Predicting neuroendocrine tumor (carcinoid) neoplasia using gene expression profiling and supervised machine learning

Novel ensemble feature selection techniques applied to high-grade gastroenteropancreatic neuroendocrine neoplasms for the prediction of survival

BACKGROUND AND OBJECTIVE

Determining the most informative features for predicting the overall survival of patients diagnosed with high-grade gastroenteropancreatic neuroendocrine neoplasms is crucial to improve individual treatment plans for patients, as well as the biological understanding of the disease. The main objective of this study is to evaluate the use of modern ensemble feature selection techniques for this purpose with respect to (a) quantitative performance measures such as predictive performance, (b) clinical interpretability, and (c) the effect of integrating prior expert knowledge.

METHODS

The Repeated Elastic Net Technique for Feature Selection (RENT) and the User-Guided Bayesian Framework for Feature Selection (UBayFS) are recently developed ensemble feature selectors investigated in this work. Both allow the user to identify informative features in datasets with low sample sizes and focus on model interpretability. While RENT is purely data-driven, UBayFS can integrate expert knowledge a priori in the feature selection process. In this work, we compare both feature selectors on a dataset comprising 63 patients and 110 features from multiple sources, including baseline patient characteristics, baseline blood values, tumor histology, imaging, and treatment information.

RESULTS

Our experiments involve data-driven and expert-driven setups, as well as combinations of both. In a five-fold cross-validated experiment without expert knowledge, our results demonstrate that both feature selectors allow accurate predictions: A reduction from 110 to approximately 20 features (around 82%) delivers near-optimal predictive performances with minor variations according to the choice of the feature selector, the predictive model, and the fold. Thereafter, we use findings from clinical literature as a source of expert knowledge. In addition, expert knowledge has a stabilizing effect on the feature set (an increase in stability of approximately 40%), while the impact on predictive performance is limited.

CONCLUSIONS

The features WHO Performance Status, Albumin, Platelets, Ki-67, Tumor Morphology, Total MTV, Total TLG, and SUVmax are the most stable and predictive features in our study. Overall, this study demonstrated the practical value of feature selection in medical applications not only to improve quantitative performance but also to deliver potentially new insights to experts.

Neuroendocrine Tumors: Genomics and Molecular Biomarkers with a Focus on Metastatic Disease

Neuroendocrine tumors (NETs) are considered rare tumors that originate from specialized endocrine cells. Patients often present with metastatic disease at the time of diagnosis, which negatively impacts their quality of life and overall survival. An understanding of the genetic mutations that drive these tumors and the biomarkers used to detect new NET cases is important to identify patients at an earlier disease stage. Elevations in CgA, synaptophysin, and 5-HIAA are most commonly used to identify NETs and assess prognosis; however, new advances in whole genome sequencing and multigenomic blood assays have allowed for a greater understanding of the drivers of NETs and more sensitive and specific tests to diagnose tumors and assess disease response. Treating NET liver metastases is important in managing hormonal or carcinoid symptoms and is imperative to improve patient survival. Treatment for liver-dominant disease is varied; delineating biomarkers that may predict response will allow for better patient stratification.

Molecular factors, diagnosis and management of gastrointestinal tract neuroendocrine tumors: An update

The prevalence of gastrointestinal neuroendocrine tumors (GI-NETs) is increasing, and despite recent advances in their therapy, it remains inadequate in patients with advanced well-differentiated neuroendocrine tumors. These tumors present many challenges concerning the molecular basis and genomic profile, pathophysiology, clinicopathological features, histopathologic classification, diagnosis and treatment. There has been an ongoing debate on diagnostic criteria and clinical behavior, and various changes have been made over the last few years. Neuroendocrine carcinoma of the gastrointestinal system is a rare but highly malignant neoplasm that is genetically distinct from gastrointestinal system neuroendocrine tumors (NETs). The diagnosis and management have changed over the past decade. Emerging novel biomarkers and metabolic players in cancer cells are useful and promising new diagnostic tools. Progress in positron emission tomography-computerized tomography and scintigraphy with new radioactive agents (⁶⁴Cu-DOTATATE or ⁶⁸Ga-DOTATATE) replacing enough octreoscan, has improved further the current diagnostic imaging. Promising results provide targeted therapies with biological agents, new drugs, chemotherapy and immunotherapy. However, the role of surgery is important, since it is the cornerstone of management. Simultaneous resection of small bowel NETs with synchronous liver metastases is a surgical challenge. Endoscopy offers novel options not only for diagnosis but also for interventional management. The therapeutic option should be individualized based on current multidisciplinary information.

Nuclear survivin is a prognosticator in gastroenteropancreatic neuroendocrine neoplasms: a meta-analysis

Purpose

Gastroenteropancreatic neuroendocrine neosplasms (GEP-NEN) are biologically heterogenous tumors with an increasing incidence over the past decades. Although efforts have been made in the treatment of these tumors, survival rates in metastasized tumor stages remain frustrating. Thus, there is an urgent need to identify novel targets as alternative treatment options. In this regard, the inhibitor of apoptosis protein (IAP) family member survivin could be such an attractive target. Therefore, aim of our meta-analysis was to assess the role of survivin as a biomarker and predictor in GEP-NEN.

Methods

Medline, Web of Science and Scopus were screened for studies that fulfilled our selection criteria. Quality assessement of the studies was based on design, methodology, generalizability and results analysis. Meta-analyses were conducted using a random-effects model and effect size measures were expressed as pooled Hazard Ratio (HR) or Odds Ratio (OR) with 95% Confidence Interval (CI).

Results

Six eligible studies with 649 patients (range 77–132) assessed survivin expression in GEP-NEN by immunohistochemistry. High expression levels of nuclear survivin in GEP-NEN correlated with a shorter overall survival (HR 3.10; 95% CI 2.15–4.47; p < 0.0001). In contrast to cytoplasmic survivin (OR 1.24; CI 0.59–2.57; p = 0.57), nuclear survivin was also associated (OR 15.23; CI 3.61–64.23; p = 0.0002) with G3/poorly differentiated GEP-NEN.

Conclusion

Nuclear Survivin is highly expressed in more aggressive G3 GEP-NEN and correlates with a poor outcome. Survivin is therefore an interesting molecule for a targeted therapy, especially for patients with highly proliferative G3 GEP-NENs.

Artificial Intelligence and Machine Learning in the Diagnosis and Management of Gastroenteropancreatic Neuroendocrine Neoplasms—A Scoping Review

Neuroendocrine neoplasms (NENs) and tumors (NETs) are rare neoplasms that may affect any part of the gastrointestinal system. In this scoping review, we attempt to map existing evidence on the role of artificial intelligence, machine learning and deep learning in the diagnosis and management of NENs of the gastrointestinal system. After implementation of inclusion and exclusion criteria, we retrieved 44 studies with 53 outcome analyses. We then classified the papers according to the type of studied NET (26 Pan-NETs, 59.1%; 3 metastatic liver NETs (6.8%), 2 small intestinal NETs, 4.5%; colorectal, rectal, non-specified gastroenteropancreatic and non-specified gastrointestinal NETs had from 1 study each, 2.3%). The most frequently used AI algorithms were Supporting Vector Classification/Machine (14 analyses, 29.8%), Convolutional Neural Network and Random Forest (10 analyses each, 21.3%), Random Forest (9 analyses, 19.1%), Logistic Regression (8 analyses, 17.0%), and Decision Tree (6 analyses, 12.8%). There was high heterogeneity on the description of the prediction model, structure of datasets, and performance metrics, whereas the majority of studies did not report any external validation set. Future studies should aim at incorporating a uniform structure in accordance with existing guidelines for purposes of reproducibility and research quality, which are prerequisites for integration into clinical practice.

