title: Pan-organ transcriptome variation across 21 cancer types.
abstract: It is widely accepted that some messenger RNAs are evolutionarily conserved across species, both in sequence and tissue-expression specificity. To date, however, little effort has been made to exploit the transcriptome divergence between cancer and adjacent normal tissue at the pan-organ level. In this work, a transcriptome sequencing dataset from 675 normal-tumor pairs, representing 21 solid organs in The Cancer Genome Atlas, is used to evaluate expression evolution. The results show that in most cancer types, gene expression divergence and organ-specificity are reduced in cancer tissue compared to adjacent normal tissue. Furthermore, we observe that all cancers share cell cycle dysregulation through interrogating differentially expressed protein coding genes. Meanwhile, weighted correlation network analysis is used to detect of the gene module structure variation between cancer and adjacent normal tissue. And modules consisting of tightly co-regulated genes in cancer change substantially compared with those in adjacent normal tissue. We thus assume that the destruction of a coordinated regulatory network might result in tumorigenesis and tumor progression. Our results provide new insights into the complex cancer biology and shed light on the mysterious regulation mode for cancer.
authors.affiliation: Cancer Institute (Key Laboratory of Cancer Prevention and Intervention, China National Ministry of Education), The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang 310009, China.
authors.forename: Wangxiong
authors.initials: W
authors.lastname: Hu
authors.affiliation: Key Laboratory of Reproductive and Genetics, Ministry of Education, Women's Hospital, Zhejiang University, Hangzhou, Zhejiang 310006, China.
authors.forename: Yanmei
authors.initials: Y
authors.lastname: Yang
authors.affiliation: Cancer Institute (Key Laboratory of Cancer Prevention and Intervention, China National Ministry of Education), The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang 310009, China.
authors.forename: Xiaofen
authors.initials: X
authors.lastname: Li
authors.affiliation: Cancer Institute (Key Laboratory of Cancer Prevention and Intervention, China National Ministry of Education), The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang 310009, China.|Research Center for Air Pollution and Health, School of Medicine, Zhejiang University, Hangzhou, Zhejiang 310009, China.
authors.forename: Shu
authors.initials: S
authors.lastname: Zheng
mesh_terms: D014408:Biomarkers, Tumor / Q000235:genetics* / Q000378:metabolism; D059447:Cell Cycle Checkpoints / Q000235:genetics; D002471:Cell Transformation, Neoplastic / Q000235:genetics* / Q000378:metabolism / Q000473:pathology; D019295:Computational Biology; D030541:Databases, Genetic; D020869:Gene Expression Profiling; D015972:Gene Expression Regulation, Neoplastic; D053263:Gene Regulatory Networks; D020022:Genetic Predisposition to Disease; D006801:Humans; D009369:Neoplasms / Q000235:genetics* / Q000378:metabolism / Q000473:pathology; D009928:Organ Specificity / Q000235:genetics; D010641:Phenotype; D012333:RNA, Messenger / Q000235:genetics* / Q000378:metabolism; D015398:Signal Transduction / Q000235:genetics; D059467:Transcriptome
chemical_list: D014408:Biomarkers, Tumor; D012333:RNA, Messenger
keywords: gene expression; organ-specific genes; pan-cancer; weighted correlation network analysis