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

Wang, Cheng; Gu, Yayun; Zhang, Kai; Xie, Kaipeng; Zhu, Meng; Dai, Ningbin; Jiang, Yue; Guo, Xuejiang; Liu, Mingxi; Dai, Juncheng; Wu, Linxiang; Jin, Guangfu; Ma, Hongxia; Jiang, Tao; Yin, Rong; Xia, Yankai; Liu, Li; Wang, Shouyu; Shen, Bin; Huo, Ran; Wang, Qianghu; Xu, Lin; Yang, Liuqing; Huang, Xingxu; Shen, Hongbing; Sha, Jiahao; Hu, Zhibin

doi:10.1038/ncomms10499

Cited by 126 publications

(176 citation statements)

References 51 publications

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“…Interestingly, consistent with our previous hypothesis that de‐methylation was an important mechanism for the reactivation of CT genes in cancers, seminomas are also a group of cancers that lack of DNA methylation . Thus, the globally de‐methylated genomes of seminoma cells could serve as the epigenetic mechanism for CT genes expression in TGCT . However, in contrast to non‐germ cell solid cancer, CT genes in TGCT are prone to be expressed in samples with driver genes ( KIT , KRAS and NRAS ) mutations, which may be attributed to the altered aneuploidy and genomic instability in these samples.…”

Section: Discussionsupporting

confidence: 80%

“…Thus, the globally de‐methylated genomes of seminoma cells could serve as the epigenetic mechanism for CT genes expression in TGCT . However, in contrast to non‐germ cell solid cancer, CT genes in TGCT are prone to be expressed in samples with driver genes ( KIT , KRAS and NRAS ) mutations, which may be attributed to the altered aneuploidy and genomic instability in these samples. Additionally, we also observed a positive association between the number of expressed CT genes with different types of immune cells.…”

Section: Discussionmentioning

confidence: 99%

“…The expression data were quantified as raw read counts. In our previous study, we analyzed the transcriptome data of normal tissues (24 different organs from 175 individuals) from the Genotype‐Tissue Expression (GTEx) project (https://www.gtexportal.org/home/) and used specificity measure to classify all human genes (50 016) into six categories (C1‐C6) based on their expression pattern, including high confidence testis‐specific expressed protein coding genes (C1) and noncoding genes (C2), moderate confidence testis‐specific expressed protein‐coding genes (C3) and noncoding genes (C4), low‐confidence testis‐specific expressed genes (C5), genes with transcripts exhibiting a testis‐specific expression pattern (C6a), and genes without transcripts exhibiting a testis‐specific expression pattern (C6b). In this study, only 1061 protein‐coding genes and 1184 long noncoding RNAs (lncRNAs) exhibited testis‐specific expression pattern with high confidence (C1 and C2 groups) as well as a median expression greater than 0.5 fragments per kilobase of exon model per million reads mapped (FPKM) in normal testis samples were included .…”

Section: Methodsmentioning

confidence: 99%

“…In our previous study, we analyzed the transcriptome data of normal tissues (24 different organs from 175 individuals) from the Genotype‐Tissue Expression (GTEx) project (https://www.gtexportal.org/home/) and used specificity measure to classify all human genes (50 016) into six categories (C1‐C6) based on their expression pattern, including high confidence testis‐specific expressed protein coding genes (C1) and noncoding genes (C2), moderate confidence testis‐specific expressed protein‐coding genes (C3) and noncoding genes (C4), low‐confidence testis‐specific expressed genes (C5), genes with transcripts exhibiting a testis‐specific expression pattern (C6a), and genes without transcripts exhibiting a testis‐specific expression pattern (C6b). In this study, only 1061 protein‐coding genes and 1184 long noncoding RNAs (lncRNAs) exhibited testis‐specific expression pattern with high confidence (C1 and C2 groups) as well as a median expression greater than 0.5 fragments per kilobase of exon model per million reads mapped (FPKM) in normal testis samples were included . According to GENCODE v19 annotation data, lncRNAs were reclassified into 6 biotypes, including three prime overlapping ncRNA (lncRNAs located within the 3' UTR of protein‐coding genes), antisense (lncRNAs overlapping any protein‐coding genes on the opposite strand), lincRNA (long intergenic noncoding RNA with a length greater than 200 bp), sense intronic (lncRNAs located within the intron of any protein‐coding gene), sense overlapping (lncRNAs within any protein‐coding gene within its intron on the coding strand), and processed transcript (transcripts without an open reading frame).…”

Section: Methodsmentioning

confidence: 99%

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Comprehensive characterization of cancer‐testis genes in testicular germ cell tumor

Chang

Wang

et al. 2019

Cancer Medicine

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Cancer‐testis (CT) genes are a group of genes restrictedly expressed in testis and multiple cancers and can serve as candidate driver genes participating in the development of cancers. Our previous study identified a number of CT genes in nongerm cell tumors, but their expression pattern in testicular germ cell tumor (TGCT), a cancer type characterized by less genomic alterations, remained largely unknown. In this study, we systematically investigated the expression pattern of CT genes in TGCT samples and evaluated the transcriptome difference between TGCT and normal testis tissues, using datasets from the UCSC Xena platform, The Cancer Genome Atlas (TCGA) and the Genotype‐Tissue Expression (GTEx) project. Pathway enrichment analysis and survival analysis were conducted to evaluate the biological function and prognostic effect of expressed CT genes. We identified that 1036 testis‐specific expressed protein‐coding genes and 863 testis‐specific expressed long noncoding RNAs (lncRNAs) were expressed in TGCT samples, including 883 CT protein‐coding genes and 710 CT lncRNAs defined previously. The number of expressed CT genes was significantly higher in seminomas ( P = 3.48 × 10 −13 ) which were characterized by frequent mutations in driver genes ( KIT , KRAS and NRAS ). In contrast, the number of expressed CT genes showed a moderate negative correlation with the fraction of copy number altered genomes (cor = −0.28, P = 1.20 × 10 −3 ). Unlike other cancers, our analysis revealed that 96.16% of the CT genes were down‐regulated in TGCT samples, while CT genes in stem cell maintenance related pathways were up‐regulated. Further survival analysis provided evidence that CT genes could also predict the prognosis of TGCT patients with both disease‐free interval and progression‐free interval as clinical endpoints. Taken together, our study provided a global view of CT genes in TGCT and provided evidence that CT genes played important roles in the progression and maintenance of TGCT.

