Sergey Roumiantsev

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.

The OncoFinder algorithm for minimizing the errors introduced by the high-throughput methods of transcriptome analysis.

The diversity of the installed sequencing and microarray equipment make it increasingly difficult to compare and analyze the gene expression datasets obtained using the different methods. Many applications requiring high-quality and low error rates cannot make use of available data using traditional analytical approaches. Recently, we proposed a new concept of signalome-wide analysis of functional changes in the intracellular pathways termed OncoFinder, a bioinformatic tool for quantitative estimation of the signaling pathway activation (SPA). We also developed methods to compare the gene expression data obtained using multiple platforms and minimizing the error rates by mapping the gene expression data onto the known and custom signaling pathways. This technique for the first time makes it possible to analyze the functional features of intracellular regulation on a mathematical basis. In this study we show that the OncoFinder method significantly reduces the errors introduced by transcriptome-wide experimental techniques. We compared the gene expression data for the same biological samples obtained by both the next generation sequencing (NGS) and microarray methods. For these different techniques we demonstrate that there is virtually no correlation between the gene expression values for all datasets analyzed (R2 < 0.1). In contrast, when the OncoFinder algorithm is applied to the data we observed clear-cut correlations between the NGS and microarray gene expression datasets. The SPA profiles obtained using NGS and microarray techniques were almost identical for the same biological samples allowing for the platform-agnostic analytical applications. We conclude that this feature of the OncoFinder enables to characterize the functional states of the transcriptomes and interactomes more accurately as before, which makes OncoFinder a method of choice for many applications including genetics, physiology, biomedicine, and molecular diagnostics.

Characteristic patterns of microrna expression in human bladder cancer

MicroRNAs (miRNAs) are small, non-coding RNAs that post-transcriptionally regulate gene expression. Their altered expression and functional activity have been observed in many human cancers. miRNAs represent promising diagnostic and prognostic molecular biomarkers, and also serve as novel therapeutic targets. We performed a systematic analysis of scientific reports that link differences in miRNA expression with the pathogenesis of bladder cancer (BC). This literature review is the first comprehensive database of miRNA molecules with biased expression profiles in BC. Among the 95 differentially expressed miRNAs that we identified from the literature, we classify 48 as up-regulated in BC, 35 as down-regulated, and 12 as contradictory (contradictory data were reported in one or more studies on the gene). In addition, we discuss the possible roles of differentially expressed miRNAs in the regulation of intracellular signaling pathways in BC.

A role for G‐CSF and GM‐CSF in nonmyeloid cancers

Granulocyte colony‐stimulating factor (G‐CSF) and granulocyte‐macrophage colony‐stimulating factor (GM‐CSF) modulate progression of certain solid tumors. The G‐CSF‐ or GM‐CSF‐secreting cancers, albeit not very common are, however, among the most rapidly advancing ones due to a cytokine‐mediated immune suppression and angiogenesis. Similarly, de novo angiogenesis and vasculogenesis may complicate adjuvant use of recombinant G‐CSF or GM‐CSF thus possibly contributing to a cancer relapse. Rapid diagnostic tools to differentiate G‐CSF‐ or GM‐CSF‐secreting cancers are not well developed therefore hindering efforts to individualize treatments for these patients. Given an increasing utilization of adjuvant G‐/GM‐CSF in cancer therapy, we aimed to summarize recent studies exploring their roles in pathophysiology of solid tumors and to provide insights into some complexities of their therapeutic applications.

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.

Non-invasive prenatal diagnostics of aneuploidy using next-generation DNA sequencing technologies, and clinical considerations

Abstract Rapidly developing next-generation sequencing (NGS) technologies produce a large amount of data across the whole human genome and allow a large number of DNA samples to be analyzed simultaneously. Screening cell-free fetal DNA (cffDNA) obtained from maternal blood using NGS technologies has provided new opportunities for non-invasive prenatal diagnosis (NIPD) of fetal aneuploidies. One of the major challenges to the analysis of fetal abnormalities is the development of accurate and reliable algorithms capable of analyzing large numbers of short sequence reads. Several such algorithms have recently been developed. Here, we provide a review of recent NGS-based NIPD methods as well as the available algorithms for short-read sequence analysis. We furthermore introduce the practical application of these algorithms for the detection of different types of fetal aneuploidies, and compare the performance, cost and complexity of each approach for clinical deployment. Our review identifies several main technologies and trends in NGS-based NIPD. The main considerations for clinical development for NIPD and screening tests using DNA sequencing are: accuracy, intellectual property, cost and the ability to screen for a wide range of chromosomal abnormalities and genetic defects. The cost of the diagnostic test depends on the sequencing method, diagnostic algorithm and volume of the tests. If the cost of sequencing equipment and reagents remains at or around current levels, targeted approaches for sequencing-based aneuploidy testing and SNP-based methods are preferred.