Trametes robiniophila represses angiogenesis and tumor growth of lung cancer via strengthening let-7d-5p and targeting NAP1L1

Trametes robiniophila (Huaier) is available to refrain lung cancer (LC) cell progression, but its impact and mechanism on angiogenesis of LC are not proved. The study was to explore the potential mechanism of Huaier repressing angiogenesis and tumor growth in LC via strengthening let-7d-5p and targeting NAP1L1. Let-7d-5p and NAP1L1 expression was detected in LC tissues and cells (A549). Pretreatment of A549 cells was with Huaier. Transfection of changed let-7d-5p and NAP1L1 was to A549 cells to uncover their roles in LC cell progression with angiogenesis. Evaluation of the impact of let-7d-5p on angiogenesis in LC was in vitro in a mouse xenograft model. Identification of the targeting of let-7d-5p with NAP1L1 was clarified. The results clarified reduced let-7d-5p but elevated NAP1L1 were manifested in LC. Huaier restrained angiogenesis and tumor growth of LC in vivo and in vitro; Augmented let-7d-5p or declined NAP1L1 motivated the therapy of Huaier on LC; Let-7d-5p negatively modulated NAP1L1; Elevated NAP1L1 reversed the influence of enhancive let-7d-5p. These results strongly suggest that Huaier represses angiogenesis and tumor growth in LC via strengthening let-7d-5p and targeting NAP1L1. Huaier/let-7d-5p/NAP1L1 axis is supposed to be a promising target for the treatment of angiogenesis and tumor growth in LC via elevated let-7d-5p and targeted NAP1L1.

Artificial intelligence in small intestinal diseases: Application and prospects

The small intestine is located in the middle of the gastrointestinal tract, so small intestinal diseases are more difficult to diagnose than other gastrointestinal diseases. However, with the extensive application of artificial intelligence in the field of small intestinal diseases, with its efficient learning capacities and computational power, artificial intelligence plays an important role in the auxiliary diagnosis and prognosis prediction based on the capsule endoscopy and other examination methods, which improves the accuracy of diagnosis and prediction and reduces the workload of doctors. In this review, a comprehensive retrieval was performed on articles published up to October 2020 from PubMed and other databases. Thereby the application status of artificial intelligence in small intestinal diseases was systematically introduced, and the challenges and prospects in this field were also analyzed.

Nucleosome assembly protein 1-like 4, a new therapeutic target for proliferation and invasion of melanoma cells

BACKGROUND

Melanoma is one of the deadliest skin cancers. The treatment of advanced melanoma has been dramatically improved by immune checkpoint inhibitors and targeted therapies. However, many patients still do not respond to these therapies.

OBJECTIVE

To investigate whether NAP1L4 can be a new therapeutic target for melanoma.

METHODS

Immunohistochemical analysis of human nevus and melanoma tissues was performed. Real-time RT-PCR and immunoblotting were performed using human samples and melanoma cell lines. Next, we examined the effect of NAP1L4 knockdown in melanoma cell lines using cell migration and invasion assays. To investigate the molecular mechanism related to these results, immunoblotting of p21 and Slug was examined. MMP-2 and MMP-9 activity assays were also performed. Further, pathway analysis between NAP1L4 and MMP-2 was performed. Finally, the effects of NAP1L4 knockdown on cell proliferation, apoptosis, and cell cycle were analyzed.

RESULTS

NAP1L4 was overexpressed in melanoma tissues compared to the nevus tissue. NAP1L4 knockdown reduced melanoma cell migration and invasion. NAP1L4 knockdown upregulated p21 and downregulated Slug expression in melanoma cells. NAP1L4 knockdown decreased the active levels of MMP-2 in the supernatant from melanoma cells. NAP1L4 knockdown inhibited apoptosis in camptothecin-induced DNA damage, induced cell cycle arrest at the G1/S phase, and inhibited cell proliferation.

CONCLUSIONS

NAP1L4 may play a role in cell migration and invasion in melanoma cells through the regulation of Slug. We propose that NAP1L4 can be a new therapeutic target for proliferation and invasion of melanoma cells.

NAP1L1: A Novel Human Colorectal Cancer Biomarker Derived From Animal Models of Apc Inactivation

Introduction

Colorectal cancer (CRC) is the second leading cause of cancer death worldwide and most deaths result from metastases. We have analyzed animal models in which Apc, a gene that is frequently mutated during the early stages of colorectal carcinogenesis, was inactivated and human samples to try to identify novel potential biomarkers for CRC.

Materials and Methods

We initially compared the proteomic and transcriptomic profiles of the small intestinal epithelium of transgenic mice in which Apc and/or Myc had been inactivated. We then studied the mRNA and immunohistochemical expression of one protein that we identified to show altered expression following Apc inactivation, nucleosome assembly protein 1–like 1 (NAP1L1) in human CRC samples and performed a prognostic correlation between biomarker expression and survival in CRC patients.

Results

Nap1l1 mRNA expression was increased in mouse small intestine following Apc deletion in a Myc dependant manner and was also increased in human CRC samples. Immunohistochemical NAP1L1 expression was decreased in human CRC samples relative to matched adjacent normal colonic tissue. In a separate cohort of 75 CRC patients, we found a strong correlation between NAP1L1 nuclear expression and overall survival in those patients who had stage III and IV cancers.

Conclusion

NAP1L1 expression is increased in the mouse small intestine following Apc inactivation and its expression is also altered in human CRC. Immunohistochemical NAP1L1 nuclear expression correlated with overall survival in a cohort of CRC patients. Further studies are now required to clarify the role of this protein in CRC.

The clinical applications of a multigene liquid biopsy (NETest) in neuroendocrine tumors

PURPOSE

There are few effective biomarkers for neuroendocrine tumors. Precision oncology strategies have provided liquid biopsies for real-time and tailored decision-making. This has led to the development of the first neuroendocrine tumor liquid biopsy (the NETest). The NETest represents a transcriptomic signature of neuroendocrine tumor (NETs) that captures tumor biology and disease activity. The data have direct clinical application in terms of identifying residual disease, disease progress and the efficacy of treatment. In this overview we assess the available published information on the metrics and clinical efficacy of the NETest.

MATERIAL AND METHODS

Published data on the NETest have been collated and analyzed to understand the clinical application of this multianalyte biomarker in NETs.

RESULTS

NETest assay has been validated as a standardized and reproducible clinical laboratory measurement. It is not affected by demographic characteristics, or acid suppressive medication. Clinical utility of the NETest has been documented in gastroenteropancreatic, bronchopulmonary NETs, in paragangliomas and pheochromocytomas. The test facilitates accurate diagnosis of a NET disease, and real-time monitoring of the disease status (stable/progressive disease). It predicts aggressive tumor behavior, identifies operative tumor resection, and efficacy of the medical treatment (e.g. somatostatin analogues), or peptide receptor radionuclide therapy (PRRT). NETest metrics and clinical applications out-perform standard biomarkers like chromogranin A.

CONCLUSIONS

The NETest exhibits clinically competent metrics as an effective biomarker for neuroendocrine tumors. Measurement of NET transcripts in blood is a significant advance in neuroendocrine tumor management and demonstrates that blood provides a viable source to identify and monitor tumor status.

The molecular biology of pancreatic neuroendocrine neoplasms: Challenges and translational opportunities

Pancreatic neuroendocrine neoplasms (PanNENs) are rare, highly heterogeneous tumours. There have been significant recent advances in our knowledge of genomic events underlying their pathogenesis. However, treatment decisions remain largely based on tumour stage and grade which is inadequate, the current classification paradigm failing to capture the significant heterogeneity in tumour biology. There is a well-acknowledged unmet clinical need for novel biomarkers to enable individualised risk-adapted therapeutic strategies for PanNEN patients. Improvements in our understanding of the molecular biology of multiple solid tumours have led to the development of new biomarker assays and gene expression signatures to guide treatment decisions in other cancer types. A similar index for PanNENs, to improve patient prognostication and classification, would be highly clinically relevant and with advances in the field now seems potentially possible. This article will seek to review the molecular biology of PanNENs, the subtypes developed to date and the potential clinical opportunities these advances may afford.

