scholarly journals Identification of prognostic significance of BIRC5 in breast cancer using integrative bioinformatics analysis

2020 ◽  
Vol 40 (2) ◽  
Author(s):  
Jian-bo Dai ◽  
Bei Zhu ◽  
Wei-jia Lin ◽  
Hai-yan Gao ◽  
Hong Dai ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Drug Interaction ◽  
Methylation Status ◽  
Prognostic Significance ◽  
Prognostic Index ◽  
Interaction Network ◽  
The Cancer Genome Atlas ◽  
Free Survival ◽  
Increased Risk ◽  
Metastatic Relapse

Abstract Aims: Baculoviral inhibitor of apoptosis repeat containing 5 (BIRC5) plays vital roles in carcinogenesis by influencing cell division and proliferation and by inhibiting apoptosis. However, the prognostic significance of BIRC5 remains unclear in breast cancer. Methods: BIRC5 expression and methylation status were evaluated using the Oncomine and The Cancer Genome Atlas (TCGA) databases. The relevance between BIRC5 and different clinicopathological features as well as survival information was analyzed using the bc-GenExMiner database and Kaplan–Meier Plotter. BIRC5–drug interaction network was obtained using the Comparative Toxicogenomics Database. Results: Based on the results from databases and own hospital data, BIRC5 was higher expressed in different breast cancer subtypes compared with the matched normal individuals. Hormone receptors were negatively correlated with BIRC5 expression, whereas the Scarff–Bloom–Richardson (SBR) grade, Nottingham Prognostic Index (NPI), human epidermal growth factor receptor-2 (HER-2) status, basal-like status, and triple-negative status were positively related to BIRC5 level in breast cancer samples with respect to normal tissues. High BIRC5 expression was responsible for shorter relapse-free survival, worse overall survival, reduced distant metastasis free survival, and increased risk of metastatic relapse event. BIRC5–drug interaction network indicated that several common drugs could modulate BIRC5 expression. Furthermore, a positive correlation between BIRC5 andcell-division cycle protein 20 (CDC20) gene was confirmed. Conclusion: BIRC5 may be adopted as a promising predictive marker and potential therapeutic target in breast cancer. Further large-scale studies are needed to more precisely confirm the value of BIRC5 in treatment of breast cancer.

scholarly journals Bioinformatics analysis revealing prognostic significance of RRM2 gene in breast cancer

2019 ◽  
Vol 39 (4) ◽  
Author(s):  
Wei-xian Chen ◽  
Liang-gen Yang ◽  
Ling-yun Xu ◽  
Lin Cheng ◽  
Qi Qian ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Survival Data ◽  
Bioinformatics Analysis ◽  
Prognostic Significance ◽  
Prognostic Index ◽  
Disease Free Survival ◽  
Cancer Prognosis ◽  
Breast Cancer Patients ◽  
Free Survival ◽  
Metastatic Relapse

Abstract Background: Ribonucleotide reductase M2 subunit (RRM2) plays vital roles in many cellular processes such as cell proliferation, invasiveness, migration, angiogenesis, senescence, and tumorigenesis. However, the prognostic significance of RRM2 gene in breast cancer remains to be investigated. Methods:RRM2 expression was initially evaluated using the Oncomine database. The relevance between RRM2 level and clinical parameters as well as survival data in breast cancer was analyzed using the Kaplan–Meier Plotter, PrognoScan, and Breast Cancer Gene-Expression Miner (bc-GenExMiner) databases. Results:RRM2 was overexpressed in different subtypes of breast cancer patients. Estrogen receptor (ER) and progesterone receptor (PR) were negatively correlated with RRM2 expression. Conversely, the Scarff–Bloom–Richardson (SBR) grade, Nottingham prognostic index (NPI), human epidermal growth factor receptor-2 (HER-2) status, nodal status, basal-like status, and triple-negative status were positively related to RRM2 level in breast cancer samples with respect to normal tissues. Patients with increased RRM2 showed worse overall survival, relapse-free survival, distant metastasis-free survival, disease-specific survival, and disease-free survival. RRM2 also exerted positive effect on metastatic relapse event. Besides, a positive correlation between RRM2 and KIF11 genes was confirmed. Conclusion: Bioinformatics analysis revealed that RRM2 might be used as a predictive biomarker for prognosis of breast cancer. Further studies are needed to more precisely elucidate the value of RRM2 in evaluating breast cancer prognosis.

scholarly journals Bioinformatics analysis of prognostic value of TRIM13 gene in breast cancer

