Correlation of genomic analysis by MyAML with chemotherapy drug sensitivity.

2015 ◽  
Vol 33 (15_suppl) ◽  
pp. 7080-7080
Author(s):  
Pamela S. Becker ◽  
Michael W. Schmitt ◽  
Lawrence A. Loeb ◽  
Weiyi Gu ◽  
Qi Wei ◽  
...  
2014 ◽  
Author(s):  
TABREZ A. MOHAMMAD ◽  
Aparna Gorthi ◽  
Andrew Robles ◽  
Xavier Bernard ◽  
Tzu-hung Hsiao ◽  
...  

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Ciara Tierney ◽  
Despina Bazou ◽  
Muntasir M. Majumder ◽  
Pekka Anttila ◽  
Raija Silvennoinen ◽  
...  

AbstractWith the introduction of novel therapeutic agents, survival in Multiple Myeloma (MM) has increased in recent years. However, drug-resistant clones inevitably arise and lead to disease progression and death. The current International Myeloma Working Group response criteria are broad and make it difficult to clearly designate resistant and responsive patients thereby hampering proteo-genomic analysis for informative biomarkers for sensitivity. In this proof-of-concept study we addressed these challenges by combining an ex-vivo drug sensitivity testing platform with state-of-the-art proteomics analysis. 35 CD138-purified MM samples were taken from patients with newly diagnosed or relapsed MM and exposed to therapeutic agents from five therapeutic drug classes including Bortezomib, Quizinostat, Lenalidomide, Navitoclax and PF-04691502. Comparative proteomic analysis using liquid chromatography-mass spectrometry objectively determined the most and least sensitive patient groups. Using this approach several proteins of biological significance were identified in each drug class. In three of the five classes focal adhesion-related proteins predicted low sensitivity, suggesting that targeting this pathway could modulate cell adhesion mediated drug resistance. Using Receiver Operating Characteristic curve analysis, strong predictive power for the specificity and sensitivity of these potential biomarkers was identified. This approach has the potential to yield predictive theranostic protein panels that can inform therapeutic decision making.


2020 ◽  
Vol 121 (5-6) ◽  
pp. 3256-3265 ◽  
Author(s):  
Shihong Ma ◽  
Dan Liu ◽  
Wenhua Tan ◽  
Botao Du ◽  
Wei Liu ◽  
...  

2018 ◽  
Vol 36 (15_suppl) ◽  
pp. e23505-e23505
Author(s):  
Qianrong Wang ◽  
Xiaowen Wang ◽  
Lei Wen ◽  
Jing Zhang ◽  
Jingyue Yang ◽  
...  

2002 ◽  
Vol 69 ◽  
pp. 59-72 ◽  
Author(s):  
Kurt Drickamer ◽  
Andrew J. Fadden

Many biological effects of complex carbohydrates are mediated by lectins that contain discrete carbohydrate-recognition domains. At least seven structurally distinct families of carbohydrate-recognition domains are found in lectins that are involved in intracellular trafficking, cell adhesion, cell–cell signalling, glycoprotein turnover and innate immunity. Genome-wide analysis of potential carbohydrate-binding domains is now possible. Two classes of intracellular lectins involved in glycoprotein trafficking are present in yeast, model invertebrates and vertebrates, and two other classes are present in vertebrates only. At the cell surface, calcium-dependent (C-type) lectins and galectins are found in model invertebrates and vertebrates, but not in yeast; immunoglobulin superfamily (I-type) lectins are only found in vertebrates. The evolutionary appearance of different classes of sugar-binding protein modules parallels a development towards more complex oligosaccharides that provide increased opportunities for specific recognition phenomena. An overall picture of the lectins present in humans can now be proposed. Based on our knowledge of the structures of several of the C-type carbohydrate-recognition domains, it is possible to suggest ligand-binding activity that may be associated with novel C-type lectin-like domains identified in a systematic screen of the human genome. Further analysis of the sequences of proteins containing these domains can be used as a basis for proposing potential biological functions.


2013 ◽  
Author(s):  
Symeon Tournis ◽  
Ioannis Stathopoulos ◽  
Kalliopi Lampropoulou-Adamidou ◽  
Theodora Koromila ◽  
Nikolaos Chatzistamatas ◽  
...  

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