A 92-gene cancer classifier predicts the site of origin for neuroendocrine tumors

Diagnostic Approaches to Neuroendocrine Neoplasms of Unknown Primary Site

ABSTRACT

Neuroendocrine tumors (NETs) are relatively uncommon heterogeneous neoplasms arising from endocrine and neuronal origin cells showing highly variable clinical behavior. By the time these tumors are discovered, up to 14% of patients with histologically proven NETs have metastasis, with the liver as the most frequently affected organ. Sometimes, no known primary site can be identified via routine imaging. Neuroendocrine tumors of unknown origin carry a poorer prognosis (compared with metastatic NETs with a known primary site) because of a lack of tailored surgical intervention and appropriate medical therapy (eg, chemotherapy or targeted therapy). A multimethod approach is frequently used in the trial to accurately determine the primary site for NETs of unknown primary sites and may include clinical, laboratory, radiological, histopathological, and surgical data. New molecular techniques using the genomic approach to identify the molecular signature have shown promising results. Various imaging modalities include ultrasound, computed tomography (CT), dual-energy CT, magnetic resonance imaging, and functional and hybrid imaging (positron emission tomography/CT, positron emission tomography/magnetic resonance imaging); somatostatin receptor imaging with new tracers is frequently used in an attempt for localization of the primary site.

Hypercalcemia and Bone Metastasis in a Case of Large Cell Neuroendocrine Carcinoma With Unknown Primary

Large cell neuroendocrine carcinoma (LCNEC) constitutes a rare subset of highly undifferentiated malignancies known for their aggressive nature. Although these tumors commonly originate in the lungs and gastrointestinal tract, their potential occurrence is not restricted to specific anatomical sites, giving rise to a variety of symptoms. Notably, cases of neuroendocrine tumors (NETs) with an unidentified primary source exhibit a graver prognosis and shorter survival periods compared to those with clearly identified origins. NETs frequently demonstrate a propensity to metastasize, spreading to diverse anatomical regions such as the liver, lungs, lymph nodes, and bones, illustrating their aggressive nature and the complexity of their management. In this context, we present the case of a 59-year-old male who sought medical attention in the emergency department due to right upper quadrant (RUQ) abdominal pain. Initial diagnostic assessments revealed significantly elevated liver function tests and severe hypercalcemia. A right upper quadrant ultrasound (RUQ US) was subsequently performed, which revealed heterogeneous hepatic echotexture with innumerable echogenic masses, suggesting a metastatic process. A computed tomography (CT) scan was then ordered to evaluate further the RUQ US findings, which showed numerous hypovascular liver masses, raising concerns of malignancy. A liver biopsy confirmed a diagnosis of LCNEC with an unidentified primary source.

Molecular deciphering of primary liver neuroendocrine neoplasms confirms its distinct existence with foregut-like profile

Isolated hepatic localizations of neuroendocrine tumors (NETs) are generally considered as metastatic NETs of unknown primary but could correspond to primary hepatic NETs (PHNETs), a poorly explored entity. We aimed to describe the clinicopathological and molecular features of PHNETs and compare them with other primary NETs. We assembled a retrospective cohort of patients managed for hepatic localization of NET without extra-hepatic primary tumor after exhaustive clinical, imaging and immunohistochemical characterization. We performed whole-exome sequencing with mutational and copy number analysis. Transcriptomic profiles were compared to pancreatic (n=31), small-bowel (n=22) and lung (n=15) NETs using principal component analysis, unsupervised clustering and gene-set enrichment analysis. Among 27 screened patients, 16 had PHNET (solitary tumor in 63%, median size 11 cm, G2 NETs in 81%) following clinical and pathological review. DNA analyses showed "foregut-like" genomic profiles with frequent alterations in pathways of Fanconi DNA repair (75%), histone modifiers (58%), adherens junctions (58%) and cell cycle control (50%). The most frequently involved genes were KMT2A (58%), ATM (42%), CDH1, CDKN2C, FANCF and MEN1 (33% each). Transcriptomic analyses showed that PHNETs clustered closer to foregut (pancreatic, lung) NETs than to midgut (small-bowel) NETs, while remaining a distinct entity with specific profile. Assessment of potentially predictive biomarkers suggested efficacy of treatments usually active in foregut NETs. In conclusion, PHNETs display a foregut-like molecular profile distinct from other types of NETs, with recurrent molecular alterations. Upon exhaustive work-up to exclude unrecognized primary tumor, PHNETs should not be considered metastatic NETs from an unknown primary. This article is protected by copyright. All rights reserved.

