Signaling protein signature predicts clinical outcome of non-small-cell lung cancer
Abstract Background Non-small-cell lung cancer (NSCLC) is characterized by abnormalities of numerous signaling proteins that play pivotal roles in cancer development and progression. Many of these proteins have been reported to be correlated with clinical outcomes of NSCLC. However, none of them cou...
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2018-03-01
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Online Access: | http://link.springer.com/article/10.1186/s12885-018-4104-4 |
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Article |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Bao-Feng Jin Fan Yang Xiao-Min Ying Lin Gong Shuo-Feng Hu Qing Zhao Yi-Da Liao Ke-Zhong Chen Teng Li Yan-Hong Tai Yuan Cao Xiao Li Yan Huang Xiao-Yan Zhan Xuan-He Qin Jin Wu Shuai Chen Sai-Sai Guo Yu-Cheng Zhang Jing Chen Dan-Hua Shen Kun-Kun Sun Lu Chen Wei-Hua Li Ai-Ling Li Na Wang Qing Xia Jun Wang Tao Zhou |
spellingShingle |
Bao-Feng Jin Fan Yang Xiao-Min Ying Lin Gong Shuo-Feng Hu Qing Zhao Yi-Da Liao Ke-Zhong Chen Teng Li Yan-Hong Tai Yuan Cao Xiao Li Yan Huang Xiao-Yan Zhan Xuan-He Qin Jin Wu Shuai Chen Sai-Sai Guo Yu-Cheng Zhang Jing Chen Dan-Hua Shen Kun-Kun Sun Lu Chen Wei-Hua Li Ai-Ling Li Na Wang Qing Xia Jun Wang Tao Zhou Signaling protein signature predicts clinical outcome of non-small-cell lung cancer BMC Cancer Adenocarcinoma Non-small-cell lung cancer Prognosis Protein signature Squamous cell carcinoma |
author_facet |
Bao-Feng Jin Fan Yang Xiao-Min Ying Lin Gong Shuo-Feng Hu Qing Zhao Yi-Da Liao Ke-Zhong Chen Teng Li Yan-Hong Tai Yuan Cao Xiao Li Yan Huang Xiao-Yan Zhan Xuan-He Qin Jin Wu Shuai Chen Sai-Sai Guo Yu-Cheng Zhang Jing Chen Dan-Hua Shen Kun-Kun Sun Lu Chen Wei-Hua Li Ai-Ling Li Na Wang Qing Xia Jun Wang Tao Zhou |
author_sort |
Bao-Feng Jin |
title |
Signaling protein signature predicts clinical outcome of non-small-cell lung cancer |
title_short |
Signaling protein signature predicts clinical outcome of non-small-cell lung cancer |
title_full |
Signaling protein signature predicts clinical outcome of non-small-cell lung cancer |
title_fullStr |
Signaling protein signature predicts clinical outcome of non-small-cell lung cancer |
title_full_unstemmed |
Signaling protein signature predicts clinical outcome of non-small-cell lung cancer |
title_sort |
signaling protein signature predicts clinical outcome of non-small-cell lung cancer |
publisher |
BMC |
series |
BMC Cancer |
issn |
1471-2407 |
publishDate |
2018-03-01 |
description |
Abstract Background Non-small-cell lung cancer (NSCLC) is characterized by abnormalities of numerous signaling proteins that play pivotal roles in cancer development and progression. Many of these proteins have been reported to be correlated with clinical outcomes of NSCLC. However, none of them could provide adequate accuracy of prognosis prediction in clinical application. Methods A total of 384 resected NSCLC specimens from two hospitals in Beijing (BJ) and Chongqing (CQ) were collected. Using immunohistochemistry (IHC) staining on stored formalin-fixed paraffin-embedded (FFPE) surgical samples, we examined the expression levels of 75 critical proteins on BJ samples. Random forest algorithm (RFA) and support vector machines (SVM) computation were applied to identify protein signatures on 2/3 randomly assigned BJ samples. The identified signatures were tested on the remaining BJ samples, and were further validated with CQ independent cohort. Results A 6-protein signature for adenocarcinoma (ADC) and a 5-protein signature for squamous cell carcinoma (SCC) were identified from training sets and tested in testing sets. In independent validation with CQ cohort, patients can also be divided into high- and low-risk groups with significantly different median overall survivals by Kaplan-Meier analysis, both in ADC (31 months vs. 87 months, HR 2.81; P < 0.001) and SCC patients (27 months vs. not reached, HR 9.97; P < 0.001). Cox regression analysis showed that both signatures are independent prognostic indicators and outperformed TNM staging (ADC: adjusted HR 3.07 vs. 2.43, SCC: adjusted HR 7.84 vs. 2.24). Particularly, we found that only the ADC patients in high-risk group significantly benefited from adjuvant chemotherapy (P = 0.018). Conclusions Both ADC and SCC protein signatures could effectively stratify the prognosis of NSCLC patients, and may support patient selection for adjuvant chemotherapy. |
topic |
Adenocarcinoma Non-small-cell lung cancer Prognosis Protein signature Squamous cell carcinoma |
url |
http://link.springer.com/article/10.1186/s12885-018-4104-4 |
