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

TL;DR

CuPCA is a web server that helps researchers analyze the relationship between cuproptosis-related genes and various cancers across 33 cancer types.

Contribution

CuPCA is the first web server providing pan-cancer analysis of cuproptosis-related genes.

Findings

CuPCA enables single and multi-gene pan-cancer analysis of cuproptosis-related genes.

The server supports mRNA–circRNA–lncRNA conjoint analysis for cancer prognosis.

CuPCA improves research efficiency by delivering analyzed data directly to users.

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/

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