Molecular Pathology of Lung Cancer

This overview of the molecular pathology of lung cancer includes a review of the most salient molecular alterations of the genome, transcriptome, and the epigenome. The insights provided by the growing use of next-generation sequencing (NGS) in lung cancer will be discussed, and interrelated concepts such as intertumor heterogeneity, intratumor heterogeneity, tumor mutational burden, and the advent of liquid biopsy will be explored. Moreover, this work describes how the evolving field of molecular pathology refines the understanding of different histologic phenotypes of non-small-cell lung cancer (NSCLC) and the underlying biology of small-cell lung cancer. This review will provide an appreciation for how ongoing scientific findings and technologic advances in molecular pathology are crucial for development of biomarkers, therapeutic agents, clinical trials, and ultimately improved patient care.

The role of molecular profiling in the diagnosis and management of metastatic undifferentiated cancer of unknown primary✰: Molecular profiling of metastatic cancer of unknown primary

Cancer of unknown primary (CUP) refers to metastatic tumors for which the primary tumor of origin cannot be determined at the time of diagnosis, despite extensive clinicopathologic investigations. Molecular profiling is increasingly able to predict a probable primary tumor type for CUP when clinicopathologic workup is inconclusive. Numerous studies have explored the use of various molecular profiling techniques for identification of site/tissue of origin of CUP. These techniques include gene expression profiling utilizing microarray, reverse transcriptase polymerase chain reaction, RNA-sequencing, somatic gene mutation profiling with next-generation DNA sequencing, and epigenomics including DNA methylation profiling. Despite the generally poor prognosis of CUP, a minority of patients can expect to benefit from targeted therapy despite being agnostic to the tissue of origin. Studies have explored the use of various molecular profiling techniques to predict prognostic and therapeutic biomarkers, with the goal of improving outcome for patients with CUP. However, discordant results between non-randomized and randomized clinical trials in evaluating tumor-type specific therapies raise uncertainties of the benefits of molecularly-predicted tissue of origin-based treatment in routine clinical use. Nevertheless, the current overall trend is in favor of using molecular tools to refine the diagnosis and clinical management of patients with CUP. More large-cohort, randomized prospective studies are needed to assess and validate the utility and feasibility of molecular profiling to uncover potentially targetable genetic alterations. These efforts will also yield further biological insights into the biology and pathogenesis of CUP (Graphical Abstract).

Liver metastases from pituitary carcinomas mimicking visceral well-differentiated neuroendocrine tumors: a series of four cases

Background

Pathologists frequently encounter neuroendocrine tumors (NETs) presenting as multiple liver masses in routine practice. Most often, these are well-differentiated tumors with characteristic histologic features. In contrast, pituitary carcinoma is very rare, and there is limited data on its natural history and pathologic characterization.

Methods

The aim of this study was to describe clinical characteristics, histomorphology, immunophenotype and follow-up of pituitary carcinoma involving the liver and mimicking well-differentiated NETs of visceral origin. We selected a group of well-differentiated NETs of the pancreas to use as immunophenotypic controls. We identified 4 patients (age range, 51 to 73) with pituitary corticotroph carcinoma with liver metastases. Three patients presented with Cushing syndrome.

Results

All cases histologically resembled well-differentiated NETs of visceral origin with Ki-67 proliferation indices of 5–42% and expression of T-PIT; metastatic tumors were not immunoreactive with CDX2, Islet 1 or TTF-1.

