scholarly journals Identification of key genes unique to the luminal A and basal-like breast cancer subtypes via bioinformatic analysis

2020 ◽  
Author(s):  
Rong Jia ◽  
Zhongxian Li ◽  
Wei Liang ◽  
Yucheng Ji ◽  
Yujie Weng ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Differentially Expressed Genes ◽  
Survival Data ◽  
Breast Cancer Subtypes ◽  
Differentially Expressed ◽  
Expression Data ◽  
Luminal A ◽  
Cancer Subtypes ◽  
Protein Protein Interaction ◽  
Basal Like Breast Cancer

Abstract Background: Breast cancer subtypes are statistically associated with prognosis. The search for markers of breast tumor heterogeneity and the development of precision medicine for patients are the current focuses of the field.Methods: We used a bioinformatic approach to identify key disease-causing genes unique to the luminal A and basal-like subtypes of breast cancer. First, we retrieved gene expression data for luminal A breast cancer, basal-like breast cancer, and normal breast tissue samples from The Cancer Genome Atlas database. The differentially expressed genes unique to the 2 breast cancer subtypes were identified and subjected to Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathway enrichment analyses. We constructed protein–protein interaction networks of the differentially expressed genes. Finally, we analyzed the key modules of the networks, which we combined with survival data to identify the unique cancer genes associated with each breast cancer subtype.Results: We identified 1,114 differentially expressed genes in luminal A breast cancer and 1,042 differentially expressed genes in basal-like breast cancer, of which the subtypes shared 500. We observed 614 and 542 differentially expressed genes unique to luminal A and basal-like breast cancer, respectively. Through enrichment analyses, protein–protein interaction network analysis, and module mining, we identified 8 key differentially expressed genes unique to each subtype. Analysis of the gene expression data in the context of the survival data revealed that high expression of NMUR1 and NCAM1 in luminal A breast cancer statistically correlated with poor prognosis, whereas the low expression levels of CDC7, KIF18A, STIL, and CKS2 in basal-like breast cancer statistically correlated with poor prognosis.Conclusions: NMUR1 and NCAM1 are novel key disease-causing genes for luminal A breast cancer, and STIL is a novel key disease-causing gene for basal-like breast cancer. These genes are potential targets for clinical treatment.

scholarly journals Identification of key genes unique to the luminal A and basal-like breast cancer subtypes via bioinformatic analysis

2020 ◽  
Author(s):  
Rong Jia ◽  
Zhongxian Li ◽  
Wei Liang ◽  
Yucheng Ji ◽  
Yujie Weng ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Differentially Expressed Genes ◽  
Survival Data ◽  
Breast Cancer Subtypes ◽  
Differentially Expressed ◽  
Expression Data ◽  
Luminal A ◽  
Cancer Subtypes ◽  
Protein Protein Interaction ◽  
Basal Like Breast Cancer

Abstract Background Breast cancer subtypes are statistically associated with prognosis. The search for markers of breast tumor heterogeneity and the development of precision medicine for patients are the current focuses of the field. Methods We used a bioinformatic approach to identify key disease-causing genes unique to the luminal A and basal-like subtypes of breast cancer. First, we retrieved gene expression data for luminal A breast cancer, basal-like breast cancer, and normal breast tissue samples from The Cancer Genome Atlas database. The differentially expressed genes unique to the 2 breast cancer subtypes were identified and subjected to Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathway enrichment analyses. We constructed protein–protein interaction networks of the differentially expressed genes. Finally, we analyzed the key modules of the networks, which we combined with survival data to identify the unique cancer genes associated with each breast cancer subtype. Results We identified 1,114 differentially expressed genes in luminal A breast cancer and 1,042 differentially expressed genes in basal-like breast cancer, of which the subtypes shared 500. We observed 614 and 542 differentially expressed genes unique to luminal A and basal-like breast cancer, respectively. Through enrichment analyses, protein–protein interaction network analysis, and module mining, we identified 8 key differentially expressed genes unique to each subtype. Analysis of the gene expression data in the context of the survival data revealed that high expression of NMUR1 and NCAM1 in luminal A breast cancer statistically correlated with poor prognosis, whereas the low expression levels of CDC7 , KIF18A , STIL , and CKS2 in basal-like breast cancer statistically correlated with poor prognosis. Conclusions NMUR1 and NCAM1 are novel key disease-causing genes for luminal A breast cancer, and STIL is a novel key disease-causing gene for basal-like breast cancer. These genes are potential targets for clinical treatment.

