Tumor Microenvironment Features as Predictive Biomarkers of Response to Immune Checkpoint Inhibitors (ICI) in Metastatic Clear Cell Renal Cell Carcinoma (mccRCC)

Abstract

Renal cell carcinoma (RCC) is the seventh most frequently diagnosed malignancy with an increasing incidence in developed countries. Despite a greater understanding of the cancer biology, which has led to an increase of therapeutic options, metastatic clear cell renal cell carcinoma (mccRCC) still have a poor prognosis with a median five-years survival rate lower than 10%. The standard of care for mccRCC has changed dramatically over the past decades with the emergence of new treatments: anti-VEGFR tyrosine kinase inhibitors, mTOR Inhibitors and immune checkpoint inhibitors (ICI) such as anti-Programmed cell-Death 1 (PD-1) and anti-anti-Programmed Death Ligand-1 (PD-L1) used as monotherapy or as a combination with anti CTLA-4 or anti angiogenic therapies. In the face of these rising therapeutic options, the question of the therapeutic sequences is crucial. Predictive biomarkers are urgently required to provide a personalized treatment for each patient. Disappointingly, the usual ICI biomarkers, PD-L1 expression and Tumor Mutational Burden, approved in melanoma or non-small cell lung cancer (NSCLC) have failed to distinguish good and poor mccRCC responders to ICI. The tumor microenvironment is known to be involved in ICI response. Innovative technologies can be used to explore the immune contexture of tumors and to find predictive and prognostic biomarkers. Recent comprehensive molecular characterization of RCC has led to the development of robust genomic signatures, which could be used as predictive biomarkers. This review will provide an overview of the components of the RCC tumor microenvironment and discuss their role in disease progression and resistance to ICI. We will then highlight the current and future ICI predictive biomarkers assessed in mccRCC with a major focus on immunohistochemistry markers and genomic signatures.

Soluble PD-L1 Is an Independent Prognostic Factor in Clear Cell Renal Cell Carcinoma

“…However, what is even more interesting in our experience is that sPDL-1 levels appear to represent a good surrogate of a response criteria to systemic therapy administered in metastatic CCRCC. In this context, there are many limitations to consider when deciding to treat CCRCC patients with immune checkpoint inhibitors based on the immunohistochemical detection of PD-1/PD-L1 positivity alone [11,27], while the search of markers to anticipate the response to immunotherapy continues [42][43][44]. A new trial (UMIN000027873) has been recently launched to evaluate the therapeutic effect of nivolumamb as a second-line therapy for advanced CCRCC based on the concentrations of serum sPD-L1.…”

Development of a novel gene signature to predict prognosis and response to PD-1 blockade in clear cell renal cell carcinoma

“…[5][6][7] Tumor immune microenvironment (TIME) which comprises infiltrated immune cells and immunomodulatory molecules has been revealed highly correlated with cancer progression and ICIs response. [8][9][10] Thus, constructing a prognostic model with the power of evaluating TIME has a great potentiality of predicting clinical outcomes and immunotherapy response in ccRCC.…”

Eosinophil counts as a relevant prognostic marker for response to nivolumab in the management of renal cell carcinoma: a retrospective study

“…This revealed that PD‐L1 expression was prognostic but not predictive of response to nivolumab. On‐going studies are being carried out to find and select predictive markers, such as tumor mutational burden, 18,19 tumor‐infiltrating lymphocytes 20 or gene expression signatures 21‐25 but due to the complexity of clinical routines, serum markers are readily available for the analysis are currently being investigated. One study conducted recently suggested a rise in eosinophils as a predictive biomarker for ORR, OS, and PFS in metastatic RCC treated with nivolumab 26 …”