
Faculty, Staff and Student Publications
Publication Date
2-17-2025
Journal
Clinical Cancer Research
Abstract
Purpose: Mismatch repair-deficient (dMMR) tumors have demonstrated favorable responses to immune checkpoint inhibition targeting PD-1. However, more in-depth identification of predictors of response could further refine patient selection for immunotherapy treatment.
Patients and methods: We undertook integrated evaluation performed on samples collected from 28 of 42 patients enrolled on the NCI-Molecular Analysis for Therapy Choice arm Z1D trial that evaluated PD-1 inhibition treatment with nivolumab in patients with noncolorectal dMMR tumors. Genomic analyses were performed using next-generation sequencing (NGS), whole-exome sequencing, and RNA sequencing and supplemented by multiplex immunofluorescence performed on tissue samples.
Results: In this dMMR population, more extensive alterations of microsatellites as assessed by measures of NGS were associated with clinical benefit and tumor mutational burden. RNA sequencing further revealed associations between clinical benefit and immune infiltration index. Gene sets enriched in patients with clinical benefit included IFN signaling, antigen processing, and PI3K-AKT-mTOR signaling, whereas hedgehog signaling was found to be enriched in subjects lacking clinical benefit.
Conclusions: These genomic data highlight the importance of immune infiltration and antigen presentation in dMMR tumors that respond to immune checkpoint blockade. In addition, they suggest that, even within a dMMR population, NGS-based measures of microsatellite instability could serve as biomarkers of immunotherapy response.
Keywords
Humans, Nivolumab, Microsatellite Instability, High-Throughput Nucleotide Sequencing, DNA Mismatch Repair, Female, Male, Follow-Up Studies, Immune Checkpoint Inhibitors, Middle Aged, Biomarkers, Tumor, Aged, Neoplasms, Adult, Treatment Outcome
DOI
10.1158/1078-0432.CCR-24-0427
PMID
39670863
PMCID
PMC11831103
PubMedCentral® Posted Date
12-13-2024
PubMedCentral® Full Text Version
Post-print
Published Open-Access
yes
Included in
Bioinformatics Commons, Biomedical Informatics Commons, Genetic Phenomena Commons, Medical Genetics Commons, Oncology Commons