Conclusions

Frequently, these cases display adrenocorticotropic hormone (ACTH) secretion and pituitary-specific transcription factor immunohistochemistry may be used as a reliable marker to distinguish metastatic pituitary carcinoma from NETs of visceral origin in addition to delineating a corticotroph carcinoma from somatotroph, lactotroph, thyrotroph, and gonadotroph lineage. Although rare, the differential diagnosis of pituitary carcinoma should be considered in metastatic well-differentiated NETs in which the site of origin is uncertain. In summary, pituitary corticotroph carcinoma can metastasize to the liver and mimic well-differentiated NET.

Diagnostic Approaches to Neuroendocrine Neoplasms of Unknown Primary Site

Neuroendocrine neoplasms (NENs) arise from cells of neuronal and endocrine differentiation. While they are a rare entity, an increasing proportion of patients with NEN present with metastatic disease and no evident primary site using routine imaging or histopathology. NENs of unknown primary site have a poorer prognosis, often due to the challenge of selecting appropriate evidence-based management. We review the available literature and guidelines for the management of NENs of unknown primary site including clinical features, biochemical tests, histopathology, imaging, surgical exploration and localised and systemic treatments. We also discuss novel molecular techniques currently under investigation to aid primary site identification.

Current Practices and Novel Techniques in the Diagnosis and Management of Neuroendocrine Tumors of Unknown Primary

Neuroendocrine tumors (NETs) comprise a heterogeneous group of neoplasms in which tumor staging/prognosis and response to treatments depend heavily on accurate and timely identification of the anatomic primary site or NET subtype. Despite recent technological advancements and use of multiple diagnostic modalities, 10% to 14% of newly diagnosed NETs are not fully characterized based on subtype or anatomic primary site. Inability to fully characterize NETs of unknown primary may cause delays in surgical intervention and limit potential treatment options. To address this unmet need, clinical validity and utility are being demonstrated for novel approaches that improve NET subtype or anatomic primary site identification. Functional imaging using Ga-radiolabeled DOTATATE positron emission tomography/computed tomography has been shown to overcome some false-positive and resolution issues associated with octreotide scanning and computed tomography/magnetic resonance imaging. Using a genomic approach, molecular tumor classification based on differential gene expression has demonstrated high diagnostic accuracy in blinded validation studies of different NET types and subtypes. Given the widespread availability of these technologies, we propose an algorithm for the workup of NETs of unknown primary that integrates these approaches. Including these technologies in the standard workup will lead to better NET subtype identification and improved treatment optimization for patients.

Gene Expression Profiling for Diagnosis of Triple-Negative Breast Cancer: A Multicenter, Retrospective Cohort Study

Background: Triple-negative breast cancer (TNBC) accounts for 12–20% of all breast cancers. Diagnosis of TNBC is sometimes quite difficult based on morphological assessment and immunohistochemistry alone, particularly in the metastatic setting with no prior history of breast cancer.

Methods: Molecular profiling is a promising diagnostic approach that has the potential to provide an objective classification of metastatic tumors with unknown primary. In this study, performance of a novel 90-gene expression signature for determination of the site of tumor origin was evaluated in 115 TNBC samples. For each specimen, expression profiles of the 90 tumor-specific genes were analyzed, and similarity scores were obtained for each of the 21 tumor types on the test panel. Predicted tumor type was compared to the reference diagnosis to calculate accuracy. Furthermore, rank product analysis was performed to identify genes that were differentially expressed between TNBC and other tumor types.

Results: Analysis of the 90-gene expression signature resulted in an overall 97.4% (112/115, 95% CI: 0.92–0.99) agreement with the reference diagnosis. Among all specimens, the signature correctly classified 97.6% of TNBC from the primary site (41/42) and lymph node metastasis (41/42) and 96.8% of distant metastatic tumors (30/31). Furthermore, a list of genes, including AZGP1, KRT19, and PIGR, was identified as differentially expressed between TNBC and other tumor types, suggesting their potential use as discriminatory markers.

Conclusion: Our results demonstrate excellent performance of a 90-gene expression signature for identification of tumor origin in a cohort of both primary and metastatic TNBC samples. These findings show promise for use of this novel molecular assay to aid in differential diagnosis of TNBC, particularly in the metastatic setting.

