DOI: 10.1007/s00259-017-3802-5Pages: 2310-2325

Clinical characteristics of patient selection and imaging predictors of outcome in solid tumors treated with checkpoint-inhibitors

1. Humanitas Clinical and Research Hospital, Medical Oncology

2. Humanitas Clinical and Research Hospital, Nuclear Medicine

3. Humanitas Clinical and Research Hospital, Immunology and Inflammation

4. Seconda Università di Napoli, Nuclear Medicine

5. Humanitas Cancer Center, Humanitas Clinical and Research Hospital, Nuclear Medicine

Correspondence to:
Egesta Lopci
Tel: +39 02 82247542
Email: egesta.lopci@gmail.com

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Abstract

The rapidly evolving knowledge on tumor immunology and the continuous implementation of immunotherapy in cancer have recently led to the FDA and EMA approval of several checkpoint inhibitors as immunotherapic agents in clinical practice. Anti-CTLA-4, anti-PD-1, and anti-PDL-1 antibodies are becoming standard of care in advanced melanoma, as well as in relapsed or metastatic lung and kidney cancer, demonstrating higher and longer response compared to standard chemotherapy. These encouraging results have fostered the evaluation of these antibodies either alone or in combination with other therapies in several dozen clinical trials for the treatment of multiple tumor types. However, not all patients respond to immune checkpoint inhibitors, hence, specific biomarkers are necessary to guide and monitor therapy. The utility of PD-L1 expression as a biomarker has varied in different clinical trials, but, to date, no consensus has been reached on whether PD-L1 expression is an ideal marker for response and patient selection; approximately 20–25% of patients will respond to immunotherapy with checkpoint inhibitors despite a negative PD-L1 staining. On the other hand, major issues concern the evaluation of objective response in patients treated with immunotherapy. Pure morphological criteria as commonly used in solid tumors (i.e. RECIST) are not sufficient because change in size is not an early and reliable marker of tumor response to biological therapies. Thus, the scientific community has required a continuous adaptation of immune-related response criteria (irRC) to overcome the problem. In this context, metabolic information and antibody-based imaging with positron emission tomography (PET) have been investigated, providing a powerful approach for an optimal stratification of patients at staging and during the evaluation of the response to therapy. In the present review we provide an overview on the clinical characteristics of patient selection when using imaging predictors of outcome in solid tumors treated with checkpoint-inhibitors.

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  • Accepted: Aug 4, 2017
  • Online: Aug 16, 2017

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