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Updated: May 6, 2026
Next Generation Sequencing for the Detection of Actionable Mutations in Solid and Liquid Tumors
Published on: September 20, 2016
A genomics-based classification of human lung tumors
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.
Insights
Genomic profiling of lung tumors revealed actionable alterations in over 55% of cases, leading to reassignment of diagnoses and improved survival for targeted therapies. This supports genome-based lung cancer diagnosis.
Area of Science:
- Oncology
- Genomics
- Cancer Diagnostics
Background:
- Lung cancer diagnosis traditionally relies on histomorphology, which may not fully capture underlying genomic drivers.
- Identifying actionable genomic alterations is crucial for personalized treatment strategies in lung cancer.
Purpose of the Study:
- To characterize genome alterations across all lung tumor histological subtypes.
- To identify genetically defined subtypes and assess their clinical relevance.
- To evaluate a genomics-based diagnostic algorithm for lung cancer.
Main Methods:
- Genome-wide characterization of alterations in 1255 lung tumors.
- Immunohistochemical studies to confirm reassigned subtypes.
- Prospective validation of a genomics-based diagnostic algorithm in 5145 patients.
Main Results:
- Over 55% of tumors harbored potentially targetable oncogenic genome alterations.
- Genomic profiling revealed significant differences within and between histological subtypes, challenging existing classifications.
- The genomics-based algorithm enabled diagnosis in 75% of patients and confirmed reassignment of large cell carcinomas.
- Improved overall survival was observed in patients with EGFR-mutant or ALK-rearranged cancers receiving targeted therapies.
Conclusions:
- Genome-based diagnosis offers a more precise classification of lung cancer subtypes.
- This approach identifies therapeutically relevant alterations and supports personalized treatment.
- Broad implementation of genome-based lung cancer diagnosis is supported by these findings.
