scholarly journals Diagnostic value of sialyl‐Tn immunocytochemistry in breast cancer presenting with pathological nipple discharge

2021 ◽  
Author(s):  
Feng Xu ◽  
Yue Gao ◽  
Xiaoli Diao ◽  
Jie Li ◽  
Hongchuan Jiang ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Nipple Discharge ◽  
Diagnostic Value ◽  
Sialyl Tn

Optimizing Breast Cancer Follow-up Care: Diagnostic Value and Costs of Additional Routine Breast Ultrasound

2010 ◽  
Vol 31 (S 01) ◽  
Author(s):  
S Wojcinski ◽  
A Farrokh ◽  
U Hille ◽  
E Hirschauer ◽  
W Schmidt ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Diagnostic Value ◽  
Breast Ultrasound ◽  
Follow Up Care

Positron emission mammography in the diagnosis of breast cancer

2016 ◽  
Vol 55 (01) ◽  
pp. 15-20 ◽  
Author(s):  
J. Farahati ◽  
A. G. Müller ◽  
E. Gillman ◽  
M. Hentschel ◽  
F. H. H. Müller
Keyword(s):  
Breast Cancer ◽  
High Specificity ◽  
Diagnostic Value ◽  
Glandular Tissue ◽  
Breast Cancer Patients ◽  
Malignant Tumours ◽  
Benign Lesions ◽  
Interventional Study ◽  
Positron Emission Mammography ◽  
Positron Emission

SummaryAim: To evaluate the diagnostic value (sensitivity, specificity) of positron emission mammography (PEM) in a single site non-interventional study using the maximum PEM uptake value (PUVmax). Patients, methods: In a singlesite, non-interventional study, 108 patients (107 women, 1 man) with a total of 151 suspected lesions were scanned with a PEM Flex Solo II (Naviscan) at 90 min p.i. with 3.5 MBq 18F-FDG per kg of body weight. In this ROI(region of interest)-based analysis, maximum PEM uptake value (PUV) was determined in lesions, tumours (PUVmaxtumour), benign lesions (PUVmaxnormal breast) and also in healthy tissues on the contralateral side (PUVmaxcontralateral breast). These values were compared and contrasted. In addition, the ratios of PUVmaxtumour / PUVmaxcontralateral breast and PUVmaxnormal breast / PUVmaxcontralateral breast were compared. The image data were interpreted independently by two experienced nuclear medicine physicians and compared with histology in cases of suspected carcinoma. Results: Based on a criteria of PUV>1.9, 31 out of 151 lesions in the patient cohort were found to be malignant (21%). A mean PUVmaxtumour of 3.78 ± 2.47 was identified in malignant tumours, while a mean PUVmaxnormal breast of 1.17 ± 0.37 was reported in the glandular tissue of the healthy breast, with the difference being statistically significant (p < 0.001). Similarly, the mean ratio between tumour and healthy glandular tissue in breast cancer patients (3.15 ± 1.58) was found to be significantly higher than the ratio for benign lesions (1.17 ± 0.41, p < 0.001). Conclusion: PEM is capable of differentiating breast tumours from benign lesions with 100% sensitivity along with a high specificity of 96%, when a threshold of PUVmax >1.9 is applied.

scholarly journals Discovery and function exploration of microRNA-155 as a molecular biomarker for early detection of breast cancer

Breast Cancer ◽  
2021 ◽  
Author(s):  
Xuemin Liu ◽  
Qingyu Chang ◽  
Haiqiang Wang ◽  
Hairong Qian ◽  
Yikun Jiang
Keyword(s):  
Breast Cancer ◽  
Early Detection ◽  
Protein Interactions ◽  
Meta Analysis ◽  
Enrichment Analysis ◽  
Diagnostic Value ◽  
Diagnostic Biomarker ◽  
Analysis Model ◽  
Sensitivity Specificity ◽  
Function Enrichment

