Dataset Information

Immunohistochemical Profile and 47-Gene Next-Generation Sequencing (NGS) Solid Tumor Panel Analysis of a Series of 13 Strumal Carcinoids.

ABSTRACT: Strumal carcinoid is an extraordinary rare tumor of the ovary consisting of thyroid tissue intermixed with neuroendocrine tumor component. The cellular origin of strumal carcinoids has been an area of debate. There is also little data on detailed immunohistochemical and molecular characteristics of these neoplasms. For this reason, this series investigated the characteristics of a series of 13 strumal carcinoids using immunohistochemical markers and a 47-gene next-generation sequencing (NGS) solid tumor panel analysis. Both cellular components showed thyroglobulin expression in all tumors. TTF-1 expression was noted in both cellular components of 11 cases. Chromogranin A was positive in both components of most tumors (n =?12, 92.3% in the neuroendocrine component and n =?10, 76.9% in the thyroid follicular component). Synaptophysin stained the neuroendocrine component of all cases, and it was also identified in the follicular thyroid component of a single case. All tumors were negative for CDX2 and calcitonin. ISLET1 was positive in the neuroendocrine component of 8 cases (6.5%). With the exception of one case, all tumors were positive for SSTR2a. The tumors were associated with a low Ki67 labeling index. All cases were microsatellite stable and no pathogenic mutations were identified using a 47-gene NGS solid tumor analysis. This series underscored that strumal carcinoids are distinct neuroendocrine tumors. The synchronous expression for thyroid follicular epithelial and neuroendocrine differentiation biomarkers may suggest a precursor cell origin displaying mixed-amphicrine differentiation. While strumal carcinoids can be diagnosed by their typical morphology and immunohistochemical profile, frequent SSTR expression may serve as a potential theranostic biomarker in the management of affected patients. In addition, the absence of common driver mutations in the NGS solid tumor panel may suggest that these neoplasms seem to be genetically unrelated to follicular epithelial-derived thyroid tumors and potentially different than other commonly identified well-differentiated neuroendocrine neoplasms. Therefore, further studies focusing on molecular characteristics of this entity are still needed.

SUBMITTER: Theurer S

PROVIDER: S-EPMC7250806 | biostudies-literature | 2020 Jun

REPOSITORIES: biostudies-literature

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Immunohistochemical Profile and 47-Gene Next-Generation Sequencing (NGS) Solid Tumor Panel Analysis of a Series of 13 Strumal Carcinoids.

Theurer S S Ingenwerth M M Herold T T Herrmann K K Schmid K W KW

Endocrine pathology 20200601 2

Strumal carcinoid is an extraordinary rare tumor of the ovary consisting of thyroid tissue intermixed with neuroendocrine tumor component. The cellular origin of strumal carcinoids has been an area of debate. There is also little data on detailed immunohistochemical and molecular characteristics of these neoplasms. For this reason, this series investigated the characteristics of a series of 13 strumal carcinoids using immunohistochemical markers and a 47-gene next-generation sequencing (NGS) sol ...[more]

PMID: 32124226

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Project description:BACKGROUND:Next-Generation Sequencing (NGS) technology has exceptionally increased the ability to sequence DNA in a massively parallel and cost-effective manner. Nevertheless, NGS data analysis requires bioinformatics skills and computational resources well beyond the possibilities of many "wet biology" laboratories. Moreover, most of projects only require few sequencing cycles and standard tools or workflows to carry out suitable analyses for the identification and annotation of genes, transcripts and splice variants found in the biological samples under investigation. These projects can take benefits from the availability of easy to use systems to automatically analyse sequences and to mine data without the preventive need of strong bioinformatics background and hardware infrastructure. RESULTS:To address this issue we developed an automatic system targeted to the analysis of NGS data obtained from large-scale transcriptome studies. This system, we named NGS-Trex (NGS Transcriptome profile explorer) is available through a simple web interface http://www.ngs-trex.org and allows the user to upload raw sequences and easily obtain an accurate characterization of the transcriptome profile after the setting of few parameters required to tune the analysis procedure. The system is also able to assess differential expression at both gene and transcript level (i.e. splicing isoforms) by comparing the expression profile of different samples.By using simple query forms the user can obtain list of genes, transcripts, splice sites ranked and filtered according to several criteria. Data can be viewed as tables, text files or through a simple genome browser which helps the visual inspection of the data. CONCLUSIONS:NGS-Trex is a simple tool for RNA-Seq data analysis mainly targeted to "wet biology" researchers with limited bioinformatics skills. It offers simple data mining tools to explore transcriptome profiles of samples investigated taking advantage of NGS technologies.

