Clinical Omics Analysis of Colorectal Cancer Incorporating Copy Number Aberrations and Gene Expression Data
Tsuyoshi YoshidaT KobayashiMasaya ItodaTaika MutoKen MiyaguchiKaoru MogushiSatoshi ShojiKazuro ShimokawaSatoru IidaHiroyuki UetakeToshiaki IshikawaKenichi SugiharaHiroshi MizushimaHiroshi Tanaka
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Colorectal cancer (CRC) is one of the most frequently occurring cancers in Japan, and thus a wide range of methods have been deployed to study the molecular mechanisms of CRC. In this study, we performed a comprehensive analysis of CRC, incorporating copy number aberration (CRC) and gene expression data. For the last four years, we have been collecting data from CRC cases and organizing the information as an "omics" study by integrating many kinds of analysis into a single comprehensive investigation. In our previous studies, we had experienced difficulty in finding genes related to CRC, as we observed higher noise levels in the expression data than in the data for other cancers. Because chromosomal aberrations are often observed in CRC, here, we have performed a combination of CNA analysis and expression analysis in order to identify some new genes responsible for CRC. This study was performed as part of the Clinical Omics Database Project at Tokyo Medical and Dental University. The purpose of this study was to investigate the mechanism of genetic instability in CRC by this combination of expression analysis and CNA, and to establish a new method for the diagnosis and treatment of CRC.Comprehensive gene expression analysis was performed on 79 CRC cases using an Affymetrix Gene Chip, and comprehensive CNA analysis was performed using an Affymetrix DNA Sty array. To avoid the contamination of cancer tissue with normal cells, laser micro-dissection was performed before DNA/RNA extraction. Data analysis was performed using original software written in the R language.We observed a high percentage of CNA in colorectal cancer, including copy number gains at 7, 8q, 13 and 20q, and copy number losses at 8p, 17p and 18. Gene expression analysis provided many candidates for CRC-related genes, but their association with CRC did not reach the level of statistical significance. The combination of CNA and gene expression analysis, together with the clinical information, suggested UGT2B28, LOC440995, CXCL6, SULT1B1, RALBP1, TYMS, RAB12, RNMT, ARHGDIB, S1000A2, ABHD2, OIT3 and ABHD12 as genes that are possibly associated with CRC. Some of these genes have already been reported as being related to CRC. TYMS has been reported as being associated with resistance to the anti-cancer drug 5-fluorouracil, and we observed a copy number increase for this gene. RALBP1, ARHGDIB and S100A2 have been reported as oncogenes, and we observed copy number increases in each. ARHGDIB has been reported as a metastasis-related gene, and our data also showed copy number increases of this gene in cases with metastasis.The combination of CNA analysis and gene expression analysis was a more effective method for finding genes associated with the clinicopathological classification of CRC than either analysis alone. Using this combination of methods, we were able to detect genes that have already been associated with CRC. We also identified additional candidate genes that may be new markers or targets for this form of cancer.Keywords:
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Structural Variation
Gene dosage
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Copy number variations (CNVs) confer significant effects on genetic innovation and phenotypic variation. Previous CNV studies in swine seldom focused on in-depth characterization of global CNVs. Using whole-genome assembly comparison (WGAC) and whole-genome shotgun sequence detection (WSSD) approaches by next generation sequencing (NGS), we probed formation signatures of both segmental duplications (SDs) and individualized CNVs in an integrated fashion, building the finest resolution CNV and SD maps of pigs so far. We obtained copy number estimates of all protein-coding genes with copy number variation carried by individuals, and further confirmed two genes with high copy numbers in Meishan pigs through an enlarged population. We determined genome-wide CNV hotspots, which were significantly enriched in SD regions, suggesting evolution of CNV hotspots may be affected by ancestral SDs. Through systematically enrichment analyses based on simulations and bioinformatics analyses, we revealed CNV-related genes undergo a different selective constraint from those CNV-unrelated regions, and CNVs may be associated with or affect pig health and production performance under recent selection. Our studies lay out one way for characterization of CNVs in the pig genome, provide insight into the pig genome variation and prompt CNV mechanisms studies when using pigs as biomedical models for human diseases.
