Expression Profiling of Selected Immune Genes and Trabecular Microarchitecture in Breast Cancer Skeletal Metastases Model: Effect of α–Tocopherol Acetate Supplementation

2022 ◽  
Author(s):  
Riadh Badraoui ◽  
Mohd Saeed ◽  
Nouha Bouali ◽  
Walid S. Hamadou ◽  
Salem Elkahoui ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Expression Profiling ◽  
Skeletal Metastases ◽  
Trabecular Microarchitecture ◽  
Immune Genes ◽  
Tocopherol Acetate

Effect of alpha tocopherol acetate in Walker 256/B cells-induced oxidative damage in a rat model of breast cancer skeletal metastases

2009 ◽  
Vol 182 (2-3) ◽  
pp. 98-105 ◽  
Author(s):  
Riadh Badraoui ◽  
Stéphane Blouin ◽  
Marie Françoise Moreau ◽  
Yves Gallois ◽  
Tarek Rebai ◽  
...  
Keyword(s):  
Breast Cancer ◽  
B Cells ◽  
Oxidative Damage ◽  
Rat Model ◽  
Alpha Tocopherol ◽  
Skeletal Metastases ◽  
Tocopherol Acetate ◽  
Walker 256

scholarly journals Identification and development of an independent immune-related genes prognostic model for breast cancer

BMC Cancer ◽  
2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Lin Chen ◽  
Yuxiang Dong ◽  
Yitong Pan ◽  
Yuhan Zhang ◽  
Ping Liu ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Regression Analysis ◽  
Cox Regression ◽  
Gene Set Enrichment Analysis ◽  
Risk Scores ◽  
Validation Dataset ◽  
Immune Gene ◽  
Cox Regression Analysis ◽  
Immune Genes ◽  
Immune Related Genes

Abstract Background Breast cancer is one of the main malignant tumors that threaten the lives of women, which has received more and more clinical attention worldwide. There are increasing evidences showing that the immune micro-environment of breast cancer (BC) seriously affects the clinical outcome. This study aims to explore the role of tumor immune genes in the prognosis of BC patients and construct an immune-related genes prognostic index. Methods The list of 2498 immune genes was obtained from ImmPort database. In addition, gene expression data and clinical characteristics data of BC patients were also obtained from the TCGA database. The prognostic correlation of the differential genes was analyzed through Survival package. Cox regression analysis was performed to analyze the prognostic effect of immune genes. According to the regression coefficients of prognostic immune genes in regression analysis, an immune risk scores model was established. Gene set enrichment analysis (GSEA) was performed to probe the biological correlation of immune gene scores. P < 0.05 was considered to be statistically significant. Results In total, 556 immune genes were differentially expressed between normal tissues and BC tissues (p < 0. 05). According to the univariate cox regression analysis, a total of 66 immune genes were statistically significant for survival risk, of which 30 were associated with overall survival (P < 0.05). Finally, a 15 immune genes risk scores model was established. All patients were divided into high- and low-groups. KM survival analysis revealed that high immune risk scores represented worse survival (p < 0.001). ROC curve indicated that the immune genes risk scores model had a good reliability in predicting prognosis (5-year OS, AUC = 0.752). The established risk model showed splendid AUC value in the validation dataset (3-year over survival (OS) AUC = 0.685, 5-year OS AUC = 0.717, P = 0.00048). Moreover, the immune risk signature was proved to be an independent prognostic factor for BC patients. Finally, it was found that 15 immune genes and risk scores had significant clinical correlations, and were involved in a variety of carcinogenic pathways. Conclusion In conclusion, our study provides a new perspective for the expression of immune genes in BC. The constructed model has potential value for the prognostic prediction of BC patients and may provide some references for the clinical precision immunotherapy of patients.

scholarly journals A prospective study revealing the role of an immune-related eRNA, WAKMAR2, in breast cancer

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Linbang Wang ◽  
Jingkun Liu ◽  
Jiaojiao Tai ◽  
Nian Zhou ◽  
Tianji Huang ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Target Genes ◽  
Pearson Correlation ◽  
Tumour Microenvironment ◽  
The Cancer Genome Atlas ◽  
Mcf7 Cells ◽  
Tumour Immunity ◽  
Immune Genes ◽  
Normal Tissues

AbstractEnhancer RNAs (eRNAs) are a subclass of non-coding RNAs that are generated during the transcription of enhancer regions and play an important role in tumourigenesis. In this study, we focused on the crucial eRNAs that participate in immune responses in invasive breast cancer (IBC). We first used The Cancer Genome Atlas and Human enhancer RNA Atlas to screen for tissue-specific eRNAs and their target genes. Through Pearson correlation analysis with immune genes, the eRNA WAKMAR2 was identified as a key candidate involved in IBC. Our further research suggested that WAKMAR2 is crucial in regulating the tumour microenvironment and may function by regulating immune-related genes, including IL27RA, RAC2, FABP7, IGLV1-51, IGHA1, and IGHD. Quantitative reverse transcription-polymerase chain reaction was used to detect the expression of WAKMAR2 in IBC and normal tissues, and the effect of WAKMAR2 on the regulation of downstream genes in MB-231 and MCF7 cells was studied in vitro. WAKMAR2 was found to be highly involved in tumour immunity and was downregulated in IBC tissues. Furthermore, the expression of WAKMAR2 and its target genes was observed at the pan-cancer level. This study provides evidence to suggest new potential targets for the treatment of breast cancer.

scholarly journals Mammary Fat of Breast Cancer: Gene Expression Profiling and Functional Characterization

PLoS ONE ◽  
2014 ◽  
Vol 9 (10) ◽  
pp. e109742 ◽  
Author(s):  
Fengliang Wang ◽  
Sheng Gao ◽  
Fei Chen ◽  
Ziyi Fu ◽  
Hong Yin ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Gene Expression ◽  
Gene Expression Profiling ◽  
Expression Profiling ◽  
Functional Characterization ◽  
Cancer Gene ◽  
Breast Cancer Gene

scholarly journals Gene expression profiling and breast cancer care: What are the potential benefits and policy implications?

2005 ◽  
Vol 7 (6) ◽  
pp. 380-389 ◽  
Author(s):  
Nina Oestreicher ◽  
Scott D Ramsey ◽  
Hannah M Linden ◽  
Jeannine S McCune ◽  
Laura J van't Veer ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Gene Expression ◽  
Gene Expression Profiling ◽  
Cancer Care ◽  
Expression Profiling ◽  
Policy Implications ◽  
Breast Cancer Care ◽  
Potential Benefits
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