scholarly journals Quantifying Risk Pathway Crosstalk Mediated by miRNA to Screen Precision drugs for Breast Cancer Patients

Genes ◽  
2019 ◽  
Vol 10 (9) ◽  
pp. 657 ◽  
Author(s):  
Xu ◽  
Lin ◽  
Zhao ◽  
Wang ◽  
Zhang ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Breast Cancer Subtype ◽  
Breast Cancer Patients ◽  
Cancer Subtypes ◽  
Risk Pathway ◽  
Therapeutic Drugs ◽  
Pathway Crosstalk ◽  
Novel Drugs ◽  
Effective Drugs ◽  
The Impact

Breast cancer has become the most common cancer that leads to women's death. Breast cancer is a complex, highly heterogeneous disease classified into various subtypes based on histological features, which determines the therapeutic options. System identification of effective drugs for each subtype remains challenging. In this work, we present a computational network biology approach to screen precision drugs for different breast cancer subtypes by considering the impact intensity of candidate drugs on the pathway crosstalk mediated by miRNAs. Firstly, we constructed and analyzed the subtype-specific risk pathway crosstalk networks mediated by miRNAs. Then, we evaluated 36 Food and Drug Administration (FDA)-approved anticancer drugs by quantifying their effects on these subtype-specific pathway crosstalk networks and combining with survival analysis. Finally, some first-line treatments of breast cancer, such as Paclitaxel and Vincristine, were optimized for each subtype. In particular, we performed precision screening of subtype-specific therapeutic drugs and also confirmed some novel drugs suitable for breast cancer treatment. For example, Sorafenib was applicable for the basal subtype treatment, Irinotecan was optimum for Her2 subtype treatment, Vemurafenib was suitable for the LumA subtype treatment, and Vorinostat could apply to LumB subtype treatment. In addition, the mechanism of these optimal therapeutic drugs in each subtype of breast cancer was further dissected. In summary, our study offers an effective way to screen precision drugs for various breast cancer subtype treatments. We also dissected the mechanism of optimal therapeutic drugs, which may provide novel insight into the precise treatment of cancer and promote researches on the mechanisms of action of drugs.

scholarly journals Study on epidemiology, risk factors and clinical characteristics of triple negative breast cancer in Bangladesh

2018 ◽  
Vol 6 (8) ◽  
pp. 2554
Author(s):  
Fatema Tuz Zohora ◽  
Mohammad Fazle Rabbi
Keyword(s):  
Breast Cancer ◽  
Risk Factors ◽  
Triple Negative Breast Cancer ◽  
Clinical Characteristics ◽  
Triple Negative ◽  
Breast Cancer Subtype ◽  
Breast Cancer Subtypes ◽  
African Women ◽  
Breast Cancer Patients ◽  
Cancer Subtypes

Breast cancer is the second most common type of cancer in Bangladesh. Although significant improvement has been made in breast cancer treatment and management, Triple Negative Breast Cancer (TNBC) is still the least known breast cancer subtype in this country. TNBC is well known for its aggressive nature and limited therapeutic options when compared to other breast cancer subtypes. Several population-based studies indicated high prevalence of TNBC in African women in addition to few recent studies indicating a growing number of TNBC patients among Asian population. However, there is a lack of evidence on TNBC patients in Bangladesh due to limited knowledge and awareness. In this paper we review the epidemiology, general risk factors and clinical characteristics of TNBC to find out the correlation between TNBC and other conventional breast cancer subtypes in Bangladesh. Some diagnostic and therapeutic approaches as well as future novel solutions for TNBC are also discussed to understand the pathologic process and treatment strategies of TNBC. Literature review reveals that, there is a lack of TNBC studies in Bangladesh. Therefore, more investigations should be carried out to address the degree of vulnerability of TNBC in breast cancer patients of Bangladesh.

scholarly journals DNA Methylation Based Molecular Subtypes Predict Prognosis in Breast Cancer Patients

2021 ◽  
Vol 28 ◽  
pp. 107327482098851
Author(s):  
Zeng-Hong Wu ◽  
Yun Tang ◽  
Yan Zhou
Keyword(s):  
Breast Cancer ◽  
Dna Methylation ◽  
Molecular Subtypes ◽  
Methylation Status ◽  
The Cancer Genome Atlas ◽  
Training Dataset ◽  
Consensus Clustering ◽  
Breast Cancer Patients ◽  
Cancer Subtypes ◽  
Novel Biomarkers

Background: Epigenetic changes are tightly linked to tumorigenesis development and malignant transformation’ However, DNA methylation occurs earlier and is constant during tumorigenesis. It plays an important role in controlling gene expression in cancer cells. Methods: In this study, we determining the prognostic value of molecular subtypes based on DNA methylation status in breast cancer samples obtained from The Cancer Genome Atlas database (TCGA). Results: Seven clusters and 204 corresponding promoter genes were identified based on consensus clustering using 166 CpG sites that significantly influenced survival outcomes. The overall survival (OS) analysis showed a significant prognostic difference among the 7 groups (p<0.05). Finally, a prognostic model was used to estimate the results of patients on the testing set based on the classification findings of a training dataset DNA methylation subgroups. Conclusions: The model was found to be important in the identification of novel biomarkers and could be of help to patients with different breast cancer subtypes when predicting prognosis, clinical diagnosis and management.

scholarly journals Human Plasma Metabolomics for Biomarker Discovery: Targeting the Molecular Subtypes in Breast Cancer

Cancers ◽  
2021 ◽  
Vol 13 (1) ◽  
pp. 147
Author(s):  
Leticia Díaz-Beltrán ◽  
Carmen González-Olmedo ◽  
Natalia Luque-Caro ◽  
Caridad Díaz ◽  
Ariadna Martín-Blázquez ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Cancer Patients ◽  
Biomarker Discovery ◽  
Molecular Subtypes ◽  
Breast Cancer Subtype ◽  
P Value ◽  
Plasma Samples ◽  
Breast Cancer Patients ◽  
Clinical Value ◽  
Molecular Phenotypes

Purpose: The aim of this study is to identify differential metabolomic signatures in plasma samples of distinct subtypes of breast cancer patients that could be used in clinical practice as diagnostic biomarkers for these molecular phenotypes and to provide a more individualized and accurate therapeutic procedure. Methods: Untargeted LC-HRMS metabolomics approach in positive and negative electrospray ionization mode was used to analyze plasma samples from LA, LB, HER2+ and TN breast cancer patients and healthy controls in order to determine specific metabolomic profiles through univariate and multivariate statistical data analysis. Results: We tentatively identified altered metabolites displaying concentration variations among the four breast cancer molecular subtypes. We found a biomarker panel of 5 candidates in LA, 7 in LB, 5 in HER2 and 3 in TN that were able to discriminate each breast cancer subtype with a false discovery range corrected p-value < 0.05 and a fold-change cutoff value > 1.3. The model clinical value was evaluated with the AUROC, providing diagnostic capacities above 0.85. Conclusion: Our study identifies metabolic profiling differences in molecular phenotypes of breast cancer. This may represent a key step towards therapy improvement in personalized medicine and prioritization of tailored therapeutic intervention strategies.

scholarly journals Clinical Significance of Annexin A2 Expression in Breast Cancer Patients

Cancers ◽  
2020 ◽  
Vol 13 (1) ◽  
pp. 2
Author(s):  
Lee D. Gibbs ◽  
Kelsey Mansheim ◽  
Sayantan Maji ◽  
Rajesh Nandy ◽  
Cheryl M. Lewis ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Cancer Patients ◽  
Clinical Significance ◽  
Cell Lines ◽  
Breast Cancer Subtypes ◽  
Enzyme Linked Immunosorbent Assay ◽  
Breast Cancer Patients ◽  
Serum Samples ◽  
Cancer Subtypes ◽  
Tumor Tissues

