Decoding Lung Cancer Mutations: A 5-year Investigation in Ordu Province

Aim: Lung cancer is the leading cause of cancer-related mortality worldwide and is most often diagnosed at an advanced stage. The increasing prominence of targeted therapy approaches in recent years has made the identification of genetic variations within tumors clinically significant. This study aimed to determine the prevalence of key mutations such as EGFR, ALK, KRAS, and PDL-1 in lung cancer cases over a five-year period, along with their distribution across histological subtypes and their association with demographic characteristics, specifically within the province of Ordu. Material and Method: This retrospective, cross-sectional study included a total of 202 patients who were diagnosed with Non-small cell lung cancer (NSCLC) and presented to the Medical Oncology Clinic of Ordu State Hospital between January 2019 and December 2023. Demographic data such as age and sex, histological subtypes, and genetic mutation analyses and other clinical parametres were evaluated. Mutation analysis focused on actionable biomarkers including EGFR, ALK, KRAS, and PDL-1, and their relationships with demographic characteristics were assessed. Results: The median age was 67 years (91.1% male). The most frequently observed histological subtype was squamous cell carcinoma (49.5%). In female patients, adenocarcinoma was the predominant (83.3%). The most commonly detected genetic alteration was PDL-1 (10.4%). EGFR mutations were significantly more frequent in older patients, whereas ALK mutations occurred in significantly younger patients. Conclusion: This study represents the first large-scale lung cancer mutation screening conducted specifically in the Ordu province. Our findings indicate regional differences, with PD-L1 being the most common alteration and squamous cell carcinoma the predominant subtype, in contrast to national data where EGFR mutations and adenocarcinoma are more frequent. These discrepancies indicate that regional characteristics and the genetic profile of the patient population should be taken into consideration during treatment planning.