Wei Cao1, Jian-Nan Liu1, Zeqi Liu1, Xu Wang1, Ze-Guang Han2, Tong Ji3, Wan-Tao Chen4, Xin Zou5. 1. Department of Oral Maxillofacial-Head and Neck Oncology, Ninth People's Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai 200011, China; Shanghai Key Laboratory of Stomatology, Shanghai 200011, China. 2. Key Laboratory of Systems Biomedicine (Ministry of Education), Shanghai Center for Systems Biomedicine, Shanghai Jiao Tong University, Shanghai, China. 3. Department of Oral Maxillofacial-Head and Neck Oncology, Ninth People's Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai 200011, China; Shanghai Key Laboratory of Stomatology, Shanghai 200011, China. Electronic address: Jitong70@hotmail.com. 4. Department of Oral Maxillofacial-Head and Neck Oncology, Ninth People's Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai 200011, China; Shanghai Key Laboratory of Stomatology, Shanghai 200011, China. Electronic address: chenwantao196323@sju.edu.cn. 5. Key Laboratory of Systems Biomedicine (Ministry of Education), Shanghai Center for Systems Biomedicine, Shanghai Jiao Tong University, Shanghai, China. Electronic address: x.zou@sjtu.edu.cn.
Abstract
OBJECTIVE: Long non-coding RNAs (lncRNAs) have important biological functions and can be used as prognostic biomarkers in cancer. To identify a lncRNA prognostic signature for head and neck squamous cell carcinoma (HNSCC). METHOD: We analysed RNA-seq data derived from the TANRIC database to identify a lncRNA prognostic signature model using the orthogonal partial least squares discrimination analysis (OPLS-DA) and 1.5-fold expression change criterion methods. The prognosis prediction model based on the lncRNA signatures and clinical parameters were evaluated using the 5-fold cross validation method. RESULTS: A total of 84 out of 3199 lncRNAs were significantly associated with the survival of patients with HNSCC (log-rank test P<0.01). Using the OPLS-DA and 1.5-fold change selection criterion, 5 lncRNAs (KTN1-AS1, LINC00460, GUSBP11, LINC00923 and RP5-894A10.6) were further selected. The prediction power of each combination of the 5 lncRNAs was evaluated through the receiver operating characteristic (ROC) curve and a three-lncRNA panel (KTN1-AS1, LINC00460 and RP5-894A10.6) achieved the highest prognostic prediction power (AUC 0.68, 95% CI 0.60-0.76, P<0.0001) in the cohort. The patients were categorized into high- and low-risk groups based on their three-lncRNA profiles. Patients with high-risk scores had worse overall survival than those with low risk scores in the cohort (log-rank test P=0.0003). Multivariable Cox regression analyses showed that the lncRNA signature and tumour grade were independent prognostic factors for patients with HNSCC. CONCLUSIONS: Our findings showed that the three-lncRNA signature might be a novel biomarker for the accurate prognosis prediction of patients with HNSCC.
OBJECTIVE: Long non-coding RNAs (lncRNAs) have important biological functions and can be used as prognostic biomarkers in cancer. To identify a lncRNA prognostic signature for head and neck squamous cell carcinoma (HNSCC). METHOD: We analysed RNA-seq data derived from the TANRIC database to identify a lncRNA prognostic signature model using the orthogonal partial least squares discrimination analysis (OPLS-DA) and 1.5-fold expression change criterion methods. The prognosis prediction model based on the lncRNA signatures and clinical parameters were evaluated using the 5-fold cross validation method. RESULTS: A total of 84 out of 3199 lncRNAs were significantly associated with the survival of patients with HNSCC (log-rank test P<0.01). Using the OPLS-DA and 1.5-fold change selection criterion, 5 lncRNAs (KTN1-AS1, LINC00460, GUSBP11, LINC00923 and RP5-894A10.6) were further selected. The prediction power of each combination of the 5 lncRNAs was evaluated through the receiver operating characteristic (ROC) curve and a three-lncRNA panel (KTN1-AS1, LINC00460 and RP5-894A10.6) achieved the highest prognostic prediction power (AUC 0.68, 95% CI 0.60-0.76, P<0.0001) in the cohort. The patients were categorized into high- and low-risk groups based on their three-lncRNA profiles. Patients with high-risk scores had worse overall survival than those with low risk scores in the cohort (log-rank test P=0.0003). Multivariable Cox regression analyses showed that the lncRNA signature and tumour grade were independent prognostic factors for patients with HNSCC. CONCLUSIONS: Our findings showed that the three-lncRNA signature might be a novel biomarker for the accurate prognosis prediction of patients with HNSCC.
Authors: Ritu Chaudhary; Xuefeng Wang; Biwei Cao; Janis De La Iglesia; Jude Masannat; Feifei Song; Juan C Hernandez-Prera; Nicholas T Gimbrone; Robbert Jc Slebos; Christine H Chung Journal: Am J Transl Res Date: 2020-02-15 Impact factor: 4.060
Authors: Chu Chen; Pawadee Lohavanichbutr; Yuzheng Zhang; John R Houck; Melissa P Upton; Behnoush Abedi-Ardekani; Antonio Agudo; Wolfgang Ahrens; Laia Alemany; Devasena Anantharaman; David I Conway; Neal D Futran; Ivana Holcatova; Kathrin Günther; Bo T Hansen; Claire M Healy; Doha Itani; Kristina Kjaerheim; Marcus M Monroe; Peter J Thomson; Benjamin L Witt; Steven Nakoneshny; Lisa A Peterson; Stephen M Schwartz; Katie R Zarins; Mia Hashibe; Paul Brennan; Laura S Rozek; Gregory Wolf; Joseph C Dort; Pei Wang Journal: Oral Oncol Date: 2019-12-10 Impact factor: 5.337