Dataset Information

Characterizing and classifying neuroendocrine neoplasms through microRNA sequencing and data mining.

ABSTRACT: Neuroendocrine neoplasms (NENs) are clinically diverse and incompletely characterized cancers that are challenging to classify. MicroRNAs (miRNAs) are small regulatory RNAs that can be used to classify cancers. Recently, a morphology-based classification framework for evaluating NENs from different anatomical sites was proposed by experts, with the requirement of improved molecular data integration. Here, we compiled 378 miRNA expression profiles to examine NEN classification through comprehensive miRNA profiling and data mining. Following data preprocessing, our final study cohort included 221 NEN and 114 non-NEN samples, representing 15 NEN pathological types and 5 site-matched non-NEN control groups. Unsupervised hierarchical clustering of miRNA expression profiles clearly separated NENs from non-NENs. Comparative analyses showed that miR-375 and miR-7 expression is substantially higher in NEN cases than non-NEN controls. Correlation analyses showed that NENs from diverse anatomical sites have convergent miRNA expression programs, likely reflecting morphological and functional similarities. Using machine learning approaches, we identified 17 miRNAs to discriminate 15 NEN pathological types and subsequently constructed a multilayer classifier, correctly identifying 217 (98%) of 221 samples and overturning one histological diagnosis. Through our research, we have identified common and type-specific miRNA tissue markers and constructed an accurate miRNA-based classifier, advancing our understanding of NEN diversity.

SUBMITTER: Nanayakkara J

PROVIDER: S-EPMC7380486 | biostudies-literature | 2020 Sep

REPOSITORIES: biostudies-literature

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Characterizing and classifying neuroendocrine neoplasms through microRNA sequencing and data mining.

Nanayakkara Jina J Tyryshkin Kathrin K Yang Xiaojing X Wong Justin J M JJM Vanderbeck Kaitlin K Ginter Paula S PS Scognamiglio Theresa T Chen Yao-Tseng YT Panarelli Nicole N Cheung Nai-Kong NK Dijk Frederike F Ben-Dov Iddo Z IZ Kim Michelle Kang MK Singh Simron S Morozov Pavel P Max Klaas E A KEA Tuschl Thomas T Renwick Neil N

NAR cancer 20200715 3

Neuroendocrine neoplasms (NENs) are clinically diverse and incompletely characterized cancers that are challenging to classify. MicroRNAs (miRNAs) are small regulatory RNAs that can be used to classify cancers. Recently, a morphology-based classification framework for evaluating NENs from different anatomical sites was proposed by experts, with the requirement of improved molecular data integration. Here, we compiled 378 miRNA expression profiles to examine NEN classification through comprehensi ...[more]

PMID: 32743554

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Project description:Background: Neuroendocrine neoplasms (NENs) are a heterogeneous group of neoplasms that span from well-differentiated neuroendocrine tumors (NETs) to highly aggressive neoplasms classified as neuroendocrine carcinomas (NECs). The genomic landscape of NENs has not been well studied. The aim of this study is to confirm the feasibility of next generation sequencing (NGS) testing circulating tumor DNA (ctDNA) in patients with NENs and characterize common alterations in the genomic landscape. Results: Of the 320 NEN patients, 182 (57%) were male with a median age of 63 years (range: 8-93) years. Tumor type included pancreatic NET (N = 165, 52%), gastrointestinal NEC (N = 52, 16%), large cell lung NEC (N = 21, 7%), nasopharyngeal NEC (N = 16, 5%) and NEC/NET not otherwise specified (N = 64, 20%). ctDNA NGS testing was performed on 338 plasma samples; 14 patients had testing performed twice and 2 patients had testing performed three times. Genomic alterations were defined in 280 (87.5%) samples with a total of 1,012 alterations identified after excluding variants of uncertain significance (VUSs) and synonymous mutations. Of the 280 samples with alterations, TP53 associated genes were most commonly altered (N = 145, 52%), followed by KRAS (N = 61, 22%), EGFR (N = 33, 12%), PIK3CA (N = 30, 11%), BRAF (N = 28, 10%), MYC (N = 28, 10%), CCNE1 (N = 28, 10%), CDK6 (N = 22, 8%), RB1 (N = 19, 7%), NF1 (N = 19, 7%), MET (N = 19, 7%), FGFR1 (N = 19, 7%), APC (N = 19, 7%), ERBB2 (N = 16, 6%) and PTEN (N = 14, 5%). Conclusions: Evaluation of ctDNA was feasible among individuals with NEN. Liquid biopsies are non-invasive methods that can provide personalized options for targeted therapies in NEN patients. Patients and Methods: Molecular alterations in 338 plasma samples from 320 patients with NEN were evaluated using clinical-grade NGS of ctDNA (Guardant360®) across multiple institutions. The test detects single nucleotide variants in 54-73 genes, copy number amplifications, fusions, and indels in selected genes.

