Clinical applications of (epi)genetics in gastroenteropancreatic neuroendocrine neoplasms: Moving towards liquid biopsies

The Use of PDX1 DNA Methylation to Distinguish Two Subtypes of Pancreatic Neuroendocrine Neoplasms with Different Prognoses

Pancreatic neuroendocrine neoplasms (pNENs) account for approximately 5% of all pancreatic tumors; thus, they constitute the second most common tumor type in the pancreas [...].

Risk Stratification of Pancreatic Neuroendocrine Neoplasms Based on Clinical, Pathological, and Molecular Characteristics

Pancreatic neuroendocrine neoplasms consist of heterogeneous diseases. Depending on the novel features detected by various modern technologies, their classification and related prognosis predictions continue to change and develop. The role of traditional clinicopathological prognostic factors, including classification systems, is also being refined, and several attempts have been made to predict a more accurate prognosis through novel serum biomarkers, genetic factors, and epigenetic factors that have been identified through various state-of-the-art molecular techniques with multiomics sequencing. In this review article, the latest research results including the traditional approach to prognostic factors and recent advanced strategies for risk stratification of pancreatic neuroendocrine neoplasms based on clinical, pathological, and molecular characteristics are summarized. Predicting prognosis through multi-factorial assessments seems to be more efficacious, and prognostic factors through noninvasive methods are expected to develop further advances in liquid biopsy in the future.

Comparison of the mutational profiles of neuroendocrine breast tumours, invasive ductal carcinomas and pancreatic neuroendocrine carcinomas

The pathophysiology and the optimal treatment of breast neuroendocrine tumours (NETs) are unknown. We compared the mutational profiles of breast NETs (n = 53) with those of 724 publicly available invasive ductal carcinoma (IDC) and 98 pancreatic NET (PNET) cases. The only significantly different pathogenetic or unknown variant rate between breast NETs and IDCs was detected in the TP53 (11.3% in breast NETs and 41% in IDCs, adjusted p value 0.027) and ADCK2 (9.4% in breast NETs vs. 0.28% in IDCs, adjusted p value 0.045) genes. Between breast NETs and PNETs, different pathogenetic or unknown variant frequencies were detected in 30 genes. For example, MEN1 was mutated in only 6% of breast NETs and 37% in PNETs (adjusted p value 0.00050), and GATA3 pathogenetic or unknown variants were only found in 17.0% of breast NETs and 0% in PNETs (adjusted p value 0.0010). The most commonly affected oncogenic pathways in the breast NET cases were PI3K/Akt/mTOR, NOTCH and RTK-RAS pathways. Breast NETs had typically clock-like mutational signatures and signatures associated with defective DNA mismatch repair in their mutational landscape. Our results suggest that the breast NET mutational profile more closely resembles that of IDCs than that of PNETs. These results also revealed several potentially druggable targets, such as MMRd, in breast NETs. In conclusion, breast NETs are indeed a separate breast cancer entity, but their optimal treatment remains to be elucidated.

Longitudinal Copy-Number Alteration Analysis in Plasma Cell-Free DNA of Neuroendocrine Neoplasms is a Novel Specific Biomarker for Diagnosis, Prognosis, and Follow-up

PURPOSE

As noninvasive biomarkers are an important unmet need for neuroendocrine neoplasms (NEN), biomarker potential of genome-wide molecular profiling of plasma cell-free DNA (cfDNA) was prospectively studied in patients with NEN.

EXPERIMENTAL DESIGN

Longitudinal plasma samples were collected from patients with well-differentiated, metastatic gastroenteropancreatic and lung NEN. cfDNA was subjected to shallow whole-genome sequencing to detect genome-wide copy-number alterations (CNA) and estimate circulating tumor DNA (ctDNA) fraction, and correlated to clinicopathologic and survival data. To differentiate pancreatic NENs (PNEN) from pancreatic adenocarcinomas (PAAD) using liquid biopsies, a classification model was trained using tissue-based CNAs and validated in cfDNA.

RESULTS

One hundred and ninety-five cfDNA samples from 43 patients with NEN were compared with healthy control cfDNA (N = 100). Plasma samples from patients with PNEN (N = 21) were used for comparison with publicly available PNEN tissue (N = 98), PAAD tissue (N = 109), and PAAD cfDNA (N = 96). Thirty percent of the NEN cfDNA samples contained ctDNA and 44% of the patients had at least one ctDNA-positive (ctDNA⁺) sample. CNAs detected in cfDNA were highly specific for NENs and the classification model could distinguish PAAD and PNEN cfDNA samples with a sensitivity, specificity, and AUC of 62%, 86%, and 79%, respectively. ctDNA-positivity was associated with higher World Health Organization (WHO) grade, primary tumor location, and higher chromogranin A and neuron-specific enolase values. Overall survival was significantly worse for ctDNA⁺ patients and increased ctDNA fractions were associated with poorer progression-free survival.

