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Systematic identification of genes with a cancer-testis expression pattern in 19 cancer types.

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TLDR
This study integrates transcriptomics data from multiple databases and systematically identifies 876 new CT genes in 19 cancer types to propose that extremely highly expressed CT genes (EECTGs) are potential drivers activated through epigenetic mechanisms and provide methods for identifying epigenetic-driver genes of cancer, which could serve as targets of future cancer therapies.
Abstract
Cancer-testis (CT) genes represent the similarity between the processes of spermatogenesis and tumorigenesis. It is possible that their selective expression pattern can help identify driver genes in cancer. In this study, we integrate transcriptomics data from multiple databases and systematically identify 876 new CT genes in 19 cancer types. We explore their relationship with testis-specific regulatory elements. We propose that extremely highly expressed CT genes (EECTGs) are potential drivers activated through epigenetic mechanisms. We find mutually exclusive associations between EECTGs and somatic mutations in mutated genes, such as PIK3CA in breast cancer. We also provide evidence that promoter demethylation and close non-coding RNAs (namely, CT-ncRNAs) may be two mechanisms to reactivate EECTG gene expression. We show that the meiosis-related EECTG (MEIOB) and its nearby CT-ncRNA have a role in tumorigenesis in lung adenocarcinoma. Our findings provide methods for identifying epigenetic-driver genes of cancer, which could serve as targets of future cancer therapies.

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Journal ArticleDOI

Genomic basis for RNA alterations in cancer

TL;DR: The most comprehensive catalogue of cancer-associated gene alterations to date, obtained by characterizing tumour transcriptomes from 1,188 donors of the Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium of the International Cancer Genome Consortium (ICGC) and The Cancer Gome Atlas (TCGA) was presented in this article.
Journal ArticleDOI

A novel plasma circular RNA circFARSA is a potential biomarker for non-small cell lung cancer.

TL;DR: The circRNA profile of NSCLC is revealed for the first time and the evidence of plasma circFARSA as a potential noninvasive biomarker for this malignancy is provided.
Journal ArticleDOI

Cancer-testis antigens: Unique cancer stem cell biomarkers and targets for cancer therapy.

TL;DR: Analysis of CTA expression patterns in embryonic germ and somatic cells, pluripotent and multipotent stem cells, cancer stem cells and their cell descendants indicates that rearrangements of characteristic CTA profiles (aberrant expression) could be associated with cancer transformation and failure of the developmental program of cell lineage specification and germ line restriction.
Journal ArticleDOI

Emerging Contributions of Cancer/Testis Antigens to Neoplastic Behaviors

TL;DR: Emerging evidence that demonstrates that CT antigens can confer a selective advantage to tumor cells by promoting oncogenic processes or permitting evasion of tumor-suppressive mechanisms is discussed.
References
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Journal ArticleDOI

Systematic and integrative analysis of large gene lists using DAVID bioinformatics resources.

TL;DR: By following this protocol, investigators are able to gain an in-depth understanding of the biological themes in lists of genes that are enriched in genome-scale studies.
Journal ArticleDOI

RNA-Seq: a revolutionary tool for transcriptomics

TL;DR: The RNA-Seq approach to transcriptome profiling that uses deep-sequencing technologies provides a far more precise measurement of levels of transcripts and their isoforms than other methods.
Journal ArticleDOI

TopHat: discovering splice junctions with RNA-Seq

TL;DR: The TopHat pipeline is much faster than previous systems, mapping nearly 2.2 million reads per CPU hour, which is sufficient to process an entire RNA-Seq experiment in less than a day on a standard desktop computer.
Journal ArticleDOI

Differential gene and transcript expression analysis of RNA-seq experiments with TopHat and Cufflinks

TL;DR: This protocol begins with raw sequencing reads and produces a transcriptome assembly, lists of differentially expressed and regulated genes and transcripts, and publication-quality visualizations of analysis results, which takes less than 1 d of computer time for typical experiments and ∼1 h of hands-on time.
Journal ArticleDOI

Comprehensive molecular portraits of human breast tumours

Daniel C. Koboldt, +355 more
- 04 Oct 2012 - 
TL;DR: The ability to integrate information across platforms provided key insights into previously defined gene expression subtypes and demonstrated the existence of four main breast cancer classes when combining data from five platforms, each of which shows significant molecular heterogeneity.
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