Research ArticleCANCER

A murine preclinical syngeneic transplantation model for breast cancer precision medicine

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Science Advances  19 Apr 2017:
Vol. 3, no. 4, e1600957
DOI: 10.1126/sciadv.1600957
  • Fig. 1 Growth rate and across-passage stability of the MDST models.

    (A) Schematic of the procedure for the establishment of MDSTs. Fragments of primary tumors (T) were collected from mice with transgenic (TG) alterations of ATX-LPA signaling pathway members and orthotopically transplanted into immunocompetent wild-type (WT) mice. A growth profile of each MDST was recorded and expressed as changes in tumor volume (mm3) per day. (B) Growth curves of MDST models. Average tumor volume (mm3) ± SD (n = 2 to 3). (C) Average growth rates expressed as tumor volume change (ΔV) per day ± SD of MDST models at different passages (P). n = 2 to 3 grafts per passage.

  • Fig. 2 Expression of LPA and ATX transgenes in the MDST models.

    (A) Polymerase chain reaction (PCR) amplification of human LPAR1, LPAR2, and LPAR3 transgenic regions in DNA isolated at different passages from distinct MDSTs. MDST IDs and passages (P) are indicated at the top. Amplification bands from known transgene-positive tissue samples are shown in column C (control). (B) Expression level of human LPAR1, LPAR2, LPAR3, and ENPP2 (ATX) transgenes in six different MDST models by RNA sequencing (RNA-seq) (n = 2). The expression level of murine Gapdh is used as an endogenous standard. CPM, counts per million. (C) Western blot analysis of transgenic Flag-M2 expression in samples from three MDST models at different passages (P). P0 represents the primary tumor. Extracellular signal–regulated kinase 2 (ERK2) protein level was used as a loading control. (D) Schematic of MDST transplantation and the ATX inhibitor MSC2285264 delivery via osmotic pump. (E) Plasma concentration level (ng/ml) of the ATX inhibitor MSC2285264 after 20 days of treatment. (F) Size of ATXLPA1-T22 MDST transplants (mm3) after 1 month of treatment with vehicle or the ATX inhibitor MSC2285264.

  • Fig. 3 Intertumor phenotypic heterogeneity of the MDST models.

    (A) Box plots of MDST growth rates. The average tumor volume changes (mm3) per day ± SD of n = 8 to 14 distinct grafts are shown for each MDST. MDST models are grouped according to their transgenic background. (B) CDH1 immunohistochemical staining of MDST. MDST IDs are indicated below each image. Representative hematoxylin and eosin–stained sections of these tumors are shown in fig. S1. (C) Phase-contrast images of cells isolated from stromal vascular fraction of healthy mammary glands, two representative carcinomas (LPA1-T22 and ATXLPA1-T22), and two representative sarcomas (LPA1-T12 and LPA2-T13).

  • Fig. 4 Molecular profiling of MDSTs and comparison with GEMMs.

    (A) Hierarchical clustering of transcriptomic data from six carcinomas and three sarcomas (n = 2 samples collected from each MDST at different transplant generations). The list of MDST samples (1 to 18) (left) is mapped to a corresponding location on the MDS diagram on the right (numbered circles). Leading logFC (fold change) value coordinates D1-D2 convey transcriptional profile relatedness. Circles 1 and 2 on the MDS graph represent two samples dissected from healthy mammary glands of WT mice. (B) Two-way unsupervised hierarchical clustering heat map of the average log2 protein expression levels by RPPA (n = 6 to 20 samples collected from each MDST at different transplant generations). Horizontal color bars at the top indicate proteomic clusters (1 to 7), subgroup classification, genotype (LPA1, LPA2, LPA3, bigenic, cMYC, and WT), and tissue type. MDST IDs are listed at the bottom. Signature 1 is composed of expression levels of PARP1, claudin-7, HER3, β-catenin, and E-cadherin proteins. (C) Intrinsic supervised clustering analysis applied to gene expression levels in 405 mouse samples taken from 17 GEMMs. MDSTs are in dark red (arrows).

  • Fig. 5 Identification of molecular targets with direct relevance to human breast cancer therapy.

    (A) Similarities between murine models and human intrinsic subtypes of breast cancer. Expression pattern comparison of three murine homologs of PAM50 classifier genes in five molecular subtypes of breast cancer [basal, Her2+, luminal A (LumA), luminal B (LumB), and normal-like] (n = 232) and nine distinct MDSTs (n = 2 samples collected from each MDST at different transplant generations). The empirical threshold for marker up-regulation is shown (blue line). RU, relative units. (B) The average expression level of select genes of interest in MDSTs is presented as the average CPM ± SD of n = 2 samples collected from each MDST at different transplant generations. (C) Expression levels for proteins of interest that are differentially expressed or activated in MDSTs. Each bar represents the average normalized linear intensity value ± SD of 6 to 20 samples collected from each MDST at different transplant generations.

