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Insertional mutagenesis identifies drivers of a novel oncogenic pathway in invasive lobular breast carcinoma

Nature Genetics volume 49, pages 1219–1230 (2017)Cite this article

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Abstract

Invasive lobular carcinoma (ILC) is the second most common breast cancer subtype and accounts for 8–14% of all cases. Although the majority of human ILCs are characterized by the functional loss of E-cadherin (encoded by CDH1), inactivation of Cdh1 does not predispose mice to develop mammary tumors, implying that mutations in additional genes are required for ILC formation in mice. To identify these genes, we performed an insertional mutagenesis screen using the Sleeping Beauty transposon system in mice with mammary-specific inactivation of Cdh1. These mice developed multiple independent mammary tumors of which the majority resembled human ILC in terms of morphology and gene expression. Recurrent and mutually exclusive transposon insertions were identified in Myh9, Ppp1r12a, Ppp1r12b and Trp53bp2, whose products have been implicated in the regulation of the actin cytoskeleton. Notably, MYH9, PPP1R12B and TP53BP2 were also frequently aberrated in human ILC, highlighting these genes as drivers of a novel oncogenic pathway underlying ILC development.

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Figure 1: SB insertional mutagenesis induces tumorigenesis in female mice with mammary-gland-specific inactivation of E-cadherin.
Figure 2: Gene expression analysis of SB-induced tumors.
Figure 3: Insertion analysis of tumors from Wap–Cre;Cdh1F/F;SB females.
Figure 4: Overview of the candidate genes in hILC.
Figure 5: Overview of the insertions and corresponding gene expression of the mutually exclusive genes.
Figure 6: Limited proliferation and survival of AdCre-transduced Cdh1F/F;mT/mG mouse mammary epithelial cells (MMECs) that were rescued by expression of truncated PPP1R12A and TRP53BP2 or by dosage reduction of MYH9.
Figure 7: Validation and characterization of candidate genes in genetically engineered mice (GEMM).

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Acknowledgements

We are grateful to E. Wientjens, J. Houthuijzen, M. van Miltenburg, O. Bleijerveld, B. van Gerwen, B. Siteur, R. de Korte-Grimmerink, N. Proost, U. Boon, C. Brambillasca, R. Mezzadra, S. Cornelissen and L. Braaf for providing technical suggestions and/or help with the experiments, S. Canisius for critical reading of the manuscript and N. Hynes (Friederich Miescher Institute, Basel) for the HC11 cells. We thank the NKI animal facility, the animal pathology facility, the mouse clinic transgenic and intervention unit, the core facility molecular pathology and biobanking (CFMPB), and the genomics core facility for their expert technical support. Financial support was provided by the Netherlands Organization for Scientific Research (NWO: Cancer Genomics Netherlands (CGCNL), Cancer Systems Biology Center (CSBC), the Netherlands Genomics Initiative (NGI) grants Zenith 93512009 (J.J.), VENI 016156012 (M.N.) and VICI 91814643 (J.J.), the EU Seventh Framework Program (EurocanPlatform project 260791 (J.J.) and Infrafrontier-I3 project 312325 (J.J.)), the European Research Council (ERC Synergy project CombatCancer) (J.J.), and a National Roadmap grant for Large-Scale Research Facilities from NWO (J.J.).

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Author notes

  1. Sjors M Kas, Julian R de Ruiter and Koen Schipper: These authors contributed equally to this work.

Authors and Affiliations

  1. Division of Molecular Pathology, The Netherlands Cancer Institute, Amsterdam, The Netherlands

    Sjors M Kas, Julian R de Ruiter, Koen Schipper, Stefano Annunziato, Eva Schut, Anne Paulien Drenth, Eline van der Burg, Christiaan Klijn, Marco J Koudijs, Jelle Wesseling, Micha Nethe & Jos Jonkers

