ResearchPad - cancer-genetics https://www.researchpad.co Default RSS Feed en-us © 2020 Newgen KnowledgeWorks <![CDATA[Human papillomavirus E7 binds Oct4 and regulates its activity in HPV-associated cervical cancers]]> https://www.researchpad.co/article/elastic_article_14755 The transcription factor Oct4 with well-known roles in embryogenesis, pluripotency and cellular reprogramming has recently been found to be expressed in several types of somatic tumors. Even though its role in cancer remains controversial, we provide evidence that Oct4 is expressed in cervical cancer tissues and cancer cell lines. The viral oncogenes of the Human Papillomavirus significantly elevate Oct4 expression both in normal and cancer cells, likely through transcriptional upregulation. While the expression levels of Oct4 in cancer are low compared to those seen in stem cells, our results suggest that they are still consequential to cell proliferation, self-renewal, and migration. We demonstrate a physical interaction of the E7 oncoprotein with Oct4, mapping to the CR3 region of E7, which correlates to a distinct Oct4 transcriptional output. Introduction of E7 into HPV(-) cells and immortalised human keratinocytes led to transcriptional and phenotypic changes, which mimicked results in HPV(+) cells. These insights provide a plausible mechanism and consequences for a long-suspected interaction.

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<![CDATA[<i>In silico</i> analyses identify lncRNAs: WDFY3-AS2, BDNF-AS and AFAP1-AS1 as potential prognostic factors for patients with triple-negative breast tumors]]> https://www.researchpad.co/article/elastic_article_13870 Long non-coding RNAs (lncRNAs) are characterized as having 200 nucleotides or more and not coding any protein, and several been identified as differentially expressed in several human malignancies, including breast cancer.MethodsHere, we evaluated lncRNAs differentially expressed in triple-negative breast cancer (TNBC) from a cDNA microarray data set obtained in a previous study from our group. Using in silico analyses in combination with a review of the current literature, we identify three lncRNAs as potential prognostic factors for TNBC patients.ResultsWe found that the expression of WDFY3-AS2, BDNF-AS, and AFAP1-AS1 was associated with poor survival in patients with TNBCs. WDFY3-AS2 and BDNF-AS are lncRNAs known to play an important role in tumor suppression of different types of cancer, while AFAP1-AS1 exerts oncogenic activity.ConclusionOur findings provided evidence that WDFY3-AS2, BDNF-AS, and AFAP1-AS1 may be potential prognostic factors in TNBC development. ]]> <![CDATA[ <i>ONECUT2</i> upregulation is associated with CpG hypomethylation at promoter‐proximal DNA in gastric cancer and triggers <i>ACSL5</i> ]]> https://www.researchpad.co/article/elastic_article_7045 What's new?

DNA hypomethylation can promote cancer development through activation of genes with oncogenic potential. Here, the authors found that CpGs in the promoter‐proximal DNA of ONECUT2 were hypomethylated in intestinal metaplasia and gastric cancers, and that hypomethylation was associated with ONECUT2 upregulation. Functional analysis demonstrated that ONECUT2 has oncogenic potential and could activate ACSL5, which is also expressed in intestinal metaplasia, suggesting that ONECUT2 and ACSL5 may cooperate to promote intestinal differentiation or development of gastric cancer. Taken together, the findings suggest that ONECUT2 and its downstream target ACSL5 could be used to develop early detection biomarkers and prevent gastric carcinogenesis.

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<![CDATA[Quantification of multicellular colonization in tumor metastasis using exome‐sequencing data]]> https://www.researchpad.co/article/N229b15d0-e860-4e5b-9883-031a99778141

Metastasis is a major cause of cancer‐related mortality, and it is essential to understand how metastasis occurs in order to overcome it. One relevant question is the origin of a metastatic tumor cell population. Although the hypothesis of a single‐cell origin for metastasis from a primary tumor has long been prevalent, several recent studies using mouse models have supported a multicellular origin of metastasis. Human bulk whole‐exome sequencing (WES) studies also have demonstrated a multiple “clonal” origin of metastasis, with different mutational compositions. Specifically, there has not yet been strong research to determine how many founder cells colonize a metastatic tumor. To address this question, under the metastatic model of “single bottleneck followed by rapid growth,” we developed a method to quantify the “founder cell population size” in a metastasis using paired WES data from primary and metachronous metastatic tumors. Simulation studies demonstrated the proposed method gives unbiased results with sufficient accuracy in the range of realistic settings. Applying the proposed method to real WES data from four colorectal cancer patients, all samples supported a multicellular origin of metastasis and the founder size was quantified, ranging from 3 to 17 cells. Such a wide‐range of founder sizes estimated by the proposed method suggests that there are large variations in genetic similarity between primary and metastatic tumors in the same subjects, which may explain the observed (dis)similarity of drug responses between tumors.

