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Screening and Identification of Novel Potential Biomarkers for Breast Cancer Brain Metastases.

ABSTRACT: Brain metastases represent a major cause of mortality among patients with breast cancer, and few effective targeted treatment options are currently available. Development of new biomarkers and therapeutic targets for breast cancer brain metastases (BCBM) is therefore urgently needed. In this study, we compared the gene expression profiles of the brain metastatic cell line MDA-MB-231-BR (231-BR) and its parental MDA-MB-231, and identified a total of 84 genes in the primary screening through a series of bioinformatic analyses, including construction of protein-protein interaction (PPI) networks by STRING database, identification of hub genes by applying of MCODE and Cytohubba algorithms, identification of leading-edge subsets of Gene Set Enrichment Analysis (GSEA), and identification of most up-regulated genes. Eight genes were identified as candidate genes due to their elevated expression in brain metastatic 231-BR cells and prognostic values in patients with BCBM. Then we knocked down the eight individual candidate genes in 231-BR cells and evaluated their impact on cell migration through a wound-healing assay, and four of them (KRT19, FKBP10, GSK3B and SPANXB1) were finally identified as key genes. Furthermore, the expression of individual key genes showed a correlation with the infiltration of major immune cells in the brain tumor microenvironment (TME) as analyzed by Tumor Immune Estimation Resource (TIMER) and Gene Expression Profiling Interactive Analysis (GEPIA), suggesting possible roles of them in regulation of the tumor immune response in TME. Therefore, the present work may provide new potential biomarkers for BCBM. Additionally, using GSEA, Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) Enrichment Analysis, we determined the top enriched cellular functions or pathways in 231-BR cells, which may help better understand the biology governing the development and progression of BCBM.

SUBMITTER: Wang L

PROVIDER: S-EPMC8792448 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:PurposeThe prognosis of breast cancer (BC) patients who develop into brain metastases (BMs) is very poor. Thus, it is of great significance to explore the etiology of BMs in BC and identify the key genes involved in this process to improve the survival of BC patients with BMs.Patients and methodsThe gene expression data and the clinical information of BC patients were downloaded from TCGA and GEO database. Differentially expressed genes (DEGs) in TCGA-BRCA and GSE12276 were overlapped to find differentially expressed metastatic genes (DEMGs). The protein-protein interaction (PPI) network of DEMGs was constructed via STRING database. ClusterProfiler R package was applied to perform the gene ontology (GO) enrichment analysis of DEMGs. The univariate Cox regression analysis and the Kaplan-Meier (K-M) curves were plotted to screen DEMGs associated with the overall survival and the metastatic recurrence survival, which were identified as the key genes associated with the BMs in BC. The immune infiltration and the expressions of immune checkpoints for BC patients with brain relapses and BC patients with other relapses were analyzed respectively. The correlations among the expressions of key genes and the differently infiltrated immune cells or the differentially expressed immune checkpoints were calculated. The gene set enrichment analysis (GSEA) of each key gene was conducted to investigate the potential mechanisms of key genes involved in BC patients with BMs. Moreover, CTD database was used to predict the drug-gene interaction network of key genes.ResultsA total of 154 DEGs were identified in BC patients at M0 and M1 in TCGA database. A total of 667 DEGs were identified in BC patients with brain relapses and with other relapses. By overlapping these DEGs, 17 DEMGs were identified, which were enriched in the cell proliferation related biological processes and the immune related molecular functions. The univariate Cox regression analysis and the Kaplan-Meier curves revealed that CXCL9 and GPR171 were closely associated with the overall survival and the metastatic recurrence survival and were identified as key genes associated with BMs in BC. The analyses of immune infiltration and immune checkpoint expressions showed that there was a significant difference of the immune microenvironment between brain relapses and other relapses in BC. GSEA indicated that CXCL9 and GPR171 may regulate BMs in BC via the immune-related pathways.ConclusionOur study identified the key genes associated with BMs in BC patients and explore the underlying mechanisms involved in the etiology of BMs in BC. These findings may provide a promising approach for the treatments of BC patients with BMs.

Project description:BACKGROUND:Breast cancer brain metastases (BCBM) develop in about 20-30% of breast cancer (BC) patients. BCBM are associated with dismal prognosis not at least due to lack of valuable molecular therapeutic targets. The aim of the study was to identify new molecular biomarkers and targets in BCBM by using complementary state-of-the-art techniques. METHODS:We compared array expression profiles of three BCBM with 16 non-brain metastatic BC and 16 primary brain tumors (prBT) using a false discovery rate (FDR) p < 0.05 and fold change (FC) > 2. Biofunctional analysis was conducted on the differentially expressed probe sets. High-density arrays were employed to detect copy number variations (CNVs) and whole exome sequencing (WES) with paired-end reads of 150 bp was utilized to detect gene mutations in the three BCBM. RESULTS:The top 370 probe sets that were differentially expressed between BCBM and both BC and prBT were in the majority comparably overexpressed in BCBM and included, e.g. the coding genes BCL3, BNIP3, BNIP3P1, BRIP1, CASP14, CDC25A, DMBT1, IDH2, E2F1, MYCN, RAD51, RAD54L, and VDR. A number of small nucleolar RNAs (snoRNAs) were comparably overexpressed in BCBM and included SNORA1, SNORA2A, SNORA9, SNORA10, SNORA22, SNORA24, SNORA30, SNORA37, SNORA38, SNORA52, SNORA71A, SNORA71B, SNORA71C, SNORD13P2, SNORD15A, SNORD34, SNORD35A, SNORD41, SNORD53, and SCARNA22. The top canonical pathway was entitled, role of BRCA1 in DNA damage response. Network analysis revealed key nodes as Akt, ERK1/2, NFkB, and Ras in a predicted activation stage. Downregulated genes in a data set that was shared between BCBM and prBT comprised, e.g. BC cell line invasion markers JUN, MMP3, TFF1, and HAS2. Important cancer genes affected by CNVs included TP53, BRCA1, BRCA2, ERBB2, IDH1, and IDH2. WES detected numerous mutations, some of which affecting BC associated genes as CDH1, HEPACAM, and LOXHD1. CONCLUSIONS:Using complementary molecular genetic techniques, this study identified shared and unshared molecular events in three highly aberrant BCBM emphasizing the challenge to detect new molecular biomarkers and targets with translational implications. Among new findings with the capacity to gain clinical relevance is the detection of overexpressed snoRNAs known to regulate some critical cellular functions as ribosome biogenesis.

