Metadata supporting data files of the related article: The phosphatase PPM1A inhibits Triple Negative Breast Cancer growth by blocking cell cycle progression
Creators: name: Mazumdar, Abhijit
name: Tahaney, William M.
name: Bollu, Lakshmi Reddy
name: Poage, Graham
name: Hill, Jamal
name: Zhang, Yun
name: Mills, Gordon B.
name: Brown, Powel H.
Publisher: name: figshare
Year: 2019
Subjects: Cancer
Cell Development, Proliferation and Death
Gene Expression (incl. Microarray and other genome-wide approaches)
Genomics
Medicine
Cancer Cell Biology
Cancer Genetics

description: The study aimed to investigate the role of a specific protein phosphatase, Mg<sup>+2</sup>/Mn<sup>+2</sup> dependent 1A (PPM1A), a crucial tumor suppressor gene, in cell cycle progression and growth in Triple Negative Breast Cancer (TNBC). The identification of key phosphatase proteins that regulate breast cancer survival and growth, and are differentially expressed in ER-negative BCs (like TNBCs), can lead to a targeted, more effective treatment of TNBC. <b>Study description and methodology: </b>The authors investigated the role of <i>PPM1A </i>in ER-negative breast cancer growth. The mechanism by which PPM1A acts to block cell cycle progression was also investigated. This was done by determining the effect of PPM1A on proteins that regulate cell cycle progression. <i>PPM1A </i>mRNA expression was performed using the Oncomine platform, on eight publicly available datasets (TCGA Breast, METABRIC (Curtis), Lu, Chin, van de Vijver, Hatzis, Bittner, and Kao datasets). Allelic deletion and somatic alteration of breast cancer tumors was completed using cBioPortal and the METABRIC dataset.<br>For <i>in vitro</i> experiments, a total of seven breast cancer cell lines were used. ZR-75-1, T47D and MCF7 are ER-positive cell lines used in the study. MDA-MB-231, SUM159, HCC1187 and HCC1937 are ER-negative cell lines used in the study. MCF10A was used as an immortalised normal cell line. Cell lines stably expressing doxycycline-inducible cDNAs (for <i>PPM1A</i> overexpression) were generated through lentiviral infection using a pTIPZ lentiviral expression system. Cell proliferation was measured by counting viable cells at indicated time points using trypan blue exclusion and the Invitrogen Countless automated cell counter. Cell proliferation was also measured in the presence and absence of cyclin-dependent kinase 2 (CDK2) and cyclin-dependent kinases 4 and 6 (CDK4/6) inhibitors. Anchorage-independent growth assays were performed to determine whether PPM1A regulates the anchorage-independent growth of <i>PPM1A</i>-transfected ER-negative breast cancer cells. Cell cycle assays were carried out to measure cell cycle distribution using the tetracycline (Tet)-inducible stable cell line SUM159, treated for 4 days with or without doxycycline. This was done using flow cytometry and propidium iodide staining (PI). Western blot analysis was performed to quantify the levels of the following proteins in <i>PPM1A</i>-transfected and vector-transfected cells: PPM1A, total and phospho-CDK2, total CDK4, total CDK6, phospho-retinoblastoma protein (RB), p21, and p27 proteins. Immunoprecipitation was carried out to determine whether there is a direct interaction between PPM1A and the three proteins CDK2, CDK4 and CDK6.<br>For <i>in vivo</i> mouse experiments, nude mice (obtained from the Jackson Laboratory, Bar Harbor, ME), were used. MDA-MB-231-<i>PPM1A</i> and vector control cells (xenografts) were injected into the mammary fat pads of nude mice and after tumors had reached a certain size, mice were randomized into two groups: doxycycline-treated mice and doxycycline-free mice. This was done to investigate the effect of PPM1A expression on tumor growth size. Immunohistochemistry was carried out using paraformaldehyde-fixed tumor samples embedded in paraffin. Tissue samples were either processed for Hematoxylin-eosin (H&amp;E) staining or immunohistochemical (IHC) staining. During immunohistochemistry, tumor samples were incubated with a ki67 antibody, to detect cell proliferation. For more details on the methodology, please refer to the published article.<br><b>Ethical approval for animal experiments: </b>Experiments using nude mice (The Jackson Laboratory, Bar Harbor, ME) were performed in accordance with M.D. Anderson Institutional Animal Care and Use Committee (IACUC)-approved protocols.<br><b>Datasets supporting the figures of the published article:</b><br>Eight publicly available datasets were analysed in this study, and in turn used to generate figures 1 and 2 of the published article. All the eight datasets were accessed and analysed through the bioinformatics portals Oncomine (<b>www.oncomine.org</b>) and cBioPortal (<b>www.cbioportal.org</b>).<br>mRNA expression data of all eight datasets and overall survival of the van de Vijver dataset supporting figure 1 of the published article were accessed and analysed through the bioinformatics portal Oncomine (www.oncomine.org). Allelic deletion and somatic copy number alterations of breast cancer tumors of the METABRIC dataset were accessed through cBioPortal (<b>https://identifiers.org/cbioportal:brca_metabric</b>). The names of the <b>eight publicly available datasets</b> as they appear in <b>Oncomine</b> are: <b>TCGA Breast</b>, <b>Curtis Breast </b>("METABRIC" in cBioPortal), <b>Lu Breast</b>, <b>Chin Breast</b>, <b>van de Vijver Breast</b>, <b>Hatzis Breast</b>, <b>Bittner Breast</b>, <b>Kao Breast.