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Research Article
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LATS1 and LATS2 suppress breast cancer progression by maintaining cell identity and metabolic state

Noa Furth, Ioannis S Pateras, Ron Rotkopf, Vassiliki Vlachou, Irina Rivkin, Ina Schmitt, Deborah Bakaev, Anat Gershoni, Elena Ainbinder, Dena Leshkowitz, Randy L Johnson, Vassilis G Gorgoulis, Moshe Oren  Correspondence email, View ORCID ProfileYael Aylon  Correspondence email
Noa Furth
1Department of Molecular Cell Biology, Weizmann Institute of Science, Rehovot, Israel
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Ioannis S Pateras
2Laboratory of Histology and Embryology Medical School, University of Athens, Athens, Greece
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Ron Rotkopf
3Department of Life Sciences Core Facilities, Faculty of Biochemistry, Weizmann Institute of Science, Rehovot, Israel
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Vassiliki Vlachou
2Laboratory of Histology and Embryology Medical School, University of Athens, Athens, Greece
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Irina Rivkin
1Department of Molecular Cell Biology, Weizmann Institute of Science, Rehovot, Israel
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Ina Schmitt
1Department of Molecular Cell Biology, Weizmann Institute of Science, Rehovot, Israel
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Deborah Bakaev
1Department of Molecular Cell Biology, Weizmann Institute of Science, Rehovot, Israel
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Anat Gershoni
1Department of Molecular Cell Biology, Weizmann Institute of Science, Rehovot, Israel
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Elena Ainbinder
3Department of Life Sciences Core Facilities, Faculty of Biochemistry, Weizmann Institute of Science, Rehovot, Israel
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Dena Leshkowitz
3Department of Life Sciences Core Facilities, Faculty of Biochemistry, Weizmann Institute of Science, Rehovot, Israel
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Randy L Johnson
4Department of Cancer Biology, University of Texas MD Anderson Cancer Center, Houston, TX, USA
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Vassilis G Gorgoulis
2Laboratory of Histology and Embryology Medical School, University of Athens, Athens, Greece
5Biomedical Research Foundation of the Academy of Athens, Athens, Greece
6Faculty of Biology, Medicine and Health, University of Manchester, Manchester Academic Health Science Centre, Manchester, UK
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Moshe Oren
1Department of Molecular Cell Biology, Weizmann Institute of Science, Rehovot, Israel
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  • For correspondence: moshe.oren@weizmann.ac.il
Yael Aylon
1Department of Molecular Cell Biology, Weizmann Institute of Science, Rehovot, Israel
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  • ORCID record for Yael Aylon
  • For correspondence: yael.aylon@weizmann.ac.il
Published 30 October 2018. DOI: 10.26508/lsa.201800171
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  • Figure 1.
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    Figure 1. LATS2-associated gene expression pattern is down-regulated specifically in lumB breast tumors.

    (A) Scatter plot of LATS1 and LATS2 expression levels in breast cancer tumors (TCGA-BRCA dataset). Pearson’s correlation coefficient 0.44. A cutoff of the 20% of tumors expressing the lowest levels of each LATS gene was used to divide the tumors into three groups: LATS1L, LATS2L, and LATSL, compared with LATSH. (B) Heatmap depicting the expression levels of a 20-gene LATS2L signature (the 20 most down-regulated genes exclusively in LATS2L tumors, compared with LATSH tumors; see Table S4 and the Materials and Methods section) in breast tumors (TCGA-BRCA) sorted according to PAM50 subtype classification. (C) Distribution of LATS2 mRNA expression levels in different breast cancer subtypes (PAM50, TCGA-BRCA); ***P-value < 0.001, t test comparing lumB tumors with all other subtypes. Number of tumors of each subtype is indicated at the bottom. (D) Kaplan-Meier analysis of survival probability of luminal breast cancer patients (METABRIC dataset, n = 1139; Cox proportional hazards model) divided according to expression levels of the LATS2L signature (as in B).

  • Figure S1.
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    Figure S1.

