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.© The Author(s) 2023. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.