scholarly journals Antibodies as leading tools to unlock the therapeutic potential in human disease

2016 ◽  
Vol 270 (1) ◽  
pp. 5-7 ◽  
Author(s):  
Flavius Martin
Keyword(s):  
Human Disease ◽  
Therapeutic Potential

Proglucagon-Derived Peptides: Mechanisms of Action and Therapeutic Potential

Physiology ◽  
2005 ◽  
Vol 20 (5) ◽  
pp. 357-365 ◽  
Author(s):  
Elaine M Sinclair ◽  
Daniel J. Drucker
Keyword(s):  
Type 2 Diabetes ◽  
Human Disease ◽  
Clinical Relevance ◽  
Therapeutic Potential ◽  
Mechanisms Of Action ◽  
Receptor Antagonists ◽  
Glucagon Receptor ◽  
Receptor Agonists ◽  
Glucagon Like Peptide

Glucagon is used for the treatment of hypoglycemia, and glucagon receptor antagonists are under development for the treatment of type 2 diabetes. Moreover, glucagon-like peptide (GLP)-1 and GLP-2 receptor agonists appear to be promising therapies for the treatment of type 2 diabetes and intestinal disorders, respectively. This review discusses the physiological, pharmacological, and therapeutic actions of the proglucagon-derived peptides, with an emphasis on clinical relevance of the peptides for the treatment of human disease.

Multiple sclerosis following treatment with a cannabinoid receptor-1 antagonist

2004 ◽  
Vol 10 (3) ◽  
pp. 330-332 ◽  
Author(s):  
B W van Oosten ◽  
J Killestein ◽  
E MH Mathus-Vliegen ◽  
C H Polman
Keyword(s):  
Multiple Sclerosis ◽  
Animal Models ◽  
Receptor Antagonist ◽  
Human Disease ◽  
Cannabinoid Receptor ◽  
Therapeutic Potential ◽  
Laboratory Research ◽  
Cannabinoid Receptor 1 ◽  
Disease Pathogenesis

Laboratory research including animal models of human disease suggests that cannabinoids might have therapeutic potential in multiple sclerosis (MS). We have recently seen a 46-year-old woman who developed MS after starting treatment with a cannabino id recepto r antagonist for obesity. The occurrence of MS several months after starting a cannabinoid receptor antagonist suggests that the cannabino id system might indeed be relevant to disease pathogenesis in MS.

scholarly journals Therapeutic potential of alpha-1 antitrypsin in human disease

2018 ◽  
Vol 23 (3) ◽  
pp. 131-135 ◽  
Author(s):  
Minsun Kim ◽  
Qing Cai ◽  
Youngman Oh
Keyword(s):  
Human Disease ◽  
Therapeutic Potential ◽  
Alpha 1 Antitrypsin

scholarly journals Unravelling similarities and differences in the role of circular and linear PVT1 in cancer and human disease

2021 ◽  
Author(s):  
Debora Traversa ◽  
Giorgia Simonetti ◽  
Doron Tolomeo ◽  
Grazia Visci ◽  
Gemma Macchia ◽  
...  
Keyword(s):  
Human Disease ◽  
Therapeutic Potential ◽  
Cell Metabolism ◽  
Exon 2 ◽  
Functional Studies ◽  
Metabolism Regulation ◽  
Non Coding Rna ◽  
Apoptosis Inhibition ◽  
The Many

AbstractThe plasmacytoma variant translocation 1 (PVT1) is a long non-coding RNA gene involved in human disease, mainly in cancer onset/progression. Although widely analysed, its biological roles need to be further clarified. Notably, functional studies on PVT1 are complicated by the occurrence of multiple transcript variants, linear and circular, which generate technical issues in the experimental procedures used to evaluate its impact on human disease. Among the many PVT1 transcripts, the linear PVT1 (lncPVT1) and the circular hsa_circ_0001821 (circPVT1) are frequently reported to perform similar pathologic and pro-tumorigenic functions when overexpressed. The stimulation of cell proliferation, invasion and drug resistance, cell metabolism regulation, and apoptosis inhibition is controlled through multiple targets, including MYC, p21, STAT3, vimentin, cadherins, the PI3K/AKT, HK2, BCL2, and CASP3. However, some of this evidence may originate from an incorrect evaluation of these transcripts as two separate molecules, as they share the lncPVT1 exon-2 sequence. We here summarise lncPVT1/circPVT1 functions by mainly focusing on shared pathways, pointing out the potential bias that may exist when the biological role of each transcript is analysed. These considerations may improve the knowledge about lncPVT1/circPVT1 and their specific targets, which deserve further studies due to their diagnostic, prognostic, and therapeutic potential.

scholarly journals The therapeutic potential of RORγ modulators in the treatment of human disease

2012 ◽  
pp. 141
Author(s):  
Patrick Griffin ◽  
Mi Ra Chang ◽  
Goswami ◽  
Mercer
Keyword(s):  
Human Disease ◽  
Therapeutic Potential

scholarly journals A deep learning approach to identify new gene targets of a novel therapeutic for human splicing disorders

2020 ◽  
Author(s):  
Dadi Gao ◽  
Elisabetta Morini ◽  
Monica Salani ◽  
Aram J. Krauson ◽  
Ashok Ragavendran ◽  
...  
Keyword(s):  
Deep Learning ◽  
Human Disease ◽  
Regulatory Networks ◽  
Therapeutic Potential ◽  
Control Point ◽  
Mrna Splicing ◽  
Disease Genes ◽  
Learning Approach ◽  
Sequence Signatures

AbstractPre-mRNA splicing is a key control point in human gene expression. Disturbances in splicing due to mutation or aberrant splicing regulatory networks lead to dysregulated protein expression and contribute to a substantial fraction of human disease. Several classes of active and selective splicing modulator compounds have been recently identified, thus proving that pre-mRNA splicing is a viable target for therapy. We describe herein the identification of BPN-15477, a novel splicing modulator compound, that restores correct splicing of exon 20 in the Elongator complex protein 1 (ELP1) gene carrying the major IVS20+6T>C mutation responsible for familial dysautonomia. We then developed a machine learning approach to evaluate the therapeutic potential of BPN-15477 to correct splicing in other human genetic diseases. Using transcriptome sequencing from compound-treated fibroblast cells, we identified treatment responsive sequence signatures, the majority of which center at the 5’ splice site of exons whose inclusion or exclusion is modulated by SMC treatment. We then leveraged this model to identify 155 human disease genes that harbor ClinVar mutations predicted to alter pre-mRNA splicing as potential targets for BPN-15477 treatment. Using in vitro splicing assays, we validated representative predictions by demonstrating successful correction of splicing defects caused by mutations in genes responsible for cystic fibrosis (CFTR), cholesterol ester storage disease (LIPA), Lynch syndrome (MLH1) and familial frontotemporal dementia (MAPT). Our study shows that deep learning techniques can identify a complex set of sequence signatures and predict response to pharmacological modulation, strongly supporting the use of in silico approaches to expand the therapeutic potential of drugs that modulate splicing.

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