Based on our hospital database, the incidence of lung cancer diagnoses was similar in obstructive sleep apnea Syndrome (OSAS) and hospital general population; among individual with a diagnosis of lung cancer, the presence of OSAS was associated with an increased risk for mortality. In the gene expression and network-level information, we revealed significant alterations of molecules related to HIF1 and metabolic pathways in the hypoxic-conditioned lung cancer cells. We also observed that GBE1 and HK2 are downstream of HIF1 pathway important in hypoxia-conditioned lung cancer cell. Furthermore, we used publicly available datasets to validate that the late-stage lung adenocarcinoma patients showed higher expression HK2 and GBE1 than early-stage ones. In terms of prognostic features, a survival analysis revealed that the high GBE1 and HK2 expression group exhibited poorer survival in lung adenocarcinoma patients. By analyzing and integrating multiple datasets, we identify molecular convergence between hypoxia and lung cancer that reflects their clinical profiles and reveals molecular pathways involved in hypoxic-induced lung cancer progression. In conclusion, we show that OSAS severity appears to increase the risk of lung cancer mortality.
Keywords: big data platform; lung cancer; obstructive sleep apnea syndrome.