Nurshat Gaifullin

Human-specific endogenous retroviral insert serves as an enhancer for the schizophrenia-linked gene PRODH

Significance We identified a human-specific endogenous retroviral insert (hsERV) that acts as an enhancer for human PRODH, hsERV_PRODH. PRODH encodes proline dehydrogenase, which is involved in neuromediator synthesis in the CNS. We show that the hsERV_PRODH enhancer acts synergistically with the CpG island of PRODH and is regulated by methylation. We detected high PRODH expression in the hippocampus, which was correlated with the undermethylated state of this enhancer. PRODH regulatory elements provide neuron-specific transcription in hippocampal cells, and the mechanism of hsERV_PRODH enhancer activity involves the binding of transcriptional factor SOX2. Because PRODH is associated with several neurological disorders, we hypothesize that the human-specific regulation of PRODH by hsERV_PRODH may have played a role in human evolution by upregulating the expression of this important CNS-specific gene. Using a systematic, whole-genome analysis of enhancer activity of human-specific endogenous retroviral inserts (hsERVs), we identified an element, hsERVPRODH, that acts as a tissue-specific enhancer for the PRODH gene, which is required for proper CNS functioning. PRODH is one of the candidate genes for susceptibility to schizophrenia and other neurological disorders. It codes for a proline dehydrogenase enzyme, which catalyses the first step of proline catabolism and most likely is involved in neuromediator synthesis in the CNS. We investigated the mechanisms that regulate hsERVPRODH enhancer activity. We showed that the hsERVPRODH enhancer and the internal CpG island of PRODH synergistically activate its promoter. The enhancer activity of hsERVPRODH is regulated by methylation, and in an undermethylated state it can up-regulate PRODH expression in the hippocampus. The mechanism of hsERVPRODH enhancer activity involves the binding of the transcription factor SOX2, whch is preferentially expressed in hippocampus. We propose that the interaction of hsERVPRODH and PRODH may have contributed to human CNS evolution.

A systematic experimental evaluation of microRNA markers of human bladder cancer.

Background: MicroRNAs (miRNAs) are a class of small RNAs that regulate gene expression. They are aberrantly expressed in many human cancers and are potential therapeutic targets and molecular biomarkers. Methods: In this study, we for the first time validated the reported data on the entire set of published differential miRNAs (102 in total) through a series of transcriptome-wide experiments. We have conducted genome-wide miRNA profiling in 17 urothelial carcinoma bladder tissues and in nine normal urothelial mucosa samples using three methods: (1) An Illumina HT-12 microarray hybridization (MA) analysis (2) a suppression-subtractive hybridization (SSH) assay followed by deep sequencing (DS) and (3) DS alone. Results: We show that DS data correlate with previously published information in 87% of cases, whereas MA and SSH data have far smaller correlations with the published information (6 and 9% of cases, respectively). qRT-PCR tests confirmed reliability of the DS data. Conclusions: Based on our data, MA and SSH data appear to be inadequate for studying differential miRNA expression in the bladder. Impact: We report the first comprehensive validated database of miRNA markers of human bladder cancer.

A method for predicting target drug efficiency in cancer based on the analysis of signaling pathway activation

A new generation of anticancer therapeutics called target drugs has quickly developed in the 21st century. These drugs are tailored to inhibit cancer cell growth, proliferation, and viability by specific interactions with one or a few target proteins. However, despite formally known molecular targets for every “target” drug, patient response to treatment remains largely individual and unpredictable. Choosing the most effective personalized treatment remains a major challenge in oncology and is still largely trial and error. Here we present a novel approach for predicting target drug efficacy based on the gene expression signature of the individual tumor sample(s). The enclosed bioinformatic algorithm detects activation of intracellular regulatory pathways in the tumor in comparison to the corresponding normal tissues. According to the nature of the molecular targets of a drug, it predicts whether the drug can prevent cancer growth and survival in each individual case by blocking the abnormally activated tumor-promoting pathways or by reinforcing internal tumor suppressor cascades. To validate the method, we compared the distribution of predicted drug efficacy scores for five drugs (Sorafenib, Bevacizumab, Cetuximab, Sorafenib, Imatinib, Sunitinib) and seven cancer types (Clear Cell Renal Cell Carcinoma, Colon cancer, Lung adenocarcinoma, non-Hodgkin Lymphoma, Thyroid cancer and Sarcoma) with the available clinical trials data for the respective cancer types and drugs. The percent of responders to a drug treatment correlated significantly (Pearsons correlation 0.77 p = 0.023) with the percent of tumors showing high drug scores calculated with the current algorithm.

