The Where and the How
For the first time, researchers have simultaneously assessed both spatial and activation information for proteins in FFPE tissue samples
George Lee | | News
To establish a cancer’s metastatic potential – and therefore the patient’s prognosis – it’s important to determine the activation status of proteins such as Rac and Cdc42. Unfortunately, existing methods offer either spatial information or activation status (via pulldown assay), but not both. To combat this, a novel detection technique specifically and rapidly identifies activated Rac and Cdc42 in FFPE tissue samples (1).
How does it work? Researchers at Hokkaido University’s Institute for Chemical Reaction Design and Discovery (WPI-ICReDD) developed molecular probes that bind specifically to activated Rac and Cdc24, then used non-contact agitation technology to speed up the binding reaction in FFPE tissue samples without negatively affecting the specimens or the quality of the staining. This approach avoids the loss of positional and heterogenicity information that takes place in pulldown assays, allowing the WPI-ICReDD team to analyze activation patterns in 50 colon cancer cases.
The results indicated that protein activity was concentrated at tumor invasive fronts and strongly corresponded with characteristics highlighted in TNM classification. In 29 of 33 tissue microarray samples, Rac/Cdc42 cell activity was higher in tumor cells than in regular colon mucosa. Increased Rac/Cdc42 activity was correlated with later disease stage and additional clinicopathologic factors such as venous and lymphatic vessel invasion.
First author Masumi Tsuda said, “This technology is effective for breast cancer and brain tumors as well as colorectal cancer, and it promises to provide useful information for predicting lymph node metastasis and for the assessment of Rac inhibitor-based therapies in the future (2).” The researchers expect their methodology to be useful in other small GTPases such as Ras, hopefully leading to personalized prognoses and more effective treatments.
- M Tsuda et al., Sci Rep, 12, 1733 (2022). PMID: 35110666.
- Science Japan (2022). Available at: https://bit.ly/37DMQFq.