35 research outputs found

    Cancer Biomarker Discovery: The Entropic Hallmark

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    Background: It is a commonly accepted belief that cancer cells modify their transcriptional state during the progression of the disease. We propose that the progression of cancer cells towards malignant phenotypes can be efficiently tracked using high-throughput technologies that follow the gradual changes observed in the gene expression profiles by employing Shannon's mathematical theory of communication. Methods based on Information Theory can then quantify the divergence of cancer cells' transcriptional profiles from those of normally appearing cells of the originating tissues. The relevance of the proposed methods can be evaluated using microarray datasets available in the public domain but the method is in principle applicable to other high-throughput methods. Methodology/Principal Findings: Using melanoma and prostate cancer datasets we illustrate how it is possible to employ Shannon Entropy and the Jensen-Shannon divergence to trace the transcriptional changes progression of the disease. We establish how the variations of these two measures correlate with established biomarkers of cancer progression. The Information Theory measures allow us to identify novel biomarkers for both progressive and relatively more sudden transcriptional changes leading to malignant phenotypes. At the same time, the methodology was able to validate a large number of genes and processes that seem to be implicated in the progression of melanoma and prostate cancer. Conclusions/Significance: We thus present a quantitative guiding rule, a new unifying hallmark of cancer: the cancer cell's transcriptome changes lead to measurable observed transitions of Normalized Shannon Entropy values (as measured by high-throughput technologies). At the same time, tumor cells increment their divergence from the normal tissue profile increasing their disorder via creation of states that we might not directly measure. This unifying hallmark allows, via the the Jensen-Shannon divergence, to identify the arrow of time of the processes from the gene expression profiles, and helps to map the phenotypical and molecular hallmarks of specific cancer subtypes. The deep mathematical basis of the approach allows us to suggest that this principle is, hopefully, of general applicability for other diseases

    Antagonism of p66shc by melanoma inhibitory activity

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    Hepatitis C virus RNA and core protein in kidney glomerular and tubular structures isolated with laser capture microdissection

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    The role of hepatits C virus (HCV) in the production of renal injury has been extensively investigated, though with conflicting results. Laser capture microdissection (LCM) was performed to isolate and collect glomeruli and tubules from 20 consecutive chronically HCV-infected patients, namely 6 with membranoproliferative glomerulonephritis, 4 with membranous glomerulonephritis, 7 with focal segmental glomerulosclerosis and 3 with IgA-nephropathy. RNA for amplification of specific viral sequences was provided by terminal continuation methodology and compared with the expression profile of HCV core protein. For each case two glomeruli and two tubular structures were microdissected and processed. HCV RNA sequences were demonstrated in 26 (65%) of 40 glomeruli, but in only 4 (10%) of the tubules (P < 0·05). HCV core protein was concomitant with viral sequences in the glomeruli and present in 31 of the 40 tubules. HCV RNA and/or HCV core protein was found in all four disease types. The immunohistochemical picture of HCV core protein was compared with the LCM-based immunoassays of the adjacent tissue sections. Immune deposits were detected in 7 (44%) of 16 biopsy samples shown to be positive by extraction methods. The present study indicates that LCM is a reliable method for measuring both HCV RNA genomic sequences and HCV core protein in kidney functional structures from chronically HCV-infected patients with different glomerulopathies and provides a useful baseline estimate to define the role of HCV in the production of renal injury. The different distribution of HCV RNA and HCV-related proteins may reflect a peculiar ‘affinity’ of kidney microenvironments for HCV and point to distinct pathways of HCV-related damage in glomeruli and tubules
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