2019 ◽  
Vol 39 (3) ◽  
Author(s):  
Wei-xian Chen ◽  
Lin Cheng ◽  
Ling-yun Xu ◽  
Qi Qian ◽  
Yu-lan Zhu
Keyword(s):  
Breast Cancer ◽  
Cancer Treatment ◽  
Cancer Patients ◽  
Bioinformatics Analysis ◽  
Prognostic Significance ◽  
Breast Cancer Treatment ◽  
Breast Cancer Patients ◽  
Relapse Free Survival ◽  
Free Survival ◽  
Metastatic Relapse

Abstract Background: Tripartite motif 13 (TRIM13) plays a significant role in various biological processes including cell growth, apoptosis, transcriptional regulation, and carcinogenesis. However, the prognostic significance of TRIM13 gene in breast cancer treatment remains largely unclear. Methods: We performed a bioinformatics analysis of the clinical parameters and survival data as it relates to TRIM13 in breast cancer patients using several online databases including Oncomine, bcGenExMiner, PrognoScan, and UCSC Xena. Results: We found that TRIM13 was lower-expressed in different subtypes of breast cancer with respect to normal tissues. Estrogen receptor and progesterone receptor status were positively correlated with TRIM13 level; whereas, the Scarff–Bloom–Richardson grade, Nottingham prognostic index, nodal status, basal-like status, and triple-negative status were negatively related to TRIM13 expression in breast cancer patients with respect to normal individuals. Lower TRIM13 expression correlated with worse distant metastasis free survival, relapse free survival, disease specific survival, and metastatic relapse free survival. We also confirmed a positive correlation between TRIM13 and RAB11FIP2 gene expression. Conclusion: Bioinformatics analysis revealed that TRIM13 may be adopted as a promising predictive biomarker for prognosis of breast cancer. More in-depth experiments and clinical trials are needed to validate the value of TRIM13 in breast cancer treatment.

scholarly journals A novel immune prognostic index for stratification of high-risk patients with early breast cancer

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Hannah Lee ◽  
Mi Jeong Kwon ◽  
Beom-Mo Koo ◽  
Hee Geon Park ◽  
Jinil Han ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Immune Response ◽  
High Risk ◽  
Early Breast Cancer ◽  
Prognostic Significance ◽  
Prognostic Index ◽  
Low Risk ◽  
Lymph Node Status ◽  
Free Survival ◽  
Risk Patients

AbstractThe prognostic value of current multigene assays for breast cancer is limited to hormone receptor-positive, human epidermal growth factor receptor 2-negative early breast cancer. Despite the prognostic significance of immune response-related genes in breast cancer, immune gene signatures have not been incorporated into most multigene assays. Here, using public gene expression microarray datasets, we classified breast cancer patients into three risk groups according to clinical risk and proliferation risk. We then developed the immune prognostic index based on expression of five immune response-related genes (TRAT1, IL2RB, CTLA4, IGHM and IL21R) and lymph node status to predict the risk of recurrence in the clinical and proliferation high-risk (CPH) group. The 10-year probability of disease-free survival (DFS) or distant metastasis-free survival (DMFS) of patients classified as high risk according to the immune prognostic index was significantly lower than those of patients classified as intermediate or low risk. Multivariate analysis revealed that the index is an independent prognostic factor for DFS or DMFS. Moreover, the C-index revealed that it is superior to clinicopathological variables for predicting prognosis. Its prognostic significance was also validated in independent datasets. The immune prognostic index identified low-risk patients among patients classified as CPH, regardless of the molecular subtype of breast cancer, and may overcome the limitations of current multigene assays.

scholarly journals Bioinformatics analysis of prognostic significance of COL10A1 in breast cancer

2020 ◽  
Vol 40 (2) ◽  
Author(s):  
Mingdi Zhang ◽  
Hongliang Chen ◽  
Maoli Wang ◽  
Fang Bai ◽  
Kejin Wu
Keyword(s):  
Breast Cancer ◽  
Bioinformatics Analysis ◽  
Prognostic Significance ◽  
Growth Factor Receptor ◽  
Disease Free Survival ◽  
Predictive Biomarker ◽  
Expression Level ◽  
Relapse Free Survival ◽  
Free Survival ◽  
Metastatic Relapse

