Single Cell Gene Co-Expression Network Reveals FECH/CROT Signature as a Prognostic Marker.
Xin ChenLingling HuYuan WangWeijun SunChao YangPublished in: Cells (2019)
Aberrant activation of signaling pathways is frequently observed and reported to be associated with the progression and poor prognosis of prostate cancer (PCa). We aimed to identify key biological processes regulated by androgen receptor (AR) using gene co-expression network from single cell resolution. The bimodal index was used to evaluate whether two subpopulations exist among the single cells. Gene expression among single cells revealed averaging pitfalls and bimodality pattern. Weighted gene co-expression network analysis (WGCNA) was used to identify modules of highly correlated genes. Twenty-nine gene modules were identified and AR-regulated modules were screened by significantly overlapping reported androgen induced differentially expressed genes. The biological function "generation of precursor metabolites and energy" was significantly enriched by AR-regulated modules with bimodality, presenting differential androgen response among subpopulations. Integrating with public ChIP-seq data, two genes FECH, and CROT has AR binding sites. Public in vitro studies also show that androgen regulates FECH and CROT. After receiving androgen deprivation therapy, patients lowly express FECH and CROT. Further survival analysis indicates that FECH/CROT signature can predict PCa recurrence. We reveal the heterogeneous function of "generation of precursor metabolites and energy" upon androgen stimulation from the perspective of single cells. Inhibitors targeting this biological process will facilitate to prevent prostate cancer progression.
Keyphrases
- poor prognosis
- network analysis
- genome wide
- single cell
- prostate cancer
- genome wide identification
- induced apoptosis
- dna methylation
- long non coding rna
- gene expression
- copy number
- rna seq
- cell cycle arrest
- transcription factor
- healthcare
- signaling pathway
- endoplasmic reticulum stress
- high throughput
- ms ms
- radical prostatectomy
- end stage renal disease
- newly diagnosed
- mental health
- chronic kidney disease
- magnetic resonance
- stem cells
- magnetic resonance imaging
- binding protein
- diabetic rats
- machine learning
- drug delivery
- oxidative stress
- patient reported
- peritoneal dialysis
- circulating tumor cells
- big data
- artificial intelligence