Identification of potential genes related to breast cancer brain metastasis in breast cancer patients

Zhang, Lijian; Wang, Luxuan; Yang, Hua; Li, Chunhui; Fang, Chuan

doi:10.1042/bsr20211615

Cited by 30 publications

(18 citation statements)

References 59 publications

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“…e extracellular matrix a ects cancer cell characteristics and is related to cell metastasis [22]. e ECM structural constituent, ECM organization, and collagen catabolic process might be responsible for the occurrence of BM in BC patients [23]. In the present study, we conducted GO annotation and KEGG pathway analyses on 19 overlapped DEGs between primary BC and BM samples.…”

Section: Discussionmentioning

confidence: 97%

Comprehensive Analysis Identifies COL1A1, COL3A1, and POSTN as Key Genes Associated with Brain Metastasis in Patients with Breast Cancer

Zheng

2022

Evidence-Based Complementary and Alternative Medicine

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Objective. Brain metastasis (BM) is associated with a high mortality in patients with breast cancer (BC). Nevertheless, the molecular mechanisms of BM in BM remain uncertain. The study aims to identify the key genes in BC in relation to BM and to assess their prognostic value. Methods. Two microarray datasets GSE125989 and GSE100534 were downloaded from the Gene Expression Omnibus (GEO) database to identify differentially expressed genes (DEGs) between primary BC and BM samples. The function enrichment analysis and protein-protein interaction (PPI) network were performed. We mapped hub genes into the Kaplan–Meier database for their correlations with BC survival. Results. Venn diagram analysis showed an overlapped upregulated DEG and 18 overlapped downregulated ones between primary BC and BM samples. We constructed the PPI network, and top 5 hub genes were sorted out according to the node degree, including type I collagen α1 chain (COL1A1), lumican (LUM), type III collagen α1 chain (COL3A1), type V collagen α2 chain (COL5A2), and periosteal protein (POSTN). The Kaplan–Meier database analysis found that COL1A1, COL3A1, and POSTN were significantly correlated with overall survival of BC patients. Conclusion. The study suggests that COL1A1, COL3A1, and POSTN may be key genes associated with BM in patients with BC.

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Section: Discussionmentioning

confidence: 97%

Comprehensive Analysis Identifies COL1A1, COL3A1, and POSTN as Key Genes Associated with Brain Metastasis in Patients with Breast Cancer

Zheng

2022

Evidence-Based Complementary and Alternative Medicine

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“…For example, the high expression levels of the five genes correlated well with the OS ( p -value = 0.00072, n = 737) and RFS ( p -value = 0.00001, n = 914) for patients with several subtypes of BC as compared to those with the low expression of these genes ( Figure 4 c,d). As collagen genes are considered crucial for the stromal microenvironment and extracellular matrix remodeling [ 53 , 54 ], while hypoxia inducible NPY1R [ 55 ] has been shown to be a determinant of breast cancer responsiveness to hormonal sensitivity and a secreted predictive marker for breast cancer metastasis [ 56 , 57 ], the increased expression of these molecules might be associated with a poor prognosis. We also noticed a significant positive Spearman correlation of these five genes with the gene sets related to stroma, lipid, early response, and steroid response ( p (ANOVA) ≤ 0.00001; Figure 4 e).…”