Structural Variation
Copy number analysis
Comparative genomic hybridization
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Various animal and cell culture models of diabetes mellitus (DM) have been established and utilized to study diabetic peripheral neuropathy (DPN). The divergence of metabolic abnormalities among these models makes their etiology complicated despite some similarities regarding the pathological and neurological features of DPN. Thus, this study aimed to review the omics approaches toward DPN, especially on the metabolic states in diabetic rats and mice induced by chemicals (streptozotocin and alloxan) as type 1 DM models and by genetic mutations (MKR, db/db and ob/ob) and high-fat diet as type 2 DM models. Omics approaches revealed that the pathways associated with lipid metabolism and inflammation in dorsal root ganglia and sciatic nerves were enriched and controlled in the levels of gene expression among these animal models. Additionally, these pathways were conserved in human DPN, indicating the pivotal pathogeneses of DPN. Omics approaches are beneficial tools to better understand the association of metabolic changes with morphological and functional abnormalities in DPN.
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Gene chip analysis
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Polycystic ovary syndrome (PCOS) is the most common gynecological endocrine disease, involving multiple genes, multiple pathways, and complex hormone secretion processes. Hence, the pathogenesis of PCOS cannot be explained by a single factor. Omics analysis includes genomics, transcriptomics, and proteomics, which are fast and effective methods for studying the pathogenesis of diseases. PCOS is primarily characterized by androgen excess, and reproductive and metabolic dysfunctions. The application of omics analysis in the body fluids, blood, cells or tissues of women with PCOS offers the potential for unexpected molecular advantages in explaining new mechanisms of PCOS etiology and pathophysiology, and provides new perspectives for identifying potential biomarkers and developing new therapeutic targets. At present, several omics analyses have been applied to produce complex datasets. In this manuscript, the recent advances in omics research on PCOS are summarized, aiming at an important and parallel review of the newly published research.
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Геномная вариабельность является основой эволюции генома человека и включает в себя вариации последовательности ДНК и структурную вариабельность. К структурной вариабельности относят вариации числа копий участка ДНК (copy number variation - CNV), размером от 1000 п.н. до нескольких десятков млн п.н. Среди них выделяют субмикроскопические CNV размером от 1000 п.н. до 3 млн п.н., часть из которых является клинически значимой, то есть ассоциирована с задержкой психомоторного развития, врожденными пороками и/или аномалиями развития, а также заболеваниями аутистического спектра. Для анализа CNV используют широкий спектр методов с различной разрешающей способностью. В качестве универсального метода детекции субмикроскопических CNV в клинической практике используется хромосомный микроматричный анализ. Однако все чаще для анализа CNV используются методы высокопроизводительного секвенирования. Наряду с развитием полногеномных технологий, разрабатывается большое количество биоинформатических алгоритмов анализа CNV, имеющих разную эффективность. В связи с этим возрастает потребность в подтверждении полученных данных с целью исключения ложноположительных результатов. Кроме того, информации только о наличии или отсутствии CNV недостаточно для медико-генетического консультирования. Для оценки повторного риска хромосомной патологии необходимо определить структуру и происхождение обнаруженной CNV. С этой целью используются молекулярно-генетические и молекулярно-цитогенетические методы. Ряд молекулярно-генетических методов, основанных на использовании ПЦР, имеют разрешающую способность, достаточную для подтверждения субмикроскопических CNV. Молекулярно-цитогенетические методы включают в себя различные модификации метода флуоресцентной in situ гибридизации. Анализ субмикроскопических CNV с использованием FISH-метода ограничен длиной и спецификой фрагментов ДНК в зондах, используемых в традиционных протоколах исследования. Поэтому актуальным становится использование методов на основе in situ гибридизации с ДНК-зондами длиной порядка нескольких т.п.н., что позволяет не только подтвердить CNV и установить ее происхождение, но и определить структуру хромосомной перестройки, лежащей в основе хромосомного/геномного дисбаланса. В статье обсуждаются возможности, преимущества и недостатки различных методов, используемых для верификации клинически значимых CNV. Genomic variability is the basis of genetic diversity and evolution and includes sequence and structural variability. Structural variability refers to variations in the number of copies of DNA (copy number variations - CNVs), ranging from 1000 bp up to several megabases (Mb) in size. Among them, some submicroscopic CNVs up to 3 Mb, can lead to clinical signs such as developmental delay, intellectual disability, congenital malformations and/or dysmorphic features, as well as autism spectrum disorders. A wide range of methods with