Abstract Background MicroRNA-155 (miR-155) may function as a diagnostic biomarker of breast cancer (BC). Nevertheless, the available evidence is controversial. Therefore, we performed this study to summarize the global predicting role of miR-155 for early detection of BC and preliminarily explore the functional roles of miR-155 in BC. Methods We first collected published studies and applied the bivariate meta-analysis model to generate the pooled diagnostic parameters of miR-155 in diagnosing BC such as sensitivity, specificity and area under curve (AUC). Then, we applied function enrichment and protein–protein interactions (PPI) analyses to explore the potential mechanisms of miR-155. Results A total of 21 studies were finally included. The results indicated that miR-155 allowed for the discrimination between BC patients and healthy controls with a sensitivity of 0.87 (95% CI 0.78–0.93), specificity of 0.82 (0.72–0.89), and AUC of 0.91 (0.88–0.93). In addition, the overall sensitivity, specificity and AUC for circulating miR-155 were 0.88 (0.76–0.95), 0.83 (0.72–0.90), and 0.92 (0.89–0.94), respectively. Function enrichment analysis revealed several vital ontologies terms and pathways associated with BC occurrence and development. Furthermore, in the PPI network, ten hub genes and two significant modules were identified to be involved in some important pathways associated with the pathogenesis of BC. Conclusions We demonstrated that miR-155 has great potential to facilitate accurate BC detection and may serve as a promising diagnostic biomarker for BC. However, well-designed cohort studies and biological experiments should be implemented to confirm the diagnostic value of miR-155 before it can be applied to routine clinical procedures.

scholarly journals Duct Excision is Still Necessary to Rule out Breast Cancer in Patients Presenting with Spontaneous Bloodstained Nipple Discharge

2011 ◽  
Vol 2011 ◽  
pp. 1-6 ◽  
Author(s):  
R. E. Foulkes ◽  
G. Heard ◽  
T. Boyce ◽  
R. Skyrme ◽  
P. A. Holland ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Malignant Disease ◽  
Nonoperative Management ◽  
Nipple Discharge ◽  
Breast Clinic ◽  
Exact Test ◽  
Malignant Lesions ◽  
Duct Excision ◽  
Symptomatic Breast ◽  
Rule Out

Introduction. Spontaneous nipple discharge is the third most common reason for presentation to a symptomatic breast clinic. Benign and malignant causes of spontaneous nipple discharge continue to be difficult to distinguish. We analyse our experience of duct excisions for spontaneous nipple discharge to try to identify features that raise suspicion of breast cancer and to identify features indicative of benign disease that would be suitable for nonoperative management.Methods. Details of one hundred and ninety-four patients who underwent duct excision for spontaneous nipple discharge between 1995 and 2005 were analysed.Results. Malignant disease was identified in 11 (5.7%) patients, 4 invasive and 7 insitu, which was 10.2% of those presenting with bloodstained discharge. All patients with malignant disease had bloodstained discharge. Discharge due to malignant disease was more likely to be bloodstained than that due to benign causes (Fisher's exact test, 2-tailedPvalue = 0.00134).Conclusion. Our findings do not support a policy of conservative management of spontaneous bloodstained nipple discharge. Cases of demonstrable spontaneous bloodstained nipple discharge should undergo duct excision to prevent malignant lesions being missed.

scholarly journals Nipple Discharge The Diagnostic Value of Testing for Occult Blood

1982 ◽  
Vol 196 (6) ◽  
pp. 651-655 ◽  
Author(s):  
MURID A. CHAUDARY ◽  
ROSEMARY R. MILLIS ◽  
GERALD C. DAVIES ◽  
JOHN L. HAYWARD
Keyword(s):  
Nipple Discharge ◽  
Occult Blood ◽  
Diagnostic Value

scholarly journals The Diagnostic Value of PET/CT in Breast Cancer Recurrence and Metastases

2017 ◽  
Vol 15 (2) ◽  
pp. 37-51
Author(s):  
Taalab, Kh. ◽  
Abutaleb, S ◽  
Moftah, G ◽  
Abdel-Mutaleb, G ◽  
Abdl-Mawla, A
Keyword(s):  
Breast Cancer ◽  
Cancer Recurrence ◽  
Diagnostic Value ◽  
Breast Cancer Recurrence ◽  
Pet Ct

scholarly journals Identification of differentially methylated genes as diagnostic and prognostic biomarkers of breast cancer

2021 ◽  
Vol 19 (1) ◽  
Author(s):  
Xiao-hong Mao ◽  
Qiang Ye ◽  
Guo-bing Zhang ◽  
Jin-ying Jiang ◽  
Hong-ying Zhao ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Cancer Diagnosis ◽  
High Sensitivity ◽  
Breast Cancer Diagnosis ◽  
Diagnostic Value ◽  
Methylation Pattern ◽  
Clinical Value ◽  
Roc Curve Analysis ◽  
Differentially Methylated Genes ◽  
Sensitivity Specificity

