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Gene expression profiling of large cell lung cancer links transcriptional phenotypes to the new histological WHO2015 classification

Karlsson, Anna LU ; Brunnström, Hans LU orcid ; Micke, Patrick ; Veerla, Srinivas LU orcid ; Mattsson, Johanna M ; La Fleur, Linnea ; Botling, Johan ; Jönsson, Mats LU ; Reuterswärd, Christel LU and Planck, Maria LU , et al. (2017) In Journal of Thoracic Oncology 12(8). p.1257-1267
Abstract

INTRODUCTION: Large cell carcinoma with or without neuroendocrine features (LCNEC and LC, respectively) constitutes a small proportion of non-small cell lung cancer (NSCLC). The WHO2015 classification guidelines changed the definition of the debated histological subtype LC to be based on immunomarkers for adenocarcinoma and squamous cancer. We sought to determine if these new guidelines translate also to the transcriptional landscape of lung cancer, and LC specifically.

METHODS: Gene expression profiling was performed using Illumina V4 HT12 microarrays on 159 cases (comprising all histological subtypes including 10 WHO2015 LC and 14 LCNEC tumors), with complimentary mutational and IHC data. Derived transcriptional phenotypes were... (More)

INTRODUCTION: Large cell carcinoma with or without neuroendocrine features (LCNEC and LC, respectively) constitutes a small proportion of non-small cell lung cancer (NSCLC). The WHO2015 classification guidelines changed the definition of the debated histological subtype LC to be based on immunomarkers for adenocarcinoma and squamous cancer. We sought to determine if these new guidelines translate also to the transcriptional landscape of lung cancer, and LC specifically.

METHODS: Gene expression profiling was performed using Illumina V4 HT12 microarrays on 159 cases (comprising all histological subtypes including 10 WHO2015 LC and 14 LCNEC tumors), with complimentary mutational and IHC data. Derived transcriptional phenotypes were validated in 199 independent tumors, including six WHO2015 LCs and five LCNEC cases.

RESULTS: Unsupervised analysis of gene expression data identified a phenotype comprising 90% of WHO2015 LC tumors, with characteristics of poorly differentiated proliferative cancer, 90% TP53 mutation rate, and lack of well-known NSCLC oncogene driver alterations. Validation in independent data confirmed aggregation of WHO2015 LCs in the specific phenotype. For LCNEC tumors, the unsupervised gene expression analysis suggested two different transcriptional patterns, corresponding to a proposed genetic division of LCNEC tumors into SCLC-like and NSCLC-like cancer based on TP53 and RB1 alteration patterns.

CONCLUSIONS: Refined classification of LC has implications for diagnosis, prognostics, and therapy decisions Our molecular analyses support the WHO2015 classification of LC and LCNEC tumors, which herein follow different tumorigenic paths and can accordingly be stratified into different transcriptional subgroups, thus linking diagnostic IHC driven classification with the transcriptional landscape of lung cancer.

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organization
publishing date
type
Contribution to journal
publication status
published
subject
in
Journal of Thoracic Oncology
volume
12
issue
8
pages
1257 - 1267
publisher
Elsevier
external identifiers
  • scopus:85021246934
  • wos:000407187400009
  • pmid:28535939
ISSN
1556-1380
DOI
10.1016/j.jtho.2017.05.008
language
English
LU publication?
yes
id
e5cfb6c0-e8e0-49a2-a0b5-a7373e324b0e
date added to LUP
2017-05-30 15:45:08
date last changed
2025-03-03 18:30:32
@article{e5cfb6c0-e8e0-49a2-a0b5-a7373e324b0e,
  abstract     = {{<p>INTRODUCTION: Large cell carcinoma with or without neuroendocrine features (LCNEC and LC, respectively) constitutes a small proportion of non-small cell lung cancer (NSCLC). The WHO2015 classification guidelines changed the definition of the debated histological subtype LC to be based on immunomarkers for adenocarcinoma and squamous cancer. We sought to determine if these new guidelines translate also to the transcriptional landscape of lung cancer, and LC specifically.</p><p>METHODS: Gene expression profiling was performed using Illumina V4 HT12 microarrays on 159 cases (comprising all histological subtypes including 10 WHO2015 LC and 14 LCNEC tumors), with complimentary mutational and IHC data. Derived transcriptional phenotypes were validated in 199 independent tumors, including six WHO2015 LCs and five LCNEC cases.</p><p>RESULTS: Unsupervised analysis of gene expression data identified a phenotype comprising 90% of WHO2015 LC tumors, with characteristics of poorly differentiated proliferative cancer, 90% TP53 mutation rate, and lack of well-known NSCLC oncogene driver alterations. Validation in independent data confirmed aggregation of WHO2015 LCs in the specific phenotype. For LCNEC tumors, the unsupervised gene expression analysis suggested two different transcriptional patterns, corresponding to a proposed genetic division of LCNEC tumors into SCLC-like and NSCLC-like cancer based on TP53 and RB1 alteration patterns.</p><p>CONCLUSIONS: Refined classification of LC has implications for diagnosis, prognostics, and therapy decisions Our molecular analyses support the WHO2015 classification of LC and LCNEC tumors, which herein follow different tumorigenic paths and can accordingly be stratified into different transcriptional subgroups, thus linking diagnostic IHC driven classification with the transcriptional landscape of lung cancer.</p>}},
  author       = {{Karlsson, Anna and Brunnström, Hans and Micke, Patrick and Veerla, Srinivas and Mattsson, Johanna M and La Fleur, Linnea and Botling, Johan and Jönsson, Mats and Reuterswärd, Christel and Planck, Maria and Staaf, Johan}},
  issn         = {{1556-1380}},
  language     = {{eng}},
  month        = {{05}},
  number       = {{8}},
  pages        = {{1257--1267}},
  publisher    = {{Elsevier}},
  series       = {{Journal of Thoracic Oncology}},
  title        = {{Gene expression profiling of large cell lung cancer links transcriptional phenotypes to the new histological WHO2015 classification}},
  url          = {{http://dx.doi.org/10.1016/j.jtho.2017.05.008}},
  doi          = {{10.1016/j.jtho.2017.05.008}},
  volume       = {{12}},
  year         = {{2017}},
}