</b>The raw genomic data of the above datasets are also accessible from various repositories as described below:TCGA dataset, available at NCBI dbGAP (<b>https://identifiers.org/dbgap:phs000178.v10.p8</b>), Curtis Breast dataset, available at the European Genome-phenome Archive, EGA (study accession ID: <b>EGAS00000000083</b>), Lu Breast dataset, available at NCBI Gene Expression Omnibus, GEO (<b>https://identifiers.org/geo:GSE5460</b>), Chin Breast dataset, available at Array Express (<b>https://identifiers.org/arrayexpress:E-TABM-158</b>), Van de Vijver Breast dataset, available at Computational Cancer Biology, Netherlands Cancer Institute (<b>http://ccb.nki.nl/data/</b>, A gene-expression signature as a predictor of survival in breast cancer, dataset: Genome-Wide Gene Expression Data for 295 Samples), Hatzis Breast dataset, available at NCBI Gene Expression Omnibus, GEO (<b>https://identifiers.org/geo:GSE25066</b>), Bittner Breast dataset, available at NCBI Gene Expression Omnibus, GEO (<b>https://identifiers.org/geo:GSE2109</b>), Kao Breast dataset, available at NCBI Gene Expression Omnibus, GEO (<b>https://identifiers.org/geo:GSE20685</b>).<b>Data supporting figure 1: </b>Dataset <b>PPM1A_Expression.xlsx </b>is in Excel file format and shows <i>PPM1A</i> expression in ER-negative breast cancers compared to ER-positive breast cancers in eight publically available datasets (see above). Data were accessed through the Oncomine Portal and used to generate Figure 1a of the published article. The "Van de Vijver Breast" dataset (<b>PPM1A_Survival.xlsx</b>) was also accessed through the Oncomine Portal and was used to generate Figure 1b of the published article. Dataset PPM1A_Survival.xlsx is in Excel file format and shows survival data for high and low <i>PPM1A</i> expression groups in all breast cancers, ER-positive breast cancers and ER-negative breast cancers, respectively.<br><b>Data supporting figure 2:</b> Dataset <b>Phosphatase_Del.xlsx</b> is in Excel file format and shows phosphatase deletions in ER-positive and ER-negative breast cancers in the METABRIC dataset. Dataset <b>PPM1A_Som_Alt.xlsx</b> is in Excel file format and shows <i>PPM1A</i> somatic alterations in various breast cancer subtypes. Data also show <i>PPM1A</i> mRNA expression levels according to type of somatic alteration and according to PAM50 breast cancer subtype classification. The "Curtis Breast" dataset (METABRIC dataset) was used to generate figure 2 of the published article, and this was accessed from cBioPortal (<b>https://identifiers.org/cbioportal:brca_metabric</b>).<br><b>Data supporting figure 3:</b> Dataset <b>PPM1A_Cell_Growth.xlsx</b> is in Excel file format and shows the results of the breast cancer cell proliferation assays (anchorage-dependent growth) and the results of anchorage-independent growth upon the induction of expression of <i>PPM1A</i> with doxycycline in cell lines SUM159, Mda-MB-231 and MCF7.<br><b>Data supporting figure 4:</b> Dataset <b>PPM1A_In_Vivo_Growth.xlsx</b> is in Excel file format and shows tumor size measurements (<i>in vivo</i> growth) of individual MDA-MB-231-PPM1A and vector control xenografts, over the course of days with and without doxycycline treatment. Data show the average tumor size with and without dox treatment for MDA-MB-231-PPM1A and vector control xenografts. Dataset <b>PPM1A_IHC.xlsx </b>shows the quantification of ki67 staining of MDA-MB-231 and vector xenograft sections, with and without doxycycline treatment.<br><b>Data supporting figure 5: </b>Dataset <b>PPM1A_Cell_Cycle.xlsx </b>supports figure 5a-c of the published article and shows the results of the cell cycle assay upon the induced expression of <i>PPM1A</i> induction. Data shows the percentage of SUM159 cells in G1, S and G2M phases of the cell cycle when <i>PPM1A</i> is overexpressed (Dox) and in the absence of <i>PPM1A</i> overexpression (no dox), respectively. Dataset <b>PPm1A_CDK_Inh.xlsx</b> shows cancer cell growth (measured as cell count), determined after treatment of triple negative breast cancer cells with the CDK2 inhibitor K03861 and CDK4/6 inhibitor Palbociclib (both inhibitors mimic the effect of <i>PPM1A</i> overexpression (i.e. suppress growth of cells).<br><b>Supplementary western blot data: </b>This dataset shows the uncropped western blots presented in figures 3A, 3B, 5D and 5E.<br><b>Data access:</b> Genomic datasets supporting figures 1 and 2 of the published article can be accessed from the bioinformatics portals Oncomine (www.oncomine.org) and cBioPortal (https://identifiers.org/cbioportal:brca_metabric) respectively. Datasets supporting figures 3, 4 and 5 of the published article are available upon request from the corresponding author Powel H. Brown, MD, PhD, Department of Clinical Cancer Prevention, The University of Texas M. D. Anderson Cancer Center, Houston, TX 77030. Phone: 713-7924509, Fax: 713-794-4679, Email: phbrown@mdanderson.org.<br>