Preprint Article Version 1 Preserved in Portico This version is not peer-reviewed

Genomic Fabric Remodeling in Prostate Cancer

Version 1 : Received: 8 March 2021 / Approved: 9 March 2021 / Online: 9 March 2021 (08:44:15 CET)

How to cite: Iacobas, S.; Iacobas, D.A. Genomic Fabric Remodeling in Prostate Cancer. Preprints 2021, 2021030242. Iacobas, S.; Iacobas, D.A. Genomic Fabric Remodeling in Prostate Cancer. Preprints 2021, 2021030242.


Prostate cancer is a leading cause of death among men but its genomic characterization and best therapeutic strategy are still under debate. The Genomic Fabric Paradigm (GFP) considers the transcriptome as a multi-dimensional mathematical object subjected to a dynamic set of expression correlations among the genes. Here, GFP is applied to gene expression profiles of three (one primary, and two secondary) cancer nodules and the surrounding normal tissue from a surgically removed prostate tumor. GFP was used to determine the regulation and rewiring of the P53 signaling, apoptosis, prostate cancer and several other pathways involved in survival and proliferation of the cancer cells. Genes responsible for the block of differentiation, evading apoptosis, immortality, insensitivity to anti-growth signals, proliferation, resistance to chemotherapy and sustained angiogenesis were found as differently regulated in the three cancer nodules with respect to the normal tissue. The analysis indicates that even histo-pathologically equally graded cancer nodules from the same tumor have substantially different transcriptomic organizations, raising legitimate questions about the validity of meta-analyses comparing large populations of healthy and cancer humans. The study suggests that GFP may provide a personalized alternative to the biomarkers’ approach of cancer genomics.


apoptosis; evading apoptosis; expression variability; cancer functional pathway; prostate cancer phenotype; immortality; proliferation; P53 signaling; transcriptomic network


Biology and Life Sciences, Biochemistry and Molecular Biology

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