Network-Based and Machine-Learning Approaches Identify Diagnostic and Prognostic Models for EMT-Type Gastric Tumors.

The microsatellite stable/epithelial-mesenchymal transition (MSS/EMT) subtype of gastric cancer represents a highly aggressive class of tumors associated with low rates of survival and considerably high probabilities of recurrence. In the era of precision medicine, the accurate and prompt diagnosis of tumors of this subtype is of vital importance. In this study, we used Weighted Gene Co-expression Network Analysis (WGCNA) to identify a differentially expressed co-expression module of mRNAs in EMT-type gastric tumors. Using network analysis and linear discriminant analysis, we identified mRNA motifs and microRNA-based models with strong prognostic and diagnostic relevance: three models comprised of (i) the microRNAs miR-199a-5p and miR-141-3p, (ii) EVC/EVC2/GLI3, and (iii) PDE2A/GUCY1A1/GUCY1B1 gene expression profiles distinguish EMT-type tumors from other gastric tumors with high accuracy (Area Under the Receiver Operating Characteristic Curve (AUC) = 0.995, AUC = 0.9742, and AUC = 0.9717; respectively). Additionally, the DMD/ITGA1/CAV1 motif was identified as the top motif with consistent relevance to prognosis (hazard ratio > 3). Molecular functions of the members of the identified models highlight the central roles of MAPK, Hh, and cGMP/cAMP signaling in the pathology of the EMT subtype of gastric cancer and underscore their potential utility in precision therapeutic approaches.

Design, construction and in vivo functional assessment of a hinge truncated sFLT01.

Gene therapy for the treatment of ocular neovascularization has reached clinical trial phases. The AAV2-sFLT01 construct was already evaluated in a phase 1 open-label trial administered intravitreally to patients with advanced neovascular age-related macular degeneration. SFLT01 protein functions by binding to VEGF and PlGF molecules and inhibiting their activities simultaneously. It consists of human VEGFR1/Flt-1 (hVEGFR1), a polyglycine linker, and the Fc region of human IgG1. The IgG1 upper hinge region of the sFLT01 molecule makes it vulnerable to radical attacks and prone to causing immune reactions. This study pursued two goals: (i) minimizing the immunogenicity and vulnerability of the molecule by designing a truncated molecule called htsFLT01 (hinge truncated sFLT01) that lacked the IgG1 upper hinge and lacked 2 amino acids from the core hinge region; and (ii) investigating the structural and functional properties of the aforesaid chimeric molecule at different levels (in silico, in vitro, and in vivo). Molecular dynamics simulations and molecular mechanics energies combined with Poisson-Boltzmann and surface area continuum solvation calculations revealed comparable free energy of binding and binding affinity for sFLT01 and htsFLT01 to their cognate ligands. Conditioned media from human retinal pigment epithelial (hRPE) cells that expressed htsFLT01 significantly reduced tube formation in HUVECs. The AAV2-htsFLT01 virus suppressed vascular development in the eyes of newborn mice. The htsFLT01 gene construct is a novel anti-angiogenic tool with promising improvements compared to existing treatments.

Prospects and challenges of cancer systems medicine: from genes to disease networks.

It is becoming evident that holistic perspectives toward cancer are crucial in deciphering the overwhelming complexity of tumors. Single-layer analysis of genome-wide data has greatly contributed to our understanding of cellular systems and their perturbations. However, fundamental gaps in our knowledge persist and hamper the design of effective interventions. It is becoming more apparent than ever, that cancer should not only be viewed as a disease of the genome but as a disease of the cellular system. Integrative multilayer approaches are emerging as vigorous assets in our endeavors to achieve systemic views on cancer biology. Herein, we provide a comprehensive review of the approaches, methods and technologies that can serve to achieve systemic perspectives of cancer. We start with genome-wide single-layer approaches of omics analyses of cellular systems and move on to multilayer integrative approaches in which in-depth descriptions of proteogenomics and network-based data analysis are provided. Proteogenomics is a remarkable example of how the integration of multiple levels of information can reduce our blind spots and increase the accuracy and reliability of our interpretations and network-based data analysis is a major approach for data interpretation and a robust scaffold for data integration and modeling. Overall, this review aims to increase cross-field awareness of the approaches and challenges regarding the omics-based study of cancer and to facilitate the necessary shift toward holistic approaches.

