Nascent proteome analysis of HCT116 TP53 wild type and TP53 knockout cells treated with Neocarcinostatin (NCS) for 6h
Ontology highlight
ABSTRACT:
INSTRUMENT(S): Orbitrap Fusion
ORGANISM(S): Homo Sapiens (human)
TISSUE(S): Epithelial Cell, Colon
DISEASE(S): Colon Cancer
SUBMITTER: 
Toman Bortecen
LAB HEAD: Jeroen Krijgsveld
PROVIDER: PXD029512 | Pride | 2022-04-27
REPOSITORIES: Pride
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Project description:Background: Gene expression profiling of breast carcinomas has increased our understanding of the heterogeneous biology of this disease and promises to impact clinical care. The aim of this study was to evaluate the prognostic value of gene expression-based classification along with established prognostic markers and mutation status of the TP53 gene, in a group of breast cancer patients with long-term (12-16 years) follow-up. Methods: The clinical and histopathological parameters of 200 breast cancer patients were studied for their effects on clinical outcome using univariate/multivariate Cox regression. The prognostic impact of mutations in the TP53 gene, identified using TTGE and sequencing, was also evaluated. Eighty of the samples were analyzed for gene expression using 42K cDNA microarrays and the patients were assigned to five previously defined molecular expression groups. The strength of the gene expression based classification versus standard markers was evaluated by adding this variable to the Cox regression model used to analyze all samples. Results: Both univariate and multivariate analysis showed that TP53 mutation status, tumor size and lymph node status were the strongest predictors of breast cancer survival for the whole group of patients. Analyses of the patients with gene expression data showed that TP53 mutation status, gene expression based classification, tumor size and lymph node status were significant predictors of survival. The TP53 mutation status showed strong association with the ?basal-like? and ?ERBB2+? gene expression subgroups, and tumors with mutation had a characteristic gene expression pattern. Conclusions: TP53 mutation status and gene-expression based groups are important survival markers of breast cancer, and these molecular markers may provide prognostic information that complements clinical variables. The study adds experience and knowledge to an ongoing characterization and classification of the disease. Experiment set consisting of 80 primary breast carcinomas collected at Ulleval University Hospital (ULL-samples), Oslo, Norway from 1990-94, and one normal sample from breast reduction surgery.
2012-09-18 | E-GEOD-40954 | biostudies-arrayexpress
Project description:SARS-CoV-2 induces widespread transcriptomic changes in host cells upon infection, in part through activation and modulation of innate immunity pathways and downstream gene regulation. However, the mechanisms by which SARS-CoV-2 and its evolutionary variants differentially affect host cell transcriptomic states remain largely unclear. Through chromatin proteomic (iDAPT-MS) analysis, we found that although SARS-CoV-2 and other pathogenic coronaviruses exhibit similar proteomic shifts on chromatin, SARS-CoV-2 uniquely promotes TP53 nuclear accumulation and activation. Parallel assessment of SARS-CoV-2 viral protein expression on host chromatin states (ATAC-seq) identifies intracellular spike protein as a key determinant of virus-mediated chromatin accessibility changes. Multilevel chromatin profiling reveals increased TP53 nuclear accumulation, TP53-associated chromatin accessibility changes, and TP53 target gene activation upon expression of SARS-CoV-2 alpha (B.1.1.7) and delta (B.1.617.2) spike variants relative to the ancestral spike sequence. TP53, ACE2, and furin cleavage are required for these changes, driving decreased cellular proliferation, increased cellular senescence, and increased cytokine release. Finally, BA.1 but not BA.2, BA.2.12.1, nor BA.4/BA.5 spike expression leads to attenuated TP53 activity and fusogenicity relative to ancestral spike. Our findings implicate spike-mediated host TP53 activation as a “rheostat” of COVID-19 pathogenicity.
2023-09-09 | PXD034648 | Pride
Project description:The adaptor protein LNK (SH2B3) has emerged as an important protein in regulating B cell development B cell leukemia. Loss-of-function mutations in LNK (SH2B3) are found in Philadelphia chromosomeâlike acute lymphoblastic leukemia (Ph-like ALL), but how LNK regulates normal B cell development or promotes leukemogenesis remains unclear. We found that combined loss of Lnk and tumor suppressors Tp53 in mice triggers a highly aggressive and transplantable precursor B-ALL. This study aims to investigate the molecular mechanism by which LNK regulates B-ALL development. We performed expression profiling of bone marrow proB progenitors from WT, Tp53-/-, Lnk-/- and preleukemic healthy Tp53/Lnk double knockout (DKO) mice, as well as leukemic bone marrow cells from DKO mice that have developed B-ALL. Results suggest that Tp53-/-Lnk-/- B-ALLs display similar gene expression profiles to human Ph-like B-ALLs, suggesting this model for preclinical and molecular studies. B220+CD19+CD43+AA4.1+IgM-NK1.1-Ly6c- bone marrow proB cells were double sorted from WT, Tp53-/-, Lnk-/- and preleukemic healthy Tp53/Lnk double knockout (DKO) mice, as well as leukemic bone marrow cells from DKO mice that have developed B-ALL. RNA was isolated using miRNeasy kit from QIAGEN and processed using the NuGEN Pico kit. The microarray analysis was performed at the PENN Molecular Profiling/Genomics Facility using GeneChip Mouse Gene 2.0ST array (Affymetrix).
