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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, Nikita; Rohlin, Anna; Eklund, Ella A; Magnusson, Maria K; Nilsson, Frida; Akyürek, Levent M; Torstensson, Per; Sayin, Volkan I; Lundgren, Anna; Hallqvist, Andreas; Raghavan, Sukanya.
Afiliação
  • Dutta N; Department of Microbiology and Immunology, Institute of Biomedicine, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden.
  • Rohlin A; Department of Clinical Genetics and Genomics, Sahlgrenska University Hospital, Gothenburg, Sweden.
  • Eklund EA; Department of Laboratory Medicine, Institute of Biomedicine, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden.
  • Magnusson MK; Department of Surgery, Institute of Clinical Sciences, Sahlgrenska Center for Cancer Research, University of Gothenburg, Gothenburg, Sweden.
  • Nilsson F; Wallenberg Center for Molecular and Translational Medicine, University of Gothenburg, Gothenburg, Sweden.
  • Akyürek LM; Department of Oncology, Sahlgrenska University Hospital, Gothenburg, Sweden.
  • Torstensson P; Department of Microbiology and Immunology, Institute of Biomedicine, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden.
  • Sayin VI; Department of Microbiology and Immunology, Institute of Biomedicine, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden.
  • Lundgren A; Department of Clinical Pathology, Institute of Biomedicine, Sahlgrenska University Hospital, Gothenburg, Sweden.
  • Hallqvist A; Department of Pulmonary Medicine, Skaraborg hospital, Skövde, Sweden.
  • Raghavan S; Department of Surgery, Institute of Clinical Sciences, Sahlgrenska Center for Cancer Research, University of Gothenburg, Gothenburg, Sweden.
Front Oncol ; 12: 1073457, 2022.
Article em En | MEDLINE | ID: mdl-36844924
ABSTRACT

Objectives:

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. Materials and

methodology:

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.

Results:

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.

Conclusion:

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.
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Texto completo: 1 Base de dados: MEDLINE Tipo de estudo: Prognostic_studies / Risk_factors_studies Idioma: En Ano de publicação: 2022 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Tipo de estudo: Prognostic_studies / Risk_factors_studies Idioma: En Ano de publicação: 2022 Tipo de documento: Article