Network analysis and the impact of Aflibercept on specific mediators of angiogenesis in HUVEC cells.

Angiogenesis, inflammation and endothelial cells' migration and proliferation exert fundamental roles in different diseases. However, more studies are needed to identify key proteins and pathways involved in these processes. Aflibercept has received the approval of the US Food and Drug Administration (FDA) for the treatment of wet AMD and colorectal cancer. Moreover, the effect of Aflibercept on VEGFR2 downstream signalling pathways has not been investigated yet. Here, we integrated text mining data, protein-protein interaction networks and multi-experiment microarray data to specify candidate genes that are involved in VEGFA/VEGFR2 signalling pathways. Network analysis of candidate genes determined the importance of the nominated genes via different centrality parameters. Thereupon, several genes-with the highest centrality indexes-were recruited to investigate the impact of Aflibercept on their expression pattern in HUVEC cells. Real-time PCR was performed, and relative expression of the specific genes revealed that Aflibercept modulated angiogenic process by VEGF/PI3KA/AKT/mTOR axis, invasion by MMP14/MMP9 axis and inflammation-related angiogenesis by IL-6-STAT3 axis. Data showed Aflibercept simultaneously affected these processes and determined the nominated axes that had been affected by the drug. Furthermore, integrating the results of Aflibercept on expression of candidate genes with the current network analysis suggested that resistance against the Aflibercept effect is a plausible process in HUVEC cells.

sFLT01 modulates invasion and metastasis in prostate cancer DU145 cells by inhibition of VEGF/GRP78/MMP2&9 axis.

BACKGROUND: About 90% of cancer-related deaths are due to metastasis of cancer cells, and angiogenesis is a critical step in this process. sFLT01 is a novel fusion protein and a dual-targeting agent that neutralizes both VEGF and PlGF proangiogenic activities. GRP78 dual effect in tumor growth and angiogenesis could be activated under VEGF stimulation. The current study was designed to investigate the inhibitory impact of sFLT01 protein on VEGF/GRP78 axis. To this point, sFLT01 construct was synthesized, recombinant plasmid was expressed in eukaryotic host cells, sFLT01-HisTag protein was extracted and analyzed. The functional activity of sFLT01 on VEGF-enhanced tube formation and angiogenesis of HUVEC cells were examined. Eventually, the inhibitory impact of sFLT01 on growth, invasiveness, and migration of human prostate cancer cell line, DU145, was assessed. Real-time PCR evaluated the level of GRP78 and its effect on the downstream factors; matrix metallopeptidase proteins 2&9 (MMP2&9) along with tissue inhibitor of metalloproteinase proteins1&2 (TIMP1&2) under sFLT01 stimulation. RESULTS: According to the data, sFLT01 protein showed modulatory impact on proliferation, invasion, and migration of DU145 cells along with the potential of HUVECs angiogenesis. Real-Time PCR analysis depicted a significant downregulation in GRP78, MMP2 and MMP9 transcripts' levels, and a subsequent elevation of TIMP1 and TIMP2 expression under sFLT01 stimulation was detected. CONCLUSION: Overall, these data indicated that the inhibitory impact of sFLT01 on cancer cells growth and invasiveness could be mediated through the modulation of VEGF/GRP78/MMP2&9 axis and activation of TIMPs.

Optogenetic control of neural differentiation in Opto-mGluR6 engineered retinal pigment epithelial cell line and mesenchymal stem cells.

