A single nucleotide variant on chromosome 10 residing within nebulette (C10orf113) distinguishes patients with basal-like human breast cancer.

Patients diagnosed with basal-like breast cancer face a more aggressive disease course and more dismal prognosis than patients diagnosed with luminal A and luminal B breast cancer molecular subtypes (1-4). We mined published microarray data (5, 6) to understand in an unbiased fashion the most distinguishing genetic and transcriptional features of tumors from patients with basal or basal-like subtype breast cancer. We identified a single nucleotide polymorphism (rs625223) residing within NEBL (C10orf113) as among the most significant genetic differences in the tumors of patients with basal-like breast cancer. In a separate cohort of patients with basal subtype breast cancer, we observed transcriptome-wide differential tumor expression of a C10orf113 transcript. Analysis of patient survival data revealed that C10orf113 primary tumor expression was correlated with recurrence-free survival and distant metastasis-free survival in patients with basal-like breast cancer, but in a contrary manner. Thus, single nucleotide variants on both chromosome 5 (7) and chromosome 10 are fundamental differences that define the genetic composition of basal-like breast cancer in humans.

High VEGF-A expression distinguishes basal-like human breast cancer.

10.31219/osf.io/x5c8z ◽

2022 ◽

Author(s):

Shahan Mamoor

Keyword(s):

Breast Cancer ◽

Survival Data ◽

Human Breast Cancer ◽

Molecular Subtypes ◽

Human Breast ◽

Luminal A ◽

Luminal B ◽

Dismal Prognosis ◽

Basal Like Breast Cancer ◽

Patients diagnosed with basal-like breast cancer face a more aggressive disease course and more dismal prognosis than patients diagnosed with luminal A and luminal B breast cancer molecular subtypes (1-4). We mined published microarray data (5, 6) to understand in an unbiased fashion the most distinguishing transcriptional features of tumors from patients with basal or basal-like subtype breast cancer. We observed transcriptome-wide differential expression of the vascular endothelial growth factor A, VEGFA, when comparing tumors of patients with basal-like breast cancer with that of other PAM50 molecular subtypes. VEGF-A mRNA was present at significantly higher quantities in the tumors of patients with basal-like breast cancer. Analysis of patient survival data revealed that VEGF-A primary tumor expression was correlated with recurrence-free survival, with higher VEGF-A associated with inferior outcomes - in basal-like patients but not in luminal A, luminal B, HER2+, or normal-like patients. High VEGF-A expression appears to distinguish basal-like human breast cancer from the other molecular subtypes.

An allele on chromosome 5 residing within the ZSWIM6 region distinguishes patients with basal-like human breast cancer.

10.31219/osf.io/ats5x ◽

2021 ◽

Author(s):

Shahan Mamoor

Keyword(s):

Breast Cancer ◽

Survival Data ◽

Human Breast Cancer ◽

Human Breast ◽

Luminal A ◽

Luminal B ◽

Basal Subtype ◽

Dismal Prognosis ◽

Basal Like Breast Cancer ◽

Patients diagnosed with basal-like (also known as basal) subtype breast cancer face a more aggressive disease course and more dismal prognosis than patients diagnosed with luminal A and luminal B breast cancer molecular subtypes (1-4). We mined published microarray data (5, 6) to understand in an unbiased fashion the most distinguishing genetic and transcriptional features of tumors from patients with basal or basal-like subtype breast cancer. We identified a single nucleotide polymorphism, rs6449531 in ZSWIM6 as among the most significant genetic differences in the tumors of patients with basal-like breast cancer. In a separate cohort of patients with basal subtype breast cancer, we observed transcriptome-wide differential expression of a ZSWIM6 transcript. Analysis of patient survival data revealed that ZSWIM6 primary tumor expression was correlated with overall survival in patients with basal subtype breast cancer. Sequence variation in the ZSWIM6 gene may be important in understanding differences in genetic background that favor development of basal subtype human breast cancer.

Low GATA3 expression distinguishes basal-like human breast cancer.

10.31219/osf.io/fzc8q ◽

2022 ◽

Author(s):

Shahan Mamoor

Keyword(s):

Breast Cancer ◽

Survival Data ◽

Human Breast Cancer ◽

Molecular Subtypes ◽

Human Breast ◽

Luminal A ◽

Luminal B ◽

Dismal Prognosis ◽

Gata3 Expression ◽

Patients diagnosed with basal-like breast cancer face a more aggressive disease course and more dismal prognosis than patients diagnosed with luminal A and luminal B breast cancer molecular subtypes (1-4). We mined published microarray data (5, 6) to understand in an unbiased fashion the most distinguishing transcriptional features of tumors from patients with basal or basal-like subtype breast cancer. We observed transcriptome-wide differential expression of the transcription factor GATA3 when comparing tumors of patients with basal-like breast cancer with that of other PAM50 molecular subtypes. GATA3 mRNA was present at significantly reduced quantities in the tumors of patients with basal-like breast cancer. Analysis of patient survival data revealed that GATA3 primary tumor expression was correlated with distant metastasis-free survival, with low GATA3 expression correlated with inferior survival outcomes. Low GATA3 expression appears to distinguish basal-like human breast cancer from the other molecular subtypes.

