OTP, CD44, and Ki-67 Immunohistochemistry to Predict Prognosis in Preoperative Lung Neuroendocrine Tumor Biopsy Specimens

Previously, OTP, CD44, and Ki-67 have been identified as prognostic biomarkers in lung carcinoids (lung neuroendocrine tumors or LNETs). We aimed to assess whether risk profiles can be established using these biomarkers on preoperative LNET biopsies. Patients with LNETs (TNM 8 stage I-III, 2003-2021) who underwent curative resection were selected from the Dutch pathology registry. Immunohistochemistry for OTP, CD44, and Ki-67 (biomarkers) was performed on matched resection and biopsy (Bx) specimens. Three pathologists revised all cases per the World Health Organization (WHO) 2021 classification. OTP and CD44 were assessed using the H-score and the Ki-67 proliferation index (PI) based on eyeball hot-spot scoring. Bx cases diagnosed as carcinoid not otherwise specified were considered low risk for relapse and atypical carcinoid as high risk. Immunostained cases were classified as low risk (OTP ≥ 50, CD44 ≥ 30, and Ki-67 < 5%) or high risk (others). Ninety-eight patients were eligible. Nineteen relapse events occurred after a median follow-up period of 83 months. The biomarkers correctly identified high risk in 89% (n = 17/19) of relapses, outperforming the WHO classification, which assigned 11% (n = 2/19) of relapses as atypical carcinoid. The negative predictive value of biomarkers was 0.96, compared with 0.82 for WHO. The biomarkers showed greater prognostic stratification in relapse-free survival analysis and higher interobserver agreement (biomarkers: κ = 0.673; WHO: κ = 0.276; both P < .001). Biomarker expression was more stable between biopsy and resection specimens, improving concordance compared with WHO (biomarkers: κ = 0.584, P < .001; WHO: κ = 0.169, P = .037). In conclusion, an OTP, CD44, and Ki-67 biomarker panel enables reliable identification of low-risk LNETs on Bx, outperforming WHO classification for prognostic stratification and biopsy-resection concordance. By accurately identifying tumors with a molecular low-risk profile on preoperative biopsies, this panel may help to guide treatment choice for patients considered for sublobar resection.