Melanoma risk prediction of nodal metastasis and long-term survival outcome by CP-GEP model in a U.S. cohort

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Mar 08, 2024, 11:05 ET

ROTTERDAM, The Netherlands and SAN DIEGO, March 8, 2024 /PRNewswire/ -- SkylineDx, an innovative molecular diagnostics company, announces the forthcoming presentation of an impactful poster by Dr. Yu, from University Hospital Cleveland Medical Center, at the upcoming AAD Annual Meeting in San Diego. The abstract concludes that the CP-GEP assay improved risk stratification for nodal metastasis and disease recurrence in patients with cutaneous melanoma [1].

Cutaneous melanoma patients diagnosed over a period of 10 years at University Hospital Cleveland Medical Center undergoing a surgical procedure to determine metastatic spread to their lymph nodes, were analyzed with the non-invasive CP-GEP assay marketed by SkylineDx as Merlin test. Merlin classified these patients as either at low risk or high risk for developing nodal metastasis and disease recurrence. Out of 176 patients, Merlin identified 66 patients as low risk. These patients could have forgone the surgical procedure due to their low risk for having metastasis in the sentinel lymph nodes, equaling reducing the surgery rate by 37.5%. Furthermore, the Merlin low-risk patients have a significant better long-term survival outcome compared to the Merlin high-risk group, 93.6% versus 79.4% for Recurrence Free Survival and 98% versus 91.4% for Melanoma Specific Survival, respectively.

The analysis unveiled Merlin test's pivotal role in effectively stratifying CM patients based on their risk of disease recurrence. The poster will be presented on March 9, 8:50AM at AAD (San Diego Convention Center, Upper Level, Sails Pavilion, Poster Center 20).

SkylineDx's Chief Scientific Officer, Jvalini Dwarkasing comments: "The study's results confirm that in this institute, the CP-GEP model has potential in optimizing patient management strategies. Recurrence events may be more effectively captured by this test as compared to current standard of care."

About CP-GEP

CP-GEP is a non-invasive prediction model for cutaneous melanoma patients that combines clinicopathologic (CP) variables with gene expression profiling (GEP). This model is able to identify cutaneous melanoma patients at low-risk for nodal metastasis who may forgo the sentinel lymph node biopsy (SLNB) procedure. The CP-GEP model was developed by Mayo Clinic and SkylineDx BV and it has been clinically validated in multiple studies More information (including references) may be obtained at www.falconprogram.com. The test has been launched in the United States and Europe as Merlin test. SkylineDx collaborates with diagnostic service providers globally to bring this test to market and increase the access. In the United States, Tempus is commercializing Tempus Merlin test.

Quest Diagnostics launched their own LDT version of the CP-GEP model in the United States, under the brand name MelaNodal Predict™.

About SkylineDx

SkylineDx is a biotechnology company focused on research & development of molecular diagnostics in oncology and inflammatory diseases. 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 predicting a patient's response to treatment. Based on test results, healthcare professionals can tailor the treatment approach to the individual patient. SkylineDx is headquartered in Rotterdam. the Netherlands, complemented by a U.S. base of operations and a CAP/CLIA certified laboratory in San Diego California, USA. To learn more about SkylineDx, please visit www.skylinedx.com.

Footnotes

1. Hill et al. Primary cutaneous melanoma patients stratified by the Merlin assay (CP-GEP): risk of nodal metastasis and long-term survival outcome in a U.S. cohort. Abstract selected for poster presentation at AAD Annual Meeting 2024. Abstract AAD2024 Hill and Yu.pdf (falconprogram.com)

SOURCE SkylineDx