In retinal degenerative disorders, when neural retinal cells are damaged, cell transplantation is one of the most promising therapeutic approaches. Optogenetic technology plays an essential role in the neural differentiation of stem cells via membrane depolarization. This study explored the efficacy of blue light stimulation in neuroretinal differentiation of Opto-mGluR6-engineered mouse retinal pigment epithelium (mRPE) and bone marrow mesenchymal stem cells (BMSCs). mRPE and BMSCs were selected for optogenetic study due to their capability to differentiate into retinal-specific neurons. BMSCs were isolated and phenotypically characterized by the expression of mesenchymal stem cell-specific markers, CD44 (99%) and CD105 (98.8%). mRPE culture identity was confirmed by expression of RPE-specific marker, RPE65, and epithelial cell marker, ZO-1. mRPE cells and BMSCs were transduced with AAV-MCS-IRES-EGFP-Opto-mGluR6 viral vector and stimulated for 5 days with blue light (470 nm). RNA and protein expression of Opto-mGluR6 were verified. Optogenetic stimulation-induced elevated intracellular Ca2+ levels in mRPE- and BMS-treated cells. Significant increase in cell growth rate and G1/S phase transition were detected in mRPE- and BMSCs-treated cultures. Pou4f1, Dlx2, Eomes, Barlh2, Neurod2, Neurod6, Rorb, Rxrg, Nr2f2, Ascl1, Hes5, and Sox8 were overexpressed in treated BMSCs and Barlh2, Rorb, and Sox8 were overexpressed in treated mRPE cells. Expression of Rho, Thy1, OPN1MW, Recoverin, and CRABP, as retinal-specific neuron markers, in mRPE and BMS cell cultures were demonstrated. Differentiation of ganglion, amacrine, photoreceptor cells, and bipolar and Muller precursors were determined in BMSCs-treated culture and were compared with mRPE. mRPE cells represented more abundant terminal Muller glial differentiation compared with BMSCs. Our results also demonstrated that optical stimulation increased the intracellular Ca2+ level and proliferation and differentiation of Opto-mGluR6-engineered BMSCs. It seems that optogenetic stimulation of mRPE- and BMSCs-engineered cells would be a potential therapeutic approach for retinal degenerative disorders.

Evaluation of the GABAA Receptor Expression and the Effects of Muscimol on the Activity of Wide Dynamic Range Neurons Following Chronic Constriction Injury of Sciatic Nerve in Rats.

INTRODUCTION: The modality of γ-aminobutyric acid type a receptors (GABAA) controls dorsal horn neuronal excitability and inhibits sensory information. This study aimed to investigate the expression of the GABAA receptor and the effects of its agonist muscimol on Wide Dynamic Range (WDR) neuronal activity in the Chronic Constriction Injury (CCI) model of neuropathic pain. METHODS: Adult male Wistar rats weighing 200 to 250 g were used to induce CCI neuropathy. Fourteen days after surgery, muscimol (0.5, 1, and 2 mg/kg IP) was injected. Then, the behavioral tests were performed. After that, the animals were killed, and the lumbar segments of the spinal cords were collected for Western blot analysis of the GABAA receptor α1 subunit expression. The electrophysiological properties of WDR neurons were studied by single-unit recordings in separate groups 14 days after CCI. RESULTS: The outcomes indicated the development of thermal hyperalgesia and mechanical allodynia after neuropathy; nonetheless, the expression of the GABAA receptor α1 subunit did not change significantly. Moreover, the evoked responses of the WDR neurons to electrical, mechanical, and thermal stimuli increased considerably. Fourteen days after CCI, muscimol administration decreased thermal hyperalgesia, mechanical allodynia, and hyper-responsiveness of the WDR neurons in CCI rats. CONCLUSION: The modulation of the spinal GABAA receptors after nerve injury can offer further insights to design new therapeutic agents to reduce neuropathic pain symptoms.

A computational model of stem cell molecular mechanism to maintain tissue homeostasis.