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<![CDATA[Sensitivity analysis of agent-based simulation utilizing massively parallel computation and interactive data visualization]]> https://www.researchpad.co/article/5c8823e3d5eed0c484639255

An essential step in the analysis of agent-based simulation is sensitivity analysis, which namely examines the dependency of parameter values on simulation results. Although a number of approaches have been proposed for sensitivity analysis, they still have limitations in exhaustivity and interpretability. In this study, we propose a novel methodology for sensitivity analysis of agent-based simulation, MASSIVE (Massively parallel Agent-based Simulations and Subsequent Interactive Visualization-based Exploration). MASSIVE takes a unique paradigm, which is completely different from those of sensitivity analysis methods developed so far, By combining massively parallel computation and interactive data visualization, MASSIVE enables us to inspect a broad parameter space intuitively. We demonstrated the utility of MASSIVE by its application to cancer evolution simulation, which successfully identified conditions that generate heterogeneous tumors. We believe that our approach would be a de facto standard for sensitivity analysis of agent-based simulation in an era of evergrowing computational technology. All the results form our MASSIVE analysis are available at https://www.hgc.jp/~niiyan/massive.

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<![CDATA[Bottom-up, integrated -omics analysis identifies broadly dosage-sensitive genes in breast cancer samples from TCGA]]> https://www.researchpad.co/article/5c605a78d5eed0c4847cd00d

The massive genomic data from The Cancer Genome Atlas (TCGA), including proteomics data from Clinical Proteomic Tumor Analysis Consortium (CPTAC), provides a unique opportunity to study cancer systematically. While most observations are made from a single type of genomics data, we apply big data analytics and systems biology approaches by simultaneously analyzing DNA amplification, mRNA and protein abundance. Using multiple genomic profiles, we have discovered widespread dosage compensation for the extensive aneuploidy observed in TCGA breast cancer samples. We do identify 11 genes that show strong correlation across all features (DNA/mRNA/protein) analogous to that of the well-known oncogene HER2 (ERBB2). These genes are generally less well-characterized regarding their role in cancer and we advocate their further study. We also discover that shRNA knockdown of these genes has an impact on cancer cell growth, suggesting a vulnerability that could be used for cancer therapy. Our study shows the advantages of systematic big data methodologies and also provides future research directions.

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<![CDATA[Identification of long intergenic non-coding RNAs (lincRNAs) deregulated in gastrointestinal stromal tumors (GISTs)]]> https://www.researchpad.co/article/5c2151b6d5eed0c4843fb86f

Long intergenic non-coding RNAs (lincRNAs) are >200 nucleotides long non-coding RNAs, which have been shown to be implicated in carcinogenic processes by interacting with cancer associated genes or other non-coding RNAs. However, their role in development of rare gastrointestinal stromal tumors (GISTs) is barely investigated. Therefore, the aim of this study was to define lincRNAs deregulated in GIST and find new GIST-lincRNA associations. Next-generation sequencing data of paired GIST and adjacent tissue samples from 15 patients were subjected to a web-based lincRNA analysis. Three deregulated lincRNAs (MALAT1, H19 and FENDRR; adjusted p-value < 0.05) were selected for expression validation in a larger group of patients (n = 22) by RT-qPCR method. However, only H19 and FENDRR showed significant upregulation in the validation cohort (adjusted p < 0.05). Further, we performed correlation analyses between expression levels of deregulated lincRNAs and GIST-associated oncogenes or GIST deregulated microRNAs. We found high positive correlations between expression of H19 and known GIST related oncogene ETV1, and between H19 and miR-455-3p. These findings expand the knowledge on lincRNAs deregulated in GIST and may be an important resource for the future studies investigating lincRNAs functionally relevant to GIST carcinogenesis.

