scholarly journals CNCDatabase: a database of non-coding cancer drivers

2020 ◽  
Vol 49 (D1) ◽  
pp. D1094-D1101
Author(s):  
Eric Minwei Liu ◽  
Alexander Martinez-Fundichely ◽  
Rajesh Bollapragada ◽  
Maurice Spiewack ◽  
Ekta Khurana
Keyword(s):  
Tumor Development ◽  
Luciferase Reporter ◽  
Whole Genome ◽  
Gene Promoters ◽  
Genome Sequences ◽  
Coding Regions ◽  
Cancer Types ◽  
Cancer Drivers ◽  
Non Coding Rnas ◽  
Experimental Validations

Abstract Most mutations in cancer genomes occur in the non-coding regions with unknown impact on tumor development. Although the increase in the number of cancer whole-genome sequences has revealed numerous putative non-coding cancer drivers, their information is dispersed across multiple studies making it difficult to understand their roles in tumorigenesis of different cancer types. We have developed CNCDatabase, Cornell Non-coding Cancer driver Database (https://cncdatabase.med.cornell.edu/) that contains detailed information about predicted non-coding drivers at gene promoters, 5′ and 3′ UTRs (untranslated regions), enhancers, CTCF insulators and non-coding RNAs. CNCDatabase documents 1111 protein-coding genes and 90 non-coding RNAs with reported drivers in their non-coding regions from 32 cancer types by computational predictions of positive selection using whole-genome sequences; differential gene expression in samples with and without mutations; or another set of experimental validations including luciferase reporter assays and genome editing. The database can be easily modified and scaled as lists of non-coding drivers are revised in the community with larger whole-genome sequencing studies, CRISPR screens and further experimental validations. Overall, CNCDatabase provides a helpful resource for researchers to explore the pathological role of non-coding alterations in human cancers.

scholarly journals CNCDatabase: a database of non-coding cancer drivers

2020 ◽  
Author(s):  
Eric Minwei Liu ◽  
Alexander Martinez-Fundichely ◽  
Rajesh Bollapragada ◽  
Maurice Spiewack ◽  
Ekta Khurana
Keyword(s):  
Gene Expression ◽  
Luciferase Reporter ◽  
Whole Genome ◽  
Gene Promoters ◽  
Genome Sequences ◽  
Coding Regions ◽  
Cancer Types ◽  
Cancer Drivers ◽  
Non Coding Rnas ◽  
Experimental Validations

ABSTRACTMost mutations in cancer genomes occur in the non-coding regions with unknown impact to tumor development. Although the increase in number of cancer whole-genome sequences has revealed numerous putative non-coding cancer drivers, their information is dispersed across multiple studies and thus it is difficult to bridge the understanding of non-coding alterations, the genes they impact and the supporting evidence for their role in tumorigenesis across multiple cancer types. To address this gap, we have developed CNCDatabase, Cornell Non-Coding Cancer driver Database (https://cncdatabase.med.cornell.edu/) that contains detailed information about predicted non-coding drivers at gene promoters, 5’ and 3’ UTRs (untranslated regions), enhancers, CTCF insulators and non-coding RNAs. CNCDatabase documents 1,111 protein-coding genes and 90 non-coding RNAs with reported drivers in their non-coding regions from 32 cancer types by computational predictions of positive selection in whole-genome sequences; differential gene expression in samples with and without mutations; or another set of experimental validations including luciferase reporter assays and genome editing. The database can be easily modified and scaled as lists of non-coding drivers are revised in the community with larger whole-genome sequencing studies, CRISPR screens and further experimental validations. Overall, CNCDatabase provides a helpful resource for researchers to explore the pathological role of non-coding alterations and their associations with gene expression in human cancers.

scholarly journals LncRNA SNHG15 modulates gastric cancer tumorigenesis by impairing miR-506-5p expression

2021 ◽  
Author(s):  
Zhiping Chen ◽  
Tianyu Zhong ◽  
Tao Li ◽  
Jinghua Zhong ◽  
Yang Tang ◽  
...  
Keyword(s):  
Gastric Cancer ◽  
Cell Proliferation ◽  
Poor Prognosis ◽  
Tumor Development ◽  
Luciferase Reporter ◽  
Reporter Assay ◽  
Ags Cells ◽  
Direct Target ◽  
Non Coding Rnas ◽  
Novel Target

