scholarly journals Interaction of H3K27me3 and Glutaminase 1 Expression on Breast Cancer Prognosis by Menopausal Status: a Cohort Study

2021 ◽  
Author(s):  
Meng Zhou ◽  
Qianxin Chen ◽  
Yuanzhong Yang ◽  
Zhuozhi Liang ◽  
Yuelin Li ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Cox Regression ◽  
Menopausal Status ◽  
Premenopausal Women ◽  
Progression Free Survival ◽  
Breast Cancer Prognosis ◽  
Cancer Prognosis ◽  
Prognostic Effect ◽  
H3k27me3 Level ◽  
Glutaminase 1

Abstract Background: Glutaminase 1 (GLS) is a potential therapeutic target for breast cancer; although GLS inhibitors have been developed, only a few subjects responded well to the therapy. Considering that the expression of trimethylation of histone H3 lysine 27 (H3K27me3) and menopausal status have been closely linked to the role of GLS, we tried to examine the modification effects of H3K27me3 and menopausal status on GLS to breast cancer prognosis, which would be helpful to identify the more suitable patients to the GLS inhibitors.Methods: Data for 963 women diagnosed with primary invasive breast cancer between 2008 and 2015 were analyzed. H3K27me3 and GLS expression in tumors were evaluated with tissue microarrays by immunohistochemistry. Hazard ratios (HRs) and their 95% confidence intervals (CIs) for overall survival (OS) and progression-free survival (PFS) were estimated using univariable and multivariable Cox regression models. The interaction was assessed on multiplicative scale by stratification analysis.Results: After a median follow-up of 70.6 months (interquartile range: 45.6-103.9), we confirmed the association between H3K27me3 and both outcomes (HR =0.57, 95% CI: 0.37-0.86 for OS; HR =0.66, 95% CI: 0.48-0.91 for PFS) and found that the prognostic roles of GLS were not statistically significant in the overall patients. There was a beneficial prognostic effect of GLS expression on OS for those with low H3K27me3 level (HR =0.50, 95% CI: 0.20-1.28) but an adverse prognostic effect for those with high H3K27me3 level (HR =3.90, 95% CI: 1.29-11.78) among premenopausal women, and the interaction was significant (Pinteraction =0.003). Similar pattern was further observed for PFS (HR =0.44, 95% CI: 0.20-0.95 for low H3K27me3 level, HR =1.35, 95% CI: 0.74-2.48 for high H3K27me3 level, Pinteraction =0.024). The interaction didn’t occur among postmenopausal women.Conclusions: This study revealed the modification effects of H3K27me3 and menopausal status on GLS to breast cancer prognosis, which would help optimize the medication strategies related to GLS inhibitors.

scholarly journals Dietary Constituents: Relationship with Breast Cancer Prognostic (MCC-SPAIN Follow-Up)

2020 ◽  
Vol 18 (1) ◽  
pp. 84
Author(s):  
Trinidad Dierssen-Sotos ◽  
Inés Gómez-Acebo ◽  
Nuria Gutiérrez-Ruiz ◽  
Nuria Aragonés ◽  
Pilar Amiano ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Protective Effect ◽  
Dietary Habits ◽  
Cox Regression ◽  
Menopausal Status ◽  
Premenopausal Women ◽  
Normal Weight ◽  
High Intake ◽  
The Relationship

