ArticleNucleic acids research2026
Rare Cancer Explorer 1.0 (RaCE 1.0): a dedicated database and analytical platform focused on rare cancers.
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.
What it found
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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.
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.
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Who cites it
2 citing papers in PubMed.
- The pseudouridine epitranscriptomic landscape of advanced prostate cancer therapeutic resistance identifies TIMM17A as a key player.Translational oncology · 2026Article
- The 2026 Nucleic Acids Research database issue and the online molecular biology database collection.Nucleic acids research · 2026Article
Corrections and comments
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Authors and funding
19 authors.
Funding
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/.
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Registered trials
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.