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. 2025 Sep 30;23(1):1019.
doi: 10.1186/s12967-025-07029-6.

TumorXDB: an integrated multi-omics xWAS/xQTL platform for cross-ethnic pan-cancer analysis

Zehua Dong #  1   2   3 , Yihang Cheng #  1   2   3 , Tao Mo  4 , Wencai Mao  4 , Wenqian Zhao  4 , Deqiang Sun  5   6   7
Affiliations

TumorXDB: an integrated multi-omics xWAS/xQTL platform for cross-ethnic pan-cancer analysis

Zehua Dong et al. J Transl Med. .

Abstract

Background: TumorXDB is a comprehensively curated tumor database integrating molecular association data (xWAS/xQTL) to explore genetic mechanisms across diverse tumors, organs, and ethnic groups. We aimed to provide a unified resource for discovering novel genetic associations and molecular mechanisms in tumors.

Methods: TumorXDB integrates four molecular-wide association studies (xWAS) and 23 molecular quantitative trait locus (xQTL) types spanning 10 physiological systems, 50 organs, and 139 cancer subtypes, while incorporating data from 25 ethnic subgroups across four major ancestral populations. To ensure data harmonization, we performed batch-effect correction using ComBat and applied the Benjamini-Hochberg (BH) procedure with false discovery rate (FDR) of < 0.05 for multiple testing correction. Meta-analysis models were developed to generate unified pan-cancer datasets, which are all accessible through a user-friendly web interface ( http://www.tumor-xdb.com ) with full data download capabilities.

Results: TumorXDB enabled robust integration of molecular data, revealing novel cross-cancer genetic associations through harmonized analysis.

Conclusions: This resource advances precision oncology by providing batch-corrected and statistically rigorous pan-cancer data for therapeutic discovery.

Keywords: Database; Multi-omics; Neoplasms; Population groups; Quantitative trait loci; Wide association study.

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Conflict of interest statement

Declarations. Ethics approval and consent to participate: Not applicable. Consent for publication: Not applicable. Competing interests: The authors declare no competing interests.

Figures

Fig. 1
Fig. 1
Interactive anatomical/ethnic filters. A Interactive anatomical model with 10 physiological systems. B Global map displaying dataset geographic/ethnic diversity
Fig. 2
Fig. 2
Database Main Interface Overview. A Home interface: Main Interface Button Functions. B Search interfaces: Search bar for SNP/gene queries; dynamic sliders to filter by statistical thresholds (P < 1 × 10–5). Only significant entries displayed by default. C Download interfaces: Hierarchical refinement via dropdown. TXT files include SNPs, beta/p-values, and metadata. D Help interface: “About” summary and reference tables for cross-referencing codes, cohorts, and classifications
Fig. 3
Fig. 3
Batch effect correction assessment. A Pre-ComBat PCA colored by batch. B Post-ComBat PCA showing cluster integration. C Correlations plot of Pre-vs-Post Combat-log10 (FDR) values. The Pearson’s correlation coefficients (r) and P values are shown in C
See this image and copyright information in PMC

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