scholarly journals The prognostic association of SPAG5 gene expression in breast cancer patients with systematic therapy

BMC Cancer ◽  
2019 ◽  
Vol 19 (1) ◽  
Author(s):  
Chenjing Zhu ◽  
Otilia Menyhart ◽  
Balázs Győrffy ◽  
Xia He
Keyword(s):  
Breast Cancer ◽  
Gene Expression ◽  
Cancer Patients ◽  
Hormonal Therapy ◽  
Roc Analysis ◽  
Survival Outcomes ◽  
Clinicopathological Factors ◽  
Breast Cancer Patients ◽  
Free Survival ◽  
Increased Risk

Abstract Background Despite much effort on the treatment of breast cancer over the decades, a great uncertainty regarding the appropriate molecular biomarkers and optimal therapeutic strategy still exists. This research was performed to analyze the association of SPAG5 gene expression with clinicopathological factors and survival outcomes. Methods We used a breast cancer database including 5667 patients with a mean follow-up of 69 months. Kaplan-Meier survival analyses for relapse free survival (RFS), overall survival (OS), and distant metastasis-free survival (DMFS) were performed. In addition, ROC analysis was performed to validate SPAG5 as a prognostic candidate gene. Results Mean SPAG5 expression value was significantly higher with some clinicopathological factors that resulted in tumor promotion and progression, including poor differentiated type, HER2 positive or TP53 mutated breast cancer. Based on ROC-analysis SPAG 5 is a suitable prognostic marker of poor survival. In patients who received chemotherapy alone, SPAG5 had only a moderate and not significant predictive impact on survival outcomes. However, in hormonal therapy, high SPAG5 expression could strongly predict prognosis with detrimental RFS (HR = 1.57, 95% CI 1.2–2.06, p = 0.001), OS (HR = 2, 95% CI 1.05–3.8, p = 0.03) and DMFS (HR = 2.36, 95% CI 1.57–3.54, p <  0.001), respectively. In addition, SPAG5 could only serve as a survival predictor in ER+, but not ER- breast cancer patients. Patients might also be at an increased risk of relapse despite being diagnosed with a lower grade cancer (well differentiated type). Conclusions SPAG5 could be used as an independent prognostic and predictive biomarker that might have clinical utility, especially in ER+ breast cancer patients who received hormonal therapy.

Comprehensive Analysis of the Expression and Prognostic Significance of THBSs in Breast Cancer

2021 ◽  
Author(s):  
Jun Wang ◽  
Xuebing Zhan ◽  
Qian Luo ◽  
Yunshu Kuang ◽  
Xiao Liang ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Gene Expression ◽  
Protein Expression ◽  
Cancer Patients ◽  
Prognostic Value ◽  
Breast Cancer Patients ◽  
Free Survival ◽  
Expression Levels ◽  
Cancer Tissues ◽  
Mrna Expression Levels

Abstract Background: Breast cancer is one of the most common tumors for women worldwide. Thrombospondins (THBSs) are reported to play important roles in various cellular processes and are involved in the occurrence and development of human cancers. However, the expression and prognostic value of THBSs family in breast cancer remain unclear.Methods: In this study, we examined the genes and protein expression levels of THBSs and their prognostic value by synthesizing several mainstream databases, including Oncomine, Human Protein Atlas (HPA), UALCAN, and KM Plotter. We also analyzed THBS interaction networks, genetic alterations, functional enrichment, and drug sensitivity with several publicly accessible databases, including GEPIA, GeneMANIA, STRING, cBioPortal, Metascape and NCI-60 database.Results: The results showed that the mRNA expression levels of THBS1, THBS2, THBS3, and THBS5 in breast cancer tissues were significantly higher than in normal tissues. The mRNA expression levels of THBS4 were different in different subtypes of breast cancer, and the protein expression levels of THBS1, THBS2, and THBS4 in breast cancer tissues were higher than in normal breast tissues. Survival analysis showed that breast cancer patients with high THBS1 gene expression showed worse overall survival (OS), relapse-free survival (RFS), and post-progression survival (PPS), and breast cancer patients with high THBS2 gene expression also showed worse RFS. Conversely, lower THBS3 levels predicted worse RFS, and lower THBS4 levels predicted worse OS, RFS, and distant metastasis-free survival (DMFS). Conclusions: These results suggest that THBSs may be potential biomarkers for breast cancer.

