Dataset Information

Notch signaling pathway: a comprehensive prognostic and gene expression profile analysis in breast cancer.

ABSTRACT: Breast cancer is a complex disease exhibiting a great degree of heterogeneity due to different molecular subtypes. Notch signaling regulates the differentiation of breast epithelial cells during normal development and plays a crucial role in breast cancer progression through the abnormal expression of the Notch up-and down-stream effectors. To date, there are only a few patient-centered clinical studies using datasets characterizing the role of Notch signaling pathway regulators in breast cancer; thus, we investigate the role and functionality of these factors in different subtypes using publicly available databases containing records from large studies. High-throughput genomic data and clinical information extracted from TCGA were analyzed. We performed Kaplan-Meier survival and differential gene expression analyses using the HALLMARK_NOTCH_SIGNALING gene set. To determine if epigenetic regulation of the Notch regulators contributes to their expression, we analyzed methylation levels of these factors using the TCGA HumanMethylation450 Array data. Notch receptors and ligands expression is generally associated with the tumor subtype, grade, and stage. Furthermore, we showed gene expression levels of most Notch factors were associated with DNA methylation rate. Modulating the expression levels of Notch receptors and effectors can be a potential therapeutic approach for breast cancer. As we outline herein, elucidating the novel prognostic and regulatory roles of Notch implicate this pathway as an essential mediator controlling breast cancer progression.

SUBMITTER: Yousefi H

PROVIDER: S-EPMC9730604 | biostudies-literature | 2022 Dec

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Notch signaling pathway: a comprehensive prognostic and gene expression profile analysis in breast cancer.

Yousefi Hassan H Bahramy Afshin A Zafari Narges N Delavar Mahsa Rostamian MR Nguyen Khoa K Haghi Atousa A Kandelouei Tahmineh T Vittori Cecilia C Jazireian Parham P Maleki Sajad S Imani Danyal D Moshksar Amin A Bitaraf Amirreza A Babashah Sadegh S Babashah Sadegh S

BMC cancer 20221207 1

Breast cancer is a complex disease exhibiting a great degree of heterogeneity due to different molecular subtypes. Notch signaling regulates the differentiation of breast epithelial cells during normal development and plays a crucial role in breast cancer progression through the abnormal expression of the Notch up-and down-stream effectors. To date, there are only a few patient-centered clinical studies using datasets characterizing the role of Notch signaling pathway regulators in breast cancer ...[more]

PMID: 36476410

Similar Datasets

Project description:BackgroundLoss of G2-specific E3-like (G2E3) protein sensitizes tumor cells to chemotherapy. However, the role of G2E3 in breast cancer development and patient's prognosis is unclear. Here, we explored the expression, prognostic significance, and regulatory pathway of G2E3 in breast cancer.MethodsTCGA and UALCAN database were utilized to explore G2E3 expression in breast cancer and normal tissues and its expression in breast cancer based on clinicopathological characteristics, respectively. The Kaplan-Meier plotter database was utilized to determine the effect of G2E3 on the prognosis of breast cancer patients. RT-PCR was utilized to validate the G2E3 expression in cancerous and normal breast tissues. Immunohistochemistry analysis was utilized to validate the prognostic effect of G2E3 expression in breast cancer patients and the relationship between G2E3 expression and lymphocyte infiltration levels. Receiver operating characteristic (ROC) curves were also generated to validate the diagnostic value of G2E3 expression in recurrence/distant organ metastasis and death. The STRING database, DAVID database, and Sanger-box tools were utilized to perform GO functional, KEGG pathway enrichment, and GSEA analysis. The TISIDB database was utilized to determine the relationship between G2E3 expression and tumor immunity. Finally, CTD database was utilized to screen for potential therapeutic compounds that could reduce the G2E3 mRNA expression.ResultsTCGA data presented that G2E3 expression was higher in breast cancer tissues than in normal breast tissues. This result was further validated by RT-PCR (P = 0.003). The Kaplan-Meier plotter database suggested that patients with high G2E3 mRNA expression had significantly shorter RFS and OS than patients with low G2E3 mRNA expression. Immunohistochemistry analysis of 156 breast cancer clinical specimens also validated patients with G2E3-positive expression had a significantly shorter DFS and OS than patients with G2E3-negative expression. Thus, G2E3 expression was an independent prognostic predictor of DFS and OS. The G2E3-positive expression also has a high diagnostic value for recurrence/distant organ metastasis and death. GSEA analysis revealed that G2E3 might be enriched in the E2F, PI3K/AKT/mTOR signaling, DNA repair pathways, and other cancer-related signaling pathways. The TISIDB database showed that G2E3 expression was significantly negatively associated with lymphocyte infiltration. This result was further validated in clinical breast cancer samples (P = 0.048; R = -0.158). Using the CTD database, we found that (+)-JQ1 compound, 1,2-dimethylhydrazine, and other compounds may decrease the G2E3 mRNA expression. These compounds could serve as potential therapeutic compounds for the clinical treatment of breast cancer.ConclusionsG2E3 expression was higher in breast cancer tissues than in normal tissues. G2E3-positive expression was related to a worse survival outcome in patients with breast cancer. Genes co-expressed with G2E3 may be enriched in the breast cancer-related signaling pathways. The G2E3 expression was significantly negatively associated with lymphocyte infiltration. G2E3 may serve as a novel prognostic biomarker and therapeutic target for breast cancer.

Project description:Breast cancer accounts for nearly half of all cancer-related deaths in women worldwide. However, the molecular mechanisms that lead to tumour development and progression remain poorly understood and there is a need to identify candidate genes associated with primary and metastatic breast cancer progression and prognosis. In this study, candidate genes associated with prognosis of primary and metastatic breast cancer were explored through a novel bioinformatics approach. Primary and metastatic breast cancer tissues and adjacent normal breast tissues were evaluated to identify biomarkers characteristic of primary and metastatic breast cancer. The Cancer Genome Atlas-breast invasive carcinoma (TCGA-BRCA) dataset (ID: HS-01619) was downloaded using the mRNASeq platform. Genevestigator 8.3.2 was used to analyse TCGA-BRCA gene expression profiles between the sample groups and identify the differentially-expressed genes (DEGs) in each group. For each group, Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathway enrichment analyses were used to determine the function of DEGs. Networks of protein-protein interactions were constructed to identify the top hub genes with the highest degree of interaction. Additionally, the top hub genes were validated based on overall survival and immunohistochemistry using The Human Protein Atlas. Of the top 20 hub genes identified, four (KRT14, KIT, RAD51, and TTK) were considered as prognostic risk factors based on overall survival. KRT14 and KIT expression levels were upregulated while those of RAD51 and TTK were downregulated in patients with breast cancer. The four proposed candidate hub genes might aid in further understanding the molecular changes that distinguish primary breast tumours from metastatic tumours as well as help in developing novel therapeutics. Furthermore, they may serve as effective prognostic risk markers based on the strong correlation between their expression and patient overall survival.

Dataset Information

Notch signaling pathway: a comprehensive prognostic and gene expression profile analysis in breast cancer.

Publications

Notch signaling pathway: a comprehensive prognostic and gene expression profile analysis in breast cancer.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets