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Estimation of Tumor Immune Signatures from Transcriptomics Data

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Handbook of Statistical Bioinformatics

Part of the book series: Springer Handbooks of Computational Statistics ((SHCS))

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Abstract

Enhancing the patients’ immune response to cancer using immune checkpoint blockages has shown promising results in treating multiple cancers over the past decades. However, the cellular composition of tumors and their immune microenvironment varies between patients and cancer types. In addition, different immune cell types play different roles in tumor control and response to therapy through either pro- or anti-tumorigenic functions. Therefore, a deep understanding of the patient-specific tumor-infiltrating immune signatures and their functions in the tumor microenvironment (TME) can help the prediction of therapy response and ultimately guide the development of personalized immunotherapies. Several computational algorithms and approaches have been developed to infer tumor immune composition using transcriptomics data. In this chapter, I will review the statistical and computational methods that estimate the tumor immune signatures from RNA sequencing data and further highlight well-executed benchmarking studies. I will also discuss challenges and opportunities for integrating signatures learned at single-cell level to characterize immune composition of bulk tumors.

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Authors and Affiliations

  1. Department of Biostatistics and Bioinformatics, Moffitt Cancer Center and Research Institute, Tampa, FL, USA

    Xiaoqing Yu

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  1. Xiaoqing Yu
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Correspondence to Xiaoqing Yu .

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Editors and Affiliations

  1. Institute of Statistics, National Yang Ming Chiao Tung University, Hsinchu, Taiwan, Taiwan

    Henry Horng-Shing Lu

  2. Department of Empirical Inference, Max Planck Institute for Intelligent Systems, TĂĽbingen, Germany

    Bernhard Schölkopf

  3. Department of Statistics and Data Science, Cornell University, Ithaca, NY, USA

    Martin T. Wells

  4. Department of Biostatistics, Yale University, New Haven, CT, USA

    Hongyu Zhao

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Yu, X. (2022). Estimation of Tumor Immune Signatures from Transcriptomics Data. In: Lu, H.HS., Schölkopf, B., Wells, M.T., Zhao, H. (eds) Handbook of Statistical Bioinformatics. Springer Handbooks of Computational Statistics. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-65902-1_16

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