Exploratory Data Analysis on Breast Cancer Prognosis

2018 ◽  
pp. 1794-1805
Author(s):  
Mohammad Mehdi Owrang O. ◽  
Yasmine M. Kanaan ◽  
Robert L. Copeland Jr. ◽  
Melvin Gaskins ◽  
Robert L. DeWitty Jr.
Keyword(s):  
Breast Cancer ◽  
Marital Status ◽  
Cancer Patients ◽  
Proportional Hazards ◽  
Breast Cancer Prognosis ◽  
Cancer Prognosis ◽  
Breast Cancer Patients ◽  
Howard University ◽  
Kaplan Meier ◽  
Seer Data

Breast cancer prognosis is a vital element of providing effective treatment for breast cancer patients. Breast cancer prediction survivability has mainly been studied based on pathological factors such as tumor size, tumor grade, number of positive lymph nodes, and hormone receptors among others. This chapter looks at the significance of the non-clinical prognostic factors of age, ethnicity, and marital status in finding the prognosis for breast cancer patients. The National Cancer Institute's SEER data and the Howard University Cancer Center Tumor Registry data are analyzed. Prognostic tool NPI (Nottingham Prognostic Index) and survival analysis tools of Cox proportional hazards and Kaplan-Meier survival curve are used in analyzing the experiments. The results suggest that age, ethnicity, and marital status have some influence on the survivability rate of breast cancer patients.

Exploratory Data Analysis on Breast Cancer Prognosis

2019 ◽  
pp. 367-380
Author(s):  
Mohammad Mehdi Owrang O. ◽  
Yasmine M. Kanaan ◽  
Robert L. Copeland Jr. ◽  
Melvin Gaskins ◽  
Robert L. DeWitty Jr.
Keyword(s):  
Breast Cancer ◽  
Marital Status ◽  
Cancer Patients ◽  
Proportional Hazards ◽  
Breast Cancer Prognosis ◽  
Cancer Prognosis ◽  
Breast Cancer Patients ◽  
Howard University ◽  
Kaplan Meier ◽  
Seer Data

Breast cancer prognosis is a vital element of providing effective treatment for breast cancer patients. Breast cancer prediction survivability has mainly been studied based on pathological factors such as tumor size, tumor grade, number of positive lymph nodes, and hormone receptors among others. This chapter looks at the significance of the non-clinical prognostic factors of age, ethnicity, and marital status in finding the prognosis for breast cancer patients. The National Cancer Institute's SEER data and the Howard University Cancer Center Tumor Registry data are analyzed. Prognostic tool NPI (Nottingham Prognostic Index) and survival analysis tools of Cox proportional hazards and Kaplan-Meier survival curve are used in analyzing the experiments. The results suggest that age, ethnicity, and marital status have some influence on the survivability rate of breast cancer patients.

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 The tumor microbiome is implicated in breast cancer prognosis

2020 ◽  
Author(s):  
Jia Zhu ◽  
Jie Wu ◽  
Changgan Mo ◽  
Siyuan Liang ◽  
Tao Lian ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Cancer Patients ◽  
Alpha Diversity ◽  
Breast Cancer Prognosis ◽  
Cancer Prognosis ◽  
Rrna Gene ◽  
Breast Cancer Patients ◽  
Immune Microenvironment ◽  
Tumor Tissues ◽  
Tumor Immune Microenvironment

