Analysis of LAGEs Family Gene Signature and Prognostic Relevance in Breast Cancer.
Hoang Dang Khoa TaWan-Chun TangNam Nhut PhanGangga AnuragaSz-Ying HouChung-Chieh ChiaoYen-Hsi LiuYung-Fu WuKuen-Haur LeeChih-Yang WangPublished in: Diagnostics (Basel, Switzerland) (2021)
Breast cancer (BRCA) is one of the most complex diseases and involves several biological processes. Members of the L-antigen (LAGE) family participate in the development of various cancers, but their expressions and prognostic values in breast cancer remain to be clarified. High-throughput methods for exploring disease progression mechanisms might play a pivotal role in the improvement of novel therapeutics. Therefore, gene expression profiles and clinical data of LAGE family members were acquired from the cBioportal database, followed by verification using the Oncomine and The Cancer Genome Atlas (TCGA) databases. In addition, the Kaplan-Meier method was applied to explore correlations between expressions of LAGE family members and prognoses of breast cancer patients. MetaCore, GlueGo, and GluePedia were used to comprehensively study the transcript expression signatures of LAGEs and their co-expressed genes together with LAGE-related signal transduction pathways in BRCA. The result indicated that higher LAGE3 messenger (m)RNA expressions were observed in BRCA tissues than in normal tissues, and they were also associated with the stage of BRCA patients. Kaplan-Meier plots showed that overexpression of LAGE1, LAGE2A, LAGE2B, and LAGE3 were highly correlated to poor survival in most types of breast cancer. Significant associations of LAGE family genes were correlated with the cell cycle, focal adhesion, and extracellular matrix (ECM) receptor interactions as indicated by functional enrichment analyses. Collectively, LAGE family members' gene expression levels were related to adverse clinicopathological factors and prognoses of BRCA patients; therefore, LAGEs have the potential to serve as prognosticators of BRCA patients.
Keyphrases
- end stage renal disease
- gene expression
- cell cycle
- chronic kidney disease
- ejection fraction
- newly diagnosed
- genome wide
- extracellular matrix
- high throughput
- cell proliferation
- prognostic factors
- peritoneal dialysis
- breast cancer risk
- dna methylation
- emergency department
- squamous cell carcinoma
- small molecule
- patient reported outcomes
- poor prognosis
- big data
- risk assessment
- climate change
- genome wide identification
- long non coding rna
- deep learning
- genome wide analysis