Effect of TP53 missense mutation R172H on the single cell gene expression of pre-neoplastic mouse mammary gland
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ABSTRACT:
PROVIDER: PRJNA1000598 | ENA |
REPOSITORIES: ENA
Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| SRR25468278_1.fastq.gz | Fastqsanger.gz | |||
| SRR25468278_2.fastq.gz | Fastqsanger.gz | |||
| SRR25468279_1.fastq.gz | Fastqsanger.gz | |||
| SRR25468279_2.fastq.gz | Fastqsanger.gz |
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Project description:To screen the related miRNAs in the occurence and development of sebaceous gland carcinoma(SGC) of the eyelid , we have employed Human Agilient microarray expression profiling as a discovery platform to identify differentially expressed miRNAs for SGC and TP53 mtation related miRNAs. Human formalin-fixed paraffin-embedded (FFPE) SGC tissues and para-carcinoma sebaceous gland(SG) FFPE samples from SGC patients were screened using microarray assay. Human FFPE SGC tissues containing TP53 mutation and human FFPE SGC tissues without TP53 mutation were screened using microarray. The overlap of two sets of microarray differentially upregulated miRNAs were selected as our research object.
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Project description:TP53, encoding for the tumor suppressor p53, is the most frequently mutated gene in human cancer. The selective pressures shaping its mutational spectrum, dominated by missense mutations, have remained enigmatic, and neomorphic gain-of-function (GOF) activities have been implicated. We generated isogenic human leukemia cell lines of the most common TP53 missense mutations using CRISPR/Cas9. Functional, DNA binding, and transcriptional analyses revealed loss-of-function (LOF) without GOF effects of missense mutations. Comprehensive mutational scanning of p53 single amino acid variants demonstrated that DNA-binding domain missense variants exert dominant-negative effects (DNE). In mice, DNE of p53 missense variants confer a selective advantage on hematopoietic cells upon DNA damage in vivo. Clinical outcomes in acute myeloid leukemia patients showed no evidence of GOF for TP53 missense mutations. These findings establish dominant-negativity as the primary unit of selection for TP53 missense mutations in myeloid malignancies.
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Project description:TP53, encoding for the tumor suppressor p53, is the most frequently mutated gene in human cancer. The selective pressures shaping its mutational spectrum, dominated by missense mutations, have remained enigmatic, and neomorphic gain-of-function (GOF) activities have been implicated. We generated isogenic human leukemia cell lines of the most common TP53 missense mutations using CRISPR/Cas9. Functional, DNA binding, and transcriptional analyses revealed loss-of-function (LOF) without GOF effects of missense mutations. Comprehensive mutational scanning of p53 single amino acid variants demonstrated that DNA-binding domain missense variants exert dominant-negative effects (DNE). In mice, DNE of p53 missense variants confer a selective advantage on hematopoietic cells upon DNA damage in vivo. Clinical outcomes in acute myeloid leukemia patients showed no evidence of GOF for TP53 missense mutations. These findings establish dominant-negativity as the primary unit of selection for TP53 missense mutations in myeloid malignancies.
