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Signaling protein signature predicts clinical outcome of non-small-cell lung cancer
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 provi...
Autores principales: | , , , , , , , , , , , , , , , , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2018
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5840771/ https://www.ncbi.nlm.nih.gov/pubmed/29510676 http://dx.doi.org/10.1186/s12885-018-4104-4 |
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author | Jin, Bao-Feng Yang, Fan Ying, Xiao-Min Gong, Lin Hu, Shuo-Feng Zhao, Qing Liao, Yi-Da Chen, Ke-Zhong Li, Teng Tai, Yan-Hong Cao, Yuan Li, Xiao Huang, Yan Zhan, Xiao-Yan Qin, Xuan-He Wu, Jin Chen, Shuai Guo, Sai-Sai Zhang, Yu-Cheng Chen, Jing Shen, Dan-Hua Sun, Kun-Kun Chen, Lu Li, Wei-Hua Li, Ai-Ling Wang, Na Xia, Qing Wang, Jun Zhou, Tao |
author_facet | Jin, Bao-Feng Yang, Fan Ying, Xiao-Min Gong, Lin Hu, Shuo-Feng Zhao, Qing Liao, Yi-Da Chen, Ke-Zhong Li, Teng Tai, Yan-Hong Cao, Yuan Li, Xiao Huang, Yan Zhan, Xiao-Yan Qin, Xuan-He Wu, Jin Chen, Shuai Guo, Sai-Sai Zhang, Yu-Cheng Chen, Jing Shen, Dan-Hua Sun, Kun-Kun Chen, Lu Li, Wei-Hua Li, Ai-Ling Wang, Na Xia, Qing Wang, Jun Zhou, Tao |
author_sort | Jin, Bao-Feng |
collection | PubMed |
description | 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. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s12885-018-4104-4) contains supplementary material, which is available to authorized users. |
format | Online Article Text |
id | pubmed-5840771 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-58407712018-03-14 Signaling protein signature predicts clinical outcome of non-small-cell lung cancer Jin, Bao-Feng Yang, Fan Ying, Xiao-Min Gong, Lin Hu, Shuo-Feng Zhao, Qing Liao, Yi-Da Chen, Ke-Zhong Li, Teng Tai, Yan-Hong Cao, Yuan Li, Xiao Huang, Yan Zhan, Xiao-Yan Qin, Xuan-He Wu, Jin Chen, Shuai Guo, Sai-Sai Zhang, Yu-Cheng Chen, Jing Shen, Dan-Hua Sun, Kun-Kun Chen, Lu Li, Wei-Hua Li, Ai-Ling Wang, Na Xia, Qing Wang, Jun Zhou, Tao BMC Cancer Research Article 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. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s12885-018-4104-4) contains supplementary material, which is available to authorized users. BioMed Central 2018-03-06 /pmc/articles/PMC5840771/ /pubmed/29510676 http://dx.doi.org/10.1186/s12885-018-4104-4 Text en © The Author(s). 2018 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated. |
spellingShingle | Research Article Jin, Bao-Feng Yang, Fan Ying, Xiao-Min Gong, Lin Hu, Shuo-Feng Zhao, Qing Liao, Yi-Da Chen, Ke-Zhong Li, Teng Tai, Yan-Hong Cao, Yuan Li, Xiao Huang, Yan Zhan, Xiao-Yan Qin, Xuan-He Wu, Jin Chen, Shuai Guo, Sai-Sai Zhang, Yu-Cheng Chen, Jing Shen, Dan-Hua Sun, Kun-Kun Chen, Lu Li, Wei-Hua Li, Ai-Ling Wang, Na Xia, Qing Wang, Jun Zhou, Tao Signaling protein signature predicts clinical outcome of non-small-cell lung cancer |
title | 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_short | 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 |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5840771/ https://www.ncbi.nlm.nih.gov/pubmed/29510676 http://dx.doi.org/10.1186/s12885-018-4104-4 |
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