Genetically engineered mouse (GEM) models have provided a wealth of information regarding the genetic causes of cancer, but their utility for preclinical drug evaluation has not been well examined. Here we have used three mammary tumor GEM models that represent three human breast cancer subtypes and have evaluated their sensitivities to chemotherapy and to three biologically targeted agents. We have selected three mouse models that resemble human breast cancer subtypes based upon common gene expression profiles; Basal-like tumors are represented by the C3(1)-T-antigen (C3-TAg) model, Luminal B tumors are represented by the MMTV-Neu model, and the P53 null transplant T11 line represents the newly described Claudin-low breast tumor subtype. On each of these models we have tested the therapeutic efficacy of: four chemotherapeutics (doxorubicin, carboplatin, paclitaxel, and cyclophosphamide), two chemotherapy combinations (carboplatin/paclitaxel and doxorubicin/cyclophosphamide), and three biologically targeted agents (erlotinib, lapatinib, and ABT-888, alone and combined with selected chemotherapies). The results from individual models were as follows: The MMTV-Neu tumors were sensitive to the single-agent chemotherapeutics carboplatin and cyclophosphamide, and cyclophosphamide dramatically increased overall survival of the MMTV-Neu mice. The targeted agents lapatinib and erlotinib were extremely effective; lapatinib produced a near complete regression in every MMTV-Neu mouse tested and both compounds lead to greatly increased survival times. In the Claudin-low T11 line, the tumors were very sensitive to cyclophosphamide. Alone and in combination with doxorubicin, cyclophosphamide was the only chemotherapeutic able to successfully cause tumor regression in this model. None of the biological inhibitors were effective as single agents in these mice, nor were they effective in combination with chemotherapeutics other than cyclophosphamide In the C3-TAg basal-like model, carboplatin alone and in combination with other drugs caused volume reduction in some of the tumors. Erlotinib was able to cause volume reductions in a third of the treated C3-Tag tumors, which revealed a heterogeneity of response within this GEM strain. None of the single agent treatments significantly increased overall survival in these mice. Those combination treatments that were effective showed a range of responses from tumor regression to slowed progression. Finally, we closely examined the heterogeneous responses of the C3-Tag tumors to carboplatin/paclitaxel and performed expression profiling of sensitive and resistant tumors. We identified a gene signature from these treated mouse tumors that was able to predict pathological complete response of human patients receiving multiagent taxane-containing neoadjuvant chemotherapy regimens. These results show that genomically selected GEM models can recapitulate findings seen in human tumors (like lapatinib responsiveness in HER2+ tumors and carboplatin sensitivity in basal-like tumors) and that GEM models can potentially be used to develop biomarkers and to test new drug combinations prior to their being tested in humans. Citation Information: Cancer Res 2011;71(24 Suppl):Abstract nr P4-03-03.
Background: The molecular characterization of primary breast cancers has led to signatures identifying risk of future metastasis and survival; however the underlying biology driving metastasis development is largely unknown. Methods: Utilizing a Rapid Autopsy Program, we have collected 61 metastatic breast cancer tumors from 7 individuals (4 triple negative, 2 HER2+, 1 ER+/HER2-) including primary tumors and 3-6 metastases/patient. We performed mRNA and DNA exome sequencing. We next used DawnRank, a novel network-based method that integrates DNA and RNA data to identify computationally determined "driver" genes (i.e. a DNA variant that significantly alters its gene expression-network) in each individual sample. Phylogenetic tree and clonal analysis were also performed, with the computationally determined drivers mapped onto these trees. Results: The breast cancer primaries were molecularly subtyped as 5 Basal-like, 1 HER2-Enriched, and 1 Luminal A; in all cases, the metastases clustered immediately adjacent to their primary tumor by hierarchical clustering analysis. Widespread DNA copy number alterations identified in the primary tumors were typically maintained throughout metastasis. On average, 1.9 ± 1.3% of DNA copy number altered genes, and 2.4 ± 0.95% of the somatic mutations per tumor were identified as "drivers" by DawnRank. There were an average of 199 ± 72 total drivers per tumor due to copy number alterations (amplifications or deletions) and 12 ± 23 drivers per tumor from somatic mutations. Phylogenetic tree analysis demonstrated that the majority of DNA copy number events occurred early in tumor development. Founding clones were defined as genetic events present in the primary and all matched metastases. Chr5q13 loss and TP53 mutation were the only consistent alterations in the founding clones of all 7 patients. Drivers on chr5q13 identified in this cohort include CCNB1, CDK7, and TAF9. Among the basal-like patients, all 5 patients' TP53 mutations were identified as a driver by DawnRank. 39% and 20% of drivers from copy number gains and losses, respectively, were identified in the primary tumor, while another 34% and 30% were not seen in the primary but were present in more than 1 metastasis within each patient. Metastasis-enriched copy number drivers not seen in any primary included FLT1, MAP2KR, and ARNT. 38% of the drivers resulting from somatic mutations were established in the primary and maintained in metastases. Of the remaining drivers from somatic mutation, only 18% were shared among metastases but not seen in the primary while 47% were not seen in any other tumor within a given patient (i.e. private to a single sample). TP53, PSEN1, CDC27, HDAC1, and BRCA1 were somatic mutation drivers established early in metastatic development, while CCNH was a consistent late driver. Conclusions: We present a novel computationally determined genetic "driver" analysis of matched breast cancer primaries and multi-organ metastases. In this cohort, our results suggest that most genetic drivers in a single tumor are based on copy number aberrations, are established early, and are maintained in metastases. In contrast to copy number, drivers from somatic mutations are acquired later, and most of the metastases continued to acquire new genetic driving features. Citation Format: Siegel MB, He X, Chen M, Hou JP, Garrett AL, Dye JB, Silva GO, Usary JE, Moylan VJ, Brady CM, Ma J, Thorne LB, Hoadley KA, Parker JS, Anders CK, Carey LA, Perou CM. Identification of early versus late drivers of breast tumors and metastasis. [abstract]. In: Proceedings of the Thirty-Eighth Annual CTRC-AACR San Antonio Breast Cancer Symposium: 2015 Dec 8-12; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2016;76(4 Suppl):Abstract nr S4-01.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.