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

Kerr, Sarah E.; Schnabel, Catherine A.; Sullivan, Peggy; Zhang, Yi; Huang, Vivian J.; Erlander, Mark G.; Brachtel, Elena F.; Dry, Sarah M.

doi:10.1038/modpathol.2013.105

Cited by 32 publications

(30 citation statements)

References 81 publications

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“…duodenum, jejunoileum, gastric or colorectal). (9) While this profiler performed well in NETs, it is inefficient if the diagnosis of a NET is already suspected, as the entire panel of 92 genes is amplified for every sample, even though only a small subset of the genes tested actually contribute to NET identification.…”

Section: Discussionmentioning

confidence: 99%

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

Maxwell

Sherman

Stashek

et al. 2014

Surgery

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Introduction The primary tumor site is unknown prior to treatment in approximately 20% of small bowel (SBNET) and pancreatic (PNET) neuroendocrine tumors despite extensive workup. It can be difficult to discern a PNET from an SBNET on hematoxylin and eosin (H&E) 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 surgical specimens and stained with up to 7 antibodies used in the NET-specific IHC algorithm. Expression of 4 genes for differentiating between PNETs and SBNETs was determined by qPCR and then used in a previously validated gene expression classifier (GEC) algorithm designed to determine the primary site from gastrointestinal (GI) NET metastases. Results The accuracy of the IHC algorithm in identifying the primary tumor site from a set of 37 metastases was 89.1%, with only 1 incorrect call. Three other samples were indeterminate due to pan-negative staining. The GEC’s accuracy in a set of 136 metastases was 94.1%. It identified the primary tumor site in all cases where IHC failed. Conclusion Performing IHC, followed by GEC for indeterminate cases, accurately identifies the primary site in SBNET and PNET metastases in virtually all patients.

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Section: Discussionmentioning

confidence: 99%

“…This method takes advantage of unique mRNA expression patterns in different tumors, and over the past few years, a handful of classifiers have become available commercially,(5, 9) though none are marketed specifically for neuroendocrine tumors. Our group recently created a GEC designed to distinguish PNET from SBNET metastases.…”

Section: Introductionmentioning

confidence: 99%

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

Maxwell

Sherman

Stashek

et al. 2014

Surgery

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“…Archival biopsy specimens were obtained and, when possible, additional biopsies were performed. Biopsies were tested by a 92-gene MCCA (reverse transcriptase-polymerase chain reaction (RT-PCR) mRNA, CancerTYPE ID, bioTheranostics, Inc., San Diego, CA, USA), as previously described [5][6][7][8][9][10]. When feasible (if remaining biopsy specimens were available or repeat biopsies were performed), additional evaluation of the tumors was carried out after obtaining the MCCA results, in an attempt to confirm or substantiate the MCCA diagnoses.…”

Section: Methodsmentioning

confidence: 99%

Poorly Differentiated Neoplasms of Unknown Primary Site: Diagnostic Usefulness of a Molecular Cancer Classifier Assay

et al. 2015

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“…Kerr [19] et al used a 92-gene cancer classifier investigating 75 NET of various origins. Although primary ovarian carcinoid tumors were not included in this study, the authors found 4 genes with promising discriminatory value for tumor typing and 15 genes for tumor subtyping of gastrointestinal, pulmonary, pancreas, thyroid, or skin origins.…”

Section: Discussionmentioning

confidence: 99%

Ki67 Proliferative Index in Carcinoid Tumors Involving Ovary

et al. 2018

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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)(1996)(1997)(1998)(1999)(2000)(2001)(2002)(2003)(2004)(2005)(2006)(2007)(2008)(2009)(2010)(2011)(2012)(2013)(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.

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

Cited by 32 publications

References 81 publications

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

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

Poorly Differentiated Neoplasms of Unknown Primary Site: Diagnostic Usefulness of a Molecular Cancer Classifier Assay

Ki67 Proliferative Index in Carcinoid Tumors Involving Ovary

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