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A Syngeneic Mouse Model of Metastatic Renal Cell Carcinoma for Quantitative and Longitudinal Assessment of Preclinical Therapies
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A Syngeneic Mouse Model of Metastatic Renal Cell Carcinoma for Quantitative and Longitudinal Assessment of Preclinical Therapies

Published on: April 12, 2017

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Tumor microenvironment and clinical efficacy of first line immunotherapy-based combinations in metastatic renal cell

Enrico Sammarco1, Martina Rossetti2, Alessia Salfi3

  • 1Medical Oncology Unit, Livorno Hospital, Azienda Toscana Nord Ovest, Livorno, Italy.

Medical Oncology (Northwood, London, England)
|May 13, 2024
PubMed

Insights

Tumor microenvironment (TME) impacts response to immune checkpoint inhibitors (ICI) in advanced renal cell carcinoma (RCC). High CD163+ macrophage infiltration correlates with poorer survival, suggesting a predictive biomarker for first-line ICI therapy.

Area of Science:

  • Oncology
  • Immunology
  • Pathology

Background:

  • The tumor microenvironment (TME) plays a critical role in modulating responses to immune checkpoint inhibitor (ICI) therapy.
  • Understanding TME characteristics in advanced renal cell carcinoma (RCC) is crucial for predicting clinical outcomes with first-line ICI treatment.
  • Immunohistochemistry (IHC) offers a method to identify potential biomarkers within the TME related to immune cell populations and checkpoint expression.

Purpose of the Study:

  • To retrospectively analyze the TME composition in advanced RCC patients treated with first-line ICI-based therapy.
  • To investigate the correlation between specific TME markers identified by IHC and treatment efficacy, including response rates, progression-free survival (PFS), and overall survival (OS).
  • To explore the potential of TME characteristics as predictive biomarkers for ICI treatment outcomes in RCC.

Main Methods:

  • Retrospective analysis of TME markers using immunohistochemistry (IHC) in tumor samples from 28 advanced RCC patients.
  • Assessment of immune cell populations including CD80+, CD163+, CD4+, and CD8+ cells, and PD-L1 Combined Positive Score (CPS).
  • Correlation of IHC findings with clinical response, PFS, and OS following first-line ICI-based treatment.

Main Results:

  • Clear cell RCC components showed higher CD80+ and CD163+ cell counts compared to non-clear cell types.
  • Metastatic disease at diagnosis was associated with increased CD163+ cell expression; sarcomatoid features correlated with higher CD4+ counts and CD4+/CD8+ ratio.
  • Patients achieving partial/complete response had lower CD163+ expression. Lower CD163+ expression correlated with improved PFS and OS. PD-L1 CPS-negative status was linked to longer OS.

Conclusions:

  • High infiltration of CD163+ macrophages, indicative of an M2-like phenotype, may identify a subset of advanced RCC patients with poor outcomes on first-line ICI therapy.
  • Specific TME features, particularly CD163+ macrophage levels, show potential as predictive biomarkers for ICI treatment efficacy in advanced RCC.
  • Further validation is warranted to integrate TME analysis into clinical decision-making for first-line ICI treatment selection in RCC.
Keywords:
CD163Immune checkpoint inhibitorRenal cell carcinomaTumor microenvironment

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