Physicians must determine whether patients with cystic tumors of the pancreas will be operated on or receive further imaging and monitoring. Biomarkers that can inform the physician of the state of progression of the tumor, as well as predict the neoplastic nature of the cyst, would be valuable for determining treatment course. Specifically, the authors would like to reduce the number of patients undergoing unneeded surgical resections, as this procedure has high morbidity. Market size can be inferred by the fact that up to 25% of the US population over the age of 70 likely harbors pancreatic cysts, which are rarely cancerous. Molecular diagnostics is expected to be a $45B industry by 2020, with the largest market share in the PCR field (27%) and the fastest growth in Oncology (CAGR 17%).
Johns Hopkins researchers have developed a technology that capitalizes on the predisposition of cancer cells to contain critically short telomeres that tend to fuse end-to-end. Using a nested qPCR strategy, the researchers are able to detect the presence of these fused telomeres in the cyst fluid of patients with pancreatic cysts. The presence of cysts predicts with 100% specificity cancerous vs. non-cancerous samples, and is detected in 61% of cancer samples. In addition, telomere fusions could predict cancer severity: fusions were significantly more likely to be detected in cases of high grade dysplasia (27%) or associated invasive cancer (43%), compared with intermediate-grade dysplasia (15%) or low-grade dysplasia (0%).
This technique has been validated in 91 patients who underwent pancreatic surgical resection.Publicationhttps://doi.org/10.1016/j.jmoldx.2017.09.006