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The Current Landscape of Antibody-based Therapies in Solid Malignancies

期刊

THERANOSTICS
卷 11, 期 3, 页码 1493-1512

出版社

IVYSPRING INT PUBL
DOI: 10.7150/thno.52614

关键词

Antibodies; cancer; therapy; mechanisms of action; challenges

资金

  1. National Institutes of Health [R01 CA195586, R01 CA247471, 1U01_CA213862, R44 DK117472, P01 CA217798]

向作者/读者索取更多资源

Monoclonal antibodies (mAbs) have revolutionized cancer therapy over the past three decades, but their efficacy remains limited by moderate response rates and resistance emergence. Resistance to mAbs is not only caused by tumor antigen heterogeneity, but also by the tumor microenvironment (TME) including inefficient delivery to the tumor, altered effector functions, and diversity in Fc-gamma receptor expression. Diagnostic and prognostic biomarkers play a crucial role in predicting response to mAb-based therapies.
Over the past three decades, monoclonal antibodies (mAbs) have revolutionized the landscape of cancer therapy. Still, this benefit remains restricted to a small proportion of patients due to moderate response rates and resistance emergence. The field has started to embrace better mAb-based formats with advancements in molecular and protein engineering technologies. The development of a therapeutic mAb with long-lasting clinical impact demands a prodigious understanding of target antigen, effective mechanism of action, gene engineering technologies, complex interplay between tumor and host immune system, and biomarkers for prediction of clinical response. This review discusses the various approaches used by mAbs for tumor targeting and mechanisms of therapeutic resistance that is not only caused by the heterogeneity of tumor antigen, but also the resistance imposed by tumor microenvironment (TME), including inefficient delivery to the tumor, alteration of effector functions in the TME, and Fc-gamma receptor expression diversity and polymorphism. Further, this article provides a perspective on potential strategies to overcome these barriers and how diagnostic and prognostic biomarkers are being used in predicting response to mAb-based therapies. Overall, understanding these interdependent parameters can improve the current mAb-based formulations and develop novel mAb-based therapeutics for achieving durable clinical outcomes in a large subset of patients.

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