    (A) Distribution of LATS2 mRNA expression levels in different breast cancer subtypes (PAM50, METABTIC dataset); ***P-value < 0.001, t test comparing lumB tumors with all other subtypes. Number of tumors of each subtype is indicated at the bottom. (B) Kaplan–Meier plot of relapse-free survival (RFS) probability of lumB breast cancer patients separated according to LATS2 expression levels (n = 407, KM-plotter [Györffy et al, 2010]).

  • Figure S2.
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    Figure S2.

    (A) Schematic representation of the conditional Lats2 locus. Upon mammary-specific CRE expression, exon 5 (colored blue) is deleted. (B) Genotyping of the Lats2 and the Cre alleles. Asterisks designate nonspecific bands. (C) Expression levels of Lats2 mRNA in WT-PyMT and Lats2-CKO PyMT tumors, quantified using RT-qPCR. Numbers of mice are indicated at the bottom; mean ± SEM; **P-value < 0.01. (D) Representative H&E-stained sections of tumors from three month old Lats2-CKO PyMT and WT-PyMT littermate controls. Inset: immunohistochemical (IHC) staining for smooth muscle actin (SMA), a marker for myoepithelial cells surrounding the adenoma/MIN. Scale bar = 200 μm. (E) Kaplan–Meier plot of survival probability of luminal breast cancer patients (METABRIC, n = 1138) divided according to relative expression of the genes commonly down-regulated in LATS2L human lumB and Lats2-CKO PyMT tumors (n = 20, see Table S4).

  • Figure 2.
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    Figure 2. LATS2 is a tumor suppressor in a mouse lumB breast cancer model.

    (A) Relative total tumor weight, as percentage of total body weight of 3-mo-old Lats2-CKO PyMT and WT-PyMT littermate controls (n = number of mice); mean ± SEM; * P-value < 0.05. (B) Three mammary glands (see the Materials and Methods section) from Lats2-CKO PyMT and WT-PyMT littermate control mice were histologically scored. The most advanced pathological lesion from each mouse was tallied. (C) Representative H&E-stained sections from WT-PyMT (adenoma/MIN) and Lats2-CKO PyMT (carcinoma); scale bar = 500 μm. (D) Expression levels of Lats2 mRNA in WT-PyMT tumors of different histological stages, analyzed by RT-qPCR; mean ± SEM. (E) Left panel: Heatmap representing hierarchical clustering of global expression patterns of tumors from Lats2-CKO PyMT (n = 4) and WT-PyMT littermate controls (n = 3). Each tumor was taken from a different mouse. Standardized rld values are shown for differentially expressed genes (P-value < 0.05, n = 1131); ad = adenoma/MIN, car = carcinoma. Right panel: PCA of the most differentially expressed genes between Lats2-CKO PyMT and WT-PyMT tumors (adjP-value < 0.05), deduced from RNA-seq analysis. (F) GSEA of 1,131 genes ranked by fold change (red to blue gradient) between WT-PyMT and Lats2-CKO PyMT tumors (P-value < 0.05) and compared with genes down-regulated in LATS2L (versus LATSH) human lumB tumors (vertical black lines).

  • Figure S3.
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    Figure S3.

    (A) Relative expression levels of the top most down-regulated genes in LATS2L breast tumors (TCGA-BRCA dataset, see Fig 1) in the panel of breast cancer cell lines included in the Cancer Cell Line Encyclopedia. Representative luminal cell lines are marked. (B) Upper panel: schematic representation of the LATS2 genomic locus. Positions of CpG island and methylation probes with differential methylation (P-value < 0.05) between LATS2L and LATS2H lumB tumors are shown. Lower panel: mean methylation of each probe in LATS2L versus LATS2H tumors. Line thickness corresponds to the P-value of the difference in methylation levels of the indicated probe between the two groups. For each probe, Pearson's correlation coefficient between expression and methylation in all lumB tumors is listed. (C) Left panel: ZR75-1 cells were transiently transfected with the indicated expression plasmids and harvested 72 h later. Cell extracts were subjected to Western blot analysis of LATS1, LATS2, and GAPDH as loading control. Right panel: ZR75-1 cells were transduced with MYC-LATS2 expression plasmid or vector control and selected with blasticidin to obtain stable expression. Cell extracts were subjected to Western blot analysis with the indicated antibodies. (D) MDA-MB-468 cells were transfected with the indicated expression plasmids and subjected 48 h later to PI exclusion analysis followed by flow cytometry analysis. “Relative cell death” represents the ratio between the percentages of dead (PI+) cells in the GFP-positive population versus the GFP-negative population. Values within each experiment were normalized to GFP transfected sample; mean ± SEM of two independent experiments.