  2. Division of Molecular Carcinogenesis, The Netherlands Cancer Institute, Amsterdam, The Netherlands

    Julian R de Ruiter, Jelle J ten Hoeve & Lodewyk F A Wessels

  3. Experimental Animal Pathology, The Netherlands Cancer Institute, Amsterdam, The Netherlands

    Sjoerd Klarenbeek

  4. Experimental Cancer Genetics, Wellcome Trust Sanger Institute, Hinxton, UK

    David J Adams

  5. Department of Pathology, The Netherlands Cancer Institute, Amsterdam, The Netherlands

    Jelle Wesseling

  6. Cancer Genomics Netherlands, The Netherlands Cancer Institute, Amsterdam, The Netherlands

    Lodewyk F A Wessels & Jos Jonkers

  7. Department of EEMCS, Delft University of Technology, Delft, The Netherlands

    Lodewyk F A Wessels

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Contributions

S.M.K., K.S., S.A., E.S., A.P.D. and E.v.d.B. performed laboratory experiments; J.R.d.R. identified the insertion sites and CISs, analyzed the RNA sequencing data sets and performed the other bioinformatic analyses; C.K. and J.J.t.H. assisted in the initial bioinformatic analysis for the identification of insertion sites and CISs; S.K. and J.W. assessed the histology of mouse tumors and quantified the immunohistochemically stained images; D.J.A. was responsible for sequencing the transposon insertions; M.J.K. initiated the breeding of the mouse lines; M.N., L.F.A.W. and J.J. supervised the experiments; and J.R.d.R., S.M.K., L.F.A.W. and J.J. wrote the manuscript.

Corresponding authors

Correspondence to Lodewyk F A Wessels or Jos Jonkers.

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Integrated supplementary information

Supplementary Figure 1 Survival curves for the individual T2/Onc transgenic mouse lines, distribution and immunohistochemical stainings of the different tumor morphologies.

(a) Survival curves Wap-Cre;Cdh1F/F;SB mice carrying the T2/Onc transposon donor loci on chromosomes 1 and 15 (n = 142 and n = 126 mice, respectively). ns, no significant difference (Mantel–Cox test). (b) Tumor morphologies of Wap-Cre;Cdh1F/F (n = 16) and Wap-Cre;Cdh1F/+;SB (n = 4) female mice. (c) Immunohistochemical detection of E-cadherin, cytokeratin 1, cytokeratin 8 and vimentin in the different tumor morphologies. Scale bar, 50 μm.

Supplementary Figure 2 Additional plots accompanying the PAM50 gene expression analyses.

(a) Unsupervised clustering (Euclidean distance, average linkage) of the SB-induced tumors with reference mouse models and human breast cancer samples from TCGA, showing the expression of all 46 orthologous mouse genes from the PAM50 gene signature. (b,c) Expression of known marker genes associated with squamous and spindle cell tumors, showing high expression of the corresponding markers in the associated molecular subtype. Boxes extend from the third (Q3) to the first (Q1) quartile (IQR), with the line at the median; whiskers extend to Q3 + 1.5 IQR and Q1 − 1.5 IQR. Points beyond the ends of the whiskers are outliers. SC, spindle cell-like; SQ, squamous-like. (d) Unsupervised clustering (Euclidean distance, average linkage) of the SB-induced molecular subtypes with the reference luminal and basal-like mouse models.

Supplementary Figure 3 Distribution of morphology and expression subtypes across the T2/Onc transgenic mouse lines.

(a) Distribution of morphology across the two T2/Onc transgenic lines, showing that there is no significant bias between the two lines. Lack of any significant bias was confirmed using pairwise Fisher’s exact tests with Benjamini–Hochberg correction. (b) Distribution of subtypes across the two T2/Onc transgenic lines, also showing no significant bias between the two lines.

Supplementary Figure 4 Histograms detailing various statistics of the identified insertions, both for all insertions and for insertions within CISs.

(a) Distribution of the insertion depths (as indicated by ShearSplink’s ULP score) over all insertions. (b) Distribution of insertion clonality scores. (c) Distribution of the maximum insertion depth (maximum ULP score) per sample. (d) Distribution of the number of insertions per sample, with a median of 29 insertions per sample. (e–h) Same statistics as in a–d, but calculated for the CIS insertions, with a median of 5 CIS insertions per sample.

Supplementary Figure 5 Additional details on the clonality of the candidate genes.

(a) Ranking of genes by their overall frequency and the median clonality of their insertions. For samples with multiple insertions in the same gene, we used the clonality of the strongest insertion to avoid underestimating the median clonality due to local hopping. For clarity, only the main candidates (occurring in six or more samples) are labeled. (b) Clonality distribution of insertions in all candidate genes, ranked (from left to right) by the frequency of each gene.

Supplementary Figure 6 Distribution of the candidate genes over the identified molecular subtypes.

