed between the two groups. Comparing responders and non-responders with MT tumor indicated no statistically significant difference between intrinsic subtypes. Non-responder PIK3CA MT tumors in the taselisib arm showed enrichment of interferon alpha response and natural killer T cells. These preliminary results show relevant differences between PIK3CA MT and WT tumors. Non-responders with PIK3CA MT tumors showed enrichment of immune related signaling in the taselisib arm. Further analyses will be presented.
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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) | 0.000 | 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 | 0.000 | 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".