The transition to multicellularity involved evolution of gene regulatory networks (GRN) to coordinate and maintain cellular processes in order to promote organism-level fitness. Transcriptomic analysis of data from The Cancer Genome Atlas has revealed networks acquired during the transition to multicellularity are often broken down in cancer leading to tumorigenesis. We aim to uncover how these pathways are rewired in Prostate cancer (PC) to evade treatment.
We have developed Evolutionary Network Analysis (ENA) a unique multi-omics approach combining genomic evolutionary analysis, transcriptomics and network biology to investigate how GRNs acquired during the transition to multicellularity are rewired in cancer. We applied our ENA to PC patient samples stratified by progression from benign to malignant and primary to metastatic tumours, creating a comprehensive landscape of gene co-expression changes across multiple stages of PC tumour progression.
Our analysis reveals as PC advances to higher Gleason grade groups, genes acquired during the transition to multicellularity become progressively more rewired. Further analysis using gene expression and functional enrichment revealed, new connections facilitate the activation of more ancient unicellular pathways associated with proliferation, angiogenesis, protein trafficking and metabolic processes. By evaluating these changes as markers of multicellularity loss and scoring them across patient clinical outcomes we have identified distinct changes as markers of multicellularity loss indicating tumour behavior.
This study presents a new paradigm in cancer biology investigating how genes cooperate in complex networks to derive tumour progression and evade drug treatment. We have demonstrated how utilizing gene co-expression signatures can be used to gain a comprehensive molecular landscape of PC, which is immensely valuable for the development of more robust therapeutic strategies.