Background: Programmed death-ligand 1 (PD-L1) is a crucial biomarker predicting efficacious treatment of immune checkpoint inhibitors (ICIs). Previous studies identified distinct staining utility among multiple PD-L1 antibodies, however, whether the genomic correlate of stained PD-L1 is also impacted by different testing assays is largely unknown. Methods: Here, we analyzed 873 lung adenocarcinoma (LUAD) samples by the FDA-approved SP263 and 22C3 antibodies, and discovered that TP53, KRAS, MET, and ALK alterations associated with high SP263/22C3-PD-L1 expression, while EGFR and ERBB2 aberrations linked to SP263/22C3-PD-L1 negativity. Results: We retrieved the data of 873 LUAD patients whose PD-L1 (SP263/22C3) and mutational data. The SP263/22C3-PD-L1 expression was significantly correlated with tumor mutational burden and was greater in metastatic lymph node than lung lesion and distal metastasis. Furthermore, TP53, MET, ALK, KRAS alterations were associated with higher SP263/22C3-PD-L1 expression, while EGFR and ERBB2 alterations were linked to SP263/22C3-PD-L1 negativity. In the TCGA database lacking fusion data except for ALK and using reverse phase protein arrays (RPPA) for quantifying PD-L1 expression, STK11 mutation exhibited negative correlation with PD-L1 mRNA (p < 0.001), but not the RPPA-PD-L1 protein-level expression (p > 0.10), while samples with ALK fusion showed a tendency of higher RPPA-PD-L1 (p = 0.088). Moreover, in the OAK trial providing data of single nucleotide variation and using SP142 (Ventana, Tucson, AZ) assay evaluating both tumor and immune cells, weak correlation between STK11 mutation and SP142-PD-L1 negativity was observed (p = 0.076). Conclusions: Identical usage of staining antibody is the fundament of further comparisons and deeper investigations. The FDA-approved SP263 and 22C3 assays with fixed reagent, machine and protocol may perform more effective and repeatable than LDTs such as the E1L3N method. In addition to the different staining utility among PD-L1 antibodies indicated by previous studies, we further provide insights into the dissimilar genomic correlates of stained PD-L1 by using different PD-L1 quantifying techniques.