Integrating a 92-Gene Expression Analysis for the Management of Neuroendocrine Tumors of Unknown Primary

Background: Neuroendocrine tumors (NETs) are rare tumors that can originate from any part of the body. Often, imaging or exploratory surgery can assist in the identification of the tumor primary site, which is critical to the management of the disease. Neuroendocrine tumors (NETs) of unknown primary constitute approximately 10-15% of all NETs. Determining the original site of the tumor is critical to providing appropriate and effective treatment. Methods: We performed a retrospective review of neuroendocrine tumors at our institution between 2012 and 2016 using a 92-gene cancer ID analysis. Results: 56 patients with NETs of unknown primary were identified. Samples for 38 of the 56 underwent the 92-gene cancer ID analysis. The primary site of the tumor was identified with >95% certainty in 35 of the 38 patients. Conclusion: The 92-gene cancer ID analysis identified a primary site in 92% of our NETs study cohort that previously had been unknown. The results have direct implications on management of patients with regard to FDA-approved treatment options.

Advances in the cytologic diagnosis of gastroenteropancreatic neuroendocrine neoplasms

Two-thirds of neuroendocrine neoplasms arising in the human body originate from the gastrointestinal system or pancreas. Gastroenteropancreatic neuroendocrine neoplasms are heterogeneous, comprising both well differentiated neuroendocrine tumors (NETs) and poorly differentiated neuroendocrine carcinomas (NECs). The clinical presentation, molecular characteristics, and behavior are distinct for NETs and NECs. Fine-needle aspiration is an important modality for the primary diagnosis and staging of these neoplasms and can provide information of prognostic and therapeutic significance. Our evolving understanding of neuroendocrine neoplasm biology has led to several iterations of classification. In this review, new concepts and issues most relevant to cytology diagnosis of gastroenteropancreatic neuroendocrine neoplasms are discussed, such as newer detection methods that aid in diagnosis and staging, recent changes in World Health Organization classification, practical issues related to grading these neoplasms on cytology, guidelines for diagnostic reporting, and panels of immunohistochemical stains for the diagnosis of metastasis. The current understanding of genetic and epigenetic events related to tumor development and potential applications for cytology also are presented as they relate to prognostication and recent therapeutic advances.

Cancer of Unknown Primary: Opportunities and Challenges

Cancer of unknown primary (CUP) is defined as histologically proven metastatic tumors whose primary site cannot be identified during pretreatment evaluation. Among all malignancies, 3%–5% remained as CUP even after the extensive radiological and pathological workup. Immunohistochemistry and molecular gene expression tumor profiling are being utilized to predict the tissue of origin. Unfortunately, the survival of these patients remains poor (6–9 months) except in 20% of patients who belong to a favorable subset (12–36 months). There is a need to understand the basic biology and to identify the molecular pathways which can be targeted with small molecules. This article reviews our current approach as well as treatment evolution occurred in the past three decades.

Ki67 Proliferative Index in Carcinoid Tumors Involving Ovary

Primary ovarian carcinoid tumors are rare neoplasms that constitute less than 0.1% of all ovarian carcinomas. However, carcinoid tumors metastatic to ovaries are more common. Cell proliferative rate is an important factor in the determination of neuroendocrine tumor prognosis. Limited data are available as regards Ki67 proliferation index in predicting the physiological features of carcinoid tumors involving the ovary. Pathology files of Mayo Clinic Rochester (1995-2014) were searched, and clinical information was collected from medical records. All cases were stained with an antibody against Ki67, and digital analysis was performed with digital imaging analysis. A total of 36 cases (median age 64 years, range 33-83 years), including 9 primary (median age 68 years, range 33-73 years) and 27 metastatic carcinoid cases (median age 64 years, range 36-83 years), were investigated in the current study. Seven out of nine (77.8%) primary ovarian carcinoids are associated with mature teratoma. Twenty two metastatic carcinoids (81.5%) were from the GI tract, four (14.8%) from the pancreas, and one (3.7%) from the posterior thorax location. There was significant difference of Ki67 index between primary (median 2.3%, range, 0.6-8.4%) and metastatic carcinoid tumors (median 9.7%, range, 1.3-46.7%) (p = 0.002). The survival time is much shorter among patients with metastatic carcinoid tumor (median survival 5.8 years) comparing to primary ovarian carcinoid tumor (median 14.2 years) (p = 0.0005). A strong association between Ki67 index and patient survival time was identified (Hazard ratio for 1-percentage point increase 1.11, p = 0.001). Comparing to primary ovarian carcinoid tumor, metastatic carcinoid usually exhibits a higher Ki67 index and a worse outcome.