CONCLUSIONS

Sequential genome-wide profiling of plasma cfDNA is a novel, noninvasive biomarker with high specificity for diagnosis, prognosis, and follow-up in metastatic NENs.

Primary tumor location (right versus left side of the colon) and resection affect the survival of patients with liver metastases from colonic neuroendocrine carcinoma: a population-based study

BACKGROUND

Colonic neuroendocrine carcinomas (co-NECs) are heterogeneous and aggressive, especially with regard to metastasis. Whether co-NECs on the right and left sides of the colon have different characteristics from colon adenocarcinoma is unknown.

METHODS

The co-NEC patients were selected from the 2010-2017 Surveillance, Epidemiology, and End Results Program (SEER) database. The right and left sides of the colon were separated by the splenic flexure. Coarsened exact matching (CEM) was performed to adjust for relevant factors before regression models were constructed.

RESULTS

A total of 669 pathologically diagnosed co-NEC patients with sufficient baseline data were identified from the SEER database. A total of 80.72% of the patients had co-NEC that originated from the right side of the colon, and their mean overall survival (mOS) was similar to that of the patients with left-sided co-NECs (right versus left: 22.30 m versus 22.55 m). A total of 44.84% of the patients were diagnosed with liver metastasis (46.68% right side versus 37.98% left side). In patients with liver metastasis, those with right-sided co-NECs had better survival than those with left-sided co-NECs (mOS right versus left: 15.37 m versus 9.62 m; adjusted hazard ratio (HR) = 0.69, 95% confidence interval (CI): 0.49-0.98, p = 0.035). To further investigate the survival benefits of primary site resection, we separated the patients who had liver metastasis according to the primary site and performed CEM to balance the groups (no patients underwent liver metastasis resection or intervention). The results suggested that primary surgery could benefit patients with both left- and right-sided co-NECs (adjusted HR = 0.50, 95% CI: 0.33-0.77, p = 0.001 on the right side; HR = 0.38, 95% CI: 0.16-0.89, p = 0.026 on the left side).

CONCLUSIONS

Co-NECs frequently originate on the right side and commonly develop liver metastasis. Right-sided co-NECs are associated with better survival than left-sided co-NECs after liver metastasis has occurred. Primary site resection is associated with prolonged survival in co-NEC patients with liver metastasis, regardless of the side from which the co-NEC has originated.

Treatment personalization in gastrointestinal neuroendocrine tumors

OPINION STATEMENT

The clinical scenario of gastroenteropancreatic neuroendocrine neoplasms (GEP-NENs) is continuously changing due to significant improvements in the definition of their molecular landscapes and the introduction of innovative therapeutic approaches. Many efforts are currently employed in the integration of the genetics/epigenetics and clinical information. This is leading to an improvement of tumor classification, prognostic stratification and ameliorating the management of patients based on a personalized approach.

Blood Molecular Genomic Analysis Predicts the Disease Course of Gastroenteropancreatic Neuroendocrine Tumor Patients: A Validation Study of the Predictive Value of the NETest®

Reliable prediction of disease status is a major challenge in managing gastroenteropancreatic neuroendocrine tumors (GEP-NETs). The aim of the study was to validate the NETest®, a blood molecular genomic analysis, for predicting the course of disease in individual patients compared to chromogranin A (CgA). NETest® score (normal ≤20%) and CgA level (normal <100 µg/L) were measured in 152 GEP-NETs. The median follow-up was 36 (4-56) months. Progression-free survival was blindly assessed (Response Evaluation Criteria in Solid Tumors [RECIST] version 1.1). Optimal cutoffs (area under the receiver operating characteristic curve [AUC]), odds ratios, as well as negative and positive predictive values (NPVs/PPVs) were calculated for predicting stable disease (SD) and progressive disease (PD). Of the 152 GEP-NETs, 86% were NETest®-positive and 52% CgA-positive. -NETest® AUC was 0.78 versus CgA 0.73 (p = ns). The optimal cutoffs for predicting SD/PD were 33% for the NETest® and 140 µg/L for CgA. Multivariate analyses identified NETest® as the strongest predictor for PD (odds ratio: 5.7 [score: 34-79%]; 12.6 [score: ≥80%]) compared to CgA (odds ratio: 3.0), tumor grade (odds ratio: 3.1), or liver metastasis (odds ratio: 7.7). The NETest® NPV for SD was 87% at 12 months. The PPV for PD was 47 and 64% (scores 34-79% and ≥80%, respectively). NETest® metrics were comparable in the watchful waiting, treatment, and no evidence of disease (NED) subgroups. For CgA (>140 ng/mL), NPV and PPV were 83 and 52%. CgA could not predict PD in the watchful waiting or NED subgroups. The NETest® reliably predicted SD and was the strongest predictor of PD. CgA had lower utility. The -NETest® anticipates RECIST-defined disease status up to 1 year before imaging alterations are apparent.

