SCDb

SCDb integrates multi-omics, genetic variation, and curated literature data for stomach cancer to support identification of disease-related genes and prognostic biomarkers.

Key Features:

• Data integration: Integrated literature mining, public microarray datasets, RNA-seq, miRNA-seq, and clinical data from The Cancer Genome Atlas (TCGA).
• Genes: Identified 9,990 stomach cancer-related genes (8,347 up-regulated, 1,643 down-regulated), with 65 genes confirmed as SC-related by enrichment analysis.
• MicroRNAs (miRNAs): Includes 457 miRNAs, with 20 associated with stomach cancer, aggregated from miRanda, miRTarget2, PicTar, PITA, and TargetScan.
• Single Nucleotide Polymorphisms (SNPs): Contains 1,570 SNPs including 108 stomach cancer-related variants retrieved from dbSNP and ClinVar.
• Transcription Factors (TFs): Lists 419 transcription factors obtained from TRANSFAC.
• Copy Number Variations (CNVs): Analyzed 44,605 CNVs using data from DGV.
• Methylation: Includes methylation data for 63 genes sourced from PubMeth.
• Drug Associations: Contains 3,404 drug-associated genes identified via WebGestalt.
• Survival Analysis: Generated Kaplan–Meier survival curves for identified SC-related genes and for 20,264 genes to assess prognostic significance.

Scientific Applications:

• Gene–disease association studies: Enable identification and characterization of genes associated with stomach cancer.
• Prognostic biomarker discovery: Support evaluation of gene-level prognostic significance via Kaplan–Meier analyses.
• Drug discovery and target prioritization: Provide drug-associated gene lists to inform therapeutic candidate selection.
• Pathogenesis research: Facilitate investigation of molecular mechanisms underlying stomach cancer using integrated multi-omics data.
• Personalized medicine approaches: Support analyses that link molecular and clinical data to inform individualized strategies.

Methodology:

SC-related genes were identified via literature mining and examination of publicly available microarray datasets; RNA-seq, miRNA-seq, and clinical data from TCGA were analyzed; enrichment analysis and Kaplan–Meier survival analysis were performed; data were retrieved from miRanda, miRTarget2, PicTar, PITA, TargetScan, dbSNP, ClinVar, TRANSFAC, DGV, PubMeth, and WebGestalt.