Abstract

Simple SummaryWe applied the genomic fabric principles for personalized gene therapy to a case of clear cell renal cell carcinoma (ccRCC). Despite decades of research, the process of finding the molecular mechanisms responsible for the disease and, more importantly, the therapeutic solution is still a work in progress. We analyzed the transcriptomes of the chest wall metastasis, two distinct cancer nodules, and the cancer-free surrounding tissue in the surgically removed right kidney of a Fuhrman grade 3 metastatic ccRCC patient. The studies revealed that even histopathologically equally classified cancer nodules from the same kidney have different transcriptomic topologies, requiring tailored therapeutic solutions not only for each patient but even for each cancer nodule. We identified death-associated protein kinase 3 (DAPK3); transcription activation suppressor (TASOR); family with sequence similarity 27, member C, long non-coding RNA (FAM27C); and UDP-N-acetylglucosaminyltransferase subunit (ALG13) as the gene master regulators of the four profiled regions and proposed molecular mechanisms by which expression manipulation of TASOR and ALG13 may selectively destroy the cancer cells without affecting many of the normal cells.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.

Highlights

  • The American Cancer Society estimates that by the end of 2020, the USA will have 73,750(45,520 men, 28,230 women) new cases of kidney (KC) and pelvis cancers, and 14,830 (9860 men and4970 women) deaths because of these cancers [1]

  • In addition to the 13,314 average expression level (AVE) that would be considered in any traditional transcriptomic study, we analyzed 13,314 relative expression variation (REV) and (13,314 × 13,313/2 =) 88,624,641 COR values, a tremendous increase of the transcriptomic information for each region

  • We too have found that cancer regulates numerous genes from major functional pathways

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Summary

Introduction

The American Cancer Society estimates that by the end of 2020, the USA will have 73,750(45,520 men, 28,230 women) new cases of kidney (KC) and pelvis cancers, and 14,830 (9860 men and4970 women) deaths because of these cancers [1]. The American Cancer Society estimates that by the end of 2020, the USA will have 73,750. (45,520 men, 28,230 women) new cases of kidney (KC) and pelvis cancers, and 14,830 4970 women) deaths because of these cancers [1]. If detected and treated early (while the cancer is confined to the kidney), the survival rate is very high (93% at 5 years). For advanced stage, when the cancer has spread to the lungs, brain, bones, and other distant parts of the body, there is only a 12% survival rate at 5 years [1]. The American Joint Committee on Cancer classifies the four KC stages on the basis of the size and extent of the tumor, spread to the nearby nodes, and metastasis to distant cells [3]. Fuhrman grade system [4] of KC stages uses the microscopic appearance of the hematoxylin and eosin-stained cells

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