Molecular pathway activation features linked with transition from normal skin to primary and metastatic melanomas in human

Melanoma is the most aggressive and dangerous type of skin cancer, but its molecular mechanisms remain largely unclear. For transcriptomic data of 478 primary and metastatic melanoma, nevi and normal skin samples, we performed high-throughput analysis of intracellular molecular networks including 592 signaling and metabolic pathways. We showed that at the molecular pathway level, the formation of nevi largely resembles transition from normal skin to primary melanoma. Using a combination of bioinformatic machine learning algorithms, we identified 44 characteristic signaling and metabolic pathways connected with the formation of nevi, development of primary melanoma, and its metastases. We created a model describing formation and progression of melanoma at the level of molecular pathway activation. We discovered six novel associations between activation of metabolic molecular pathways and progression of melanoma: for allopregnanolone biosynthesis, L-carnitine biosynthesis, zymosterol biosynthesis (inhibited in melanoma), fructose 2, 6-bisphosphate synthesis and dephosphorylation, resolvin D biosynthesis (activated in melanoma), D-myo-inositol hexakisphosphate biosynthesis (activated in primary, inhibited in metastatic melanoma). Finally, we discovered fourteen tightly coordinated functional clusters of molecular pathways. This study helps to decode molecular mechanisms underlying the development of melanoma.

MiRImpact, a new bioinformatic method using complete microRNA expression profiles to assess their overall influence on the activity of intracellular molecular pathways

ABSTRACT MicroRNAs (miRs) are short noncoding RNA molecules that regulate expression of target mRNAs. Many published sources provide information about miRs and their targets. However, bioinformatic tools elucidating higher level impact of the established total miR profiles, are still largely missing. Recently, we developed a method termed OncoFinder enabling quantification of the activities of intracellular molecular pathways basing on gene expression data. Here we propose a new technique, MiRImpact, which enables to link miR expression data with its estimated outcome on the regulation of molecular pathways, like signaling, metabolic, cytoskeleton rearrangement, and DNA repair pathways. MiRImpact uses OncoFinder rationale for pathway activity calculations, with the major distinctions that (i) it deals with the concentrations of miRs - known regulators of gene products participating in molecular pathways, and (ii) miRs are considered as negative regulators of target molecules, if other is not specified. MiRImpact operates with 2 types of databases: for molecular targets of miRs and for gene products participating in molecular pathways. We applied MiRImpact to compare regulation of human bladder cancer-specific signaling pathways at the levels of mRNA and miR expression. We took 2 most complete alternative databases of experimentally validated miR targets – miRTarBase and DianaTarBase, and an OncoFinder database featuring 2725 gene products and 271 signaling pathways. We showed that the impact of miRs is orthogonal to pathway regulation at the mRNA level, which stresses the importance of studying posttranscriptional regulation of gene expression. We also report characteristic set of miR and mRNA regulation features linked with bladder cancer.

Data aggregation at the level of molecular pathways improves stability of experimental transcriptomic and proteomic data

ABSTRACT High throughput technologies opened a new era in biomedicine by enabling massive analysis of gene expression at both RNA and protein levels. Unfortunately, expression data obtained in different experiments are often poorly compatible, even for the same biologic samples. Here, using experimental and bioinformatic investigation of major experimental platforms, we show that aggregation of gene expression data at the level of molecular pathways helps to diminish cross- and intra-platform bias otherwise clearly seen at the level of individual genes. We created a mathematical model of cumulative suppression of data variation that predicts the ideal parameters and the optimal size of a molecular pathway. We compared the abilities to aggregate experimental molecular data for the 5 alternative methods, also evaluated by their capacity to retain meaningful features of biologic samples. The bioinformatic method OncoFinder showed optimal performance in both tests and should be very useful for future cross-platform data analyses.

Gene expression and molecular pathway activation signatures of MYCN-amplified neuroblastomas

Neuroblastoma is a pediatric cancer arising from sympathetic nervous system. Remarkable heterogeneity in outcomes is one of its widely known features. One of the traits strongly associated with the unfavorable subtype is the amplification of oncogene MYCN. Here, we performed cross-platform biomarker detection by comparing gene expression and pathway activation patterns from the two literature reports and from our experimental dataset, combining profiles for the 761 neuroblastoma patients with known MYCN amplification status. We identified 109 / 25 gene expression / pathway activation biomarkers strongly linked with the MYCN amplification. The marker genes/pathways are involved in the processes of purine nucleotide biosynthesis, ATP-binding, tetrahydrofolate metabolism, building mitochondrial matrix, biosynthesis of amino acids, tRNA aminoacylation and NADP-linked oxidation-reduction processes, as well as in the tyrosine phosphatase activity, p53 signaling, cell cycle progression and the G1/S and G2/M checkpoints. To connect molecular functions of the genes involved in MYCN-amplified phenotype, we built a new molecular pathway using known intracellular protein interaction networks. The activation of this pathway was highly selective in discriminating MYCN-amplified neuroblastomas in all three datasets. Our data also suggest that the phosphoinositide 3-kinase (PI3K) inhibitors may provide new opportunities for the treatment of the MYCN-amplified neuroblastoma subtype.

