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 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.

Randomized trial of observation versus adjuvant therapy with cyclophosphamide, fluorouracil, prednisone with or without tamoxifen following mastectomy in postmenopausal women with node-positive breast cancer.

1988 ◽  
Vol 6 (9) ◽  
pp. 1388-1396 ◽  
Author(s):  
J N Ingle ◽  
L K Everson ◽  
H S Wieand ◽  
J K Martin ◽  
H J Votava ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Adjuvant Therapy ◽  
Postmenopausal Women ◽  
Survival Data ◽  
Observation Time ◽  
Relapse Free Survival ◽  
Free Survival ◽  
Node Positive ◽  
Overall Survival Benefit ◽  
Positive Breast Cancer

Following mastectomy for node-positive breast cancer, 261 postmenopausal women were randomized to observation or adjuvant treatment with cyclophosphamide, fluorouracil, prednisone (CFP) alone or combined with tamoxifen (T). Doses used were: C, 150 mg/m2 intravenously (IV) days 1 to 5; F, 300 mg/m2 IV days 1 to 5; P, 10 mg by mouth 3 times daily on days 1 to 7; and T, 10 mg by mouth 2 times daily. A total of ten courses of treatment, administered every 6 weeks, was planned and T was stopped 6 weeks after the last course of CFP. Two hundred thirty-four patients were fully eligible and evaluable. With a median observation time slightly in excess of 5 years, the proportion of recurrences on each arm were: CFP, 29 of 75 (39%); CFPT, 29 of 71 (41%); and observation, 50 of 88 (57%). Relapse-free survival distributions for both CFP and CFPT were superior to observation (both two-sided P = .01). Considering prognostic factors in covariate analysis revealed two-sided P = .0006 for CFP v observation and P = .0003 for CFPT v observation. No substantial difference was identified between CFP and CFPT. Survival data are not yet mature with 31% dead; and, although slight separations of the curves exist in favor of the treatment arms, no significant differences in survival have been seen. Both adjuvant therapy programs are well tolerated and there were no treatment-related deaths. Further maturation of the data is required to determine if the advantages in relapse-free survival will be translated into any overall survival benefit which must be considered the goal of primary interest.

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 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 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 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 Identification of death-associated protein-like 1 (DAPL1) as a novel prognostic biomarker of breast cancer

2020 ◽  
Author(s):  
Haichao Zhang ◽  
Xin Qu ◽  
Lu Han
Keyword(s):  
Breast Cancer ◽  
Dna Repair ◽  
Survival Data ◽  
Immune Cell ◽  
Excision Repair ◽  
Analysis Data ◽  
Clinical Prognosis ◽  
Free Survival ◽  
Normal Tissues ◽  
M1 Macrophage

Abstract Background: It is meaningful to identify the potential clinical prognosis-associated oncogenes for cases with breast cancer, considering the complicated pathogenesis of breast cancer.Methods: We first utilized the bioinformatics approach to investigate the role of the DAPL1 (death-associated protein-like 1) in breast cancer, based on the available datasets of TCGA and GEO.Results: DAPL1 is lowly expressed in breast cancer tissues compared with the normal tissues. For the breast cancer cases of the TCGA-BRCA cohort, we observed a correlation between lowly expressed DAPL1 gene and poor clinical prognosis of overall survival ( P =0.0028). Based on the survival data of GEO, the low DAPL1 expression was associated with a poor prognosis of distant metastasis free survival ( P =0.0023), and relapse free survival ( P =0.0065). DAPL1 expression was linked to the mutation status or copy number variation o f several genes, such as MAP3K1 , NUP98 , and CCDC59. The infiltration level of immune cells (e.g., M1 macrophage, Follicular B helper T cells, etc.) may be involved in the etiology of breast cancer. Based on the DAPL1 -correlated genes, GSEA, GO, and KEGG analysis data indicated the association between DAPL1 expression and a series of biological issues, such as DNA packaging complex, DNA repair complex, nucleotide excision repair, ubiquitin-like protein binding, and ubiquitin proteasome pathway. We also identified several DAPL1 -associated phosphorylation kinases, such as MAPK, PRKACA, and GSK3B.Conclusions: DAPL1 gene is first identified as a prognosis biomarker of breast cancer, and the underlying molecular mechanism involves protein phosphorylation, immune cell infiltration, and DNA repair or protein ubiquitin-associated cellular pathways.

scholarly journals The Alterations and Potential Roles of MCMs in Breast Cancer

2021 ◽  
Vol 2021 ◽  
pp. 1-17
Author(s):  
Xinyu Liu ◽  
Ying Liu ◽  
Qiangshan Wang ◽  
Siqi Song ◽  
Lingjun Feng ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Gene Network ◽  
Relapse Free Survival ◽  
Minichromosome Maintenance ◽  
Free Survival ◽  
Oncomine Database ◽  
Kaplan Meier ◽  
Eukaryotic Dna ◽  
Coexpressed Genes ◽  
Kaplan Meier Plotter

The minichromosome maintenance (MCM) protein family plays a key role in eukaryotic DNA replication and has been confirmed to be associated with the occurrence and progression of many tumors. However, the expression levels, functions, and prognostic values of MCMs in breast cancer (BC) have not been clearly and systematically explained. In this article, we studied the transcriptional levels of MCMs in BC based on the Oncomine database. Kaplan-Meier plotter was used to analyze prognostic value of MCMs in human BC patients. Furthermore, we constructed a MCM coexpression gene network and performed functional annotation analysis through DAVID to reveal the functions of MCMs and coexpressed genes. The data showed that the expression of MCM2–8 and MCM10 but not MCM1 and MCM9 was upregulated in BC. Kaplan-Meier plotter analysis revealed that high transcriptional levels of MCM2, MCM4–7, and MCM10 were significantly related to low relapse-free survival (RFS) in BC patients. In contrast, high levels of MCM1 and MCM9 predicted high RFS for BC patients. This study suggests that MCM2, MCM4–7, and MCM10 possess great potential to be valuable prognostic biomarkers for BC and that MCM1 and MCM9 may serve as potential treatment targets for BC patients.

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