The panel of syntaxin 1 and insulinoma-associated protein 1 outperforms classic neuroendocrine markers in pulmonary neuroendocrine neoplasms

Biomarkers in gastroenteropancreatic neuroendocrine neoplasms

PURPOSE OF REVIEW

Gastroenteropancreatic neuroendocrine neoplasms (GEP-NEN) represent a heterogenous group of rare tumors emanating from neuroendocrine cells that are clinically silent for prolonged periods of time without detection. Traditional biomarkers lack sufficiently high enough specificity and sensitivity for these tumors and their secreted products. New molecules are sought to improve accuracy of detection and monitoring of GEP-NENs. The purpose of this review is to highlight recent advances in the discovery of novel biomarkers and their potential characteristics and utility as markers of GEP-NENs.

RECENT FINDINGS

Several recent GEP-NEN investigations regarding NETest demonstrate superior sensitivity and specificity in diagnosis and disease monitoring as compared with chromogranin A. Among several tissue-based emergent candidate molecules as biomarkers for GEP-NEN INSM1 has demonstrated consistently excellent characteristics when compared with traditional markers including chromogranin A, synaptophysin, and CD56.

SUMMARY

For the diagnosis and clinical monitoring of NEN, there still exists a considerable need for better biomarkers. Novel technology has resulted in a promising liquid biopsy for the detection and monitoring of GEP-NENs. The search for improved tissue biomarkers has resulted in identification of one potential candidate whereas several others remain in the investigatory phase.

STS-BN: An efficient Bayesian network method for detecting causal SNPs

Background: The identification of the causal SNPs of complex diseases in large-scale genome-wide association analysis is beneficial to the studies of pathogenesis, prevention, diagnosis and treatment of these diseases. However, existing applicable methods for large-scale data suffer from low accuracy. Developing powerful and accurate methods for detecting SNPs associated with complex diseases is highly desired.

Results: We propose a score-based two-stage Bayesian network method to identify causal SNPs of complex diseases for case-control designs. This method combines the ideas of constraint-based methods and score-and-search methods to learn the structure of the disease-centered local Bayesian network. Simulation experiments are conducted to compare this new algorithm with several common methods that can achieve the same function. The results show that our method improves the accuracy and stability compared to several common methods. Our method based on Bayesian network theory results in lower false-positive rates when all correct loci are detected. Besides, real-world data application suggests that our algorithm has good performance when handling genome-wide association data.

Conclusion: The proposed method is designed to identify the SNPs related to complex diseases, and is more accurate than other methods which can also be adapted to large-scale genome-wide analysis studies data.

Insulinoma-Associated Protein 1 (INSM1): Diagnostic, Prognostic, and Therapeutic Use in Small Cell Lung Cancer

Small cell lung carcinoma (SCLC) is an aggressive and difficult to treat cancer. Although immunohistochemistry is not mandatory for a SCLC diagnosis, it might be required, especially in small samples. Insulinoma-associated protein 1 (INSM1) is expressed in endocrine and nervous tissues during embryogenesis, generally absent in adults and re-expressed in SCLC and other neuroendocrine neoplasms. Its high specificity propelled its use as diagnostic biomarker and an attractive therapeutic target. Herein, we aim to provide a systematic and critical review on the use of INSM1 for diagnosis, prognostication and the treatment of SCLC. An extensive bibliographic search was conducted in PubMed® focusing on articles published since 2015. According to the literature, INSM1 is a highly sensitive (75–100%) and specific (82–100%) neuroendocrine immunohistochemical marker for SCLC diagnosis. It can be used in histological and cytological samples. Although advantageous, its standalone use is currently not recommended. Studies correlating INSM1 expression and prognosis have disclosed contrasting results, although the expression seemed to entail a worse survival. Targeting INSM1 effectively suppressed SCLC growth either as a suicide gene therapy regulator or as an indirect target of molecular-targeted therapy. INSM1 represents a valuable biomarker for a SCLC diagnosis that additionally offers vast opportunities for the development of new prognostic and therapeutic strategies.