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<![CDATA[Role for the Mammalian Swi5-Sfr1 Complex in DNA Strand Break Repair through Homologous Recombination]]> https://www.researchpad.co/article/5989da4aab0ee8fa60b8c9cc

In fission yeast, the Swi5-Sfr1 complex plays an important role in homologous recombination (HR), a pathway crucial for the maintenance of genomic integrity. Here we identify and characterize mammalian Swi5 and Sfr1 homologues. Mouse Swi5 and Sfr1 are nuclear proteins that form a complex in vivo and in vitro. Swi5 interacts in vitro with Rad51, the DNA strand-exchange protein which functions during HR. By generating Swi5−/− and Sfr1−/− embryonic stem cell lines, we found that both proteins are mutually interdependent for their stability. Importantly, the Swi5-Sfr1 complex plays a role in HR when Rad51 function is perturbed in vivo by expression of a BRC peptide from BRCA2. Swi5−/− and Sfr1−/− cells are selectively sensitive to agents that cause DNA strand breaks, in particular ionizing radiation, camptothecin, and the Parp inhibitor olaparib. Consistent with a role in HR, sister chromatid exchange induced by Parp inhibition is attenuated in Swi5−/− and Sfr1−/− cells, and chromosome aberrations are increased. Thus, Swi5-Sfr1 is a newly identified complex required for genomic integrity in mammalian cells with a specific role in the repair of DNA strand breaks.

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<![CDATA[Short Telomeres Initiate Telomere Recombination in Primary and Tumor Cells]]> https://www.researchpad.co/article/5989da0bab0ee8fa60b77a00

Human tumors that lack telomerase maintain telomeres by alternative lengthening mechanisms. Tumors can also form in telomerase-deficient mice; however, the genetic mechanism responsible for tumor growth without telomerase is unknown. In yeast, several different recombination pathways maintain telomeres in the absence of telomerase—some result in telomere maintenance with minimal effects on telomere length. To examine non-telomerase mechanisms for telomere maintenance in mammalian cells, we used primary cells and lymphomas from telomerase-deficient mice (mTR−/− and Eμmyc+mTR−/−) and CAST/EiJ mouse embryonic fibroblast cells. These cells were analyzed using pq-ratio analysis, telomere length distribution outliers, CO-FISH, Q-FISH, and multicolor FISH to detect subtelomeric recombination. Telomere length was maintained during long-term growth in vivo and in vitro. Long telomeres, characteristic of human ALT cells, were not observed in either late passage or mTR−/− tumor cells; instead, we observed only minimal changes in telomere length. Telomere length variation and subtelomeric recombination were frequent in cells with short telomeres, indicating that length maintenance is due to telomeric recombination. We also detected telomere length changes in primary mTR−/− cells that had short telomeres. Using mouse mTR+/− and human hTERT+/− primary cells with short telomeres, we found frequent length changes indicative of recombination. We conclude that telomere maintenance by non-telomerase mechanisms, including recombination, occurs in primary cells and is initiated by short telomeres, even in the presence of telomerase. Most intriguing, our data indicate that some non-telomerase telomere maintenance mechanisms occur without a significant increase in telomere length.

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<![CDATA[AML1/ETO Oncoprotein Is Directed to AML1 Binding Regions and Co-Localizes with AML1 and HEB on Its Targets]]> https://www.researchpad.co/article/5989da66ab0ee8fa60b91f46

A reciprocal translocation involving chromosomes 8 and 21 generates the AML1/ETO oncogenic transcription factor that initiates acute myeloid leukemia by recruiting co-repressor complexes to DNA. AML1/ETO interferes with the function of its wild-type counterpart, AML1, by directly targeting AML1 binding sites. However, transcriptional regulation determined by AML1/ETO probably relies on a more complex network, since the fusion protein has been shown to interact with a number of other transcription factors, in particular E-proteins, and may therefore target other sites on DNA. Genome-wide chromatin immunoprecipitation and expression profiling were exploited to identify AML1/ETO-dependent transcriptional regulation. AML1/ETO was found to co-localize with AML1, demonstrating that the fusion protein follows the binding pattern of the wild-type protein but does not function primarily by displacing it. The DNA binding profile of the E-protein HEB was grossly rearranged upon expression of AML1/ETO, and the fusion protein was found to co-localize with both AML1 and HEB on many of its regulated targets. Furthermore, the level of HEB protein was increased in both primary cells and cell lines expressing AML1/ETO. Our results suggest a major role for the functional interaction of AML1/ETO with AML1 and HEB in transcriptional regulation determined by the fusion protein.

