Comprehensive genomic and transcriptomic characterization of high-grade gastro-entero-pancreatic neoplasms.

BACKGROUND: High-grade gastro-entero-pancreatic neoplasms (HG GEP-NENs) can be stratified according to their morphology and Ki-67 values into three prognostic classes: neuroendocrine tumors grade 3 (NETs G3), neuroendocrine carcinomas with Ki-67 < 55% (NECs <55) and NECs with Ki-67 ≥ 55% (NECs ≥55). METHODS: We analyzed a cohort of 49 HG GEP-NENs by targeted Next-Generation Sequencing (TrueSight Oncology 500), RNA-seq, and immunohistochemistry for p53, Rb1, SSTR-2A, and PD-L1. RESULTS: Frequent genomic alterations affected TP53 (26%), APC (20%), KRAS and MEN1 (both 11%) genes. NET G3 were enriched in MEN1 (p = 0.02) mutations, while both NECs groups were enriched in TP53 (p = 0.001), APC (p = 0.002) and KRAS (p = 0.02) mutations and tumors with TMB ≥ 10 muts/Mb (p = 0.01). No differentially expressed (DE) gene was found between NECs <55% and NECs ≥55%, while 1129 DE genes were identified between NET G3 and NECs. A slight enrichment of CD4+ and CD8+ T cells in NECs and of cancer-associated fibroblasts and macrophages (M2-like) in NET G3. Multivariate analysis identified histologic type and Rb1 loss as independent prognostic factors for overall survival. CONCLUSIONS: This study showed that GEP-NET G3 and GEP-NECs exhibit clear genomic and transcriptomic differences, differently from GEP-NECs <55% and GEP-NECs ≥55%, and provided molecular findings with prognostic and potentially predictive value.

Lung carcinoid tumours: histology and Ki-67, the eternal rivalry.

WHO classification of Thoracic Tumours defines lung carcinoid tumours (LCTs) as well-differentiated neuroendocrine neoplasms (NENs) classified in low grade typical (TC) and intermediate grade atypical carcinoids (AC). Limited data exist concerning protein expression and morphologic factors able to predict disease aggressiveness. Though Ki-67 has proved to be a powerful diagnostic and prognostic factor for Gastro-entero-pancreatic NENs, its role in lung NENs is still debated. A retrospective series of 370 LCT from two oncology centers was centrally reviewed. Morphology and immunohistochemical markers (Ki-67, TTF-1, CD44, OTP, SSTR-2A, Ascl1, and p53) were studied and correlated with Overall Survival (OS), Cancer-specific survival (CSS) and Disease-free survival (DFS). Carcinoid histology was confirmed in 355 patients: 297 (83.7%) TC and 58 (16.3%) AC. Ki-67 at 3% was the best value in predicting DFS. Ki-67 ≥ 3% tumours were significantly associated with AC histology, stage III-IV, smoking, vascular invasion, tumour spread through air spaces OTP negativity, and TTF-1, Ascl1 and p53 positivity. After adjustment for center and period of diagnosis, both Ki-67 (≥3 versus <3) and histology (AC versus TC) alone significantly added prognostic information to OS and CSS multivariable model with age, stage and OTP; addition of both variables did not provide further prognostic information. Conversely, an improved significance of the DFS prediction model at multivariate analysis was seen by adding Ki-67 (≥3 versus <3, P adj = 0.01) to TC and AC histological distinction, age, lymph node involvement, residual tumour and OTP. Ki-67 ≥ 3% plays a potentially pivotal role in LCT prognosis, irrespective of histological grade.

Ascl1 and OTP tumour expressions are associated with disease-free survival in lung atypical carcinoids.

According to World Health Organization guidelines, atypical carcinoids (ACs) are well-differentiated lung neuroendocrine tumours with 2-10 mitoses/2 mm2 and/or foci of necrosis (usually punctate). Besides morphological criteria, no further tools in predicting AC clinical outcomes are proposed. The aim of this work was to identify novel factors able to predict AC disease aggressiveness and progression. METHODS AND RESULTS: Three hundred-seventy lung carcinoids were collected and centrally reviewed by two expert pathologists. Morphology and immunohistochemical markers (Ki-67, TTF-1, CD44, OTP, SSTR2A, Ascl1, p53, and Rb1) were studied and correlated with disease-free survival (DFS) and overall survival (OS). Fifty-eight of 370 tumours were defined as AC. Survival analysis showed that patients with Ascl1 + ACs and those with OTP-ACs had a significantly worse DFS than patients with Ascl1-ACs and OTP + ACs, respectively. Combining Ascl1 and OTP expressions, groups were formed reflecting the aggressiveness of disease (P = 0.0005). Ki-67 ≥10% patients had a significantly worse DFS than patients with Ki-67 <10%. At multivariable analysis, Ascl1 (present versus absent, hazard ratio [HR] = 3.42, 95% confidence interval [CI] 1.35-8.65, P = 0.009) and OTP (present versus absent, HR = 0.26, 95% CI 0.10-0.68, P = 0.006) were independently associated with DFS. The prognosis of patients with Ki-67 ≥10% tended to be worse compared to that with Ki-67 <10%. On the contrary, OTP (present versus absent, HR = 0.28, 95% CI 0.09-0.89, P = 0.03), tumour stage (III-IV versus I-II, HR = 4.25, 95% CI 1.42-12.73, P = 0.01) and increasing age (10-year increase, HR = 1.67, 95% CI 1.04-2.68, P = 0.03) were independently associated with OS. CONCLUSION: This retrospective analysis of lung ACs showed that Ascl1 and OTP could be the main prognostic drivers of postoperative recurrence.