Translational Diagnostics and Therapeutics in Pancreatic Neuroendocrine Tumors

Pancreatic neuroendocrine tumors (PNET) are rare tumors, but have been increasing in incidence. Although typically thought of as indolent, more than half of patients present with metastatic disease. For many years, the only mutations commonly known in these tumors were those in the MEN1 gene. Recently, the genetics underlying PNETs have been further defined through exome sequencing. The most frequent alterations found in sporadic PNETs are in MEN1, DAXX/ATRX, and a variety of genes in the mTOR pathway. Confirmation of these mutations has prompted trials with a number of drugs active in these pathways, and two drugs were eventually approved in 2011-sunitinib and everolimus. New data additionally identify the MET and CD47 receptors as potential novel drug targets. Yet despite improvements in progression-free survival with sunitinib and everolimus, further studies defining when to use these agents and factors associated with limitations in their utility are needed. As more discoveries are made in the laboratory that elucidate additional molecular mechanisms important in the initiation and metastasis of PNETs, continued efforts to translate these discoveries into distinct new therapies will be needed to improve patient survival. Clin Cancer Res; 22(20); 5022-9. ©2016 AACR SEE ALL ARTICLES IN THIS CCR FOCUS SECTION, "ENDOCRINE CANCERS REVISING PARADIGMS".

Changes in gene expression in small bowel neuroendocrine tumors associated with progression to metastases

BACKGROUND

Small bowel neuroendocrine tumors (SBNETs) present frequently with metastases, yet little is known about the molecular basis of this progression. This study sought to identify the serial differential expression of genes between normal small bowel, primary small bowel neuroendocrine tumors, and liver metastases.

METHODS

RNA isolated from matched normal small bowel tissue, primary small bowel neuroendocrine tumors, and liver metastases in 12 patients was analyzed with whole transcriptome expression microarrays and RNA-Seq. Changes in gene expression between primary small bowel neuroendocrine tumors and normal small bowels, and liver metastases versus primary small bowel neuroendocrine tumors were calculated. Common genes that were differentially expressed serially (increasing or decreasing from normal small bowel to primary small bowel neuroendocrine tumors to liver metastases) were identified, and 10 were validated using qPCR.

RESULTS

Use of 2 transcriptome platforms allowed for a robust discrimination of genes important in small bowel neuroendocrine tumors progression. Serial differential expression was validated in 7/10 genes, all of which had been described previously in abdominal cancers, and with several interacting with members of the AKT, MYC, or MAPK3 pathways. Liver metastases had consistent underexpression of PMP22, while high expression of SERPINA10 and SYT13 was characteristic of both pSBTs and liver metastases.

CONCLUSION

Identification of the serial differential expression of genes from normal tissues to primary tumors to metastases lends insight into important pathways for SBNETs progression. Differential expression of various genes, including PMP22, SYT13 and SERPINA10, are associated with the progression of SBNETs and warrant further investigation.

Analytical Performance of a Gene Expression Classifier for Medullary Thyroid Carcinoma

BACKGROUND

The aim of this study was to demonstrate the analytical validity of an RNA classifier for medullary thyroid carcinoma (MTC).