The gastric cancer (GC) patients commonly have a poor prognosis due to its invasiveness and distant metastasis. Growing evidence proved that aberrant long non-coding RNAs (lncRNAs) expression contributes to tumor development and progression. LncRNA SNHG15 has been reported to be involved in many different kinds of cancer, while its role in GC remains unclear. In the present study, we found that SNHG15 was up-regulated in GC tissues and cell lines. Silencing SNHG15 suppressed proliferation migration, invasion and promoted apoptosis of AGS cells. More importantly, microRNA-506-5p (miR-506-5p) was predicted as a direct target of SNHG15 by binding its 3’-UTR and further verified using luciferase reporter assay. Meanwhile, the results of rescue experiments revealed that knockdown of miR-506-5p expression reversed the functional effects of SNHG15 silenced on cell proliferation, migration, invasion and apoptosis. In conclusion, our findings revealed that SNHG15 executed oncogenic properties in GC progression through targeting miR-506-5p, which might provide a novel target for the GC treatment.

scholarly journals Ennet: construction of potential cancer-driving networks based on somatic enhancer mutations only

2017 ◽  
Author(s):  
Ya Cui ◽  
Yiwei Niu ◽  
Xueyi Teng ◽  
Dan Wang ◽  
Huaxia Luo ◽  
...  
Keyword(s):  
Neural Development ◽  
Somatic Mutations ◽  
Gene Interactions ◽  
Whole Genome ◽  
Sequencing Technology ◽  
Cancer Types ◽  
Cancer Drivers ◽  
New Perspective ◽  
Pan Cancer ◽  
Potential Cancer

AbstractWhole genome sequencing technology has facilitated the discovery of a large number of somatic mutations in enhancers (SMEs), whereas the utility of SMEs in tumorigenesis has not been fully explored. Here we present Ennet, a method to comprehensively investigate SMEs enriched networks (SME-networks) in cancer by integrating SMEs, enhancer-gene interactions and gene-gene interactions. Using Ennet, we performed a pan-cancer analysis in 2004 samples from 8 cancer types and found many well-known cancer drivers were involved in the SME-networks, includingESR1,SMAD3,MYC,EGFR,BCL2andPAX5. Meanwhile, Ennet also identified many new networks with less characterization but have potentially important roles in cancer, including a large SME-network in medulloblastoma (MB), which contains genes enriched in the glutamate receptor and neural development pathways. Interestingly, SME-networks are specific across cancer types, and the vast majority of the genes identified by Ennet have few mutations in gene bodies. Collectively, our work suggests that using enhancer-only somatic mutations can be an effective way to discover potential cancer-driving networks. Ennet provides a new perspective to explore new mechanisms for tumor progression from SMEs.

scholarly journals Population Genomic Analysis of 962 Whole Genome Sequences of Humans Reveals Natural Selection in Non-Coding Regions

PLoS ONE ◽  
2015 ◽  
Vol 10 (3) ◽  
pp. e0121644 ◽  
Author(s):  
Fuli Yu ◽  
Jian Lu ◽  
Xiaoming Liu ◽  
Elodie Gazave ◽  
Diana Chang ◽  
...  
Keyword(s):  
Natural Selection ◽  
Genomic Analysis ◽  
Whole Genome ◽  
Genome Sequences ◽  
Coding Regions ◽  
Population Genomic

scholarly journals Profiling of NUMTs in Gingivobuccal Oral Cancer

2020 ◽  
Author(s):  
Arindam Palodhi ◽  
Tanisha Singla ◽  
Arindam Maitra
Keyword(s):  
Squamous Cell Carcinoma ◽  
Oral Cancer ◽  
Oral Squamous Cell Carcinoma ◽  
Cell Carcinoma ◽  
Whole Genome ◽  
Genome Sequences ◽  
Pcr Assay ◽  
Cancer Types ◽  
Mitochondrial Sequences ◽  
Paired Tumour

