Independent Meta-Analysis Shows SkylineDx's Merlin CP-GEP Assay Accurately Stratifies Patients for Sentinel Lymph Node Biopsy Selection

• The independent meta-analysis assessed the overall predictive performance of the CP-GEP model, which demonstrated a high Sensitivity Rate (93%) and Negative Predictive Value (95%) across all stages, reinforcing its reliability and effectiveness as a clinical tool to guide decisions around SLNB.
• CP-GEP model is an effective deselection tool for SLNB, allowing clinicians to identify patients who can forgo the invasive surgical procedure and its potentials complications.
• Despite diversity among the studies, CP-GEP performed consistently in identifying those at low risk of sentinel lymph node metastasis.

ROTTERDAM, Netherlands and SAN DIEGO, July 8, 2025 /PRNewswire/ -- SkylineDx, an innovative diagnostics company specializing in the research and development of molecular diagnostics for oncology, inflammatory and infectious diseases, announced today an independent meta-analysis in Critical Reviews of Oncology/Hematology. The study demonstrates that SkylineDx's Merlin CP-GEP Assay accurately stratifies patients with cutaneous melanoma for optimal selection for sentinel lymph node biopsy (SLNB), an invasive surgical procedure with the potential for complications. Merlin is a genomic test to guide treatment decisions in early-stage melanoma.

SLNB is currently the gold standard procedure for patients with newly diagnosed melanoma, but it provides limited benefit for patients at low risk of sentinel node metastases. Identifying patients unlikely to benefit from SLNB is essential to avoiding unnecessary risks of the procedure and costs, which is why SkylineDx developed the Merlin Assay.

"Merlin CP-GEP provides valuable clinical information on a patient's risk of sentinel-node metastasis and should therefore be considered as part of current standards of care in patients with clinically node-negative cutaneous melanomas ≤4.0 mm in thickness," said Associated Professor, Chair of Melanoma Surgical Oncology at Melanoma Institute Australia and Principal Investigator Alexander C.J. van Akkooi, MD, PhD, FRACS. "The study showed that Merlin's CP-GEP model is an effective deselection tool for all T1-T3 patients, demonstrating its best performance in T2. In alignment with clinical guidelines, in practice, this subgroup is usually referred for surgery. Merlin was able to reduce the number of surgeries by 31% as these Merlin Low Risk patients had a risk of nodal metastasis of only 4%."

The meta-analysis parameters included studies published from 2020 to June 2024, totaling 1,099 patients within four selected studies. Findings include:

• This systematic review and meta-analysis demonstrated that the Merlin Assay CP-GEP model presents the hallmarks of an effective deselection tool for SLNB.
• Despite heterogeneity between studies, the test performed consistently well, identifying those at low risk of SLN positivity, particularly for patients with pT2 melanoma.
• Across all primary tumor groups (pT1-pT4), the SLNB positivity rate was 17.8%. Merlin was able to identify 27% as low risk for nodal metastasis with a post-test positivity rate of only 5%.
• Negative Predictive Value and Sentinel Lymph Node Biopsy Reduction Rate were highest for both pT1 and pT2 melanomas (T1: NPV 94%, T2: NPV 95%; T1: RR 72%, T2 RR 31%).

"It is really exciting to see that the robust and consistent performance of our Merlin Assay has been confirmed independently by this work led by Dr. Wong and Dr. van Akkooi", said SkylineDx Chief Scientific Officer, Jvalini Dwarkasing, PhD. "These findings further validate its clinical utility as a precision medicine tool to guide more informed decisions around sentinel lymph node biopsies in melanoma patients."

To learn more information about SkylineDx and its commitment to improving melanoma care for a more personalized and effective approach to treatment, visit www.skylinedx.com.

About the Merlin Assay (CP-GEP)

CP-GEP is a non-invasive prediction model for cutaneous melanoma patients and is the only commercially available GEP test that combines clinicopathologic (CP) variables with gene expression profiling (GEP) into a single integrated algorithm. This CP-GEP model is also the only GEP test that provides a binary stratification of all patients based on being High or Low Risk for metastasis and thereby assigns them to the appropriate surgical action categories as listed in evidence-based cancer treatment, prevention and screening guidelines. The advanced CP-GEP model was developed by Mayo Clinic and SkylineDx and is the latest commercially launched GEP test, which has been clinically validated in multiple studies on a global basis. The test has been launched in the United States and Europe as Merlin. SkylineDx collaborates with diagnostic service providers globally to bring this test to market and increase patient access. More information (including references) may be obtained at www.falconprogram.com and www.merlinmelanomatest.com

About SkylineDx

SkylineDx is a biotechnology company focused on research and development of molecular diagnostics in oncology, inflammatory and infectious 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 US 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:

Predictive Performance of the Clinicopathologic Gene Expression Profile (CP-GEP) in Identifying Cutaneous Melanoma Patients for Whom Sentinel Lymph Node Biopsy is Unnecessary: A Systematic Review and Meta-Analysis. Terence Wong, Sydney Ch'ng, Peter Ferguson , Linda Martin , Alexander M Menzies , Inês Pires da Silva, Georgina V Long , Richard A Scolyer, Alexander van Akkooi, Serigne N Lo.  Link to the publication.

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SOURCE SkylineDx