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)
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 | Illumina HiSeq 2500 | 164 |
| Publications | Citations |
|---|---|
|
High-Resolution Profiling of Lung Adenocarcinoma Identifies Expression Subtypes with Specific Biomarkers and Clinically Relevant Vulnerabilities.
Cancer Res 82: 2022 3917-3931 |
14 |
|
Dissecting transcriptome signals of anti-PD-1 response in lung adenocarcinoma.
Sci Rep 14: 2024 21096 |
0 |