Great news, we have a new Mini-Review published in Frontiers Oncology entitled “Clinical Overview of MDM2/X-Targeted Therapies“, which is apart of the Research Topic Human tumor-derived p53 mutants: a growing family of oncoproteins
Here is a little snippet from the Abstract to wet your appetite!
MDM2 and MDMX are the primary negative regulators of p53, which under normal conditions maintain low intracellular levels of p53 by targeting it to the proteasome for rapid degradation and inhibiting its transcriptional activity. Both MDM2 and MDMX function as powerful oncogenes and are commonly over-expressed in some cancers, including sarcoma (~20%) and breast cancer (~15%).
In this overview, we will review the current MDM2- and MDMX-targeted therapies in development, focusing particularly on compounds that have entered into early phase clinical trials. We will highlight the challenges pertaining to predictive biomarkers for and toxicities associated with these compounds, as well as identify potential combinatorial strategies to enhance its anti-cancer efficacy.
The article is Open Access, which means its free for everyone and anyone to read and download!
You can view and download it directly here [Link]
Its no secrete that Funding for Science in Australia, and around the world (see refs below), is in decline. The result is lower and lower success rates. While we wait for the #NHMRC to release the outcomes for 2015, the word on the street is that we can expect only 10-12% of grants to be successful. In other words, for 90% of Australia’s researchers they are wasting ~3 months of the year for nothing. Consequently as the funding pool decreases, funds naturally flow towards ‘sure bet’ senior researchers. This means that this wasted time is felt the hardest by early- and mid- career researchers (#EMCRs) who cannot compete with the long CVs of their senior peers, and are seen as a potential risky investment. Below is a graph I put together from the 2013 data, which is the most up to date information currently at hand. This trend of funding more senior researchers is clearly seen in the massive increase in average age of the CIA (chief investigator) on project grants over the past 30 years. It used to peak around 40 years, which perfectly aligned with the drop off in fellowships. So there was a very clear and clean transition from Post-Doctoral Funding for those that wanted to transition to a team leader role. However now, the average age has shifted to >50 years. This has created a significant 10-15 year ‘Funding Hole’ for EMCRs, where there are very limited number of fellowships on offer, and little to no chance of securing a project grant. While there has been a lot of talk about this black box, no solution or action has been taken to stem the loss of young, bright and talented researchers being forced out of research. Without action soon, we run the real risk that there will be no succession plan, and Australia’s ability to remain internationally competitive will be set back decades.
Great News, we have a new review article that has just been published online today in Inside the Cell!
Its Open Access, so that means its free for everyone to read!
During mitotic exit, phosphatases reverse thousands of phosphorylation events in a specific temporal order to ensure that cell division occurs correctly. This review explores how the physicochemical properties of the phosphosite and surrounding amino acids affect interactions with phosphatase/s and help determine the dephosphorylation of individual phosphorylation sites during mitotic exit.
The Full Reference and link for the Article can be found below:
Samuel Rogers, Rachael McCloy, D Neil Watkins and Andrew Burgess Mechanisms regulating phosphatase specificity and the removal of individual phosphorylation sites during mitotic exit Inside the Cell [Link]
Great news we are currently looking for a new honours student for 2016.
The title of the project is “Developing novel biosensors to monitor DNA damage in cancer cells”.
Its a very exciting new project incorporating cutting edge microscopy and fluorescent biosensors.
If you think you have what it takes and are interested please feel free contact myself, or UNSW SoMS.
For more information on the UNSW honours program please visit: http://medicalsciences.med.unsw.edu.au/students/soms-honours/
Below is an example of the images that will be created during the project.
I often get asked how to uses Thresholds to measure things in Image J.
Below are some of the Basic Steps for using Thresholds:
- Open your image and duplicate it (Image>Duplicate)
- On the duplicate go to Image>Adjust>Threshold
- Play with the sliders until all of your cells are red.
