2 resultados para cell cycle arrest
em QSpace: Queen's University - Canada
Resumo:
Vascular smooth muscle cell migration is a significant contributor to many aspects of heart disease, and specifically atherosclerosis. Tissue damage in the arteries can result in the formation of a fatty streak. Smooth muscle cells (SMC) can then migrate to this site to form a fibrous cap, stabilizing the fatty plaque. Since cardiovascular disease is the leading cause of death in developed countries, this function of SMC is an essential area of study. The formation of lamellipodia and circular dorsal ruffles were studied in this project as indicators that cell migration is occurring. The roles of the proteins p53, Rac, caldesmon and PTEN were investigated with regards to these actin-based structures. The tumour suppressor p53 is often reported to cause apoptosis, senescence or cell cycle arrest when stress is placed on a cell, but has recently been shown to regulate cell migration as well. It was determined in this project that p53 could inhibit the formation of both lamellipodia and circular dorsal ruffles. It was also shown that this could occur directly through an inhibition of the GTPase Rac. Previous studies have shown that p53 can upregulate caldesmon, a protein which is known to bind to and stabilize actin filaments while inhibiting Arp2/3-mediated branching. It was confirmed that p53 could upregulate caldesmon, and that caldesmon could inhibit the formation of lamellipodia and circular dorsal ruffles. The phosphorylation of caldesmon by p21-associated kinase (PAK) or extracellular signal-related kinase (Erk) was shown to effectively reverse the ability of caldesmon to inhibit these structures. The role of phosphatase and tensin homologue deleted on chromosome 10 (PTEN) was also studied with regards to this signalling pathway. PTEN was shown to inhibit lamellipodia and circular dorsal ruffles through its lipid phosphatase activity. It was concluded that p53 can inhibit the formation of lamellipodia and circular dorsal ruffles in vascular SMC, and that this occurs through Rac, caldesmon and PTEN.
Resumo:
Breast cancer is the most frequently diagnosed cancer in women, accounting for over 25% of cancer diagnoses and 13% of cancer-related deaths in Canadian women. There are many types of therapies for treatment or management of breast cancer, with chemotherapy being one of the most widely used. Taxol (paclitaxel) is one of the most extensively used chemotherapeutic agents for treating cancers of the breast and numerous other sites. Taxol stabilizes microtubules during mitosis, causing the cell cycle to arrest until eventually the cell undergoes apoptosis. Although Taxol has had significant benefits in many patients, response rates range from only 25-69%, and over half of Taxol-treated patients eventually acquire resistance to the drug. Drug resistance remains one of the greatest barriers to effective cancer treatment, yet little has been discerned regarding resistance to Taxol, despite its widespread clinical use. Kinases are known to be heavily involved in cancer development and progression, and several kinases have been linked to resistance of Taxol and other chemotherapeutic agents. However, a systematic screen for kinases regulating Taxol resistance is lacking. Thus, in this study, a set of kinome-wide screens was conducted to interrogate the involvement of kinases in the Taxol response. Positive-selection and negative-selection CRISPR-Cas9 screens were conducted, whereby a pooled library of 5070 sgRNAs targeted 507 kinase-encoding genes in MCF-7 breast cancer cells that were Taxol-sensitive (WT) or Taxol-resistant (TxR) which were then treated with Taxol. Next generation sequencing (NGS) was performed on cells that survived Taxol treatment, allowing identification and quantitation of sgRNAs. STK38, Blk, FASTK and Nek3 stand out as potentially critical kinases for Taxol-induced apoptosis to occur. Furthermore, kinases CDKL1 and FRK may have a role in Taxol resistance. Further validation of these candidate kinases will provide novel pre-clinical data about potential predictive biomarkers or therapeutic targets for breast cancer patients in the future.