Stem cells, with their capacity to self-renew and to differentiate to more specialized cell types, play a key role to maintain homeostasis in adult tissues. To investigate how, in the dynamic stochastic environment of a tissue, non-genetic diversity and the precise balance between proliferation and differentiation are achieved, it is necessary to understand the molecular mechanisms of the stem cells in decision making process. By focusing on the impact of stochasticity, we proposed a computational model describing the regulatory circuitry as a tri-stable dynamical system to reveal the mechanism which orchestrate this balance. Our model explains how the distribution of noise in genes, linked to the cell regulatory networks, affects cell decision-making to maintain homeostatic state. The noise effect on tissue homeostasis is achieved by regulating the probability of differentiation and self-renewal through symmetric and/or asymmetric cell divisions. Our model reveals, when mutations due to the replication of DNA in stem cell division, are inevitable, how mutations contribute to either aging gradually or the development of cancer in a short period of time. Furthermore, our model sheds some light on the impact of more complex regulatory networks on the system robustness against perturbations.

Phylogenetic and phylodynamic study of Human T-cell lymphotropic virus Type 1 (HTLV-1) in Iran.

Human T-lymphotropic virus type-1 (HTLV-1) is a retrovirus that causes the neurological disorder HTLV-1 associated myelopathy/ tropical spastic paraparesis (HAM/TSP) and/or adult T-cell leukemia/lymphoma (ATLL). Iran is one of the endemic regions of the HTLV-1 in the Middle East. To infer the origin of the virus in Iran and to follow the movements of human population and routes of virus spread to this country, phylogenetic and phylodynamic analyses were performed. To this purpose, the long terminal repeat (LTR) region of HTLV-1 was used. New LTR sequences were obtained from 100 blood samples which infected with HTLV-1. Moreover, all Iranian LTR sequences which have been reported so far, were obtained from GenBank database. Sequences were aligned and maximum-likelihood and Bayesian tree topologies were explored. After identification of Iranian specific cluster, molecular-clock and coalescent models were used to estimate time to the most recent common ancestor (tMRCA). Bayesian Skyline Plots (BSP), representing population dynamics HTLV-1 strains back to the MRCA, were estimated using BEAST software. Phylogenetic analysis demonstrated that the Iranian, Kuwaiti, German, Israelite and southern Indian isolates are located within the widespread "transcontinental" subgroup A clade of HTLV-1 Cosmopolitan subtype a. Molecular clock analysis of the Iranian cluster dated back their respective tMRCA to be 1290 AC with a 95% HPD confidence intervals (918, 1517). BSPs indicated a rapid exponential growth rate in the effective number of infections prior the 15th century. Our results support the hypothesis of a multiple introductions of HTLV-1 into Iran with the majority of introductions occurring in prior the 15th century, at the same time the Mongol invasion of Iran. Our results further suggest that HTLV-1 introduction into Iran was facilitated by the commercial/migratory linkage as known as the ancient Silk Road which linked China to Antioch (now in Turkey).

Integrative Analysis of Breast Cancer Cells Reveals an Epithelial-Mesenchymal Transition Role in Adaptation to Acidic Microenvironment.

Early ducts of breast tumors are unequivocally acidic. High rates of glycolysis combined with poor perfusion lead to a congestion of acidic metabolites in the tumor microenvironment, and pre-malignant cells must adapt to this acidosis to thrive. Adaptation to acidosis selects cancer cells that can thrive in harsh conditions and are capable of outgrowing the normal or non-adapted neighbors. This selection is usually accompanied by phenotypic change. Epithelial mesenchymal transition (EMT) is one of the most important switches correlated to malignant tumor cell phenotype and has been shown to be induced by tumor acidosis. New evidence shows that the EMT switch is not a binary system and occurs on a spectrum of transition states. During confirmation of the EMT phenotype, our results demonstrated a partial EMT phenotype in our acid-adapted cell population. Using RNA sequencing and network analysis we found 10 dysregulated network motifs in acid-adapted breast cancer cells playing a role in EMT. Our further integrative analysis of RNA sequencing and SILAC proteomics resulted in recognition of S100B and S100A6 proteins at both the RNA and protein level. Higher expression of S100B and S100A6 was validated in vitro by Immunocytochemistry. We further validated our finding both in vitro and in patients' samples by IHC analysis of Tissue Microarray (TMA). Correlation analysis of S100A6 and LAMP2b as marker of acidosis in each patient from Moffitt TMA approved the acid related role of S100A6 in breast cancer patients. Also, DCIS patients with higher expression of S100A6 showed lower survival compared to lower expression. We propose essential roles of acid adaptation in cancer cells EMT process through S100 proteins such as S100A6 that can be used as therapeutic strategy targeting both acid-adapted and malignant phenotypes.

