High-grade Gastroenteropancreatic Neuroendocrine neoplasms (H-NENs) comprehend well-differentiated tumors (NET G3) and poorly differentiated carcinomas (NEC) with proliferative activity indexes as mitotic count (MC) >20 mitoses/10 HPF and Ki-67 >20%. At present, no specific therapy for H-NENs exists and the several evidences of microenvironment involvement in their pathogenesis pave the way for tailored therapies. Forty-five consecutive cases, with available information about T-cell, immune, and non-immune markers, from surgical pathology and clinical databases of 2 Italian institutions were immunostained for Arginase, CD33, CD163 and CD66 myeloid markers. The association between features was assessed by Spearman's correlation coefficient. A unsupervised K-means algorithm was used to identify clusters of patients according to inputs of microenvironment features and the relationship between clusters and clinicopathological features, including cancer-specific survival (CSS), was analyzed. The H-NEN population was composed of 6 (13.3%) NET G3 and 39 (86.7%) NEC. Overall, significant positive associations were found between myeloid (CD33, CD163 and Arginase) and T/immune markers (CD3, CD4, CD8, PD-1 and HLA-I). Myeloid and T-cell markers CD3 and CD8 identified two clusters of patients from unsupervised K-means analysis. Cases grouped in cluster 1 with more myeloid infiltrates, T cell, HLA and expression of inhibitory receptors and ligands in the stroma (PD-1, PD-L1) had significantly better CSS than patients in cluster 2. Multivariable analysis showed that Ki-67 (>55 vs. <55, HR 8.60, CI 95% 2.61-28.33, p < 0.0001) and cluster (1 vs. 2, HR 0.43, CI 95% 0.20-0.93, p = 0.03) were significantly associated with survival. High grade gastroenteropancreatic neuroendocrine neoplasms can be further classified into two prognostic sub-populations of tumors driven by different tumor microenvironments and immune features able to generate the framework for evaluating new therapeutic strategies.

Myeloid and T-Cell Microenvironment Immune Features Identify Two Prognostic Sub-Groups in High-Grade Gastroenteropancreatic Neuroendocrine Neoplasms

Mangogna, Alessandro
Writing – Original Draft Preparation
;
2021

Abstract

High-grade Gastroenteropancreatic Neuroendocrine neoplasms (H-NENs) comprehend well-differentiated tumors (NET G3) and poorly differentiated carcinomas (NEC) with proliferative activity indexes as mitotic count (MC) >20 mitoses/10 HPF and Ki-67 >20%. At present, no specific therapy for H-NENs exists and the several evidences of microenvironment involvement in their pathogenesis pave the way for tailored therapies. Forty-five consecutive cases, with available information about T-cell, immune, and non-immune markers, from surgical pathology and clinical databases of 2 Italian institutions were immunostained for Arginase, CD33, CD163 and CD66 myeloid markers. The association between features was assessed by Spearman's correlation coefficient. A unsupervised K-means algorithm was used to identify clusters of patients according to inputs of microenvironment features and the relationship between clusters and clinicopathological features, including cancer-specific survival (CSS), was analyzed. The H-NEN population was composed of 6 (13.3%) NET G3 and 39 (86.7%) NEC. Overall, significant positive associations were found between myeloid (CD33, CD163 and Arginase) and T/immune markers (CD3, CD4, CD8, PD-1 and HLA-I). Myeloid and T-cell markers CD3 and CD8 identified two clusters of patients from unsupervised K-means analysis. Cases grouped in cluster 1 with more myeloid infiltrates, T cell, HLA and expression of inhibitory receptors and ligands in the stroma (PD-1, PD-L1) had significantly better CSS than patients in cluster 2. Multivariable analysis showed that Ki-67 (>55 vs. <55, HR 8.60, CI 95% 2.61-28.33, p < 0.0001) and cluster (1 vs. 2, HR 0.43, CI 95% 0.20-0.93, p = 0.03) were significantly associated with survival. High grade gastroenteropancreatic neuroendocrine neoplasms can be further classified into two prognostic sub-populations of tumors driven by different tumor microenvironments and immune features able to generate the framework for evaluating new therapeutic strategies.
17-apr-2021
Pubblicato
https://www.mdpi.com/2077-0383/10/8/1741
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8072982/
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