ArticleBriefings in bioinformatics2023
ICBcomb: a comprehensive expression database for immune checkpoint blockade combination therapy.
Article in Briefings in bioinformatics, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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Who cites it
5 citing papers in PubMed.
- Deciphering cancer therapy resistance via patient-level single-cell transcriptomics with CellResDB.Communications biology · 2025Article
- ImmiR: A database of microRNAs associated with immune checkpoints and infiltrates.Computational and structural biotechnology journal · 2025Article
- TCellSI: A novel method for T cell state assessment and its applications in immune environment prediction.iMeta · 2024Article
- Applications of pyroptosis activators in tumor immunotherapy.Materials today. Bio · 2024Review
- A method for predicting drugs that can boost the efficacy of immune checkpoint blockade.Nature immunology · 2024Article
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9 authors.
Funding
Abstract
The success of immune checkpoint blockade (ICB) promotes the immunotherapy to be a new pillar in cancer treatment. However, the low response rate of the ICB therapy limits its application. To increase the response rate and enhance efficacy, the ICB combination therapy has emerged and its clinical trials are increasing. Nevertheless, the gene expression profile and its pattern of ICB combination were not comprehensively studied, which limits the understanding of the ICB combination therapy and the identification of new drugs. Here, we constructed ICBcomb (http://bioinfo.life.hust.edu.cn/ICBcomb/), a comprehensive database, by analyzing the human and mouse expression data of the ICB combination therapy and comparing them between groups treated with ICB, other drugs or their combinations. ICBcomb contains 1399 samples across 29 cancer types involving 52 drugs. It provides a user-friendly web interface for demonstrating the results of the available comparisons in the ICB combination therapy datasets with five functional modules: [1, 2] the 'Dataset/Disease' modules for browsing the expression, enrichment and comparison results in each dataset or disease; [3] the 'Gene' module for inputting a gene symbol and displaying its expression and comparison results across datasets/diseases; [4] the 'Gene Set' module for GSVA/GSEA enrichment analysis on the built-in gene sets and the user-input gene sets in different comparisons; [5] the 'Immune Cell' module for immune cell infiltration comparison between different groups by immune cell abundance analysis. The ICBcomb database provides the first resource for gene expression profile and comparison in ICB combination therapy, which may provide clues for discovering the mechanism of effective combination strategies and new combinatory drugs.
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