Abstract Background: Collagen type X alpha 1 (COL10A1) is overexpressed in diverse tumors and displays vital roles in tumorigenesis. However, the prognostic value of COL10A1 in breast cancer remains unclear. Methods: The expression of COL10A1 was analyzed by the Oncomine database and UALCAN cancer database. The relationship between COL10A1 expression level and clinical indicators including prognostic data in breast cancer were analyzed by the Kaplan–Meier Plotter, PrognoScan, and Breast Cancer Gene-Expression Miner (bc-GenExMiner) databases. Results: COL10A1 was up-regulated in different subtypes of breast cancer. Estrogen receptor (ER), progesterone receptor (PR), human epidermal growth factor receptor-2 (HER-2) status and nodal status were positively correlated with COL10A1 expression. Conversely, age, the Scarff–Bloom–Richardson (SBR) grade, basal-like status, and triple-negative status were negatively related to COL10A1 level in breast cancer samples compared with normal tissues. Patients with increased COL10A1 expression level showed worse overall survival (OS), relapse-free survival (RFS), distant metastasis-free survival (DMFS) and disease-free survival (DFS). COL10A1 was positively correlated with metastatic relapse-free survival. GSEA analysis revealed that enrichment of TGF-β signaling pathway. 15-leucine-rich repeat containing membrane protein (LRRC15) is a correlated gene of COL10A1. Conclusion: Bioinformatics analysis revealed that COL10A1 might be considered as a predictive biomarker for prognosis of breast cancer. Further experiments and clinical trials are essential to elucidate the value of COL10A1 in breast cancer treatment.

scholarly journals Bioinformatics analysis of prognostic value of PITX1 gene in breast cancer

2020 ◽  
Vol 40 (9) ◽  
Author(s):  
Qiaoyun Wang ◽  
Shuai Zhao ◽  
Lei Gan ◽  
Zhixiang Zhuang
Keyword(s):  
Breast Cancer ◽  
Survival Data ◽  
Malignant Tumors ◽  
Prognostic Index ◽  
Bioinformatic Analysis ◽  
Prognostic Parameters ◽  
Relapse Free Survival ◽  
Free Survival ◽  
Metastatic Relapse ◽  
Pitx1 Gene

Abstract Background: Paired-like homeodomain transcription factor 1 (PITX1) participates in miscellaneous biological processes including cell growth, development, progression and invasion in various malignant tumors. However, the analysis of the association between PITX1 expression and the survival in breast cancer remains unclear. Methods: Clinical prognostic parameters and survival data related to PITX1 in breast cancer patients were performed using the bioinformatic analysis including Oncomine, Bc-GenExMiner v4.3, PrognoScan and UCSC Xena. Results: We found that PITX1 gene expression was significantly higher in different histological classification of breast cancer. The Scarff–Bloom–Richardson (SBR) grade, Nottingham prognostic index (NPI), estrogen receptor (ER) negative, epidermal growth factor receptor-2 (HER2) positive, lymph node positive, triple-negative status and basal-like status were positively correlated with PITX1 level, except for patients’ age and the progesterone receptor (PR) status. We have found that the increased PITX1 expression correlated with worse relapse-free survival, disease specific survival and overall survival. PITX1 was positively correlated with metastatic relapse-free survival and distant metastasis-free survival. We also confirmed positive correlation between PITX1 and the nucleotide-binding oligomerization domain 2 (NOD2). Conclusion: The lower expression of PITX1 was associated with better clinical prognostic parameters and clinical survival in breast cancer according to the bioinformatic analysis.

scholarly journals Untangling the clinicopathological significance of MRE11-RAD50-NBS1 complex in sporadic breast cancers

2021 ◽  
Vol 7 (1) ◽  
Author(s):  
Adel Alblihy ◽  
Ahmed Shoqafi ◽  
Michael S. Toss ◽  
Mashael Algethami ◽  
Anna E. Harris ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Large Scale ◽  
Cancer Susceptibility ◽  
Excision Repair ◽  
Univariate Analysis ◽  
Prognostic Significance ◽  
Prognostic Index ◽  
The Cancer Genome Atlas ◽  
Breast Cancers ◽  
Poor Survival