  • Figure 3.
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    Figure 3. LATS2 promotes death of lumB cells.

    (A) ZR75-1 cells were treated with 1 μM 5-aza-2′-deoxycytidine (5-Aza) for 4 d. Upper panel: RT-qPCR analysis of LATS2 mRNA; mean ± SD of two technical replicates. Lower panel: Western blot analysis of LATS2 protein. (B) Functional enrichment of cell viability-related terms for differentially expressed genes in luminal cancer cell lines with transient silencing (siLATS2) or stable overexpression (OE) of LATS2, compared with controls. Ingenuity Pathway Analysis (IPA); Diseases or Functions annotations. (C) ZR75-1 cells were transiently transfected with GFP-LATS1 or GFP-LATS2, stained with anti-cleaved caspase 3 (CC3) antibody after 48 h, and subjected to imaging flow cytometry (ImageStreamX). Only cells with intact nucleus and positive GFP signal were analyzed; mean ± SEM of staining intensity; ***P-value < 0.001. (D) ZR75-1 cells were transfected with GFP-LATS1 or GFP-LATS2 or GFP only (vector). 72 h later, cell viability was assessed by PI exclusion followed by flow cytometry analysis. “Cell death” represents the ratio between the percentages of dead cells (PI+) in the GFP-positive population versus the GFP-negative population; mean ± SEM of three independent experiments; ***P-value < 0.001. Representative FACS results are shown on the right; in each case, upper and lower panels represent the GFP-positive and GFP-negative subpopulation, respectively, of the same transfected culture. (E) ZR75-1 cells stably transduced with MYC-LATS2 plasmid or control vector were subjected to PI exclusion analysis followed by flow cytometry. Left panel: percentage of dead (PI+) cells. Right panel: cell count of live (PI−) cells; mean ± SEM of three independent experiments; *P-value < 0.05, **P-value < 0.01. (F) Histological samples from carcinomas of Lats2-CKO PyMT and WT-PyMT littermate controls were immunostained for γH2AX and cleaved caspase 3 (CC3, left panel, scale bar = 100 μm). Right panel: mean ± SEM of percentage of positive cells, based on at least nine sections of each genotype; ***P-value < 0.001.

  • Figure 4.
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    Figure 4. LATS2 augments oxidative phosphorylation.

    (A) KEGG pathways enrichment analysis for genes differentially regulated in Lats2-CKO PyMT compared with WT-PyMT tumors (adjP-value < 0.05, n = 114). (B) ZR75-1 cells stably transfected with an MYC-LATS2 plasmid (LATS2) or with control vector were cultured with or without glucose for 3 d. Cell death was measured by PI exclusion followed by FACS analysis. Values from each experiment were normalized to % PI+ of control cells grown in glucose-containing medium; mean ± SEM of three independent experiments. (C) Extracellular acidification rate (ECAR, indicative of glycolysis) and oxygen consumption rate (OCR, indicative of respiration) of ZR75-1 cells stably expressing MYC-LATS2, relative to vector control cells, determined by Seahorse; mean ± SEM of five independent experiments. Representative tracks of Seahorse measurements are shown on the right. (D) Respiration measured by OCR in WT-PyMT and Lats2-CKO PyMT tumor-derived cell lines; mean ± SEM in log 10 scale of three independent experiments; P-value < 0.05. Bottom: representative Seahorse track.

  • Figure S4.
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    Figure S4.

    (A) Genotyping of the Lats2 and Cre alleles in the PyMT-derived cell lines (see primers location in Fig S2A). (B) Relative expression of Lats2 mRNA in cell lines derived from WT- or Lats2-CKO-PyMT tumors, analyzed by RTqPCR; mean ± SEM of 2 and three independently isolated cell lines, respectively, originating from different tumors. ***P-value < 0.001.