METHODS

Fresh-frozen tissue specimens were obtained from commercial sources, and MTC diagnoses were confirmed by histopathology review. De-identified patient fine-needle aspiration biopsies (FNABs) and whole blood from normal donors were obtained. Total RNA was extracted, amplified, and hybridized to custom microarrays for gene expression analysis. Gene expression data were normalized and classified via a machine learning algorithm. Positive control materials were produced from MTC tissues and tested across multiple experiments and laboratories. Twenty-seven MTC tissue specimens were used to evaluate the sensitivity of the MTC classifier. Gene expression data from tissues and FNABs were used to model classifier response to mixtures of MTC samples with normal thyroid tissue, a benign thyroid nodule, a Hürthle cell adenoma, and whole blood. Select mixture conditions were confirmed in vitro. Assay tolerance to RNA input variation (5-25 ng) and genomic DNA contamination (30% by mass) was evaluated. The intra- and inter-run reproducibility and inter-laboratory accuracy of MTC classifier results were characterized.

RESULTS

The MTC classifier sensitivity of 96.3% [confidence interval 81.0-99.9%] was determined retrospectively using 27 MTC confirmed tissue specimens. One false-negative result in a necrotic tissue implicated sample necrosis in reduced classifier sensitivity. Dilution modeling of MTC samples with normal or benign tissues showed consistent detection of MTC down to 20% sample proportions, with in vitro confirmation of 20% analytical sensitivity. Classifier tolerance to RNA input variation (5-25 ng), genomic DNA contamination (30% by mass), and an interfering substance (blood) was demonstrated with 100% accurate classifier results under all tested conditions. The maximum observed run-to-run score difference for a single FNAB sample was ∼1 unit compared with the average score difference between 38 MTC and non-MTC FNABs of ∼32 units. MTC classifier results for 20 tissues processed from total RNA in two different laboratories showed 100% concordance.

CONCLUSIONS

The MTC classifier, offered as part of the routine molecular testing of cytology-indeterminate thyroid nodules, demonstrates robust analytical sensitivity, specificity, accuracy, and reproducibility.

The importance of surfactant proteins-New aspects on macrophage phagocytosis

Surfactant and its components have multiple functions. The so called collectins are surfactant proteins which opsonize bacteria and improve pulmonary host defense via the phagocytosis and clearance of microorganisms and particles. In this special issue of the Annals of Anatomy a new surfactant protein, Surfactant Associated 3, is highlighted. As outlined in this mini review Surfactant Associated 3 is regarded as an enhancer of phagocytosis. In addition, the role played by SP-A is updated and open research questions raised.

Towards a new classification of gastroenteropancreatic neuroendocrine neoplasms

Gastroenteropancreatic neuroendocrine neoplasms (GEP-NENs) constitute a heterogeneous group of tumours associated with variable clinical presentations, growth rates, and prognoses. To improve the management of GEP-NENs, the WHO developed a classification system that enables tumours to be graded based on markers of cell proliferation in biopsy specimens. Indeed, histopathology has been a mainstay in the diagnosis of GEP-NENs, and the WHO grading system facilitates therapeutic decision-making; however, considerable intratumoural heterogeneity, predominantly comprising regional variations in proliferation rates, complicates the evaluation of tumour biology. The use of molecular imaging modalities to delineate the most-aggressive cell populations is becoming more widespread. In addition, molecular profiling is increasingly undertaken in the clinical setting, and genomic studies have revealed a number of chromosomal alterations in GEP-NENs, although the 'drivers' of neoplastic development have not been identified. Thus, our molecular understanding of GEP-NENs remains insufficient to inform on patient prognosis or selection for treatments, and the WHO classification continues to form the basis for management of this disease. Nevertheless, our increasing understanding of the molecular genetics and biology of GEP-NENs has begun to expose flaws in the WHO classification. We describe the current understanding of the molecular characteristics of GEP-NENs, and discuss how advances in molecular profiling measurements, including assays of circulating mRNAs, are likely to influence the management of these tumours.