Abstract Background: Some breast cancer patients are prone to recurrence and metastasis. Increasing evidence suggests that the breast tissue contains a diverse population of bacteria, which may be modulating the risk of breast cancer development or progression. However, the extent of microbial contribution to the tumor immune microenvironment in breast cancer remains unknown. Here, we explored the potential influence of the tumor microbiota on the local immune microenvironment and breast cancer prognosis.Methods: Using 16S rRNA gene sequencing, we analyzed the tumor microbiome composition and identified bacteria that were differentially abundant between breast cancer patients with recurrence or metastasis (R/M) and those without recurrence or metastasis (NRM). We performed total RNA sequencing in tumor tissues from patients in both groups to determine differentially expressed genes (DEGs). The landscape of tumor-infiltrating immune cells (TIICs) subtypes in the tumor immune microenvironment was analyzed using CIBERSORT, based on the gene expression profiling of tumor tissues. Differences in the tumor microbiomes were then correlated with DEGs and differences in TIICs, in order to determine how microbial abundance may contribute to cancer progression.Results: Microbial alpha-diversity was higher in NRM patients than in R/M patients. The composition and functions of the tumor microbiome communities differed between the two groups. We found higher alpha-diversity, higher abundance of Ruminococcus, Butyrivibrio, and Deinococcus, and lower abundance of Microbacterium could serve as a predictor of better prognosis in breast cancer patients. We also found that 16 genes, including CD36, showed differential expression in NRM compared to R/M, and differences in the composition of TIICs were observed between the two groups. In addition, we observed that the different tumor microbiome profiles were associated with DEGs and differences in TIICs between the two groups.Conclusions: The tumor microbiome may affect the prognosis of breast cancer patients by influencing the tumor immune microenvironment. Thus, the tumor microbiome may be a useful prognostic indicator.

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.

scholarly journals Abnormal Long Non-Coding RNAs Expression Patterns Have the Potential Ability for Predicting Survival and Treatment Response in Breast Cancer

Genes ◽  
2021 ◽  
Vol 12 (7) ◽  
pp. 996
Author(s):  
Ana Carolina Pavanelli ◽  
Flavia Rotea Mangone ◽  
Luciana R. C. Barros ◽  
Juliana Machado-Rugolo ◽  
Vera L. Capelozzi ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Cancer Patients ◽  
Predictive Value ◽  
Expression Patterns ◽  
Survival Rates ◽  
In Silico Analysis ◽  
Cancer Prognosis ◽  
Response To Treatment ◽  
Breast Cancer Patients ◽  
Non Coding Rnas

Abnormal long non-coding RNAs (lncRNAs) expression has been documented to have oncogene or tumor suppressor functions in the development and progression of cancer, emerging as promising independent biomarkers for molecular cancer stratification and patients’ prognosis. Examining the relationship between lncRNAs and the survival rates in malignancies creates new scenarios for precision medicine and targeted therapy. Breast cancer (BRCA) is a heterogeneous malignancy. Despite advances in its molecular classification, there are still gaps to explain in its multifaceted presentations and a substantial lack of biomarkers that can better predict patients’ prognosis in response to different therapeutic strategies. Here, we performed a re-analysis of gene expression data generated using cDNA microarrays in a previous study of our group, aiming to identify differentially expressed lncRNAs (DELncRNAs) with a potential predictive value for response to treatment with taxanes in breast cancer patients. Results revealed 157 DELncRNAs (90 up- and 67 down-regulated). We validated these new biomarkers as having prognostic and predictive value for breast cancer using in silico analysis in public databases. Data from TCGA showed that compared to normal tissue, MIAT was up-regulated, while KCNQ1OT1, LOC100270804, and FLJ10038 were down-regulated in breast tumor tissues. KCNQ1OT1, LOC100270804, and FLJ10038 median levels were found to be significantly higher in the luminal subtype. The ROC plotter platform results showed that reduced expression of these three DElncRNAs was associated with breast cancer patients who did not respond to taxane treatment. Kaplan–Meier survival analysis revealed that a lower expression of the selected lncRNAs was significantly associated with worse relapse-free survival (RFS) in breast cancer patients. Further validation of the expression of these DELncRNAs might be helpful to better tailor breast cancer prognosis and treatment.

scholarly journals Pressures and their Relation to the Psychological Hardiness among Breast Cancer Patients: الضغوط وعلاقتها بالصلابة النفسية لدى المصابات بسرطان الثدي

2020 ◽  
Vol 4 (41) ◽  
Author(s):  
Anas Ramadan Al-Masri
Keyword(s):  
Breast Cancer ◽  
Marital Status ◽  
Cancer Patients ◽  
Negative Correlation ◽  
Social Economic ◽  
Statistical Significance ◽  
Married Women ◽  
Breast Cancer Patients ◽  
Number Of Children ◽  
Psychological Hardiness