different resolution is used for CNVs analysis. To date, chromosomal microarray analysis (CMA) is a universal method for CNVs detection. However, with the advent methods of next-generation sequencing, their applicability for CNV analysis is increasingly being estimated. Therefore, with the development of genome-wide technologies and bioinformatic tools for CNV analysis, there is an increasing need to confirm the obtained data in order to establish the true values of their sensitivity and specificity. In addition, information only about localization and gene content of CNVs is not enough for genetic counseling for the family. It is necessary to define structure and origin of the detected CNV to assess accurate recurrence risk of chromosome imbalance. For this purpose, molecular genetics and molecular cytogenetic methods are used. There are some methods of molecular genetics based on PCR with sufficient resolution to confirm submicroscopic CNV longer than 1000 bp. Analysis of submicroscopic CNVs by various modifications of FISH-method is limited by the length and specificity of DNA fragments in probes used in conventional FISH-protocols. Therefore, application of DNA probes of the order of several kb in length becomes relevant. If both group of methods allow to confirm CNVs detected by wide-genome technologies, than the latter are used to estimate the structure of chromosomal imbalance. Possibilities, advantages and disadvantages of different methods for CNVs verification are discussed.
Gene dosage
Comparative genomic hybridization
Structural Variation
Copy number analysis
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Copy number variation(CNV) is increasingly recognized as a source of inter-individual differences in genome sequence and is proposed as a driving force for genome evolution and phenotypic variation.Many CNVs result in different levels of gene expression, which may account for a significant proportion of normal phenotypic variation and human diseases.This review unveiled the research process and study strategy of CNVs.Subsequently, the potential mechanisms of CNV formation and its forensic applications were discussed.In addition, the first-generation copy number variation map of the human genome was introduced, which demonstrated that DNA copy number variation was associated with specific chromosomal rearrangements and genomic disorders.
Variation (astronomy)
Structural Variation
Copy number analysis
Gene dosage
Human genetic variation
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Background
A copy number variant is a DNA segment containing an increased or decreased number of copies in comparison with a reference genome. Copy number variation (CNV) contributes significantly to genomic diversity, representing the most prevalent type of structural variation in the human genome. In several cases, CNV causes disease by altering gene dosage or by indirect alteration of gene expression. Several studies have been focusing on investigating the role of CNVs in nervous system disorders such as Parkinson9s disease and Alzheimer9s disease.Aim
The aim of the present study was to investigate CNV and association with variable adult age of onset (AAO) of Huntington9s disease. Several candidate genes have been identified that may show CNV and are candidates for involvement in neurological disease. These candidates were identified from published proteomic and genetic analysis, unpublished yeast genetic interaction studies or candidate scanning of the literature. Thus we are analysing the copy number of these genes in HD cohorts to assess whether there is an association with variation of AAO. We are assessing CNV using the Parologue Ratio Test (PRT), which employs quantitative duplex PCR. Primers are designed to precisely amplify a portion of the variable region and an unlinked reference region with no variation in copy number. We are currently analysing several CNVs in candidate genes by PRT on a cohort of HD patients to evaluate possible correlations between this variation and the AAO of HD. Any influence of CNV on AAO will be validated using functional assays in mammalian cell culture.Candidate gene
Gene dosage
Structural Variation
Genome-wide Association Study
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Omics
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Purpose of review The purpose of this review is to recapture recent advances in cachexia-related diseases, mainly cancer cachexia, and treatment using genomic, transcriptomics, proteomic, and metabolomics-related techniques. Recent findings From recent studies in the cancer cachexia field it is clear that the tumor has a direct effect on distant organs via its secretome. The affected pathways on the other hand were largely known from earlier studies with changes in energy-related pathways (mainly lipid metabolism) and the protein degradation pathways. Treatment-oriented studies use mostly rodent models and in-vivo cultures and it is too early for human studies. Summary Omics tools are powerful if used in the right way. Omics research has identified the tumor as an important player in cancer cachexia and some interesting novel treatments have been found in experimental models.
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Cancer Cachexia
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