Project description:Gliomas are the most common malignant primary brain tumors characterized by poor prognosis. The genotyping of tumors using next generation sequencing (NGS) platforms enables the identification of genetic alterations that constitute diagnostic, prognostic and predictive biomarkers. The present study investigated the molecular profile of 32 tumor samples from 32 patients with high-grade gliomas by implementing a broad 80-gene targeted NGS panel while reporting their clinicopathological characteristics and outcomes. Subsequently, 14 of 32 tumor specimens were also genotyped using a 55-gene NGS panel to validate the diagnostic accuracy and clinical utility of the extended panel. The median follow-up was 19.2 months. In total, 129 genetic alterations including 33 structural variants were identified in 38 distinct genes. Among 96 variants (single nucleotide variants and insertions and deletions), 38 were pathogenic and 58 variants of unknown clinical significance. TP53 was the most frequently mutated gene, followed by PTEN and IDH1 genes. Glioma patients with IDH1 mutant tumors were younger and had significantly longer overall survival compared to patients with wild-type IDH1 tumors. Similarly, tumors with TP53 mutations were more likely observed in younger patients with glioma. Subsequently, a comparison of mutational profiles of samples analyzed by both panels was also performed. Implementation of the comprehensive pan-cancer and the MOL panels resulted in the identification of 37 and 15 variants, respectively. Of those, 13 were common. Comprehensive pan-cancer panel identified 24 additional variants, 22 of which were located in regions that were not targeted by the MOL panel. By contrast, the MOL panel identified two additional variants. Overall, the present study demonstrated that using an extended tumor profile assay instead of a glioma-specific tumor profile panel identified additional genetic changes that may be taken into consideration as potential therapeutic targets for glioma diagnosis and molecular classification.

Project description:BackgroundIn recent years more than 20 assemblers have been proposed to tackle the hard task of assembling NGS data. A common heuristic when assembling a genome is to use several assemblers and then select the best assembly according to some criteria. However, recent results clearly show that some assemblers lead to better statistics than others on specific regions but are outperformed on other regions or on different evaluation measures. To limit these problems we developed GAM-NGS (Genomic Assemblies Merger for Next Generation Sequencing), whose primary goal is to merge two or more assemblies in order to enhance contiguity and correctness of both. GAM-NGS does not rely on global alignment: regions of the two assemblies representing the same genomic locus (called blocks) are identified through reads' alignments and stored in a weighted graph. The merging phase is carried out with the help of this weighted graph that allows an optimal resolution of local problematic regions.ResultsGAM-NGS has been tested on six different datasets and compared to other assembly reconciliation tools. The availability of a reference sequence for three of them allowed us to show how GAM-NGS is a tool able to output an improved reliable set of sequences. GAM-NGS is also a very efficient tool able to merge assemblies using substantially less computational resources than comparable tools. In order to achieve such goals, GAM-NGS avoids global alignment between contigs, making its strategy unique among other assembly reconciliation tools.ConclusionsThe difficulty to obtain correct and reliable assemblies using a single assembler is forcing the introduction of new algorithms able to enhance de novo assemblies. GAM-NGS is a tool able to merge two or more assemblies in order to improve contiguity and correctness. It can be used on all NGS-based assembly projects and it shows its full potential with multi-library Illumina-based projects. With more than 20 available assemblers it is hard to select the best tool. In this context we propose a tool that improves assemblies (and, as a by-product, perhaps even assemblers) by merging them and selecting the generating that is most likely to be correct.

Dataset Information

Immunohistochemical Profile and 47-Gene Next-Generation Sequencing (NGS) Solid Tumor Panel Analysis of a Series of 13 Strumal Carcinoids.

Publications

Immunohistochemical Profile and 47-Gene Next-Generation Sequencing (NGS) Solid Tumor Panel Analysis of a Series of 13 Strumal Carcinoids.

Similar Datasets

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