Dataset Information

Genome-wide analysis of gynecologic cancer: The Cancer Genome Atlas in ovarian and endometrial cancer.

ABSTRACT: Cancer typically develops due to genetic abnormalities, but a single gene abnormality cannot completely account for the onset of cancer. The Cancer Genome Atlas (CGA) project was conducted for the cross-sectional genome-wide analysis of numerous genetic abnormalities in various types of cancer. This approach has facilitated the identification of novel AT-rich interaction domain 1A gene mutations in ovarian clear cell carcinoma, frequent tumor protein 53 (TP53) gene mutations in high-grade ovarian serous carcinoma, and Kirsten rat sarcoma and B-rapidly accelerated fibrosarcoma proto-oncogene, serine/threonine kinase gene mutations in low-grade ovarian serous carcinoma. Genome-wide analysis of endometrial cancers has led to the establishment of four subgroups: Polymerase ultramutated, microsatellite instability hypermutated, genome copy-number low and genome copy-number high. These results may facilitate the improvement of the prediction of patient prognosis and therapeutic sensitivity in various types of gynecologic cancer. The enhanced use of currently available therapeutic agents and the development of novel drugs may be facilitated by the novel classification of ovarian cancer based on TP53 mutations, the efficacy of poly (ADP-ribose) polymerase inhibitors for tumors with breast cancer 1/2 mutations and the effect of phosphoinositide-3-kinase (PI3K)/mammalian target of rapamycin inhibitors for tumors with mutations in the PI3K/protein kinase B signaling pathway. Important results have been revealed by genome-wide analyses; however, the pathogenic underlying mechanisms of gynecologic cancer will require further studies and multilateral evaluation using epigenetic, transcriptomic and proteomic analyses, in addition to genomic analysis.

SUBMITTER: Iijima M

PROVIDER: S-EPMC5403284 | biostudies-literature | 2017 Mar

REPOSITORIES: biostudies-literature

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Genome-wide analysis of gynecologic cancer: The Cancer Genome Atlas in ovarian and endometrial cancer.

Iijima Moito M Banno Kouji K Okawa Ryuichiro R Yanokura Megumi M Iida Miho M Takeda Takashi T Kunitomi-Irie Haruko H Adachi Masataka M Nakamura Kanako K Umene Kiyoko K Nogami Yuya Y Masuda Kenta K Tominaga Eiichiro E Aoki Daisuke D

Oncology letters 20170110 3

Cancer typically develops due to genetic abnormalities, but a single gene abnormality cannot completely account for the onset of cancer. The Cancer Genome Atlas (CGA) project was conducted for the cross-sectional genome-wide analysis of numerous genetic abnormalities in various types of cancer. This approach has facilitated the identification of novel AT-rich interaction domain 1A gene mutations in ovarian clear cell carcinoma, frequent tumor protein 53 (<i>TP53</i>) gene mutations in high-grade ...[more]

PMID: 28454214

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Project description:Cell adhesion molecules (CAMs) determine the behavior of cancer cells during metastasis. Although some CAMs are dysregulated in certain types of cancer and are associated with cancer progression, to the best of our knowledge, a comprehensive study of CAMs has not been undertaken, particularly in endometrial cancer (EC). In the present study the expression of 225 CAMs in EC patients with various clinicopathological phenotypes were evaluated by statistical analysis using publicly available data from The Cancer Genome Atlas database. The Kaplan-Meier method, and univariate and multivariate Cox proportional hazards regression models were used for survival analyses. Among the differentially expressed CAMs that were associated with aggressive clinicopathological phenotypes, 10 CAM genes were independent prognostic factors compared with other clinicopathological prognostic factors, including stage, grade, age, lymph node status, peritoneal cytology and histological subtype. A total of six genes (L1 cell adhesion molecule, mucin 15, cell surface associated, cell adhesion associated, oncogene regulated, immunoglobulin superfamily member 9B, protocadherin 9 and protocadherin β1) were selected for integrative analysis. The six-gene signature was demonstrated to be an independent prognostic factor and could effectively stratify patients with different risks. Patients with more high-expression CAMs had a higher risk of poor overall survival (OS) rate. The mortality risk for patients with elevation of >4 CAMs was 11 times of that in those without elevation of these 6 CAMs. Similar results were obtained when relapse-free survival (RFS) time was used during the analysis. Prognostic reliability of the six-gene model was validated using data of an independent cohort from the International Cancer Genome Consortium. In conclusion, a combination of CAM alterations contributed to progression and aggressiveness of EC. The six-gene signature was effective for predicting worse OS and RFS in patients with EC and could be complementary to the present clinical prognostic criteria.

Project description:UnlabelledViruses are causally associated with a number of human malignancies. In this study, we sought to identify new virus-cancer associations by searching RNA sequencing data sets from >2,000 patients, encompassing 21 cancers from The Cancer Genome Atlas (TCGA), for the presence of viral sequences. In agreement with previous studies, we found human papillomavirus 16 (HPV16) and HPV18 in oropharyngeal cancer and hepatitis B and C viruses in liver cancer. Unexpectedly, however, we found HPV38, a cutaneous form of HPV associated with skin cancer, in 32 of 168 samples from endometrial cancer. In 12 of the HPV38-positive (HPV38(+)) samples, we observed at least one paired read that mapped to both human and HPV38 genomes, indicative of viral integration into the host DNA, something not previously demonstrated for HPV38. The expression levels of HPV38 transcripts were relatively low, and all 32 HPV38(+) samples belonged to the same experimental batch of 40 samples, whereas none of the other 128 endometrial carcinoma samples were HPV38(+), raising doubts about the significance of the HPV38 association. Moreover, the HPV38(+) samples contained the same 10 novel single nucleotide variations (SNVs), leading us to hypothesize that one patient was infected with this new isolate of HPV38, which was integrated into his/her genome and may have cross-contaminated other TCGA samples within batch 228. Based on our analysis, we propose guidelines to examine the batch effect, virus expression level, and SNVs as part of next-generation sequencing (NGS) data analysis for evaluating the significance of viral/pathogen sequences in clinical samples.ImportanceHigh-throughput RNA sequencing (RNA-Seq), followed by computational analysis, has vastly accelerated the identification of viral and other pathogenic sequences in clinical samples, but cross-contamination during the processing of the samples remain a major problem that can lead to erroneous conclusions. We found HPV38 sequences specifically present in RNA-Seq samples from endometrial cancer patients from TCGA, a virus not previously associated with this type of cancer. However, multiple lines of evidence suggest possible cross-contamination in these samples, which were processed together in the same batch. Despite this potential cross-contamination, our data indicate that we have detected a new isolate of HPV38 that appears to be integrated into the human genome. We also provide general guidelines for computational detection and interpretation of pathogen-disease associations.

Dataset Information

Genome-wide analysis of gynecologic cancer: The Cancer Genome Atlas in ovarian and endometrial cancer.

Publications

Genome-wide analysis of gynecologic cancer: The Cancer Genome Atlas in ovarian and endometrial cancer.

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