The current study aims at recognizing the relationship between the health, family, social, economic and psychological pressures and their relation to psychological hardiness among breast cancer patients. The researcher follows descriptive and explanatory approaches to explain this relationship. The research sample consists of 150 women affected by breast cancer; and researcher used the scale of breast cancer patients’ pressures (prepared by Hijazi, 2012), as well as the scale of psychological hardiness (prepared by Mukhaimer, 1997). Results indicated having a negative correlation between the overall rigidity aspect and the health, family, social, economic and psychological pressures. The study also indicated having health, psychological and social pressures affecting breast cancer patients, having differences of statistical significance in family and psychological pressures refer in the marital status variable to married women while having lack of differences of statistical significance in health, social and economic pressures refer to the children variable. Results also indicated that women affected by breast cancer have psychological hardiness, having a negative correlation between the aspects of commitment and control, and the health, family, social, economic, psychological, having a correlation between the aspect of control and the health and economic pressures, having a negative correlation between the aspect of the challenge and the family, social, economic, psychological, having differences of statistical significance in control referring to the marital status variable for the married women and having differences of statistical significance in control, challenge, commitment referring to the number of children variable.

Gasdermin D as a potential prognosis and treatment response prediction biomarker for invasive breast cancer.

2021 ◽  
Vol 39 (15_suppl) ◽  
pp. e12548-e12548
Author(s):  
Xianghou Xia ◽  
Wenjuan Yin ◽  
Jiefei Mao ◽  
Jiejie Hu ◽  
Dehong Zou ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Cancer Patients ◽  
Invasive Breast Cancer ◽  
Response Prediction ◽  
Chemotherapy Response ◽  
Breast Cancer Patients ◽  
Free Survival ◽  
Kaplan Meier ◽  
Kaplan Meier Plotter ◽  
Treatment Response Prediction

e12548 Background: Pyroptosis is a type of inflammatory cell death mediated by gasdermins. Pyroptosis is critical for macrophage against pathogen infection. Recently growing evidences show that pyroptosis may affect development and progression of many cancers. We aim to explore the expression and related function of pyroptosis executioner Gasdermin D (GSDMD) in breast cancer. Methods: We investigated the expression level of GSDMD using TNM plotter and Breast Cancer landscape proteome with TCGA, GTEx and TARGET databases, and the prognostic value of GSDMD in invasive breast cancer using Kaplan-Meier plotter with TCGA, GEO and EGA databases. The treatment response prediction values of GSDMD in invasive breast were calculated using ROC-plotter with GEO database. Further validation of the prognostic value and chemotherapy response prediction value of GSDMD were carried out with immunohistochemical staining on tissues from 165 cases of breast cancer patients receiving neoadjuvant chemotherapy in our cancer center. Results: TNM plotter and breast cancer landscape proteome portal analysis shows that overall expression level of GSDMD in invasive breast cancer tissue is 1.67 folds higher than it is in breast normal tissues ( p=1.05*e-06). Expression of GSDMD in LuminalB subtype (p=0.019) and Her2 subtype(p=0.04) is significantly higher than it is in TNBC subtype. Calculations with Kaplan-Meier plotter show expression of GSDMD is negatively correlated with overall survival(OS), HR=0.61(0.4−0.95) p=0.027 and relapse free survival (RFS), HR =0.65(0.58−0.63), p=8.7*e-14 and distant metastasis free survival (DMFS) HR =0.75(0.61−0.91), p=0.0038 in breast cancer patients. ROC-plotter calculations show high GSDMD expression is a powerful endocrine therapy (AUC=0.731 p=6*e-09 ) and chemotherapy response (AUC=0.64 p=8*e-05 ) predictor based on 5-year RFS in overall breast cancer patients. Our IHC staining analysis shows consistent prognostic and chemotherapy prediction value of GSDMD expression in TNBC patients. Conclusions: In conclusion, our findings suggest that high expression of GSDMD is positively correlated with prognosis and therapeutic response in breast cancer. GSDMD is a promising prognostic marker and therapeutic response predictor in invasive breast cancer.