NAP1L1 is a prognostic biomarker and contribute to doxorubicin chemotherapy resistance in human hepatocellular carcinoma

Background

Hepatocellular carcinoma (HCC) is one of the most fatal cancers, and its molecular basis needs to be delineated to identify biomarkers for its potential treatment. The purpose of this study was to identify a novel gene, nucleosome assembly proteins 1-like 1 protein (NAP1L1), associated with aggressive phenotypes of HCC.

Methods

Immunohistochemical staining was used to detect NAP1L1 protein expression in HCC tissues. The prognostic value of NAP1L1 expression was determined using Kaplan–Meier analysis and the Cox proportional hazards model. CCK-8 and apoptosis assays were used to detect the chemosensitivity in vitro. Xenograft tumor models were used to evaluate tumor cell proliferation and chemosensitivity in vivo.

Results

NAP1L1 expression was significantly upregulated in tumor tissues as compared to adjacent non-tumor tissues. High NAP1L1 expression in HCC tissues was associated with aggressive clinicopathologic features, such as serum AFP levels, tumor size and tumor number. Patients with high NAP1L1 expression had poor overall survival in our cohort and in the extra-validation cohort analyzed by TCGA microarray dataset and was further identified as an independent prognostic factor in HCC patients treated with radical resection. Both in vitro and in vivo assays showed that NAP1L1 promoted HCC cell proliferation and contribute to chemotherapy resistance. Further analyses found that some certain stemness associated genes were decreased concurrently with NAP1L1 down-regulation in HCC cell lines.

Conclusions

Our findings support that NAP1L1 is a prognostic biomarker and may contribute to chemotherapy resistance in human hepatocellular carcinoma.

Tracking knowledge evolution, hotspots and future directions of emerging technologies in cancers research: a bibliometrics review

Due to various environmental pollution issues, cancers have become the “first killer” of human beings in the 21st century and their control has become a global strategy of human health. The increasing development of emerging information technologies has provided opportunities for prevention, early detection, diagnosis, intervention, prognosis, nursing, and rehabilitation of cancers. In recent years, the literature associated with emerging technologies in cancer has grown rapidly, but few studies have used bibliometrics and a visualization approach to conduct deep mining and reveal a panorama of this field. To explore the dynamic knowledge evolution of emerging information technologies in cancer literature, we comprehensively analyzed the development status and research hotspots in this field from bibliometrics perspective. We collected 7,136 articles (2000-2017) from the Web of Science database and visually displayed the dynamic knowledge evolution process via the analysis on time-sequence changes, spatial distribution, knowledge base, and hotspots. Much institutional cooperation occurs in this field, and research groups are relatively concentrated. BMC Bioinformatics, PLOS One, Journal of Urology, Scientific Reports, and Bioinformatics are the top five journals in this field. Research hotspots are mainly concentrated in two dimensions: the disease dimension (e.g., cancer, breast cancer, and prostate cancer), and the technical dimension (e.g., robotics, machine learning, data mining, and etc.). The emerging technologies in cancer research is fast ascending and promising. This study also provides researchers with panoramic knowledge of this field, as well as research hotspots and future directions.

The use of Ki-67 labeling index to grade pulmonary well-differentiated neuroendocrine neoplasms: current best evidence

Although Ki-67 labeling index (Ki-67%) is not a diagnostic or grading criterion in the World Health Organization classification of pulmonary carcinoid tumor, oncologists often request this test. A survey was administered at a North American Society for Neuroendocrine Tumors meeting to understand how Ki-67% is used in oncologic practices. A systematic literature review was performed to gather best evidence regarding the use of Ki-67%. Consecutive pulmonary carcinoids were stratified into pulmonary typical carcinoids with Ki-67% <5% (group A, n = 187), typical carcinoids with Ki-67% ≥5% (group B, n = 38) and atypical carcinoids irrespective of Ki-67% (group C, n = 31). Overall survival, progression-free survival, recurrence proportions and time to recurrence were compared, by group, using the log-rank test, chi-square statistics and ANOVA, respectively. Our survey confirmed that Ki-67% is frequently used by specialists caring for these patients. Ki-67% of 1-7% significantly correlated with overall survival in the literature but we found no information about Ki-67% cut-off values that would accurately distinguish pulmonary typical from atypical carcinoids or estimate the prognosis of patients stratified by World Health Organization diagnosis and Ki-67% cut-off. Overall survival was significantly different in our 3 patient groups (p < 0.001), with survival probabilities decreasing from groups A to C. Progression-free survival was significantly longer in group A than B (p < 0.007). Our results support the concept that by combining World Health Organization diagnosis and Ki-67%, pulmonary carcinoids can be stratified into 3 grades: G1 (typical carcinoids with Ki-67% <5), G2 (typical carcinoids with Ki-67% ≥5%) and G3 (atypical carcinoids) with different prognoses.

The NETest: The Clinical Utility of Multigene Blood Analysis in the Diagnosis and Management of Neuroendocrine Tumors

The neuroendocrine neoplasms test (NETest) is a multianalyte liquid biopsy that measures neuroendocrine tumor gene expression in blood. This unique signature precisely defines the biological activity of an individual tumor in real time. The assay meets the 3 critical requirements of an optimal biomarker: diagnostic accuracy, prognostic value, and predictive therapeutic assessment. NETest performance metrics are sensitivity and specificity and in head-to-head comparison are 4-fold to 10-fold more accurate than chromogranin A. NETest accurately identifies completeness of surgery and response to somatostatin analogs. Clinical registry data demonstrate significant clinical utility in watch/wait programs.

Histone deacetylase inhibitor thailandepsin-A activates Notch signaling and suppresses neuroendocrine cancer cell growth in vivo

Novel therapies for neuroendocrine (NE) cancers are desperately needed as they frequently present as metastatic disease and cause debilitating symptoms by secreting excessive hormones. Induction of Notch isoforms has a tumor suppressive effect in NE cancer cell lines, and we have observed that histone deacetylase inhibitors (HDACi) potently activate Notch. In this study, we describe the potential for Burkholderia thailandensis-derived class I HDACi thailandepsin A (TDP-A) as a Notch activator and therapeutic agent against NE cancer. IC₅₀ for TDP-A was determined to be 4-6 nM in NE cancer cell lines (BON, MZ-CRC-1, and TT) without cytotoxicity to lung fibroblasts. The binding characteristics of TDP-A to its target HDAC1 was examined using bioluminescence resonance energy transfer (BRET). Western blot and flow cytometry analysis showed that TDP-A induces cell cycle arrest and apoptosis in a dose-dependent manner. TDP-A dose-dependently activated the Notch pathway as measured by increasing functional CBF1-luciferase reporter signal and mRNA and protein expressions of Notch isoforms, which were attenuated by pretreatment with γ-secretase inhibitor DAPT. Furthermore, TDP-A lead to changes in expression level of downstream targets of Notch pathway and reduced expression of NE cancer markers. An in vivo study demonstrated that TDP-A suppressed NE cancer progression. These results show that TDP-A, as a Notch activator, is a promising agent against NE cancers.

The clinical utility of circulating neuroendocrine gene transcript analysis in well-differentiated paragangliomas and pheochromocytomas

CONTEXT

Paragangliomas and pheochromocytomas (PPGLs) exhibit variable malignancy, which is difficult to determine by histopathology, amine measurements or tissue genetic analyses.

OBJECTIVE

To evaluate whether a 51-neuroendocrine gene blood analysis has clinical utility as a diagnostic and prognostic marker.

DESIGN

Prospective cohort study. Well-differentiated PPGLs (n = 32), metastatic (n = 4); SDHx mutation (n = 25); 12 biochemically active, Lanreotide treated (n = 4). Nine patients had multiple sampling. Age- and gender-matched controls and GEP-NETs (comparators).

METHODS

Circulating neuroendocrine tumor mRNA measured (qPCR) with multianalyte algorithmic analysis. Metabolic, epigenomic and proliferative genes as well as somatostatin receptor expression were assessed (averaged, normalized gene expression: mean ± s.e.m.). Amines were measured by HPLC and chromogranin A by ELISA. Analyses (2-tailed): Fisher's test, non-parametric (Mann-Whitney), receiver-operator curve (ROC) and multivariate analysis (MVA). All data are presented as mean ± s.e.m.

