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OTP, CD44, Ki-67 Immunohistochemistry to Predict Prognosis in Preoperative Lung Neuroendocrine Tumor Biopsy Specimens
Tijmen J J van Weert1, Laura Moonen1, Lisa M Hillen1
1Department of Pathology, GROW Research Institute for Oncology and Reproduction, Maastricht University Medical Centre (MUMC), Maastricht, The Netherlands.
Abstract:
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 Dutch pathology registry (PALGA). Immunohistochemistry for OTP, CD44 and Ki-67 (biomarkers) was performed on matched resection and biopsy (Bx) specimens. Three pathologists revised all cases per the WHO 2021 classification (WHO). OTP and CD44 were assessed by H-score, Ki-67 proliferation index (PI) by eyeball hot-spot scoring. Bx cases diagnosed as carcinoid not otherwise specified (NOS) were considered low risk for relapse and atypical carcinoid (AC) as high risk. Immunostained cases were classified as low risk (OTP≥50, CD44≥30, Ki-67<5%) or high risk (others). Ninety-eight patients were eligible. Nineteen relapse events occurred after a median follow-up 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 AC. Negative predictive value of biomarkers was 0.96 compared to 0.82 for WHO. The biomarkers showed greater prognostic stratification in relapse-free survival analysis and higher inter-observer agreement (biomarkers: κ=0.673; WHO: κ=0.276, both p<0.001). Biomarker expression was more stable between biopsy and resection specimen, improving concordance compared to WHO (biomarkers: κ=0.584, p<0.001; WHO: κ=0.169, p=0.037). 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.