AbstractThe MRE11–RAD50–NBS1 (MRN) complex is critical for genomic stability. Although germline mutations in MRN may increase breast cancer susceptibility, such mutations are extremely rare. Here, we have conducted a comprehensive clinicopathological study of MRN in sporadic breast cancers. We have protein expression profiled for MRN and a panel of DNA repair factors involved in double-strand break repair (BRCA1, BRCA2, ATM, CHK2, ATR, Chk1, pChk1, RAD51, γH2AX, RPA1, RPA2, DNA-PKcs), RECQ DNA helicases (BLM, WRN, RECQ1, RECQL4, RECQ5), nucleotide excision repair (ERCC1) and base excision repair (SMUG1, APE1, FEN1, PARP1, XRCC1, Pol β) in 1650 clinical breast cancers. The prognostic significance of MRE11, RAD50 and NBS1 transcripts and their microRNA regulators (hsa-miR-494 and hsa-miR-99b) were evaluated in large clinical datasets. Expression of MRN components was analysed in The Cancer Genome Atlas breast cancer cohort. We show that low nuclear MRN is linked to aggressive histopathological phenotypes such as high tumour grade, high mitotic index, oestrogen receptor- and high-risk Nottingham Prognostic Index. In univariate analysis, low nuclear MRE11 and low nuclear RAD50 were associated with poor survival. In multivariate analysis, low nuclear RAD50 remained independently linked with adverse clinical outcomes. Low RAD50 transcripts were also linked with reduced survival. In contrast, overexpression of hsa-miR-494 and hsa-miR-99b microRNAs was associated with poor survival. We observed large-scale genome-wide alterations in MRN-deficient tumours contributing to aggressive behaviour. We conclude that MRN status may be a useful tool to stratify tumours for precision medicine strategies.

scholarly journals A Novel Integrative Multiomics Method Reveals a Hypoxia-Related Subgroup of Breast Cancer with Significantly Decreased Survival

2019 ◽  
Author(s):  
Maryam Pouryahya ◽  
Jung Hun Oh ◽  
Pedram Javanmard ◽  
James C. Mathews ◽  
Zehor Belkhatir ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Network Inference ◽  
Survival Rates ◽  
Tumor Hypoxia ◽  
Network Connectivity ◽  
Interaction Network ◽  
Enrichment Analysis ◽  
The Cancer Genome Atlas ◽  
Omics Analysis ◽  
Increased Risk

AbstractThe remarkable growth of multi-platform genomic profiles has led to the multiomics data integration challenge. The effective integration of such data provides a comprehensive view of the molecular complexity of cancer tumors and can significantly improve clinical out-come predictions. In this study, we present a novel network-based integration method of multiomics data as well as a clustering technique involving the Wasserstein (Earth Mover’s) distance from the theory of optimal mass transport. We applied our proposed method of integrative Wasserstein-based clustering (iWCluster) to invasive breast carcinoma from The Cancer Genome Atlas (TCGA) project. The subtypes were characterized by the concordant effect of mRNA expression, DNA copy number alteration, and DNA methylation as well as the interaction network connectivity of the gene products. iW-Cluster is substantially more effective in distinguishing clusters with different survival rates as compared to isolated one-dimensional conventional omics analysis. Applying iWCluster to breast cancer TCGA data successfully recovered the known PAM50 molecular subtypes. In addition, iWCluster preserves the gene-specific data, which enables us to interpret the results and perform further analysis of significant genes for a specific cluster. The gene ontology enrichment analysis of significant genes in our substantially low survival sub-group leads to the well-known phenomenon of tumor hypoxia and the transcription factor ETS1 whose expression is induced by hypoxia. Increased expression of ETS1 is associated with an increased risk of recurrence and worse prognosis in breast cancer. Consequently, we believe iWCluster has the potential to discover novel subtypes by accentuating the genes that have concordant multiomics measurements in their interaction network, which are challenging to find without the network inference or with single omics analysis.

scholarly journals DNA Methylation Based Molecular Subtypes Predict Prognosis in Breast Cancer Patients

2021 ◽  
Vol 28 ◽  
pp. 107327482098851
Author(s):  
Zeng-Hong Wu ◽  
Yun Tang ◽  
Yan Zhou
Keyword(s):  
Breast Cancer ◽  
Dna Methylation ◽  
Molecular Subtypes ◽  
Methylation Status ◽  
The Cancer Genome Atlas ◽  
Training Dataset ◽  
Consensus Clustering ◽  
Breast Cancer Patients ◽  
Cancer Subtypes ◽  
Novel Biomarkers

