Opposing effects of estrogen and Runx2 on breast cancer cell proliferation: identification of a reciprocally-regulated gene signature with clinical prognostic value
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ABSTRACT:
ORGANISM(S): Homo sapiens
SUBMITTER: Chimge NO
PROVIDER: S-ECPF-GEOD-30597 | biostudies-other | 2012 Feb
REPOSITORIES: biostudies-other
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Project description:Analysis of reciprocal modulation of Runx2 and E2 signaling in BCA. Our objective was to investigate whether the interaction between estrogen and Runx2 signaling in breast cancer (BCa) could help refine an estrogen-responsive gene signature with improved prognostic value. MCF7/Rx2dox BCa cells conditionally expressing Runx2 upon doxycycline treatment were treated with estradiol and/or doxycycline to induce Runx2, and global gene expression was profiled to define genes regulated by estradiol, Runx2, or both.
2012-03-06 | E-GEOD-30597 | biostudies-arrayexpress
Project description:Analysis of reciprocal modulation of Runx2 and E2 signaling in BCA. Our objective was to investigate whether the interaction between estrogen and Runx2 signaling in breast cancer (BCa) could help refine an estrogen-responsive gene signature with improved prognostic value.
2012-03-06 | GSE30597 | GEO
Project description:To assess the clinical significance of the interaction between estrogen and Runx2 signaling, previously shown in vitro.MCF7/Rx2(dox) breast cancer cells were treated with estradiol and/or doxycycline to induce Runx2, and global gene expression was profiled to define genes regulated by estradiol, Runx2, or both. Anchorage-independent growth was assessed by soft-agar colony formation assays. Expression of gene sets defined using the MCF7/Rx2(dox) system was analyzed in pre- and on-treatment biopsies from hormone receptor-positive patients undergoing neoadjuvant letrozole treatment in two independent studies, and short-term changes in gene expression were correlated with tumor size reduction or Ki67 index at surgery.Reflecting its oncogenic property, estradiol strongly promoted soft-agar colony formation, whereas Runx2 blocked this process suggesting tumor suppressor property. Transcriptome analysis of MCF7/Rx2(dox) cells treated with estradiol and/or doxycycline showed reciprocal attenuation of Runx2 and estrogen signaling. Correspondingly in breast cancer tumors, expression of estradiol- and Runx2-regulated genes was inversely correlated, and letrozole increased expression of Runx2-stimulated genes, as defined in the MCF7/Rx2(dox) model. Of particular interest was a gene set upregulated by estradiol and downregulated by Runx2 in vitro; its short-term response to letrozole treatment associated with tumor size reduction and Ki67 index at surgery better than other estradiol-regulated gene sets.This work provides clinical evidence for the importance of antagonism between Runx2 and E2 signaling in breast cancer. Likely sensing the tension between them, letrozole responsiveness of a genomic node, positively regulated by estradiol and negatively regulated by Runx2 in vitro, best correlated with the clinical efficacy of letrozole treatment.
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Project description:RNA modifications implicate pathological and prognosis significance in cancer development and progression, of which, m6A and m5C are representative regulators. These RNA modifications could produce effects on the function of other RNA by regulating gene expression. Thus, in this study, we aimed to explore the correlation between m6A/m5C regulators and early-stage lung adenocarcinoma (LUAD). Only the early-stage LUAD samples were included in this investigation, and the RNA-seq dataset of The Cancer Genome Atlas (TCGA) cohort was utilized to evaluate the expression of 37 m6A/m5C regulated genes. Based on the expression level of these 37 genes, early-stage LUAD patients were divided into 2 clusters, which were performed by consensus clustering, and the m6A/m5C subtypes had significantly different prognostic outcomes (p < 0.001). Cluster1, which has a better prognosis, was characterized by the C3 (inflammatory) immune subtype, low immune infiltration, chemokine expression, major histocompatibility complex (MHC) expression, and immune checkpoint molecule expression. Furthermore, compared with cluster1, cluster2 showed a T cell exhaustion state, characterized by a high expression of immune checkpoint genes, and immune cells, such as T cells, CD8+ T cells, cytotoxic lymphocytes, NK cells, and so on. In addition, patients in cluster2 were with high tumor mutational burden (TMB) and numerous significant mutated oncogene and tumor suppressor genes, such as WNT10B, ERBB4, SMARCA4, TP53, and CDKN2A (p < 0.001). A total of 19 genes were mostly related to the prognosis of LUAD and were upregulated in cluster2 (p < 0.05), showing a positive correlation with the mRNA expression of 37 m6A/m5C regulated genes. The predictive risk model was constructed using Cox and LASSO (least absolute shrinkage and selection operator) regression analysis. Finally, a seven-gene m6A/m5C risk model, comprising of METTL3, NPLOC4, RBM15, YTHDF1, IGF2BP1, NSUN3, and NSUN7, was constructed to stratify the prognosis of early-stage LUAD (p = 0.0049, AUC = 0.791). The high-risk score was associated with a poorer prognosis. This model was also validated using two additional GEO datasets: GSE72094 (p = 0.011, AUC = 0.736) and GSE50081 (p = 0.012, AUC = 0.628). In summary, it was established that the m6A/m5C-regulated genes performed a crosstalk function in the mRNA expression of early-stage LUAD. By interacting with other mRNA genes, m6A/m5C modification disturbs DNA replication and the tumor immune microenvironment (TIME). The seven-gene risk model may be a critical tool for the prognostic assessment of early-stage LUAD.