Increasing evidence suggests that AnxA2 contributes to invasion and metastasis of breast cancer. However, the clinical significance of AnxA2 expression in breast cancer has not been reported. The expression of AnxA2 in cell lines, tumor tissues, and serum samples of breast cancer patients were analyzed by immunoblotting, immunohistochemistry, and enzyme-linked immunosorbent assay, respectively. We found that AnxA2 was significantly upregulated in tumor tissues and serum samples of breast cancer patients compared with normal controls. The high expression of serum AnxA2 was significantly associated with tumor grades and poor survival of the breast cancer patients. Based on molecular subtypes, AnxA2 expression was significantly elevated in tumor tissues and serum samples of triple-negative breast cancer (TNBC) patients compared with other breast cancer subtypes. Our analyses on breast cancer cell lines demonstrated that secretion of AnxA2 is associated with its tyrosine 23 (Tyr23) phosphorylation in cells. The expression of non-phosphomimetic mutant of AnxA2 in HCC1395 cells inhibits its secretion from cells compared to wild-type AnxA2, which further suggest that Tyr23 phosphorylation is a critical step for AnxA2 secretion from TNBC cells. Our analysis of AnxA2 phosphorylation in clinical samples further confirmed that the phosphorylation of AnxA2 at Tyr23 was high in tumor tissues of TNBC patients compared to matched adjacent non-tumorigenic breast tissues. Furthermore, we observed that the diagnostic value of serum AnxA2 was significantly high in TNBC compared with other breast cancer subtypes. These findings suggest that serum AnxA2 concentration could be a potential diagnostic biomarker for TNBC patients.

scholarly journals CBR3 V244M is associated with LVEF reduction in breast cancer patients treated with doxorubicin

2021 ◽  
Vol 7 (1) ◽  
Author(s):  
Jennifer K. Lang ◽  
Badri Karthikeyan ◽  
Adolfo Quiñones-Lombraña ◽  
Rachael Hageman Blair ◽  
Amy P. Early ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Cancer Patients ◽  
Care Center ◽  
Left Ventricular ◽  
The Body ◽  
Left Ventricular Ejection ◽  
Breast Cancer Patients ◽  
Ventricular Ejection Fraction ◽  
Echocardiographic Parameters ◽  
The Impact

Abstract Background The CBR3 V244M single nucleotide polymorphism has been linked to the risk of anthracycline-related cardiomyopathy in survivors of childhood cancer. There have been limited prospective studies examining the impact of CBR3 V244M on the risk for anthracycline-related cardiotoxicity in adult cohorts. Objectives This study evaluated the presence of associations between CBR3 V244M genotype status and changes in echocardiographic parameters in breast cancer patients undergoing doxorubicin treatment. Methods We recruited 155 patients with breast cancer receiving treatment with doxorubicin (DOX) at Roswell Park Comprehensive Care Center (Buffalo, NY) to a prospective single arm observational pharmacogenetic study. Patients were genotyped for the CBR3 V244M variant. 92 patients received an echocardiogram at baseline (t0 month) and at 6 months (t6 months) of follow up after DOX treatment. Apical two-chamber and four-chamber echocardiographic images were used to calculate volumes and left ventricular ejection fraction (LVEF) using Simpson’s biplane rule by investigators blinded to all patient data. Volumetric indices were evaluated by normalizing the cardiac volumes to the body surface area (BSA). Results Breast cancer patients with CBR3 GG and AG genotypes both experienced a statistically significant reduction in LVEF at 6 months following initiation of DOX treatment for breast cancer compared with their pre-DOX baseline study. Patients homozygous for the CBR3 V244M G allele (CBR3 V244) exhibited a further statistically significant decrease in LVEF at 6 months following DOX therapy in comparison with patients with heterozygous AG genotype. We found no differences in age, pre-existing cardiac diseases associated with myocardial injury, cumulative DOX dose, or concurrent use of cardioprotective medication between CBR3 genotype groups. Conclusions CBR3 V244M genotype status is associated with changes in echocardiographic parameters suggestive of early anthracycline-related cardiomyopathy in subjects undergoing chemotherapy for breast cancer.

scholarly journals Impact of Pharmaceutical Prophylaxis on Radiation-Induced Liver Disease Following Radioembolization

Cancers ◽  
2021 ◽  
Vol 13 (9) ◽  
pp. 1992
Author(s):  
Max Seidensticker ◽  
Matthias Philipp Fabritius ◽  
Jannik Beller ◽  
Ricarda Seidensticker ◽  
Andrei Todica ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Metastatic Breast Cancer ◽  
Liver Disease ◽  
Positive Impact ◽  
Metastatic Breast ◽  
Normal Liver ◽  
Liver Parenchyma ◽  
Breast Cancer Patients ◽  
Radiation Induced ◽  
The Impact

