ROTTERDAM, Netherlands and SAN DIEGO, June 23, 2020 /PRNewswire/ -- Last week, SkylineDx signed the 10th collaboration agreement with an academic partner for research under the extensive Falcon R&D Program to further validate both melanoma (skin cancer) tests. The 10 clinical centers represent 6 countries on 3 continents with data on over 3,500 cutaneous melanoma patients. The data generated will be used in the validation of the Merlin and Peregrine assay. The Merlin assay has been developed to predict a patient's risk of having metastasis in the sentinel lymph node. If a patient is identified as low-risk, the surgery that removes the sentinel lymph node can be safely avoided. The Merlin assay is developed on a US patient dataset[2] and validated in a European dataset[3]. The group of patients without metastasis in their sentinel lymph nodes, are currently considered low risk, although a significant number of patients will see their melanoma returning within 5 years. The Peregrine assay has been developed to identify patients at high risk of disease recurrence within this group of patients now considered low-risk, so treatment options can be discussed[4-5].
"I am very pleased that we are continuing our research with global partners for retrospective validation studies. Even more clinical groups have expressed interest to collaborate and are likely to be added in the near future to this research initiative. Processing of the biobanked samples is in full swing and we expect to have all the results for analyses by the end of 2020. The peer reviewed publication will follow shortly in 2021," explains Dharminder Chahal, CEO SkylineDx.
About Merlin & Peregrine
Both assays are using the CP-GEP model, a powerful algorithm that calculates the risk of metastasis in a patient's sentinel lymph nodes (predictive use) and the risk of the melanoma returning (prognostic use). The model is able to calculate risk on an individual basis through a combination analysis of 8 genes from the patient's primary tumor, the tumor thickness and the patient's age. The model has been previously published in JCO Precision Oncology[2]. The predictive use of the CP-GEP model is the main focus of the Merlin Study Initiative. The prognostic use of the CP-GEP model is the main focus of the Peregrine Study Initiative. Both are developed under the wings of the Falcon R&D Program. More information on www.falconprogram.com.
About SkylineDx
SkylineDx is a biotechnology company, mainly focused on research & development of molecular diagnostics in oncology. The company is headquartered in Rotterdam (the Netherlands) and complemented with a field medical and scientific affairs team in the US and a CAP/CLIA certified laboratory in San Diego (California). SkylineDx uses its expertise to bridge the gap between academically discovered gene expression signatures and commercially available diagnostic products with high clinical utility, assisting healthcare professionals in accurately determining the type or status of disease or predict a patient's response to treatment. Based on test results, healthcare professionals can tailor the treatment approach to the individual patient. To learn more, please visit www.skylinedx.com.
Footnotes
1 Link to this press release on website SkylineDx (click here)
2 Bellomo et al., 2020. Model combining tumor molecular and clinicopathologic risk factors predicts sentinel lymph node metastasis in primary cutaneous melanoma. JCO Precis Oncol 4:319-334 (click here)
3 Mulder & Dwarkasing et al., 2019. Validation of a clinicopathological and gene expression profile (CP-GEP) model for sentinel lymph node metastasis in primary cutaneous melanoma. Annals of Oncology30:2019(issue suppl 5; mdz255.014). Click here.
4 Eggermont et al., 2020. Using a clinicopathologic and gene expression model to identify melanoma patients at high risk for disease relapse. J Clin Oncol 38:2020(suppl; abstr 10068). Click here.
5 Wever et al., 2020. Identification of stage IIA melanoma patients at high risk for disease relapse using a clinicopathologic and gene expression model. J Clin Oncol 38:2020(suppl; abstr e22088). Click here.
