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Updated: Sep 8, 2026
Predictive Immune Modeling of Solid Tumors
Published on: February 25, 2020
Protocol to identify novel immunotherapy biomarkers based on transcriptomic data in human cancers
1Department of Oncology, The Affiliated Wuxi People's Hospital of Nanjing Medical University, Wuxi 214023, China; Department of Oncology, The First Affiliated Hospital of Nanjing Medical University, Nanjing 210029, China; Wuxi Clinical College of Nanjing Medical University, Wuxi 214023, China.
Abstract:
Immune checkpoint inhibitors have transformed the management of advanced cancers, but biomarkers for the prediction of therapeutic responses have not been fully uncovered. Here, we provide a step-by-step approach for the identification of novel biomarkers from public transcriptomic datasets. We comprehensively summarize the available transcriptomic datasets containing immunotherapy information and describe the necessary procedures to evaluate the effectiveness of a novel immunotherapy biomarker, which may accelerate the identification of novel immunotherapy biomarkers. For complete details on the use and execution of this protocol, please refer to Mei et al.1.
Insights
Identifying new biomarkers for cancer immunotherapy response is crucial. This study outlines a protocol using public transcriptomic data to find and validate novel biomarkers, aiding treatment prediction.
Area of Science:
- Oncology
- Bioinformatics
- Immunology
Background:
- Immune checkpoint inhibitors (ICIs) have revolutionized advanced cancer treatment.
- Predictive biomarkers for ICI therapy response remain largely undiscovered.
- Identifying reliable biomarkers is essential for personalized cancer immunotherapy.
Purpose of the Study:
- To present a systematic protocol for discovering novel biomarkers of therapeutic response to cancer immunotherapies.
- To guide researchers in utilizing public transcriptomic datasets for biomarker identification.
- To accelerate the development and validation of new biomarkers for immunotherapy.
Main Methods:
- Comprehensive review and summarization of public transcriptomic datasets relevant to immunotherapy.
- Description of step-by-step procedures for biomarker identification and evaluation.
- Methodology for assessing the predictive efficacy of potential novel biomarkers.
Main Results:
- A structured approach for leveraging public transcriptomic data is detailed.
- The protocol facilitates the evaluation of novel immunotherapy biomarker candidates.
- The presented methodology aims to streamline the biomarker discovery pipeline.
Conclusions:
- This protocol offers a standardized framework for identifying and validating biomarkers for cancer immunotherapy.
- Utilizing public transcriptomic data can significantly expedite the discovery of predictive biomarkers.
- The approach has the potential to improve patient selection for immunotherapy and enhance treatment outcomes.