Diagnostic criteria and evolving molecular characterization of pulmonary neuroendocrine carcinomas

Neuroendocrine carcinomas of the lung are currently classified into two categories: small cell lung carcinoma and large cell neuroendocrine carcinoma. Diagnostic criteria for small cell- and large cell neuroendocrine carcinoma are based solely on tumor morphology; however, overlap in histologic and immunophenotypic features between the two types of carcinoma can potentially make their classification challenging. Accurate diagnosis of pulmonary neuroendocrine carcinomas is paramount for patient management, as clinical course and treatment differ between small cell and large cell neuroendocrine carcinoma. Molecular-genetic, transcriptomic, and proteomic data published over the past decade suggest that small cell and large cell neuroendocrine carcinomas are not homogeneous categories but rather comprise multiple groups of distinctive malignancies. Nuances in the susceptibility of small cell lung carcinoma subtypes to different chemotherapeutic regimens and the discovery of targetable mutations in large cell neuroendocrine carcinoma suggest that classification and treatment of neuroendocrine carcinomas may be informed by ancillary molecular and protein expression testing going forward. This review summarizes current diagnostic criteria, prognostic and predictive correlates of classification, and evidence of previously unrecognized subtypes of small cell and large cell neuroendocrine carcinoma.

INSM1, a Novel Biomarker for Detection of Neuroendocrine Neoplasms: Cytopathologists’ View

Background: Insulinoma-associated protein 1 (INSM1) has been considered as a novel immunostain for neuroendocrine tumors (NETs) and is hypothesized to be more reliable than first-generation NET biomarkers, such as CGA (chromogranin A), SYP (synaptophysin) and CD56 (neural cell adhesion molecule). In this review, we summarize existing literature on INSM1′s reliability as an immunostain for detection of various NETs, its results in comparison to first-generation NET biomarkers, and its expression in both non-NETs and benign tissues/cells on cytology specimens (cell blocks/smears).

Syntaxin-1 and Insulinoma-Associated Protein 1 Expression in Breast Neoplasms with Neuroendocrine Features

Introduction: A subset of breast neoplasia is characterized by features of neuroendocrine differentiation. Positivity for Neuroendocrine markers by immunohistochemistry is required for the diagnosis. Sensitivity and specificity of currently used markers are limited; based on the definitions of WHO Classification of Tumours, 5th edition, about 50% of breast tumors with features of neuroendocrine differentiation express chromogranin-A and 16% express synaptophysin. We assessed the applicability of two novel markers, syntaxin-1 and insulinoma-associated protein 1 (INSM1) in breast carcinomas. Methods: Hypercellular (Type B) mucinous carcinomas, solid papillary carcinomas, invasive carcinomas of no special type with neuroendocrine features and ductal carcinomas in situ of neuroendocrine subtype were included in our study. The immunohistochemical panel included chromogranin A, synaptophysin, CD56, syntaxin-1 and INSM1. The specificity of syntaxin-1 and INSM1 was determined using samples negative for chromogranin A, synaptophysin and CD56. Results: The sensitivity of syntaxin-1 was 84.7% (50/59), with diffuse positivity in more than 60% of the cases. Syntaxin-1 also had an excellent specificity (98.1%). Depending on the definition for positivity, the sensitivity of INSM1 was 89.8% (53/59) or 86.4% (51/59), its specificity being 57.4% or 88.9%. The sensitivities of chromogranin A, synaptophysin and CD56 were 98.3, 74.6 and 22.4%, respectively. Discussion: Syntaxin-1 and INSM1 are sensitive and specific markers of breast tumors with neuroendocrine features, outperforming chromogranin A and CD56. We recommend syntaxin-1 and INSM1 to be included in the routine neuroendocrine immunohistochemical panel.