Ye Zhao1, Lixiao Liu1, Jinduo Zhao1, Xuedan Du2, Qiongjie Yu2, Jinting Wu2, Bin Wang2, Rongying Ou1. 1. Department of Obstetrics and Gynecology, The First Affiliated Hospital of Wenzhou Medical University, Wenzhou, Zhejiang, People's Republic of China. 2. Department of Chemoradiation Oncology, The First Affiliated Hospital of Wenzhou Medical University, Wenzhou, Zhejiang, People's Republic of China.
Abstract
INTRODUCTION: Breast cancer is the most common form of cancer worldwide and a serious threat to women. Hypoxia is thought to be associated with poor prognosis of patients with cancer. Long non-coding RNAs are differentially expressed during tumorigenesis and can serve as unambiguous molecular biomarkers for the prognosis of breast cancer. METHODS: Here, we accessed the data from The Cancer Genome Atlas for model construction and performed Gene Ontology and Kyoto Encyclopedia of Genes and Genomes analyses to identify biological functions. Four prognostic hypoxia-related lncRNAs identified by univariate, LASSO, and multivariate Cox regression analyses were used to develop a prognostic risk-related signature. Kaplan-Meier and receiver operating characteristic curve analyses were performed, and independent prognostic factor analysis and correlation analysis with clinical characteristics were utilized to evaluate the specificity and sensitivity of the signature. Survival analysis and receiver operating characteristic curve analyses of the validation cohort were operated to corroborate the robustness of the model. RESULTS: Our results demonstrate the development of a reliable prognostic gene signature comprising four long non-coding RNAs (AL031316.1, AC004585.1, LINC01235, and ACTA2-AS1). The signature displayed irreplaceable prognostic power for overall survival in patients with breast cancer in both the training and validation cohorts. Furthermore, immune cell infiltration analysis revealed that B cells, CD4 T cells, CD8 T cells, neutrophils, and dendritic cells were significantly different between the high-risk and low-risk groups. The high-risk and low-risk groups could be precisely distinguished using the risk signature to predict patient outcomes. DISCUSSION: In summary, our study proves that hypoxia-related long non-coding RNAs serve as accurate indicators of poor prognosis and short overall survival, and are likely to act as potential targets for future cancer therapy.
INTRODUCTION: Breast cancer is the most common form of cancer worldwide and a serious threat to women. Hypoxia is thought to be associated with poor prognosis of patients with cancer. Long non-coding RNAs are differentially expressed during tumorigenesis and can serve as unambiguous molecular biomarkers for the prognosis of breast cancer. METHODS: Here, we accessed the data from The Cancer Genome Atlas for model construction and performed Gene Ontology and Kyoto Encyclopedia of Genes and Genomes analyses to identify biological functions. Four prognostic hypoxia-related lncRNAs identified by univariate, LASSO, and multivariate Cox regression analyses were used to develop a prognostic risk-related signature. Kaplan-Meier and receiver operating characteristic curve analyses were performed, and independent prognostic factor analysis and correlation analysis with clinical characteristics were utilized to evaluate the specificity and sensitivity of the signature. Survival analysis and receiver operating characteristic curve analyses of the validation cohort were operated to corroborate the robustness of the model. RESULTS: Our results demonstrate the development of a reliable prognostic gene signature comprising four long non-coding RNAs (AL031316.1, AC004585.1, LINC01235, and ACTA2-AS1). The signature displayed irreplaceable prognostic power for overall survival in patients with breast cancer in both the training and validation cohorts. Furthermore, immune cell infiltration analysis revealed that B cells, CD4 T cells, CD8 T cells, neutrophils, and dendritic cells were significantly different between the high-risk and low-risk groups. The high-risk and low-risk groups could be precisely distinguished using the risk signature to predict patient outcomes. DISCUSSION: In summary, our study proves that hypoxia-related long non-coding RNAs serve as accurate indicators of poor prognosis and short overall survival, and are likely to act as potential targets for future cancer therapy.
Authors: Philipp Kapranov; Jill Cheng; Sujit Dike; David A Nix; Radharani Duttagupta; Aarron T Willingham; Peter F Stadler; Jana Hertel; Jörg Hackermüller; Ivo L Hofacker; Ian Bell; Evelyn Cheung; Jorg Drenkow; Erica Dumais; Sandeep Patel; Gregg Helt; Madhavan Ganesh; Srinka Ghosh; Antonio Piccolboni; Victor Sementchenko; Hari Tammana; Thomas R Gingeras Journal: Science Date: 2007-05-17 Impact factor: 47.728
Authors: Mathias Uhlen; Cheng Zhang; Sunjae Lee; Evelina Sjöstedt; Linn Fagerberg; Gholamreza Bidkhori; Rui Benfeitas; Muhammad Arif; Zhengtao Liu; Fredrik Edfors; Kemal Sanli; Kalle von Feilitzen; Per Oksvold; Emma Lundberg; Sophia Hober; Peter Nilsson; Johanna Mattsson; Jochen M Schwenk; Hans Brunnström; Bengt Glimelius; Tobias Sjöblom; Per-Henrik Edqvist; Dijana Djureinovic; Patrick Micke; Cecilia Lindskog; Adil Mardinoglu; Fredrik Ponten Journal: Science Date: 2017-08-18 Impact factor: 47.728