[Translational Research and Diagnostics in Lung Cancer]

Overview

Journal Pathologe

Specialty Pathology

Date 2012 Sep 13

PMID 22968733

Citations 2

Authors

F Goke

S Perner

Affiliations

Soon will be listed here.

Abstract

Lung cancer is the most common malignant disease leading to death worldwide. Histologically, it is broadly subcategorized into small cell lung cancer (SCLC) and non-small cell lung cancer (NSCLC), with the latter mainly consisting of the major entities adenocarcinoma and squamous cell carcinoma. However, molecular profiling of various lung cancer entities has revealed major molecular differences within distinct histological tumor entities, resulting in the integration of molecular alterations in the subclassification of lung cancers. These findings can only estimate the genetic complexity of lung tumors. Large scale molecular profiling has the potential to identify novel diagnostic, prognostic and predictive markers as well as therapeutic targets. Importantly, this recently arising categorization of lung carcinomas can be regarded as an example for the characterization of malignomas of other organ systems. The pioneer model for this molecular subcategorization is the classification of malignant lymphomas.

Citing Articles

Prediction of pathologic stage in non-small cell lung cancer using machine learning algorithm based on CT image feature analysis.

Yu L, Tao G, Zhu L, Wang G, Li Z, Ye J BMC Cancer. 2019; 19(1):464.

PMID: 31101024 PMC: 6525347. DOI: 10.1186/s12885-019-5646-9.

A genomics-based classification of human lung tumors.

Sci Transl Med. 2013; 5(209):209ra153.

PMID: 24174329 PMC: 4006630. DOI: 10.1126/scitranslmed.3006802.

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