Boxuan Liu1, Yun Zhao2, Shuanying Yang1. 1. Department of Critical Care and Respiratory Medicine, The Second Affiliated Hospital, Xi'an Jiaotong University, Xi'an, Shaanxi, 710004, People's Republic of China. 2. Department of Cardiology, The First Affiliated Hospital, Xi'an Jiaotong University, Xi'an, Shaanxi, 710004, People's Republic of China.
Abstract
PURPOSE: Lung cancer is the most common and deadly cancer type affecting humans. Although huge progress has been made on early diagnosis and precision treatment, the overall 5 year survival rate remains low. In this study, we constructed an autophagy-related long non-coding RNA (lncRNA) prognostic signature for guiding clinical practice. METHODS: From The Cancer Genome Atlas, we retrieved mRNA and lncRNA expression matrices of patients with lung squamous carcinoma. We then established a prognostic risk model using Lasso regression and multivariate Cox regression. The model generated a risk score to differentiate high- and low-risk groups. An ROC curve and nomogram were used to visualize the predictive ability of the current signatures. Finally, we used Gene Set Enrichment Analysis to determine gene ontology and pathway enrichment. RESULTS: After screening 1248 autophagy-related lncRNAs, we selected seven lncRNAs (LUCAT1, AC022150.2, AL035425.3, AC138976.2, AC106786.1, GPRC5D-AS1 and AP006545.2) for our signature. Univariate (hazard ratio [HR] = 2.147, 95% confidence interval [CI]: 1.681-2.743, P < 0.001) and multivariate (HR = 2.096, 95% CI: 1.652-2.658, P < 0.001) Cox regression analyses revealed that the risk score is an independent predictive factor for LUSC patients. Further, areas under the receiver operating characteristic curve were 0.622, 0.699, and 0.721, respectively, for the 1 year, 3 year, and 5 year risk scores-indicating a reliable model. Selected lncRNAs were primarily enriched in autophagy, metabolism, MAPK pathway, and JAK/STAT pathway. Further drug sensitivity analysis revealed that low-risk patients were more sensitive to Cisplatin, Docetaxel, Vinblastine, and Vinorelbine. Finally, a multi-omics analysis found that lncRNA-linked proteins IKBKB and SQSTM1 were expressed at low levels and significantly correlated in tumor samples, compared with normal tissue. CONCLUSION: Our prognostic model successfully predicted patient prognosis in lung cancer.
PURPOSE: Lung cancer is the most common and deadly cancer type affecting humans. Although huge progress has been made on early diagnosis and precision treatment, the overall 5 year survival rate remains low. In this study, we constructed an autophagy-related long non-coding RNA (lncRNA) prognostic signature for guiding clinical practice. METHODS: From The Cancer Genome Atlas, we retrieved mRNA and lncRNA expression matrices of patients with lung squamous carcinoma. We then established a prognostic risk model using Lasso regression and multivariate Cox regression. The model generated a risk score to differentiate high- and low-risk groups. An ROC curve and nomogram were used to visualize the predictive ability of the current signatures. Finally, we used Gene Set Enrichment Analysis to determine gene ontology and pathway enrichment. RESULTS: After screening 1248 autophagy-related lncRNAs, we selected seven lncRNAs (LUCAT1, AC022150.2, AL035425.3, AC138976.2, AC106786.1, GPRC5D-AS1 and AP006545.2) for our signature. Univariate (hazard ratio [HR] = 2.147, 95% confidence interval [CI]: 1.681-2.743, P < 0.001) and multivariate (HR = 2.096, 95% CI: 1.652-2.658, P < 0.001) Cox regression analyses revealed that the risk score is an independent predictive factor for LUSC patients. Further, areas under the receiver operating characteristic curve were 0.622, 0.699, and 0.721, respectively, for the 1 year, 3 year, and 5 year risk scores-indicating a reliable model. Selected lncRNAs were primarily enriched in autophagy, metabolism, MAPK pathway, and JAK/STAT pathway. Further drug sensitivity analysis revealed that low-risk patients were more sensitive to Cisplatin, Docetaxel, Vinblastine, and Vinorelbine. Finally, a multi-omics analysis found that lncRNA-linked proteins IKBKB and SQSTM1 were expressed at low levels and significantly correlated in tumor samples, compared with normal tissue. CONCLUSION: Our prognostic model successfully predicted patient prognosis in lung cancer.
Authors: Chih-Wen Shu; Charitha Madiraju; Dayong Zhai; Kate Welsh; Paul Diaz; Eduard Sergienko; Renata Sano; John C Reed Journal: J Biomol Screen Date: 2011-01-18
Authors: Elin Karlsson; Gizeh Pérez-Tenorio; Risul Amin; Josefine Bostner; Lambert Skoog; Tommy Fornander; Dennis C Sgroi; Bo Nordenskjöld; Anna-Lotta Hallbeck; Olle Stål Journal: Breast Cancer Res Date: 2013 Impact factor: 6.466