4.7 Review

Towards the molecular era of discriminating multiple lung cancers

Journal

EBIOMEDICINE
Volume 90, Issue -, Pages -

Publisher

ELSEVIER
DOI: 10.1016/j.ebiom.2023.104508

Keywords

Multiple primary lung cancers; Intrapulmonary metastasis; Differential diagnosis; Molecule; Genetics

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In the era of histopathology-based diagnosis, discriminating multiple lung cancers (MLCs) has become a clinical dilemma. Recent advances in molecular technologies have improved the precision in distinguishing between multiple primary lung cancers (MPLCs) and intrapulmonary metastasis (IPMs). This review summarizes the latest progress in molecular identification of MLCs and compares various methods based on somatic mutations, chromosome alterations, microRNAs, and tumor microenvironment markers. It also discusses current challenges in genomics-based discrimination, including detection technology selection, next-generation sequencing, and intratumoral heterogeneity (ITH). Overall, this paper highlights the importance of entering the primary stage of molecule-based diagnostics.
In the era of histopathology-based diagnosis, the discrimination between multiple lung cancers (MLCs) poses sig-nificant uncertainties and has thus become a clinical dilemma. However, recent significant advances and increased application of molecular technologies in clonal relatedness assessment have led to more precision in distinguishing between multiple primary lung cancers (MPLCs) and intrapulmonary metastasis (IPMs). This review summarizes recent advances in the molecular identification of MLCs and compares various methods based on somatic mutations, chromosome alterations, microRNAs, and tumor microenvironment markers. The paper also discusses current challenges at the forefront of genomics-based discrimination, including the selection of detection technology, application of next-generation sequencing, and intratumoral heterogeneity (ITH). In summary, this paper highlights an entrance into the primary stage of molecule-based diagnostics.Copyright (c) 2023 Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (http:// creativecommons.org/licenses/by-nc-nd/4.0/).

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