Predicting gastroenteropancreatic neuroendocrine neoplasms (GEP-NENs)

A technology for GEP-NEN and neuroendocrine tumors, applied in the field of GEP-NEN diagnosis and prognosis, can solve the problems of low sensitivity and/or specificity, inability to detect early disease, inability to treat, etc., and achieve low-cost results

Active Publication Date: 2014-01-08
YALE UNIV
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

Available methods are limited, for example, by low sensitivity and / or specificity and inability to detect early disease
GEP-NEN is often not diagnosed until it metastasizes and is often untreatable

Method used

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  • Predicting gastroenteropancreatic neuroendocrine neoplasms (GEP-NENs)
  • Predicting gastroenteropancreatic neuroendocrine neoplasms (GEP-NENs)
  • Predicting gastroenteropancreatic neuroendocrine neoplasms (GEP-NENs)

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Experimental program
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Effect test

Embodiment 1

[0361] Sample preparation, RNA extraction, real-time PCR

[0362]Normal and tumor samples were obtained for detection and determination of GEP-NEN biomarker expression levels by real-time PCR. Normal samples included twenty-seven (27) normal small intestinal (SI) mucosa samples (NML), and thirteen (13) normal human enterochromaffin (EC) cell preparations (NML_EC; by fluorescence activated cells of normal mucosa Sorting (FACS) obtained; EC cells with a purity>98% (Modlin IM et al., "The functional characterization of normal and neoplastic human enterochromaffin cells (normal and tumor human enterochromaffin cells)" JClin EndocrinolMetab2006;91(6):2340-8).

[0363] Tumor samples included fifty-three (53) primary SIGEP-NENs and twenty-one (21) corresponding liver metastases collected from a frozen biobank (all tissues were microdissected). The GEP-NEN samples were obtained from enrolled patients following a protocol approved by the Yale University Institutional Review Board. Tu...

Embodiment 2

[0397] After natural logarithm (ln) transformation, and enter After GenomicSuite, Principal Component Analysis (PCA) was performed to describe the structure of the high-dimensional expression data. PCA can visualize and compare transcript expression patterns across multiple samples (eg, normal, tumor, GEP-NEN vs. other tumors, GEP-NEN subtypes, primary vs. metastatic / malignant). PCA reduces the dimensionality of the expression data—obtained using 9-biomarker and 21-biomarker panels, respectively—to three unrelated principal components (PCs) that explain the most variation (JolliffeIT, "Principle Component Analysis) ” Springer, 1986.). PCA plotting is visualized in three-dimensional space for the first (1 st ), the second (2 nd ) and third (3 rd ) principal component assignment.

[0398] For the 9 and 21 genomes, the average expression data for multiple samples were superimposed in this PCA coordinate system. The centroid (center of mass (average expression)) of each sam...

Embodiment 3

[0409] Statistical analysis and tumor profiling were performed on the transformed expression data obtained from the 9- and 21 -biomarker panels as described above.

[0410] 9- Biomarker panel

[0411] Mean (M) transcript expression levels and standard deviation (SD) for the 9-biomarker panel were calculated for primary tumor subtypes and normal EC cell preparations. The average normal expression of the biomarkers is: CgA (M 正常 =-9.2,SD=4.2), Ki-67(M 正常 =-4.5, SD 正常 =1.1), Kiss1(M 正常 =-4.0, SD 正常 =3.2), NAP1L1 (M 正常 =-8.3, SD 正常 =1.1), NRP2(M 正常 =-9.3, SD=3.8) and survivin (M 正常 =-6.0, SD 正常 = 1.0), which were significantly different from the mean expression in primary tumors both overall (all tumors) and between individual subtypes. See p-values ​​and fold changes (FC) listed in Table 2 below. Transcript expression level detection in a subset of samples (n=35) was again evaluated. The data are highly correlated (R 2 =0.93, p=0.001), showing that the method is high...

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Abstract

Described are embodiments related to gastroenteropancreatic neuroendocrine neoplasms (GEP-NEN) biomarkers and agents, systems, and kits for detecting the same, and associated GEP-NEN diagnostic, prognostic, and predictive methods and uses thereof, such as detection, prediction, staging, profiling, classification, and monitoring treatment efficacy and other outcomes.

Description

[0001] Cross References to Related Applications [0002] This application claims the benefit of US Provisional Application No. 61 / 448,137, filed March 1, 2011, the disclosure of which is incorporated herein by reference in its entirety for all purposes. [0003] References to Sequence Listings Submitted via EFS-Web [0004] The entire contents of the following sequence listing submitted electronically via the USPTO (United States Patent and Trademark Office) EFS-WEB server as described in MPEP § 1730 II.B.2(a)(C) are hereby incorporated by reference in their entirety for all purposes. The sequence listing in the electronic submission text file is identified as follows: [0005] file name build date size (bytes) 669102000140Seqlist February 28, 2012 447,716 bytes technical field [0006] The invention described herein relates to gastroenteropancreatic neuroendocrine neoplasm (GEP-NEN) biomarkers and reagents, systems and kits for detect...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): C12Q1/68
CPCC12Q2600/112G01N33/57438C12Q1/6886C12Q2600/118C12Q2600/158G01N33/68
Inventor I·M·莫德林
Owner YALE UNIV
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