- Click ‘Apply’
- You should now have a ‘binary’ black and white image
- Now go to menu Process>Binary and select ‘fill holes’
- You may also want to select erode, dilate, open or close to optimise the binary image so that you have nice solid filling of your cells.
- Now go to menu Analyse>Set Measurements. Select all the things you want to measure.
- Critical steps: make sure that you select your original image (not the binary) in the ‘Redirect to:’ pull down Menu
- Also make sure the ‘Limit to threshold’ checkbox is ticked and also tick the ‘Add to overlay’ and ‘Display label’.
- Click ok to close the ‘Set Measurements’ box.
- Now go to Analyse>Analyse Particles
- Here you will need to play around with the size and circularity settings (bit of trial and error) in order to get accurate identification of your cells or ROIs. I suggest making duplicates before you start so that you can quickly try different things to see which one works best.
- Make sure you have the Display results tick box selected.
- Once you click ok you should have a the measurements box appear with all your measurements for each cell.
- You can copy and paste these into Excel or what ever program you like to use.
- Go get a coffee and cake you deserve it!
Here is a very simple guide for determining the level of fluorescence in a given region (e.g nucleus)
- Select the cell of interest using any of the drawing/selection tools (i.e. rectangle, circle, polygon or freeform)
- From the Analyze menu select “set measurements”. Make sure you have AREA, INTEGRATED DENSITY and MEAN GRAY VALUE selected (the rest can be ignored).
- Now select “Measure” from the analyze menu or hit cmd+m (apple). You should now see a popup box with a stack of values for that first cell.
- Now go and select a region next to your cell that has no fluroence, this will be your background.
NB: the size is not important. If you want to be super accurate here take 3+ selections from around the cell.
- Repeat this step for the other cells in the field of view that you want to measure.
- Once you have finished, select all the data in the Results window, and copy (cmd+c) and paste (cmd+v) into a new excel worksheet (or similar program)
- Use this formula to calculate the corrected total cell fluorescence (CTCF).
NB: You can use excel to perform this calculation for you.
CTCF = Integrated Density – (Area of selected cell X Mean fluorescence of background readings)
- Make a graph and your done. Notice that in this example that the rounded up mitotic cell appears to have a much higher level of staining, but this is actually due to its smaller size, which concentrates the staining in a smaller space. So if you just used the raw integrated density you would have data suggesting that the flattened cell has less staining then the rounded up one, when in reality they have a similar level of fluorescence.
How to Cite this if you wold like to:
We have used this method in these papers:
McCloy, R. A., Rogers, S., Caldon, C. E., Lorca, T., Castro, A., and Burgess, A. (2014) Partial inhibition of Cdk1 in G 2 phase overrides the SAC and decouples mitotic events. Cell Cycle 13, 1400–1412 [Link]
Burgess A, Vigneron S, Brioudes E, Labbé J-C, Lorca T & Castro A (2010) Loss of human Greatwall results in G2 arrest and multiple mitotic defects due to deregulation of the cyclin B-Cdc2/PP2A balance. Proc Natl Acad Sci USA 107: 12564–12569
But you can also find a similar method published here:
Gavet O & Pines J (2010) Progressive activation of CyclinB1-Cdk1 coordinates entry to mitosis. Dev Cell 18: 533-543
Potapova TA, Sivakumar S, Flynn JN, Li R & Gorbsky GJ (2011) Mitotic progression becomes irreversible in prometaphase and collapses when Wee1 and Cdc25 are inhibited. Mol Biol Cell 22: 1191–1206
And my apologies to any others that I have not mentioned.
Great news our recent paper “Global phosphoproteomic mapping of early mitotic exit in human cells identifies novel substrate dephosphorylation motifs., Molecular & Cellular Proteomics, 2015 (DOI: 10.3410/f.725545508.793507630), has been recommended in F1000Prime as being of special significance in its field by F1000 Faculty Member Angus Nairn.
Really glad to see that all our hard work and research is being found useful for the research community.