RESULTS

PPGL were NETest positive (100%). All exhibited higher scores than controls (55 ± 5% vs 8 ± 1%, P = 0.0001), similar to GEP-NETs (47 ± 5%). ROC analysis area under curve was 0.98 for differentiating PPGLs/controls (cut-off for normal: 26.7%). Mutation status was not directly linked to NETest. Genetic and molecular clustering was associated (P < 0.04) with NETest scores. Metastatic (80 ± 9%) and multicentric (64 ± 9%) disease had significantly (P < 0.04) higher scores than localized disease (43 ± 7%). Progressive disease (PD) had the highest scores (86 ± 2%) vs stable (SD, 41 ± 2%) (P < 0.0001). The area under the curve for PD from SD was 0.93 (cut-off for PD: 53%). Proliferation, epigenetic and somatostatin receptor gene expression was elevated (P < 0.03) in PD. Metabolic gene expression was decreased in SDHx mutations. Repeat NETest measurements defined clinical status in the 9 patients (6 SD and 3 PD). Amine measurement was non-informative. Multivariate analysis identified NETest >53% as an independent prognostic factor.

CONCLUSION

Circulating NET transcript analysis is positive (100% diagnostic) in well-differentiated PCC/PGL, scores were elevated in progressive disease irrespective of mutation or biochemical activity and elevated levels were prognostic.

A Delphic consensus assessment: imaging and biomarkers in gastroenteropancreatic neuroendocrine tumor disease management

The complexity of the clinical management of neuroendocrine neoplasia (NEN) is exacerbated by limitations in imaging modalities and a paucity of clinically useful biomarkers. Limitations in currently available imaging modalities reflect difficulties in measuring an intrinsically indolent disease, resolution inadequacies and inter-/intra-facility device variability and that RECIST (Response Evaluation Criteria in Solid Tumors) criteria are not optimal for NEN. Limitations of currently used biomarkers are that they are secretory biomarkers (chromogranin A, serotonin, neuron-specific enolase and pancreastatin); monoanalyte measurements; and lack sensitivity, specificity and predictive capacity. None of them meet the NIH metrics for clinical usage. A multinational, multidisciplinary Delphi consensus meeting of NEN experts (n = 33) assessed current imaging strategies and biomarkers in NEN management. Consensus (>75%) was achieved for 78% of the 142 questions. The panel concluded that morphological imaging has a diagnostic value. However, both imaging and current single-analyte biomarkers exhibit substantial limitations in measuring the disease status and predicting the therapeutic efficacy. RECIST remains suboptimal as a metric. A critical unmet need is the development of a clinico-biological tool to provide enhanced information regarding precise disease status and treatment response. The group considered that circulating RNA was better than current general NEN biomarkers and preliminary clinical data were considered promising. It was resolved that circulating multianalyte mRNA (NETest) had clinical utility in both diagnosis and monitoring disease status and therapeutic efficacy. Overall, it was concluded that a combination of tumor spatial and functional imaging with circulating transcripts (mRNA) would represent the future strategy for real-time monitoring of disease progress and therapeutic efficacy.

Blood and tissue neuroendocrine tumor gene cluster analysis correlate, define hallmarks and predict disease status

A multianalyte algorithmic assay (MAAA) identifies circulating neuroendocrine tumor (NET) transcripts (n=51) with a sensitivity/specificity of 98%/97%. We evaluated whether blood measurements correlated with tumor tissue transcript analysis. The latter were segregated into gene clusters (GC) that defined clinical 'hallmarks' of neoplasia. A MAAA/cluster integrated algorithm (CIA) was developed as a predictive activity index to define tumor behavior and outcome. We evaluated three groups. Group 1: publically available NET transcriptome databases (n=15; GeneProfiler). Group 2: prospectively collected tumors and matched blood samples (n=22; qRT-PCR). Group 3: prospective clinical blood samples, n=159: stable disease (SD): n=111 and progressive disease (PD): n=48. Regulatory network analysis, linear modeling, principal component analysis (PCA), and receiver operating characteristic analyses were used to delineate neoplasia 'hallmarks' and assess GC predictive utility. Our results demonstrated: group 1: NET transcriptomes identified (92%) genes elevated. Group 2: 98% genes elevated by qPCR (fold change >2, P<0.05). Correlation analysis of matched blood/tumor was highly significant (R(2)=0.7, P<0.0001), and 58% of genes defined nine omic clusters (SSTRome, proliferome, signalome, metabolome, secretome, epigenome, plurome, and apoptome). Group 3: six clusters (SSTRome, proliferome, metabolome, secretome, epigenome, and plurome) differentiated SD from PD (area under the curve (AUC)=0.81). Integration with blood-algorithm amplified the AUC to 0.92±0.02 for differentiating PD and SD. The CIA defined a significantly lower SD score (34.1±2.6%) than in PD (84±2.8%, P<0.0001). In conclusion, circulating transcripts measurements reflect NET tissue values. Integration of biologically relevant GC differentiate SD from PD. Combination of GC data with the blood-algorithm predicted disease status in >92%. Blood transcript measurement predicts NET activity.

Decoding the Molecular and Mutational Ambiguities of Gastroenteropancreatic Neuroendocrine Neoplasm Pathobiology

Gastroenteropancreatic neuroendocrine neoplasms (GEP-NEN), considered a heterogeneous neoplasia, exhibit ill-defined pathobiology and protean symptomatology and are ubiquitous in location. They are difficult to diagnose, challenging to manage, and outcome depends on cell type, secretory product, histopathologic grading, and organ of origin. A morphologic and molecular genomic review of these lesions highlights tumor characteristics that can be used clinically, such as somatostatin-receptor expression, and confirms features that set them outside the standard neoplasia paradigm. Their unique pathobiology is useful for developing diagnostics using somatostatin-receptor targeted imaging or uptake of radiolabeled amino acids specific to secretory products or metabolism. Therapy has evolved via targeting of protein kinase B signaling or somatostatin receptors with drugs or isotopes (peptide-receptor radiotherapy). With DNA sequencing, rarely identified activating mutations confirm that tumor suppressor genes are relevant. Genomic approaches focusing on cancer-associated genes and signaling pathways likely will remain uninformative. Their uniquely dissimilar molecular profiles mean individual tumors are unlikely to be easily or uniformly targeted by therapeutics currently linked to standard cancer genetic paradigms. The prevalence of menin mutations in pancreatic NEN and P27^KIP1 mutations in small intestinal NEN represents initial steps to identifying a regulatory commonality in GEP-NEN. Transcriptional profiling and network-based analyses may define the cellular toolkit. Multianalyte diagnostic tools facilitate more accurate molecular pathologic delineations of NEN for assessing prognosis and identifying strategies for individualized patient treatment. GEP-NEN remain unique, poorly understood entities, and insight into their pathobiology and molecular mechanisms of growth and metastasis will help identify the diagnostic and therapeutic weaknesses of this neoplasia.

Molecular functions and significance of the MTA family in hormone-independent cancer

The members of the metastasis-associated protein (MTA) family play pivotal roles in both physiological and pathophysiological processes, especially in cancer development and metastasis, and their role as master regulators has come to light. Due to the fact that they were first identified as crucial factors in estrogen receptor-mediated breast cancer metastasis, most of the early studies focused on their hormone-dependent functions. However, the accumulating evidence shows that the members of MTA family are deregulated in most, if not all, the cancers studied so far. Therefore, the levels as well as the activities of the MTA family members are widely accepted as potential biomarkers for diagnosis, prognosis, and predictors of overall survival. They function differently in different cancers with specific mechanisms. p53 and HIF-1α appear to be the respectively common upstream and downstream regulator of the MTA family in both development and metastasis of a wide spectrum of cancers. Here, we review the expression and clinical significance of the MTA family, focusing on hormone-independent cancers. To illustrate the molecular mechanisms, we analyze the MTA family-related signaling pathways in different cancers. Finally, targeting the MTA family directly or the pathways involved in the MTA family indirectly could be invaluable strategies in the development of cancer therapeutics.

Gene network-based analysis identifies two potential subtypes of small intestinal neuroendocrine tumors

BACKGROUND

Tumor transcriptomes contain information of critical value to understanding the different capacities of a cell at both a physiological and pathological level. In terms of clinical relevance, they provide information regarding the cellular "toolbox" e.g., pathways associated with malignancy and metastasis or drug dependency. Exploration of this resource can therefore be leveraged as a translational tool to better manage and assess neoplastic behavior. The availability of public genome-wide expression datasets, provide an opportunity to reassess neuroendocrine tumors at a more fundamental level. We hypothesized that stringent analysis of expression profiles as well as regulatory networks of the neoplastic cell would provide novel information that facilitates further delineation of the genomic basis of small intestinal neuroendocrine tumors.

RESULTS

We re-analyzed two publically available small intestinal tumor transcriptomes using stringent quality control parameters and network-based approaches and validated expression of core secretory regulatory elements e.g., CPE, PCSK1, secretogranins, including genes involved in depolarization e.g., SCN3A, as well as transcription factors associated with neurodevelopment (NKX2-2, NeuroD1, INSM1) and glucose homeostasis (APLP1). The candidate metastasis-associated transcription factor, ST18, was highly expressed (>14-fold, p < 0.004). Genes previously associated with neoplasia, CEBPA and SDHD, were decreased in expression (-1.5 - -2, p < 0.02). Genomic interrogation indicated that intestinal tumors may consist of two different subtypes, serotonin-producing neoplasms and serotonin/substance P/tachykinin lesions. QPCR validation in an independent dataset (n = 13 neuroendocrine tumors), confirmed up-regulated expression of 87% of genes (13/15).

CONCLUSIONS

An integrated cellular transcriptomic analysis of small intestinal neuroendocrine tumors identified that they are regulated at a developmental level, have key activation of hypoxic pathways (a known regulator of malignant stem cell phenotypes) as well as activation of genes involved in apoptosis and proliferation. Further refinement of these analyses by RNAseq studies of large-scale databases will enable definition of individual master regulators and facilitate the development of novel tissue and blood-based tools to better understand diagnose and treat tumors.

Constitutive patterns of gene expression regulated by RNA-binding proteins

Background

RNA-binding proteins regulate a number of cellular processes, including synthesis, folding, translocation, assembly and clearance of RNAs. Recent studies have reported that an unexpectedly large number of proteins are able to interact with RNA, but the partners of many RNA-binding proteins are still uncharacterized.

Results

We combined prediction of ribonucleoprotein interactions, based on catRAPID calculations, with analysis of protein and RNA expression profiles from human tissues. We found strong interaction propensities for both positively and negatively correlated expression patterns. Our integration of in silico and ex vivo data unraveled two major types of protein–RNA interactions, with positively correlated patterns related to cell cycle control and negatively correlated patterns related to survival, growth and differentiation. To facilitate the investigation of protein–RNA interactions and expression networks, we developed the catRAPID express web server.

Conclusions

Our analysis sheds light on the role of RNA-binding proteins in regulating proliferation and differentiation processes, and we provide a data exploration tool to aid future experimental studies.

Diagnosis and prediction of neuroendocrine liver metastases: a protocol of six systematic reviews

Background

Patients with hepatic metastases from neuroendocrine tumors (NETs) benefit from an early diagnosis, which is crucial for the optimal therapy and management. Diagnostic procedures include morphological and functional imaging, identification of biomarkers, and biopsy.

Objective

The aim of six systematic reviews discussed in this study is to assess the predictive value of Ki67 index and other biomarkers, to compare the diagnostic accuracy of morphological and functional imaging, and to define the role of biopsy in the diagnosis and prediction of neuroendocrine tumor liver metastases.

Methods

An objective group of librarians will provide an electronic search strategy to examine the following databases: MEDLINE, EMBASE and The Cochrane Library (Cochrane Database of Systematic Reviews, Cochrane Central Register of Controlled Trials (CENTRAL), Database of Abstracts of Reviews of Effects). There will be no restriction concerning language and publication date. The qualitative and quantitative synthesis of the systematic review will be conducted with randomized controlled trials (RCT), prospective and retrospective comparative cohort studies, and case-control studies. Case series will be collected in a separate database and only used for descriptive purposes.

Results

This study is ongoing and presents a protocol of six systematic reviews to elucidate the role of histopathological and biochemical markers, biopsies of the primary tumor and the metastases as well as morphological and functional imaging modalities for the diagnosis and prediction of neuroendocrine liver metastases.

Conclusions

These systematic reviews will assess the value and accuracy of several diagnostic modalities in patients with NET liver metastases, and will provide a basis for the development of clinical practice guidelines.

Trial Registration

The systematic reviews have been prospectively registered with the International Prospective Register of Systematic Reviews (PROSPERO): CRD42012002644; http://www.metaxis.com/prospero/full_doc.asp?RecordID=2644 (Archived by WebCite at http://www.webcitation.org/6LzCLd5sF), CRD42012002647; http://www.metaxis.com/prospero/full_doc.asp?RecordID=2647 (Archived by WebCite at http://www.webcitation.org/6LzCRnZnO), CRD42012002648; http://www.metaxis.com/prospero/full_doc.asp?RecordID=2648 (Archived by WebCite at http://www.webcitation.org/6LzCVeuVR), CRD42012002649; http://www.metaxis.com/prospero/full_doc.asp?RecordID=2649 (Archived by WebCite at http://www.webcitation.org/6LzCZzZWU), CRD42012002650; http://www.metaxis.com/prospero/full_doc.asp?RecordID=2650 (Archived by WebCite at http://www.webcitation.org/6LzDPhGb8), CRD42012002651; http://www.crd.york.ac.uk/PROSPERO/display_record.asp?ID=CRD42012002651#.UrMglPRDuVo (Archived by WebCite at http://www.webcitation.org/6LzClCNff).

Chromogranin A and its fragments as regulators of small intestinal neuroendocrine neoplasm proliferation

INTRODUCTION

Chromogranin A is a neuroendocrine secretory product and its loss is a feature of malignant NEN de-differentiation. We hypothesized that chromogranin A fragments were differentially expressed during NEN metastasis and played a role in the regulation of NEN proliferation.

METHODS

Chromogranin A mRNA (PCR) and protein (ELISA/western blot) were studied in 10 normal human mucosa, 5 enterochromaffin cell preparations, 26 small intestinal NEN primaries and 9 liver metastases. Cell viability (WST-1 assay), proliferation (bromodeoxyuridine ELISA) and expression of AKT/AKT-P (CASE ELISA/western blot) in response to chromogranin A silencing, inhibition of prohormone convertase and mTOR inhibition (RAD001/AKT antisense) as well as different chromogranin A fragments were examined in 4 SI-NEN cell lines.

RESULTS

Chromogranin A mRNA and protein levels were increased (37-340 fold, p<0.0001) in small intestinal NENs compared to normal enterochromaffin cells. Western blot identified chromogranin A-associated processing bands including vasostatin in small intestinal NENs as well as up-regulated expression of prohormone convertase in metastases. Proliferation in small intestinal NEN cell lines was decreased by silencing chromogranin A as well as by inhibition of prohormone convertase (p<0.05). This inhibition also decreased secretion of chromogranin A (p<0.05) and 5-HT (p<0.05) as well as expression of vasostatin. Metastatic small intestinal NEN cell lines were stimulated (50-80%, p<0.05) and AKT phosphorylated (Ser473: p<0.05) by vasostatin I, which was completely reversed by RAD001 (p<0.01) and AKT antisense (p<0.05) while chromostatin inhibited proliferation (~50%, p<0.05).

CONCLUSION

Chromogranin A was differentially regulated in primary and metastatic small intestinal NENs and cell lines. Chromogranin A fragments regulated metastatic small intestinal NEN proliferation via the AKT pathway indicating that CgA plays a far more complex role in the biology of these tumors than previously considered.