The aim of this study was to characterize the relationship between the intake of the major nutrients and prognosis in breast cancer. A cohort based on 1350 women with invasive (stage I-IV) breast cancer (BC) was followed up. Information about their dietary habits before diagnosis was collected using a semi-quantitative Food Frequency Questionnaire. Participants without FFQ or with implausible energy intake were excluded. The total amount consumed of each nutrient (Kcal/day) was divided into tertiles, considering as “high intakes” those above third tertile. The main effect studied was overall survival. Cox regression was used to assess the association between death and nutrient intake. During a median follow-up of 6.5 years, 171 deaths were observed. None of the nutrients analysed was associated with mortality in the whole sample. However, in normal-weight women (BMI 18.5–25 kg/m2) a high intake of carbohydrates (≥809 Kcal/day), specifically monosaccharides (≥468 Kcal/day), worsened prognostic compared to lowest (≤352 Kcal/day). Hazard Ratios (HRs) for increasing tertiles of intake were HR:2.22 95% CI (1.04 to 4.72) and HR:2.59 95% CI (1.04 to 6.48), respectively (p trend = 0.04)). Conversely, high intakes of polyunsaturated fats (≥135 Kcal/day) improved global survival (HR: 0.39 95% CI (0.15 to 1.02) p-trend = 0.05) compared to the lowest (≤92.8 kcal/day). In addition, a protective effect was found substituting 100 kcal of carbohydrates with 100 kcal of fats in normal-weight women (HR: 0.76 95% CI (0.59 to 0.98)). Likewise, in premenopausal women a high intake of fats (≥811 Kcal/day) showed a protective effect (HR:0.20 95% CI (0.04 to 0.98) p trend = 0.06). Finally, in Estrogen Receptors (ER) negative tumors, we found a protective effect of high intake of animal proteins (≥238 Kcal/day, HR: 0.24 95% CI (0.06 to 0.98). According to our results, menopausal status, BMI and ER status could play a role in the relationship between diet and BC survival and must be taken into account when studying the influence of different nutrients.

scholarly journals Association between SNPs within MicroRNA Binding Sites and the Prognosis of Breast Cancer

2020 ◽  
Author(s):  
Liwen Zhang ◽  
Lu Han ◽  
Yubei Huang ◽  
Ziwei Feng ◽  
Xin Wang ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Cancer Patients ◽  
Binding Sites ◽  
Cox Regression ◽  
Breast Cancer Prognosis ◽  
Stage I ◽  
Cancer Prognosis ◽  
Stage Ii ◽  
Breast Cancer Patients ◽  
Survival Times

Abstract Background: Single nucleotide polymorphisms (SNPs) within microRNA binding sites can affect the binding of microRNA to mRNA and regulate gene expression, thereby contributing to the prognosis of cancer. We performed this study to explore the association between SNPs within microRNA binding sites and the prognosis of breast cancer.Methods: We carried out a two-stage study including 2647 breast cancer patients, with a median follow-up of 68 months (range 0-159). In stage I, we genotyped 192 SNPs within microRNA binding sites using the Illumina Goldengate platform. In stage II, we validated SNPs significantly associated with breast cancer prognosis in another dataset using the TaqMan platform. Survival times was calculated, and Kaplan-Meier curves and Cox regression model were used to analyze survival of breast cancer patients with different genotypes.Results: We identified 8 SNPs significantly associated with breast cancer prognosis in stage I (P<0.05), and only rs10878441 was statistically significant in stage II (AA vs CC: adjusted HR=2.21, 95% CI: 1.11-4.42, P=0.024). We combined the data from stage I and stage II, and found that, compared with rs10878441 AA genotype, CC genotype was significantly associated with poor survival of breast cancer (HR=1.69, 95% CI: 1.18-2.42, P=0.004; adjusted HR=2.19, 95% CI: 1.30-3.70, P=0.003). Stratified analyses demonstrated that rs10878441 was related to breast cancer prognosis in grade II patients and lymph node-negative patients (P<0.05).Conclusions: The LRKK2 rs10878441 CC genotype is associated with poor prognosis of breast cancer in a Chinese population, and it could be used as a potential prognostic biomarker for breast cancer. Further studies are warranted.

scholarly journals Inflammatory Potential of the Diet and Risk of Breast Cancer in the European Investigation Into Cancer and Nutrition (EPIC) Study

2021 ◽  
Author(s):  
Carlota Castro-Espin ◽  
Antonio Agudo ◽  
Catalina Bonet ◽  
Verena Katzke ◽  
Renée Turzanski-Fortner ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Physical Activity ◽  
Cox Regression ◽  
Menopausal Status ◽  
Premenopausal Women ◽  
Underlying Mechanism ◽  
Potential Effect ◽  
Inflammatory Score ◽  
Hazard Ratios ◽  
Increased Risk