  • Table 1 Phenotypic and molecular characteristics of the MDST models.

    Growth rate is expressed as the average change in volume (mm3) per day ± SD (n = 8 to 14). Epithelial-mesenchymal transition (EMT) score is based on the levels of Ctnnb1, Cdh1, Cldn7, mir200a, Snai1, Twist1, Tgfb1, and Zeb (table S1). A detailed histopathological examination of each MDST is presented in section S1. Statistical analysis of growth rate differences between MDSTs is reported in table S5. SG-CDH1+, slow-growing, CDH1-positive (<55 mm3/day); FG-CDH1+, fast-growing, CDH1-positive (>55 mm3/day); FG-mixed, fast-growing, mixed; FGM, fast-growing/mesenchymal; N/A, not applicable.

    MDSTGrowth rate (mm3/day)HistologySubclassCDH1 statusInflammatory infiltrationEMT score
    LPA2-T3322.45 (±10.45), n = 12AdenocarcinomaSG-CDH1+PositiveMixed/moderated−10
    ATXLPA2-T2622.84 (±14.82), n = 11High-grade adenocarcinomaSG-CDH1+PositiveMixed/moderated−3.3
    LPA3-T1333.07 (±19.5), n = 8AdenocarcinomaSG-CDH1+PositiveMixed/moderated−13.76
    LPA1-T2235.46 (±24.49), n = 9AdenocarcinomaSG-CDH1+PositiveMixed/moderated−6.6
    ATXLPA1-T2249.09 (±16.85), n = 11High-grade adenocarcinomaSG-CDH1+PositiveMixed/moderated−7.5
    LPA2-T1667.19 (±18.82), n = 10AdenocarcinomaFG-CDH1+PositiveMixed/moderatedN/A
    ATXLPA2-T1684.46 (±50.91), n = 13High-grade carcinomaFG-mixedMixedMixed/moderated−0.5
    LPA1-T12755.93 (±23.35), n = 14High-grade sarcomaFGMNegativeMixed/moderatedN/A
    LPA1-T1789.35 (±28.82), n = 13High-grade sarcomaFGMNegativeN/AN/A
    LPA1-T12104.02 (±29.13), n = 8High-grade sarcomaFGMNegativeMixed/moderated+13
    LPA2-T43144.12 (±78.17), n = 14High-grade sarcomaFGMNegativeN/A+16.9
    LPA2-T13168.35 (±98.56), n = 10High-grade sarcomaFGMNegativeN/A+13.5

Supplementary Materials

  • Supplementary material for this article is available at http://advances.sciencemag.org/cgi/content/full/3/4/e1600957/DC1

    fig. S1. MDST histology.

    fig. S2. Sensitivity of MDST lines to genotoxic treatment.

    fig. S3. Intrinsic clustering analysis of MDST models and GEMMs.

    fig. S4. MDST sensitivity to tamoxifen.

    fig. S5. Predictive power of MDST models for tumor sensitivity to targeted inhibition.

    fig. S6. In vitro induction of DNA damage in MDST cells.

    fig. S7. Correlation between PARP1 protein expression and PARP inhibitor sensitivity in cell lines.

    fig. S8. Development and initial validation of the PSP score.

    table S1. Relative expression levels of EMT genes by RNA-seq.

    table S2. Amplification, mutation, and deletion frequencies of genes commonly altered in human breast invasive carcinomas and differentially expressed in multiple MDST models.

    table S3. Somatic mutations in MDST models.

    table S4. PSP signature gene list.

    table S5. Statistical analysis of growth rate differences between MDST models.

    section S1. Histopathology report.

  • Supplementary Materials

    This PDF file includes:

    • fig. S1. MDST histology.
    • fig. S2. Sensitivity of MDST lines to genotoxic treatment.
    • fig. S3. Intrinsic clustering analysis of MDST models and GEMMs.
    • fig. S4. MDST sensitivity to tamoxifen.
    • fig. S5. Predictive power of MDST models for tumor sensitivity to targeted inhibition.
    • fig. S6. In vitro induction of DNA damage in MDST cells.
    • fig. S7. Correlation between PARP1 protein expression and PARP inhibitor sensitivity in cell lines.
    • fig. S8. Development and initial validation of the PSP score.
    • table S1. Relative expression levels of EMT genes by RNA-seq.
    • table S2. Amplification, mutation, and deletion frequencies of genes commonly altered in human breast invasive carcinomas and differentially expressed in multiple MDST models.
    • table S3. Somatic mutations in MDST models.
    • table S4. PSP signature gene list.
    • table S5. Statistical analysis of growth rate differences between MDST models.
    • section S1. Histopathology report.

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