Rare neuroendocrine tumours: results of the surveillance of rare cancers in Europe project

Because of the low incidence, and limited opportunities for large patient volume experiences, there are very few relevant studies of neuroendocrine tumours (NETs). A large population-based database (including cancer patients diagnosed from 1978 to 2002 and registered in 76 population-based cancer registries [CRs]), provided by the project 'surveillance of rare cancers in Europe' (RARECARE) is used to describe the basic indicators of incidence, prevalence and survival of NETs, giving a unique overview on the burden of NETs in Europe. NETs at all cancer sites, excluding lung, were analysed in this study. In total over 20,000 incident cases of NETs were analysed and a data quality check upon specific NETs was performed. The overall incidence rate for NETs was 25/1,000,000 and was highest in patients aged 65 years and older with well differentiated endocrine carcinomas (non-functioning pancreatic and gastrointestinal) (40 per 1,000,000). We estimated that slightly more than 100,000 people were diagnosed with NETs and still alive in EU27 at the beginning of 2008. Overall, NETs had a 5 year relative survival of 50%; survival was low (12%) for poorly differentiated endocrine carcinoma, and relatively high (64%) for well differentiated carcinoma (not functioning of the pancreas and digestive organs). Within NETs, endocrine carcinoma of thyroid gland had the best 5-year relative survival (82%). Because of the complexity and number of the different disciplines involved with NETs (as they arise in many organs), a multidisciplinary approach delivered in highly qualified reference centres and an international network between those centres is recommended.

The identification of gut neuroendocrine tumor disease by multiple synchronous transcript analysis in blood

Gastroenteropancreatic (GEP) neuroendocrine neoplasms (NENs) are increasing in both incidence and prevalence. A delay in correct diagnosis is common for these lesions. This reflects the absence of specific blood biomarkers to detect NENs. Measurement of the neuroendocrine secretory peptide Chromogranin A (CgA) is used, but is a single value, is non-specific and assay data are highly variable. To facilitate tumor detection, we developed a multi-transcript molecular signature for PCR-based blood analysis. NEN transcripts were identified by computational analysis of 3 microarray datasets: NEN tissue (n = 15), NEN peripheral blood (n = 7), and adenocarcinoma (n = 363 tumors). The candidate gene signature was examined in 130 blood samples (NENs: n = 63) and validated in two independent sets (Set 1 [n = 115, NENs: n = 72]; Set 2 [n = 120, NENs: n = 58]). Comparison with CgA (ELISA) was undertaken in 176 samples (NENs: n = 81). 51 significantly elevated transcript markers were identified. Gene-based classifiers detected NENs in independent sets with high sensitivity (85–98%), specificity (93–97%), PPV (95–96%) and NPV (87–98%). The AUC for the NEN gene-based classifiers was 0.95–0.98 compared to 0.64 for CgA (Z-statistic 6.97–11.42, p<0.0001). Overall, the gene-based classifier was significantly (χ² = 12.3, p<0.0005) more accurate than CgA. In a sub-analysis, pancreatic NENs and gastrointestinal NENs could be identified with similar efficacy (79–88% sensitivity, 94% specificity), as could metastases (85%). In patients with low CgA, 91% exhibited elevated transcript markers. A panel of 51 marker genes differentiates NENs from controls with a high PPV and NPV (>90%), identifies pancreatic and gastrointestinal NENs with similar efficacy, and confirms GEP-NENs when CgA levels are low. The panel is significantly more accurate than the CgA assay. This reflects its utility to identify multiple diverse biological components of NENs. Application of this sensitive and specific PCR-based blood test to NENs will allow accurate detection of disease, and potentially define disease progress enabling monitoring of treatment efficacy.

Neuroendocrine phenotype alteration and growth suppression through apoptosis by MK-2206, an allosteric inhibitor of AKT, in carcinoid cell lines in vitro

Carcinoids are neuroendocrine malignancies characterized by their overproduction of various bioactive hormones that lead to the carcinoid syndrome. We have shown previously that AKT serves as a key regulator of growth and phenotypic expression of tumor markers in carcinoids by the genetic depletion of AKT expression. However, no small-molecule inhibitor of AKT kinase activity has been developed until recently. MK-2206, a novel allosteric inhibitor of AKT, is currently undergoing clinical trials for the treatment of solid tumors. In this study, we explored the effect of MK-2206 on carcinoid cell proliferation and bioactive hormone production in vitro in two carcinoid cell lines - pancreatic carcinoid BON and bronchopulmonary H727. Treatment with MK-2206 effectively suppressed AKT phosphorylation at serine 473 and significantly reduced cell proliferation in a dose-dependent manner. Most importantly, MK-2206 treatment resulted in a significant reduction in ASCL1, CgA, and NSE expression, collectively recognized as markers of neuroendocrine tumor malignancy. Furthermore, MK-2206-treated cells showed an increase in levels of cleaved PARP and cleaved caspase-3, with a concomitant reduction in levels of Mcl-1 and XIAP, indicating that the antiproliferative effect of MK-2206 occurs through the induction of apoptosis. In conclusion, MK-2206 suppresses carcinoid tumor growth, and alters its neuroendocrine phenotype, indicating that this drug may be beneficial for patients with carcinoid syndrome. These studies merit further clinical investigation.

Knockdown of nucleosome assembly protein 1-like 1 promotes dimethyl sulfoxide-induced differentiation of P19CL6 cells into cardiomyocytes

Transplantation of cardiomyocytes derived from stem cells is a promising option for cardiac repair. However, how to obtain efficient cardiomyocytes from stem cells is still a great challenge. Understanding of the mechanism that regulates the cardiac differentiation of stem cells is necessary for the effective induction of cardiomyocytes. A clonal derivative named P19CL6 cells can easily differentiate into cardiomyocytes with 1% dimethyl sulfoxide (DMSO) treatment, which offers a valuable model to study cardiomyocytes differentiation in vitro. In this study, the isobaric tags for relative and absolute quantitation (iTRAQ) proteomics were performed to identify proteins associated with cardiomyocytes differentiation of P19CL6 cells induced by DMSO. Out of 543 non-redundant proteins identified, 207 proteins showed significant changes during differentiation with ≥1.2-fold or ≤0.83-fold changes cut-offs. Nine proteins were confirmed by the quantitative real-time polymerase chain reaction (qRT-PCR) and Western blot analysis respectively. Notably, broad consistency was well showed between mRNA and protein expression for down-regulation of nucleosome assembly protein 1-like 1 (Nap1l1). Further study revealed that knockdown of Nap1l1 by stable transfection of shRNA vector significantly accelerated DMSO-induced cardiomyocytes differentiation of P19CL6 cells characterized by increases in expression of cardiac specific transcription factors, genes, and proteins (GATA4, MEF-2C, ANP, BNP, cTNT, and β-MHC). Therefore, Nap1l1 is a novel protein that regulates cardiomyocytes differentiation of P19CL6 cells induced by DMSO.

Assessment of reproducibility of cancer survival risk predictions across medical centers

BACKGROUND

Two most important considerations in evaluation of survival prediction models are 1) predictability - ability to predict survival risks accurately and 2) reproducibility - ability to generalize to predict samples generated from different studies. We present approaches for assessment of reproducibility of survival risk score predictions across medical centers.

METHODS

Reproducibility was evaluated in terms of consistency and transferability. Consistency is the agreement of risk scores predicted between two centers. Transferability from one center to another center is the agreement of the risk scores of the second center predicted by each of the two centers. The transferability can be: 1) model transferability - whether a predictive model developed from one center can be applied to predict the samples generated from other centers and 2) signature transferability - whether signature markers of a predictive model developed from one center can be applied to predict the samples from other centers. We considered eight prediction models, including two clinical models, two gene expression models, and their combinations. Predictive performance of the eight models was evaluated by several common measures. Correlation coefficients between predicted risk scores of different centers were computed to assess reproducibility - consistency and transferability.