Abstract The role of chronic inflammation on breast cancer (BC) risk remains unclear beyond as an underlying mechanism of obesity and physical activity. We aimed to evaluate the association between the inflammatory potential of the diet and risk of BC overall, according to menopausal status and tumour subtypes. Within the European Prospective Investigation into Cancer and Nutrition cohort, 318,686 women were followed for 14 years, among whom 13,246 incident BC cases were identified. The inflammatory potential of the diet was characterized by an inflammatory score of the diet (ISD). Multivariable Cox regression models were used to assess the potential effect of the ISD on BC risk by means of hazard ratios (HR) and 95% confidence intervals (CI). ISD was positively associated with BC risk. Each increase of one standard deviation (1-Sd) of the score increased by 4% the risk of BC (HR=1.04; 95% CI: 1.01-1.07). Women in the highest quintile of the ISD (indicating most pro-inflammatory diet) had a 12% increase in risk compared with those in the lowest quintile (HR=1.12; 95% CI: 1.04-1.21) with a significant trend. The association was strongest among premenopausal women, with an 8% increased risk for 1-Sd increase in the score (HR=1.08; 95% CI: 1.01-1.14). The pattern of the association was quite homogeneous by BC subtypes based on hormone receptor status. There were no significant interactions between ISD and body mass index, physical activity or alcohol consumption. Women consuming more pro-inflammatory diets as measured by ISD are at increased risk for BC, especially premenopausal women.

scholarly journals Stable breast cancer prognosis

2021 ◽  
Author(s):  
Xiaomei Li ◽  
Lin Liu ◽  
Jiuyong Li ◽  
Thuc Duy Le
Keyword(s):  
Breast Cancer ◽  
Causal Inference ◽  
Prediction Models ◽  
Cox Regression ◽  
Data Distribution ◽  
Breast Cancer Prognosis ◽  
Training Data ◽  
Cancer Prognosis ◽  
Training Dataset ◽  
Inference Theory

Predicting breast cancer prognosis helps improve the treatment and management of the disease. In the last decades, many prediction models have been developed for breast cancer prognosis based on transcriptomic data. A common assumption made by these models is that the test and training data follow the same distribution. However, in practice, due to the heterogeneity of breast cancer and the different environments (e.g. hospitals) where data are collected, the distribution of the test data may shift from that of the training data. For example, new patients likely have different breast cancer stage distribution from those in the training dataset. Thus these existing methods may not provide stable prediction performance for breast cancer prognosis in situations with the shift of data distribution. In this paper, we present a novel stable prediction method for reliable breast cancer prognosis under data distribution shift. Our model, known as Deep Global Balancing Cox regression (DGBCox), is based on the causal inference theory. In DGBCox, firstly high-dimensional gene expression data is transferred to latent network-based representations by a deep auto-encoder neural network. Then after balancing the latent representations using a proposed causality-based approach, causal latent features are selected for breast cancer prognosis. Causal features have persistent relationships with survival outcomes even under distribution shift across different environments according to the causal inference theory. Therefore, the proposed DGBCox method is robust and stable for breast cancer prognosis. We apply DGBCox to 12 test datasets from different breast cancer studies. The results show that DGBCox outperforms benchmark methods in terms of both prediction accuracy and stability. We also propose a permutation importance algorithm to rank the genes in the DGBCox model. The top 50 ranked genes suggest that the cell cycle and the organelle organisation could be the most relevant biological processes for stable breast cancer prognosis.

scholarly journals Associations of reproductive factors with breast cancer prognosis and the modifying effects of menopausal status

2019 ◽  
Vol 9 (1) ◽  
pp. 385-393
Author(s):  
Jia‐Yi Zhang ◽  
Mei‐Xia Wang ◽  
Xiang Wang ◽  
Yue‐Lin Li ◽  
Zhuo‐Zhi Liang ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Menopausal Status ◽  
Reproductive Factors ◽  
Breast Cancer Prognosis ◽  
Cancer Prognosis

scholarly journals Inflammatory Potential of the Diet and Risk of Breast Cancer in the European Investigation Into Cancer and Nutrition (EPIC) Study