A Stochastic Model of DNA Double-Strand Breaks Repair Throughout the Cell Cycle.

Cell cycle phase is a decisive factor in determining the repair pathway of DNA double-strand breaks (DSBs) by non-homologous end joining (NHEJ) or homologous recombination (HR). Recent experimental studies revealed that 53BP1 and BRCA1 are the key mediators of the DNA damage response (DDR) with antagonizing roles in choosing the appropriate DSB repair pathway in G1, S, and G2 phases. Here, we present a stochastic model of biochemical kinetics involved in detecting and repairing DNA DSBs induced by ionizing radiation during the cell cycle progression. A three-dimensional stochastic process is defined to monitor the cell cycle phase and DSBs repair at times after irradiation. To estimate the model parameters, a Metropolis Monte Carlo method is applied to perform maximum likelihood estimation utilizing the kinetics of γ-H2AX and RAD51 foci formation in G1, S, and G2 phases. The recruitment of DSB repair proteins is verified by comparing our model predictions with the corresponding experimental data on human cells after exposure to X and γ-radiation. Furthermore, the interaction between 53BP1 and BRCA1 is simulated for G1 and S/G2 phases determining the competition between NHEJ and HR pathways in repairing induced DSBs throughout the cell cycle. In accordance with recent biological data, the numerical results demonstrate that the maximum proportion of HR occurs in S phase cells and the high level of NHEJ takes place in G1 and G2 phases. Moreover, the stochastic realizations of the total yield of simple and complex DSBs ligation are compared for G1 and S/G2 damaged cells. Finally, the proposed stochastic model is validated when DSBs induced by different particle radiation such as iron, silicon, oxygen, proton, and carbon.

A Network-Based Comparison Between Molecular Apocrine Breast Cancer Tumor and Basal and Luminal Tumors by Joint Graphical Lasso.

Joint graphical lasso (JGL) approach is a Gaussian graphical model to estimate multiple graphical models corresponding to distinct but related groups. Molecular apocrine (MA) breast cancer tumor has similar characteristics to luminal and basal subtypes. Due to the relationship between MA tumor and two other subtypes, this paper investigates the similarities and differences between the MA genes association network and the ones corresponding to other tumors by taking advantageous of JGL properties. Two distinct JGL graphical models are applied to two sub-datasets including the gene expression information of the MA and the luminal tumors and also the MA and the basal tumors. Then, topological comparisons between the networks such as finding the shared edges are applied. In addition, several support vector machine (SVM) classification models are performed to assess the discriminating power of some critical nodes in the networks, like hub nodes, to discriminate the tumors sample. Applying the JGL approach prepares an appropriate tool to observe the networks of the MA tumor and other subtypes in one map. The results obtained by comparing the networks could be helpful to generate new insight about MA tumor for future studies.

Molecular Basis of Bicalutamide Response Alteration of Androgen Receptor Caused by Single Nucleotide Polymorphisms: An In Silico Investigation.

