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Modeling of Patient-Derived Xenografts in Colorectal Cancer.
Katsiampoura, Anastasia; Raghav, Kanwal; Jiang, Zhi-Qin; Menter, David G; Varkaris, Andreas; Morelli, Maria P; Manuel, Shanequa; Wu, Ji; Sorokin, Alexey V; Rizi, Bahar Salimian; Bristow, Christopher; Tian, Feng; Airhart, Susan; Cheng, Mingshan; Broom, Bradley M; Morris, Jeffrey; Overman, Michael J; Powis, Garth; Kopetz, Scott.
Afiliação
  • Katsiampoura A; Department of Gastrointestinal Medical Oncology, The University of Texas MD Anderson Cancer Center, Houston, Texas.
  • Raghav K; Department of Gastrointestinal Medical Oncology, The University of Texas MD Anderson Cancer Center, Houston, Texas.
  • Jiang ZQ; Department of Gastrointestinal Medical Oncology, The University of Texas MD Anderson Cancer Center, Houston, Texas.
  • Menter DG; Department of Gastrointestinal Medical Oncology, The University of Texas MD Anderson Cancer Center, Houston, Texas.
  • Varkaris A; Department of Genitourinary Medical Oncology, The University of Texas MD Anderson Cancer Center, Houston, Texas.
  • Morelli MP; Department of Gastrointestinal Medical Oncology, The University of Texas MD Anderson Cancer Center, Houston, Texas.
  • Manuel S; Department of Gastrointestinal Medical Oncology, The University of Texas MD Anderson Cancer Center, Houston, Texas.
  • Wu J; Department of Gastrointestinal Medical Oncology, The University of Texas MD Anderson Cancer Center, Houston, Texas.
  • Sorokin AV; Department of Gastrointestinal Medical Oncology, The University of Texas MD Anderson Cancer Center, Houston, Texas.
  • Rizi BS; Department of Gastrointestinal Medical Oncology, The University of Texas MD Anderson Cancer Center, Houston, Texas.
  • Bristow C; Department of Applied Cancer Science Institute, The University of Texas MD Anderson Cancer Center, Houston, Texas.
  • Tian F; Department of Gastrointestinal Medical Oncology, The University of Texas MD Anderson Cancer Center, Houston, Texas.
  • Airhart S; Department of Biostatistics, The University of Texas MD Anderson Cancer Center, Houston, Texas.
  • Cheng M; The Jackson Laboratory, Bar Harbor, Maine.
  • Broom BM; Department of Bioinformatics & Computational Biology, The University of Texas MD Anderson Cancer Center, Houston, Texas.
  • Morris J; Department of Biostatistics, The University of Texas MD Anderson Cancer Center, Houston, Texas.
  • Overman MJ; Department of Gastrointestinal Medical Oncology, The University of Texas MD Anderson Cancer Center, Houston, Texas.
  • Powis G; Sanford Burnham Prebys Discovery Institute, La Jolla, California.
  • Kopetz S; Department of Gastrointestinal Medical Oncology, The University of Texas MD Anderson Cancer Center, Houston, Texas. skopetz@mdanderson.org.
Mol Cancer Ther ; 16(7): 1435-1442, 2017 07.
Article em En | MEDLINE | ID: mdl-28468778
ABSTRACT
Developing realistic preclinical models using clinical samples that mirror complex tumor biology and behavior are vital to advancing cancer research. While cell line cultures have been helpful in generating preclinical data, the genetic divergence between these and corresponding primary tumors has limited clinical translation. Conversely, patient-derived xenografts (PDX) in colorectal cancer are highly representative of the genetic and phenotypic heterogeneity in the original tumor. Coupled with high-throughput analyses and bioinformatics, these PDXs represent robust preclinical tools for biomarkers, therapeutic target, and drug discovery. Successful PDX engraftment is hypothesized to be related to a series of anecdotal variables namely, tissue source, cancer stage, tumor grade, acquisition strategy, time to implantation, exposure to prior systemic therapy, and genomic heterogeneity of tumors. Although these factors at large can influence practices and patterns related to xenotransplantation, their relative significance in determining the success of establishing PDXs is uncertain. Accordingly, we systematically examined the predictive ability of these factors in establishing PDXs using 90 colorectal cancer patient specimens that were subcutaneously implanted into immunodeficient mice. Fifty (56%) PDXs were successfully established. Multivariate analyses showed tissue acquisition strategy [surgery 72.0% (95% confidence interval (CI) 58.2-82.6) vs. biopsy 35% (95% CI 22.1%-50.6%)] to be the key determinant for successful PDX engraftment. These findings contrast with current empiricism in generating PDXs and can serve to simplify or liberalize PDX modeling protocols. Better understanding the relative impact of these factors on efficiency of PDX formation will allow for pervasive integration of these models in care of colorectal cancer patients. Mol Cancer Ther; 16(7); 1435-42. ©2017 AACR.
Assuntos

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Neoplasias Colorretais / Ensaios Antitumorais Modelo de Xenoenxerto / Modelos Animais de Doenças Tipo de estudo: Guideline / Prognostic_studies Limite: Animals / Female / Humans / Male Idioma: En Ano de publicação: 2017 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Neoplasias Colorretais / Ensaios Antitumorais Modelo de Xenoenxerto / Modelos Animais de Doenças Tipo de estudo: Guideline / Prognostic_studies Limite: Animals / Female / Humans / Male Idioma: En Ano de publicação: 2017 Tipo de documento: Article