Evidence map›Paper›PMID 40990162›Full record

ArticleNucleic acids research2026

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

Yihao Chen, Le Zhang, Chuanfan Zhong, Songbo Li, Ruidong Li, Zhenyu Jia, Peisheng Huang, Shuo Wang, Zitao He, Huawei Lin and 9 more

Abstract read
In one paragraph

Article in Nucleic acids research, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

  1. Article
  2. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

19 authors.

Yihao ChenDepartment of Andrology, Guangzhou First People's Hospital, School of Medicine, South China University of Technology, Guangzhou, Guangdong 510180, China.ORCID 0009-0002-9703-7645
Le ZhangGenetics, Genomics, and Bioinformatics Program, University of California, Riverside, CA 92521, United States.
Chuanfan ZhongDepartment of Urology, Guangdong Key Laboratory of Clinical Molecular Medicine and Diagnostics, Guangzhou First People's Hospital, Guangzhou Medical University, Guangzhou,Guangdong 510180, China.
Songbo LiDepartment of Urology, Nanxishan Hospital of Guangxi Zhuang Autonomous Region, The Second People's Hospital of Guangxi Zhuang Autonomous Region, Guilin 541002, China.
Ruidong LiGenetics, Genomics, and Bioinformatics Program, University of California, Riverside, CA 92521, United States.ORCID 0000-0002-4822-2898
Zhenyu JiaGenetics, Genomics, and Bioinformatics Program, University of California, Riverside, CA 92521, United States.ORCID 0000-0002-1428-904X
Peisheng HuangDepartment of Urology, Huizhou Central People's Hospital, Huizhou, Guangdong 516001, China.
Shuo WangDepartment of Andrology, Guangzhou First People's Hospital, School of Medicine, South China University of Technology, Guangzhou, Guangdong 510180, China.
Zitao HeDepartment of Andrology, Guangzhou First People's Hospital, School of Medicine, South China University of Technology, Guangzhou, Guangdong 510180, China.
Huawei LinThe Second Clinical College, Guangzhou Medical University, Guangzhou, Guangdong 510180, China.
Xiaowen LinThe Second Clinical College, Guangzhou Medical University, Guangzhou, Guangdong 510180, China.
Kai ChenDepartment of Pathology, Guangzhou Medical University Affiliated Women and Children's Medical Center, Guangzhou, Guangdong 510623, China.
Zhuoya HuangDepartment of Pathology, Huizhou Central People's Hospital, Huizhou, Guangdong 516001, China.
Shanshan MoDepartment of Andrology, Guangzhou First People's Hospital, School of Medicine, South China University of Technology, Guangzhou, Guangdong 510180, China.
Zhouda CaiDepartment of Andrology, Guangzhou First People's Hospital, School of Medicine, South China University of Technology, Guangzhou, Guangdong 510180, China.
Junhong DengDepartment of Andrology, Guangzhou First People's Hospital, School of Medicine, South China University of Technology, Guangzhou, Guangdong 510180, China.
Weide ZhongDepartment of Urology, Guangdong Key Laboratory of Clinical Molecular Medicine and Diagnostics, Guangzhou First People's Hospital, Guangzhou Medical University, Guangzhou,Guangdong 510180, China.
Jiahong ChenDepartment of Urology, Huizhou Central People's Hospital, Huizhou, Guangdong 516001, China.
Jianming LuDepartment of Andrology, Guangzhou First People's Hospital, School of Medicine, South China University of Technology, Guangzhou, Guangdong 510180, China.ORCID 0000-0002-3794-641X

Funding

Guangdong Provincial Natural Science Foundation 2022A1515010344National Natural Science Foundation of China 82003271National Natural Science Foundation of China 82573325Regional Joint Fund - Regional Cultivation Project 2023A1515140040Science and Technology Development Fund 006/2023/SKLScience and Technology Development Fund 0116/2023/RIA2Young Scientists Fund of the National Natural Science Foundation of China 82404028
6 · The paper itself

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/.

Indexed as

Databases, GeneticNeoplasmsRare DiseasesSoftwareHumansImmunotherapyPrecision Medicine

Identifiers

PMID40990162
PMCPMC12807777

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.