Abstract Background Aberrant DNA methylation is significantly associated with breast cancer. Methods In this study, we aimed to determine novel methylation biomarkers using a bioinformatics analysis approach that could have clinical value for breast cancer diagnosis and prognosis. Firstly, differentially methylated DNA patterns were detected in breast cancer samples by comparing publicly available datasets (GSE72245 and GSE88883). Methylation levels in 7 selected methylation biomarkers were also estimated using the online tool UALCAN. Next, we evaluated the diagnostic value of these selected biomarkers in two independent cohorts, as well as in two mixed cohorts, through ROC curve analysis. Finally, prognostic value of the selected methylation biomarkers was evaluated breast cancer by the Kaplan-Meier plot analysis. Results In this study, a total of 23 significant differentially methylated sites, corresponding to 9 different genes, were identified in breast cancer datasets. Among the 9 identified genes, ADCY4, CPXM1, DNM3, GNG4, MAST1, mir129-2, PRDM14, and ZNF177 were hypermethylated. Importantly, individual value of each selected methylation gene was greater than 0.9, whereas predictive value for all genes combined was 0.9998. We also found the AUC for the combined signature of 7 genes (ADCY4, CPXM1, DNM3, GNG4, MAST1, PRDM14, ZNF177) was 0.9998 [95% CI 0.9994–1], and the AUC for the combined signature of 3 genes (MAST1, PRDM14, and ZNF177) was 0.9991 [95% CI 0.9976–1]. Results from additional validation analyses showed that MAST1, PRDM14, and ZNF177 had high sensitivity, specificity, and accuracy for breast cancer diagnosis. Lastly, patient survival analysis revealed that high expression of ADCY4, CPXM1, DNM3, PRDM14, PRKCB, and ZNF177 were significantly associated with better overall survival. Conclusions Methylation pattern of MAST1, PRDM14, and ZNF177 may represent new diagnostic biomarkers for breast cancer, while methylation of ADCY4, CPXM1, DNM3, PRDM14, PRKCB, and ZNF177 may hold prognostic potential for breast cancer.

scholarly journals Integrative transcriptome data mining for identification of core lncRNAs in breast cancer

PeerJ ◽  
2019 ◽  
Vol 7 ◽  
pp. e7821 ◽  
Author(s):  
Xiaoming Zhang ◽  
Jing Zhuang ◽  
Lijuan Liu ◽  
Zhengguo He ◽  
Cun Liu ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Gene Expression ◽  
Prognostic Value ◽  
Early Stage ◽  
Expression Profiles ◽  
Diagnostic Value ◽  
The Cancer Genome Atlas ◽  
Functional Enrichment ◽  
Differentially Expressed ◽  
Data Set

Background Cumulative evidence suggests that long non-coding RNAs (lncRNAs) play an important role in tumorigenesis. This study aims to identify lncRNAs that can serve as new biomarkers for breast cancer diagnosis or screening. Methods First, the linear fitting method was used to identify differentially expressed genes from the breast cancer RNA expression profiles in The Cancer Genome Atlas (TCGA). Next, the diagnostic value of all differentially expressed lncRNAs was evaluated using a receiver operating characteristic (ROC) curve. Then, the top ten lncRNAs with the highest diagnostic value were selected as core genes for clinical characteristics and prognosis analysis. Furthermore, core lncRNA-mRNA co-expression networks based on weighted gene co-expression network analysis (WGCNA) were constructed, and functional enrichment analysis was performed using the Database for Annotation, Visualization and Integrated Discovery (DAVID). The differential expression level and diagnostic value of core lncRNAs were further evaluated by using independent data set from Gene Expression Omnibus (GEO). Finally, the expression status and prognostic value of core lncRNAs in various tumors were analyzed based on Gene Expression Profiling Interactive Analysis (GEPIA). Results Seven core lncRNAs (LINC00478, PGM5-AS1, AL035610.1, MIR143HG, RP11-175K6.1, AC005550.4, and MIR497HG) have good single-factor diagnostic value for breast cancer. AC093850.2 has a prognostic value for breast cancer. AC005550.4 and MIR497HG can better distinguish breast cancer patients in early-stage from the advanced-stage. Low expression of MAGI2-AS3, LINC00478, AL035610.1, MIR143HG, and MIR145 may be associated with lymph node metastasis in breast cancer. Conclusion Our study provides candidate biomarkers for the diagnosis and prognosis of breast cancer, as well as a bioinformatics basis for the further elucidation of the molecular pathological mechanism of breast cancer.

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