Immune correlates of outcome in patients with leiomyosarcoma (LMS) treated with durvalumab plus olaparib or cediranib: Transcriptome analysis from the DAPPER study.
Bibliographic record
Abstract
11567 Background: Immune checkpoint blockade (ICB) as monotherapy has not shown clinical benefit in non-inflamed (cold) tumors such as LMS. Combining ICB with angiogenesis, or poly-ADP ribose polymerase (PARP) inhibitors may increase tumor immunogenicity by altering the immune cell composition of the tumor microenvironment (TME). In the DAPPER trial [NCT03851614], advanced LMS pts were randomized to receive ICB (Durvalumab 1500mg IV q4w) with either angiogenesis- (Cediranib 20mg qd PO on 5 days/week) or PARP inhibition (Olaparib 300mg bid PO) until unacceptable toxicity or disease progression (Ayodele et al, J Clin Oncol, 2021). Here, we present the results of transcriptomic and immune biomarker analyses of patients (pts) in the whole cohort. Methods: Radiologic responses were assessed using RECISTv1.1 and survival analysis performed by Kaplan-Meier method. Transcriptome analysis by RNAseq was performed on fresh tumor biopsies obtained from all pts at screening. Relative fractions of 22 immune cell subsets in the TME were inferred from gene-expression profiles using CIBERSORT v1.06. Gene set variation analysis (GVSA) to identify transcriptomic signatures associated with progression-free (PFS) or overall survival (OS) benefit was performed using GSVA R package v1.42. For comparison with an independent cohort, GVSA was also performed using transcriptome data from LMS pts (n = 104) in the cancer genome atlas (TCGA) dataset. Results: Among 28 response-evaluable pts, 1 (3.6%) had partial response; 10 (35.7%) had stable disease (SD); and 17 (60.7%) had progressive disease. Median PFS and OS were 2.8 months (95% CI, 2.8 – 5.4) and 14.6 months (95% CI 10.7 – NR), respectively. RNAseq data of adequate quality was available for 17 pts. Using the median CIBERSORT score as cut-off, pts with high M1 macrophage levels at baseline had significantly longer OS (p = 0.0019). High M1/M2 macrophage ratio score was also associated with longer OS (p = 0.05). GVSA identified 7 immune- and angiogenesis-related signatures that were associated with significantly longer OS. After false discovery rate correction, 1 signature comprising genes reflective of high overall B-cell activity remained significant. No transcriptomic signatures were associated with OS in the TCGA LMS cohort where pts did not receive ICB. Conclusions: Transcriptomic analysis shows that macrophage presence in the TME is associated with longer OS. Association of the B-cell activity signature with longer OS in LMS pts on the DAPPER trial, but not in the ICB treatment-naïve TCGA cohort suggests that high B-cell activity may identify pts who are more likely to have favorable outcomes with ICB and supports previous reports in sarcoma (Petitprez et al, Nature, 2020). Our results support ongoing further evaluation and integration of these biomarkers in LMS. Clinical trial information: NCT03851614 .
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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 | 0.000 |
| 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 | 0.000 |
| 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".