SexTumorDB: a comprehensive resource of sex-dependent tumor landscape at single-cell resolution

Sex is one of the most fundamental biological variables, with a profound impact on tumor incidence, mortality, treatment response and prognosis, making it a critical consideration for precision oncology. Despite its well-established role in tumors, sex bias is often overlooked in both basic research and clinical practice. Our understanding of sex disparities in tumors, especially in non-reproductive tumors and non-malignant components, remains limited, necessitating a comprehensive investigation of sexual dimorphism in cancer. To address this gap, we developed the SexTumorDB database, an integrated resource containing RNA sequencing profiles of non-reproductive tumors at single-cell resolution. SexTumorDB covers 13 cancer types with the highest incidence in either males or females, encompassing 2,014,043 cells from 532 samples, including 319 male and 213 female samples. The SexTumorDB datasets were rigorously curated, processed, and standardized. By making this resource publicly available through online repositories and web applications, we aim to advance the understanding of sex disparities in the tumor microenvironments (TMEs) and foster the development of sex-specific anticancer treatment strategies in the future.

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Publication Details

Journal
Scientific Data
Published
2026-02-25
DOI
https://doi.org/10.1038/s41597-026-06707-4
Primary Topic
Single-cell and spatial transcriptomics
Type
article
Field-Weighted Citation Impact
0.00

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article

SexTumorDB: a comprehensive resource of sex-dependent tumor landscape at single-cell resolution

Ruya Sun, Qiqi Deng, Di Wang
Scientific Data
Single-cell and spatial transcriptomics
article

SexTumorDB: a comprehensive resource of sex-dependent tumor landscape at single-cell resolution

Ruya Sun, Qiqi Deng, Di Wang
article en

Abstract

Sex is one of the most fundamental biological variables, with a profound impact on tumor incidence, mortality, treatment response and prognosis, making it a critical consideration for precision oncology. Despite its well-established role in tumors, sex bias is often overlooked in both basic research and clinical practice. Our understanding of sex disparities in tumors, especially in non-reproductive tumors and non-malignant components, remains limited, necessitating a comprehensive investigation of sexual dimorphism in cancer. To address this gap, we developed the SexTumorDB database, an integrated resource containing RNA sequencing profiles of non-reproductive tumors at single-cell resolution. SexTumorDB covers 13 cancer types with the highest incidence in either males or females, encompassing 2,014,043 cells from 532 samples, including 319 male and 213 female samples. The SexTumorDB datasets were rigorously curated, processed, and standardized. By making this resource publicly available through online repositories and web applications, we aim to advance the understanding of sex disparities in the tumor microenvironments (TMEs) and foster the development of sex-specific anticancer treatment strategies in the future.

Scientific Data
Sir Run Run Shaw Hospital (CN), Ministry of Education (ET), Zhejiang University (CN)
Sir Run Run Shaw Hospital, National Natural Science Foundation of China, Zhejiang University, Natural Science Foundation of Zhejiang Province
Gender equality
Openalex Percentile: Top 43%
Single-cell and spatial transcriptomics
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