Pan-Tumor Genomic Biomarkers for PD-1 Based Immunotherapy
Ontology highlight
ABSTRACT: Tumor mutation burden (TMB) and a T-cell-inflamed gene expression profile (GEP) independently predict clinical outcome in pembrolizumab-treated patients in 22 indications and stratify distinct targets of resistance biology.
REPOSITORIES: dbGaP
Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| GapExchange_phs001572.v1.p1.xml | Xml | |||
| dbGaPEx2.1.5.xsd | Other | |||
| Study_Report.phs001572.PD1.v1.p1.MULTI.pdf | ||||
| manifest_phs001572.PD1.v1.p1.c3.DS-CA-IRB.pdf | ||||
| datadict_v2.xsl | Other |
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Project description:Programmed cell death protein-1 (PD-1) and programmed cell death ligand-1 (PD-L1) checkpoint blockade immunotherapy elicits durable antitumor effects in multiple cancers, yet not all patients respond. We report the evaluation of >300 patient samples across 22 tumor types from four KEYNOTE clinical trials. Tumor mutational burden (TMB) and a T cell-inflamed gene expression profile (GEP) exhibited joint predictive utility in identifying responders and nonresponders to the PD-1 antibody pembrolizumab. TMB and GEP were independently predictive of response and demonstrated low correlation, suggesting that they capture distinct features of neoantigenicity and T cell activation. Analysis of The Cancer Genome Atlas database showed TMB and GEP to have a low correlation, and analysis by joint stratification revealed biomarker-defined patterns of targetable-resistance biology. These biomarkers may have utility in clinical trial design by guiding rational selection of anti-PD-1 monotherapy and combination immunotherapy regimens.
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Project description:In recent years, immunotherapies targeting programmed death-1 (PD-1)/programmed death ligand 1 (PD-L1) have provided great hopes for patients with cancer. A successful anti-PD-1/PD-L1 therapy includes not only the elimination of immunosuppressive tumor cells but also the rejuvenation of exhausted T cells. Nevertheless, the efficacy of therapy is still low, so that biomarker-driven therapy has attracted more and more attention to identify patients who are likely to benefit from therapy and to reduce unnecessary disease progression. While many studies have focused on characteristics of tumor biopsies, biomarkers linked to T cell exhaustion and rejuvenation have just become new hot spots in drug response studies. However, no biomarker is perfect in drug response prediction currently, so there is an urgent need for other biomarkers to compensate for the deficiency. In this review, we summarize some approved and candidate biomarkers predictive of drug response before and during PD-1/PD-L1 blockade, including those characterizing responsive or suppressive tumor cells and those evaluating the T cell rejuvenation. Overall, we set up a comprehensive network of biomarkers of tumor characteristics and T cell rejuvenation, predicting drug response before and during anti-PD-1/PD-L1 therapies.
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Project description:Pan-tumor genomic biomarkers for personalization of PD-1 checkpoint blockade based immunotherapy
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