TY - JOUR
T1 - Continuity of transcriptomes among colorectal cancer subtypes based on meta-analysis
AU - Ma, Siyuan
AU - Ogino, Shuji
AU - Parsana, Princy
AU - Nishihara, Reiko
AU - Qian, Zhirong
AU - Shen, Jeanne
AU - Mima, Kosuke
AU - Masugi, Yohei
AU - Cao, Yin
AU - Nowak, Jonathan A.
AU - Shima, Kaori
AU - Hoshida, Yujin
AU - Giovannucci, Edward L.
AU - Gala, Manish K.
AU - Chan, Andrew T.
AU - Fuchs, Charles S.
AU - Parmigiani, Giovanni
AU - Huttenhower, Curtis
AU - Waldron, Levi
N1 - Funding Information:
This work was supported by the STARR Cancer Consortium, the National Cancer Institute at the National Institutes of Health (1R03CA191447-01A1 and U24CA180996 to LW), NIH grants (P01 CA87969 to MJS; UM1 CA186107 to MJS; P01 CA55075 to WCW; UM1 CA167552 to WCW; P50 CA127003 to CSF; R01 CA151993 to SO; R35 CA197735 to SO; K07 CA190673 to RN), and by grants from The Project P Fund (to CSF), the Friends of the Dana-Farber Cancer Institute (to SO), the Bennett Family Fund, and the Entertainment Industry Foundation through National Colorectal Cancer Research Alliance. The content is solely the responsibility of the authors and does not necessarily represent the official views of the NIH. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. The authors assume full responsibility for analyses and interpretation of these data.
Publisher Copyright:
© 2018 The Author(s).
PY - 2018/9/25
Y1 - 2018/9/25
N2 - Background: 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. Results: 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. Conclusions: 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.
AB - Background: 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. Results: 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. Conclusions: 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.
KW - Colon cancer
KW - Progression
KW - Transcriptional profiling
KW - Tumor
UR - http://www.scopus.com/inward/record.url?scp=85054014576&partnerID=8YFLogxK
U2 - 10.1186/s13059-018-1511-4
DO - 10.1186/s13059-018-1511-4
M3 - Article
C2 - 30253799
AN - SCOPUS:85054014576
VL - 19
JO - Genome Biology
JF - Genome Biology
SN - 1474-7596
IS - 1
M1 - 142
ER -