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How should molecular findings be integrated in the classification for lung cancer?

The use of molecular diagnostics in the diagnosis and management of patients with advanced lung cancer has become widespread. Although molecular classification has increasingly been incorporated in the pathologic classification of certain types of human tumors (particularly within the hematologic, g...

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Autores principales: Hung, Yin P., Chirieac, Lucian R.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: AME Publishing Company 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7653151/
https://www.ncbi.nlm.nih.gov/pubmed/33209647
http://dx.doi.org/10.21037/tlcr-20-153
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author Hung, Yin P.
Chirieac, Lucian R.
author_facet Hung, Yin P.
Chirieac, Lucian R.
author_sort Hung, Yin P.
collection PubMed
description The use of molecular diagnostics in the diagnosis and management of patients with advanced lung cancer has become widespread. Although molecular classification has increasingly been incorporated in the pathologic classification of certain types of human tumors (particularly within the hematologic, glial, and bone/soft tissue malignancies), genetic findings have not been formally incorporated into the pathologic classification of lung cancer, which presently relies solely on the assessment of histologic and immunophenotypic characteristics. Whether molecular classification should be adopted in lung cancer would depend on the diagnostic, prognostic, and predictive impacts of such classification—and whether these impacts confer significant values additive to those derived from the routine histologic and immunophenotypic assessment. We provide a brief overview on the genetics of lung cancer, including adenocarcinoma, squamous cell carcinoma, and neuroendocrine tumors (small cell carcinoma, large cell neuroendocrine carcinoma, and carcinoid tumors). We consider the values of molecular information with some examples, in terms of the current diagnostic, prognostic, and predictive impacts. Finally, we discuss the conceptual and technical challenges of adopting a molecular classification for lung cancer in clinical management for patients. While there are conceptual and technical hurdles to tackle in implementing molecular classification in the pathologic classification of lung cancer, such integrated histologic-molecular diagnosis may allow one to personalize and optimize therapy for patients with advanced lung cancer.
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spelling pubmed-76531512020-11-17 How should molecular findings be integrated in the classification for lung cancer? Hung, Yin P. Chirieac, Lucian R. Transl Lung Cancer Res Review Article on New Developments in Lung Cancer Diagnosis and Pathological Patient Management Strategies The use of molecular diagnostics in the diagnosis and management of patients with advanced lung cancer has become widespread. Although molecular classification has increasingly been incorporated in the pathologic classification of certain types of human tumors (particularly within the hematologic, glial, and bone/soft tissue malignancies), genetic findings have not been formally incorporated into the pathologic classification of lung cancer, which presently relies solely on the assessment of histologic and immunophenotypic characteristics. Whether molecular classification should be adopted in lung cancer would depend on the diagnostic, prognostic, and predictive impacts of such classification—and whether these impacts confer significant values additive to those derived from the routine histologic and immunophenotypic assessment. We provide a brief overview on the genetics of lung cancer, including adenocarcinoma, squamous cell carcinoma, and neuroendocrine tumors (small cell carcinoma, large cell neuroendocrine carcinoma, and carcinoid tumors). We consider the values of molecular information with some examples, in terms of the current diagnostic, prognostic, and predictive impacts. Finally, we discuss the conceptual and technical challenges of adopting a molecular classification for lung cancer in clinical management for patients. While there are conceptual and technical hurdles to tackle in implementing molecular classification in the pathologic classification of lung cancer, such integrated histologic-molecular diagnosis may allow one to personalize and optimize therapy for patients with advanced lung cancer. AME Publishing Company 2020-10 /pmc/articles/PMC7653151/ /pubmed/33209647 http://dx.doi.org/10.21037/tlcr-20-153 Text en 2020 Translational Lung Cancer Research. All rights reserved. https://creativecommons.org/licenses/by-nc-nd/4.0/Open Access Statement: This is an Open Access article distributed in accordance with the Creative Commons Attribution-NonCommercial-NoDerivs 4.0 International License (CC BY-NC-ND 4.0), which permits the non-commercial replication and distribution of the article with the strict proviso that no changes or edits are made and the original work is properly cited (including links to both the formal publication through the relevant DOI and the license). See: https://creativecommons.org/licenses/by-nc-nd/4.0 (https://creativecommons.org/licenses/by-nc-nd/4.0/) .
spellingShingle Review Article on New Developments in Lung Cancer Diagnosis and Pathological Patient Management Strategies
Hung, Yin P.
Chirieac, Lucian R.
How should molecular findings be integrated in the classification for lung cancer?
title How should molecular findings be integrated in the classification for lung cancer?
title_full How should molecular findings be integrated in the classification for lung cancer?
title_fullStr How should molecular findings be integrated in the classification for lung cancer?
title_full_unstemmed How should molecular findings be integrated in the classification for lung cancer?
title_short How should molecular findings be integrated in the classification for lung cancer?
title_sort how should molecular findings be integrated in the classification for lung cancer?
topic Review Article on New Developments in Lung Cancer Diagnosis and Pathological Patient Management Strategies
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7653151/
https://www.ncbi.nlm.nih.gov/pubmed/33209647
http://dx.doi.org/10.21037/tlcr-20-153
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