2021 ◽  
Vol 5 (Supplement_2) ◽  
pp. 264-264
Author(s):  
Carlota Castro-Espin ◽  
Antonio Agudo ◽  
Catalina Bonet ◽  
Elisabete Weiderpass ◽  
Elio Riboli ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Cox Regression ◽  
Menopausal Status ◽  
Premenopausal Women ◽  
Potential Effect ◽  
Funding Sources ◽  
Inflammatory Score ◽  
Increased Risk ◽  
Incident Breast Cancer ◽  
Prospective Investigation

Abstract Objectives We aimed to evaluate the association between the inflammatory potential of the diet and the risk of breast cancer overall, by tumour subtypes and according to menopausal status. Methods A total of 318,686 women from the European Prospective Investigation into Cancer and Nutrition (EPIC) were followed for 14 years, among whom 13,246 incident breast cancer cases were identified. Dietary inflammatory potential was characterized by an inflammatory score of the diet (ISD). Multivariable Cox regression models were used to assess the potential effect of the ISD on the risk of overall breast cancer and by tumour subtypes by means of the hazard ratio (HR) and 95% confidence interval (95% CI). Results ISD was positively associated with breast cancer risk. Adjusted for relevant confounders, each increase of one standard deviation (1-SD) of the score increased by 4% the risk of breast cancer (HR 1.04; 95% CI: 1.01–1.07). Women in the highest quintile of the ISD (indicating most pro-inflammatory diet) had a 12% increase in risk compared with those in the lowest quintile (HR 1.12; 95% CI: 1.04–1.21) with a significant trend. The association was more pronounced among premenopausal women, with increased risk of 8% for 1-SD increase of the score (HR 1.08; 95% CI: 1.01–1.14). The pattern of the association was quite homogeneous by tumour subtypes based on hormone receptor status. There were no significant interactions  between ISD and body mass index, physical activity or alcohol consumption. Conclusions Women consuming more pro-inflammatory diets as measured by ISD are at increased risk for breast cancer, especially premenopausal women. Funding Sources

scholarly journals FGFR1 Is Associated With Tamoxifen Resistance and Poor Prognosis of ER-Positive Breast Cancers by Suppressing ER Protein Expression

2021 ◽  
Vol 20 ◽  
pp. 153303382110049
Author(s):  
Qing Lv ◽  
Shiming Guan ◽  
Mingjie Zhu ◽  
Hu Huang ◽  
Junqiang Wu ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Protein Expression ◽  
Cox Regression ◽  
Breast Cancer Prognosis ◽  
Cancer Prognosis ◽  
In Vitro Assays ◽  
Breast Cancers ◽  
Er Positive ◽  
Fgfr1 Expression ◽  
Er Expression

Fibroblast growth factor receptor 1 (FGFR1) is widely recognized as a key player in mammary carcinogenesis and associated with the prognosis and therapeutic response of breast cancers. With the aim of investigating the correlation between FGFR1 expression and estrogen receptor (ER) and exploring the effect of FGFR1 on endocrine therapy response and ER+ breast cancer prognosis, we examined the FGFR1 protein expression among 184 ER-positive breast cancers by the immunohistochemistry (IHC) method, analyzed the association between FGFR1 expression and disease characters using the Pearson’s chi-square test, and assessed the prognostic role of FGFR1 among breast cancers using Cox regression and Kaplan-Meier analyses. Moreover, in vitro assays were conducted to confirm the correlation between FGFR1 and ER expression and investigate the effect of FGFR1 on tamoxifen (TAM) sensitivity in ER+ breast cancer. The results showed that ER expression was negatively correlated with FGFR1 expression ( P = 0.011, r = -0.221). Moreover, FGFR1 expression was one of the prognostic factors of ER-positive breast cancer (OR = 1.974, 95% CI = 1.043-3.633), and high FGFR1 expression was correlated with decreased breast cancer overall survival. In addition, knocking down FGFR1 inhibited cell proliferation and enhanced TAM sensitivity in TAM-resistant cells. In conclusion, we found that there was a significant negative correlation between FGFR1 and ER levels in ER+ breast cancers, high FGFR1 protein expression was associated with poor breast cancer prognosis, down-regulating FGFR1 could elevate ER expression and is associated with enhanced TAM sensitivity in ER+ breast cancers.

