Identification and evaluation of network modules for the prognosis of basal-like breast cancer

Discovery and characterization of functional modules associated with body weight in broilers

Aim of the present study was to investigate whether body weight (BW) in broilers is associated with functional modular genes. To this end, first a GWAS for BW was conducted using 6,598 broilers and the high density SNP array. The next step was to search for positional candidate genes and QTLs within strong LD genomic regions around the significant SNPs. Using all positional candidate genes, a network was then constructed and community structure analysis was performed. Finally, functional enrichment analysis was applied to infer the functional relevance of modular genes. A total number of 645 positional candidate genes were identified in strong LD genomic regions around 11 genome-wide significant markers. 428 of the positional candidate genes were located within growth related QTLs. Community structure analysis detected 5 modules while functional enrichment analysis showed that 52 modular genes participated in developmental processes such as skeletal system development. An additional number of 14 modular genes (GABRG1, NGF, APOBEC2, STAT5B, STAT3, SMAD4, MED1, CACNB1, SLAIN2, LEMD2, ZC3H18, TMEM132D, FRYL and SGCB) were also identified as related to body weight. Taken together, current results suggested a total number of 66 genes as most plausible functional candidates for the trait examined.

Six novel immunoglobulin genes as biomarkers for better prognosis in triple-negative breast cancer by gene co-expression network analysis

Gene co-expression network analysis (GCNA) can detect alterations in regulatory activities in case/control comparisons. We propose a framework to detect novel genes and networks for predicting breast cancer recurrence. Thirty-four prognosis candidate genes were selected based on a literature review. Four Gene Expression Omnibus Series (GSE) microarray datasets (n = 920) were used to create gene co-expression networks based on these candidates. We applied the framework to four comparison groups according to node (+/−) and recurrence (+/−). We identified a sub-network containing two candidate genes (LST1 and IGHM) and six novel genes (IGHA1, IGHD, IGHG1, IGHG3, IGLC2, and IGLJ3) related to B cell-specific immunoglobulin. These novel genes were correlated with recurrence under the control of node status and were found to function as tumor suppressors; higher mRNA expression indicated a lower risk of recurrence (hazard ratio, HR = 0.87, p = 0.001). We created an immune index score by performing principle component analysis and divided the genes into low and high groups. This discrete index significantly predicted relapse-free survival (RFS) (high: HR = 0.77, p = 0.019; low: control). Public tool KM Plotter and TCGA-BRCA gene expression data were used to validate. We confirmed these genes are correlated with RFS and distal metastasis-free survival (DMFS) in triple-negative breast cancer (TNBC) and general breast cancer.

Fibroblast growth factor receptor 4 (FGFR4) and fibroblast growth factor 19 (FGF19) autocrine enhance breast cancer cells survival

Basal-like breast cancer is an aggressive tumor subtype with poor prognosis. The discovery of underlying mechanisms mediating tumor cell survival, and the development of novel agents to target these pathways, is a priority for patients with basal-like breast cancer. From a functional screen to identify key drivers of basal-like breast cancer cell growth, we identified fibroblast growth factor receptor 4 (FGFR4) as a potential mediator of cell survival. We found that FGFR4 mediates cancer cell survival predominantly via activation of PI3K/AKT. Importantly, a subset of basal-like breast cancer cells also secrete fibroblast growth factor 19 (FGF19), a canonical ligand specific for FGFR4. siRNA-mediated silencing of FGF19 or neutralization of extracellular FGF19 by anti-FGF19 antibody (1A6) decreases AKT phosphorylation, suppresses cancer cell growth and enhances doxorubicin sensitivity only in the FGFR4⁺/FGF19⁺ breast cancer cells. Consistently, FGFR4/FGF19 co-expression was also observed in 82 out of 287 (28.6%) primary breast tumors, and their expression is strongly associated with AKT phosphorylation, Ki-67 staining, higher tumor stage and basal-like phenotype. In summary, our results demonstrated the presence of an FGFR4/FGF19 autocrine signaling that mediates the survival of a subset of basal-like breast cancer cells and suggest that inactivation of this autocrine loop may potentially serve as a novel therapeutic intervention for future treatment of breast cancers.