Project description:BackgroundThe esophageal mixed neuroendocrine-non-neuroendocrine neoplasm (MiNEN) is an extremely rare but poor prognosis tumor.ObjectivesThis retrospective study aimed to analyze the clinical characteristics of MiNEN and to investigate postoperative survival and prognostic factors.DesignThis retrospective study analyzed 69 patients diagnosed with esophageal MiNEN at two major esophageal cancer centers in China from January 2000 to December 2021.MethodsWe assessed demographic data, tumor characteristics, treatment modalities, and survival outcomes. Statistical analyses included Kaplan-Meier survival curves and Cox regression models to evaluate prognostic factors.ResultsThe most common histological types were combinations of small-cell carcinoma and squamous carcinoma (91.3%). The correct diagnostic rate of preoperative pathologic biopsy was only 4.3%. The median overall survival (OS) was 24.0 months, and disease-free survival (DFS) was 16.6 months. The 1-, 3-, and 5-year survival rates were 84.1%, 34.8%, and 25.3%, respectively. A peak period of recurrence or metastasis occurs in the first year after surgery, and regional lymph node recurrence is the main route of postoperative recurrence or metastasis. Tumor size, T-stage, N-stage, and tumor, lymph node, metastasis (TNM) stage were significant prognostic factors. Subgroup analyses showed that in patients with limited-stage MiNEN in stages I-III, the postoperative adjuvant treatment modality failed to improve OS and DFS compared with surgery alone. Postoperative adjuvant therapy also failed to prolong OS and DFS in patients with lymph node-positive MiNEN. No significant survival benefits were observed with different surgical techniques or adjuvant chemotherapy regimens.ConclusionEsophageal MiNEN has aggressive behavior and a poor prognosis. In China, the pathologic type of esophageal MiNEN may be dominated by a combination of small-cell carcinoma and squamous carcinoma. Early-stage disease significantly correlated with improved survival outcomes. Current treatment protocols, similar to those for other esophageal cancers, show limited efficacy in improving patient survival.

Project description:IntroductionCalcitonin-producing pancreatic neuroendocrine neoplasms (CT-pNENs) are an extremely rare clinical entity, with approximately 60 cases reported worldwide. While CT-pNENs can mimic the clinical and diagnostic features of medullary thyroid carcinoma, their molecular profile is poorly understood.MethodsWhole-exome sequencing (WES) was performed on tumor and corresponding serum samples of five patients with increased calcitonin serum levels and histologically validated calcitonin-positive CT-pNENs. cBioPortal analysis and DAVID gene enrichment analysis were performed to identify dysregulated candidate genes compared to control databases. Immunohistochemistry was used to detect the protein expression of MUC4 and MUC16 in CT-pNEN specimens.ResultsMutated genes known in the literature in pNENs like MEN1 (35% of cases), ATRX (18-20% of cases) and PIK3CA (1.4% of cases) were identified in cases of CT-pNENs. New somatic SNVs in ATP4A, HES4, and CAV3 have not been described in CT- pNENs, yet. Pathogenic germline mutations in FGFR4 and DPYD were found in three of five cases. Mutations of CALCA (calcitonin) and the corresponding receptor CALCAR were found in all five tumor samples, but none of them resulted in protein sequelae or clinical relevance. All five tumor cases showed single nucleotide variations (SNVs) in MUC4, and four cases showed SNVs in MUC16, both of which were membrane-bound mucins. Immunohistochemistry showed protein expression of MUC4 in two cases and MUC16 in one case, and the liver metastasis of a third case was double positive for MUC4 and MUC16. The homologous recombination deficiency (HRD) score of all tumors was low.DiscussionCT-pNENs have a unique molecular signature compared to other pNEN subtypes, specifically involving the FGFR4, DPYD, MUC4, MUC16 and the KRT family genes. However, a major limitation of our study was the relative small number of only five cases. Therefore, our WES data should be interpreted with caution and the mutation landscape in CT-pNENs needs to be verified by a larger number of patients. Further research is needed to explain differences in pathogenesis compared with other pNENs. In particular, multi-omics data such as RNASeq, methylation and whole genome sequencing could be informative.

Dataset Information

Characterizing and classifying neuroendocrine neoplasms through microRNA sequencing and data mining.

Publications

Characterizing and classifying neuroendocrine neoplasms through microRNA sequencing and data mining.

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