  • Figure 5.
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    Figure 5. PPARγ signaling correlates with LATS2 in human and mouse tumors and promotes cell death in a LATS2-dependent manner.

    (A) KEGG pathways significantly enriched within the list of genes commonly down-regulated in Lats2-CKO PyMT (compared with WT-PyMT) tumors and LATS2L lumB human tumors (TCGA). (B) RT-qPCR quantification of Pparg and Plin1 expression in tumors derived from 3 mo old Lats2-CKO PyMT (n = 9) and WT-PyMT littermate controls (n = 6); mean ± SEM; *P-value < 0.05, ***P-value < 0.001. (C) Expression levels of the indicated genes (left) and proteins (right) in cultured WT PyMT and Lats2-CKO PyMT tumor-derived cells stably transduced with LATS2 or vector control; mean ± SD of 2 technical repeats. (D) ZR75-1 cells were transfected with GFP-LATS2 or control GFP plasmid, stained 48 h later with anti-PPARγ and cleaved caspase 3 (CC3) antibodies, and subjected to imaging flow cytometry (ImageStreamX). Only GFP-positive cells with intact nuclei were analyzed. Cells with nuclear localization of the transfected protein were identified by similarity between GFP and DAPI staining. Percentage of cells positively stained for PPARγ in each subpopulation is presented. Representative images are shown at the bottom. BF = bright field. (E) Left panel: scatter plot depicting PPARG and LATS2 expression in luminal tumors in the TCGA-BRCA dataset (n = 613). Right panel: GSEA of genes ranked according to expression fold change between LATS2L tumors and LATSH tumors in the TCGA lumB dataset. (F) Kaplan-Meier analysis of survival probability of luminal breast cancer patients (METABRIC dataset, n = 1139; Cox proportional hazards model) defined according to expression levels of LATS2 and PPARG. (G) RT-qPCR quantification of PPARG and LPL (left) and LATS2 (right) mRNA in ZR75-1 cells treated for 48 h with increasing concentrations of RGZ (0, 10, 25, 50, and 100 μM, respectively); mean ± SD of two technical replicates. (H) ZR75-1/vector (vector) and ZR75-1/LATS2 (LATS2) cells were treated with 100 μM RGZ for 48 h, followed by PI exclusion analysis; mean ± SEM of the ratio between % PI+ cells in each cell type, from three independent experiments. (I) Cell lines derived from WT-PyMT and Lats2-CKO PyMT tumors were treated with 100 μM RGZ for 48 h, followed by PI exclusion analysis; mean ± SEM of the ratio between % PI+ cells in treated versus untreated cells, from two independent experiments.

  • Figure S5.
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    Figure S5.

    (A) ZR75-1 cells were treated with 1 μM 5-aza-2′-deoxycytidine (5-Aza) for 4 d. PPARG and LPL mRNA levels were analyzed by RT-qPCR; mean ± SD of two technical replicates. (B) Scatter plot depicting PPARG and LATS1 mRNA expression levels in luminal tumors (TCGA BRCA dataset, n = 613). (C) ZR75-1 cells were transfected with either control vector (GFP only) or GFP-LATS2 expression plasmid and treated with 100 μM RGZ for 4 d. Cell death was measured as in Fig 3D. Values were normalized relative to nontreated cells transfected with vector only. (D) ZR75-1 cells were transfected with the indicated siRNA oligonucleotides and treated with 100 μM RGZ for 4 d. The percentage of dead cells was measured by PI exclusion followed by flow cytometry analysis, and values were normalized to nontreated siControl cells.

  • Figure S6.
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    Figure S6.

