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Updated: Nov 16, 2025
A Syngeneic Mouse Model of Metastatic Renal Cell Carcinoma for Quantitative and Longitudinal Assessment of Preclinical Therapies
Published on: April 12, 2017
Finding predictive factors for immunotherapy in metastatic renal-cell carcinoma: What are we looking for?
Annalisa Guida1, Roberto Sabbatini2, Lara Gibellini3
1Department of Biomedical, Metabolic and Neural Sciences, University of Modena and Reggio Emilia, Modena, Italy; Medical Oncology, Azienda Ospedaliera Santa Maria, Terni, Italy.
Abstract:
A major breakthrough in cancer immunotherapy was the development of monoclonal antibodies targeting inhibitory immune checkpoint proteins. This approach demonstrated significant antitumor activity and efficacy in different cancer types, including metastatic renal cell carcinoma (mRCC). In the majority of patients, this drug is able to restore the patient's tumour-specific T-cell-mediated response thus improving both overall survival and objective response rate. However, a lack of clinical response occurs in a number of patients, raising questions about how to predict and increase the number of patients who receive long-term clinical benefit from immune checkpoint therapy or not. The aim of this review is to summarize available data about immune biomarkers in patients with mRCC treated with immunotherapy.
Insights
Immune checkpoint inhibitors show promise for metastatic renal cell carcinoma (mRCC) by restoring T-cell responses. This review explores immune biomarkers to predict and enhance patient benefits from immunotherapy.
Area of Science:
- Oncology
- Immunology
- Biomarkers
Background:
- Monoclonal antibodies targeting immune checkpoint proteins represent a breakthrough in cancer immunotherapy.
- These therapies have shown significant antitumor activity and efficacy in metastatic renal cell carcinoma (mRCC).
- Immune checkpoint inhibitors restore anti-tumour T-cell responses, improving survival and response rates in many mRCC patients.
Purpose of the Study:
- To review immune biomarkers for predicting response to immunotherapy in mRCC patients.
- To identify strategies for increasing the number of patients who benefit from immune checkpoint therapy.
- To address the challenge of non-response in a subset of mRCC patients.
Main Methods:
- Literature review of studies on immune biomarkers in mRCC treated with immunotherapy.
- Synthesis of data on predictive and prognostic immune markers.
- Analysis of factors influencing clinical benefit from immune checkpoint inhibitors.
Main Results:
- Immune checkpoint inhibitors offer significant clinical benefits for a majority of mRCC patients.
- A subset of patients does not respond to current immunotherapy regimens.
- Various immune biomarkers are being investigated for their potential to predict treatment response.
Conclusions:
- Predictive immune biomarkers are crucial for optimizing immunotherapy in mRCC.
- Further research is needed to identify reliable biomarkers for patient stratification.
- Personalizing immunotherapy based on immune profiles may enhance long-term clinical benefits for mRCC patients.
