Down-regulation of uPAR and Cathepsin B retards cofilin dephosphorylation

Gondi, Christopher S.; Kandhukuri, Neelima; Kondraganti, Shakuntala; Gujrati, Meena; Olivero, William C.; Dinh, Dzung H.; Rao, Jasti S.

doi:10.3892/ijo.28.3.633

Cited by 18 publications

(20 citation statements)

References 27 publications

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“…Direct proof of this mechanism in vivo is lacking in the literature. A second clue to cathepsin involvement in tumor cell migration comes from a study of cathepsin B knockdown in glioma cells [25]. Inhibition of glioma cell migration with cathepsin B down-regulation correlated with altered cofilin phosphorylation.…”

Section: Discussionmentioning

confidence: 99%

Cathepsin L increases invasion and migration of B16 melanoma

Yang

Cox

2007

Cancer Cell Int

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Background: Most cancers express elevated protease levels which contribute to certain aspects of tumor behavior such as growth, metastatic spread, and angiogenesis. Elevation of the cathepsins of the cysteine protease family correlates with increased invasion of tumor cells. Cysteine proteases such as cathepsins B, H and L type participate in tumor cell invasion as extracellular proteases, yet are enzymes whose exact roles in metastasis are still being elucidated.

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Section: Discussionmentioning

confidence: 99%

Cathepsin L increases invasion and migration of B16 melanoma

Yang

Cox

2007

Cancer Cell Int

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“…Small interfering RNAs (siRNAs) are believed to be more potent inhibitors of gene expression with less toxicity (27). Our laboratory had already employed shRNA-based RNAi plasmid system for the downregulation of uPAR in prostate cancer (28), glioma (11, 29–33), and meningioma (34, 35). We have utilized a plasmid construct expressing the same small hairpin RNA (shRNA) to target uPAR.…”

Section: Therapeutic Rnai-mediated Strategies For Targeting the Upar mentioning

confidence: 99%

Therapeutic Potential of siRNA-mediated Targeting of Urokinase Plasminogen Activator, Its Receptor, and Matrix Metalloproteinases

Gondi

Rao

2008

Methods in Molecular Biology

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Summary Targeting proteases and their activators would retard the invasive ability of cancer cells and, has been shown to induce apoptosis in certain instances. Various methods have been developed to specifically target proteases molecules in an attempt to retard invasion and migration. Of these methods, RNA interference (RNAi) holds great therapeutic potential. RNAi technology is now being used to target specific molecules for use as potential anti-cancer agents. RNAi-mediated silencing is almost catalytic when compared to antisense. Of these targets, the uPAR-uPA system and MMPs holds great promise Targeting uPA/uPAR may provide additive or synergistic treatment benefits if used in combination with conventional therapeutics such as chemotherapy or radiation. Studies point to the fact that specifically targeting MMP-9 or MMP-2 singly or in combination with other proteases could have specific therapeutic implications in the treatment of cancer. In this review we discuss the therapeutic potential of siRNA-mediated targeting of uPAR-uPA system and MMPs as therapeutic agents for the treatment of cancer.

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“…45,46 The predicted edge between experimental drug 2-[formyl(hydroxy)amino]methyl-4-methylpentanoic acid (DB03683) and APAF1 was supported by their shared association with MMP9. 47 …”

Section: Resultsmentioning

confidence: 99%

OWL-NETS: Transforming OWL Representations for Improved Network Inference

et al. 2017

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Our knowledge of the biological mechanisms underlying complex human disease is largely incomplete. While Semantic Web technologies, such as the Web Ontology Language (OWL), provide powerful techniques for representing existing knowledge, well-established OWL reasoners are unable to account for missing or uncertain knowledge. The application of inductive inference methods, like machine learning and network inference are vital for extending our current knowledge. Therefore, robust methods which facilitate inductive inference on rich OWL-encoded knowledge are needed. Here, we propose OWL-NETS (NEtwork Transformation for Statistical learning), a novel computational method that reversibly abstracts OWL-encoded biomedical knowledge into a network representation tailored for network inference. Using several examples built with the Open Biomedical Ontologies, we show that OWL-NETS can leverage existing ontology-based knowledge representations and network inference methods to generate novel, biologically-relevant hypotheses. Further, the lossless transformation of OWL-NETS allows for seamless integration of inferred edges back into the original knowledge base, extending its coverage and completeness.

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Down-regulation of uPAR and Cathepsin B retards cofilin dephosphorylation

Cited by 18 publications

References 27 publications

Cathepsin L increases invasion and migration of B16 melanoma

Cathepsin L increases invasion and migration of B16 melanoma

Therapeutic Potential of siRNA-mediated Targeting of Urokinase Plasminogen Activator, Its Receptor, and Matrix Metalloproteinases

OWL-NETS: Transforming OWL Representations for Improved Network Inference

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