The vast majority of drugs act through binding to their protein targets. Prediction of the interaction between small molecules and these receptors is a key element in the process of drug discovery. Advances in structural biology have enabled us to resolve the three-dimensional structure of proteins, which are the targets of the drugs. Pharmacogenetics also helped researchers to study the structural variations arise from the single nucleotide polymorphisms (SNPs) and to survey the effects these variations in drug design and development. These improvements led to the identification of structural changes caused by SNPs, which affect the drug interaction with their receptors, called drug response. In this study, the interaction between androgen receptor and bicalutamide was investigated using a computational analysis. The results of these analyses were then used for identification of nonsynonymous SNPs that are potentially involved in drug response alterations. The data show that amino acids Met895, Trp741, Arg752, Ile899, Leu707, Gly708, Gln711, Met745, Met749, Thr877, Phe764, Met742, Asn705 and Leu704 are the main residues involved in the interaction between androgen receptor and bicalutamide. The occurrence of nonsynonymous polymorphisms I843T, L708R, H690P, I870M, N757S, L713F, G744E, L678P, M788V, M781I, A722T, H875Y, I842V, and F827L in this receptor greatly affected its interaction with bicalutamide, and they were able to cause drug resistance. The results of this study could be useful in predicting the response to treatment in patients receiving bicalutamide.

A Network-Based Integrative Workflow to Unravel Mechanisms Underlying Disease Progression.

Unraveling mechanisms underlying diseases has motivated the development of systems biology approaches. The key challenges for the development of mathematical models and computational tool are (1) the size of molecular networks, (2) the nonlinear nature of spatio-temporal interactions, and (3) feedback loops in the structure of interaction networks. We here propose an integrative workflow that combines structural analyses of networks, high-throughput data, and mechanistic modeling. As an illustration of the workflow, we use prostate cancer as a case study with the aim of identifying key functional components associated with primary to metastasis transitions. Analysis carried out by the workflow revealed that HOXD10, BCL2, and PGR are the most important factors affected in primary prostate samples, whereas, in the metastatic state, STAT3, JUN, and JUNB are playing a central role. The identified key elements of each network are validated using patient survival analysis. The workflow presented here allows experimentalists to use heterogeneous data sources for the identification of diagnostic and prognostic signatures.

DNA methylation regulates discrimination of enhancers from promoters through a H3K4me1-H3K4me3 seesaw mechanism.

BACKGROUND: DNA methylation at promoters is largely correlated with inhibition of gene expression. However, the role of DNA methylation at enhancers is not fully understood, although a crosstalk with chromatin marks is expected. Actually, there exist contradictory reports about positive and negative correlations between DNA methylation and H3K4me1, a chromatin hallmark of enhancers. RESULTS: We investigated the relationship between DNA methylation and active chromatin marks through genome-wide correlations, and found anti-correlation between H3K4me1 and H3K4me3 enrichment at low and intermediate DNA methylation loci. We hypothesized "seesaw" dynamics between H3K4me1 and H3K4me3 in the low and intermediate DNA methylation range, in which DNA methylation discriminates between enhancers and promoters, marked by H3K4me1 and H3K4me3, respectively. Low methylated regions are H3K4me3 enriched, while those with intermediate DNA methylation levels are progressively H3K4me1 enriched. Additionally, the enrichment of H3K27ac, distinguishing active from primed enhancers, follows a plateau in the lower range of the intermediate DNA methylation level, corresponding to active enhancers, and decreases linearly in the higher range of the intermediate DNA methylation. Thus, the decrease of the DNA methylation switches smoothly the state of the enhancers from a primed to an active state. We summarize these observations into a rule of thumb of one-out-of-three methylation marks: "In each genomic region only one out of these three methylation marks {DNA methylation, H3K4me1, H3K4me3} is high. If it is the DNA methylation, the region is inactive. If it is H3K4me1, the region is an enhancer, and if it is H3K4me3, the region is a promoter". To test our model, we used available genome-wide datasets of H3K4 methyltransferases knockouts. Our analysis suggests that CXXC proteins, as readers of non-methylated CpGs would regulate the "seesaw" mechanism that focuses H3K4me3 to unmethylated sites, while being repulsed from H3K4me1 decorated enhancers and CpG island shores. CONCLUSIONS: Our results show that DNA methylation discriminates promoters from enhancers through H3K4me1-H3K4me3 seesaw mechanism, and suggest its possible function in the inheritance of chromatin marks after cell division. Our analyses suggest aberrant formation of promoter-like regions and ectopic transcription of hypomethylated regions of DNA. Such mechanism process can have important implications in biological process in where it has been reported abnormal DNA methylation status such as cancer and aging.