A Genomic Alternative to Identify Medullary Thyroid Cancer Preoperatively in Thyroid Nodules with Indeterminate Cytology

BACKGROUND

The use of calcitonin screening for the rare medullary thyroid cancer (MTC) is controversial due to questions of efficacy, accuracy, and cost-effectiveness. This study reports the results of a large prospective validation using a machine-trained algorithm (MTC Classifier) to preoperatively identify MTC in fine-needle aspiration biopsies in lieu of calcitonin measurements.

METHODS

Cytology analysis on a prospective consecutive series of 50,430 thyroid nodule biopsies yielded a total of 7815 indeterminate (Bethesda categories III/IV) cases, which were tested with the MTC classifier. A prospective, consecutively submitted series of 2673 Bethesda III-VI cases with cytology determined locally was also evaluated. RNA was isolated and tested for the MTC Classifier using microarrays.

RESULTS

Forty-three cases were positive by the MTC Classifier among 10,488 tested nodules (0.4%), consistent with the low prevalence of MTC. Of these, all but one was histologically or biochemically confirmed as MTC, yielding a positive predictive value (PPV) of 98%. Of the positive cases, only 19 (44%) had been specifically suspected of MTC by cytology, highlighting the limitations of light microscopy to detect this disease. Three surgically confirmed MTC cases that were detected by the MTC Classifier had low basal serum calcitonin values, indicating these would have been missed by traditional calcitonin screening methods. A pooled analysis of three independent validation sets demonstrates high test sensitivity (97.9%), specificity (99.8%), PPV (97.9%), and negative predictive value (99.8%).

CONCLUSIONS

A clinical paradigm is proposed, whereby cytologically indeterminate thyroid nodules being tested for common malignancies using gene expression can be simultaneously tested for MTC using the same genomic assay at no added cost.

Poorly differentiated neoplasms of unknown primary site: diagnostic usefulness of a molecular cancer classifier assay

PURPOSE

Definition of the lineage of poorly differentiated neoplasms (PDNs) presenting as cancer of unknown primary site (CUP) is important since many of these tumors are treatment-sensitive. Gene expression profiling and a molecular cancer classifier assay (MCCA) may provide a new method of diagnosis when standard pathologic evaluation and immunohistochemical (IHC) staining is unsuccessful.

PATIENTS AND METHODS

Thirty of 751 CUP patients (4%) seen from 2000-2012 had PDNs without a definitive lineage diagnosed by histology or IHC (median 18 stains, range 9-46). Biopsies from these 30 patients had MCCA (92-gene reverse transcriptase-polymerase chain reaction mRNA) performed. Additional IHC, gene sequencing, fluorescent in situ hybridization for specific genetic alterations, and repeat biopsies were performed to support MCCA diagnoses, and clinical features correlated. Seven patients had MCCA performed initially and received site-specific therapy.

RESULTS

Lineage diagnoses were made by MCCA in 25 of 30 (83 %) patients, including ten carcinomas (three germ cell, two neuroendocrine, five others), eight sarcomas [three peritoneal mesotheliomas, one primitive neuroectodermal tumor (PNET), four others], five melanomas, and two lymphomas. Additional IHC and genetic testing [BRAF, i(12)p] supported the MCCA diagnoses in 11 of 16 tumors. All seven patients (two germ cell, two neuroendocrine, two mesothelioma, one lymphoma) responded to site-specific therapy based on the MCCA diagnosis, and remain alive (five progression-free) from 25+ to 72+ months.

CONCLUSION

The MCCA provided a specific lineage diagnosis and tissue of origin in most patients with PDNs unclassifiable by standard pathologic evaluation. Earlier use of MCCA will expedite diagnosis and direct appropriate first-line therapy, which is potentially curative for several of these tumor types.

Biochemical Diagnosis and Preoperative Imaging of Gastroenteropancreatic Neuroendocrine Tumors

Neuroendocrine tumors are a group of neoplasms that can arise in a variety of locations throughout the body and often metastasize early. A patient's only chance for cure is surgical removal of the primary tumor and all associated metastases, although even when surgical cure is unlikely, patients can benefit from surgical debulking. A thorough preoperative workup will often require multiple clinical tests and imaging studies to locate the primary tumor, delineate the extent of the disease, and assess tumor functionality. This review discusses the biomarkers important for the diagnosis of these tumors and the imaging modalities needed.

