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Genomics-Based Classification

Posted in Biomarkers & Medical Diagnostics, CANCER BIOLOGY & Innovations in Cancer Therapy, Chemical Genetics, Genome Biology, Genomic Testing: Methodology for Diagnosis, International Global Work in Pharmaceutical, Personalized and Precision Medicine & Genomic Research, Pharmacogenomics, Population Health Management, Genetics & Pharmaceutical, tagged diagnostic accuracy, genomic classification algorithm, large cell tumors, Lung cancer, Network Genomic Medicine (NGM), personalized treatment, Sci Transl Med, The Clinical Lung Cancer Genome Project (CLCGP) on November 1, 2013| 3 Comments »

Genomics-Based Classification

Author and Curator: Larry H. Bernstein, MD, FCAP

and

Curator: Aviva Lev-Ari, PhD, RN

This article is a recently reported use of genomics to classify lung cancer published in Science Translational Medicine.

A Genomics-Based Classification of Human Lung Tumors

Sci Transl Med 30 Oct 2013; 5(209), p. 209ra153 http://dx.doi.org/10.1126/scitranslmed.3006802

The Clinical Lung Cancer Genome Project (CLCGP) and Network Genomic Medicine (NGM),*,†

↵†Corresponding authors. E-mail: roman.thomas@uni-koeln.de (R.T.); reinhard.buettner@uk-koeln.de (R.B.); juergen.wolf@uk-koeln.de (J.W.)

↵* Lists of participants and their affiliations appear at the end of the paper.

Abstract

We characterized genome alterations in 1255 clinically annotated lung tumors of all histological subgroups to identify genetically defined and clinically relevant subtypes. More than 55% of all cases had at least one oncogenic genome alteration

potentially amenable to specific therapeutic intervention, including
several personalized treatment approaches that are already in clinical evaluation.

Marked differences in the pattern of genomic alterations existed between and within histological subtypes, thus

challenging the original histomorphological diagnosis.
Immunohistochemical studies confirmed many of these reassigned subtypes.
The reassignment eliminated almost all cases of large cell carcinomas,

some of which had therapeutically relevant alterations. Prospective testing of our genomics-based diagnostic algorithm in 5145 lung cancer patients enabled

a genome-based diagnosis in 3863 (75%) patients,
confirmed the feasibility of rational reassignments of large cell lung cancer, and
led to improvement in overall survival in patients with EGFR-mutant or ALK-rearranged cancers.

Thus, our findings provide support for broad implementation of genome-based diagnosis of lung cancer.