Literature DB >> 23434521

Identification of somatic mutations in human prostate cancer by RNA-Seq.

Xiaolin Xu1, KaiChang Zhu, Feng Liu, Yue Wang, JianGuo Shen, Jizhong Jin, Zhong Wang, Lin Chen, Jiadong Li, Min Xu.   

Abstract

RNA-Seq is a recently developed tool to characterize transcriptomes using a massively parallel sequencing technique. In spite of its broad usage in gene expression profiling, RNA-Seq can also be used to discover single nucleotide variants in transcribed regions. Here we report the result of an analysis of transcriptome sequencing data of 5 human prostate cancer tissues. A total of 116 disruptive mutations (frameshift indels or nonsynonymous nucleotide substitutions) in 92 genes are revealed with high confidence. Among these genes, several candidates are of particular interest. For example, a frameshift insertion/deletion (indel) is found in the coding region of TNFSF10, which disrupts the intact open reading frame and undermines the ability of TNFSF10 to induce apoptosis, in consequence promoting abnormal tumor progression. In summary, our findings demonstrate the use of RNA-Seq in somatic mutation screening, and provide a list of candidate genes which can be used in prostate cancer diagnosis and treatment.
Copyright © 2013 Elsevier B.V. All rights reserved.

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Year:  2013        PMID: 23434521     DOI: 10.1016/j.gene.2013.01.046

Source DB:  PubMed          Journal:  Gene        ISSN: 0378-1119            Impact factor:   3.688


  9 in total

Review 1.  Single-nucleotide variants in human RNA: RNA editing and beyond.

Authors:  Yan Guo; Hui Yu; David C Samuels; Wei Yue; Scott Ness; Ying-Yong Zhao
Journal:  Brief Funct Genomics       Date:  2019-02-14       Impact factor: 4.241

2.  Alternative applications for distinct RNA sequencing strategies.

Authors:  Leng Han; Kasey C Vickers; David C Samuels; Yan Guo
Journal:  Brief Bioinform       Date:  2014-09-22       Impact factor: 11.622

3.  Identification of potential key genes and high-frequency mutant genes in prostate cancer by using RNA-Seq data.

Authors:  Ze Zhang; He Wu; Hong Zhou; Yunhe Gu; Yufeng Bai; Shiliang Yu; Ruihua An; Jiping Qi
Journal:  Oncol Lett       Date:  2018-01-24       Impact factor: 2.967

4.  Integrated RNA and DNA sequencing improves mutation detection in low purity tumors.

Authors:  Matthew D Wilkerson; Christopher R Cabanski; Wei Sun; Katherine A Hoadley; Vonn Walter; Lisle E Mose; Melissa A Troester; Peter S Hammerman; Joel S Parker; Charles M Perou; D Neil Hayes
Journal:  Nucleic Acids Res       Date:  2014-06-26       Impact factor: 16.971

5.  Practicability of detecting somatic point mutation from RNA high throughput sequencing data.

Authors:  Quanhu Sheng; Shilin Zhao; Chung-I Li; Yu Shyr; Yan Guo
Journal:  Genomics       Date:  2016-04-02       Impact factor: 5.736

6.  Gene profiling of bone around orthodontic mini-implants by RNA-sequencing analysis.

Authors:  Kyung-Yen Nahm; Jung Sun Heo; Jae-Hyung Lee; Dong-Yeol Lee; Kyu-Rhim Chung; Hyo-Won Ahn; Seong-Hun Kim
Journal:  Biomed Res Int       Date:  2015-02-11       Impact factor: 3.411

7.  Proteomic-coupled-network analysis of T877A-androgen receptor interactomes can predict clinical prostate cancer outcomes between White (non-Hispanic) and African-American groups.

Authors:  Naif Zaman; Paresa N Giannopoulos; Shafinaz Chowdhury; Eric Bonneil; Pierre Thibault; Edwin Wang; Mark Trifiro; Miltiadis Paliouras
Journal:  PLoS One       Date:  2014-11-19       Impact factor: 3.240

8.  Transcriptome analysis revealed chimeric RNAs, single nucleotide polymorphisms and allele-specific expression in porcine prenatal skeletal muscle.

Authors:  Yalan Yang; Zhonglin Tang; Xinhao Fan; Kui Xu; Yulian Mu; Rong Zhou; Kui Li
Journal:  Sci Rep       Date:  2016-06-29       Impact factor: 4.379

9.  Search for potential reading frameshifts in cds from Arabidopsis thaliana and other genomes.

Authors:  Y M Suvorova; M A Korotkova; K G Skryabin; E V Korotkov
Journal:  DNA Res       Date:  2019-04-01       Impact factor: 4.458

  9 in total

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