Genomic Fabric Remodeling in Metastatic Clear Cell Renal Cell Carcinoma (ccRCC): A New Paradigm and Proposal for a Personalized Gene Therapy Approach

Abstract

Published transcriptomic data from surgically removed metastatic clear cell renal cell carcinoma samples were analyzed from the genomic fabric paradigm (GFP) perspective to identify the best targets for gene therapy. GFP considers the transcriptome as a multi-dimensional mathematical object constrained by a dynamic set of expression controls and correlations among genes. Every gene in the chest wall metastasis, two distinct cancer nodules, and the surrounding normal tissue of the right kidney was characterized by three independent measures: average expression level, relative expression variation, and expression correlation with each other gene. The analyses determined the cancer-induced regulation, control, and remodeling of the chemokine and vascular endothelial growth factor (VEGF) signaling, apoptosis, basal transcription factors, cell cycle, oxidative phosphorylation, renal cell carcinoma, and RNA polymerase pathways. Interestingly, the three cancer regions exhibited different transcriptomic organization, suggesting that the gene therapy should not be personalized only for every patient but also for each major cancer nodule. The gene hierarchy was established on the basis of gene commanding height, and the gene master regulators DAPK3,TASOR, FAM27C and ALG13 were identified in each profiled region. We delineated the molecular mechanisms by which TASOR overexpression and ALG13 silencing would selectively affect the cancer cells with little consequences for the normal cells.

Personalized 1-2-3-Gene(s) Tickets to Cancer-Free Prostate

“…The independence and complementarity of these types of characteristics was proved in Figure 1. It was also proved in previous publications for apoptosis in human thyroid [21], chemokine signaling in human kidney [18] and mouse cortex [65], evading apoptosis in human prostate [31], ionic channels in mouse heart [66], and PI3K-AKT signaling in mouse hippocampus [67]).…”

“…The power of the Genomic Fabric Paradigm [18] used here comes from extending the workable transcriptomic information by 4-5 orders of magnitude by considering for each quantified gene all the ready available independent characteristics: AVE, REV and COR. While AVE (the average expression level across biological replicas) is used in all studies to determine whether the gene was significantly regulated in cancer with respect to the normal tissue, the ignored REV and COR bring additional fundamental information.…”

“…Our results with distinct regulations even at the cancer nodule level within the same tumor (see Table 3 and Figure 2 in the present report, Figs. 2, 3 and 4 in [18] and [31]) question the idea of "transcriptomic signature", common for large cancer affected populations. We consider such cancer transcriptomic signatures as artefacts of the meta-analyses combining transcriptomic data from many individuals (not always demographically grouped as race, age and other major criterion), collected by numerous labs using (some)times distinct transcriptomic platforms and experimental protocols.…”

“…In this report for metabolism (Figures 5 and 6) and in previous publications for basal transcription, RNA polymerase and cell-cycle [18], apoptosis [21], and enzymes [31], we included predictions of what might happen when targeting the GMR by a gene therapy. Unfortunately, there was no possibility to validate experimentally any of these predic-tions on the patients from which we have collected the prostate tissues.…”

“…This tumor heterogeneity [11,12], both at histo-pathological and transcriptomic [13,14] levels within the prostate of one patient as well as among patients, complicates significantly the treatment options [15][16][17]. Moreover, together with the biomarker(s) whose altered sequence or expression level is thought indicative for that cancer type, unique combinations of hundreds other genes are mutated or/and regulated in each cancer nodule with respect to the surrounding, cancer-free tissue [18]. The unique combination of affected genes is the direct result of the never repeatable association of favoring factors affecting the entire body (race, age, medical history, habits, diet, stress, climate etc.)…”