Background: Radioembolization (RE) with yttrium-90 (90Y) resin microspheres yields heterogeneous response rates in with primary or secondary liver cancer. Radiation-induced liver disease (RILD) is a potentially life-threatening complication with higher prevalence in cirrhotics or patients exposed to previous chemotherapies. Advances in RILD prevention may help increasing tolerable radiation doses to improve patient outcomes. This study aimed to evaluate the impact of post-therapeutic RILD-prophylaxis in a cohort of intensely pretreated liver metastatic breast cancer patients; Methods: Ninety-three patients with liver metastases of breast cancer received RE between 2007 and 2016. All Patients received RILD prophylaxis for 8 weeks post-RE. From January 2014, RILD prophylaxis was changed from ursodeoxycholic acid (UDCA) and prednisolone (standard prophylaxis [SP]; n = 59) to pentoxifylline (PTX), UDCA and low-dose low molecular weight heparin (LMWH) (modified prophylaxis (MP); n = 34). The primary endpoint was toxicity including symptoms of RILD; Results: Dose exposure of normal liver parenchyma was higher in the modified vs. standard prophylaxis group (47.2 Gy (17.8–86.8) vs. 40.2 Gy (12.5–83.5), p = 0.017). All grade RILD events (mild: bilirubin ≥ 21 µmol/L (but <30 μmol/L); severe: (bilirubin ≥ 30 µmol/L and ascites)) were observed more frequently in the SP group than in the MP group, albeit without significance (7/59 vs. 1/34; p = 0.140). Severe RILD occurred in the SP group only (n = 2; p > 0.1). ALBI grade increased in 16.7% patients in the MP and in 27.1% patients in the SP group, respectively (group difference not significant); Conclusions: At established dose levels, mild or severe RILD events proved rare in our cohort. RILD prophylaxis with PTX, UDCA and LMWH appears to have an independent positive impact on OS in patients with metastatic breast cancer and may reduce the frequency and severity of RILD. Results of this study as well as pathophysiological considerations warrant further investigations of RILD prophylaxis presumably targeting combinations of anticoagulation (MP) and antiinflammation (SP) to increase dose prescriptions in radioembolization.

scholarly journals PITX2 DNA-Methylation: Predictive versus Prognostic Value for Anthracycline-Based Chemotherapy in Triple-Negative Breast Cancer Patients

Breast Care ◽  
2020 ◽  
pp. 1-9
Author(s):  
Rudolf Napieralski ◽  
Gabriele Schricker ◽  
Gert Auer ◽  
Michaela Aubele ◽  
Jonathan Perkins ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Dna Methylation ◽  
Cancer Patients ◽  
Triple Negative Breast Cancer ◽  
Predictive Value ◽  
Untreated Patient ◽  
Triple Negative ◽  
Statistical Significance ◽  
Breast Cancer Patients ◽  
The Impact

<b><i>Background:</i></b> PITX2 DNA methylation has been shown to predict outcomes in high-risk breast cancer patients after anthracycline-based chemotherapy. To determine its prognostic versus predictive value, the impact of PITX2 DNA methylation on outcomes was studied in an untreated cohort vs. an anthracycline-treated triple-negative breast cancer (TNBC) cohort. <b><i>Material and Methods:</i></b> The percent DNA methylation ratio (PMR) of paired-like homeodomain transcription factor 2 (PITX2) was determined by a validated methylation-specific real-time PCR test. Patient samples of routinely collected archived formalin-fixed paraffin-embedded (FFPE) tissue and clinical data from 144 TNBC patients of 2 independent cohorts (i.e., 66 untreated patients and 78 patients treated with anthracycline-based chemotherapy) were analyzed. <b><i>Results:</i></b> The risk of 5- and 10-year overall survival (OS) increased continuously with rising PITX2 DNA methylation in the anthracycline-treated population, but it increased only slightly during 10-year follow-up time in the untreated patient population. PITX2 DNA methylation with a PMR cutoff of 2 did not show significance for poor vs. good outcomes (OS) in the untreated patient cohort (HR = 1.55; <i>p</i> = 0.259). In contrast, the PITX2 PMR cutoff of 2 identified patients with poor (PMR &#x3e;2) vs. good (PMR ≤2) outcomes (OS) with statistical significance in the anthracycline-treated cohort (HR = 3.96; <i>p</i> = 0.011). The results in the subgroup of patients who did receive anthracyclines only (no taxanes) confirmed this finding (HR = 5.71; <i>p</i> = 0.014). <b><i>Conclusion:</i></b> In this hypothesis-generating study PITX2 DNA methylation demonstrated predominantly predictive value in anthracycline treatment in TNBC patients. The risk of poor outcome (OS) correlates with increasing PITX2 DNA methylation.

