Programmed Death Ligand -1 and Gene Mutation Characterization of Lung Malignancies in Patients at a Rural Hospital in Central India

INTRODUCTION: Lung malignancy is one of the most common neoplasms worldwide. Accurate histology sub-typing and identification of gene mutations in lung tumours are considered important to administer targeted therapy for improved clinical outcome. Our aim is to determine the frequency of EGFR mutation and Programmed death ligand-1 (PD -L1) status of lung malignancies in patients attending a rural hospital in Central India. MATERIALS AND METHODS: Formalin-fixed histology diagnosed lung malignancy (n=99) bronchoscopic/trucut lung biopsies were identified and the tissue blocks and slides were retrieved. Histology typing and staging of the lesions was assessed. PD-L1 expression on biopsy was detected by immunohistochemistry using commercially available primary antibody. PD-L1 expression was assessed and semi-quantified based on the intensity and proportion of tumour cells stained for the marker. EGFR gene mutation at exon19 and 21 was detected by polymerase chain reaction of tissue from paraffin blocks. Final analysis was performed on 87 biopsies for status of EGFR mutation and PD-L1 expression. RESULTS: The average age of lung malignancies patients was 63 years, with a preponderance of males. Advance disease in stage III and stage IV was more common in squamous cell carcinoma as compared to adenocarcinoma (p < 0.01). Mutations at exon 19-21 of the EGFR gene were detected in 7/87 (8%) cases of adenocarcinoma and all of these patients were non-smokers. A total of 52.9% of biopsies showed PD-L1 expression, which was higher in adenocarcinoma patients (p=0.04), smokers (p=0.00), and stage II and III patients (p= 0.00). CONCLUSION: EGFR gene mutations at exon 19 or 21 are seen in lung adenocarcinoma cases. PD-L1 expression was observed in EGFR mutated tissues. Our results should be further validated with large sample size and multicenter clinical data before extrapolation to design immunotherapy strategies.