Prognostic Model for High-Grade Neuroendocrine Carcinoma of the Lung Incorporating Genomic Profiling and Poly (ADP-ribose) Polymerase-1 Expression.

Purpose: High-grade neuroendocrine carcinoma (HGNEC) of the lung is an aggressive cancer with a complex biology. We aimed to explore the prognostic value of genetic aberrations and poly(ADP-ribose) polymerase-1 (PARP1) expression in HGNEC and to establish a novel prognostic model.

Materials And Methods: We retrospectively enrolled 191 patients with histologically confirmed HGNEC of the lung. Tumor tissues were analyzed using PARP1 immunohistochemistry (IHC; N = 191) and comprehensive cancer panel sequencing (n = 102). Clinical and genetic data were used to develop an integrated Cox hazards model.

Results: Strong PARP1 IHC expression (intensity 3) was observed in 153 of 191 (80.1%) patients, and the mean PARP1 H-score was 285 (range, 5-300). To develop an integrated Cox hazard model, our data set included information from 357 gene mutations and 19 clinical profiles. When the targeted mutation profiles were combined with clinical profiles, 12 genes (, , , , , , , , , , , and ) were identified as prognostic factors for survival. The integrated Cox hazard model, which combines mutation profiles with a baseline model, outperformed the baseline model (incremental area under the curve 0.84 0.78; = 8.79e-12). The integrated model stratified patients into high- and low-risk groups with significantly different disease-free and overall survival (integrated model: hazard ratio, 7.14 [95% CI, 4.07 to 12.54]; < .01; baseline model: 4.38 [2.56 to 7.51]; < .01).

Conclusion: We introduced a new prognostic model for HGNEC that combines genetic and clinical data. The integrated Cox hazard model outperformed the baseline model in predicting the survival of patients with HGNEC.