Mouse Models of Breast Cancer Share Amplification and Deletion Events with Human Breast Cancer

Rennhack, Jonathan; To, Briana; Wermuth, Harrison R.; Andrechek, Eran R.

doi:10.1007/s10911-017-9374-y

Cited by 17 publications

(20 citation statements)

References 55 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…For instance, significant gene-expression heterogeneity has been observed in both MMTV-Myc and MMTV-Met transgenic mice, with noted similarity to human breast cancer [ 84–86 ]. Moving past gene expression, the same data have been used to predict copy number alterations across numerous transgenic mouse models, revealing potential driver events shared between mouse and human breast cancer [ 87 ]. In addition to the basic characterization of the mouse models, recent studies have shown a promising role for transgenic mice in development of treatment.…”

Section: Development Of New Targeted Therapies and Beyondmentioning

confidence: 99%

Triple-Negative Breast Cancer and the Potential for Targeted Therapy

2017

View full text Add to dashboard Cite

Breast cancer is composed of several well-recognized subtypes including estrogen receptor, progesterone receptor and HER2 triple-negative breast cancer (TNBC). Without available targeted therapy options, standard of care for TNBC remains chemotherapy. It is of interest to note that TNBC tumors generally have better responses to chemotherapy compared with other subtypes. However, patients without complete response account for approximately 80% of TNBC. Mounting evidence suggests significant heterogeneity within the TNBC subtype, and studies have focused on genetic targets with high rates of altered expression. Recent studies suggest clear possibilities for benefits from targeted therapy in TNBC. In this review, we summarize studies of targeted therapy, including within mouse models, and discuss their applications in the development of combinatorial treatments to treat TNBC.

show abstract

Section: Development Of New Targeted Therapies and Beyondmentioning

confidence: 99%

Triple-Negative Breast Cancer and the Potential for Targeted Therapy

2017

View full text Add to dashboard Cite

show abstract

“…Expanding upon these findings with additional tumor models and samples, numerous reports have documented mouse and human counterparts at the level of gene expression [ 8 – 12 ]. In addition, copy number variation at the chromosome [ 13 ]and gene level [ 14 ]has been predicted from expression data and examined similarity to human breast cancer. The gene level CNV predictions demonstrated that chromosomal alterations were associated with histological subtypes[ 14 ].…”

Section: Introductionmentioning

confidence: 99%

“…In addition, copy number variation at the chromosome [ 13 ]and gene level [ 14 ]has been predicted from expression data and examined similarity to human breast cancer. The gene level CNV predictions demonstrated that chromosomal alterations were associated with histological subtypes[ 14 ]. With gene expression similarities to human breast cancer, a critical need remains to address how the tumor histology of mouse mammary tumors is related to gene expression programs.…”

Section: Introductionmentioning

confidence: 99%

Histological subtypes of mouse mammary tumors reveal conserved relationships to human cancers

2018

Self Cite

View full text Add to dashboard Cite

Human breast cancer has been characterized by extensive transcriptional heterogeneity, with dominant patterns reflected in the intrinsic subtypes. Mouse models of breast cancer also have heterogeneous transcriptomes and we noted that specific histological subtypes were associated with particular subsets. We hypothesized that unique sets of genes define each tumor histological type across mouse models of breast cancer. Using mouse models that contained both gene expression data and expert pathologist classification of tumor histology on a sample by sample basis, we predicted and validated gene expression signatures for Papillary, EMT, Microacinar and other histological subtypes. These signatures predict known histological events across murine breast cancer models and identify counterparts of mouse mammary tumor types in subtypes of human breast cancer. Importantly, the EMT, Adenomyoepithelial, and Solid signatures were predictive of clinical events in human breast cancer. In addition, a pan-cancer comparison revealed that the histological signatures were active in a variety of human cancers such as lung, oral, and esophageal squamous tumors. Finally, the differentiation status and transcriptional activity implicit within these signatures was identified. These data reveal that within tumor histology groups are unique gene expression profiles of differentiation and pathway activity that stretch well beyond the transgenic initiating events and that have clear applicability to human cancers. As a result, our work provides a predictive resource and insights into possible mechanisms that govern tumor heterogeneity.

show abstract

“…Several studies published in recent years have compared genetically engineered breast cancer mouse model tumor transcriptomes with human disease (25)(26)(27), delineated disease progression observed in the mouse (28), and provided characterization of murine cell line orthotopic injection models (11). Here, we have expanded these efforts to interrogate MSGE in 18 different models of metastatic breast cancer, including cells in culture, intravenous injection and orthotopic implantation of cells, and GEMMs.…”

Section: Discussionmentioning

confidence: 99%

Metastasis-Specific Gene Expression in Autochthonous and Allograft Mouse Mammary Tumor Models: Stratification and Identification of Targetable Signatures

Ross

Szczepanek

Lee

et al. 2020

Molecular Cancer Research

View full text Add to dashboard Cite

Breast cancer metastasis is a leading cause of cancer-related death of women in the United States. A hurdle in advancing metastasis-targeted intervention is the phenotypic heterogeneity between primary and secondary lesions. To identify metastasisspecific gene expression profiles we performed RNA-sequencing of breast cancer mouse models; analyzing metastases from models of various drivers and routes. We contrasted the models and identified common, targetable signatures. Allograft models exhibited more mesenchymal-like gene expression than genetically engineered mouse models (GEMM), and primary culturing of GEMM-derived metastatic tissue induced mesenchymal-like gene expression. In addition, metastasis-specific transcriptomes differed between tail vein and orthotopic injection of the same cell line. Gene expression common to models of spontaneous metastasis included sildenafil response and nicotine degradation pathways. Strikingly, in vivo sildenafil treatment significantly reduced metastasis by 54%, while nicotine significantly increased metastasis by 46%. These data suggest that (i) actionable metastasis-specific pathways can be readily identified, (ii) already available drugs may have great potential to alleviate metastatic incidence, and (iii) metastasis may be influenced greatly by lifestyle choices such as the choice to consume nicotine products. In summary, while mouse models of breast cancer metastasis vary in ways that must not be ignored, there are shared features that can be identified and potentially targeted therapeutically. Implications: The data we present here exposes critical variances between preclinical models of metastatic breast cancer and identifies targetable pathways integral to metastatic spread.

show abstract

Mouse Models of Breast Cancer Share Amplification and Deletion Events with Human Breast Cancer

Cited by 17 publications

References 55 publications

Triple-Negative Breast Cancer and the Potential for Targeted Therapy

Triple-Negative Breast Cancer and the Potential for Targeted Therapy

Histological subtypes of mouse mammary tumors reveal conserved relationships to human cancers

Metastasis-Specific Gene Expression in Autochthonous and Allograft Mouse Mammary Tumor Models: Stratification and Identification of Targetable Signatures

Contact Info

Product

Resources

About