Candidate protein biomarkers in pancreatic neuroendocrine neoplasms grade 3

Pancreatic neuroendocrine neoplasms (PanNENs) are rare tumours that compose 1–2% of all pancreatic tumours. Patients with metastatic grade 3 neoplasia are usually treated with chemotherapy but have a poor progression-free and overall survival. According to the WHO 2017 classification, they are divided into neuroendocrine tumours (NETs) G3 and neuroendocrine carcinomas (NECs). Despite the new classification, new diagnostic and prognostic biomarkers are needed to sub-categorise the patients and to help guide therapy decisions. Blood from 42 patients and 42 healthy controls were screened for the presence of 92 proteins with the Immuno-Oncology panel using the Proximity Extension Assay provided by Olink Biosciences. Immunohistochemical staining of FAS ligand (FASLG) was performed on 16 patient tumour specimens using a commercial antibody. Fifty-four out of 87 evaluable proteins differed significantly in concentration between blood from patients and blood from healthy controls. FASLG was the only protein for which the concentration in blood was significantly lower in patients compared to controls and the levels correlated negatively to Ki-67 index. Seven of 14 evaluable PanNEN G3 specimens showed FASLG immunoreactivity in the tumour cells while there was scattered immunoreactivity in immune cells. Positive FASLG immunoreactivity correlated to well-differentiated morphology. FASLG concentration in blood was significantly lower in patients with pancreatic NENs G3 compared to controls, and the expression in tumour tissue was variable. Furthermore, FASLG was negatively correlated to Ki-67 and was more frequently expressed in well-differentiated tumours. Taken together, these results may suggest a role of FASLG in PanNENs.

PDX1 DNA Methylation Distinguishes Two Subtypes of Pancreatic Neuroendocrine Neoplasms with a Different Prognosis

DNA methylation is a crucial epigenetic mechanism for gene expression regulation and cell differentiation. Furthermore, it was found to play a major role in multiple pathological processes, including cancer. In pancreatic neuroendocrine neoplasms (PNENs), epigenetic deregulation is also considered to be of significance, as the most frequently mutated genes have an important function in epigenetic regulation. However, the exact changes in DNA methylation between PNENs and the endocrine cells of the pancreas, their likely cell-of-origin, remain largely unknown. Recently, two subtypes of PNENs have been described which were linked to cell-of-origin and have a different prognosis. A difference in the expression of the transcription factor PDX1 was one of the key molecular differences. In this study, we performed an exploratory genome-wide DNA methylation analysis using Infinium Methylation EPIC arrays (Illumina) on 26 PNENs and pancreatic islets of five healthy donors. In addition, the methylation profile of the PDX1 region was used to perform subtyping in a global cohort of 83 PNEN, 2 healthy alpha cell and 3 healthy beta cell samples. In our exploratory analysis, we identified 26,759 differentially methylated CpGs and 79 differentially methylated regions. The gene set enrichment analysis highlighted several interesting pathways targeted by altered DNA methylation, including MAPK, platelet-related and immune system-related pathways. Using the PDX1 methylation in 83 PNEN, 2 healthy alpha cell and 3 healthy beta cell samples, two subtypes were identified, subtypes A and B, which were similar to alpha and beta cells, respectively. These subtypes had different clinicopathological characteristics, a different pattern of chromosomal alterations and a different prognosis, with subtype A having a significantly worse prognosis compared with subtype B (HR 0.22 [95% CI: 0.051–0.95], p = 0.043). Hence, this study demonstrates that several cancer-related pathways are differently methylated between PNENs and normal islet cells. In addition, we validated the use of the PDX1 methylation status for the subtyping of PNENs and its prognostic importance.

Biomarkers for Pancreatic Neuroendocrine Neoplasms (PanNENs) Management-An Updated Review

Pancreatic neuroendocrine tumors (PanNENs) are rare sporadic cancers or develop as part of hereditary syndromes. PanNENs can be both functioning and non-functioning based on whether they produce bioactive peptides. Some PanNENs are well differentiated while others-poorly. Symptoms, thus, depend on both oncological and hormonal causes. PanNEN diagnosis and treatment benefit from and in some instances are guided by biomarker monitoring. However, plasmatic monoanalytes are only suggestive of PanNEN pathological status and their positivity is typically followed by deepen diagnostic analyses through imaging techniques. There is a strong need for new biomarkers and follow-up modalities aimed to improve the outcome of PanNEN patients. Liquid biopsy follow-up, i.e., sequential analysis on tumor biomarkers in body fluids offers a great potential, that need to be substantiated by additional studies focusing on the specific markers and the timing of the analyses. This review provides the most updated panorama on PanNEN biomarkers.