scholarly journals “To Be or Not to Be in a Good Shape”: Diagnostic and Clinical Value of Nuclear Shape Irregularities in Thyroid and Breast Cancer

2014 ◽  
pp. 101-121 ◽  
Author(s):  
Gianni Bussolati ◽  
Francesca Maletta ◽  
Sofia Asioli ◽  
Laura Annaratone ◽  
Anna Sapino ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Nuclear Shape ◽  
Clinical Value ◽  
Good Shape

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.

Testing of Functional Integrity of p53 Protein in Primary Breast Cancer by a Rapid Quantitative p53-p21WAF1 Double Assay May Improve the Clinical Value of p53

Tumor Biology ◽  
2006 ◽  
Vol 27 (5) ◽  
pp. 252-260
Author(s):  
Gregor Westhof ◽  
Michael Olbrecht ◽  
Manfred Wolff ◽  
Sven Schiermeier ◽  
Ralf C. Zimmermann ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Primary Breast Cancer ◽  
P53 Protein ◽  
Clinical Value ◽  
Functional Integrity

scholarly journals Mapping of Genomic Vulnerabilities in the Post-Translational Ubiquitination, SUMOylation and Neddylation Machinery in Breast Cancer

Cancers ◽  
2021 ◽  
Vol 13 (4) ◽  
pp. 833
Author(s):  
Jesús Fuentes-Antrás ◽  
Ana Lucía Alcaraz-Sanabria ◽  
Esther Cabañas Morafraile ◽  
María del Mar Noblejas-López ◽  
Eva María Galán-Moya ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Drug Development ◽  
Gene Mutations ◽  
Complete Response ◽  
Breast Cancer Patients ◽  
Clinical Value ◽  
Luminal A ◽  
Genomic Alterations ◽  
Cancer Hallmarks ◽  
Worse Prognosis

The dysregulation of post-translational modifications (PTM) transversally impacts cancer hallmarks and constitutes an appealing vulnerability for drug development. In breast cancer there is growing preclinical evidence of the role of ubiquitin and ubiquitin-like SUMO and Nedd8 peptide conjugation to the proteome in tumorigenesis and drug resistance, particularly through their interplay with estrogen receptor signaling and DNA repair. Herein we explored genomic alterations in these processes using RNA-seq and mutation data from TCGA and METABRIC datasets, and analyzed them using a bioinformatic pipeline in search of those with prognostic and predictive capability which could qualify as subjects of drug research. Amplification of UBE2T, UBE2C, and BIRC5 conferred a worse prognosis in luminal A/B and basal-like tumors, luminal A/B tumors, and luminal A tumors, respectively. Higher UBE2T expression levels were predictive of a lower rate of pathological complete response in triple negative breast cancer patients following neoadjuvant chemotherapy, whereas UBE2C and BIRC5 expression was higher in luminal A patients with tumor relapse within 5 years of endocrine therapy or chemotherapy. The transcriptomic signatures of USP9X and USP7 gene mutations also conferred worse prognosis in luminal A, HER2-enriched, and basal-like tumors, and in luminal A tumors, respectively. In conclusion, we identified and characterized the clinical value of a group of genomic alterations in ubiquitination, SUMOylation, and neddylation enzymes, with potential for drug development in breast cancer.

The Clinical Value of Parasternal Sentinel Node Biopsy in Breast Cancer

2006 ◽  
Vol 13 (3) ◽  
pp. 321-326 ◽  
Author(s):  
Marjut Hannele Kristiina Leidenius ◽  
Leena Anneli Krogerus ◽  
Terttu Sinikka Toivonen ◽  
Esa Antero Leppänen ◽  
Karl Albert Johan von Smitten
Keyword(s):  
Breast Cancer ◽  
Sentinel Node ◽  
Sentinel Node Biopsy ◽  
Clinical Value ◽  
Node Biopsy

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 Radiomics Nomogram Based on Radiomics Score from Multiregional Diffusion-Weighted MRI and Clinical Factors for Evaluating HER-2 2+ Status of Breast Cancer

Diagnostics ◽  
2021 ◽  
Vol 11 (8) ◽  
pp. 1491
Author(s):  
Chunli Li ◽  
Jiandong Yin
Keyword(s):  
Breast Cancer ◽  
Characteristic Curve ◽  
Receiver Operator Characteristic Curve ◽  
Clinical Factors ◽  
Clinical Value ◽  
Logistic Analysis ◽  
Diffusion Weighted ◽  
Apparent Diffusion ◽  
Her 2 ◽  
Multivariate Logistic Analysis