Problems with the diagnosis of metastatic neuroendocrine neoplasms. Which diagnostic criteria should we use to determine tumor origin and help guide therapy?

Neuroendocrine neoplasms (NENs) can often present with metastatic disease before the primary tumor is discovered. Metastatic lesions are generally classified as well differentiated and poorly differentiated for prognostic and therapeutic purposes. In addition, for well-differentiated neuroendocrine tumors (WDNETs), pathologists are expected to determine the site of origin, if not already known, and grade the tumors. However, it is often difficult for pathologists to provide this information with certainty without knowing the site of tumor origin, as different criteria have been proposed by WHO for classification of gastrointestinal and pulmonary NENs. In this review, we will discuss the current classification and grading schema of NENs and their impact on clinical care, the differential diagnosis of NENs, the use of immunohistochemical stains that help identify tumor site of origin, and a proposed approach for the diagnosis and classification of metastatic NENs.

A practical method to determine the site of unknown primary in metastatic neuroendocrine tumors

INTRODUCTION

The site of a primary neuroendocrine tumor (NET) tumor is unknown before treatment in approximately 20% of small bowel (SBNET) and pancreatic (PNET) cases despite extensive workup. It can be difficult to discern a PNET from an SBNET on hematoxylin and eosin stains, and thus, more focused diagnostic tests are required. Immunohistochemistry (IHC) and gene expression profiling are two methods used to identify the tissue of origin from biopsied metastases.

METHODS

Tissue microarrays were created from operative specimens and stained with up to seven antibodies used in the NET-specific IHC algorithm. Expression of four genes for differentiating between PNETs and SBNETs was determined by quantitative polymerase chain reaction and then used in a previously validated gene expression classifier (GEC) algorithm designed to determine the primary site from gastrointestinal NET metastases.

RESULTS

The accuracy of the IHC algorithm in identifying the primary tumor site from a set of 37 metastases was 89%, with only one incorrect call. Three other samples were indeterminate as the result of pan-negative staining. The GEC's accuracy in a set of 136 metastases was 94%. The algorithm identified the primary tumor site in all cases in which IHC failed.

CONCLUSION

Performing IHC, followed by GEC for indeterminate cases, identifies accurately the primary site in SBNET and PNET metastases in virtually all patients.

Gene expression accurately distinguishes liver metastases of small bowel and pancreas neuroendocrine tumors

Small bowel (SBNETs) and pancreatic neuroendocrine tumors (PNETs) often present with liver metastases. Although liver biopsy establishes a neuroendocrine diagnosis, the primary tumor site is frequently unknown without exploratory surgery. Gene expression differences in metastases may distinguish primary SBNETs and PNETs. This study sought to determine expression differences of four genes in neuroendocrine metastases and to create a gene expression algorithm to distinguish the primary site. Nodal and liver metastases from SBNETs and PNETs (n = 136) were collected at surgery under an Institutional Review Board-approved protocol. Quantitative PCR measured expression of bombesin-like receptor-3, opioid receptor kappa-1, oxytocin receptor, and secretin receptor in metastases. Logistic regression models defined an algorithm predicting the primary tumor site. Models were developed on a training set of 21 nodal metastases and performance was validated on an independent set of nodal and liver metastases. Expression of all four genes was significantly different in SBNET compared to PNET metastases. The optimal model employed expression of bombesin-like receptor-3 and opioid receptor kappa-1. When these genes did not amplify, the algorithm used oxytocin receptor and secretin receptor expression, which allowed classification of all 136 metastases with 94.1 % accuracy. In the independent liver metastasis validation set, 52/56 (92.9 %) were correctly classified. Positive predictive values were 92.5 % for SBNETs and 93.8 % for PNETs. This validated algorithm accurately distinguishes SBNET and PNET metastases based on their expression of four genes. High accuracy in liver metastases demonstrates applicability to the clinical setting. Studies assessing this algorithm's utility in prospective clinical decision-making are warranted.