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<![CDATA[Interplay between BRCA1 and RHAMM Regulates Epithelial Apicobasal Polarization and May Influence Risk of Breast Cancer]]> https://www.researchpad.co/article/5989da34ab0ee8fa60b85897

Genetic analysis identifies the HMMR gene as a modifier of the breast cancer risk associated with BRCA1 gene mutation, while cell biological analysis of the protein product suggests a function in regulating development of the mammary gland.

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<![CDATA[SUMO Modification Regulates BLM and RAD51 Interaction at Damaged Replication Forks]]> https://www.researchpad.co/article/5989da28ab0ee8fa60b818c9

SUMO modification of BLM controls the switch between BLM's pro- and anti-recombinogenic roles in homologous recombination following DNA damage during replication.

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<![CDATA[The Genomic Landscape of the Ewing Sarcoma Family of Tumors Reveals Recurrent STAG2 Mutation]]> https://www.researchpad.co/article/5989dac5ab0ee8fa60bb22b3

The Ewing sarcoma family of tumors (EFT) is a group of highly malignant small round blue cell tumors occurring in children and young adults. We report here the largest genomic survey to date of 101 EFT (65 tumors and 36 cell lines). Using a combination of whole genome sequencing and targeted sequencing approaches, we discover that EFT has a very low mutational burden (0.15 mutations/Mb) but frequent deleterious mutations in the cohesin complex subunit STAG2 (21.5% tumors, 44.4% cell lines), homozygous deletion of CDKN2A (13.8% and 50%) and mutations of TP53 (6.2% and 71.9%). We additionally note an increased prevalence of the BRCA2 K3326X polymorphism in EFT patient samples (7.3%) compared to population data (OR 7.1, p = 0.006). Using whole transcriptome sequencing, we find that 11% of tumors pathologically diagnosed as EFT lack a typical EWSR1 fusion oncogene and that these tumors do not have a characteristic Ewing sarcoma gene expression signature. We identify samples harboring novel fusion genes including FUS-NCATc2 and CIC-FOXO4 that may represent distinct small round blue cell tumor variants. In an independent EFT tissue microarray cohort, we show that STAG2 loss as detected by immunohistochemistry may be associated with more advanced disease (p = 0.15) and a modest decrease in overall survival (p = 0.10). These results significantly advance our understanding of the genomic and molecular underpinnings of Ewing sarcoma and provide a foundation towards further efforts to improve diagnosis, prognosis, and precision therapeutics testing.

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<![CDATA[Inferring Clonal Composition from Multiple Sections of a Breast Cancer]]> https://www.researchpad.co/article/5989da33ab0ee8fa60b854dd

Cancers arise from successive rounds of mutation and selection, generating clonal populations that vary in size, mutational content and drug responsiveness. Ascertaining the clonal composition of a tumor is therefore important both for prognosis and therapy. Mutation counts and frequencies resulting from next-generation sequencing (NGS) potentially reflect a tumor's clonal composition; however, deconvolving NGS data to infer a tumor's clonal structure presents a major challenge. We propose a generative model for NGS data derived from multiple subsections of a single tumor, and we describe an expectation-maximization procedure for estimating the clonal genotypes and relative frequencies using this model. We demonstrate, via simulation, the validity of the approach, and then use our algorithm to assess the clonal composition of a primary breast cancer and associated metastatic lymph node. After dividing the tumor into subsections, we perform exome sequencing for each subsection to assess mutational content, followed by deep sequencing to precisely count normal and variant alleles within each subsection. By quantifying the frequencies of 17 somatic variants, we demonstrate that our algorithm predicts clonal relationships that are both phylogenetically and spatially plausible. Applying this method to larger numbers of tumors should cast light on the clonal evolution of cancers in space and time.