nMETR: Technique for facile recovery of hypomethylation genomic tags

Genome-wide methylation studies frequently lack adequate controls to estimate proportions of background reads in the resulting datasets. To generate appropriate control pools, we developed technique termed nMETR (non-methylated tag recovery) based on digestion of genomic DNA with methylation-sensitive restriction enzyme, ligation of adapter oligonucleotide and PCR amplification of non-methylated sites associated with genomic repetitive elements. The protocol takes only two working days to generate amplicons for deep sequencing. We applied nMETR for human DNA using BspFNI enzyme and retrotransposon Alu-specific primers. 454-sequencing enabled identification of 1113 nMETR tag sites, of them ~65% were parts of CpG islands. Representation of reads inversely correlated with methylation levels, thus confirming nMETR fidelity. We created software that eliminates background reads and enables to map and annotate individual tags on human genome. nMETR tags may serve as the controls for large-scale epigenetic studies and for identifying unmethylated transposable elements located close to genomic CpG islands.

Potentialities of MicroRNA Diagnosis in Patients with Bladder Cancer

Despite promising vista of the use of microRNA in molecular diagnosis of bladder cancer, there are few data on their expression profiles, which impedes assessment of diagnostic value of these marker molecules. In this study, suppression subtractive hybridization, on-chip hybridization, and high-throughput deep sequencing focused on profiling microRNA and assessing the diagnostic value of revealed marker molecules.

Recent Inserts of Transposable Elements Affect Structure and Functions of Human Genome

Transposable elements (TEs) are selfish fragments of DNA able to reproduce themselves into the host genomes. TEs typically occupy ∼40–50% of the mammalian genomes. In our studies, we focus on evolutionary recent TE inserts that appeared in the DNA of human ancestor lineage after divergence with the chimpanzee ancestry, i.e. less than ∼6 million years ago. These human specific elements (hsTEs) represent only a minor fraction of the whole TE cargo of the human genome. hsTEs are represented by the four families called HERV-K(HML-2), L1, Alu and SVA. The number of human specific copies for HERV-K(HML-2), L1, Alu and SVA families is approx. 150, 1,200, 5,500 and 860 copies per genome, respectively. Taken together, hsTEs shape ∼6.4 megabases of human DNA, which is about 6-times lower than what is occupied by the human specific simple nucleotide polymorphisms, and 23-times smaller than the overall length of human specific deletions and duplications. However, although modest in terms of genomic proportion, hsTEs should be regarded as the perspective candidates for being molecular genetic agents of human speciation. Unlike most of random mutations and duplications, each novel insert of hsTE has provided to the recipient genomic locus a set of functional transcriptional factor binding sites positively selected during the TE evolution. For example, clusters of novel inserts of Alu elements may serve as CpG islets, SVA elements provide functional splice sites and polyadenylation signals, whereas L1 and HERV-K(HML-2) elements donate enhancers, promoters, splice sites and polyadenylation signals. Significant proportion of the human-specific genomic deletions, duplications and translocations has been also generated due to ectopic recombinations between the different individual TE inserts. Among the other, we report for the first time a detailed functional characteristics of the HERV-K(HML-2) hsTEs done at the genome-wide level. We have identified 65 active in vivo human specific promoters contributed by these elements. We also identified three cases of the hsTE-mediated human specific transcriptional regulation of functional protein-coding genes taking part in brain development during embryogenesis. We found ∼180 human specific polyadenylation signals transferred by the SVA elements into the introns of known functional genes. Scaling of these data to the total number of the hsTEs predicts that hundreds of human genes are regulated by these elements. Finally, we discovered the first exclusively human specific TE family, represented by ∼80 members formed by a combination of a part of a CpG islet of human gene MAST2 ansd of the 3′-terminal part of an SVA retrotransposon. According to our estimates, this family, termed CpG-SVA, was far more active than the ancestral SVA family. Our data indicate that MAST2 regulatory sequence was recruited during the evolution to provide effective CpG-SVA transcription in human testicular germ-line cells.