2019-08-30 | GSE131484 | GEO
Project description:SUMMARY Medulloblastoma is the most common malignant brain tumor in children. It is thought to result from transformation of granule cell precursors (GCPs) in the developing cerebellum, but little is known about the early stages of the disease. Here we identify a pre-neoplastic stage of medulloblastoma in patched heterozygous mice, a model of the human disease. We show that pre-neoplastic cells are present in the majority of patched mutants, although only 16% of these mice develop tumors. Pre-neoplastic cells, like tumor cells, exhibit activation of the Sonic hedgehog pathway and constitutive proliferation. Importantly, they also lack expression of the wild-type patched allele, suggesting that loss of patched is an early event in tumorigenesis. While pre-neoplastic cells resemble GCPs and tumor cells in many respects, they have a distinct molecular signature. Genes that mark the pre-neoplastic stage include regulators of migration, apoptosis and differentiation, processes critical for normal development but previously unrecognized for their role in medulloblastoma. The identification and molecular characterization of pre-neoplastic cells provides insight into the early steps in medulloblastoma formation, and may yield important markers for early detection and therapy of this disease. ANIMALS Patched heterozygous mice (Goodrich et al., 1997) were obtained from Matthew Scott's lab at Stanford, and maintained by breeding with 129X1/SvJ mice from Jackson Laboratories. Math1-GFP transgenic mice (Lumpkin et al., 2003) were provided by Jane Johnson at UT Southwestern Medical Center. Math1-GFP/patched+/- mice were generated by crossing patched heterozygotes with Math1-GFP mice, and then backcrossing to Math1-GFP mice three times before further analysis. All mice were maintained in the Cancer Center Isolation Facility at Duke University Medical Center. ISOLATION OF CELLS Granule cell precursors (GCPs) were isolated from 7-day-old (P7) patched+/- mice; preneoplastic cells were obtained from 6 week-old patched mutants; and tumor cells were obtained from 10-25-week old patched mutants displaying physical and behavioral signs of medulloblastoma. Cells were isolated from each source using a protocol described in (Wechsler- Reya and Scott, 1999). Briefly, cerebella were digested in solution containing 10 U/ml papain Oliver et al. Pre-Neoplastic Stage of Medulloblastoma - 8 - (Worthington, Lakewood, NJ) and 250 U/ml DNase (Sigma) and triturated to obtain a cell suspension. This suspension was centrifuged through a step gradient of 35% and 65% Percoll (Amersham Biosciences, Piscataway, NJ), and cells were harvested from the 35%-65% interface. Cells were resuspended in serum-free culture medium consisting of Neurobasal containing B27 supplement, sodium pyruvate, L-glutamine, and penicillin/streptomycin (all from Invitrogen, Carlsbad, California) and counted on a hemacytometer. Cells used for RNA isolation were centrifuged and flash frozen in liquid nitrogen. For proliferation assays or immunostaining, cells were plated on poly-D-lysine (PDL)-coated tissue culture vessels and incubated in serum-free culture medium. MICROARRAY HYBRIDIZATION AND ANALYSIS RNA from GCPs, pre-neoplastic cells and tumor cells (isolated as described above, but not FACS-sorted) and from normal adult cerebellum (not dissociated) was converted to cDNA using the Superscript Choice cDNA kit (Invitrogen) and a T7-dT(24) primer (Genset/Proligo, Boulder, CO). cRNA was generated using a T7-transcription/labeling kit from Enzo Life Sciences and hybridized to Affymetrix U74Av2 chips (Affymetrix, Santa Clara, CA). Chips were scanned, and hybridization data were acquired using Affymetrix Suite 5.0 software. Affymetrix CEL files were normalized and quantified using Bioconductor software with the gcRMA model to quantify gene expression levels (Gentleman and Carey, 2002). Unsupervised principal components analysis (PCA) was used to identify the relationships among normal adult cerebellum, GCPs, pre-neoplastic cells and tumor cells based on expression profiles. To identify genes that were differentially expressed among GCPs, pre-neoplastic cells and tumor cells, supervised analysis was carried out. A gene-by-gene ANOVA model with three groups (GCP, pre-neoplastic, tumor) was used to fit the log2-transformed intensities. To correct for multiple comparisons, the nominal p-value was adjusted using the false discovery rate (Benjamini and Hochberg, 1995). Genes were considered to be differentially expressed if they satisfied all of the following criteria: a difference in expression greater than 1.9-fold between any two groups, a maximum absolute intensity difference larger than 32 units, and an adjusted pvalue < 0.01. There were 118 genes that met these criteria. The identities of differentially expressed genes were verified by integrating data from the Affymetrix and Unigene databases. Gene functions were determined using information from Gene Ontology, Unigene, LocusLink and PubMed databases. Clustering was performed with Cluster and Treeview (Eisen et al., 1998). All statistical analysis was performed using R-1.7 software (Dalgaard, 2002). Results were visualized with Spotfire 6.0 (Somerville, MA). CORRESPONDING AUTHOR Robert J. Wechsler-Reya* Dept. of Pharmacology & Cancer Biology, Duke University Medical Center Box 3813, Durham, NC 27710 Phone: 919-613-8754. Fax: 919-668-3556. Email: rw.reya@duke.edu Keywords = medulloblastoma Keywords = brain tumor Keywords = pre-neoplastic Keywords = patched Keywords = hedgehog Keywords = migration Keywords = differentiation
2005-03-22 | GSE2426 | GEO