    (A) Schematic representation of the conditional Lats1 locus. Upon mammary-specific Cre expression, exon 4 (colored blue) is excised. (B) Genotyping of the Lats1 allele. (C) Expression of Lats1 mRNA in WT- and Lats1-CKO PyMT tumors, analyzed by RT-qPCR. Mean ± SEM of tumors from different mice. Mouse numbers indicated at the bottom; ***P-value < 0.001. (D) LATS1 and LATS2 mRNA expression levels in human breast cancer tumors (TCGA-BRCA dataset). Tumors were stratified according to histological type (n = 1095). (E) Genes were ranked according to fold change between LATS1 siRNA (siLATS1) and control siRNA in transiently transfected MCF7 cells (left) or between LATS1 overexpression and vector control in ZR75-1 cells (ZR75-1/LATS1, right) and compared with differentially expressed genes in Lats1-CKO PyMT tumors (adjP-value < 0.05, FC > 1.5). (F) YAP/TAZ target genes (Dupont gene set, Dupont et al, 2011), differentially expressed in either Lats1-or Lats2-CKO PyMT tumors relative to their WT-PyMT littermate controls (P-value < 0.05). The heat map depicts the log ratio between Lats-CKO and WT-PyMT littermate controls; grey indicates genes not significantly differentially expressed between the two conditions. (G) ZR75-1 cells were transfected with the indicated siRNA oligonucleotides. CYR61 and IGFBP3 mRNA levels were analyzed by RT-qPCR; mean ± SD of two technical replicates. (H) Functional enrichment analysis (GO biological processes) for genes differentially regulated upon LATS1 silencing in either ZR75-1 (FC > 1.5, adjP-value < 0.05, n = 733, left panel) or MCF7 (FC > 1.5, adjP-value < 0.05, n = 285, right panel). The 10 most enriched terms for each cell line are shown.

  • Figure 6.
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    Figure 6. Deletion of Lats1 is phenotypically distinct from Lats2 deletion in PyMT tumors.

    (A) Relative tumor weight, as percentage of total body weight, in three month old Lats1-CKO PyMT and WT-PyMT littermate controls (n = number of mice); mean ± SEM; *P-value < 0.05. (B) Three mammary glands from Lats1-CKO PyMT and WT-PyMT littermate controls were histologically scored and tallied. Right panel: representative H&E-stained adenosquamous carcinoma sample from a Lats1-CKO PyMT tumor (scale bar = 200 μm). (C) Immunohistochemistry analysis of ERα protein expression in tumors from 3-mo-old Lats1-CKO PyMT and WT-PyMT littermate controls. Left panel: two representative tumor sections from each genotype (scale bar = 100 μm). Right panel: mean ± SEM of % ER+ cells in tumors from eight Lats1-CKO PyMT and 6 WT-PyMT mice; *P-value < 0.05. (D) Immunohistochemistry analysis of CK14, performed as in (C). Right panel depicts mean ± SEM of percentage of slide area with intense membranous CK14 staining in the invasive front of the tumor; *P-value < 0.05. (E) Heatmap representing hierarchical clustering of global expression patterns of tumors from 3-mo-old Lats1-CKO PyMT and WT-PyMT littermate controls. Standardized rld values are shown for differentially expressed genes (P-value < 0.05, n = 2029). ad = adenoma/MIN, car = carcinoma, asc = adenosquamous carcinoma; (F) Left panel: GSEA assessing PPARγ transcriptional activity in Lats1-CKO PyMT versus Lats2-CKO PyMT tumors. Genes differentially expressed (adjP-value < 0.05) in either Lats1-CKO PyMT (compared with littermate controls) or Lats2-CKO PyMT (compared with littermate controls) were ranked according to fold change differences (log ratio) and compared with a gene set comprising PPARγ target genes (El Akoum, 2014). Right panel: box plot representing mean fold change (log 2) of genes comprising the PPAR pathway (KEGG database) in Lats1-CKO PyMT and Lats2-CKO PyMT, each compared with their WT-PyMT littermate controls. Only genes with P-value of comparison < 0.05 were included; ***P-value < 0.001.

  • Figure 7.
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    Figure 7. Down-regulation of LATS1 promotes the formation of tumors enriched in basal-like features.

