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Generation and molecular characterization of pancreatic cancer patient-derived xenografts reveals their heterologous nature

Pancreatic ductal adenocarcinoma (PDAC) is the most challenging type of cancer to treat, with a 5-year survival rate of <10%. Furthermore, because of the large portion of the inoperable cases, it is difficult to obtain specimens to study the biology of the tumors. Therefore, a patient-derived xen...

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Autores principales: Jung, Jaeyun, Lee, Cue Hyunkyu, Seol, Hyang Sook, Choi, Yeon Sook, Kim, Eunji, Lee, Eun Ji, Rhee, Je-Keun, Singh, Shree Ram, Jun, Eun Sung, Han, Buhm, Hong, Seung Mo, Kim, Song Cheol, Chang, Suhwan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Impact Journals LLC 2016
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5308744/
https://www.ncbi.nlm.nih.gov/pubmed/27613834
http://dx.doi.org/10.18632/oncotarget.11530
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author Jung, Jaeyun
Lee, Cue Hyunkyu
Seol, Hyang Sook
Choi, Yeon Sook
Kim, Eunji
Lee, Eun Ji
Rhee, Je-Keun
Singh, Shree Ram
Jun, Eun Sung
Han, Buhm
Hong, Seung Mo
Kim, Song Cheol
Chang, Suhwan
author_facet Jung, Jaeyun
Lee, Cue Hyunkyu
Seol, Hyang Sook
Choi, Yeon Sook
Kim, Eunji
Lee, Eun Ji
Rhee, Je-Keun
Singh, Shree Ram
Jun, Eun Sung
Han, Buhm
Hong, Seung Mo
Kim, Song Cheol
Chang, Suhwan
author_sort Jung, Jaeyun
collection PubMed
description Pancreatic ductal adenocarcinoma (PDAC) is the most challenging type of cancer to treat, with a 5-year survival rate of <10%. Furthermore, because of the large portion of the inoperable cases, it is difficult to obtain specimens to study the biology of the tumors. Therefore, a patient-derived xenograft (PDX) model is an attractive option for preserving and expanding these tumors for translational research. Here we report the generation and characterization of 20 PDX models of PDAC. The success rate of the initial graft was 74% and most tumors were re-transplantable. Histological analysis of the PDXs and primary tumors revealed a conserved expression pattern of p53 and SMAD4; an exome single nucleotide polymorphism (SNP) array and Comprehensive Cancer Panel showed that PDXs retained over 94% of cancer-associated variants. In addition, Polyphen2 and the Sorting Intolerant from Tolerant (SIFT) prediction identified 623 variants among the functional SNPs, highlighting the heterologous nature of pancreatic PDXs; an analysis of 409 tumor suppressor genes and oncogenes in Comprehensive Cancer Panel revealed heterologous cancer gene mutation profiles for each PDX-primary tumor pair. Altogether, we expect these PDX models are a promising platform for screening novel therapeutic agents and diagnostic markers for the detection and eradication of PDAC.
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spelling pubmed-53087442017-03-09 Generation and molecular characterization of pancreatic cancer patient-derived xenografts reveals their heterologous nature Jung, Jaeyun Lee, Cue Hyunkyu Seol, Hyang Sook Choi, Yeon Sook Kim, Eunji Lee, Eun Ji Rhee, Je-Keun Singh, Shree Ram Jun, Eun Sung Han, Buhm Hong, Seung Mo Kim, Song Cheol Chang, Suhwan Oncotarget Research Paper Pancreatic ductal adenocarcinoma (PDAC) is the most challenging type of cancer to treat, with a 5-year survival rate of <10%. Furthermore, because of the large portion of the inoperable cases, it is difficult to obtain specimens to study the biology of the tumors. Therefore, a patient-derived xenograft (PDX) model is an attractive option for preserving and expanding these tumors for translational research. Here we report the generation and characterization of 20 PDX models of PDAC. The success rate of the initial graft was 74% and most tumors were re-transplantable. Histological analysis of the PDXs and primary tumors revealed a conserved expression pattern of p53 and SMAD4; an exome single nucleotide polymorphism (SNP) array and Comprehensive Cancer Panel showed that PDXs retained over 94% of cancer-associated variants. In addition, Polyphen2 and the Sorting Intolerant from Tolerant (SIFT) prediction identified 623 variants among the functional SNPs, highlighting the heterologous nature of pancreatic PDXs; an analysis of 409 tumor suppressor genes and oncogenes in Comprehensive Cancer Panel revealed heterologous cancer gene mutation profiles for each PDX-primary tumor pair. Altogether, we expect these PDX models are a promising platform for screening novel therapeutic agents and diagnostic markers for the detection and eradication of PDAC. Impact Journals LLC 2016-08-23 /pmc/articles/PMC5308744/ /pubmed/27613834 http://dx.doi.org/10.18632/oncotarget.11530 Text en Copyright: © 2016 Jung et al. http://creativecommons.org/licenses/by/2.5/ This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Paper
Jung, Jaeyun
Lee, Cue Hyunkyu
Seol, Hyang Sook
Choi, Yeon Sook
Kim, Eunji
Lee, Eun Ji
Rhee, Je-Keun
Singh, Shree Ram
Jun, Eun Sung
Han, Buhm
Hong, Seung Mo
Kim, Song Cheol
Chang, Suhwan
Generation and molecular characterization of pancreatic cancer patient-derived xenografts reveals their heterologous nature
title Generation and molecular characterization of pancreatic cancer patient-derived xenografts reveals their heterologous nature
title_full Generation and molecular characterization of pancreatic cancer patient-derived xenografts reveals their heterologous nature
title_fullStr Generation and molecular characterization of pancreatic cancer patient-derived xenografts reveals their heterologous nature
title_full_unstemmed Generation and molecular characterization of pancreatic cancer patient-derived xenografts reveals their heterologous nature
title_short Generation and molecular characterization of pancreatic cancer patient-derived xenografts reveals their heterologous nature
title_sort generation and molecular characterization of pancreatic cancer patient-derived xenografts reveals their heterologous nature
topic Research Paper
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5308744/
https://www.ncbi.nlm.nih.gov/pubmed/27613834
http://dx.doi.org/10.18632/oncotarget.11530
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