Unlocking Precise Lung Cancer Detection Through Minimal Panel Immunostaining in Small Biopsy Samples.

Introduction Lung cancer diagnosis faces challenges due to morphological heterogeneity and limited biopsy tissue. This study evaluates the efficacy of a minimal panel immunostaining technique using immunohistochemical markers like napsin A, thyroid transcription factor 1 (TTF-1), p63, and synaptophysin to improve the precision of lung carcinoma subclassification. Methods A retrospective analytical study was conducted at the Histopathology Laboratory of Saveetha Medical College and Hospital, Chennai, from January 2018 to February 2024. A total of 64 lung carcinoma cases were analyzed. Inclusion criteria included biopsy samples from lung lesions with a confirmed diagnosis of lung carcinoma based on histomorphological examination, covering all age groups and both genders. Non-carcinomatous lung lesions were excluded. Clinical data were obtained from the Medical Information Archiving Software (MIAS) database and histopathological examination request forms. Under a light microscope, tissue samples were examined after being fixed in formalin, processed, and stained with hematoxylin and eosin (H&E). Additionally, a minimal panel of immunohistochemical markers, including napsin A, TTF-1, p63, and synaptophysin, was used to subclassify lung carcinomas. Results The age group older than 50 years was the most affected, with a higher incidence in males. Histologically, 49% of cases were adenocarcinoma, 42% were squamous cell carcinoma, and 9% were small cell carcinoma. Immunohistochemistry (IHC) results adjusted these proportions to 54.6% adenocarcinoma, 31.2% squamous cell carcinoma, and 14% small cell carcinoma, showing a 5.6% increase in adenocarcinoma cases. The most common adenocarcinoma pattern was mixed, followed by acinar. TTF-1 and napsin A were crucial for identifying adenocarcinoma, while p63 was key for squamous cell carcinoma. Synaptophysin confirmed neuroendocrine differentiation in small cell carcinoma. Conclusion Incorporating a minimal panel of IHC markers significantly enhances the accuracy of lung carcinoma subclassification, addressing diagnostic challenges posed by morphological heterogeneity and limited sample size. This approach supports more precise and efficient clinical care for patients with lung cancer. Further validation in diverse clinical settings is recommended.