scholarly journals Prognostic impact of the glypican family of heparan sulfate proteoglycans on the survival of breast cancer patients

2021 ◽  
Author(s):  
Paulina Karin Grillo ◽  
Balázs Győrffy ◽  
Martin Götte
Keyword(s):  
Breast Cancer ◽  
Gene Expression ◽  
Heparan Sulfate ◽  
Cancer Patients ◽  
Heparan Sulfate Proteoglycans ◽  
Prognostic Impact ◽  
Breast Cancer Patients ◽  
Relapse Free Survival ◽  
Free Survival ◽  
The Impact

Abstract Purpose Dysregulated expression of proteoglycans influences the outcome and progression of numerous cancers. Several studies have investigated the role of individual glypicans in cancer, however, the impact of the whole glypican family of heparan sulfate proteoglycans on prognosis of a large patient cohort of breast cancer patients has not yet been investigated. In the present study, our aim was to investigate the prognostic power of the glypicans in breast cancer patients. Methods We used a public database including both gene expression data and survival information for 3951 breast cancer patients to determine the prognostic value of glypicans on relapse-free survival using Cox regression analysis. Moreover, we performed quantitative Real-Time PCR to determine glypican gene expression levels in seven representative breast cancer cell lines. Results We found that high GPC3 levels were associated with a better prognosis in overall breast cancer patients. When stratified by hormone receptor status, we found that in worse prognosis subtypes low GPC1 levels correlate with a longer relapse-free survival, and in more favorable subtypes low GPC6 was associated with longer survival. Conclusion Our study concludes that glypicans could act as subtype-specific biomarkers for the prognosis of breast cancer patients and sparks hope for future research on glypicans possibly eventually providing targets for the treatment of the disease.

scholarly journals Impact of Post-diagnosis Weight Change on Survival Outcomes in a Multiethnic Cohort of Breast Cancer Patients

2020 ◽  
Author(s):  
Lihua Shang ◽  
Masaya Hattori ◽  
Gini Fleming ◽  
Nora Jaskowiak ◽  
Donald Hedeker ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Overall Survival ◽  
Cancer Patients ◽  
Weight Change ◽  
Repeated Measures ◽  
Disease Free Survival ◽  
Metastatic Breast ◽  
Survival Outcomes ◽  
Breast Cancer Patients ◽  
Increased Risk

Abstract Purpose: To evaluate weight change patterns over time following the diagnosis of breast cancer, and to examine the association of post-diagnosis weight change and survival outcomes in Black and White patients.Methods: The study included 2,888 women diagnosed with non-metastatic breast cancer in 2000-2017 in Chicago. Longitudinal repeated measures of weight and height were collected, along with a questionnaire survey including questions on body size. Multilevel mixed-effects models were used to examine changes in body mass index (BMI). Delayed entry Cox proportional hazards models were used to investigate the impacts of changing slope of BMI on survival outcomes. Results: At diagnosis, most patients were overweight or obese with a mean BMI of 27.5 kg/m2 and 31.5 kg/m2 for Blacks and Whites, respectively. Notably, about 45% of the patients had cachexia before death and substantial weight loss started about 30 months before death. In multivariable-adjusted analyses, compared to stable weight, BMI loss (>0.5 kg/m2/year) showed greater than 2-fold increased risk in overall survival (hazard ratio [HR]=2.68, 95%CI 1.95-3.66), breast cancer specific survival (HR=2.93, 95%CI 1.86-4.62), and disease-free survival (HR=2.25, 95%CI 1.63-3.11). The associations were not modified by race, age at diagnosis, and pre-diagnostic weight. BMI gain (>0.5 kg/m2/year) was also related to worse survival, but the effect was weak (HR=1.53, 95%CI 1.06-2.22 for overall survival).Conclusion: BMI loss is a strong predictor of worse breast cancer outcomes. Growing prevalence of obesity may hide diagnosis of cancer cachexia, which can occur in a large proportion of breast cancer patients long before death.

scholarly journals Impact of Post-diagnosis Weight Change on Survival Outcomes in Black and White Breast Cancer Patients

