Abstract A02: Biomarkers of drug response to buparlisib: Results of next-generation sequencing in a phase II trial of advanced endometrial carcinoma
Bibliographic record
Abstract
Abstract Background: Genetic alterations in the phosphatidylinositol 3-kinase (PI3K) pathway are frequent in endometrial carcinoma (EC; 59% PIK3CA and 66% PTEN alterations; Kandoth C et al., Nature 2013), thus providing a rationale for testing PI3K inhibitors in this tumor type. A Phase II, single-arm clinical trial of buparlisib, an oral pan-PI3K inhibitor that inhibits all four class I PI3K isoforms (α, β, δ, γ), as second-line therapy, was conducted in advanced EC (N=70). All patients (pts) received buparlisib 100 mg/day until disease progression or discontinuation due to an adverse event. The primary objective was objective response rate (RECIST v1.1) in pts with PI3K-activated tumors (PIK3CA and/or PTEN alteration) or in all pts. The activity of single-agent buparlisib was marginal and PI3K pathway activation was not associated with a better outcome in this pt population (Teneriello MG et al., ICACT 2013). Retrospective molecular characterization was undertaken to assess a potential alternate contribution to PI3K pathway activation in EC and the impact on response to treatment. Methods: Next-generation sequencing data were generated for 51 pts (serous n=17, endometrioid n=28, unknown n=6) and targeted coding regions of approximately 400 genes. Using standard bioinformatics tools, short nucleotide variants (SNVs) were called. To generate signatures of PI3K pathway activation, data from the TCGA endometrial cohort (Kandoth C et al., Nature 2013) were first leveraged. Levels of pAKT (pT308 and pS473) and pS6 (pS235 and pS240), proxies for PI3K pathway activation, were modeled using SNVs in the TCGA endometrial cohort. Specifically, elastic net models predicting pAKT and pS6 were optimized using somatic SNVs for endometrioid (6-gene model) and serous (3-gene model) subtypes separately. The TCGA models were then used to create pathway activation scores for each pt based on their molecular profile. Results: No significant relationships were found for pts with the serous subtype, hence the results focus on the endometrioid subtype. Subgroup analysis was performed to assess trends in progression-free survival (PFS) using Cox proportional hazards regression. Pts with the lowest PI3K pathway activation scores, based on the pAKT TCGA model, including pts with PTEN wildtype (n=5), trended towards a lower risk of PFS event compared with pts with moderate or high activation (n=23). In addition, pts with the highest pathway activation scores, based on the pS6 TCGA model, including pts with alterations in mTOR (n=5), trended towards a higher risk of PFS event compared with pts with moderate or low activation (n=23). When combining the two signatures, pts with high pS6 activation (n=5) had a higher risk of PFS event followed by pts with low pS6 and high pAKT scores (n=19) compared with pts with low pS6 and low pAKT scores (n=4). PIK3CA mutations were unrelated to pAKT in the TCGA model for the endometrioid subtype, but PIK3CA-mutated tumors in the TCGA model had slightly higher levels of pS6. Conclusion: In both models, pts with the lowest levels of PI3K pathway activation trended towards a lower risk of PFS event compared with pts with moderate or high levels of PI3K activation. A possible explanation is that the high levels of PI3K pathway activation observed in EC may represent a challenge for single-agent inhibition. Alternatively, for this single-arm study in EC, we can only elucidate the prognostic value of the biomarker and not the contribution of the treatment per se. Further validation with larger sample sizes is warranted to support this hypothesis further. Citation Format: Nadia Solovieff, Angad Pal Singh, Hans Bitter, Markus Riester, Michael Teneriello, Amit Oza, Bradley Monk, Douglas Robinson, Lucia Trandafir, Cristian Massacesi, Emmanuelle di Tomaso, R. Wendel Naumann. Biomarkers of drug response to buparlisib: Results of next-generation sequencing in a phase II trial of advanced endometrial carcinoma. [abstract]. In: Proceedings of the AACR Special Conference: Targeting the PI3K-mTOR Network in Cancer; Sep 14-17, 2014; Philadelphia, PA. Philadelphia (PA): AACR; Mol Cancer Ther 2015;14(7 Suppl):Abstract nr A02.
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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 | 0.003 | 0.004 |
| 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".