Garcia-Cortes, D. | bioRxiv Science

bioRxiv2022

Loss of long-range co-expression is a common trait in cancer

Cancer cells display common features and enabling characteristics collectively known as the Hallmarks of Cancer, which occur alongside alterations in the regulatory mechanisms controlling gene transcription. Gene co-expression networks (GCNs) provide a framework to identify correlated gene sets that may share these regulatory mechanisms. Previously, we reported the loss of long-range co-expression in breast, lung, kidney, and hematopoietic cancer GCNs. Here, we expand the analysis to fifteen tissues, comprising 8,772 samples from two independent datasets. Unlike healthy phenotypes, cancer GCNs show that the strongest gene-pair interactions are intra-chromosomal, with their strength decaying as base-pair distance increases. Tumor GCN communities are strongly associated with cancerrelated processes and are enriched in gene families located on the same chromosome. In contrast, normal GCN communities are linked to metabolic and cell maintenance processes. Riboproteins remain highly co-expressed in both cancer and normal GCNs, highlighting their importance for cell viability. Notably, in other chronic diseases, such as Type-2 Diabetes and Alzheimers disease, the loss of long-range co-expression is absent, suggesting it is a distinctive feature of cancer.

cancer biology↗

bioRxiv2018

Loss of Trans Regulation in Breast Cancer Molecular Subtypes

Breast carcinomas are characterized by anomalous gene regulatory programs. As is well known, gene expression programs are able to shape phenotypes. Hence, the understanding of gene co-expression may shed light on the underlying mechanisms behind the transcriptional regulatory programs affecting tumor development and evolution. For instance, in breast cancer, there is a clear loss of inter-chromosomal (trans-) co-expression, compared with healthy tissue. At the same time cis- (intra-chromosomal) interactions are favored in breast tumors. In order to have a deeper understanding of regulatory phenomena in cancer, here, we constructed Gene Co-expression Networks by using 848 RNA-seq whole-genome samples corresponding to the four breast cancer molecular subtypes, as well as healthy tissue. We quantify the cis-/trans- co-expression imbalance in all phenotypes. Additionally, we measured the association between co-expression and physical distance between genes, and characterized the proportion of intra/inter-cytoband interactions per phenotype. We confirmed loss of trans- co-expression in all molecular subtypes. We also observed that gene cisco-expression decays abruptly with distance in all tumors in contrast with healthy tissue. We observed co-expressed gene hotspots, that tend to be connected at cytoband regions, and coincide accurately with already known copy number altered regions, such as Chr17q12, or Chr8q24.3 for all subtypes. Our methodology recovered different alterations already reported for specific breast cancer subtypes, showing how co-expression network approaches might help to capture distinct events that modify the cell regulatory program.

systems biology↗