RESULTS

Two public datasets, the lung cancer data generated from four medical centers and colon cancer data generated from two medical centers, were analyzed. The risk score estimates for lung cancer patients predicted by three of four centers agree reasonably well. In general, a good prediction model showed better cross-center consistency and transferability. The risk scores for the colon cancer patients from one (Moffitt) medical center that were predicted by the clinical models developed from the another (Vanderbilt) medical center were shown to have excellent model transferability and signature transferability.

CONCLUSIONS

This study illustrates an analytical approach to assessing reproducibility of predictive models and signatures. Based on the analyses of the two cancer datasets, we conclude that the models with clinical variables appear to perform reasonable well with high degree of consistency and transferability. There should have more investigations on the reproducibility of prediction models including gene expression data across studies.

EGFR/TGFα and TGFβ/CTGF Signaling in Neuroendocrine Neoplasia: Theoretical Therapeutic Targets

Neuroendocrine neoplasms (NENs) are a heterogeneous family of malignancies whose proliferation is partially dependent on growth factors secreted by the microenvironment and the tumor itself. Growth factors which were demonstrated to be important in experimental models of NENs include EGF (epidermal growth factor), TGF (transforming growth factor) α, TGFβ and CTGF (connective tissue growth factor). EGF and TGFα bind to the EGF receptor to stimulate an intact RAS/RAF/MAPK pathway, leading to the transcription of genes associated with cell proliferation, invasion and metastasis. Theoretically, TGFα stimulation can be inhibited at several points of the MAPK pathway, but success is limited to NEN models and is not evident in the clinical setting. TGFβ1 stimulates TGFβ receptors (TGFβRI and TGFβRII) resulting in inhibition of neuroendocrine cell growth through SMAD-mediated activation of the growth inhibitor P21(WAF1/CIP1). Although some NENs are inhibited by TGFβ1, paradoxical growth is seen in experimental models of gastric and small intestinal (SI) NENs. Therapeutic targeting of TGFβ1 in NENs is therefore complicated by uncertainty of the effect of TGFβ1 secretion on the direction of proliferative regulation. CTGF expression is associated with more malignant clinical phenotypes in a variety of cancers, including NENs. CTGF promotes growth in gastric and SI-NEN models, and is implicated as a mediator of local and distant fibrosis caused by NENs of enterochromaffin cell origin. CTGF inhibitors are available, but their anti-proliferative effect has not been tested in NENs. In summary, growth factors are essential for NEN proliferation, and although interventions targeting these proteins are effective in experimental models, only limited clinical efficacy has been identified.

Improving the diagnosis and management of neuroendocrine tumors: utilizing new advances in biomarker and molecular imaging science

Neuroendocrine tumors (NET) are malignant solid tumors that arise in hormone-secreting tissue of the diffuse neuroendocrine system or endocrine glands. Although traditionally understood to be a rare disease, the incidence and prevalence of NET have increased greatly in the past 3 decades. However, during this time, progress in diagnosis and outcome of NET has generally been modest. In order to achieve improved outcome in NET, a better understanding of NET biology combined with more reliable serum markers and better techniques to identify tumor localization and small lesions are needed. Although some NET biomarkers exist, sensitive and specific markers that predict tumor growth and behavior are generally lacking. In addition, the integration of new molecular imaging technologies in patient diagnosis and follow-up has the potential to enhance care. To discuss developments and issues required to improve diagnostics and management of NET patients, with specific focus on the latest advances in molecular imaging and biomarker science, 17 global leaders in the fields of NET, molecular imaging and biomarker technology gathered to participate in a 2-day meeting hosted by Prof. Kjell Öberg at the University of Uppsala in Sweden. During this time, findings were presented regarding methods with potential prognostic and treatment applications in NET or other types of cancers. This paper describes the symposium presentations and resulting discussions.

Neuroendocrine tumor disease: an evolving landscape

Gastroenteropancreatic neuroendocrine neoplasms (GEP-NENs) represent a heterogenous group of tumors arising from a variety of neuroendocrine cell types. The incidence and prevalence of GEP-NENs have markedly increased over the last three decades. Symptoms are often absent in early disease, or vague and nonspecific even in advanced disease. Delayed diagnosis is thus common. Chromogranin A is the most commonly used biomarker but has limitations as does the proliferative marker Ki-67%, which is often used for tumor grading and determination of therapy. The development of a multidimensional prognostic nomogram may be valuable in predicting tumor behavior and guiding therapy but requires validation. Identification of NENs that express somatostatin receptors (SSTR) allows for SSTR scintigraphy and positron emission tomography imaging using novel radiolabeled compounds. Complete surgical resection of limited disease or endoscopic ablation of small lesions localized in stomach or rectum can provide cure; however, the majority of GEP-NENs are metastatic (most frequently the liver and/or mesenteric lymph nodes) at diagnosis. Selected patients with metastatic disease may benefit from advanced surgical techniques including hepatic resection or liver transplantation. Somatostatin analogs are effective for symptomatic treatment and exhibit some degree of antiproliferative activity in small intestinal NENs. There is a place for streptozotocin, temozolomide, and capecitabine in the management of pancreatic NENs, while new agents targeting either mTOR (everolimus) or angiogenic (sunitinib) pathways have shown efficacy in these lesions.

Assessment of performance of survival prediction models for cancer prognosis

BACKGROUND

Cancer survival studies are commonly analyzed using survival-time prediction models for cancer prognosis. A number of different performance metrics are used to ascertain the concordance between the predicted risk score of each patient and the actual survival time, but these metrics can sometimes conflict. Alternatively, patients are sometimes divided into two classes according to a survival-time threshold, and binary classifiers are applied to predict each patient's class. Although this approach has several drawbacks, it does provide natural performance metrics such as positive and negative predictive values to enable unambiguous assessments.

METHODS

We compare the survival-time prediction and survival-time threshold approaches to analyzing cancer survival studies. We review and compare common performance metrics for the two approaches. We present new randomization tests and cross-validation methods to enable unambiguous statistical inferences for several performance metrics used with the survival-time prediction approach. We consider five survival prediction models consisting of one clinical model, two gene expression models, and two models from combinations of clinical and gene expression models.

RESULTS

A public breast cancer dataset was used to compare several performance metrics using five prediction models. 1) For some prediction models, the hazard ratio from fitting a Cox proportional hazards model was significant, but the two-group comparison was insignificant, and vice versa. 2) The randomization test and cross-validation were generally consistent with the p-values obtained from the standard performance metrics. 3) Binary classifiers highly depended on how the risk groups were defined; a slight change of the survival threshold for assignment of classes led to very different prediction results.

CONCLUSIONS

1) Different performance metrics for evaluation of a survival prediction model may give different conclusions in its discriminatory ability. 2) Evaluation using a high-risk versus low-risk group comparison depends on the selected risk-score threshold; a plot of p-values from all possible thresholds can show the sensitivity of the threshold selection. 3) A randomization test of the significance of Somers' rank correlation can be used for further evaluation of performance of a prediction model. 4) The cross-validated power of survival prediction models decreases as the training and test sets become less balanced.

The biological hallmarks of ileal carcinoids

Endocrine tumours derived from the small intestine, ileal carcinoids, produce and secrete the hormones tachykinins and serotonin, which induces the specific symptoms related to the tumour. Because of their low proliferation rate, they are often discovered at late stages when metastases have occurred. The biology that characterizes these tumours differs in many ways from what is generally recognized for other malignancies. In this overview, the current knowledge on the development and progression of ileal carcinoids is described.

The impact of incidental identification on the stage at presentation of lower gastrointestinal carcinoids

BACKGROUND

Over the past 3 decades, there has been a significant increase in the incidence of gastrointestinal carcinoid tumors in the United States. Incidentally discovered carcinoids in the lower gastrointestinal tract have probably contributed to this increase. In this study we aimed to compare the clinicopathologic characteristics of incidentally discovered carcinoids of the small and large bowel with those identified as a result of symptoms.

STUDY DESIGN

We performed a retrospective review of 58 consecutive patients with nonappendiceal gastrointestinal carcinoids: 30 small bowel and 28 large bowel. We compared asymptomatic patients with lower gastrointestinal tract carcinoids identified by routine colonoscopy with those identified as a result of symptoms.