Bar plots indicating the distribution of all candidate genes over the molecular subtypes. Red bars indicate significant associations between candidate genes and the corresponding molecular subtype (FDR < 0.1, one-sided Fisher’s exact test with Benjamini–Hochberg correction). (a,b) This analysis was performed for both the set of 99 tumors with an ILC morphology (a) and the full set of 123 tumor samples (to increase statistical power) (b). The latter analysis identified an additional enrichment for Trps1 in the combined mILC-1 and mILC-2 subtypes, suggesting that Trps1 may play a role in the ILC morphology of these tumors. Additionally, the mILC-2 subtype was further enriched for insertions in Arid1a and Rasgrf1, indicating that expression differences between mILC-1 and mILC-2 may in part be driven by insertions in these genes.

Supplementary Figure 7 Additional details on the insertion patterns and differential expression of the candidate genes.

(a) Insertion pattern in Gab1, showing bias toward activating insertions. (b) Boxplots for the main candidate genes showing the difference in expression after the insertion sites in the corresponding gene between samples with and without an insertion. The boxplots and P values were calculated using IM-Fusion’s differential expression test, which essentially compares the expression of exons after the insertion sites in each gene between samples with an insertion and samples without an insertion, after normalizing for differences in overall expression between samples (see the Online Methods for more details). Boxes extend from the third (Q3) to the first (Q1) quartile (IQR), with the line at the median; whiskers extend to Q3 + 1.5 IQR and Q1 − 1.5 IQR. P values were calculated using the non-parametric Mann–Whitney U test. Green/purple boxplots indicate significant increases and decreases in expression (P < 0.05), respectively. (c) Insertion pattern in Trps1, showing bias toward truncating/inactivating insertions.

Supplementary Figure 8 Representative images and quantification of immunohistochemical staining for phosphorylated ERK1/2, a downstream protein of the RAS/MAPK signaling pathway.

(a) Representative images of different percentages of phosphorylated ERK1/2(Thr202/Tyr204) staining in SB-induced tumors. Scale bar, 50 μm. (b) Quantification of phosphorylated ERK1/2(Thr202/Tyr204) staining in the different molecular subtypes. Mean ± s.d.

Supplementary Figure 9 Overview of the mutations and copy-number events in the TGCA breast cancer data set (816 samples) for each of the main candidate genes and CDH1.

Percentages indicate the fraction of tumors with alterations in the respective genes.

Supplementary Figure 10 Myh9 haploinsufficiency in ILC formation in SB-induced tumor-derived cell lines with or without Myh9 insertion.

(a) Distribution of the number of insertions per sample in Myh9, showing that the majority of the tumors show single insertions in the gene. (b) PCR amplification of the transposon–Myh9 junction fragments in polyclonal SB-induced tumor-derived cell lines. (c) Heterozygous Myh9 insertions by PCR in clones derived from two SB-induced tumor cell lines. Green color indicates a correct clone; red color indicates an incorrect clone.

Supplementary Figure 11 Expression of truncated Ppp1r12a/b and Trp53bp2 and PPP1R12A protein expression in SB-induced tumors.

(a–c) Truncated Ppp1r12a/b and Trp53bp2 in SB-induced tumors, as visualized by northern blot analysis. (d) Expression of PPP1R12A in SB-induced tumors with and without insertions in Ppp1r12a, as visualized by immunoblotting using an anti-PPP1R12A antibody. β-actin is shown as a loading control. (e) Coimmunoprecipitation of PP1 in HC11 cells expressing GFP, truncated PPP1R12A or TRP53BP2, as visualized by immunoblotting using anti-FLAG and anti-PP1 antibodies.

Supplementary Figure 12 Characterization of cell death, cell survival markers and activation of a p53 response in E-cadherin-deficient cells expressing truncated PPP1R12A or TRP53BP2 or showing reduced levels of MYH9.