2021 ◽  
Author(s):  
Lihua Shang ◽  
Masaya Hattori ◽  
Gini Fleming ◽  
Nora Jaskowiak ◽  
Donald Hedeker ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Overall Survival ◽  
Cancer Patients ◽  
Weight Change ◽  
Repeated Measures ◽  
Disease Free Survival ◽  
Survival Outcomes ◽  
Breast Cancer Patients ◽  
Black And White ◽  
Increased Risk

Abstract Purpose: To evaluate weight change patterns over time following the diagnosis of breast cancer, and to examine the association of post-diagnosis weight change and survival outcomes in Black and White patients.Methods: The study included 2,888 women diagnosed with non-metastatic breast cancer in 2000-2017 in Chicago. Longitudinal repeated measures of weight and height were collected, along with a questionnaire survey including questions on body size. Multilevel mixed-effects models were used to examine changes in body mass index (BMI). Delayed entry Cox proportional hazards models were used to investigate the impacts of changing slope of BMI on survival outcomes. Results: At diagnosis, most patients were overweight or obese with a mean BMI of 27.5 kg/m2 and 31.5 kg/m2 for Blacks and Whites, respectively. Notably, about 45% of the patients had cachexia before death and substantial weight loss started about 30 months before death. In multivariable-adjusted analyses, compared to stable weight, BMI loss (>0.5 kg/m2/year) showed greater than 2-fold increased risk in overall survival (hazard ratio [HR]=2.60, 95%CI 1.88-3.59), breast cancer specific survival (HR=3.05, 95%CI 1.91-4.86), and disease-free survival (HR=2.12, 95%CI 1.52-2.96). The associations were not modified by race, age at diagnosis, and pre-diagnostic weight. BMI gain (>0.5 kg/m2/year) was also related to worse survival, but the effect was weak (HR=1.60, 95%CI 1.10-2.33 for overall survival).Conclusion: BMI loss is a strong predictor of worse breast cancer outcomes. Growing prevalence of obesity may hide diagnosis of cancer cachexia, which can occur in a large proportion of breast cancer patients long before death.

scholarly journals The therapy is making me sick: how online portal communications between breast cancer patients and physicians indicate medication discontinuation

2018 ◽  
Vol 25 (11) ◽  
pp. 1444-1451 ◽  
Author(s):  
Zhijun Yin ◽  
Morgan Harrell ◽  
Jeremy L Warner ◽  
Qingxia Chen ◽  
Daniel Fabbri ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Side Effects ◽  
Cancer Patients ◽  
Hormonal Therapy ◽  
Medical Center ◽  
Healthcare Providers ◽  
Breast Cancer Patients ◽  
Online Portal ◽  
Medication Discontinuation ◽  
Increased Risk

Abstract Objective Online platforms have created a variety of opportunities for breast patients to discuss their hormonal therapy, a long-term adjuvant treatment to reduce the chance of breast cancer occurrence and mortality. The goal of this investigation is to ascertain the extent to which the messages breast cancer patients communicated through an online portal can indicate their potential for discontinuing hormonal therapy. Materials and Methods We studied the de-identified electronic medical records of 1106 breast cancer patients who were prescribed hormonal therapy at Vanderbilt University Medical Center over a 12-year period. We designed a data-driven approach to investigate patients’ patterns of messaging with healthcare providers, the topics they communicated, and the extent to which these messaging behaviors associate with the likelihood that a patient will discontinue a prescribed 5-year regimen of therapy. Results The results indicates that messaging rate over time [hazard ratio (HR) = 1.373, P = 0.002], mentions of side effects (HR = 1.214, P = 0.006), and surgery-related topics (HR = 1.170, P = 0.034) were associated with increased risk of early medication discontinuation. In contrast, seeking professional suggestions (HR = 0.766, P = 0.002), expressing gratitude to healthcare providers (HR = 0.872, P = 0.044), and mentions of drugs used to treat side effects (HR = 0.807, P = 0.013) were associated with decreased risk of medication discontinuation. Discussion and Conclusion This investigation suggests that patient-generated content can inform the study of health-related behaviors. Given that approximately 50% of breast cancer patients do not complete a course of hormonal therapy as described, the identification of factors associated with medication discontinuation can facilitate real-time interventions to prevent early discontinuation.

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