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Section: Discussionsupporting

confidence: 80%

Section: Discussionmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

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Comprehensive characterization of cancer‐testis genes in testicular germ cell tumor

Chang

Wang

et al. 2019

Cancer Medicine

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“…For example the peptides derived from CT antigens have been used in the clinical trials for several types of cancer, including head and neck cancer and lung cancer .To date, more than 200 known CT genes have been identified in the CT database (http://www.cta.lncc.br) . Using publically available databases, such as The Cancer Genome Atlas (TCGA), The Encyclopedia of DNA Elements (ENCODE), and The Functional Annotation of The Mammalian Genome (FANTOM), we previously performed a comprehensive analysis to describe the expression characteristics of CT genes and define the extremely highly expressed CT genes (EECTGs) that may be potential epi‐driver genes in 19 cancer types . Epi‐driver genes are expressed aberrantly in tumors but not frequently mutated and regulated by DNA methylation or chromatin modification according to the criteria demonstrated by Vogelstein .…”

Section: Introductionmentioning

confidence: 99%

Cancer‐testis gene PIWIL1 promotes cell proliferation, migration, and invasion in lung adenocarcinoma

et al. 2017

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Piwi‐like RNA‐mediated gene silencing 1 (PIWIL1) has been identified as a novel extremely highly expressed cancer‐testis (CT) gene in lung adenocarcinoma. However, the exact function and mechanism of PIWIL1 in lung adenocarcinoma remains unclear. Herein, we sought to investigate the role of PIWIL1 in the occurrence and development of lung adenocarcinoma. We examined the expression pattern of PIWIL1 in The Cancer Genome Atlas (TCGA) lung adenocarcinoma samples, and validated it by Real‐Time PCR (RT‐PCR) in additional 21 paired lung adenocarcinoma tissues and 16 normal tissues. Subsequently, we explored the biological function of PIWIL1 in A549 and H1299 cell lines by gain and loss‐of‐function analyses. Using TCGA lung adenocarcinoma data, we further performed coexpression and Gene Ontology (GO) analyses, and analyzed the association of DNA methylation levels in PIWIL1 promoter region with its expression. Finally, we evaluated its expression in different mutation status of significantly mutated genes (SMGs) in TCGA lung adenocarcinoma data. We observed that PIWIL1 was expressed in testis and lung adenocarcinoma but not in other normal tissues, and its high expression was associated with shortened survival of lung cancer patients. Overexpression of PIWIL1 could facilitate the proliferation, invasion and migration of lung adenocarcinoma cells and vice versa. GO analysis revealed that PIWIL1 upregulated genes were enriched in embryonic development, cell proliferation and regulation of transcription. Moreover, promoter DNA hypomethylation of PIWIL1 could contribute to its aberrant expression in tumors. Interestingly, PIWIL1 expression was significantly higher in patients without hepatocyte growth factor (HGF) or serine/threonine kinase 11 (STK11) mutation (P = 0.006 and 0.005, respectively). PIWIL1 is an epidriver gene in lung adenocarcinoma, indicating a potential target for further therapy.

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Combined RNA/tissue profiling identifies novel Cancer/testis genes

et al. 2021

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Cancer/Testis (CT) genes are induced in germ cells, repressed in somatic cells, and derepressed in somatic tumors, where these genes can contribute to cancer progression. CT gene identification requires data obtained using standardized protocols and technologies. This is a challenge because data for germ cells, gonads, normal somatic tissues, and a wide range of cancer samples stem from multiple sources and were generated over substantial periods of time. We carried out a GeneChip-based RNA profiling analysis using our own data for testis and enriched germ cells, data for somatic cancers from the Expression Project for Oncology, and data for normal somatic tissues from the Gene Omnibus Repository. We identified 478 candidate loci that include known CT genes, numerous genes associated with oncogenic processes, and novel candidates that are not referenced in the Cancer/Testis Database (www.cta.lncc.br). We complemented RNA expression data at the protein level for SPESP1, GALNTL5, PDCL2, and C11orf42 using cancer tissue microarrays covering malignant tumors of breast, uterus, thyroid, and kidney, as well as published RNA profiling and immunohistochemical data provided by the Human Protein Atlas (www.proteinatlas.org). We report that combined RNA/tissue profiling identifies novel CT genes that may be of clinical interest as therapeutical targets or biomarkers. Our findings also highlight the challenges of detecting truly germ cell-specific mRNAs and the proteins they encode in highly heterogenous testicular, somatic, and tumor tissues. AbbreviationsCT genes, Cancer/testis genes; TMAs, Tissue microarrays.

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

Cited by 126 publications

References 51 publications

Comprehensive characterization of cancer‐testis genes in testicular germ cell tumor

Comprehensive characterization of cancer‐testis genes in testicular germ cell tumor

Cancer‐testis gene PIWIL1 promotes cell proliferation, migration, and invasion in lung adenocarcinoma

Combined RNA/tissue profiling identifies novel Cancer/testis genes

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