scholarly journals Identification of key genes unique to the luminal a and basal-like breast cancer subtypes via bioinformatic analysis

2020 ◽  
Vol 18 (1) ◽  
Author(s):  
Rong Jia ◽  
Zhongxian Li ◽  
Wei Liang ◽  
Yucheng Ji ◽  
Yujie Weng ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Differentially Expressed Genes ◽  
Survival Data ◽  
Breast Cancer Subtypes ◽  
Differentially Expressed ◽  
Expression Data ◽  
Luminal A ◽  
Cancer Subtypes ◽  
Protein Protein Interaction ◽  
Basal Like Breast Cancer

Abstract Background Breast cancer subtypes are statistically associated with prognosis. The search for markers of breast tumor heterogeneity and the development of precision medicine for patients are the current focuses of the field. Methods We used a bioinformatic approach to identify key disease-causing genes unique to the luminal A and basal-like subtypes of breast cancer. First, we retrieved gene expression data for luminal A breast cancer, basal-like breast cancer, and normal breast tissue samples from The Cancer Genome Atlas database. The differentially expressed genes unique to the 2 breast cancer subtypes were identified and subjected to Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathway enrichment analyses. We constructed protein–protein interaction networks of the differentially expressed genes. Finally, we analyzed the key modules of the networks, which we combined with survival data to identify the unique cancer genes associated with each breast cancer subtype. Results We identified 1114 differentially expressed genes in luminal A breast cancer and 1042 differentially expressed genes in basal-like breast cancer, of which the subtypes shared 500. We observed 614 and 542 differentially expressed genes unique to luminal A and basal-like breast cancer, respectively. Through enrichment analyses, protein–protein interaction network analysis, and module mining, we identified 8 key differentially expressed genes unique to each subtype. Analysis of the gene expression data in the context of the survival data revealed that high expression of NMUR1 and NCAM1 in luminal A breast cancer statistically correlated with poor prognosis, whereas the low expression levels of CDC7, KIF18A, STIL, and CKS2 in basal-like breast cancer statistically correlated with poor prognosis. Conclusions NMUR1 and NCAM1 are novel key disease-causing genes for luminal A breast cancer, and STIL is a novel key disease-causing gene for basal-like breast cancer. These genes are potential targets for clinical treatment.

scholarly journals Microvascular proliferation in luminal A and basal-like breast cancer subtypes

2015 ◽  
Vol 68 (11) ◽  
pp. 891-897 ◽  
Author(s):  
Maria Ryssdal Kraby ◽  
Kristi Krüger ◽  
Signe Opdahl ◽  
Lars J Vatten ◽  
Lars A Akslen ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Breast Cancer Subtypes ◽  
Luminal A ◽  
Cancer Subtypes ◽  
Microvascular Proliferation ◽  
Basal Like Breast Cancer

scholarly journals Key Genes and Prognostic Analysis in HER2+ Breast Cancer

2021 ◽  
Vol 20 ◽  
pp. 153303382098329
Author(s):  
Yujie Weng ◽  
Wei Liang ◽  
Yucheng Ji ◽  
Zhongxian Li ◽  
Rong Jia ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Gene Expression ◽  
Differentially Expressed Genes ◽  
Protein Interaction ◽  
Differentially Expressed ◽  
Protein Kinase Activity ◽  
Protein Protein Interaction ◽  
Risk Of Death ◽  
Her2 Breast Cancer ◽  
Key Genes

