The 52K cathepsin-D of breast cancer: structure, regulation, function and clinical value

Author(s):  
Henri Rochefort ◽  
Patrick Augereau ◽  
Françoise Capony ◽  
Marcel Garcia ◽  
Vincent Cavailles ◽  
...  
Pharmaceutics ◽  
2021 ◽  
Vol 13 (6) ◽  
pp. 837
Author(s):  
Olja Mijanovic ◽  
Anastasiia I. Petushkova ◽  
Ana Brankovic ◽  
Boris Turk ◽  
Anna B. Solovieva ◽  
...  

Lysosomal proteases play a crucial role in maintaining cell homeostasis. Human cathepsin D manages protein turnover degrading misfolded and aggregated proteins and favors apoptosis in the case of proteostasis disruption. However, when cathepsin D regulation is affected, it can contribute to numerous disorders. The down-regulation of human cathepsin D is associated with neurodegenerative disorders, such as neuronal ceroid lipofuscinosis. On the other hand, its excessive levels outside lysosomes and the cell membrane lead to tumor growth, migration, invasion and angiogenesis. Therefore, targeting cathepsin D could provide significant diagnostic benefits and new avenues of therapy. Herein, we provide a brief overview of cathepsin D structure, regulation, function, and its role in the progression of many diseases and the therapeutic potentialities of natural and synthetic inhibitors and activators of this protease.


Cancers ◽  
2021 ◽  
Vol 13 (1) ◽  
pp. 147
Author(s):  
Leticia Díaz-Beltrán ◽  
Carmen González-Olmedo ◽  
Natalia Luque-Caro ◽  
Caridad Díaz ◽  
Ariadna Martín-Blázquez ◽  
...  

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.


Tumor Biology ◽  
2006 ◽  
Vol 27 (5) ◽  
pp. 252-260
Author(s):  
Gregor Westhof ◽  
Michael Olbrecht ◽  
Manfred Wolff ◽  
Sven Schiermeier ◽  
Ralf C. Zimmermann ◽  
...  

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 ◽  
...  

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.


2010 ◽  
Vol 9 (1) ◽  
pp. 23-30 ◽  
Author(s):  
Daniel E Abbott ◽  
Naira V Margaryan ◽  
Jacqueline Jeruss ◽  
Seema Khan ◽  
Virginia Kaklamani ◽  
...  

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

Tumor Biology ◽  
1996 ◽  
Vol 17 (5) ◽  
pp. 290-298 ◽  
Author(s):  
V. Cappelletti ◽  
L. Fioravanti ◽  
P. Miodini ◽  
G. Di Fronzo

2021 ◽  
Vol 19 (1) ◽  
Author(s):  
Xiao-hong Mao ◽  
Qiang Ye ◽  
Guo-bing Zhang ◽  
Jin-ying Jiang ◽  
Hong-ying Zhao ◽  
...  

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.


Diagnostics ◽  
2021 ◽  
Vol 11 (8) ◽  
pp. 1491
Author(s):  
Chunli Li ◽  
Jiandong Yin

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.


1995 ◽  
Vol 7 (2) ◽  
pp. 97-102
Author(s):  
Liangzhong Xu ◽  
Weiping Zhu ◽  
Taiming Zhang ◽  
Aiping Jing ◽  
Zhenzhou Shen

Sign in / Sign up

Export Citation Format

Share Document