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<![CDATA[Brg1 Loss Attenuates Aberrant Wnt-Signalling and Prevents Wnt-Dependent Tumourigenesis in the Murine Small Intestine]]> https://www.researchpad.co/article/5989daf5ab0ee8fa60bc2a13

Tumourigenesis within the intestine is potently driven by deregulation of the Wnt pathway, a process epigenetically regulated by the chromatin remodelling factor Brg1. We aimed to investigate this interdependency in an in vivo setting and assess the viability of Brg1 as a potential therapeutic target. Using a range of transgenic approaches, we deleted Brg1 in the context of Wnt-activated murine small intestinal epithelium. Pan-epithelial loss of Brg1 using VillinCreERT2 and AhCreERT transgenes attenuated expression of Wnt target genes, including a subset of stem cell-specific genes and suppressed Wnt-driven tumourigenesis improving animal survival. A similar increase in survival was observed when Wnt activation and Brg1 loss were restricted to the Lgr5 expressing intestinal stem cell population. We propose a mechanism whereby Brg1 function is required for aberrant Wnt signalling and ultimately for the maintenance of the tumour initiating cell compartment, such that loss of Brg1 in an Apc-deficient context suppresses adenoma formation. Our results highlight potential therapeutic value of targeting Brg1 and serve as a proof of concept that targeting the cells of origin of cancer may be of therapeutic relevance.

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<![CDATA[Algorithms to Model Single Gene, Single Chromosome, and Whole Genome Copy Number Changes Jointly in Tumor Phylogenetics]]> https://www.researchpad.co/article/5989da5bab0ee8fa60b8fd58

We present methods to construct phylogenetic models of tumor progression at the cellular level that include copy number changes at the scale of single genes, entire chromosomes, and the whole genome. The methods are designed for data collected by fluorescence in situ hybridization (FISH), an experimental technique especially well suited to characterizing intratumor heterogeneity using counts of probes to genetic regions frequently gained or lost in tumor development. Here, we develop new provably optimal methods for computing an edit distance between the copy number states of two cells given evolution by copy number changes of single probes, all probes on a chromosome, or all probes in the genome. We then apply this theory to develop a practical heuristic algorithm, implemented in publicly available software, for inferring tumor phylogenies on data from potentially hundreds of single cells by this evolutionary model. We demonstrate and validate the methods on simulated data and published FISH data from cervical cancers and breast cancers. Our computational experiments show that the new model and algorithm lead to more parsimonious trees than prior methods for single-tumor phylogenetics and to improved performance on various classification tasks, such as distinguishing primary tumors from metastases obtained from the same patient population.

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<![CDATA[Specific Variants in the MLH1 Gene Region May Drive DNA Methylation, Loss of Protein Expression, and MSI-H Colorectal Cancer]]> https://www.researchpad.co/article/5989da54ab0ee8fa60b8e93d

Background

We previously identified an association between a mismatch repair gene, MLH1, promoter SNP (rs1800734) and microsatellite unstable (MSI-H) colorectal cancers (CRCs) in two samples. The current study expanded on this finding as we explored the genetic basis of DNA methylation in this region of chromosome 3. We hypothesized that specific polymorphisms in the MLH1 gene region predispose it to DNA methylation, resulting in the loss of MLH1 gene expression, mismatch-repair function, and consequently to genome-wide microsatellite instability.

Methodology/Principal Findings

We first tested our hypothesis in one sample from Ontario (901 cases, 1,097 controls) and replicated major findings in two additional samples from Newfoundland and Labrador (479 cases, 336 controls) and from Seattle (591 cases, 629 controls). Logistic regression was used to test for association between SNPs in the region of MLH1 and CRC, MSI-H CRC, MLH1 gene expression in CRC, and DNA methylation in CRC. The association between rs1800734 and MSI-H CRCs, previously reported in Ontario and Newfoundland, was replicated in the Seattle sample. Two additional SNPs, in strong linkage disequilibrium with rs1800734, showed strong associations with MLH1 promoter methylation, loss of MLH1 protein, and MSI-H CRC in all three samples. The logistic regression model of MSI-H CRC that included MLH1-promoter-methylation status and MLH1 immunohisotchemistry status fit most parsimoniously in all three samples combined. When rs1800734 was added to this model, its effect was not statistically significant (P-value  = 0.72 vs. 2.3×10−4 when the SNP was examined alone).

Conclusions/Significance

The observed association of rs1800734 with MSI-H CRC occurs through its effect on the MLH1 promoter methylation, MLH1 IHC deficiency, or both.

