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  • Perspective
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Harnessing big data to characterize immune-related adverse events

Nature Reviews Clinical Oncology volume 19, pages 269–280 (2022)Cite this article

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Abstract

Immune-checkpoint inhibitors (ICIs) have transformed patient care in oncology but are associated with a unique spectrum of organ-specific inflammatory toxicities known as immune-related adverse events (irAEs). Given the expanding use of ICIs, an increasing number of patients with cancer experience irAEs, including severe irAEs. Proper diagnosis and management of irAEs are important to optimize the quality of life and long-term outcomes of patients receiving ICIs; however, owing to the substantial heterogeneity within irAEs, and despite multicentre initiatives, performing clinical studies of these toxicities with a sufficient cohort size is challenging. Pioneering studies from the past few years have demonstrated that aggregate clinical data, real-world data (such as data on pharmacovigilance or from electronic health records) and multi-omics data are alternative tools well suited to investigating the underlying mechanisms and clinical presentations of irAEs. In this Perspective, we summarize the advantages and shortcomings of different sources of ‘big data’ for the study of irAEs and highlight progress made using such data to identify biomarkers of irAE risk, evaluate associations between irAEs and therapeutic efficacy, and characterize the effects of demographic and anthropometric factors on irAE risk. Harnessing big data will accelerate research on irAEs and provide key insights that will improve the clinical management of patients receiving ICIs.

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Fig. 1: Exponential growth of big data from representative data sources.
Fig. 2: Identification of irAE biomarkers.
Fig. 3: Association between irAEs and ICI efficacy.
Fig. 4: Associations between irAEs and demographic factors.

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Acknowledgements

The authors receive funding support from the Cancer Prevention and Research Institute of Texas (grant RP190570 to L.H.) and National Institutes of Health (grants R01HL141466, R01HL155990 and R01HL156021 to J.J.M.). The authors thank L. Chastain (University of Texas MD Anderson Cancer Center) for editorial assistance. The authors regret that page limitations have prevented them from including all the relevant studies in this Perspective.

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  1. These authors contributed equally: Ying Jing, Jingwen Yang.

Authors and Affiliations

  1. Clinical Research Institute, Shanghai Jiao Tong University School of Medicine, Shanghai, China

    Ying Jing

  2. Center for Epigenetics and Disease Prevention, Institute of Biosciences and Technology, Texas A&M University, Houston, TX, USA

    Jingwen Yang & Leng Han

  3. Department of Internal Medicine, Vanderbilt University Medical Center, Nashville, TN, USA

    Douglas B. Johnson

  4. Section of Cardio-Oncology & Immunology, Division of Cardiology, Cardiovascular Research Institute, University of California San Francisco, San Francisco, CA, USA

    Javid J. Moslehi

  5. Department of Translational Medical Sciences, College of Medicine, Texas A&M University, Houston, TX, USA

    Leng Han

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D.B.J. has been an advisory board member or consultant for Bristol Myers Squibb, Catalyst, Iovance, Jansen, Mallinckrodt, Merck, Mosaic ImmunoEngineering, Novartis, Oncosec, Pfizer, and Targovax and receives grant support from Bristol Myers Squibb and Incyte for work outside the scope of this article. J.J.M. has served on advisory boards for Amgen, AstraZeneca, Audentes, Boston Biomedical, Bristol Myers Squibb, Cytokinetics, Deciphera, Immuno-Core, Ipsen, Janssen, Myovant, Precigen Triple-Gene, Regeneron and Takeda. Y.J., J.Y. and L.H. declare no competing interests.

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Related links

Clinical Proteomic Tumour Analysis Consortium (CPTAC): https://proteomics.cancer.gov/programs/cptac

ClinicalStudyDataRequest.com: https://clinicalstudydatarequest.com/

ClinicalTrials.gov: https://clinicaltrials.gov/

FDA Adverse Event Reporting System (FAERS): https://www.fda.gov/drugs/questions-and-answers-fdas-adverse-event-reporting-system-faers/fda-adverse-event-reporting-system-faers-public-dashboard

Flatiron Health: https://rwe.flatiron.com/

Gene Expression Omnibus (GEO): https://www.ncbi.nlm.nih.gov/geo/

Genotype-Tissue Expression (GTEx): https://gtexportal.org/home/

Human Protein Atlas (HPA): https://www.proteinatlas.org/

Human Tumour Atlas Network (HTAN): https://humantumoratlas.org/

IQVIA datasets: https://www.iqvia.com/solutions/real-world-evidence/real-world-data-and-insights

Optum Clinformatics: https://www.optum.com/occt

REISAMIC: https://www.reisamic.fr/

Sequence Read Archive (SRA): https://www.ncbi.nlm.nih.gov/sra

TCRdb: http://bioinfo.life.hust.edu.cn/TCRdb/

The Cancer Genome Atlas (TCGA): https://portal.gdc.cancer.gov/

UK Biobank: https://www.ukbiobank.ac.uk/

VigiBase: https://who-umc.org/vigibase/

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Jing, Y., Yang, J., Johnson, D.B. et al. Harnessing big data to characterize immune-related adverse events. Nat Rev Clin Oncol 19, 269–280 (2022). https://doi.org/10.1038/s41571-021-00597-8

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