Papillary Thyroid Cancer Remodels the Genetic Information Processing Pathways.

The genetic causes of the differentiated, highly treatable, and mostly non-fatal papillary thyroid cancer (PTC) are not yet fully understood. The mostly accepted PTC etiology blames the altered sequence or/and expression level of certain biomarker genes. However, tumor heterogeneity and the patient's unique set of favoring factors question the fit-for-all gene biomarkers. Publicly accessible gene expression profiles of the cancer nodule and the surrounding normal tissue from a surgically removed PTC tumor were re-analyzed to determine the cancer-induced alterations of the genomic fabrics responsible for major functional pathways. Tumor data were compared with those of standard papillary and anaplastic thyroid cancer cell lines. We found that PTC regulated numerous genes associated with DNA replication, repair, and transcription. Results further indicated that changes of the gene networking in functional pathways and the homeostatic control of transcript abundances also had major contributions to the PTC phenotype occurrence. The purpose to proliferate and invade the entire gland may explain the substantial transcriptomic differences we detected between the cells of the cancer nodule and those spread in homo-cellular cultures (where they need only to survive). In conclusion, the PTC etiology should include the complex molecular mechanisms involved in the remodeling of the genetic information processing pathways.

Advanced Molecular Solutions for Cancer Therapy-The Good, the Bad, and the Ugly of the Biomarker Paradigm.

Identifying the most effective actionable molecules whose "smart" manipulation might selectively kill/slow down/stop the proliferation of cancer cells, with few side effects on the normal cells of the tissue, was for decades the single major objective of countless investigators [...].

Genomic Fabrics of the Excretory System's Functional Pathways Remodeled in Clear Cell Renal Cell Carcinoma.

Clear cell renal cell carcinoma (ccRCC) is the most frequent form of kidney cancer. Metastatic stages of ccRCC reduce the five-year survival rate to 15%. In this report, we analyze the ccRCC-induced remodeling of the five KEGG-constructed excretory functional pathways in a surgically removed right kidney and its metastasis in the chest wall from the perspective of the Genomic Fabric Paradigm (GFP). The GFP characterizes every single gene in each region by these independent variables: the average expression level (AVE), relative expression variability (REV), and expression correlation (COR) with each other gene. While the traditional approach is limited to only AVE analysis, the novel REV analysis identifies the genes whose correct expression level is critical for cell survival and proliferation. The COR analysis determines the real gene networks responsible for functional pathways. The analyses covered the pathways for aldosterone-regulated sodium reabsorption, collecting duct acid secretion, endocrine and other factor-regulated sodium reabsorption, proximal tubule bicarbonate reclamation, and vasopressin-regulated water reabsorption. The present study confirms the conclusion of our previously published articles on prostate and kidney cancers that even equally graded cancer nodules from the same tumor have different transcriptomic topologies. Therefore, the personalization of anti-cancer therapy should go beyond the individual, to his/her major cancer nodules.

Metabolic Deregulation in Pulmonary Hypertension.

The high morbidity and mortality rate of pulmonary arterial hypertension (PAH) is partially explained by metabolic deregulation. The present study complements our previous publication in "Genes" by identifying significant increases of the glucose transporter solute carrier family 2 (Slc2a1), beta nerve growth factor (Ngf), and nuclear factor erythroid-derived 2-like 2 (Nfe2l2) in three standard PAH rat models. PAH was induced by subjecting the animals to hypoxia (HO), or by injecting with monocrotaline in either normal (CM) or hypoxic (HM) atmospheric conditions. The Western blot and double immunofluorescent experiments were complemented with novel analyses of previously published transcriptomic datasets of the animal lungs from the perspective of the Genomic Fabric Paradigm. We found substantial remodeling of the citrate cycle, pyruvate metabolism, glycolysis/gluconeogenesis, and fructose and mannose pathways. According to the transcriptomic distance, glycolysis/gluconeogenesis was the most affected functional pathway in all three PAH models. PAH decoupled the coordinated expression of many metabolic genes, and replaced phosphomannomutase 2 (Pmm2) with phosphomannomutase 1 (Pmm1) in the center of the fructose and mannose metabolism. We also found significant regulation of key genes involved in PAH channelopathies. In conclusion, our data show that metabolic dysregulation is a major PAH pathogenic factor.

Molecules at Play in Cancer.

Despite its wide range of incidence, cancer can spontaneously occur in any part of the body and invade regions other than the originally affected tissue [...].

Theory and Applications of the (Cardio) Genomic Fabric Approach to Post-Ischemic and Hypoxia-Induced Heart Failure.

The genomic fabric paradigm (GFP) characterizes the transcriptome topology by the transcripts' abundances, the variability of the expression profile, and the inter-coordination of gene expressions in each pathophysiological condition. The expression variability analysis provides an indirect estimate of the cell capability to limit the stochastic fluctuations of the expression levels of key genes, while the expression coordination analysis determines the gene networks in functional pathways. This report illustrates the theoretical bases and the mathematical framework of the GFP with applications to our microarray data from mouse models of post ischemic, and constant and intermittent hypoxia-induced heart failures. GFP analyses revealed the myocardium priorities in keeping the expression of key genes within narrow intervals, determined the statistically significant gene interlinkages, and identified the gene master regulators in the mouse heart left ventricle under normal and ischemic conditions. We quantified the expression regulation, alteration of the expression control, and remodeling of the gene networks caused by the oxygen deprivation and determined the efficacy of the bone marrow mono-nuclear stem cell injections to restore the normal transcriptome. Through the comprehensive assessment of the transcriptome, GFP would pave the way towards the development of personalized gene therapy of cardiac diseases.