AbstractVery little information exists on the NUclear MiTochondrial sequences (NUMTs) in oral squamous cell carcinoma-gingivobuccal (OSCC-GB). We analysed whole genome sequences obtained from paired tumour and blood DNA from 25 patients of OSCC-GB for detecting NUMTs. Nine potential somatic NUMTs and 78 germline NUMTs were identified in these patients. None of the somatic NUMTs could be confirmed by PCR assay. None of the germline NUMTs were found to be specific for OSCC-GB. Although there have been recent reports on detection of somatic NUMTs in other cancer types, our results suggest NUMTs, both somatic and germline, are not involved in OSCC-GB.

scholarly journals Scanning window analysis of non-coding regions within normal-tumor whole-genome sequence samples

2020 ◽  
Author(s):  
J P Torcivia ◽  
R Mazumder
Keyword(s):  
Colon Adenocarcinoma ◽  
Whole Genome Sequence ◽  
Whole Genome ◽  
Coding Region ◽  
Coding Regions ◽  
Functional Aspects ◽  
Scanning Window ◽  
Cancer Types ◽  
Carcinoma Colon ◽  
Pan Cancer

Abstract Genomics has benefited from an explosion in affordable high-throughput technology for whole-genome sequencing. The regulatory and functional aspects in non-coding regions may be an important contributor to oncogenesis. Whole-genome tumor-normal paired alignments were used to examine the non-coding regions in five cancer types and two races. Both a sliding window and a binning strategy were introduced to uncover areas of higher than expected variation for additional study. We show that the majority of cancer associated mutations in 154 whole-genome sequences covering breast invasive carcinoma, colon adenocarcinoma, kidney renal papillary cell carcinoma, lung adenocarcinoma and uterine corpus endometrial carcinoma cancers and two races are found outside of the coding region (4 432 885 in non-gene regions versus 1 412 731 in gene regions). A pan-cancer analysis found significantly mutated windows (292 to 3881 in count) demonstrating that there are significant numbers of large mutated regions in the non-coding genome. The 59 significantly mutated windows were found in all studied races and cancers. These offer 16 regions ripe for additional study within 12 different chromosomes—2, 4, 5, 7, 10, 11, 16, 18, 20, 21 and X. Many of these regions were found in centromeric locations. The X chromosome had the largest set of universal windows that cluster almost exclusively in Xq11.1—an area linked to chromosomal instability and oncogenesis. Large consecutive clusters (super windows) were found (19 to 114 in count) providing further evidence that large mutated regions in the genome are influencing cancer development. We show remarkable similarity in highly mutated non-coding regions across both cancer and race.

scholarly journals Molecular Epidemiology and Whole-Genome Analysis of Bovine Foamy Virus in Japan

Viruses ◽  
2021 ◽  
Vol 13 (6) ◽  
pp. 1017
Author(s):  
Hirohisa Mekata ◽  
Tomohiro Okagawa ◽  
Satoru Konnai ◽  
Takayuki Miyazawa
Keyword(s):  
Phylogenetic Analyses ◽  
Foamy Virus ◽  
Pcr Analysis ◽  
Whole Genome ◽  
Genome Sequences ◽  
Whole Genome Analysis ◽  
Virus Family ◽  
Bovine Foamy Virus ◽  
Novel Genotype

Bovine foamy virus (BFV) is a member of the foamy virus family in cattle. Information on the epidemiology, transmission routes, and whole-genome sequences of BFV is still limited. To understand the characteristics of BFV, this study included a molecular survey in Japan and the determination of the whole-genome sequences of 30 BFV isolates. A total of 30 (3.4%, 30/884) cattle were infected with BFV according to PCR analysis. Cattle less than 48 months old were scarcely infected with this virus, and older animals had a significantly higher rate of infection. To reveal the possibility of vertical transmission, we additionally surveyed 77 pairs of dams and 3-month-old calves in a farm already confirmed to have BFV. We confirmed that one of the calves born from a dam with BFV was infected. Phylogenetic analyses revealed that a novel genotype was spread in Japan. In conclusion, the prevalence of BFV in Japan is relatively low and three genotypes, including a novel genotype, are spread in Japan.

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