Relevance of Fc Gamma Receptor Polymorphisms in Cancer Therapy With Monoclonal Antibodies

Abstract

Therapeutic monoclonal antibodies (mAbs), including immune checkpoint inhibitors (ICIs), are an important breakthrough for the treatment of cancer and have dramatically changed clinical outcomes in a wide variety of tumours. However, clinical response varies among patients receiving mAb-based treatment, so it is necessary to search for predictive biomarkers of response to identify the patients who will derive the greatest therapeutic benefit. The interaction of mAbs with Fc gamma receptors (FcγR) expressed by innate immune cells is essential for antibody-dependent cellular cytotoxicity (ADCC) and this binding is often critical for their in vivo efficacy. FcγRIIa (H131R) and FcγRIIIa (V158F) polymorphisms have been reported to correlate with response to therapeutic mAbs. These polymorphisms play a major role in the affinity of mAb receptors and, therefore, can exert a profound impact on antitumor response in these therapies. Furthermore, recent reports have revealed potential mechanisms of ICIs to modulate myeloid subset composition within the tumour microenvironment through FcγR-binding, optimizing their anti-tumour activity. The purpose of this review is to highlight the clinical contribution of FcγR polymorphisms to predict response to mAbs in cancer patients.

Neutrophils as immune effector cells in antibody therapy in cancer

“…It has been demonstrated that certain polymorphisms in FcγRs may affect the clinical outcome of antibody therapy in cancer patients. 218 The FCGR2A-H131 and FCGR3A-V158 alleles, with relatively high-affinity binding of IgG1 antibodies, appear to be correlated with progressive free survival of rituximab-treated follicular lymphoma patients, 219 cetuximabtreated colorectal cancer patients, [220][221][222] and trastuzumab-treated breast cancer patients. 223 The latter is in line with the involvement of both myeloid and possibly also NK immune effector cells in mAbmediated tumor cell destruction.…”

“…Despite the great improvements in cancer treatment, still many patients do not benefit from antibody treatment. It has been demonstrated that certain polymorphisms in FcγRs may affect the clinical outcome of antibody therapy in cancer patients 218 . The FCGR2A‐H131 and FCGR3A‐V158 alleles, with relatively high‐affinity binding of IgG1 antibodies, appear to be correlated with progressive free survival of rituximab‐treated follicular lymphoma patients, 219 cetuximab‐treated colorectal cancer patients, 220–222 and trastuzumab‐treated breast cancer patients 223 .…”

Targeting Innate Immunity in Glioma Therapy

“…One limitation of the monoclonal antibody approach might be mediated by the presence of Fc polymorphisms. In fact, some of these polymorphisms expressed by innate immune cells interfere with the affinity of monoclonal antibodies, influencing the response to these therapies [81].…”

Advances in artificial intelligence to predict cancer immunotherapy efficacy

“…( 51 ) suggested combining DNA and RNA sequencing, immunohistochemical staining results, demographic baseline data, medical history, and laboratory test results to analyze the information related to efficacy and break the limitation of relying only on PD-1 expression level and TMB level to predict immunotherapy response, and develop a mature model for immunotherapy response prediction for Chinese lung cancer patients. Along with PD-L1 expression, TMB, and TIL, it has been demonstrated that miRNA abnormalities ( 62 ), EGFR mutations ( 54 ), TP53 mutations ( 63 ), ALK rearrangements ( 55 ), gut microbiota ( 56 ), Fc gamma receptor (FcγR) polymorphisms ( 57 ) and serum complement levels ( 58 ) all influence immunotherapy response to some extent. It would facilitate the robustness of prediction if this information could be merged with pathological sections and imaging histology to form multi-omics integrated data.…”