Title |
Continuity of transcriptomes among colorectal cancer subtypes based on meta-analysis
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Published in |
Genome Biology, September 2018
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DOI | 10.1186/s13059-018-1511-4 |
Pubmed ID | |
Authors |
Siyuan Ma, Shuji Ogino, Princy Parsana, Reiko Nishihara, Zhirong Qian, Jeanne Shen, Kosuke Mima, Yohei Masugi, Yin Cao, Jonathan A. Nowak, Kaori Shima, Yujin Hoshida, Edward L. Giovannucci, Manish K. Gala, Andrew T. Chan, Charles S. Fuchs, Giovanni Parmigiani, Curtis Huttenhower, Levi Waldron |
Abstract |
Previous approaches to defining subtypes of colorectal carcinoma (CRC) and other cancers based on transcriptomes have assumed the existence of discrete subtypes. We analyze gene expression patterns of colorectal tumors from a large number of patients to test this assumption and propose an approach to identify potentially a continuum of subtypes that are present across independent studies and cohorts. We examine the assumption of discrete CRC subtypes by integrating 18 published gene expression datasets and > 3700 patients, and contrary to previous reports, find no evidence to support the existence of discrete transcriptional subtypes. Using a meta-analysis approach to identify co-expression patterns present in multiple datasets, we identify and define robust, continuously varying subtype scores to represent CRC transcriptomes. The subtype scores are consistent with established subtypes (including microsatellite instability and previously proposed discrete transcriptome subtypes), but better represent overall transcriptional activity than do discrete subtypes. The scores are also better predictors of tumor location, stage, grade, and times of disease-free survival than discrete subtypes. Gene set enrichment analysis reveals that the subtype scores characterize T-cell function, inflammation response, and cyclin-dependent kinase regulation of DNA replication. We find no evidence to support discrete subtypes of the CRC transcriptome and instead propose two validated scores to better characterize a continuity of CRC transcriptomes. |
X Demographics
Geographical breakdown
Country | Count | As % |
---|---|---|
United States | 14 | 39% |
United Kingdom | 3 | 8% |
Australia | 2 | 6% |
Germany | 1 | 3% |
Comoros | 1 | 3% |
India | 1 | 3% |
Finland | 1 | 3% |
Unknown | 13 | 36% |
Demographic breakdown
Type | Count | As % |
---|---|---|
Members of the public | 16 | 44% |
Scientists | 15 | 42% |
Science communicators (journalists, bloggers, editors) | 3 | 8% |
Practitioners (doctors, other healthcare professionals) | 2 | 6% |
Mendeley readers
Geographical breakdown
Country | Count | As % |
---|---|---|
Unknown | 63 | 100% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Researcher | 12 | 19% |
Student > Ph. D. Student | 7 | 11% |
Student > Master | 5 | 8% |
Student > Bachelor | 4 | 6% |
Professor | 4 | 6% |
Other | 8 | 13% |
Unknown | 23 | 37% |
Readers by discipline | Count | As % |
---|---|---|
Biochemistry, Genetics and Molecular Biology | 15 | 24% |
Medicine and Dentistry | 9 | 14% |
Agricultural and Biological Sciences | 5 | 8% |
Engineering | 3 | 5% |
Immunology and Microbiology | 2 | 3% |
Other | 4 | 6% |
Unknown | 25 | 40% |