Section: Resultsmentioning

confidence: 99%

Delineation of Pathogenomic Insights of Breast Cancer in Young Women

Paul

George

Saini

et al. 2022

Cells

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The prognosis of breast cancer (BC) in young women (BCYW) aged ≤40 years tends to be poorer than that in older patients due to aggressive phenotypes, late diagnosis, distinct biologic, and poorly understood genomic features of BCYW. Considering the estimated predisposition of only approximately 15% of the BC population to BC-promoting genes, the underlying reasons for an increased occurrence of BCYW, at large, cannot be completely explained based on general risk factors for BC. This underscores the need for the development of next-generation of tissue- and body fluid-based prognostic and predictive biomarkers for BCYW. Here, we identified the genes associated with BCYW with a particular focus on the age, intrinsic BC subtypes, matched normal or normal breast tissues, and BC laterality. In young women with BC, we observed dysregulation of age-associated cancer-relevant gene sets in both cancer and normal breast tissues, sub-sets of which substantially affected the overall survival (OS) or relapse-free survival (RFS) of patients with BC and exhibited statically significant correlations with several gene modules associated with cellular processes such as the stroma, immune responses, mitotic progression, early response, and steroid responses. For example, high expression of COL1A2, COL5A2, COL5A1, NPY1R, and KIAA1644 mRNAs in the BC and normal breast tissues from young women correlated with a substantial reduction in the OS and RFS of BC patients with increased levels of these exemplified genes. Many of the genes upregulated in BCYW were overexpressed or underexpressed in normal breast tissues, which might provide clues regarding the potential involvement of such genes in the development of BC later in life. Many of BCYW-associated gene products were also found in the extracellular microvesicles/exosomes secreted from breast and other cancer cell-types as well as in body fluids such as urine, saliva, breast milk, and plasma, raising the possibility of using such approaches in the development of non-invasive, predictive and prognostic biomarkers. In conclusion, the findings of this study delineated the pathogenomics of BCYW, providing clues for future exploration of the potential predictive and prognostic importance of candidate BCYW molecules and research strategies as well as a rationale to undertake a prospective clinical study to examine some of testable hypotheses presented here. In addition, the results presented here provide a framework to bring out the importance of geographical disparities, to overcome the current bottlenecks in BCYW, and to make the next quantum leap for sporadic BCYW research and treatment.

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“…Moreover, the PPI network was created, with 29 hub genes being identified. After being examined through the cBioportal online platform and the Oncomine database, 8 key genes were finally obtained, including COL14A1, COL3A1, COL6A3, THY1, MMP14, GAP43, PTPRN, and SNAP25, of which COL3A1 and COL6A3 were also identified to play potentially important roles in BMBC in patients with breast cancer in a recent study [ 8 ].…”

Section: Discussionmentioning

confidence: 99%

Identification of Key Genes Associated with Brain Metastasis from Breast Cancer: A Bioinformatics Analysis

et al. 2022

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Background As the second most frequent factor of brain metastasis worldwide, breast cancer and its pathogenesis have been researched intensively. Nevertheless, the molecular mechanisms of brain metastasis from breast cancer (BMBC) remain uncertain. The purpose of this study was to explore the key genes concerning the prognosis of BMBC and identify their predictive value. Material/Methods Obtained from the Gene Expression Omnibus (GEO) database, microarray datasets GSE125989, GSE52604, and GSE159956 were used to identify the differentially expressed genes (DEGs) and perform function enrichment analysis. Results Of a total of 240 DEGs, 113 genes were upregulated and 127 genes were downregulated. The protein–protein interaction (PPI) was performed through STRING, and 29 hub genes were screened through Cytoscape. After being examined through the cBioportal online platform and the Oncomine database, 8 key genes were finally obtained, including COL14A1, COL3A1, COL6A3, THY1, MMP14, GAP43, PTPRN, and SNAP25. In the validation dataset GSE46928, COL14A1 was shown to have predictive significance of brain metastasis in breast cancer. Conclusions The key genes explored in this article could assist in identifying the molecular mechanism of BMBC. Also, COL14A1, COL3A1, COL6A3, THY1, MMP14, GAP43, PTPRN, and SNAP25 might be candidate targets for diagnosis and treatment of BMBC, and COL3A1 might have predictive value.

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Identification of potential genes related to breast cancer brain metastasis in breast cancer patients

Cited by 30 publications

References 59 publications

Comprehensive Analysis Identifies COL1A1, COL3A1, and POSTN as Key Genes Associated with Brain Metastasis in Patients with Breast Cancer

Comprehensive Analysis Identifies COL1A1, COL3A1, and POSTN as Key Genes Associated with Brain Metastasis in Patients with Breast Cancer

Delineation of Pathogenomic Insights of Breast Cancer in Young Women

Identification of Key Genes Associated with Brain Metastasis from Breast Cancer: A Bioinformatics Analysis

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