(a) Representative dot plots depicting the proportions of Annexin V (AN)- and/or propidium iodide (PI)-positive cells 72 h after seeding of AdCre-transduced Cdh1F/F MMECs with simultaneous transduction of Lenti-GFP, Lenti-Ppp1r12aex1-9 or Lenti-Trp53bp2ex13-18. (b) Quantification of Annexin V– and PI-positive cells from AdCre-transduced Cdh1F/F MMECs with simultaneous transduction of Lenti-GFP, Lenti-Ppp1r12aex1-9 or Lenti-Trp53bp2ex13-18. Asterisks indicate P < 0.05 (Welch’s t-test). Mean ± s.d. of three independent experiments. (c) Expression of total and phosphorylated AKT, ERK1/2 and S6 72 h after seeding of AdCre-transduced Cdh1F/F MMECs with simultaneous transduction of Lenti-GFP, Lenti-Ppp1r12aex1-9 or Lenti-Trp53bp2ex13-18, as visualized by immunoblotting. β-actin is shown as a loading control. (d) Cell survival of AdCre-transduced Cdh1F/F;mT/mG MMECs with simultaneous shRNA-mediated knockdown of Myh9 with different shRNAs, as quantified by using real-time IncuCyte imaging for 200 h. Mean ± s.d. of three independent experiments. (e) PCR amplification of the transposon–Trp53bp2 and transposon–Myh9 junction fragments in polyclonal SB-induced tumor-derived cell lines. (f) Expression of p53 and p21 in SB-induced tumor-derived cell lines with insertions in Trp53bp2 or Myh9 as compared to SB-induced tumor-derived cell line controls, as visualized by immunoblotting. Cells were treated for 6 h with water (control) or doxorubicin (Dox; 1 μM). β-actin is shown as a loading control. (g) Expression of p53 and p21 in SB-induced tumor-derived clones with insertions in Myh9 as compared to SB-induced tumor-derived control clones, as visualized by immunoblotting. Cells were treated for 6 h with water (control) or doxorubicin (Dox; 1 μM). β-actin is shown as a loading control. Exp, exposure.

Supplementary Figure 13 Overview of Cre-conditional alleles and distribution of the tumor morphology in the different genetically engineered mouse models.

(a) Depiction of Cre-conditional invCAG-Ppp1r12aex1-9-IRES-Luc and invCAG-Trp53bp2ex13-18-IRES-Luc alleles in the Col1a1 locus. Cre-mediated recombination allows inversion of the CAG promoter, resulting in expression of PPP1R12A1-418aa or TRP53BP2766-1134aa accompanied by luciferase expression. (b) Recombination status of the Cre-conditional alleles in tumors from Wap-Cre;Cdh1F/F;Ppp1r12 aex1-9 and Wap-Cre;Cdh1F/F;Trp53bp2ex13-18 mice, as visualized by PCR. EcadF and EcadD are PCRs to detect the Cdh1F and Cdh1Δ alleles, respectively. ShuttleR detects the recombined (p1 and p3; 1,054 bp) and non-recombined (p1 and p2; 897 bp) Cre-conditional alleles (primer positions are shown in a). (c) Histological classification of tumors from Wap-Cre;Cdh1F/F;Ppp1r12aex1-9 (n = 27) and Wap-Cre;Cdh1F/F;Trp53bp2ex13-18 (n = 30) mice. (d) Histological classification of tumors (n = 11) from Wap-Cre;Cdh1F/F;Cas9 mice injected with Lenti-CRISPR-sgMyh9.

Supplementary Figure 14 Clustering statistics for different numbers of clusters in the NMF subtype analysis.

(a) Overview of various clustering statistics for different numbers of clusters (2–5) in the NMF analysis of the SB-induced tumors. (b) Consensus maps for the same cluster sizes, showing the consistency of cluster assignments for the different numbers of clusters.

Supplementary information

Supplementary Text and Figures

Supplementary Figures 1–14 and Supplementary Note (PDF 5345 kb)

Supplementary Table 1

Overview of sample information including sample IDs, mouse IDs, T2/Onc lines, histopathology types, RNA-seq IDs, metastasis sites and subtypes. (XLSX 15 kb)

Supplementary Table 2

Overview of the identified candidate genes and various statistics for each gene. (XLSX 11 kb)

Supplementary Table 3

Overview of all primers used in this study for genotyping, cloning and northern blotting. (XLSX 12 kb)

Supplementary Table 4

Detailed information about antibodies and antigen retrieval methods used in immunohistochemical experiments. (XLSX 10 kb)

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Kas, S., de Ruiter, J., Schipper, K. et al. Insertional mutagenesis identifies drivers of a novel oncogenic pathway in invasive lobular breast carcinoma. Nat Genet 49, 1219–1230 (2017). https://doi.org/10.1038/ng.3905

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