scholarly journals Identification of Key Transcription Factors and Immune Infiltration Patterns Associated With Breast Cancer Prognosis Using WGCNA and Cox Regression Analysis

2021 ◽  
Vol 11 ◽  
Author(s):  
Xin Yin ◽  
Jiaxiang Liu ◽  
Xin Wang ◽  
Tianshu Yang ◽  
Gen Li ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Transcription Factors ◽  
Cox Regression ◽  
Risk Group ◽  
Breast Cancer Prognosis ◽  
The Cancer Genome Atlas ◽  
Cancer Prognosis ◽  
Breast Cancer Cell Lines ◽  
Cox Regression Analysis ◽  
Immune Infiltration

Breast cancer is the most frequently diagnosed cancer and the second leading cause of cancer death among women worldwide. Therefore, the need for effective breast cancer treatment is urgent. Transcription factors (TFs) directly participate in gene transcription, and their dysregulation plays a key role in breast cancer. Our study identified 459 differentially expressed TFs between tumor and normal samples from The Cancer Genome Atlas database. Based on gene expression analysis and weighted gene co-expression network analysis, the co-expression yellow module was found to be integral for breast cancer progression. A total of 121 genes in the yellow module were used for function enrichment. To further confirm prognosis-related TFs, COX regression and LASSO analyses were performed; consequently, a prognostic risk model was constructed, and its validity was verified. Ten prognosis-related TFs were identified according to their expression profile, survival probability, and target genes. COPS5, HDAC2, and NONO were recognized as hub TFs in breast cancer. These TFs were highly expressed in human breast cancer cell lines and clinical breast cancer samples; this result was consistent with the information from multiple databases. Immune infiltration analysis revealed that the proportions of resting dendritic and mast cells were greater in the low-risk group than those in the high-risk group. Thus, in this study, we identified three hub biomarkers related to breast cancer prognosis. The results provide a framework for the co-expression of TF modules and immune infiltration in breast cancer.

scholarly journals Association Study between SNPs within MicroRNA Binding Sites and the Prognosis of Breast Cancer

2020 ◽  
Author(s):  
Liwen Zhang ◽  
Lu Han ◽  
Yubei Huang ◽  
Ziwei Feng ◽  
Xin Wang ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Cancer Patients ◽  
Binding Sites ◽  
Cox Regression ◽  
Breast Cancer Prognosis ◽  
Stage I ◽  
Cancer Prognosis ◽  
Stage Ii ◽  
Breast Cancer Patients ◽  
Survival Times

Abstract Background: Single nucleotide polymorphisms (SNPs) within microRNA binding sites can affect the binding of microRNA to mRNA and regulate gene expression, thereby contributing to the prognosis of cancer. We performed this study to explore the association between SNPs within microRNA binding sites and the prognosis of breast cancer.Methods: We carried out a two-stage study including 2647 breast cancer patients. In stage I, we genotyped 192 SNPs within microRNA binding sites using the Illumina Goldengate platform. In stage II, we validated SNPs significantly associated with breast cancer prognosis in another dataset using the TaqMan platform. Survival times was calculated, and Kaplan-Meier curves and Cox regression model were used to analyze survival of breast cancer patients with different genotypes.Results: We identified 8 SNPs significantly associated with breast cancer prognosis in stage I (P<0.05), and only rs10878441 was statistically significant in stage II (AA vs CC: adjusted HR=2.21, 95% CI: 1.11-4.42, P=0.024). We combined the data from stage I and stage II, and found that, compared with rs10878441 AA genotype, CC genotype was significantly associated with poor survival of breast cancer (HR=1.69, 95% CI: 1.18-2.42, P=0.004; adjusted HR=2.19, 95% CI: 1.30-3.70, P=0.003). Stratified analyses demonstrated that rs10878441 was related to breast cancer prognosis in grade II patients and lymph node-negative patients (P<0.05).Conclusions: The LRKK2 rs10878441 CC genotype is associated with poor prognosis of breast cancer in a Chinese population, and it could be used as a potential prognostic biomarker for breast cancer. Further studies are warranted.

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