PPM10 CORRELATION AND HIEARCHICAL CLUSTERING ORDER ANALYSIS OF TOP 25 CO-OCCURRING GENOMIC ALTERATIONS IN NON-SMALL CELL LUNG CANCER

The study was designed to analyze co-occurrence pattern of top 25 genomic alterations in patients with non-small cell lung cancer (NSCLC) to inform future research. The Flatiron Clinico-Genomic Database (CGDB) is a linked data source including electronic medical record and genomics data from Foundation Medicine, Inc. Patients with advanced or metastatic NSCLC were eligible for this study if they received anti-cancer therapy within 180 days after diagnosis. The 25 biomarkers with highest alteration rate were identified. Correlation matrix and cluster analysis were used. Of 5807 eligible patients, 5536 (95.3%) had at least one of 25 top biomarkers, among which the top 5 highest are TP53(65.1%), KRAS (29.7%), CDKN2A (26.7%), PDL1 (18.4%), and EGFR (17.9%). There are 1404 (24.2%) patients had two co-occurring biomarkers, 1317 (22.7%) three co-occurring biomarkers, 998 (17.2%) four co-occurring biomarkers, and 591 (10.2%) had five co-occurring biomarkers. The pairwise correlation matrix indicated strong and significant correlations occurs between CDKN2B and CDKNN2A (ρ=0.725, p<0.0001); NFKBIA and NKX2-1 (ρ=0.796, p<0.0001), SOX2 and PIK3CA (ρ=0.479, p<0.0001). Medium correlation was observed between RB1 and TP53 (ρ=0.14, p<0.0001), KRAS and STK11 (ρ=0.169, p<0.0001), KRAS and RBM10 (ρ=0.133, p<0.0001). Further hierarchical clustering order analysis show 6 co-occurrence patterns among SMARCA4, STK11 AND KEAP1, ATM, KRAS and RBM10, ARID1A and LRP1B, PTEN, MLL2, PIK3CA, SOX2, TP53, and RB1, ERBB2, CDKN2A, and CDKN2B, EGFR, MDM2, MYC, NKX2-1 and NFKBIA. The genomic alterations in NSCLC patients are very heterogeneous and reflect the underlying tumor biology. Strong co-occurrence among certain genes may exist and graphic presentation may help identify patterns.