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Role of Genomic Instability in Immunotherapy with Checkpoint Inhibitors
George Yaghmour1, Manjari Pandey2, Catherine Ireland3
1Department of Hematology/Oncology, The West Cancer Center, The University of Tennessee Health Science Center, Memphis, TN, U.S.A. gyaghmour@westclinic.com.
Aim:
We evaluated whether tumor genome sequencing to detect the number and type of alterations could be used as a valuable biomarker for judging the potential utility of immune checkpoint inhibitors in patients with advanced cancers.
Materials And Methods:
We identified patients with solid tumors who were treated with checkpoint inibitors and had received commercially available next generation sequencing (NGS). Tumors profiled by Caris Life Sciences, Foundation Medicine and Guardant360 between 2013 and 2015. Patients were divided into 5 quintiles based on mutational load (pathogenic mutations plus variants of undetermined significance).
Results:
Fifty patients with solid tumors on immunotherapy that had NGS reports available were identified. Top quintile patients had more genomic alterations (median=16.5) than the others (median=2) and had more pathogenic mutations in cell-cycle regulatory genes (100% versus 48%). The overall survival (OS) was significantly superior for patients in the top quintile (722 days) versus the others (432 days). We found no significant difference in progression-free survival (PFS) between the two groups. The objective response rate was numerically higher for the top quintile (50%) vs. others (20%). Programmed cell death protein 1 (PD1) and programmed death-ligand 1 (PDL1) status by immunohistochemistry was not associated with outcomes.
Conclusion:
The use of immune checkpoint blockade in tumors with higher mutational load was associated with improved OS. Our results suggest that the evaluation of tumor genomes may be predictive of immunotherapy benefit.
Insights
Tumor genome sequencing can identify patients likely to benefit from immune checkpoint inhibitors. Higher tumor mutational load predicts improved overall survival in advanced cancer patients receiving immunotherapy.
Area of Science:
- Oncology
- Genomics
- Immunotherapy
Background:
- Immune checkpoint inhibitors (ICIs) have revolutionized cancer treatment.
- Predictive biomarkers are crucial for optimizing ICI therapy efficacy.
- Tumor mutational burden (TMB) is an emerging biomarker for ICI response.
Purpose of the Study:
- To evaluate tumor genome sequencing for detecting alterations as a biomarker for ICI utility.
- To assess the relationship between mutational load and clinical outcomes in advanced cancer patients treated with ICIs.
Main Methods:
- Retrospective analysis of 50 advanced cancer patients treated with ICIs.
- Next-generation sequencing (NGS) data from commercial platforms (Caris, Foundation Medicine, Guardant360).
- Patients stratified into quintiles based on mutational load (pathogenic mutations + variants of undetermined significance).
Main Results:
- Patients in the top quintile of mutational load had significantly more genomic alterations (median 16.5 vs 2).
- Top quintile patients showed superior overall survival (OS) (722 vs 432 days).
- No significant difference in progression-free survival (PFS); numerically higher objective response rate (50% vs 20%) in the top quintile.
Conclusions:
- Higher tumor mutational load, identified via genome sequencing, is associated with improved OS in patients receiving ICIs.
- Tumor genome evaluation may serve as a predictive biomarker for immunotherapy benefit.
- Standard IHC markers for PD1/PDL1 were not associated with outcomes in this cohort.
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