The Role of Intraoperative Thyroglobuline Level of Lymph Node in the Management of Papillary Thyroid Cancer (Determination of a Cutoff Point).

BACKGROUND: Some studies have shown that a preoperative high concentration of thyroglobulin (Tg) in wash out of fine-needle aspiration cytology of cervical lymph nodes mandate therapeutic lymph node dissection. However, there is disagreement about the minimum concentration of Tg which could have diagnostic value. Hence, according to our literature review, this study is the first one which designed to do intraoperatively. Therefore, this study was conducted and aimed to determine the clinical diagnostic value of Tg lymph nodes in the diagnosis of metastatic thyroid cancer. METHODS: In a cross-sectional study, 65 patients with papillary thyroid carcinoma (PTC) who were thyroidectomy candidates were chosen and during surgery, before the removal of lymph nodes in the neck, fine-needle sampling was performed and the level of Tg in the samples, nature of the sample sent for biopsy and Tg levels in affected and unaffected lymph nodes were determined. RESULTS: The mean levels of washout Tg in malignant and nonmalignant lymph nodes were 622.1 ± 66.2 and 1.38 ± 0.43 ng/ml, respectively, and the difference between the two groups was significant (P < 0.001). The Tg cut-off point for the detection of lymph node metastases was 0.7 ng/dl, and according to it, Tg washout sensitivity was 93.8%, specificity of 92.4%, false positives 7.76%, false negatives 6.3%, positive predictive value was 92.3%, and negative predictive value was 93.8% and accuracy was 93.1%. CONCLUSION: Based on the results, Tg level of cervical lymph nodes in patients with PTC is a suitable criterion for the diagnosis of lymph node which can be determined through fine-needle biopsy. Therefore, it is suggested that in patients with suspicion of lymph nodes involvement during surgery, fine-needle biopsy and determination of the Tg level performed.

Evolutionary emergence of angiogenesis in avascular tumors using a spatial public goods game.

Natural selection in cancer often results in the emergence of increasingly malignant tumor cells that display many if not all of the hallmarks of cancer. One of the most important traits acquired during cancer progression is angiogenesis. Tumor cells capable of secreting pro-angiogenic factors can be seen as cooperators where the improved oxygenation, nutrient delivery and waste disposal resulting from angiogenesis could be seen as a public good. Under this view, the relatively costly secretion of molecular signals required to orchestrate angiogenesis would be undertaken exclusively by cooperating tumor cells but the benefits of angiogenesis would be felt by neighboring tumor cells regardless of their contribution to the process. In this work we detail a mathematical model to better understand how clones capable of secreting pro-angiogenic factors can emerge in a tumor made of non-cooperative tumor cells. Given the importance of the spatial configuration of the tumor in determining the efficacy of the secretion of pro-angiogenic factors as well as the benefits of angiogenesis we have developed a spatial game theoretic approach where interactions and public good diffusion are described by graphs. The results show that structure of the population affects the evolutionary dynamics of the pro-angiogenic clone. Specifically, when the benefit of angiogenesis is represented by sigmoid function with regards to the number of pro-angiogenic clones then the probability of the coexistence of pro-angiogenic and angiogenesis-neutral clones increases. Our results demonstrate that pro-angiogenic clone equilibrates into clusters that appear from surrounding vascular tissues towards the center of tumor. These clusters appear notably less dense after anti-angiogenic therapy.

MMP-TIMP interactions in cancer invasion: An evolutionary game-theoretical framework.

