Combinatory analysis of immune cell subsets and tumor-specific genetic variants predict clinical response to PD-1 blockade in patients with non-small cell lung cancer.

Dutta N, Rohlin A, Eklund EA, Magnusson MK, Nilsson F, Aky├╝rek LM, Torstensson P, Sayin VI, Lundgren A, Hallqvist A, Raghavan S

Front Oncol 12 (-) 1073457 [2023-02-09; online 2023-02-09]

Immunotherapy by blocking programmed death protein-1 (PD-1) or programmed death protein-ligand1 (PD-L1) with antibodies (PD-1 blockade) has revolutionized treatment options for patients with non-small cell lung cancer (NSCLC). However, the benefit of immunotherapy is limited to a subset of patients. This study aimed to investigate the value of combining immune and genetic variables analyzed within 3-4 weeks after the start of PD-1 blockade therapy to predict long-term clinical response. Blood collected from patients with NSCLC were analyzed for changes in the frequency and concentration of immune cells using a clinical flow cytometry assay. Next-generation sequencing (NGS) was performed on DNA extracted from archival tumor biopsies of the same patients. Patients were categorized as clinical responders or non-responders based on the 9 months' assessment after the start of therapy. We report a significant increase in the post-treatment frequency of activated effector memory CD4+ and CD8+ T-cells compared with pre-treatment levels in the blood. Baseline frequencies of B cells but not NK cells, T cells, or regulatory T cells were associated with the clinical response to PD-1 blockade. NGS of tumor tissues identified pathogenic or likely pathogenic mutations in tumor protein P53, Kirsten rat sarcoma virus, Kelch-like ECH-associated protein 1, neurogenic locus notch homolog protein 1, and serine/threonine kinase 11, primarily in the responder group. Finally, multivariate analysis of combined immune and genetic factors but neither alone, could discriminate between responders and non-responders. Combined analyses of select immune cell subsets and genetic mutations could predict early clinical responses to immunotherapy in patients with NSCLC and after validation, can guide clinical precision medicine efforts.

Clinical Genomics Gothenburg [Service]

PubMed 36844924

DOI 10.3389/fonc.2022.1073457

Crossref 10.3389/fonc.2022.1073457

pmc: PMC9948027


Publications 9.5.0