Rare Cancer Explorer 1.0 (RaCE 1.0): a dedicated database and analytical platform focused on rare cancers

Rare cancers face major research challenges due to limited sample sizes and data scarcity. Existing pan-cancer databases mainly focus on common cancer types, while rare cancers often lack sufficient attention and systematic data collection. In addition, their high heterogeneity and the scarcity of studies on genomic features, immune environments, and drug responses lead to significant gaps in current databases and analytical tools. To address these limitations, we developed the Rare Cancer Explorer (RaCE), a dedicated database for integrated curation, analysis, and visualization of rare cancers. RaCE consolidates 5451 samples spanning 13 rare solid tumor types from 69 independent datasets, offering researchers a one-stop data analysis toolkit. The database provides one integrated dataset meta-analysis module and eight dedicated rare cancer functional analysis modules, including transcriptomics, immune infiltration, and immunotherapy response prediction, with a specialized focus on modeling gene effects and drug sensitivity in rare cancer cell lines. RaCE distinguishes itself through robust interactive functionalities, enabling users to seamlessly explore multi-layered insights from gene functions to therapeutic targets, thereby accelerating precision medicine and translational research for rare cancers. Compared to existing databases, RaCE demonstrates unique advantages in supporting rare cancer research through comprehensive data integration. The database is freely accessible at https://biospace.shinyapps.io/race/ or https://hiplot.com.cn/race/.

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Institutions

Publication Details

Journal
Nucleic Acids Research
Published
2025-08-31
DOI
https://doi.org/10.1093/nar/gkaf911
Citations
2
Primary Topic
Epigenetics and DNA Methylation
Type
article
Field-Weighted Citation Impact
1.61

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article

Rare Cancer Explorer 1.0 (RaCE 1.0): a dedicated database and analytical platform focused on rare cancers

Kai Chen, Shanshan Mo, Weide Zhong, Chuanfan Zhong et al.
2 citations
Nucleic Acids Research
Epigenetics and DNA Methylation
1.61
article

Rare Cancer Explorer 1.0 (RaCE 1.0): a dedicated database and analytical platform focused on rare cancers

Kai Chen, Shanshan Mo, Weide Zhong, Chuanfan Zhong, Zhuoya Huang, Xiaowen Lin, Zhonglian He, Jianming Lü, Peisheng Huang, Zhenyu Jia, Yihao Chen, Zhouda Cai, Le Zhang, Shuo Wang, Ruidong Li, Huan Lin, Songbo Li, Jiahong Chen, Junhong Deng
article en
2 citations

Abstract

Rare cancers face major research challenges due to limited sample sizes and data scarcity. Existing pan-cancer databases mainly focus on common cancer types, while rare cancers often lack sufficient attention and systematic data collection. In addition, their high heterogeneity and the scarcity of studies on genomic features, immune environments, and drug responses lead to significant gaps in current databases and analytical tools. To address these limitations, we developed the Rare Cancer Explorer (RaCE), a dedicated database for integrated curation, analysis, and visualization of rare cancers. RaCE consolidates 5451 samples spanning 13 rare solid tumor types from 69 independent datasets, offering researchers a one-stop data analysis toolkit. The database provides one integrated dataset meta-analysis module and eight dedicated rare cancer functional analysis modules, including transcriptomics, immune infiltration, and immunotherapy response prediction, with a specialized focus on modeling gene effects and drug sensitivity in rare cancer cell lines. RaCE distinguishes itself through robust interactive functionalities, enabling users to seamlessly explore multi-layered insights from gene functions to therapeutic targets, thereby accelerating precision medicine and translational research for rare cancers. Compared to existing databases, RaCE demonstrates unique advantages in supporting rare cancer research through comprehensive data integration. The database is freely accessible at https://biospace.shinyapps.io/race/ or https://hiplot.com.cn/race/.

Nucleic Acids ResearchVol. 54(D1)
University of California, Riverside (US), Macau University of Science and Technology (MO), Second Affiliated Hospital of Guangzhou Medical University (CN), First Affiliated Hospital of Guangzhou Medical University (CN), Guangzhou Women and Children Medical Center (CN), The People's Hospital of Guangxi Zhuang Autonomous Region (CN), Guangzhou First People's Hospital (CN), Institut thématique Génétique, génomique et bioinformatique (FR), Huizhou Central People's Hospital (CN), Nanxi Mountain Hospital (CN), Guangzhou Medical University (CN)
National Natural Science Foundation of China, Natural Science Foundation of Guangdong Province, Fundo para o Desenvolvimento das Ciências e da Tecnologia, Natural Science Foundation for Young Scientists of Shanxi Province, Young Scientists Fund
Openalex Percentile: Top 15%
Epigenetics and DNA Methylation
1.61
DOIOpen Access PDFOpenAlex
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