Literature DB >> 32338212

Integrating Bioinformatics Strategies in Cancer Immunotherapy: Current and Future Perspectives.

Houda N Washah1, Elliasu Y Salifu1, Opeyemi Soremekun1, Ahmed A Elrashedy1, Geraldene Munsamy1, Fisayo A Olotu1, Mahmoud E S Soliman1.   

Abstract

For the past few decades, the mechanisms of immune responses to cancer have been exploited extensively and significant attention has been given into utilizing the therapeutic potential of the immune system. Cancer immunotherapy has been established as a promising innovative treatment for many forms of cancer. Immunotherapy has gained its prominence through various strategies, including cancer vaccines, monoclonal antibodies (mAbs), adoptive T cell cancer therapy, and immune checkpoint therapy. However, the full potential of cancer immunotherapy is yet to be attained. Recent studies have identified the use of bioinformatics tools as a viable option to help transform the treatment paradigm of several tumors by providing a therapeutically efficient method of cataloging, predicting and selecting immunotherapeutic targets, which are known bottlenecks in the application of immunotherapy. Herein, we gave an insightful overview of the types of immunotherapy techniques used currently, their mechanisms of action, and discussed some bioinformatics tools and databases applied in the immunotherapy of cancer. This review also provides some future perspectives in the use of bioinformatics tools for immunotherapy. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.net.

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Keywords:  Cancer immunotherapy; bioinformatics; immune system; immunotherapeutic targets; monoclonal antibody; therapeutic strategies

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Year:  2020        PMID: 32338212     DOI: 10.2174/1386207323666200427113734

Source DB:  PubMed          Journal:  Comb Chem High Throughput Screen        ISSN: 1386-2073            Impact factor:   1.339


  2 in total

1.  BRCA1-Associated Protein Is a Potential Prognostic Biomarker and Is Correlated With Immune Infiltration in Liver Hepatocellular Carcinoma: A Pan-Cancer Analysis.

Authors:  Qiang Ju; Xin-Mei Li; Heng Zhang; Yan-Jie Zhao
Journal:  Front Mol Biosci       Date:  2020-11-02

2.  Analysis of the key prognostic genes and potential traditional Chinese medicine therapeutic targets in glioblastoma based on bioinformatics and network pharmacology methods.

Authors:  Zhiyu Xia; Peng Gao; Yu Chen; Lei Shu; Lei Ye; Hongwei Cheng; Xingliang Dai; Yangchun Hu; Zhongyong Wang
Journal:  Transl Cancer Res       Date:  2022-05       Impact factor: 0.496

  2 in total

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