Evidence map›Paper›PMID 39231258›Full record

ArticleDatabase : the journal of biological databases and curation2024

CuPCA: a web server for pan-cancer association analysis of large-scale cuproptosis-related genes.

Yishu Xu, Zhenshu Ma, Yajie Wang, Long Zhang, Jiaming Ye, Yuan Chen, Zhengrong Yuan

Abstract read
In one paragraph

Article in Database : the journal of biological databases and curation, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0cells of the map it votes in
0citing papers in PubMed
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1 · What the graph read from it

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.

2 · The registry

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3 · Its place in the literature

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0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

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5 · Who and what money

Authors and funding

7 authors.

Yishu XuCollege of Biological Sciences and Technology, Beijing Forestry University, Beijing 100083, China.
Zhenshu MaCollege of Computer Science and Technology, Beijing Forestry University, Beijing 100083, China.
Yajie WangDepartment of Clinical Laboratory, Beijing Ditan Hospital, Capital Medical University, Beijing 100015, China.
Long ZhangCollege of Art, Beijing Forestry University, Beijing 100083, China.
Jiaming YeCollege of Biological Sciences and Technology, Beijing Forestry University, Beijing 100083, China.
Yuan ChenDepartment of Clinical Laboratory, Beijing Ditan Hospital, Capital Medical University, Beijing 100015, China.ORCID 0009-0002-3167-9151
Zhengrong YuanCollege of Biological Sciences and Technology, Beijing Forestry University, Beijing 100083, China.ORCID 0009-0003-2221-7630

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Copper-induced cell death is a novel mechanism of cell death, which is defined as cuproptosis. The increasing level of copper can produce toxicity in cells and may cause the occurrence of cell death. Several previous studies have proved that cuproptosis has a tight association with various cancers. Thus, the discovery of relationships between cuproptosis-related genes (CRGs) and human cancers is of great importance. Pan-cancer analysis can efficiently help researchers find out the relationship between multiple cancers and target genes precisely and make various prognostic analyses on cancers and cancer patients. Pan-cancer web servers can provide researchers with direct results of pan-cancer prognostic analyses, which can greatly improve the efficiency of their work. However, to date, no web server provides pan-cancer analysis about CRGs. Therefore, we introduce the cuproptosis pan-cancer analysis database (CuPCA), the first database for various analysis results of CRGs through 33 cancer types. CuPCA is a user-friendly resource for cancer researchers to gain various prognostic analyses between cuproptosis and cancers. It provides single CRG pan-cancer analysis, multi-CRGs pan-cancer analysis, multi-CRlncRNA pan-cancer analysis, and mRNA-circRNA-lncRNA conjoint analysis. These analysis results can not only indicate the relationship between cancers and cuproptosis at both gene level and protein level, but also predict the conditions of different cancer patients, which include their clinical condition, survival condition, and their immunological condition. CuPCA procures the delivery of analyzed data to end users, which improves the efficiency of wide research as well as releases the value of data resources. Database URL: http://cupca.cn/.

Indexed as

Databases, GeneticInternetNeoplasmsHumansSoftware

Identifiers

PMID39231258
PMCPMC11373563

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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.