scholarly journals Web-based access to mouse models of human cancers: the Mouse Tumor Biology (MTB) Database

2001 ◽  
Vol 29 (1) ◽  
pp. 95-97 ◽  
Author(s):  
C. J. Bult
Keyword(s):  
Mouse Models ◽  
Tumor Biology ◽  
Mouse Tumor ◽  
Web Based ◽  
Human Cancers

scholarly journals How Genetically Engineered Mouse Tumor Models Provide Insights Into Human Cancers

2011 ◽  
Vol 29 (16) ◽  
pp. 2273-2281 ◽  
Author(s):  
Katerina Politi ◽  
William Pao
Keyword(s):  
Mouse Models ◽  
Cancer Biology ◽  
Human Cancer ◽  
Genetically Engineered ◽  
Mouse Tumor ◽  
Tumor Models ◽  
Genetically Engineered Mouse Models ◽  
Human Cancers ◽  
Chemically Induced

Genetically engineered mouse models (GEMMs) of human cancer were first created nearly 30 years ago. These early transgenic models demonstrated that mouse cells could be transformed in vivo by expression of an oncogene. A new field emerged, dedicated to generating and using mouse models of human cancer to address a wide variety of questions in cancer biology. The aim of this review is to highlight the contributions of mouse models to the diagnosis and treatment of human cancers. Because of the breadth of the topic, we have selected representative examples of how GEMMs are clinically relevant rather than provided an exhaustive list of experiments. Today, as detailed here, sophisticated mouse models are being created to study many aspects of cancer biology, including but not limited to mechanisms of sensitivity and resistance to drug treatment, oncogene cooperation, early detection, and metastasis. Alternatives to GEMMs, such as chemically induced or spontaneous tumor models, are not discussed in this review.

scholarly journals Mouse Tumor Biology (MTB): a database of mouse models for human cancer

2014 ◽  
Vol 43 (D1) ◽  
pp. D818-D824 ◽  
Author(s):  
Carol J. Bult ◽  
Debra M. Krupke ◽  
Dale A. Begley ◽  
Joel E. Richardson ◽  
Steven B. Neuhauser ◽  
...  
Keyword(s):  
Mouse Models ◽  
Human Cancer ◽  
Tumor Biology ◽  
Mouse Tumor

scholarly journals Abstract 5102: Identifying relevant mouse models of human cancer using the mouse tumor biology database (MTB)

2018 ◽  
Author(s):  
Dale A. Begley ◽  
Debra M. Krupke ◽  
Steven B. Neuhauser ◽  
Joel E. Richardson ◽  
John P. Sundberg ◽  
...  
Keyword(s):  
Mouse Models ◽  
Human Cancer ◽  
Tumor Biology ◽  
Mouse Tumor

scholarly journals Identifying mouse models for skin cancer using the Mouse Tumor Biology Database

2014 ◽  
Vol 23 (10) ◽  
pp. 761-763 ◽  
Author(s):  
Dale A. Begley ◽  
Debra M. Krupke ◽  
Steven B. Neuhauser ◽  
Joel E. Richardson ◽  
Paul N. Schofield ◽  
...  
Keyword(s):  
Skin Cancer ◽  
Mouse Models ◽  
Tumor Biology ◽  
Mouse Tumor

scholarly journals The Mouse Tumor Biology Database: A Comprehensive Resource for Mouse Models of Human Cancer

2017 ◽  
Vol 77 (21) ◽  
pp. e67-e70 ◽  
Author(s):  
Debra M. Krupke ◽  
Dale A. Begley ◽  
John P. Sundberg ◽  
Joel E. Richardson ◽  
Steven B. Neuhauser ◽  
...  
Keyword(s):  
Mouse Models ◽  
Human Cancer ◽  
Tumor Biology ◽  
Mouse Tumor

scholarly journals Finding mouse models of human lymphomas and leukemia's using the Jackson laboratory mouse tumor biology database

2015 ◽  
Vol 99 (3) ◽  
pp. 533-536 ◽  
Author(s):  
Dale A. Begley ◽  
John P. Sundberg ◽  
Debra M. Krupke ◽  
Steven B. Neuhauser ◽  
Carol J. Bult ◽  
...  
Keyword(s):  
Mouse Models ◽  
Laboratory Mouse ◽  
Tumor Biology ◽  
Mouse Tumor ◽  
Jackson Laboratory

scholarly journals Electronic access to mouse tumor data: the Mouse Tumor Biology Database (MTB) project

1999 ◽  
Vol 27 (1) ◽  
pp. 99-105 ◽  
Author(s):  
C. J. Bult ◽  
D. M. Krupke ◽  
J. T. Eppig
Keyword(s):  
Tumor Biology ◽  
Mouse Tumor ◽  
Electronic Access

scholarly journals Multiomics Analysis Reveals that GLS and GLS2 Differentially Modulate the Clinical Outcomes of Cancer

2019 ◽  
Vol 8 (3) ◽  
pp. 355 ◽  
Author(s):  
Subbroto Saha ◽  
S.M. Islam ◽  
M. Abdullah-AL-Wadud ◽  
Saiful Islam ◽  
Farman Ali ◽  
...  
Keyword(s):  
Clinical Outcomes ◽  
Methylation Status ◽  
Prognostic Biomarkers ◽  
Functional Protein ◽  
Poor Overall Survival ◽  
Web Based ◽  
Human Cancers ◽  
Multivariate Survival ◽  
Protein Partners ◽  
Relationship Of

Kidney-type glutaminase (GLS) and liver-type glutaminase (GLS2) are dysregulated in many cancers, making them appealing targets for cancer therapy. However, their use as prognostic biomarkers is controversial and remains an active area of cancer research. Here, we performed a systematic multiomic analysis to determine whether glutaminases function as prognostic biomarkers in human cancers. Glutaminase expression and methylation status were assessed and their prominent functional protein partners and correlated genes were identified using various web-based bioinformatics tools. The cross-cancer relationship of glutaminases with mutations and copy number alterations was also investigated. Gene ontology (GO) and pathway analysis were performed to assess the integrated effect of glutaminases and their correlated genes on various cancers. Subsequently, the prognostic roles of GLS and GLS2 in human cancers were mined using univariate and multivariate survival analyses. GLS was frequently over-expressed in breast, esophagus, head-and-neck, and blood cancers, and was associated with a poor prognosis, whereas GLS2 overexpression implied poor overall survival in colon, blood, ovarian, and thymoma cancers. Both GLS and GLS2 play oncogenic and anti-oncogenic roles depending on the type of cancer. The varying prognostic characteristics of glutaminases suggest that GLS and GLS2 expression differentially modulate the clinical outcomes of cancers.

scholarly journals DisruptingTP53 in mouse models of human cancers

2003 ◽  
Vol 21 (3) ◽  
pp. 321-326 ◽  
Author(s):  
John M. Parant ◽  
Guillermina Lozano
Keyword(s):  
Mouse Models ◽  
Human Cancers
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