Single Cell Gene Co-Expression Network Reveals FECH/CROT Signature as a Prognostic Marker

Abstract

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.

Construction of a 6-gene prognostic signature to assess prognosis of patients with pancreatic cancer

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Single-cell network biology for resolving cellular heterogeneity in human diseases

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Single-cell analysis of localized low- and high-grade prostate cancers

“…Newly emergent single-cell technologies hold the key to profiling the vast heterogeneous landscapes of prostate cancer [8,[14][15][16][17][18][19]. Recently, whole genomes of 20 single cells from localized prostate tumors were sequenced [20], revealing significant cell-to-cell variation in mutations and complex subclonal trajectories.…”