Development and validation of a decision tree for distinguishing pulmonary adenocarcinomas with mucinous features and metastatic colorectal adenocarcinoma

Abstract

AbstractBackgroundDiagnosis of mucinous carcinomas in the lung on transbronchial biopsy or fine‐needle aspiration (FNA) samples can be difficult for the pathologist, because primary and metastatic tumors can have similar morphological, immunohistochemical, and molecular characteristics. Correct diagnosis is key to determine appropriate therapy and to distinguish primary from metastatic disease. This distinction often falls to the pathologist in patients with a history of mucinous adenocarcinoma of the colon. Despite its drawbacks, immunohistochemistry is often employed to help assign a primary site for mucinous adenocarcinomas in the lung. However, the published data in this regard is limited to studies that use only a handful of markers.MethodsThe authors examined the staining characteristics and heterogeneity of CK7, TTF‐1, NapsinA, CK20, CDX2, and SATB2 in resection specimens of pulmonary adenocarcinomas with mucinous features and metastatic colorectal adenocarcinoma.ResultsBased on the heterogeneity, sensitivity, and specificity in this cohort, the authors developed a decision tree based on TTF‐1, SATB2, CDX2, and CK7 to categorize tumors as primary or metastatic lesions. Validation of the decision tree in FNA specimens from the lungs and lung‐draining lymph nodes showed 84% concurrence in cases from the lung and 100% concurrence in cases from the lymph node. In cases where the algorithm assigned a primary site, it was 95% accurate compared to the multidisciplinary diagnosis.ConclusionsThis method holds promise in distinguishing primary versus metastatic lesions in resection, biopsy, and FNA samples from the lungs.