The contrasting role of p16Ink4A patterns of expression in neuroendocrine and non-neuroendocrine lung tumors : a comprehensive analysis with clinicopathologic and molecular correlations

Lung cancer encompasses a constellation of malignancies with no validated prognostic markers. p16Ink4A expression has been reported in different subtypes of lung cancers; however, its prognostic value is controversial. Here, we sought to investigate the clinical significance of p16Ink4A immunoexpression according to specific staining patterns and its operational implications. A total of 502 tumors, including 277 adenocarcinomas, 84 squamous cell carcinomas, 22 large cell carcinomas, 47 typical carcinoids, 12 atypical carcinoids, 28 large cell neuroendocrine carcinomas, and 32 small cell carcinomas were reviewed and subjected to immunohistochemical analysis for p16Ink4A and Ki67. The spectrum of p16Ink4A expression was annotated for each case as negative, sporadic, focal, or diffuse. Expression at immunohistochemical level showed intra-tumor homogeneity, regardless tumor histotype. Enrichments in cells expressing p16Ink4A were observed from lower- to higher-grade neuroendocrine malignancies, whereas a decrease was seen in poorly and undifferentiated non-neuroendocrine carcinomas. Tumor proliferation indices were higher in neuroendocrine tumors expressing p16Ink4A while non-neuroendocrine malignancies immunoreactive for p16Ink4A showed a decrease in Ki67-positive cells. Quantitative statistical analyses including each histotype and the p16Ink4A status confirmed the independent prognostic role of p16Ink4A expression, being a high-risk indicator in neuroendocrine tumors and a marker of good prognosis in non-neuroendocrine lung malignancies. In this study, we provide circumstantial evidence to suggest that the routinary assessment of p16Ink4A expression using a three-tiered scoring algorithm, even in a small biopsy, may constitute a reliable, reproducible, and cost-effective substrate for a more accurate risk stratification of each individual patient.