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.

Combinatorial high-throughput experimental and bioinformatic approach identifies molecular pathways linked with the sensitivity to anticancer target drugs

Effective choice of anticancer drugs is important problem of modern medicine. We developed a method termed OncoFinder for the analysis of new type of biomarkers reflecting activation of intracellular signaling and metabolic molecular pathways. These biomarkers may be linked with the sensitivity to anticancer drugs. In this study, we compared the experimental data obtained in our laboratory and in the Genomics of Drug Sensitivity in Cancer (GDS) project for testing response to anticancer drugs and transcriptomes of various human cell lines. The microarray-based profiling of transcriptomes was performed for the cell lines before the addition of drugs to the medium, and experimental growth inhibition curves were built for each drug, featuring characteristic IC50 values. We assayed here four target drugs - Pazopanib, Sorafenib, Sunitinib and Temsirolimus, and 238 different cell lines, of which 11 were profiled in our laboratory and 227 - in GDS project. Using the OncoFinder-processed transcriptomic data on ∼600 molecular pathways, we identified pathways showing significant correlation between pathway activation strength (PAS) and IC50 values for these drugs. Correlations reflect relationships between response to drug and pathway activation features. We intersected the results and found molecular pathways significantly correlated in both our assay and GDS project. For most of these pathways, we generated molecular models of their interaction with known molecular target(s) of the respective drugs. For the first time, our study uncovered mechanisms underlying cancer cell response to drugs at the high-throughput molecular interactomic level.

Low doses of X-rays induce prolonged and ATM-independent persistence of γH2AX foci in human gingival mesenchymal stem cells

Diagnostic imaging delivering low doses of radiation often accompany human mesenchymal stem cells (MSCs)-based therapies. However, effects of low dose radiation on MSCs are poorly characterized. Here we examine patterns of phosphorylated histone H2AX (γH2AX) and phospho-S1981 ATM (pATM) foci formation in human gingiva-derived MSCs exposed to X-rays in time-course and dose-response experiments. Both γH2AX and pATM foci accumulated linearly with dose early after irradiation (5–60 min), with a maximum induction observed at 30–60 min (37 ± 3 and 32 ± 3 foci/cell/Gy for γH2AX and pATM, respectively). The number of γH2AX foci produced by intermediate doses (160 and 250 mGy) significantly decreased (40–60%) between 60 and 240 min post-irradiation, indicating rejoining of DNA double-strand breaks. In contrast, γH2AX foci produced by low doses (20–80 mGy) did not change after 60 min. The number of pATM foci between 60 and 240 min decreased down to control values in a dose-independent manner. Similar kinetics was observed for pATM foci co-localized with γH2AX foci. Collectively, our results suggest differential DNA double-strand break signaling and processing in response to low vs. intermediate doses of X-rays in human MSCs. Furthermore, mechanisms governing the prolonged persistence of γH2AX foci in these cells appear to be ATM-independent.

New bioinformatic tool for quick identification of functionally relevant endogenous retroviral inserts in human genome

Abstract Endogenous retroviruses (ERVs) and LTR retrotransposons (LRs) occupy ∼8% of human genome. Deep sequencing technologies provide clues to understanding of functional relevance of individual ERVs/LRs by enabling direct identification of transcription factor binding sites (TFBS) and other landmarks of functional genomic elements. Here, we performed the genome-wide identification of human ERVs/LRs containing TFBS according to the ENCODE project. We created the first interactive ERV/LRs database that groups the individual inserts according to their familial nomenclature, number of mapped TFBS and divergence from their consensus sequence. Information on any particular element can be easily extracted by the user. We also created a genome browser tool, which enables quick mapping of any ERV/LR insert according to genomic coordinates, known human genes and TFBS. These tools can be used to easily explore functionally relevant individual ERV/LRs, and for studying their impact on the regulation of human genes. Overall, we identified ∼110,000 ERV/LR genomic elements having TFBS. We propose a hypothesis of “domestication” of ERV/LR TFBS by the genome milieu including subsequent stages of initial epigenetic repression, partial functional release, and further mutation-driven reshaping of TFBS in tight coevolution with the enclosing genomic loci.