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Multi-Omics Data Analysis for Cancer Research: Colorectal Cancer, Liver Cancer and Lung Cancer

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Methodologies of Multi-Omics Data Integration and Data Mining

Part of the book series: Translational Bioinformatics ((TRBIO,volume 19))

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Abstract

Cancer is a multifactorial disease caused by the malfunction and modification of numerous biological entities, including genes, proteins, mRNAs, miRNAs, and metabolites. Recent advances in high-throughput technologies have generated massive amounts of diverse biological data, allowing researchers to investigate a large number of omics markers. While analyzing single omics data sets can reveal a wealth of information in a unidirectional fashion, because DNA, RNA, protein, and metabolite frequently collaborate to perform biological functions, the complementary effects and interactions between multiple molecular layers cannot be fully assessed. As a result, only by integrating multiple types of omics data can we gain a systematic and comprehensive understanding of the functional mechanisms underlying DNA-level alterations in tumors and identify novel genes, markers, vital networks, and pathways. We will briefly discuss the current state of colorectal cancer, liver cancer, and lung cancer research in this article. Additionally, we discuss various multi-omics analyses conducted in the fields of colorectal cancer, liver cancer, and lung cancer research, which provide insight into novel cancer diagnostic and treatment approaches. We hope to inspire researchers to use multi-omics approaches to investigate cancer at the molecular, cellular, and systemic levels.

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Acknowledgments

We thank all the individuals who have helped us in this study. We acknowledge the valuable work of the many investigators whose published articles we were unable to cite owing to space limitations.

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Authors and Affiliations

  1. School of Life Sciences, Jiangsu University, Zhenjiang, Jiangsu, China

    Hantao Zhang & Min Tang

  2. Department of Rheumatology & Immunology, the Affiliated Hospital of Jiangsu University, Zhenjiang, China

    Xun Gong

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  1. Hantao Zhang
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  2. Xun Gong
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Correspondence to Min Tang .

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Editors and Affiliations

  1. Department of Bioinformatics and Systems Biology, Center of AI biology, College of Life Science and Technology, Huazhong University of Science and Technology, Wuhan, China

    Kang Ning

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This work was financially supported by the grants from the National Natural Science Foundation of China (31861143051, 31872425, 32002235, 31602008) and Senior Talent Foundation of Jiangsu University (19JDG039).

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Zhang, H., Gong, X., Tang, M. (2023). Multi-Omics Data Analysis for Cancer Research: Colorectal Cancer, Liver Cancer and Lung Cancer. In: Ning, K. (eds) Methodologies of Multi-Omics Data Integration and Data Mining. Translational Bioinformatics, vol 19. Springer, Singapore. https://doi.org/10.1007/978-981-19-8210-1_5

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