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Review
. 2024 Mar 21;25(6):3563.
doi: 10.3390/ijms25063563.

Immunotherapy and Cancer: The Multi-Omics Perspective

Clelia Donisi  1 , Andrea Pretta  1 , Valeria Pusceddu  1 , Pina Ziranu  1 , Eleonora Lai  1 , Marco Puzzoni  1 , Stefano Mariani  1 , Elena Massa  1 , Clelia Madeddu  1 , Mario Scartozzi  1
Affiliations
Review

Immunotherapy and Cancer: The Multi-Omics Perspective

Clelia Donisi et al. Int J Mol Sci. .

Abstract

Immunotherapies have revolutionized cancer treatment approaches. Because not all patients respond positively to immune therapeutic agents, it represents a challenge for scientists who strive to understand the mechanisms behind such resistance. In-depth exploration of tumor biology, using novel technologies such as omics science, can help decode the role of the tumor immune microenvironment (TIME) in producing a response to the immune blockade strategies. It can also help to identify biomarkers for patient stratification and personalized treatment. This review aims to explore these new models and highlight their possible pivotal role in changing clinical practice.

Keywords: AI; biomarkers; immunotherapy; multi-omics science; state of the art.

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Conflict of interest statement

The authors declare no conflicts of interest.

References

    1. Xu Y., Su G.-H., Ma D., Xiao Y., Shao Z.-M., Jiang Y.-Z. Technological advances in cancer immunity: From immunogenomics to single-cell analysis and artificial intelligence. Signal Transduct. Target. Ther. 2021;6:312. doi: 10.1038/s41392-021-00729-7. - DOI - PMC - PubMed
    1. Xie J., Luo X., Deng X., Tang Y., Tian W., Cheng H., Zhang J., Zou Y., Guo Z., Xie X. Advances in artificial intelligence to predict cancer immunotherapy efficacy. Front. Immunol. 2023;13:1076883. doi: 10.3389/fimmu.2022.1076883. - DOI - PMC - PubMed
    1. Jiang A., Liu Y., Chen O., Liu Z., Cai H., Wang L., Qi L. Editorial: Multi-omics approaches for decoding heterogeneity in cancer immunotherapy. Front. Pharmacol. 2023;14:1324212. doi: 10.3389/fphar.2023.1324212. - DOI - PMC - PubMed
    1. Lee T.-A., Tsai E.-Y., Liu S.-H., Hung S.-D.H., Chang S.-J., Chao C.-H., Lai Y.-J., Yamaguchi H., Li C.-W. Post-translational Modification of PD-1: Potential Pathways for Cancer Immunotherapy. Cancer Res. 2024;84:800–807. doi: 10.1158/0008-5472.can-23-2664. - DOI - PMC - PubMed
    1. Srivastava A.K., Guadagnin G., Cappello P., Novelli F. Post-Translational Modifications in Tumor-Associated Antigens as a Platform for Novel Immuno-Oncology Therapies. Cancers. 2022;15:138. doi: 10.3390/cancers15010138. - DOI - PMC - PubMed

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