Title: Multi-omics Analysis reveals novel therapeutic vulnerabilities in lung cancer

Accession Number: GSE159857

Link to Dataset: https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE159857

Repository: Gene Expression Omnibus (GEO)

Data Type(s): Gene Expression

Experiment Type(s): Expression profiling by high throughput sequencing

Organism(s): Homo sapiens

Summary: Non-small cell lung cancer (NSCLC) comprises the majority (~85 percent) of all lung tumors, with lung adenocarcinoma (LUAD) and squamous cell carcinoma (LUSC) being the most frequently diagnosed histological subtypes. Currently, multi-modal omics profiles had been carried out in NSCLC, but no studies reported yet a systems biology approach to provide a complete picture of molecular perturbations specifically for LUAD and LUSC.

Publication(s) associated with this dataset:

• Thaiparambil J, Dong J, Grimm SL, Perera D, Ambati CS, Putluri V, Robertson M, Patel TD, Mistretta B, Gunaratne PH, Kim MP, Yustein JT, Putluri N, Coarfa C, El-Zein R. 2022. Integrative metabolomics and transcriptomics analysis reveals novel therapeutic vulnerabilities in lung cancer. Cancer Med doi:10.1002/cam4.4933 PMID:35676822

Project(s) associated with this dataset:

• Baylor College of Medicine: Data Management and Analysis Core
• Baylor College of Medicine: Research Support Core