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A prognostic model for overall survival of patients with early-stage non-small cell lung cancer: a multicentre, retrospective study

BACKGROUND: Intratumoural heterogeneity has been previously shown to be related to clonal evolution and genetic instability and associated with tumour progression. Phenotypically, it is reflected in the diversity of appearance and morphology within cell populations. Computer-extracted features relat...

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Autores principales: Lu, Cheng, Bera, Kaustav, Wang, Xiangxue, Prasanna, Prateek, Xu, Jun, Janowczyk, Andrew, Beig, Niha, Yang, Michael, Fu, Pingfu, Lewis, James, Choi, Humberto, Schmid, Ralph A, Berezowska, Sabina, Schalper, Kurt, Rimm, David, Velcheti, Vamsidhar, Madabhushi, Anant
Formato: Online Artículo Texto
Lenguaje:English
Publicado: 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7646741/
https://www.ncbi.nlm.nih.gov/pubmed/33163952
http://dx.doi.org/10.1016/s2589-7500(20)30225-9
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author Lu, Cheng
Bera, Kaustav
Wang, Xiangxue
Prasanna, Prateek
Xu, Jun
Janowczyk, Andrew
Beig, Niha
Yang, Michael
Fu, Pingfu
Lewis, James
Choi, Humberto
Schmid, Ralph A
Berezowska, Sabina
Schalper, Kurt
Rimm, David
Velcheti, Vamsidhar
Madabhushi, Anant
author_facet Lu, Cheng
Bera, Kaustav
Wang, Xiangxue
Prasanna, Prateek
Xu, Jun
Janowczyk, Andrew
Beig, Niha
Yang, Michael
Fu, Pingfu
Lewis, James
Choi, Humberto
Schmid, Ralph A
Berezowska, Sabina
Schalper, Kurt
Rimm, David
Velcheti, Vamsidhar
Madabhushi, Anant
author_sort Lu, Cheng
collection PubMed
description BACKGROUND: Intratumoural heterogeneity has been previously shown to be related to clonal evolution and genetic instability and associated with tumour progression. Phenotypically, it is reflected in the diversity of appearance and morphology within cell populations. Computer-extracted features relating to tumour cellular diversity on routine tissue images might correlate with outcome. This study investigated the prognostic ability of computer-extracted features of tumour cellular diversity (CellDiv) from haematoxylin and eosin (H&E)-stained histology images of non-small cell lung carcinomas (NSCLCs). METHODS: In this multicentre, retrospective study, we included 1057 patients with early-stage NSCLC with corresponding diagnostic histology slides and overall survival information from four different centres. CellDiv features quantifying local cellular morphological diversity from H&E-stained histology images were extracted from the tumour epithelium region. A Cox proportional hazards model based on CellDiv was used to construct risk scores for lung adenocarcinoma (LUAD; 270 patients) and lung squamous cell carcinoma (LUSC; 216 patients) separately using data from two of the cohorts, and was validated in the two remaining independent cohorts (comprising 236 patients with LUAD and 335 patients with LUSC). We used multivariable Cox regression analysis to examine the predictive ability of CellDiv features for 5-year overall survival, controlling for the effects of clinical and pathological parameters. We did a gene set enrichment and Gene Ontology analysis on 405 patients to identify associations with differentially expressed biological pathways implicated in lung cancer pathogenesis. FINDINGS: For prognosis of patients with early-stage LUSC, the CellDiv LUSC model included 11 discriminative CellDiv features, whereas for patients with early-stage LUAD, the model included 23 features. In the independent validation cohorts, patients predicted to be at a higher risk by the univariable CellDiv model had significantly worse 5-year overall survival (hazard ratio 1·48 [95% CI 1·06–2·08]; p=0·022 for The Cancer Genome Atlas [TCGA] LUSC group, 2·24 [1·04–4·80]; p=0·039 for the University of Bern LUSC group, and 1·62 [1·15–2·30]; p=0·0058 for the TCGA LUAD group). The identified CellDiv features were also found to be strongly associated with apoptotic signalling and cell differentiation pathways. INTERPRETATION: CellDiv features were strongly prognostic of 5-year overall survival in patients with early-stage NSCLC and also associated with apoptotic signalling and cell differentiation pathways. The CellDiv-based risk stratification model could potentially help to determine which patients with early-stage NSCLC might receive added benefit from adjuvant therapy. FUNDING: National Institue of Health and US Department of Defense.