Project description:Brain metastases are an increasing burden among breast cancer patients, particularly for those with HER2+ and triple negative (TN) subtypes. Mechanistic insight into the pathophysiology of brain metastases and preclinical validation of therapies has relied almost exclusively on intracardiac injection of brain-homing cells derived from highly aggressive TN MDA-MB-231 and HER2+ BT474 breast cancer cell lines. Yet, these well characterized models are far from representing the tumor heterogeneity observed clinically and, due to their fast progression in vivo, their suitability to validate therapies for established brain metastasis remains limited. The goal of this study was to develop and characterize novel human brain metastasis breast cancer patient-derived xenografts (BM-PDXs) to study the biology of brain metastasis and to serve as tools for testing novel therapeutic approaches. We obtained freshly resected brain metastases from consenting donors with breast cancer. Tissue was immediately implanted in the mammary fat pad of female immunocompromised mice and expanded as BM-PDXs. Brain metastases from 3/4 (75%) TN, 1/1 (100%) estrogen receptor positive (ER+), and 5/9 (55.5%) HER2+ clinical subtypes were established as transplantable BM-PDXs. To facilitate tracking of metastatic dissemination using BM-PDXs, we labeled PDX-dissociated cells with EGFP-luciferase followed by reimplantation in mice, and generated a BM-derived cell line (F2-7). Immunohistologic analyses demonstrated that parental and labeled BM-PDXs retained expression of critical clinical markers such as ER, progesterone receptor, epidermal growth factor receptor, HER2, and the basal cell marker cytokeratin 5. Similarly, RNA sequencing analysis showed clustering of parental, labeled BM-PDXs and their corresponding cell line derivative. Intracardiac injection of dissociated cells from BM-E22-1, resulted in magnetic resonance imaging-detectable macrometastases in 4/8 (50%) and micrometastases (8/8) (100%) mice, suggesting that BM-PDXs remain capable of colonizing the brain at high frequencies. Brain metastases developed 8-12?weeks after ic injection, located to the brain parenchyma, grew around blood vessels, and elicited astroglia activation characteristic of breast cancer brain metastasis. These novel BM-PDXs represent heterogeneous and clinically relevant models to study mechanisms of brain metastatic colonization, with the added benefit of a slower progression rate that makes them suitable for preclinical testing of drugs in therapeutic settings.

Project description:Brain metastases originating from lung adenocarcinoma (LAD) occur frequently. The aim of the current study was to assess potential biomarkers for the prognosis of lung adenocarcinoma brain metastasis (LAD-BM) through the analysis of gene expression microarrays. The current study downloaded two gene expression datasets, GSE14108 and GSE10245, from the Gene Expression Omnibus database. From GSE14108 and GSE10245, 19 LAD-BM samples and 40 primary LAD samples were selected for analysis. To identify the differentially expressed genes (DEGs), the current study compared the two sample groups, using the limma R package. Subsequently, pathway enrichment analysis was conducted using the Cluster Profiler R package, and the construction of the protein-protein interaction (PPI) network was executed utilizing the Search Tool for the Retrieval of Interacting Genes database. The microRNA-target network was built using the TargetScore R package. Then, these networks were established and visualized using Cytoscape software. An array of 463 DEGs was identified in the LAD-BM samples, including 256 upregulated and 207 downregulated genes. Based on functional term enrichment analysis using the Gene Ontology database and signaling pathway enrichment analysis using the Kyoto Encyclopedia of Genes and Genomes database, it was identified that the overlapping DEGs were primarily involved in chemokine-associated signal transduction, which may mediate lung cancer cell metastasis to the brain. Chemokine ligand 2, lysozyme, matrix metalloproteinase-2 (MMP-2), lysyl oxidase (LOX) and granzyme B were identified as potential biomarkers according to a topological analysis of the PPI networks. Two notable nodes, MMP-2 and LOX, appeared in the PPI network and were key points in the microRNA-target network, as they were regulated by hsa-let-7d. Many DEGs and microRNAs were regarded as prognostic biomarkers for lung adenocarcinoma metastasis in the current study. These DEGs were primarily associated with chemokine-mediated signaling pathways. In addition, MMP-2 and LOX were predicted to be targets of hsa-let-7d.

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Screening and Identification of Novel Potential Biomarkers for Breast Cancer Brain Metastases.

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