High-resolution lung adenocarcinoma expression subtypes identify tumors with dependencies on MET, CDK4, CDK6, and PD-L1

Lung adenocarcinoma is one of the most common cancer types with various treatment modalities. However, better biomarkers to predict therapeutic response are still needed to improve precision medicine. We utilized a consensus hierarchical clustering approach on 509 LUAD cases from TCGA to identify five robust LUAD expression subtypes. We then integrated genomic (patient and cell line) and proteomic data to help define biomarkers of response to targeted therapies and immunotherapies. This approach defined subtypes with unique proteogenomic and dependency profiles.

Type: Other
Archiver: European Genome-Phenome Archive (EGA)

1 Dataset 1 Publication

Click on a Dataset ID in the table below to learn more, and to find out who to contact about access to these data

Dataset ID	Description	Technology	Samples
EGAD00001009339	High-resolution lung adenocarcinoma expression subtypes identify tumors with dependencies on MET, CDK4, CDK6, and PD-L1	Illumina HiSeq 2500	164

Publications	Citations
High-Resolution Profiling of Lung Adenocarcinoma Identifies Expression Subtypes with Specific Biomarkers and Clinically Relevant Vulnerabilities. Roh W, Geffen Y, Cha H, Miller M, Anand S, Kim J, Heiman DI, Gainor JF, Laird PW, Cherniack AD, Ock CY, Lee SH, Getz G, National Cancer Institute Center for Cancer Genomics Tumor Molecular Pathology (TMP) Analysis Working Group. Cancer Res 82: 2022 3917-3931	10

Publications

Citations

High-Resolution Profiling of Lung Adenocarcinoma Identifies Expression Subtypes with Specific Biomarkers and Clinically Relevant Vulnerabilities.
Roh W, Geffen Y, Cha H, Miller M, Anand S, Kim J, Heiman DI, Gainor JF, Laird PW, Cherniack AD, Ock CY, Lee SH, Getz G, National Cancer Institute Center for Cancer Genomics Tumor Molecular Pathology (TMP) Analysis Working Group. Cancer Res 82: 2022 3917-3931