RESULTS

Twenty-eight (48.3%) incidentally identified carcinoids (15 small bowel and 13 large bowel) were compared with 30 (51.7%) symptomatic carcinoids. Incidental ileal carcinoids were similar in size (mean ± SD, 1.3 ± 0.61 vs 1.7 ± 1.13, p = 0.45) and incidence of lymph node metastases (12 in 15 vs 9 in 15, p = 0.43) to symptomatic ileal carcinoids. However, incidental ileal carcinoids had a lower incidence of distant metastases (1 in 15 vs 7 in 15, p = 0.035) compared with symptomatic ileal carcinoids. There was no difference in tumor size, extent of lymph node metastases, or distant metastases between incidental and symptomatic large bowel carcinoids.

CONCLUSIONS

Ileal carcinoids identified at screening colonoscopy are associated with a significantly decreased incidence of distant metastases compared with those identified after development of symptoms, despite similar size and extent of lymph node metastases. However, incidental large bowel carcinoids appear to have similar staging to those identified as a result of symptoms.

Small intestinal neuroendocrine cell pathobiology: 'carcinoid' tumors

PURPOSE OF REVIEW

Neuroendocrine tumors, particularly small intestinal tumors, also grouped as 'carcinoids', are defined by an increasing incidence and prevalence, a poor response to current therapies, and confusion regarding appropriate models for drug development. Despite these issues, approximately 350 studies were published in the last year.

RECENT FINDINGS

Two sources of confusion are clearly apparent. First, pharmacotherapeutic studies using pancreatic tumor cell lines as models for small intestinal or 'carcinoid' tumor biology are considered appropriate. Second, there is continued inclusion and analysis of pancreatic endocrine tumors with small intestinal neuroendocrine tumors in clinical studies. One highlight of this year is additional data confirming the significant differences between pancreatic tumor cell lines and small intestinal cell lines, the different gene expressions, for example, PAX8, between these two tumor types, and the observations that these two tumors respond differently in clinical trials, for example, to mammalian target of rapamycin (mTOR) inhibitors. Other highlights include delineating the role of the tumor microenvironment in the development of fibrosis and developing a minimum pathology dataset and a prognostic nomogram that may have utility in stratifying patients for clinical studies.

SUMMARY

A number of interesting studies have been published during 2009-2010, but critical areas remain that require resolution. Current data, for the most part, reflect amplification of previously held concepts with modest advances in novel information.

Neuroendocrine tumors in children and young adults: rare or not so rare

This review focuses on neuroendocrine tumors (NETs) that arise in the diffuse neuroendocrine system; these rare tumors can develop in any organ that has dispersed single endocrine cells, for example, the intestine, or in an organ that has clusters of endocrine cells, for example, pancreatic islets. Previously considered benign, NETs are now recognized to recur locally or metastasize to liver and bone if not completely excised early in their course of development. This article summarizes the epidemiology and reviews the diagnostic and therapeutic challenges of NETs in children and youth, noting especially those NETs that are more prevalent in young people than in older adults.

Paraneoplastic antigen Ma2 autoantibodies as specific blood biomarkers for detection of early recurrence of small intestine neuroendocrine tumors

Background

Small intestine neuroendocrine tumors (SI-NETs) belong to a rare group of cancers. Most patients have developed metastatic disease at the time of diagnosis, for which there is currently no cure. The delay in diagnosis is a major issue in the clinical management of the patients and new markers are urgently needed. We have previously identified paraneoplastic antigen Ma2 (PNMA2) as a novel SI-NET tissue biomarker. Therefore, we evaluated whether Ma2 autoantibodies detection in the blood stream is useful for the clinical diagnosis and recurrence of SI-NETs.

Methodology/Principal Findings

A novel indirect ELISA was set up to detect Ma2 autoantibodies in blood samples of patients with SI-NET at different stages of disease. The analysis was extended to include typical and atypical lung carcinoids (TLC and ALC), to evaluate whether Ma2 autoantibodies in the blood stream become a general biomarker for NETs. In total, 124 blood samples of SI-NET patients at different stages of disease were included in the study. The novel Ma2 autoantibody ELISA showed high sensitivity, specificity and accuracy with ROC curve analysis underlying an area between 0.734 and 0.816. Ma2 autoantibodies in the blood from SI-NET patients were verified by western blot and sequential immunoprecipitation. Serum antibodies of patients stain Ma2 in the tumor tissue and neurons. We observed that SI-NET patients expressing Ma2 autoantibody levels below the cutoff had a longer progression and recurrence-free survival compared to those with higher titer. We also detected higher levels of Ma2 autoantibodies in blood samples from TLC and ALC patients than from healthy controls, as previously shown in small cell lung carcinoma samples.

Conclusion

Here we show that high Ma2 autoantibody titer in the blood of SI-NET patients is a sensitive and specific biomarker, superior to chromogranin A (CgA) for the risk of recurrence after radical operation of these tumors.

Differential gene expression profile of MAGE family in taiwanese patients with colorectal cancer

BACKGROUND

The melanoma-associated antigen (MAGE) gene family consists of different expression patterns in various tumor types. They are considered tumor-specific antigens and are ideal targets for cancer immunotherapy. The purpose of this study is to identify the expression profiles of the MAGE family genes in Taiwanese colorectal cancer patients.

METHODS

In this study, a well-constructed chip array platform was used to analyze the expression of the MAGE family genes of 100 colorectal cancer tissues. Statistical analysis of the experimental results and patients' clinical manifestations were also conducted.

RESULTS

The results showed MAGE-A2 (87%), -A7 (83%), -A8 (75%), -A12 (71%), -B2 (75%), -B3 (79%), -D2 (75%), -F1 (79%), and -H1 (70%) were significantly overexpressed genes in colorectal cancer tissues. MAGE-A2 was the most highly overexpressed gene among the MAGE family. MAGE-B3 gene expression is statistically correlated with tumor size, lymph node, and UICC stage. In addition, the overexpression of MAGE-D2 and -H1 genes are statistically correlated to the tumor size and depth, respectively (P < 0.05).

CONCLUSIONS

This is the first comprehensive report to clarify the differential expression profile of whole MAGE family in CRCs, and it might provide some crucial information about the carcinogenesis and progression in Taiwanese patients with CRC.

Pathology reporting of neuroendocrine tumors: application of the Delphic consensus process to the development of a minimum pathology data set

Epithelial neuroendocrine tumors (NETs) have been the subject of much debate regarding their optimal classification. Although multiple systems of nomenclature, grading, and staging have been proposed, none has achieved universal acceptance. To help define the underlying common features of these classification systems and to identify the minimal pathology data that should be reported to ensure consistent clinical management and reproducibility of data from therapeutic trials, a multidisciplinary team of physicians interested in NETs was assembled. At a group meeting, the participants discussed a series of "yes" or "no" questions related to the pathology of NETs and the minimal data to be included in the reports. After discussion, anonymous votes were taken, using the Delphic principle that 80% agreement on a vote of either yes or no would define a consensus. Questions that failed to achieve a consensus were rephrased once or twice and discussed, and additional votes were taken. Of 108 questions, 91 were answerable either yes or no by more than 80% of the participants. There was agreement about the importance of proliferation rate for tumor grading, the landmarks to use for staging, the prognostic factors assessable by routine histology that should be reported, the potential for tumors to progress biologically with metastasis, and the current status of advanced immunohistochemical and molecular testing for treatment-related biomarkers. The lack of utility of a variety of immunohistochemical stains and pathologic findings was also agreed upon. A consensus could not be reached for the remaining 17 questions, which included both minor points related to extent of disease assessment and some major areas such as terminology, routine immunohistochemical staining for general neuroendocrine markers, use of Ki67 staining to assess proliferation, and the relationship of tumor grade to degree of differentiation. On the basis of the results of the Delphic voting, a minimum pathology data set was developed. Although there remains disagreement among experts about the specific classification system that should be used, there is agreement about the fundamental pathology data that should be reported. Examination of the areas of disagreement reveals significant opportunities for collaborative study to resolve unanswered questions.