scholarly journals KBoost: a new method to infer gene regulatory networks from gene expression data

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Luis F. Iglesias-Martinez ◽  
Barbara De Kegel ◽  
Walter Kolch
Keyword(s):  
Breast Cancer ◽  
Gene Regulatory Networks ◽  
Regulatory Networks ◽  
Bayesian Model Averaging ◽  
Model Averaging ◽  
R Package ◽  
Breast Cancer Patients ◽  
Sources Of Information ◽  
Cancer Subtypes ◽  
Gene Regulatory

AbstractReconstructing gene regulatory networks is crucial to understand biological processes and holds potential for developing personalized treatment. Yet, it is still an open problem as state-of-the-art algorithms are often not able to process large amounts of data within reasonable time. Furthermore, many of the existing methods predict numerous false positives and have limited capabilities to integrate other sources of information, such as previously known interactions. Here we introduce KBoost, an algorithm that uses kernel PCA regression, boosting and Bayesian model averaging for fast and accurate reconstruction of gene regulatory networks. We have benchmarked KBoost against other high performing algorithms using three different datasets. The results show that our method compares favorably to other methods across datasets. We have also applied KBoost to a large cohort of close to 2000 breast cancer patients and 24,000 genes in less than 2 h on standard hardware. Our results show that molecularly defined breast cancer subtypes also feature differences in their GRNs. An implementation of KBoost in the form of an R package is available at: https://github.com/Luisiglm/KBoost and as a Bioconductor software package.

scholarly journals Surgery for primary tumor benefits survival for breast cancer patients with bone metastases: a large cohort retrospective study

BMC Cancer ◽  
2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Zhangheng Huang ◽  
Xin Zhou ◽  
Yuexin Tong ◽  
Lujian Zhu ◽  
Ruhan Zhao ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Prognostic Factors ◽  
Bone Metastases ◽  
Cancer Patients ◽  
Primary Tumor ◽  
Predictive Accuracy ◽  
Rank Test ◽  
Breast Cancer Patients ◽  
Risk Of Death ◽  
The Impact

Abstract Background The role of surgery for the primary tumor in breast cancer patients with bone metastases (BM) remains unclear. The purpose of this study was to determine the impact of surgery for the primary tumor in breast cancer patients with BM and to develop prognostic nomograms to predict the overall survival (OS) of breast cancer patients with BM. Methods A total of 3956 breast cancer patients with BM from the Surveillance, Epidemiology, and End Results database between 2010 and 2016 were included. Propensity score matching (PSM) was used to eliminate the bias between the surgery and non-surgery groups. The Kaplan-Meier analysis and the log-rank test were performed to compare the OS between two groups. Cox proportional risk regression models were used to identify independent prognostic factors. Two nomograms were constructed for predicting the OS of patients in the surgery and non-surgery groups, respectively. In addition, calibration curve, receiver operating characteristic (ROC) curve, and decision curve analysis (DCA) were used to evaluate the performance of nomograms. Result The survival analysis showed that the surgery of the primary tumor significantly improved the OS for breast cancer patients with BM. Based on independent prognostic factors, separate nomograms were constructed for the surgery and non-surgery groups. The calibration and ROC curves of these nomograms indicated that both two models have high predictive accuracy, with the area under the curve values ≥0.700 on both the training and validation cohorts. Moreover, DCA showed that nomograms have strong clinical utility. Based on the results of the X-tile analysis, all patients were classified in the low-risk-of-death subgroup had a better prognosis. Conclusion The surgery of the primary tumor may provide survival benefits for breast cancer patients with BM. Furthermore, these prognostic nomograms we constructed may be used as a tool to accurately assess the long-term prognosis of patients and help clinicians to develop individualized treatment strategies.

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