TIA Centre Seminar Series: Dr. Pingjun Chen

Full Title: Pathomic features reveal immune and molecular evolution from lung preneoplasia to invasive adenocarcinoma

Abstract: Lung adenocarcinoma (ADC) is the most common histologic subtype of lung cancer, and atypical adenomatous hyperplasia is the only recognized preneoplasia to ADC, which may progress to adenocarcinoma in situ (AIS) and minimally invasive adenocarcinoma (MIA) and eventually to invasive ADC. Although molecular evolution during early lung carcinogenesis has been explored in recent years, the progress has been significantly hindered, primarily due to insufficient materials from ADC precursors. In this talk, I will present our study employing state-of-the-art deep learning and artificial intelligence techniques to robustly segment and recognize cells on routinely used H&E histopathology images and extract nine biology-relevant pathomic features to decode lung preneoplasia evolution. Extracted pathomic features revealed a progressive increase of atypical epithelial cells from normal to AAH, AIS, MIA, and ADC, consistent with the results from tissue-consuming and expensive molecular/immune profiling. Furthermore, pathomics analysis manifested progressively increasing cellular intratumor heterogeneity along with the evolution from normal lung to invasive ADC. These findings demonstrated the feasibility and substantial potential of pathomics in studying lung cancer carcinogenesis directly from the low-cost routine H&E staining.