Hongpan Zhang1,2, Meihan Liu2, Guobo Du1,2, Bin Yu3, Xiaojie Ma1,2, Yan Gui1,2, Lu Cao1,2, Xianfu Li4,5, Bangxian Tan6,7. 1. Department of Oncology, Affiliated Hospital of North Sichuan Medical College, No. 1, Maoyuan south road, Shunqing District, Nanchong City, Sichuan Province, 637000, People's Republic of China. 2. North Sichuan Medical College, No. 55 Dongshun road, Gaoping district, Nanchong, Sichuan province, People's Republic of China. 3. Guangyuan Central Hospital, No. 16 Jingxiangzi, Lizhou district, Guangyuan, Sichuan province, People's Republic of China. 4. Department of Oncology, Affiliated Hospital of North Sichuan Medical College, No. 1, Maoyuan south road, Shunqing District, Nanchong City, Sichuan Province, 637000, People's Republic of China. lixianfu13@163.com. 5. North Sichuan Medical College, No. 55 Dongshun road, Gaoping district, Nanchong, Sichuan province, People's Republic of China. lixianfu13@163.com. 6. Department of Oncology, Affiliated Hospital of North Sichuan Medical College, No. 1, Maoyuan south road, Shunqing District, Nanchong City, Sichuan Province, 637000, People's Republic of China. tbx_nsmc@126.com. 7. North Sichuan Medical College, No. 55 Dongshun road, Gaoping district, Nanchong, Sichuan province, People's Republic of China. tbx_nsmc@126.com.
Abstract
BACKGROUND: Non-small cell lung cancer is the most common subtype of lung cancer in the world. However, the survival rate of non-small cell lung cancer patients remains low currently. Immune checkpoint and long non-coding RNAs are emerging as critical roles in prognostic significance and the immunotherapeutic response of non-small cell lung cancer. It is critical to discern LncRNAs related with immune checkpoints in patients with Non-small cell lung cancer. METHODS: In this study, immune checkpoint-linked LncRNAs were determined and achieved by the co-expression analysis. Immune checkpoint-linked LncRNAs with noteworthy prognostic value (P < 0.05) gained were next utilized to separate into two cluster by non-negative matrix factorization (NMF). Univariate and a least absolute shrinkage and selection operator were applied to construct an immune checkpoint-linked LncRNAs model. Kaplan-Meier analysis, Gene Set Enrichment Analysis, and the nomogram were utilized to investigate the LncRNAs model. Lastly, the capability immunotherapy and chemotherapy prediction value of this risk model were also estimated. RESULTS: The model consisting of ten immune checkpoint-related LncRNAs was acknowledged to be a self-determining predictor of prognosis. Through regrouping the NSCLC patients by this model, difference between them more efficiently on immunotherapeutic response, tumor microenvironment and chemotherapy response could be discovered. This risk model related to the immune checkpoint-based LncRNAs may have an excellent clinical prediction for prognosis and the immunotherapeutic response in patients with NSCLC. CONCLUSIONS: We performed an integrative analysis of LncRNAs linked with immune checkpoints and emphasized the significance of NSCLC subtypes classification, immune checkpoints related LncRNAs in estimating the tumor microenvironment score, immune cell infiltration of the tumor, immunotherapy, and chemotherapy response.
BACKGROUND: Non-small cell lung cancer is the most common subtype of lung cancer in the world. However, the survival rate of non-small cell lung cancer patients remains low currently. Immune checkpoint and long non-coding RNAs are emerging as critical roles in prognostic significance and the immunotherapeutic response of non-small cell lung cancer. It is critical to discern LncRNAs related with immune checkpoints in patients with Non-small cell lung cancer. METHODS: In this study, immune checkpoint-linked LncRNAs were determined and achieved by the co-expression analysis. Immune checkpoint-linked LncRNAs with noteworthy prognostic value (P < 0.05) gained were next utilized to separate into two cluster by non-negative matrix factorization (NMF). Univariate and a least absolute shrinkage and selection operator were applied to construct an immune checkpoint-linked LncRNAs model. Kaplan-Meier analysis, Gene Set Enrichment Analysis, and the nomogram were utilized to investigate the LncRNAs model. Lastly, the capability immunotherapy and chemotherapy prediction value of this risk model were also estimated. RESULTS: The model consisting of ten immune checkpoint-related LncRNAs was acknowledged to be a self-determining predictor of prognosis. Through regrouping the NSCLC patients by this model, difference between them more efficiently on immunotherapeutic response, tumor microenvironment and chemotherapy response could be discovered. This risk model related to the immune checkpoint-based LncRNAs may have an excellent clinical prediction for prognosis and the immunotherapeutic response in patients with NSCLC. CONCLUSIONS: We performed an integrative analysis of LncRNAs linked with immune checkpoints and emphasized the significance of NSCLC subtypes classification, immune checkpoints related LncRNAs in estimating the tumor microenvironment score, immune cell infiltration of the tumor, immunotherapy, and chemotherapy response.
Authors: Julie Brahmer; Karen L Reckamp; Paul Baas; Lucio Crinò; Wilfried E E Eberhardt; Elena Poddubskaya; Scott Antonia; Adam Pluzanski; Everett E Vokes; Esther Holgado; David Waterhouse; Neal Ready; Justin Gainor; Osvaldo Arén Frontera; Libor Havel; Martin Steins; Marina C Garassino; Joachim G Aerts; Manuel Domine; Luis Paz-Ares; Martin Reck; Christine Baudelet; Christopher T Harbison; Brian Lestini; David R Spigel Journal: N Engl J Med Date: 2015-05-31 Impact factor: 91.245
Authors: Freddie Bray; Jacques Ferlay; Isabelle Soerjomataram; Rebecca L Siegel; Lindsey A Torre; Ahmedin Jemal Journal: CA Cancer J Clin Date: 2018-09-12 Impact factor: 508.702
Authors: Mathew J Garnett; Elena J Edelman; Sonja J Heidorn; Chris D Greenman; Anahita Dastur; King Wai Lau; Patricia Greninger; I Richard Thompson; Xi Luo; Jorge Soares; Qingsong Liu; Francesco Iorio; Didier Surdez; Li Chen; Randy J Milano; Graham R Bignell; Ah T Tam; Helen Davies; Jesse A Stevenson; Syd Barthorpe; Stephen R Lutz; Fiona Kogera; Karl Lawrence; Anne McLaren-Douglas; Xeni Mitropoulos; Tatiana Mironenko; Helen Thi; Laura Richardson; Wenjun Zhou; Frances Jewitt; Tinghu Zhang; Patrick O'Brien; Jessica L Boisvert; Stacey Price; Wooyoung Hur; Wanjuan Yang; Xianming Deng; Adam Butler; Hwan Geun Choi; Jae Won Chang; Jose Baselga; Ivan Stamenkovic; Jeffrey A Engelman; Sreenath V Sharma; Olivier Delattre; Julio Saez-Rodriguez; Nathanael S Gray; Jeffrey Settleman; P Andrew Futreal; Daniel A Haber; Michael R Stratton; Sridhar Ramaswamy; Ultan McDermott; Cyril H Benes Journal: Nature Date: 2012-03-28 Impact factor: 49.962