This study aimed to establish and validate a radiomics nomogram using the radiomics score (rad-score) based on multiregional diffusion-weighted imaging (DWI) and apparent diffusion coefficient (ADC) features combined with clinical factors for evaluating HER-2 2+ status of breast cancer. A total of 223 patients were retrospectively included. Radiomic features were extracted from multiregional DWI and ADC images. Based on the intratumoral, peritumoral, and combined regions, three rad-scores were calculated using the logistic regression model. Independent parameters were selected among clinical factors and combined rad-score (com-rad-score) using multivariate logistic analysis and used to construct a radiomics nomogram. The performance of the nomogram was evaluated using calibration, discrimination, and clinical usefulness. The areas under the receiver operator characteristic curve (AUCs) of intratumoral and peritumoral rad-scores were 0.824/0.763 and 0.794/0.731 in the training and validation cohorts, respectively. Com-rad-score achieved the highest AUC (0.860/0.790) among three rad-scores. ER status and com-rad-score were selected to establish the nomogram, which yielded good discrimination (AUC: 0.883/0.848) and calibration. Decision curve analysis demonstrated the clinical value of the nomogram in the validation cohort. In conclusion, radiomics nomogram, including clinical factors and com-rad-score, showed favorable performance for evaluating HER-2 2+ status in breast cancer.

Qualitative Diagnosis of Solid Breast Mass by Blood Flow in Solid Breast Mass

2021 ◽  
Vol 11 (7) ◽  
pp. 1887-1894
Author(s):  
Chen Cheng ◽  
Chunhong Hu ◽  
Shengli Zhou ◽  
Hongyan Zhao ◽  
Ming Yu
Keyword(s):  
Breast Cancer ◽  
Blood Flow ◽  
High Speed ◽  
Malignant Tumors ◽  
Resistance Index ◽  
The Body ◽  
Breast Mass ◽  
Physical And Mental Health ◽  
Clinical Value ◽  
Hemodynamic Information

Breast cancer is one of the most common malignant tumors that seriously endangers women’s physical and mental health and even life-threatening. With the increasing incidence of breast malignant tumors year by year, people are increasingly concerned about the health of female breasts. However, due to the lack of primary prevention methods for breast cancer, the key to improving the cure rate of breast cancer and reducing mortality is early detection, early diagnosis, and early treatment. Hemodynamics embodies the characteristics and laws of the movement of blood and its components in the body. Clinically, monitoring of hemodynamic indicators is usually used to reveal the physiological or pathological changes of the body and understand the development process of the disease. The blood flow in the tumor tissue is high-speed and high-impedance. CDFI can show the distribution of blood flow in the mass. The highest peak velocity (PSV), resistance index (RI) and pulsatility index (PI) of systolic phase can be measured by sampling. This study use contrast-enhanced ultrasound (CEUS) combined with color energy Doppler flow imaging (CDFI) to explore the hemodynamic information of the main blood supply arteries and masses of the breast, analyze the abnormal hemodynamic information of tumors and surrounding tissues, and explore the blood in the breast, the clinical value of hydrodynamics in the qualitative diagnosis of breast masses.

The functional role of oncogenic lncRNA BCAR4 for cancer outcome

2021 ◽  
Vol 27 ◽  
Author(s):  
Bei Wang ◽  
Wen Xu ◽  
Yuxuan Cai ◽  
Kai Liu ◽  
Jiacheng Wu ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Gastric Cancer ◽  
Molecular Mechanisms ◽  
Clinical Value ◽  
Non Coding Rna ◽  
Entry Points ◽  
Multiple Processes ◽  
Cancer Outcome ◽  
Long Non Coding Rna

Background: Long non-coding RNA (lncRNA) breast cancer anti-estrogen resistance 4 (BCAR4) is a characterized oncogenic lncRNA in different cancers. This review is dedicated to summarize various molecular mechanisms of BCAR4 and demonstrate that the biological functions exerted by BCAR4 are good entry points for therapy. Methods: The molecular mechanism of BCAR4 acting on tumors is summarized by reviewing PubMed. Results: The expression of lncRNA BCAR4 is abnormally increased in all kinds of tumors, including colorectal cancer, prostate cancer, bladder cancer, gastric cancer, chondrosarcoma, glioma, breast cancer, glioma, gastric cancer, liver cancer, cervical cancer, lung cancer, etc. Besides, BCAR4 mediates multiple processes involved in carcinogenesis, including proliferation, invasion, anti-apoptosis, migration. Conclusion: BCAR4 may show great clinical value in this direction as a therapeutic cancer target.

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