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Dilley, William G.; Kalyanaraman, S.; Verma, Sulekha; Cobb, J. Perren; Laramie, Jason M.; Lairmore, Terry C.

doi:10.1186/1476-4598-4-9

Cited by 57 publications

(14 citation statements)

References 70 publications

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“…The fold changes observed were relatively modest, ranging from 0.47 (downregulated in WHO-3) to 2.26 (upregulated in WHO-3 group), and did not overlap significantly with genes discussed above by Missiaglia or Duerr et al Since these studies and others 20, 21, 22 using varying genomic expression array platforms have identified different, non-overlapping genes thought to be of importance, we decided to focus our efforts on one important class of genes known to play a role in these tumors using a qPCR based strategy in order to develop a reliable and predictive model. Other reasons for choosing this strategy include the fact that studies comparing qPCR to microarray results have shown and increased sensitivity of the former, that members of the GPCR group emerged as candidates with differential expression in our exon arrays and in Drozdov’s study, and this class of genes is deemed as one of the most promising for development of new therapeutic agents by the pharmaceutical industry 23 .…”

Section: Discussionmentioning

confidence: 56%

Differentiation of small bowel and pancreatic neuroendocrine tumors by gene-expression profiling

Carr

Boese

Spanheimer

et al. 2012

Surgery

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Section: Discussionmentioning

confidence: 56%

Differentiation of small bowel and pancreatic neuroendocrine tumors by gene-expression profiling

Carr

Boese

Spanheimer

et al. 2012

Surgery

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“…Any future studies, should, in addition, assess whether medications or conditions associated with non-specific elevations in neuroendocrine cell numbers, e.g., PPIs, increase transcript expression. Given the similarities in biology (i.e., expression of receptors, pathways involved in secretion, molecular pathways e.g., MEN-I) [71]–[73] between GEP-NENs and other NENs e.g., pheochromytomas or medullary thyroid cancers, it would be useful to assess whether the PCR test can accurately identify these lesions. The existence of tumors with a significant neuroendocrine component e.g., prostate tumors [74] or colorectal cancers [75], [76], provides additional clinical samples in which to evaluate the efficacy of the PCR test.…”

Section: Discussionmentioning

confidence: 99%

The Identification of Gut Neuroendocrine Tumor Disease by Multiple Synchronous Transcript Analysis in Blood

2013

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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.

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“…The gene expression profile for neuroendocrine tumors in patients with the MEN1 syndrome was recently reported [44]. The syndrome is characterized by neuroendocrine tumors of the parathyroids, pituitary, and pancreatic islets.…”

Section: Discussionmentioning

confidence: 99%

Gene Expression Patterns in Pancreatic Tumors, Cells and Tissues

et al. 2007

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BackgroundCancers of the pancreas originate from both the endocrine and exocrine elements of the organ, and represent a major cause of cancer-related death. This study provides a comprehensive assessment of gene expression for pancreatic tumors, the normal pancreas, and nonneoplastic pancreatic disease.Methods/ResultsDNA microarrays were used to assess the gene expression for surgically derived pancreatic adenocarcinomas, islet cell tumors, and mesenchymal tumors. The addition of normal pancreata, isolated islets, isolated pancreatic ducts, and pancreatic adenocarcinoma cell lines enhanced subsequent analysis by increasing the diversity in gene expression profiles obtained. Exocrine, endocrine, and mesenchymal tumors displayed unique gene expression profiles. Similarities in gene expression support the pancreatic duct as the origin of adenocarcinomas. In addition, genes highly expressed in other cancers and associated with specific signal transduction pathways were also found in pancreatic tumors.ConclusionThe scope of the present work was enhanced by the inclusion of publicly available datasets that encompass a wide spectrum of human tissues and enabled the identification of candidate genes that may serve diagnostic and therapeutic goals.

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Untitled

Cited by 57 publications

References 70 publications

Differentiation of small bowel and pancreatic neuroendocrine tumors by gene-expression profiling

Differentiation of small bowel and pancreatic neuroendocrine tumors by gene-expression profiling

The Identification of Gut Neuroendocrine Tumor Disease by Multiple Synchronous Transcript Analysis in Blood

Gene Expression Patterns in Pancreatic Tumors, Cells and Tissues

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