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Automated whole-slide images assessment of immune infiltration in resected non-small-cell lung cancer: towards better risk-stratification
BACKGROUND: High immune infiltration is associated with favourable prognosis in patients with non-small-cell lung cancer (NSCLC), but an automated workflow for characterizing immune infiltration, with high validity and reliability, remains to be developed. METHODS: We performed a multicentre retrosp...
Autores principales: | , , , , , , , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9172185/ https://www.ncbi.nlm.nih.gov/pubmed/35672787 http://dx.doi.org/10.1186/s12967-022-03458-9 |
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author | Lin, Huan Pan, Xipeng Feng, Zhengyun Yan, Lixu Hua, Junjie Liang, Yanting Han, Chu Xu, Zeyan Wang, Yumeng Wu, Lin Cui, Yanfen Huang, Xiaomei Shi, Zhenwei Chen, Xin Chen, Xiaobo Zhang, Qingling Liang, Changhong Zhao, Ke Li, Zhenhui Liu, Zaiyi |
author_facet | Lin, Huan Pan, Xipeng Feng, Zhengyun Yan, Lixu Hua, Junjie Liang, Yanting Han, Chu Xu, Zeyan Wang, Yumeng Wu, Lin Cui, Yanfen Huang, Xiaomei Shi, Zhenwei Chen, Xin Chen, Xiaobo Zhang, Qingling Liang, Changhong Zhao, Ke Li, Zhenhui Liu, Zaiyi |
author_sort | Lin, Huan |
collection | PubMed |
description | BACKGROUND: High immune infiltration is associated with favourable prognosis in patients with non-small-cell lung cancer (NSCLC), but an automated workflow for characterizing immune infiltration, with high validity and reliability, remains to be developed. METHODS: We performed a multicentre retrospective study of patients with completely resected NSCLC. We developed an image analysis workflow for automatically evaluating the density of CD3(+) and CD8(+) T-cells in the tumour regions on immunohistochemistry (IHC)-stained whole-slide images (WSIs), and proposed an immune scoring system “I-score” based on the automated assessed cell density. RESULTS: A discovery cohort (n = 145) and a validation cohort (n = 180) were used to assess the prognostic value of the I-score for disease-free survival (DFS). The I-score (two-category) was an independent prognostic factor after adjusting for other clinicopathologic factors. Compared with a low I-score (two-category), a high I-score was associated with significantly superior DFS in the discovery cohort (adjusted hazard ratio [HR], 0.54; 95% confidence interval [CI] 0.33–0.86; P = 0.010) and validation cohort (adjusted HR, 0.57; 95% CI 0.36–0.92; P = 0.022). The I-score improved the prognostic stratification when integrating it into the Cox proportional hazard regression models with other risk factors (discovery cohort, C-index 0.742 vs. 0.728; validation cohort, C-index 0.695 vs. 0.685). CONCLUSION: This automated workflow and immune scoring system would advance the clinical application of immune microenvironment evaluation and support the clinical decision making for patients with resected NSCLC. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12967-022-03458-9. |
format | Online Article Text |
id | pubmed-9172185 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-91721852022-06-08 Automated whole-slide images assessment of immune infiltration in resected non-small-cell lung cancer: towards better risk-stratification Lin, Huan Pan, Xipeng Feng, Zhengyun Yan, Lixu Hua, Junjie Liang, Yanting Han, Chu Xu, Zeyan Wang, Yumeng Wu, Lin Cui, Yanfen Huang, Xiaomei Shi, Zhenwei Chen, Xin Chen, Xiaobo Zhang, Qingling Liang, Changhong Zhao, Ke Li, Zhenhui Liu, Zaiyi J Transl Med Research BACKGROUND: High immune infiltration is associated with favourable prognosis in patients with non-small-cell lung cancer (NSCLC), but an automated workflow for characterizing immune infiltration, with high validity and reliability, remains to be developed. METHODS: We performed a multicentre retrospective study of patients with completely resected NSCLC. We developed an image analysis workflow for automatically evaluating the density of CD3(+) and CD8(+) T-cells in the tumour regions on immunohistochemistry (IHC)-stained whole-slide images (WSIs), and proposed an immune scoring system “I-score” based on the automated assessed cell density. RESULTS: A discovery cohort (n = 145) and a validation cohort (n = 180) were used to assess the prognostic value of the I-score for disease-free survival (DFS). The I-score (two-category) was an independent prognostic factor after adjusting for other clinicopathologic factors. Compared with a low I-score (two-category), a high I-score was associated with significantly superior DFS in the discovery cohort (adjusted hazard ratio [HR], 0.54; 95% confidence interval [CI] 0.33–0.86; P = 0.010) and validation cohort (adjusted HR, 0.57; 95% CI 0.36–0.92; P = 0.022). The I-score improved the prognostic stratification when integrating it into the Cox proportional hazard regression models with other risk factors (discovery cohort, C-index 0.742 vs. 0.728; validation cohort, C-index 0.695 vs. 0.685). CONCLUSION: This automated workflow and immune scoring system would advance the clinical application of immune microenvironment evaluation and support the clinical decision making for patients with resected NSCLC. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12967-022-03458-9. BioMed Central 2022-06-07 /pmc/articles/PMC9172185/ /pubmed/35672787 http://dx.doi.org/10.1186/s12967-022-03458-9 Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data. |
spellingShingle | Research Lin, Huan Pan, Xipeng Feng, Zhengyun Yan, Lixu Hua, Junjie Liang, Yanting Han, Chu Xu, Zeyan Wang, Yumeng Wu, Lin Cui, Yanfen Huang, Xiaomei Shi, Zhenwei Chen, Xin Chen, Xiaobo Zhang, Qingling Liang, Changhong Zhao, Ke Li, Zhenhui Liu, Zaiyi Automated whole-slide images assessment of immune infiltration in resected non-small-cell lung cancer: towards better risk-stratification |
title | Automated whole-slide images assessment of immune infiltration in resected non-small-cell lung cancer: towards better risk-stratification |
title_full | Automated whole-slide images assessment of immune infiltration in resected non-small-cell lung cancer: towards better risk-stratification |
title_fullStr | Automated whole-slide images assessment of immune infiltration in resected non-small-cell lung cancer: towards better risk-stratification |
title_full_unstemmed | Automated whole-slide images assessment of immune infiltration in resected non-small-cell lung cancer: towards better risk-stratification |
title_short | Automated whole-slide images assessment of immune infiltration in resected non-small-cell lung cancer: towards better risk-stratification |
title_sort | automated whole-slide images assessment of immune infiltration in resected non-small-cell lung cancer: towards better risk-stratification |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9172185/ https://www.ncbi.nlm.nih.gov/pubmed/35672787 http://dx.doi.org/10.1186/s12967-022-03458-9 |
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