Unknown

Dataset Information

0

GCclassifier: An R package for the prediction of molecular subtypes of gastric cancer.


ABSTRACT: Gastric cancer (GC) is one of the most commonly diagnosed malignancies, threatening millions of lives worldwide each year. Importantly, GC is a heterogeneous disease, posing a significant challenge to the selection of patients for more optimized therapy. Over the last decades, extensive community effort has been spent on dissecting the heterogeneity of GC, leading to the identification of distinct molecular subtypes that are clinically relevant. However, so far, no tool is publicly available for GC subtype prediction, hindering the research into GC subtype-specific biological mechanisms, the design of novel targeted agents, and potential clinical applications. To address the unmet need, we developed an R package GCclassifier for predicting GC molecular subtypes based on gene expression profiles. To facilitate the use by non-bioinformaticians, we also provide an interactive, user-friendly web server implementing the major functionalities of GCclassifier. The predictive performance of GCclassifier was demonstrated using case studies on multiple independent datasets.

SUBMITTER: Li J 

PROVIDER: S-EPMC10831507 | biostudies-literature | 2024 Dec

REPOSITORIES: biostudies-literature

altmetric image

Publications

GCclassifier: An R package for the prediction of molecular subtypes of gastric cancer.

Li Jiang J   He Lingli L   Zhang Xianrui X   Li Xiang X   Wang Lishi L   Zhu Zhongxu Z   Song Kai K   Wang Xin X  

Computational and structural biotechnology journal 20240117


Gastric cancer (GC) is one of the most commonly diagnosed malignancies, threatening millions of lives worldwide each year. Importantly, GC is a heterogeneous disease, posing a significant challenge to the selection of patients for more optimized therapy. Over the last decades, extensive community effort has been spent on dissecting the heterogeneity of GC, leading to the identification of distinct molecular subtypes that are clinically relevant. However, so far, no tool is publicly available for  ...[more]

Similar Datasets

| S-EPMC8802764 | biostudies-literature
| PRJNA329144 | ENA
2018-03-20 | GSE84437 | GEO
2018-03-20 | GSE84433 | GEO
2018-03-20 | GSE84426 | GEO
2023-03-18 | GSE147163 | GEO
| PRJNA613226 | ENA
| S-EPMC9899380 | biostudies-literature
| S-EPMC5922408 | biostudies-literature
| S-EPMC10713392 | biostudies-literature