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Tumor Characteristics and Treatment Responsiveness in Pembrolizumab-Treated Non-Small Cell Lung Carcinoma

  • 0Department of Pathology and Laboratory Medicine, Roswell Park Comprehensive Cancer Center, Buffalo, NY 14203, USA.
Cancers +

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February 24, 2024

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February 24, 2024

View abstract on PubMed

Summary

This summary is machine-generated.

Tumor characteristics like higher viable tumor cells and more tumor-infiltrating lymphocytes (TILs) predict better response to pembrolizumab in non-small cell lung cancer (NSCLC). These findings aid personalized immunotherapy strategies for NSCLC patients.

Area Of Science

  • Oncology
  • Immunotherapy
  • Pathology

Background

  • Pembrolizumab, an immune checkpoint inhibitor (ICI), is a key treatment for non-small cell lung cancer (NSCLC).
  • Predicting patient response to pembrolizumab is crucial for personalized therapy.
  • Tumor histopathologic features may correlate with treatment outcomes.

Purpose Of The Study

  • To investigate the association between pre-treatment histopathologic features and pembrolizumab response in NSCLC patients.
  • To identify unique tumor characteristics predictive of favorable outcomes.

Main Methods

  • Retrospective analysis of 84 NSCLC patients treated with pembrolizumab.
  • Evaluation of clinical data and pre-treatment histopathologic features.
  • Response assessment using Response Evaluation Criteria in Solid Tumors (RECIST).

Main Results

  • Patients with complete or partial response (responsive group) showed significantly higher overall survival.
  • Higher pre-treatment viable tumor cell content and tumor-infiltrating lymphocytes (TILs) were observed in responsive groups.
  • Lower extracellular stroma proportion was associated with better response.

Conclusions

  • Positive treatment responses to pembrolizumab in NSCLC are linked to better prognosis.
  • Viable tumor cell and tumor-infiltrating lymphocyte proportions correlate with treatment responsiveness.
  • Further prospective studies are needed to validate these histopathologic predictors.

Keywords:

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