Frontiers in Oncology (Oct 2019)
Integrative Analysis Reveals Across-Cancer Expression Patterns and Clinical Relevance of Ribonucleotide Reductase in Human Cancers
- Yongfeng Ding,
- Yongfeng Ding,
- Yongfeng Ding,
- Tingting Zhong,
- Tingting Zhong,
- Tingting Zhong,
- Min Wang,
- Xueping Xiang,
- Xueping Xiang,
- Guoping Ren,
- Zhongjuan Jia,
- Qinghui Lin,
- Qian Liu,
- Jingwen Dong,
- Linrong Li,
- Xiawei Li,
- Haiping Jiang,
- Lijun Zhu,
- Haoran Li,
- Dejun Shen,
- Lisong Teng,
- Chen Li,
- Jimin Shao,
- Jimin Shao
Affiliations
- Yongfeng Ding
- Department of Pathology & Pathophysiology, and Cancer Institute of the Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
- Yongfeng Ding
- Key Laboratory of Disease Proteomics of Zhejiang Province, Key Laboratory of Cancer Prevention and Intervention of China National Ministry of Education, Research Center for Air Pollution and Health, Zhejiang University School of Medicine, Hangzhou, China
- Yongfeng Ding
- Key Laboratory of Precision Diagnosis and Treatment for Hepatobiliary and Pancreatic Tumor of Zhejiang Province, Department of Medical Oncology, Department of Pathology, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
- Tingting Zhong
- Department of Pathology & Pathophysiology, and Cancer Institute of the Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
- Tingting Zhong
- Key Laboratory of Disease Proteomics of Zhejiang Province, Key Laboratory of Cancer Prevention and Intervention of China National Ministry of Education, Research Center for Air Pollution and Health, Zhejiang University School of Medicine, Hangzhou, China
- Tingting Zhong
- Department of Pathology, Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, Hangzhou, China
- Min Wang
- Department of Human Genetics, Zhejiang University School of Medicine, Hangzhou, China
- Xueping Xiang
- Department of Pathology & Pathophysiology, and Cancer Institute of the Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
- Xueping Xiang
- Key Laboratory of Disease Proteomics of Zhejiang Province, Key Laboratory of Cancer Prevention and Intervention of China National Ministry of Education, Research Center for Air Pollution and Health, Zhejiang University School of Medicine, Hangzhou, China
- Guoping Ren
- Key Laboratory of Precision Diagnosis and Treatment for Hepatobiliary and Pancreatic Tumor of Zhejiang Province, Department of Medical Oncology, Department of Pathology, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
- Zhongjuan Jia
- Department of Pathology & Pathophysiology, and Cancer Institute of the Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
- Qinghui Lin
- Department of Pathology & Pathophysiology, and Cancer Institute of the Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
- Qian Liu
- Department of Pathology & Pathophysiology, and Cancer Institute of the Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
- Jingwen Dong
- Department of Pathology & Pathophysiology, and Cancer Institute of the Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
- Linrong Li
- Department of Pathology & Pathophysiology, and Cancer Institute of the Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
- Xiawei Li
- Department of Pathology & Pathophysiology, and Cancer Institute of the Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
- Haiping Jiang
- Key Laboratory of Precision Diagnosis and Treatment for Hepatobiliary and Pancreatic Tumor of Zhejiang Province, Department of Medical Oncology, Department of Pathology, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
- Lijun Zhu
- Key Laboratory of Precision Diagnosis and Treatment for Hepatobiliary and Pancreatic Tumor of Zhejiang Province, Department of Medical Oncology, Department of Pathology, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
- Haoran Li
- Discovery Biochemistry, Kymera Therapeutics, Cambridge, MA, United States
- Dejun Shen
- Southern California Permanente Medical Group, Department of Pathology, Downey Medical Center, Downey, CA, United States
- Lisong Teng
- Key Laboratory of Precision Diagnosis and Treatment for Hepatobiliary and Pancreatic Tumor of Zhejiang Province, Department of Medical Oncology, Department of Pathology, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
- Chen Li
- Department of Human Genetics, Zhejiang University School of Medicine, Hangzhou, China
- Jimin Shao
- Department of Pathology & Pathophysiology, and Cancer Institute of the Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
- Jimin Shao
- Key Laboratory of Disease Proteomics of Zhejiang Province, Key Laboratory of Cancer Prevention and Intervention of China National Ministry of Education, Research Center for Air Pollution and Health, Zhejiang University School of Medicine, Hangzhou, China
- DOI
- https://doi.org/10.3389/fonc.2019.00956
- Journal volume & issue
-
Vol. 9
Abstract
Mining cancer-omics databases deepens our understanding of cancer biology and can lead to potential breakthroughs in cancer treatment. Here, we propose an integrative analytical approach to reveal across-cancer expression patterns and identify potential clinical impacts for genes of interest from five representative public databases. Using ribonucleotide reductase (RR), a key enzyme in DNA synthesis and cancer-therapeutic targeting, as an example, we characterized the mRNA expression profiles and inter-component associations of three RR subunit genes and assess their differing pathological and prognostic significance across over 30-types of cancers and their related subtypes. Findings were validated by immunohistochemistry with clinical tissue samples (n = 211) collected from multiple cancer centers in China and with clinical follow-up. Underlying mechanisms were further explored and discussed using co-expression gene network analyses. This framework represents a simple, efficient, accurate, and comprehensive approach for cancer-omics resource analysis and underlines the necessity to separate the tumors by their histological or pathological subtypes during the clinical evaluation of molecular biomarkers.
Keywords
- cancer-omics
- integrative analysis
- ribonucleotide reductase
- expression characteristics
- clinical relevance
- gene networks