Human epidermal growth factor 2 (HER2)+ breast cancer is considered the most dangerous type of breast cancers. Herein, we used bioinformatics methods to identify potential key genes in HER2+ breast cancer to enable its diagnosis, treatment, and prognosis prediction. Datasets of HER2+ breast cancer and normal tissue samples retrieved from Gene Expression Omnibus and The Cancer Genome Atlas databases were subjected to analysis for differentially expressed genes using R software. The identified differentially expressed genes were subjected to gene ontology and Kyoto Encyclopedia of Genes and Genomes pathway enrichment analyses followed by construction of protein-protein interaction networks using the STRING database to identify key genes. The genes were further validated via survival and differential gene expression analyses. We identified 97 upregulated and 106 downregulated genes that were primarily associated with processes such as mitosis, protein kinase activity, cell cycle, and the p53 signaling pathway. Visualization of the protein-protein interaction network identified 10 key genes ( CCNA2, CDK1, CDC20, CCNB1, DLGAP5, AURKA, BUB1B, RRM2, TPX2, and MAD2L1), all of which were upregulated. Survival analysis using PROGgeneV2 showed that CDC20, CCNA2, DLGAP5, RRM2, and TPX2 are prognosis-related key genes in HER2+ breast cancer. A nomogram showed that high expression of RRM2, DLGAP5, and TPX2 was positively associated with the risk of death. TPX2, which has not previously been reported in HER2+ breast cancer, was associated with breast cancer development, progression, and prognosis and is therefore a potential key gene. It is hoped that this study can provide a new method for the diagnosis and treatment of HER2 + breast cancer.

Comprehensive immunohistochemical analysis of RET, BCAR1, and BCAR3 expression in patients with Luminal A and B breast cancer subtypes

2022 ◽  
Author(s):  
Ana Carolina Pavanelli ◽  
Flavia Rotea Mangone ◽  
Piriya Yoganathan ◽  
Simone Aparecida Bessa ◽  
Suely Nonogaki ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Immunohistochemical Analysis ◽  
Breast Cancer Subtypes ◽  
Luminal A ◽  
Cancer Subtypes

scholarly journals Differential expression of CKS2 in cancers of the breast.

2021 ◽  
Author(s):  
Shahan Mamoor
Keyword(s):  
Breast Cancer ◽  
Differential Expression ◽  
Survival Data ◽  
Normal Breast ◽  
Differentially Expressed ◽  
Regulatory Subunit ◽  
Luminal A ◽  
Gene Encoding ◽  
Significant Differential Expression ◽  
Primary Tumors

Breast cancer affects women at relatively high frequency (1). We mined published microarray datasets (2, 3) to determine in an unbiased fashion and at the systems level genes most differentially expressed in the primary tumors of patients with breast cancer. We report here significant differential expression of the gene encoding the CDC28 protein kinase regulatory subunit 2, CKS2, when comparing primary tumors of the breast to the tissue of origin, the normal breast. CKS2 was also differentially expressed in the tumor cells of patients with triple negative breast cancer. CKS2 mRNA was present at significantly higher quantities in tumors of the breast as compared to normal breast tissue. Analysis of human survival data revealed that expression of CKS2 in primary tumors of the breast was correlated with overall survival in patients with basal and luminal A subtype cancer, but in a contrary manner. CKS2 may be of relevance to initiation, maintenance or progression of cancers of the female breast.

scholarly journals Differential expression of mab-21 like 1 in cancers of the breast.

2021 ◽  
Author(s):  
Shahan Mamoor
Keyword(s):  
Breast Cancer ◽  
Differential Expression ◽  
Survival Data ◽  
Molecular Subtype ◽  
Differentially Expressed Gene ◽  
Normal Breast ◽  
Differentially Expressed ◽  
Luminal A ◽  
Significant Differential Expression ◽  
Primary Tumors

Breast cancer affects women at relatively high frequency (1). We mined published microarray datasets (2, 3) to determine in an unbiased fashion and at the systems level genes most differentially expressed in the primary tumors of patients with breast cancer. We report here significant differential expression of the gene encoding mab-21 like 1, MAB21L1, when comparing primary tumors of the breast to the tissue of origin, the normal breast. MAB21L1 was also differentially expressed in the tumor cells of patients with triple negative breast cancer. MAB21L1 mRNA was present at significantly lower quantities in tumors of the breast as compared to normal breast tissue. Analysis of human survival data revealed that expression of MAB21L1 in primary tumors of the breast was correlated with overall survival in patients with luminal A subtype cancer, demonstrating a relationship between primary tumor expression of a differentially expressed gene and patient survival outcomes influenced by molecular subtype. MAB21L1 may be of relevance to initiation, maintenance or progression of cancers of the female breast.

scholarly journals Differential expression of TUFT1 in cancers of the breast.