Personalized 3-Gene Panel for Prostate Cancer Target Therapy.

Many years and billions spent for research did not yet produce an effective answer to prostate cancer (PCa). Not only each human, but even each cancer nodule in the same tumor, has unique transcriptome topology. The differences go beyond the expression level to the expression control and networking of individual genes. The unrepeatable heterogeneous transcriptomic organization among men makes the quest for universal biomarkers and "fit-for-all" treatments unrealistic. We present a bioinformatics procedure to identify each patient's unique triplet of PCa Gene Master Regulators (GMRs) and predict consequences of their experimental manipulation. The procedure is based on the Genomic Fabric Paradigm (GFP), which characterizes each individual gene by the independent expression level, expression variability and expression coordination with each other gene. GFP can identify the GMRs whose controlled alteration would selectively kill the cancer cells with little consequence on the normal tissue. The method was applied to microarray data on surgically removed prostates from two men with metastatic PCas (each with three distinct cancer nodules), and DU145 and LNCaP PCa cell lines. The applications verified that each PCa case is unique and predicted the consequences of the GMRs' manipulation. The predictions are theoretical and need further experimental validation.

Retinal Genomic Fabric Remodeling after Optic Nerve Injury.

Glaucoma is a multifactorial neurodegenerative disease, characterized by degeneration of the retinal ganglion cells (RGCs). There has been little progress in developing efficient strategies for neuroprotection in glaucoma. We profiled the retina transcriptome of Lister Hooded rats at 2 weeks after optic nerve crush (ONC) and analyzed the data from the genomic fabric paradigm (GFP) to bring additional insights into the molecular mechanisms of the retinal remodeling after induction of RGC degeneration. GFP considers three independent characteristics for the expression of each gene: level, variability, and correlation with each other gene. Thus, the 17,657 quantified genes in our study generated a total of 155,911,310 values to analyze. This represents 8830x more data per condition than a traditional transcriptomic analysis. ONC led to a 57% reduction in RGC numbers as detected by retrograde labeling with 1,1'-dioctadecyl-3,3,3,3'-tetramethylindocarbocyanine perchlorate (DiI). We observed a higher relative expression variability after ONC. Gene expression stability was used as a measure of transcription control and disclosed a robust reduction in the number of very stably expressed genes. Predicted protein-protein interaction (PPI) analysis with STRING revealed axon and neuron projection as mostly decreased processes, consistent with RGC degeneration. Conversely, immune response PPIs were found among upregulated genes. Enrichment analysis showed that complement cascade and Notch signaling pathway, as well as oxidative stress and kit receptor pathway were affected after ONC. To expand our studies of altered molecular pathways, we examined the pairwise coordination of gene expressions within each pathway and within the entire transcriptome using Pearson correlations. ONC increased the number of synergistically coordinated pairs of genes and the number of similar profiles mainly in complement cascade and Notch signaling pathway. This deep bioinformatic study provided novel insights beyond the regulation of individual gene expression and disclosed changes in the control of expression of complement cascade and Notch signaling functional pathways that may be relevant for both RGC degeneration and remodeling of the retinal tissue after ONC.

Powerful quantifiers for cancer transcriptomics.

Every day, investigators find a new link between a form of cancer and a particular alteration in the sequence or/and expression level of a key gene, awarding this gene the title of "biomarker". The clinician may choose from numerous available panels to assess the type of cancer based on the mutation or expression regulation ("transcriptomic signature") of "driver" genes. However, cancer is not a "one-gene show" and, together with the alleged biomarker, hundreds other genes are found as mutated or/and regulated in cancer samples. Regardless of the platform, a well-designed transcriptomic study produces three independent features for each gene: Average expression level, expression variability and coordination with expression of each other gene. While the average expression level is used in all studies to identify what genes were up-/down-regulated or turn on/off, the other two features are unfairly ignored. We use all three features to quantify the transcriptomic change during the progression of the disease and recovery in response to a treatment. Data from our published microarray experiments on cancer nodules and surrounding normal tissue from surgically removed tumors prove that the transcriptomic topologies are not only different in histopathologically distinct regions of a tumor but also dynamic and unique for each human being. We show also that the most influential genes in cancer nodules [the Gene Master Regulators (GMRs)] are significantly less influential in the normal tissue. As such, "smart" manipulation of the cancer GMRs expression may selectively kill cancer cells with little consequences on the normal ones. Therefore, we strongly recommend a really personalized approach of cancer medicine and present the experimental procedure and the mathematical algorithm to identify the most legitimate targets (GMRs) for gene therapy.

Gene expression changes associated with myocarditis and fibrosis in hearts of mice with chronic chagasic cardiomyopathy.

Chronic chagasic cardiomyopathy is a leading cause of heart failure in Latin American countries. About 30% of Trypanosoma cruzi-infected individuals develop this severe symptomatic form of the disease, characterized by intense inflammatory response accompanied by fibrosis in the heart. We performed an extensive microarray analysis of hearts from a mouse model of this disease and identified significant alterations in expression of approximately 12% of the sampled genes. Extensive up-regulations were associated with immune-inflammatory responses (chemokines, adhesion molecules, cathepsins, and major histocompatibility complex molecules) and fibrosis (extracellular matrix components, lysyl oxidase, and tissue inhibitor of metalloproteinase 1). Our results indicate potentially relevant factors involved in the pathogenesis of the disease that may provide new therapeutic targets in chronic Chagas disease.