Abstract CT203: Multi-omic analysis of serial biopsies to inform biomarkers of sensitivity to olaparib and durvalumab in patients with metastatic <i>BRCA</i>-wildtype triple negative breast cancer (mTNBC)
Bibliographic record
Abstract
Abstract Background: The phase 2 Adaptive Multi-Drug Treatment of Evolving Cancers (AMTEC) trial (NCT03801369) evaluated the efficacy of the combination of the PARP inhibitor Olaparib (Ola) and the PD-L1 inhibitor Durvalumab (Durva) in participants with BRCA-wildtype mTNBC. The combination was found to be effective with a median progression free survival (mPFS) of 5.5 months (AACR 2022). Here we report on updated biomarker analyses from paired biopsies (Bx) pre- and on-Ola therapy from 14 AMTEC participants. Methods: AMTEC participants undergo a pre-Ola Bx (Bx1), then one (28-day) cycle of Ola monotherapy with a repeat on-Ola Bx (Bx2) before adding Durva to Ola. Multi-omic profiling of DNA, RNA, and protein signals in Bx1 and Bx2 using Deep candidate gene sequencing, RNAseq, Nanostring Digital Spatial Profiling (DSP), and multiplex immunohistochemistry (mIHC) was correlated with clinical outcomes to identify predictors of Ola + Durva sensitivity, and adaptive resistance to PARPi therapy. Results: We identified over 30 biomarkers, with the optimal predictive value arising from Bx2. Key potential biomarkers were confirmed in an independent test set. Markers of good prognosis: • Basal Immune Activated (BLIA)/Basal Immune Suppressed (BLIS subtype) - A BLIA subtype on Bx2 was associated with a mPFS of 7.36 months compared to 1.71 months for BLIS/Luminal androgen receptor subtypes (p=0.001) • Multi-omic immune composite - A positive immune consensus signature (RNA, DSP, mIHC) on Bx2 was associated with a mPFS of 7.36 months compared to 2.29 months (p=0.005) • B cell activation signature - We developed a novel B-cell RNA activation signature that was highly predictive of response in Bx2, with mPFS of 8.54 and 1.04 months in signature-positive and signature-negative tumors, respectively (p=0.0004) Markers of poor prognosis: • AKT/MAPK pathway - AKT pathway gene mutations in Bx2 with concomitant protein phosphorylation of pathway members correlated with a shorter mPFS of 2.4 months compared to 7.13 months for no pathway mutation/activation (p=0.03). MAPK pathway protein phosphorylation in Bx2 was a negative prognostic factor, with mPFS of 2.17 months (p=0.004) • Angiogenesis - An upregulated Hallmark of Cancer angiogenesis RNA signature on Bx2 was associated with a shorter mPFS of 1.94 months compared to 7.95 months with no angiogenesis upregulation (p=0.0009) The following markers did not show significant association with survival outcomes on AMTEC: • PD-L1 positivity by IHC (defined as >1% Tumor Proportion Score, 22C3 antibody) • Tumor mutational burden • HRD, as measured by Rad51 foci or by mutations in HR pathway members Conclusions: Findings highlight the value of paired Bxs to identify predictive biomarkers of PARPi + immune checkpoint inhibitor sensitivity. The striking predictive value of the BLIA/BLIS signature warrants evaluation in a larger trial. Emerging resistance mechanisms justify AMTEC trial expansion to include PARPi + MEKi or PARPi + AKTi in biomarker selected patients, which is now in progress. Citation Format: Zahi I. Mitri, Allison L. Creason, Jayne M. Stommel, Daniel Bottomly, Jeong Youn Lim, SMMART Clinical Trials Program, Christopher L. Corless, Shannon McWeeney, Gordon B. Mills. Multi-omic analysis of serial biopsies to inform biomarkers of sensitivity to olaparib and durvalumab in patients with metastatic BRCA-wildtype triple negative breast cancer (mTNBC) [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 2 (Late-Breaking, Clinical Trial, and Invited Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(7_Suppl):Abstract nr CT203.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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 | 0.000 |
| 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".