    (A) Genes were ranked according to fold change between Lats1-CKO PyMT and WT-PyMT tumors (P-value < 0.05), and compared with genes differentially expressed in ER-negative PyMT tumors (GSE64453), using GSEA. (B) Genes were ranked as in (A) and compared with genes down-regulated in mature luminal cells relative to mammary stem cells (GSE19446), using GSEA. (C) Genes were ranked as in (A) and compared with genes up-regulated in human basal-like tumors relative to luminal tumors (TCGA, see the Materials and Methods section) (left panel) or genes up-regulated in human basal tumors relative to lumB (GSE45827), using GSEA. (D) Box plot representing mean fold change (log2) of genes comprising the basal tumor signature (see the Materials and Methods section and Table S3), in Lats1-CKO PyMT and Lats2-CKO PyMT tumors compared with their WT-PyMT littermate controls. (E) Heatmap depicting the expression levels of the 20 most down-regulated genes in LATS1L tumors relative to LATSH tumors (see Table S4 and the Materials and Methods section). Tumors were sorted according to the PAM50 classification. (F) Relative expression levels of LATS1 in different breast cancer subtypes (PAM50 and TCGA-BRCA). Numbers of samples are indicated at the bottom. ANOVA coupled with Dunnett's test; ***P-value < 0.01. (G) Immunohistochemistry (IHC) analysis of LATS1 and LATS2 in luminal and triple negative (TN) human tumors. Representative tumor sections of human lumB and TN tumors are shown in the upper panel (scale bar = 100 μm). Lower panel: human tumor samples (n = number of samples in each subtype) were scored by IHC (see the Materials and Methods section) for LATS1 and LATS2; *P-value < 0.05, ***P-value < 0.001. (H) Genes were ranked according to fold change between control siRNA-transfected and LATS1 siRNA-transfected (siLATS1) MCF7 cells and compared with the indicated gene sets (Creighton et al, 2008; Massarweh et al, 2008), using GSEA. (I) WT-PyMT, Lats1-CKO PyMT, and Lats2-CKO PyMT mice were injected IP with 4-hydroxytamoxifen (Tamoxifen) or left untreated (no treatment); n = 12, 18, 7, 10, 9, and 9, respectively.

  • Figure S7.
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    Figure S7.

    Metascape Tripathi et al 2015pathways enrichment analysis (Tripathi et al 2015, http://metascape.org) of differentially expressed genes (counts > 5, FC > 1.5, adjP-value < 0.05) in Lats2-CKO mammary tumors (PyMT) or Lats2-CKO livers, relative to their WT littermate controls. Heatmap shows the enrichment score (−log10(P-value)) for each pathway in each of the differentially expressed gene lists.

Supplementary Materials

  • Figures
  • Table S1 (A) Pathway enrichment analysis (GeneAnalytics, Pathways) of genes differentially expressed following siRNA-mediated silencing of LATS2 in MCF7 and ZR75-1 cells, as well as upon overexpression of exogenous GFP-LATS2 in ZR75-1 cells. (B) Differentially expressed genes contributing to the enrichment of cell death categories by IPA.

  • Table S2 Metabolism-related functional terms (IPA-diseases and functions module) significantly enriched among genes differentially expressed upon modulation of LATS2 levels in the human luminal cell lines MCF7 and ZR75-1.

  • Table S3 Genes comprising the basal-associated gene signature shown in Fig 7D. Expression difference between Lats-CKO PyMT and WT PyMT littermate control tumors (log2 ratio) is shown for each gene.

  • Table S4 Gene signatures used for human tumor expression and survival analysis.

  • Table S5 Reagents used throughout this study.

  • Table S6 List of gene sets used for GSEA analysis.

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LATS1 and LATS2 tumor suppression in breast cancer
Noa Furth, Ioannis S Pateras, Ron Rotkopf, Vassiliki Vlachou, Irina Rivkin, Ina Schmitt, Deborah Bakaev, Anat Gershoni, Elena Ainbinder, Dena Leshkowitz, Randy L Johnson, Vassilis G Gorgoulis, Moshe Oren, Yael Aylon
Life Science Alliance Oct 2018, 1 (5) e201800171; DOI: 10.26508/lsa.201800171

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LATS1 and LATS2 tumor suppression in breast cancer
Noa Furth, Ioannis S Pateras, Ron Rotkopf, Vassiliki Vlachou, Irina Rivkin, Ina Schmitt, Deborah Bakaev, Anat Gershoni, Elena Ainbinder, Dena Leshkowitz, Randy L Johnson, Vassilis G Gorgoulis, Moshe Oren, Yael Aylon
Life Science Alliance Oct 2018, 1 (5) e201800171; DOI: 10.26508/lsa.201800171
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