What is Tissue Microarray technology?
Tissue Microarray (TMA) technology is a relatively new investigative tool for harvesting small cylinders of tissue from a range of standard histological sections and arranging them on a on a single microscope glass slide in a grid-like manner. The arrays are subsequently treated with antibodies (proteins which specifically detect and bind to molecular targets of interest) that are complexed with a staining medium to determine the protein and molecular signatures of the underlying pathology of the tissue samples. This technique allows maximization of tissue resources by analysis of small core biopsies of blocks, rather than complete sections. Using this technology, a carefully planned array can be constructed with cases from pathology tissue block archives, such that a 20-year survival analysis can be performed on a cohort of hundreds patients, simultaneously using just a few micro-liters of antibody.
Using TMA technology investigators are beginning to unveil the underlying mechanisms by which healthy tissues are transformed into malignancies and are gaining unparalleled insight as to which patient populations are most likely to respond to a given treatment regimen. TMAs hold tremendous promise for improved accuracy in prognosis, therapy planning and drug discovery.
What does a Tissue Microarray slide look like?
How long does the scanner take to scan in a whole slide?
What is the average number of tissue slices per slide?
Was an automatic slide feeder used?
Why were there not as many work units for the Help Defeat Cancer project?
How can I find the latest status on the Help Defeat Cancer Project?
Is there a podcast for the Help Defeat Cancer Project?
Screen saver/Graphics: What was the large circle on the Help Defeat Cancer graphic, and what did the Distance and Filter mask graphics mean?
The round image at the left side of the application window showed the image of a slice of tissue sample, which the members computer processed. The tissues may have been stained with certain compounds to better highlight certain features, such as the nuclei of cells. The square "Filter Mask" in the upper right showed how one of many of the mathematical filters responded to a particular square subsection outlined in the tissue image at the left. The shading showed that particular filter's response value for each point ranging from dark (low response) to light (high response). You could see some correspondence between the outlined area and the Filter Mask. The shading in the "Distance Mask" at the lower right showed how the particular filter's response is relevant to a mathematical pattern being developed over all of the filters. This is a highly oversimplified description of what was displayed and computed. But, it does let you see a glimpse of the computation that was performed.