2021 ◽  
Author(s):  
Shahan Mamoor
Keyword(s):  
Breast Cancer ◽  
Differential Expression ◽  
Survival Data ◽  
Normal Breast ◽  
Differentially Expressed ◽  
Luminal A ◽  
Gene Encoding ◽  
Significant Differential Expression ◽  
Primary Tumors ◽  
Microarray Datasets

Breast cancer affects women at relatively high frequency (1). We mined published microarray datasets (2, 3) to determine in an unbiased fashion and at the systems level genes most differentially expressed in the primary tumors of patients with breast cancer. We report here significant differential expression of the gene encoding the tuftelin 1, TUFT1, when comparing primary tumors of the breast to the tissue of origin, the normal breast. TUFT1 was also differentially expressed in the tumor cells of patients with triple negative breast cancer. TUFT1 mRNA was present at significantly higher quantities in tumors of the breast as compared to normal breast tissue. Analysis of human survival data revealed that expression of TUFT1 in primary tumors of the breast was correlated with distant metastasis-free survival in patients with basal and luminal A subtype cancer. TUFT1 may be of relevance to initiation, maintenance or progression of cancers of the female breast.

scholarly journals Differential expression of defective in cullin neddylation 1 domain-containing 3 in cancers of the breast.

2021 ◽  
Author(s):  
Shahan Mamoor
Keyword(s):  
Breast Cancer ◽  
Differential Expression ◽  
Survival Data ◽  
Molecular Subtype ◽  
Differentially Expressed Gene ◽  
Normal Breast ◽  
Differentially Expressed ◽  
Luminal A ◽  
Significant Differential Expression ◽  
Primary Tumors

Breast cancer affects women at relatively high frequency (1). We mined published microarray datasets (2, 3) to determine in an unbiased fashion and at the systems level genes most differentially expressed in the primary tumors of patients with breast cancer. We report here significant differential expression of the gene encoding defective in cullin neddylation 1 domain-containing 3, DCUN1D3, when comparing primary tumors of the breast to the tissue of origin, the normal breast. DCUN1D3 mRNA was present at significantly lower quantities in tumors of the breast as compared to normal breast tissue. Analysis of human survival data revealed that expression of DCUN1D3 in primary tumors of the breast was correlated with recurrence-free survival in patients with basal, luminal A and luminal B subtype cancers, demonstrating a relationship between primary tumor expression of a differentially expressed gene and patient survival outcomes influenced by PAM50 molecular subtype. DCUN1D3 may be of relevance to initiation, maintenance or progression of cancers of the female breast.

scholarly journals Differential expression of KIF11 in cancers of the breast.

2021 ◽  
Author(s):  
Shahan Mamoor
Keyword(s):  
Breast Cancer ◽  
Differential Expression ◽  
Survival Data ◽  
Normal Breast ◽  
Differentially Expressed ◽  
Luminal A ◽  
Gene Encoding ◽  
Significant Differential Expression ◽  
Primary Tumors ◽  
Microarray Datasets

Breast cancer affects women at relatively high frequency (1). We mined published microarray datasets (2, 3) to determine in an unbiased fashion and at the systems level genes most differentially expressed in the primary tumors of patients with breast cancer. We report here significant differential expression of the gene encoding the kinesin family member 11, KIF11, when comparing primary tumors of the breast to the tissue of origin, the normal breast. KIF11 was also differentially expressed in the tumor cells of patients with triple negative breast cancer. KIF11 mRNA was present at significantly higher quantities in tumors of the breast as compared to normal breast tissue. Analysis of human survival data revealed that expression of KIF11 in primary tumors of the breast was correlated with overall survival in patients with basal and luminal A subtype cancer, but in a contrary manner. KIF11 may be of relevance to initiation, maintenance or progression of cancers of the female breast.

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