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Project description:Li-Fraumeni syndrome (LFS) is a rare, clinically and genetically heterogeneous inherited cancer syndrome. Most cases are due to mutations in TP53. CHK2 is a minor predisposing locus; we recently mapped a third locus to 1q23. In both TP53 and non-TP53 LFS, there is evidence for risk heterogeneity within and between kindreds, suggesting additional risk modifiers. Using BAC- and SNP-based microarrays, we performed genomic profiling of primary soft tissue sarcomas, osteosarcomas and matching constitutive samples of 10 LFS patients (6 with and 4 without TP53 mutations), to identify genome-wide patterns of copy number changes and loss-of-heterozygosity (LOH). Our complementing global approaches revealed several interesting patterns for TP53 and non-TP53 LFS tumors, including positive (1q/7, 3p/15, 4q/9q, 8q/19p, 9p/10q, 13/14 and 15q/18q) and negative (2q/9q, 3q/14q and 4q/6q) associations between chromosomal regions. The region containing the oncogene TWIST1 (7p21.1) was the most common gain independent of TP53 status and tumor type, while LOH of 8q11.2 with the tumor suppressor ST18 was the only region exclusively associated with non-TP53 soft tissue sarcomas. We resequenced known mutations in BRAF, KRAS and NRAS and identified somatic NRAS mutations in 2 of 10 tumors. TP53 and non-TP53 LFS tumors shared multiple hits in genes of the p53 and overlapping pathways. Although common dogma in cancer genetics holds that multiple hits in the same pathway are redundant and thus unlikely, we show that different combinations of genetic alterations in both TP53 and non-TP53 LFS tumors appear to act together in the p53 network in LFS tumorigenesis Keywords: Comparative genomic hybridization Using the Spectral Genomics dye-swap BAC arrays we studied 10 Li Fraumeni syndrome tumor cases
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2016-04-01 | GSE76940 | GEO
Project description:TP53 mutations are a poor prognostic factor in breast cancers. This study sets out to identify the gene set that determine expression signature of the TP53 status (TP53 signature) and to correlate it with clinical outcome. Using comprehensive expression analysis and DNA sequencing of the TP53 gene in 38 Japanese breast cancer patients, we have isolated a gene set of 33 genes from differentially expressed genes in the learning set (n=26), depending on the TP53 status. Predictive accuracy of TP53 status by gene expression profile was 83.3% in the test set (n=12). As independent external datasets, two published datasets were introduced for validation of TP53 status prediction (251 Swedish samples) and survival analysis (both the Swedish and 295 Dutch samples). TP53 signature has the ability to predict recurrence-free survival (RFS) of 29 stage I and II Japanese breast cancers (log rank, P = 0.032), and RFS, overall survival of two independently published datasets (log rank, both P < 0.0001). Multivariate analysis has shown an independent and significant prognostic factor with a hazard ratio (HR) for recurrence and survival in two external datasets (P < 0.0001). The TP53 signature is also a strong prognostic factor in the subgroups: estrogen-receptor positive, lymph node (LN) positive and negative, intermediate/high risk in St. Gallen criteria, and high risk in National Cancer Institute (NCI) criteria (log rank, P < 0.0001). TP53 signature is a reliable and independent predictor of the outcome of disease in operated breast cancer. Experiment Overall Design: Microarray hybridizations (Agilent: Whole Human Genome Oligo Microarray; 41k unique probe) were carried out with 1μg Cy3 labeled cRNA and 1 μg Cy5 labeled cRNA, both prepared from each sample and reference pool, respectively. Experiment Overall Design: Fluorescent intensities of scanned images were quantified by ArrayVision Ver.8 rev.4 (Imaging research). Experiment Overall Design: The gene expression data was quantified and analyzed by GeneSpring 6.2 (Silicon Genetics). To identify the TP53 status predictor gene set, a Wilcoxon rank sum test along with Benjamini and Hochberg false discovery rate (FDR) was used.
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Project description:Purpose: Next-generation sequencing (NGS) has revolutionized systems-based analysis of cellular pathways. The goals of this study are to compare TP53-WT and TP53-KO HCT116 cells transcriptome profiling (RNA-seq) under 5-FU treatment condition and to evaluate the correlation between transcriptome profileing and chromatin accessibility under 5-FU treatment. Methods: HCT116 cell profiles of TP53-WT and TP53- KO were generated by deep sequencing, in duplicates, using Illumina GAIIx. The sequence reads that passed quality filters were analyzed at the transcript isoform levels: Burrows–Wheeler Aligner (BWA) followed by ANOVA (ANOVA). Conclusions: Our study represents the detailed analysis of TP53-WT and TP53-KO HCT116 cell transcriptomes under 5-FU treatment with different timepoint, with biologic replicates, generated by RNA-seq technology. The optimized data analysis workflows reported here should provide a framework for comparative investigations of expression profiles. Our results show that RNA-seq offers a comprehensive and more accurate quantitative and qualitative evaluation of mRNA content within a TP53-WT and TP53-KO cells with and without 5-FU treatment in different timepoint. We conclude that NGS based transcriptome characterization would expedite genetic network analyses and permit the dissection of complex biologic functions.
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