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Project description:Gliomas are the most common and aggressive primary tumors in adults. The current approaches, such as histological classification and molecular genetics, have limitation in prediction of individual therapeutic outcomes due to heterogeneity within the tumor groups. Recent studies have proposed several gene signatures to predict glioma's prognosis. However, most of the gene expression profiling studies have been performed on relatively small number of patients and combined probes from diverse microarray chips. Here, we identified prognostic 89 common genes from diverse microarray chips. The 89-gene signature classified patients into good and bad prognostic groups which differed in the overall survival significantly, reflecting the biological characteristics and heterogeneity. The robustness and accuracy of the gene signature as an independent prognostic factor was validated in three microarray and one RNA-seq data sets independently. By incorporating into histological classification and molecular marker, the 89-gene signature could further stratify patients with 1p/19q co-deletion and IDH1 mutation. Additionally, subset analyses suggested that the 89-gene signature could predict patients who would benefit from adjuvant chemotherapy. Conclusively, we propose that the 89-gene signature would have an independent and accurate prognostic value for clinical use. This study also offers opportunities for novel targeted treatment of individual patients.
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Project description:BackgroundColon cancer is a common malignant tumor in the digestive tract. Exploring new treatment targets is of great significance for improving the survival rate of colon cancer patients. The present study mainly analyzes the impact of proliferation essential genes (PLEGs) on the prognosis and chemotherapy response of colon cancer patients, as well as identifying the expression and cellular functions of important PLEG.MethodsThe DepMap database was utilized for identification of PLEG in colon cancer cells. Through DEGs screening, WGCNA, univariate cox regression survival analysis, and LASSO, a PLEG signature (PLEGs) model was constructed. The impact of PLEGs on the prognosis of colon cancer patients and their response to chemotherapy was further analyzed. Finally, we conducted a random forest analysis and implemented functional experiments to investigate the prominent PLEG that is linked to the development of colon cancer.ResultsBased on the expression and prognosis of PLEG, we constructed a PLEGs prognosis model which can effectively predict the prognosis of colon cancer patients and their response to chemotherapy treatment. Random forest analysis showed that UBA1 is a key PLEG in the progression of colon cancer. Immunohistochemistry results revealed that UBA1 protein is significantly upregulated in colon cancer tissues. Cell functional experiments demonstrated that knocking down UBA1 can inhibit the proliferation, invasion, and migration abilities of colon cancer cells.ConclusionPLEGs have the potential to serve as predictive biomarkers for prognosis and chemotherapy response in colon cancer patients. Among the PLEG, UBA1 plays a prominent role in promoting the malignant progression of colon cancer cells.
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Project description:Tumour proliferation is one of the main biological phenotypes limiting cure in oncology. Extensive research is being performed to unravel the key players in this process. To exploit the potential of published gene expression data, creation of a signature for proliferation can provide valuable information on tumour status, prognosis and prediction. This will help individualizing treatment and should result in better tumour control, and more rapid and cost-effective research and development. From in vitro published microarray studies, two proliferation signatures were compiled. The prognostic value of these signatures was tested in five large clinical microarray data sets. More than 1000 patients with breast, renal or lung cancer were included. One of the signatures (110 genes) had significant prognostic value in all data sets. Stratifying patients in groups resulted in a clear difference in survival (P-values <0.05). Multivariate Cox-regression analyses showed that this signature added substantial value to the clinical factors used for prognosis. Further patient stratification was compared to patient stratification with several well-known published signatures. Contingency tables and Cramer's V statistics indicated that these primarily identify the same patients as the proliferation signature does. The proliferation signature is a strong prognostic factor, with the potential to be converted into a predictive test. Furthermore, evidence is provided that supports the idea that many published signatures track the same biological processes and that proliferation is one of them.
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Project description:Analyses whether, and if so, gene expression can add prognostic information in the subgroups of patients with tumours with low or high proliferative activity. As proliferation measured with MAI and PPH3 has repeatedly been shown to be the best prognosticator in node-negative breast cancer (high sensitivity, little overtreatment). Total RNA were extracted from 94 lymph node negative breast cancer patients
2014-03-05 | E-GEOD-46563 | biostudies-arrayexpress
Project description:Analyses whether, and if so, gene expression can add prognostic information in the subgroups of patients with tumours with low or high proliferative activity. As proliferation measured with MAI and PPH3 has repeatedly been shown to be the best prognosticator in node-negative breast cancer (high sensitivity, little overtreatment).
2014-03-05 | GSE46563 | GEO
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