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doaj-4c3796d5eb42404c84422808102b61292020-11-25T02:18:31ZengBMCBMC Cancer1471-24072018-03-0118111210.1186/s12885-018-4104-4Signaling protein signature predicts clinical outcome of non-small-cell lung cancerBao-Feng Jin0Fan Yang1Xiao-Min Ying2Lin Gong3Shuo-Feng Hu4Qing Zhao5Yi-Da Liao6Ke-Zhong Chen7Teng Li8Yan-Hong Tai9Yuan Cao10Xiao Li11Yan Huang12Xiao-Yan Zhan13Xuan-He Qin14Jin Wu15Shuai Chen16Sai-Sai Guo17Yu-Cheng Zhang18Jing Chen19Dan-Hua Shen20Kun-Kun Sun21Lu Chen22Wei-Hua Li23Ai-Ling Li24Na Wang25Qing Xia26Jun Wang27Tao Zhou28State Key Laboratory of Proteomics, Institute of Basic Medical Sciences, China National Center of Biomedical AnalysisDepartment of Thoracic Surgery, People’s HospitalComputational Medicine Laboratory, Beijing Institute of Basic Medical SciencesState Key Laboratory of Proteomics, Institute of Basic Medical Sciences, China National Center of Biomedical AnalysisComputational Medicine Laboratory, Beijing Institute of Basic Medical SciencesState Key Laboratory of Proteomics, Institute of Basic Medical Sciences, China National Center of Biomedical AnalysisDepartment of Thoracic Surgery, People’s HospitalDepartment of Thoracic Surgery, People’s HospitalState Key Laboratory of Proteomics, Institute of Basic Medical Sciences, China National Center of Biomedical AnalysisThe 90th Hospital of JinanThe 90th Hospital of JinanDepartment of Thoracic Surgery, People’s HospitalState Key Laboratory of Proteomics, Institute of Basic Medical Sciences, China National Center of Biomedical AnalysisState Key Laboratory of Proteomics, Institute of Basic Medical Sciences, China National Center of Biomedical AnalysisState Key Laboratory of Proteomics, Institute of Basic Medical Sciences, China National Center of Biomedical AnalysisState Key Laboratory of Proteomics, Institute of Basic Medical Sciences, China National Center of Biomedical AnalysisState Key Laboratory of Proteomics, Institute of Basic Medical Sciences, China National Center of Biomedical AnalysisState Key Laboratory of Proteomics, Institute of Basic Medical Sciences, China National Center of Biomedical AnalysisState Key Laboratory of Proteomics, Institute of Basic Medical Sciences, China National Center of Biomedical AnalysisState Key Laboratory of Proteomics, Institute of Basic Medical Sciences, China National Center of Biomedical AnalysisDepartment of Pathology, People’s Hospital, Peking UniversityDepartment of Pathology, People’s Hospital, Peking UniversityInstitute of Pathology, Southwest Cancer Center, Southwest HospitalState Key Laboratory of Proteomics, Institute of Basic Medical Sciences, China National Center of Biomedical AnalysisState Key Laboratory of Proteomics, Institute of Basic Medical Sciences, China National Center of Biomedical AnalysisState Key Laboratory of Proteomics, Institute of Basic Medical Sciences, China National Center of Biomedical AnalysisState Key Laboratory of Proteomics, Institute of Basic Medical Sciences, China National Center of Biomedical AnalysisDepartment of Thoracic Surgery, People’s HospitalState Key Laboratory of Proteomics, Institute of Basic Medical Sciences, China National Center of Biomedical AnalysisAbstract Background Non-small-cell lung cancer (NSCLC) is characterized by abnormalities of numerous signaling proteins that play pivotal roles in cancer development and progression. Many of these proteins have been reported to be correlated with clinical outcomes of NSCLC. However, none of them could provide adequate accuracy of prognosis prediction in clinical application. Methods A total of 384 resected NSCLC specimens from two hospitals in Beijing (BJ) and Chongqing (CQ) were collected. Using immunohistochemistry (IHC) staining on stored formalin-fixed paraffin-embedded (FFPE) surgical samples, we examined the expression levels of 75 critical proteins on BJ samples. Random forest algorithm (RFA) and support vector machines (SVM) computation were applied to identify protein signatures on 2/3 randomly assigned BJ samples. The identified signatures were tested on the remaining BJ samples, and were further validated with CQ independent cohort. Results A 6-protein signature for adenocarcinoma (ADC) and a 5-protein signature for squamous cell carcinoma (SCC) were identified from training sets and tested in testing sets. In independent validation with CQ cohort, patients can also be divided into high- and low-risk groups with significantly different median overall survivals by Kaplan-Meier analysis, both in ADC (31 months vs. 87 months, HR 2.81; P < 0.001) and SCC patients (27 months vs. not reached, HR 9.97; P < 0.001). Cox regression analysis showed that both signatures are independent prognostic indicators and outperformed TNM staging (ADC: adjusted HR 3.07 vs. 2.43, SCC: adjusted HR 7.84 vs. 2.24). Particularly, we found that only the ADC patients in high-risk group significantly benefited from adjuvant chemotherapy (P = 0.018). Conclusions Both ADC and SCC protein signatures could effectively stratify the prognosis of NSCLC patients, and may support patient selection for adjuvant chemotherapy.http://link.springer.com/article/10.1186/s12885-018-4104-4AdenocarcinomaNon-small-cell lung cancerPrognosisProtein signatureSquamous cell carcinoma |