Digestive MiNENs: Could histological classification and molecular characterization drive clinical outcome and therapeutic approach?

Mixed neuroendocrine-non-neuroendocrine neoplasms (MiNENs) are epithelial neoplasms in which neuroendocrine and non-neuroendocrine discrete components are combined, each of which constitutes ≥ 30% of the neoplasm. The finding of an additional neuroendocrine component seems to characterize the tumor's biological behavior. Few studies have proved MiNENs histogenetic and molecular characterization, and the development of molecular markers for more accurate classification of MiNENs represents a clinical need. However, a common origin of the neuroendocrine and non-neuroendocrine components from a pluripotent cancer stem cell could be suggested. The optimal clinical management of MiNENS is largely unknown. Whenever feasible, curative-intent resection should be performed for localized disease; in advanced disease, the treatment should be targeted to the component responsible for the metastatic spreading. This paper provides a revision of the current knowledge on MiNENs, focusing on available evidence about their molecular characterization to suggest a prognostic stratification of these rare forms.

A2AR Expression and Immunosuppressive Environment Independent of KRAS and GNAS Mutations in Pseudomyxoma Peritonei.

In pseudomyxoma peritonei (PMP), KRAS and GNAS mutations are frequent. We hypothesized that these mutations may contribute to the suppression of antitumor immunity: KRAS may induce GMCSF expression, while GNAS may enhance the expression of cyclic adenosine monophosphate and A2AR signaling. This study aimed to explore possible mechanisms facilitated by KRAS and GNAS mutations for escaping immune surveillance. Additionally, we looked for new potential therapeutic and prognostic targets in this rare disease which is poorly characterized at the molecular level. GM-CSF, A2AR, CD73, CD39, and PD-L1 expression was investigated by immunohistochemistry in 40 PMPs characterized for GNAS and KRAS mutational status. Immune cell populations were studied by immunohistochemistry and nanostring nCounter®. Following the criteria of a prognostic nomogram reported for PMP, we stratified the patients into two different risk groups, with 28 "low-risk" and 12 "high-risk" patients. We observed the expression of GM-CSF (74%); CD39 (37%); CD73 (53%); A2AR (74%); and PD-L1 (16%) which was unrelated to GNAS or KRAS status. The tumor microenvironment showed the presence of CD4+ T cells (86%); CD8+ T cells (27%); CD20+ B (67%); CD15+ cells (86%); and CD163+ M2 macrophages (67%), while CD56+ NK cells were absent. CD163 expression (27%) in PMP tumor cells was associated with poor prognosis. GNAS mutation and A2AR expression were not associated with a specific immune transcriptional signature. However, the expression assay revealed 21 genes associated with prognosis. The "high-risk" patients exhibited worse progression-free survival (HR = 2.3, CI 95%: 1.1-5.1, p = 0.034) and significant downregulation of MET, IL8, PPARG, DTX4, HMGA1, ZIC2, WNT5B, and CCRL2. In conclusion, we documented the presence of immunosuppressive factors such as GM-CSF, A2AR, and PD-L1 in PMP. These factors were not associated with GNAS and KRAS status and could be explored as therapeutic molecular targets. Additionally, a set of potential prognostic biomarkers, including CD163 expression in tumor cells, deserve further investigation.

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

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.

Beyond Traditional Morphological Characterization of Lung Neuroendocrine Neoplasms: In Silico Study of Next-Generation Sequencing Mutations Analysis across the Four World Health Organization Defined Groups.

Lung neuroendocrine neoplasms (LNENs) represent a rare and heterogeneous population of lung tumors. LNENs incidence rate has increased dramatically over the past 30 years. The current World Health Organization LNENs classification (WHO 2015), distinguished four LNENs prognostic categories, according to their morphology, necrosis amount and mitotic count: typical carcinoid (TC), atypical-carcinoid (AC), large cell neuroendocrine carcinoma (LCNEC) and small cell lung cancer (SCLC). At present, due to their rarity and biological heterogeneity there is still no consensus on the best therapeutic approach. Next-generation-sequencing analysis showed that WHO 2015 LNENs classes, could be characterized also by specific molecular alterations: frequently mutated genes involving chromatin remodeling and generally characterized by low mutational burden (MB) are frequently detected in both TC and AC; otherwise, TP53 and RB1 tumor suppressor genes alterations and high MB are usually detected in LCNEC and SCLC. We provide an overview concerning gene mutations in each WHO 2015 LNENs class in order to report the current LNENs mutational status as potential tool to better understand their clinical outcome and to drive medical treatment.