Elevated SOX11 expression distinguishes basal-like human breast cancer.

10.31219/osf.io/esg5k ◽

2022 ◽

Author(s):

Shahan Mamoor

Keyword(s):

Breast Cancer ◽

Survival Data ◽

Human Breast Cancer ◽

Molecular Subtypes ◽

Human Breast ◽

Luminal A ◽

Luminal B ◽

Dismal Prognosis ◽

Sox11 Expression ◽

Patients diagnosed with basal-like breast cancer face a more aggressive disease course and more dismal prognosis than patients diagnosed with luminal A and luminal B breast cancer molecular subtypes (1-4). We mined published microarray data (5, 6) to understand in an unbiased fashion the most distinguishing transcriptional features of tumors from patients with basal or basal-like subtype breast cancer. We observed transcriptome-wide differential expression of SRY-box 11, SOX11, when comparing tumors of patients with basal-like breast cancer with that of other PAM50 molecular subtypes. SOX11 mRNA was present at significantly higher quantities in the tumors of patients with basal-like breast cancer. Analysis of patient survival data revealed that SOX11 primary tumor expression was correlated with overall survival, with higher SOX11 associated with inferior outcomes - in basal-like patients but not in luminal A, luminal B, HER2+, or normal-like patients. Elevated SOX11 expression appears to distinguish basal-like human breast cancer from the other molecular subtypes.

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

10.21203/rs.3.rs-28637/v1 ◽

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 ◽

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.

Differential expression of FXYD1 in cancers of the breast.

10.31219/osf.io/7gbuw ◽

2021 ◽

Author(s):

Shahan Mamoor

Keyword(s):

Breast Cancer ◽

Overall Survival ◽

Differential Expression ◽

Survival Data ◽

Molecular Subtype ◽

Normal Breast ◽

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 FXYD domain containing ion transport regulator 1, FXYD1, when comparing primary tumors of the breast to the tissue of origin, the normal breast. FXYD1 mRNA was present at significantly reduced quantity in tumors of the breast as compared to normal breast tissue. Analysis of human survival data revealed that expression of FXYD1 in primary tumors of the breast was correlated with overall survival in patients with basal and luminal A subtype cancers, demonstrating a relationship between correlation of primary tumor expression with overall survival based on molecular subtype. FXYD1 may be of relevance to initiation, maintenance or progression of cancers of the female breast.

Differential expression of the integrator complex subunit 7 in cancers of the breast.

10.31219/osf.io/zkftb ◽

2021 ◽

Author(s):

Shahan Mamoor

Keyword(s):

Breast Cancer ◽

Differential Expression ◽

Survival Data ◽

Normal Breast ◽

Luminal A ◽

Gene Encoding ◽

Significant Differential Expression ◽

Primary Tumors ◽

Free Survival ◽

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 integrator complex subunit 7, INTS7, when comparing primary tumors of the breast to the tissue of origin, the normal breast. INTS7 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 INTS7 in primary tumors of the breast was correlated with distant metastasis-free survival in patients with luminal A and HER2+ type cancers, but contrarily. INTS7 may be of relevance to initiation, maintenance or progression of cancers of the female breast.

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

World Journal of Surgical Oncology ◽

10.1186/s12957-020-02042-z ◽

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 ◽

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.

Differential expression of chromobox 4 in cancers of the breast.

10.31219/osf.io/kdf7b ◽

2021 ◽

Author(s):

Shahan Mamoor

Keyword(s):

Breast Cancer ◽

Overall Survival ◽

Differential Expression ◽

Survival Data ◽

Molecular Subtype ◽

Normal Breast ◽

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 chromobox 4, CBX4, when comparing primary tumors of the breast to the tissue of origin, the normal breast. CBX4 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 CBX4 in primary tumors of the breast was correlated with overall survival in patients with luminal A type cancer, demonstrating a relationship between correlation of primary tumor expression with overall survival based on molecular subtype. CBX4 may be of relevance to initiation, maintenance or progression of cancers of the female breast.

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

10.21203/rs.3.rs-28637/v2 ◽

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 ◽

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.