One of the main steps in solid cancers to invade surrounding tissues is degradation of tissue barriers in the extracellular matrix. This operation that leads to initiate, angiogenesis and metastasis to other organs, is essentially consequence of collapsing dynamic balance between matrix metalloproteinases (MMP) and tissue inhibitors of metalloproteinases (TIMP). In this work, we model the MMP-TIMP interaction in both normal tissue and invasive cancer using evolutionary game theory. Our model explains how invasive cancer cells get the upper hand in MMP-TIMP imbalance scenarios. We investigate dynamics of them over time and discuss stable and nonstable states in the population. Numerical simulations presented here provide the identification of key genotypic features in the tumor invasion and a natural description for phenotypic variability. The simulation results are consistent with the experimental results in vitro observations presented in medical literature. Finally, by the provided results the necessary conditions to inhibit cancer invasion or prolong its course are explained. In this way, two therapeutic approaches with respect to how they could meet the required conditions are considered.

MicroRNA and Transcription Factor Gene Regulatory Network Analysis Reveals Key Regulatory Elements Associated with Prostate Cancer Progression.

Technological and methodological advances in multi-omics data generation and integration approaches help elucidate genetic features of complex biological traits and diseases such as prostate cancer. Due to its heterogeneity, the identification of key functional components involved in the regulation and progression of prostate cancer is a methodological challenge. In this study, we identified key regulatory interactions responsible for primary to metastasis transitions in prostate cancer using network inference approaches by integrating patient derived transcriptomic and miRomics data into gene/miRNA/transcription factor regulatory networks. One such network was derived for each of the clinical states of prostate cancer based on differentially expressed and significantly correlated gene, miRNA and TF pairs from the patient data. We identified key elements of each network using a network analysis approach and validated our results using patient survival analysis. We observed that HOXD10, BCL2 and PGR are the most important factors affected in primary prostate samples, whereas, in the metastatic state, STAT3, JUN and JUNB are playing a central role. Benefiting integrative networks our analysis suggests that some of these molecules were targeted by several overexpressed miRNAs which may have a major effect on the dysregulation of these molecules. For example, in the metastatic tumors five miRNAs (miR-671-5p, miR-665, miR-663, miR-512-3p and miR-371-5p) are mainly responsible for the dysregulation of STAT3 and hence can provide an opportunity for early detection of metastasis and development of alternative therapeutic approaches. Our findings deliver new details on key functional components in prostate cancer progression and provide opportunities for the development of alternative therapeutic approaches.

MGP-HMM: Detecting genome-wide CNVs using an HMM for modeling mate pair insertion sizes and read counts.

MOTIVATION: Association of Copy Number Variation (CNV) with schizophrenia, autism, developmental disabilities and fatal diseases such as cancer is verified. Recent developments in Next Generation Sequencing (NGS) have facilitated the CNV studies. However, many of the current CNV detection tools are not capable of discriminating tandem duplication from non-tandem duplications. RESULTS: In this study, we propose MGP-HMM as a tool which besides detecting genome-wide deletions discriminates tandem duplications from non-tandem duplications. MGP-HMM takes mate pair abnormalities into account and predicts the digitized number of tandem or non-tandem copies. Abnormalities in the mate pair directions and insertion sizes, after being mapped to the reference genome, are elucidated using a Hidden Markov Model (HMM). For this purpose, a Mixture Gaussian density with time-dependent parameters is applied for emitting mate pair insertion sizes from HMM states. Indeed, depending on observed abnormalities in mate pair insertion size or its orientation, each component in the mixture density will have different parameters. MGP-HMM also applies a Poisson distribution for modeling read depth data. This parametric modeling of the mate pair reads enables us to estimate the length of CNVs precisely, which is an advantage over methods which rely only on read depth approach for the CNV detection. Hidden state of the proposed HMM is the digitized copy number of a genomic segment and states correspond to the multipliers of the mixture Gaussian components. The accuracy of our model is validated on a set of next generation sequencing real and simulated data and is compared to other tools.