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spelling pubmed-76467412020-11-06 A prognostic model for overall survival of patients with early-stage non-small cell lung cancer: a multicentre, retrospective study Lu, Cheng Bera, Kaustav Wang, Xiangxue Prasanna, Prateek Xu, Jun Janowczyk, Andrew Beig, Niha Yang, Michael Fu, Pingfu Lewis, James Choi, Humberto Schmid, Ralph A Berezowska, Sabina Schalper, Kurt Rimm, David Velcheti, Vamsidhar Madabhushi, Anant Lancet Digit Health Article BACKGROUND: Intratumoural heterogeneity has been previously shown to be related to clonal evolution and genetic instability and associated with tumour progression. Phenotypically, it is reflected in the diversity of appearance and morphology within cell populations. Computer-extracted features relating to tumour cellular diversity on routine tissue images might correlate with outcome. This study investigated the prognostic ability of computer-extracted features of tumour cellular diversity (CellDiv) from haematoxylin and eosin (H&E)-stained histology images of non-small cell lung carcinomas (NSCLCs). METHODS: In this multicentre, retrospective study, we included 1057 patients with early-stage NSCLC with corresponding diagnostic histology slides and overall survival information from four different centres. CellDiv features quantifying local cellular morphological diversity from H&E-stained histology images were extracted from the tumour epithelium region. A Cox proportional hazards model based on CellDiv was used to construct risk scores for lung adenocarcinoma (LUAD; 270 patients) and lung squamous cell carcinoma (LUSC; 216 patients) separately using data from two of the cohorts, and was validated in the two remaining independent cohorts (comprising 236 patients with LUAD and 335 patients with LUSC). We used multivariable Cox regression analysis to examine the predictive ability of CellDiv features for 5-year overall survival, controlling for the effects of clinical and pathological parameters. We did a gene set enrichment and Gene Ontology analysis on 405 patients to identify associations with differentially expressed biological pathways implicated in lung cancer pathogenesis. FINDINGS: For prognosis of patients with early-stage LUSC, the CellDiv LUSC model included 11 discriminative CellDiv features, whereas for patients with early-stage LUAD, the model included 23 features. In the independent validation cohorts, patients predicted to be at a higher risk by the univariable CellDiv model had significantly worse 5-year overall survival (hazard ratio 1·48 [95% CI 1·06–2·08]; p=0·022 for The Cancer Genome Atlas [TCGA] LUSC group, 2·24 [1·04–4·80]; p=0·039 for the University of Bern LUSC group, and 1·62 [1·15–2·30]; p=0·0058 for the TCGA LUAD group). The identified CellDiv features were also found to be strongly associated with apoptotic signalling and cell differentiation pathways. INTERPRETATION: CellDiv features were strongly prognostic of 5-year overall survival in patients with early-stage NSCLC and also associated with apoptotic signalling and cell differentiation pathways. The CellDiv-based risk stratification model could potentially help to determine which patients with early-stage NSCLC might receive added benefit from adjuvant therapy. FUNDING: National Institue of Health and US Department of Defense. 2020-10-19 2020-11 /pmc/articles/PMC7646741/ /pubmed/33163952 http://dx.doi.org/10.1016/s2589-7500(20)30225-9 Text en This is an Open Access article under the CC BY-NC-ND 4.0 license. http://creativecommons.org/licenses/by-nc-nd/4.0/
spellingShingle Article
Lu, Cheng
Bera, Kaustav
Wang, Xiangxue
Prasanna, Prateek
Xu, Jun
Janowczyk, Andrew
Beig, Niha
Yang, Michael
Fu, Pingfu
Lewis, James
Choi, Humberto
Schmid, Ralph A
Berezowska, Sabina
Schalper, Kurt
Rimm, David
Velcheti, Vamsidhar
Madabhushi, Anant
A prognostic model for overall survival of patients with early-stage non-small cell lung cancer: a multicentre, retrospective study
title A prognostic model for overall survival of patients with early-stage non-small cell lung cancer: a multicentre, retrospective study
title_full A prognostic model for overall survival of patients with early-stage non-small cell lung cancer: a multicentre, retrospective study
title_fullStr A prognostic model for overall survival of patients with early-stage non-small cell lung cancer: a multicentre, retrospective study
title_full_unstemmed A prognostic model for overall survival of patients with early-stage non-small cell lung cancer: a multicentre, retrospective study
title_short A prognostic model for overall survival of patients with early-stage non-small cell lung cancer: a multicentre, retrospective study
title_sort prognostic model for overall survival of patients with early-stage non-small cell lung cancer: a multicentre, retrospective study
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7646741/
https://www.ncbi.nlm.nih.gov/pubmed/33163952
http://dx.doi.org/10.1016/s2589-7500(20)30225-9
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