Micropapillary Histology

Abstract

Non–small cell lung carcinoma is a histologically diverse group of tumors that until recently has been treated homogeneously. As a result, pathologists recognized major classes of squamous, adenocarcinoma, and large cell carcinoma, with subclasses and variants to ensure accurate diagnosis, to identify rare subtypes, to assist pathologist communication, and to create uniformity in research despite the fact that these classes did not generally influence clinical decision-making. This has changed radically in the last few years. Chemotherapeutic regimens may be tailored based on histologic subtype, and targeted therapies are contraindicated in certain histologic subtypes. Molecular classification has led to insights into tumor pathogenesis, prognostication, and therapeutics. While the molecular age in lung cancer diagnostics and targeted therapeutics is driving the movement towards personalized medicine, it needs to be emphasized that pathologists have been providing personalized information all along. In fact, if we divide the patient-specific information into 4 categories—histologic classification, pathologic staging, prognostic markers of survival, and predictive markers of therapeutic response—pathologists can better understand the interplay of existing practice and novel findings in their current and future practice. In this issue of the American Journal of Clinical Pathology, Achcar and colleagues 1 provide an example of how morphologic classification and molecular classification provide complementary data that serve different components of personalized patient-specific information. In fact, this work demonstrates the issues that exist once these distinct data sets are merged, and shows us the challenges that face the surgical pathologists, thoracic pathologists, and molecular pathologists of the future.