Background: Epigenetic changes are tightly linked to tumorigenesis development and malignant transformation’ However, DNA methylation occurs earlier and is constant during tumorigenesis. It plays an important role in controlling gene expression in cancer cells. Methods: In this study, we determining the prognostic value of molecular subtypes based on DNA methylation status in breast cancer samples obtained from The Cancer Genome Atlas database (TCGA). Results: Seven clusters and 204 corresponding promoter genes were identified based on consensus clustering using 166 CpG sites that significantly influenced survival outcomes. The overall survival (OS) analysis showed a significant prognostic difference among the 7 groups (p<0.05). Finally, a prognostic model was used to estimate the results of patients on the testing set based on the classification findings of a training dataset DNA methylation subgroups. Conclusions: The model was found to be important in the identification of novel biomarkers and could be of help to patients with different breast cancer subtypes when predicting prognosis, clinical diagnosis and management.

scholarly journals Relationship between Ribosomal Protein S6-pS240 Expression and other Prognostic Factors in Non-Special Type Invasive Breast Cancer

Breast Care ◽  
2018 ◽  
Vol 14 (3) ◽  
pp. 171-175
Author(s):  
Frederik Cuperjani ◽  
Lumturije Gashi ◽  
Fisnik Kurshumliu ◽  
Shemsedin Dreshaj ◽  
Fitim Selimi
Keyword(s):  
Breast Cancer ◽  
Ribosomal Protein ◽  
Invasive Breast Cancer ◽  
Menopausal Status ◽  
Treatment Protocol ◽  
Prognostic Index ◽  
Disease Free Survival ◽  
Ki 67 ◽  
Free Survival ◽  
Disease Free

Background: The aim of this study was to investigate the immunohistochemical expression of ribosomal protein (RP) S6-pS240 in non-special type invasive breast cancer in relation to other prognostic markers and gain new insights to facilitate more individualized treatment. Methods: The following clinical and histopathological parameters of 120 patients were determined: S6-pS240 expression, age, menopausal status, tumor size and grade, TNM stage, Nottingham Prognostic Index (NPI), lymph node stage, estrogen and progesterone receptor (ER/PR) expression, HER2/neu amplification, lymphovascular invasion, and proliferative index as measured by Ki-67. Treatment protocol and disease-free survival were evaluated accordingly. Results: Significant positive correlations were seen between S6-pS240 expression and Ki-67 values (rho = 0.530, p < 0.001), and NPI (rho = 0.370, p < 0.001) and HER2/neu amplification (rho = 0.368, p < 0.001). A negative correlation was found between S6-pS240 and ER/PR expression (rho = 0.362, p < 0.001). Patients with negative RP S6-pS240 expression had significantly longer disease-free survival (log-rank test, p = 0.005). Conclusion: Immunohistochemical analysis of RP S6-pS240 is a valuable additional prognostic marker in patients with invasive breast cancer. Routine use of S6-pS240 immunohistochemistry is recommended.

scholarly journals Methylation of the NT5E Gene Is Associated with Poor Prognostic Factors in Breast Cancer

Diagnostics ◽  
2020 ◽  
Vol 10 (11) ◽  
pp. 939
Author(s):  
Young Ju Jeong ◽  
Hoon Kyu Oh ◽  
Hye Ryeon Choi ◽  
Sung Hwan Park
Keyword(s):  
Breast Cancer ◽  
Prognostic Factors ◽  
Methylation Status ◽  
Prognostic Significance ◽  
Disease Free Survival ◽  
Receptor Expression ◽  
Gene Methylation ◽  
Clinicopathologic Characteristics ◽  
Large Tumor ◽  
The Mean

Cluster of differentiation (CD) 73, which is encoded by the NT5E gene, regulates production of immunosuppressive adenosine and is an emerging checkpoint in cancer immunotherapy. Despite the significance of CD73 in immuno-oncology, the roles of the NT5E gene methylation in breast cancer have not been well-defined yet. Therefore, we aimed to investigate the prognostic significance of the NT5E gene methylation in breast cancer. The DNA methylation status of the NT5E gene was analyzed using pyrosequencing in breast cancer tissues. In addition, the levels of inflammatory markers and lymphocyte infiltration were evaluated. The mean methylation level of the NT5E gene was significantly higher in breast cancer than in normal breast tissues. In the analysis of relevance with clinicopathologic characteristics, the mean methylation levels of the NT5E gene were significantly higher in patients with large tumor size, high histologic grade, negative estrogen receptor expression, negative Bcl-2 expression, and premenopausal women. There was no difference in disease-free survival according to the methylation status of the NT5E gene. We found that the NT5E gene methylation was related to breast cancer development and associated with poor prognostic factors in breast cancer. Our results suggest that the NT5E gene methylation has potential as an epigenetic biomarker in breast cancer.

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