क्लिनिकल और सेलुलर इम्यूनोलॉजी जर्नल

क्लिनिकल और सेलुलर इम्यूनोलॉजी जर्नल
खुला एक्सेस

आईएसएसएन: 2155-9899

अमूर्त

Cancer Neoantigens: A Promising Source of Immunogens for Cancer Immunotherapy

Ayumu Ito, Shigehisa Kitano, Yongji Kim, Moeko Inoue, Masanori Fuse, Kohei Tada, and Kiyoshi Yoshimura

Recent progress in cancer immunotherapy has been remarkable, especially the clinical development of immune checkpoint inhibitors, such as anti-CTLA-4 and anti-PD-1 antibodies. The success of these agents has revealed the importance of anti-tumor immune activities in curing cancers.

Cancer peptide vaccines constitute another approach to eliciting and boosting anti-tumor immune responses. While conventional cancer vaccines have had limited clinical efficacy, targeting mainly tumor-associated selfantigens, a novel approach is now being explored to target tumor-specific antigens generated from gene mutations occurring in tumor cells during neoplastic transformation. Theoretically, immune responses to these so-called “cancer neoantigens” are not attenuated by host central tolerance in the thymus and do not trigger autoimmune reactions. Despite these theoretical considerations, until recently there were major technical difficulties in applying neoantigen-based cancer vaccines to bedside practice, because the mutations in each tumor are so numerous and which one/subset of neoantigens would be immunogenic enough to eliminate the tumor is uncertain. Recent developments in genomics and bioinformatics, including massively parallel sequencing (MPS) and epitope prediction algorithms, have provided a major breakthrough, enabling more comprehensive and efficient identification of target antigens. Although further refinements are needed for actual bedside application, the preclinical and clinical evidence for the effectiveness of targeting cancer neoantigens continues to accumulate.

In this review, we discuss the current status and future challenges of developing neoantigen-based personalized immunotherapy.

अस्वीकरण: इस सार का अनुवाद कृत्रिम बुद्धिमत्ता उपकरणों का उपयोग करके किया गया था और अभी तक इसकी समीक्षा या सत्यापन नहीं किया गया है।
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