Breast-Conserving Therapy is Associated with Better Survival than Mastectomy in Early-Stage Breast Cancer: A Propensity Score Analysis

2021 ◽  
Author(s):  
Jiali Ji ◽  
Shushu Yuan ◽  
Jiawei He ◽  
Hong Liu ◽  
Lei Yang ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Propensity Score ◽  
Cancer Patients ◽  
Propensity Score Analysis ◽  
Early Stage ◽  
Breast Conserving Therapy ◽  
Early Stage Breast Cancer ◽  
Breast Cancer Patients ◽  
Kaplan Meier ◽  
Score Analysis

Abstract Background: Recent retrospective studies have reported that breast-conserving therapy (BCT) led to improved overall survival (OS) than mastectomy in some populations. We aimed to compare the efficacy of BCT and mastectomy using the SEER database. Methods: Between 2010 and 2015, 99,790 eligible patients were identified. We included early-stage breast cancer patients with 5cm or smaller tumors and three or fewer positive lymph nodes in our study. We compared the OS results among patients with BCT and mastectomy. Kaplan-Meier plots, Cox proportional hazard regressions were used to evaluate the outcomes. Propensity-score matching was used to assemble a cohort of patients with similar baseline characteristics. Results: In our study, 77,452 (77.6%) patients underwent BCT and 22,338 (22.4%) underwent mastectomy. The 5-year OS rate was 94.7% in the BCT group and 87.6% in the mastectomy group (P <0.001). After matching, multivariate analysis in the matched cohort showed that women underwent mastectomy was associated with worse OS results compared with those with BCT (Hazard ratio (HR) = 1.628; 95% confidence intervals (CIs) = 1.445- 1.834, P<0.001). Patients with different subtypes and age group (>50 years old; ≤50 years old) received BCT all showed significantly better OS than those received mastectomy. The effect of surgery choice on survival was the same in matched and all cohorts. Conclusions: Our study showed that BCT was associated with improved survival compared with mastectomy in early-stage breast cancer patients. It seems advisable to encourage patients to receive BCT rather than mastectomy in early-stage patients when feasible and appropriate.

scholarly journals The Clinicopathological features and survival outcomes of patients with different metastatic sites in stage IV breast cancer

BMC Cancer ◽  
2019 ◽  
Vol 19 (1) ◽  
Author(s):  
Ru Wang ◽  
Yayun Zhu ◽  
Xiaoxu Liu ◽  
Xiaoqin Liao ◽  
Jianjun He ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Brain Metastasis ◽  
Cancer Patients ◽  
Stage Iv ◽  
Clinicopathological Features ◽  
Breast Cancer Patients ◽  
Kaplan Meier ◽  
Stage Iv Breast Cancer ◽  
Multivariable Analyses ◽  
Metastatic Sites

Abstract Background The features and survival of stage IV breast cancer patients with different metastatic sites are poorly understood. This study aims to examine the clinicopathological features and survival of stage IV breast cancer patients according to different metastatic sites. Methods Using the Surveillance, Epidemiology, and End Results database, we restricted our study population to stage IV breast cancer patients diagnosed between 2010 to 2015. The clinicopathological features were examined by chi-square tests. Breast cancer-specific survival (BCSS) and overall survival (OS) were compared among patients with different metastatic sites by the Kaplan-Meier method with log-rank test. Univariable and multivariable analyses were also performed using the Cox proportional hazard model to identify statistically significant prognostic factors. Results A total of 18,322 patients were identified for survival analysis. Bone-only metastasis accounted for 39.80% of patients, followed by multiple metastasis (33.07%), lung metastasis (10.94%), liver metastasis (7.34%), other metastasis (7.34%), and brain metastasis (1.51%). The Kaplan-Meier plots showed that patients with bone metastasis had the best survival, while patients with brain metastasis had the worst survival in both BCSS and OS (p < 0.001, for both). Multivariable analyses showed that age, race, marital status, grade, tumor subtype, tumor size, surgery of primary cancer, and a history of radiotherapy or chemotherapy were independent prognostic factors. Conclusion Stage IV breast cancer patients have different clinicopathological characteristics and survival outcomes according to different metastatic sites. Patients with bone metastasis have the best prognosis, and brain metastasis is the most aggressive subgroup.

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