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<![CDATA[An Accurate Prostate Cancer Prognosticator Using a Seven-Gene Signature Plus Gleason Score and Taking Cell Type Heterogeneity into Account]]> https://www.researchpad.co/article/5989da1fab0ee8fa60b7e4ce

One of the major challenges in the development of prostate cancer prognostic biomarkers is the cellular heterogeneity in tissue samples. We developed an objective Cluster-Correlation (CC) analysis to identify gene expression changes in various cell types that are associated with progression. In the Cluster step, samples were clustered (unsupervised) based on the expression values of each gene through a mixture model combined with a multiple linear regression model in which cell-type percent data were used for decomposition. In the Correlation step, a Chi-square test was used to select potential prognostic genes. With CC analysis, we identified 324 significantly expressed genes (68 tumor and 256 stroma cell expressed genes) which were strongly associated with the observed biochemical relapse status. Significance Analysis of Microarray (SAM) was then utilized to develop a seven-gene classifier. The Classifier has been validated using two independent Data Sets. The overall prediction accuracy and sensitivity is 71% and 76%, respectively. The inclusion of the Gleason sum to the seven-gene classifier raised the prediction accuracy and sensitivity to 83% and 76% respectively based on independent testing. These results indicated that our prognostic model that includes cell type adjustments and using Gleason score and the seven-gene signature has some utility for predicting outcomes for prostate cancer for individual patients at the time of prognosis. The strategy could have applications for improving marker performance in other cancers and other diseases.

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<![CDATA[Acute Pancreatitis Accelerates Initiation and Progression to Pancreatic Cancer in Mice Expressing Oncogenic Kras in the Nestin Cell Lineage]]> https://www.researchpad.co/article/5989d9d5ab0ee8fa60b65993

Targeting of oncogenic Kras to the pancreatic Nestin-expressing embryonic progenitor cells and subsequently to the adult acinar compartment and Nestin-expressing cells is sufficient for the development of low grade pancreatic intraepithelial neoplasia (PanIN) between 2 and 4 months. The mice die around 6 month-old of unrelated causes, and it is therefore not possible to assess whether the lesions will progress to carcinoma. We now report that two brief episodes of caerulein-induced acute pancreatitis in 2 month-old mice causes rapid PanIN progression and pancreatic ductal adenocarcinoma (PDAC) development by 4 months of age. These events occur with similar frequency as observed in animals where the oncogene is targeted during embryogenesis to all pancreatic cell types. Thus, these data show that oncogenic Kras-driven PanIN originating in a non-ductal compartment can rapidly progress to PDAC when subjected to a brief inflammatory insult.

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<![CDATA[Second Generation Sequencing of the Mesothelioma Tumor Genome]]> https://www.researchpad.co/article/5989d9dfab0ee8fa60b6915a

The current paradigm for elucidating the molecular etiology of cancers relies on the interrogation of small numbers of genes, which limits the scope of investigation. Emerging second-generation massively parallel DNA sequencing technologies have enabled more precise definition of the cancer genome on a global scale. We examined the genome of a human primary malignant pleural mesothelioma (MPM) tumor and matched normal tissue by using a combination of sequencing-by-synthesis and pyrosequencing methodologies to a 9.6X depth of coverage. Read density analysis uncovered significant aneuploidy and numerous rearrangements. Method-dependent informatics rules, which combined the results of different sequencing platforms, were developed to identify and validate candidate mutations of multiple types. Many more tumor-specific rearrangements than point mutations were uncovered at this depth of sequencing, resulting in novel, large-scale, inter- and intra-chromosomal deletions, inversions, and translocations. Nearly all candidate point mutations appeared to be previously unknown SNPs. Thirty tumor-specific fusions/translocations were independently validated with PCR and Sanger sequencing. Of these, 15 represented disrupted gene-encoding regions, including kinases, transcription factors, and growth factors. One large deletion in DPP10 resulted in altered transcription and expression of DPP10 transcripts in a set of 53 additional MPM tumors correlated with survival. Additionally, three point mutations were observed in the coding regions of NKX6-2, a transcription regulator, and NFRKB, a DNA-binding protein involved in modulating NFKB1. Several regions containing genes such as PCBD2 and DHFR, which are involved in growth factor signaling and nucleotide synthesis, respectively, were selectively amplified in the tumor. Second-generation sequencing uncovered all types of mutations in this MPM tumor, with DNA rearrangements representing the dominant type.

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