Introduction: In our previous study, we constructed a Lung Cancer Explorer (LCE) database housing lung cancer-specific expression data and clinical data from over 6700 patients in 56 studies.
Methods: Using this dataset of the largest collection of lung cancer gene expression along with our meta-analysis method, we systematically interrogated the association between gene expression and overall survival as well as the expression difference between tumor and normal (adjacent non-malignant tissue) samples in lung adenocarcinoma (ADC) and lung squamous cell carcinoma (SQCC). A case study for FAM83A and FAM83B was performed as a demonstration for hypothesis testing with our database.
Results: We showed that the reproducibility of results across studies varied by histological subtype and analysis type. Genes and pathways unique or common to the two histological subtypes were identified and the results were integrated into LCE to facilitate user exploration. In our case study, we verified the findings from a previous study on FAM83A and FAM83B in non-small cell lung cancer.
Conclusions: This study used gene expression data from a large cohort of patients to explore the molecular differences between lung ADC and SQCC.
Keywords: FAM83; gene expression difference between tumor and normal; lung cancer; meta-analysis; survival association analysis; systematic analysis.