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Test Code: 13222

The MelaNodal PredictTM test is a laboratory-developed test that predicts the risk of sentinel lymph node metastasis in sentinel lymph node biopsy (SLNB)-eligible patients with cutaneous melanoma. It is a non-invasive, quantitative reverse transcription-polymerase chain reaction (qRT-PCR) assay that uses the CP-GEP (clinicopathologic-gene expression profile) model developed by SkylineDx in collaboration with the Mayo Clinic.1 It is performed on formalin-fixed, paraffin-embedded primary tumor tissue from patients being considered for the SLNB per current guidelines.2-3 The results identify patients who may safely forgo the SLNB procedure due to a low risk of nodal metastasis and reduced long-term risk of recurrence.

Results are generated using the CP-GEP (clinicopathologic-gene expression profile) model, which determines a probability score that aligns with either one of a binary output: low risk or high risk. The model is a logistic regression-based algorithm that incorporates patient age, Breslow depth, and the gene expression of 8 target genes (MLANA, GDF15, CXCL8, LOXL4, TGFBR1, ITGB3, PLAT, SERPINE2) and 2 control genes (RPLP0 and ACTB). A patient whose probability score falls above a predefined cutoff value is considered high risk, and a patient whose probability score falls below that predefined cutoff value is considered low risk.1

Table 1 shows MelaNodal Predict gene panel and function

Click on the table to open in a new window.

The CP-GEP (clinocopathologic-gene expression profile) model has demonstrated that a low-risk result indicates the patient has a 3% risk of nodal positivity; thus, a sentinel lymph node biopsy (SLNB) procedure may be avoided.4 A high-risk result indicates the patient has a 23.7% risk of nodal positivity; thus, a SLNB may be considered.4 These results should be interpreted in accordance with NCCN recommendations for the SLNB procedure (Table 2).2

Table 2 shows the NCCN recommendations for the SLNB procedure. 

Click on the table to open in a new window.

 

Low-risk patients have a lower risk of recurrence, distant metastasis, and death compared to high-risk patients across stages I through III (Table 3).5-8

Table 3 shows Long-term outcomes for low-risk and high-risk CP-GEP:

CP-GEP, clinicopathologic-gene expression profile; DMFS, distant metastasis-free survival; MSS, melanoma specific-free survival; RFS, recurrence-free survival.

a Stages I to II or I to III

b Stages I to III

 

Click on the table to open in a new window.

Patients with a low-risk result who forgo the SLNB procedure have a low risk of developing any type of recurrence and/or death from their melanoma at 5 years. For patients who undergo the SLNB procedure and are in the SLNB-negative, early stage I/IIA group, further risk stratification can help identify patients who are more likely to relapse or die from their melanoma and may benefit from enhanced clinical management plans.7

MelaNodal Predict is intended for patients ≥18 years who have newly diagnosed invasive cutaneous melanoma and are being considered for the sentinel lymph node biopsy (SLNB) procedure, or those who fall within guideline-recommended SLNB eligibility that includes T1-T4 melanomas. 

The sentinel lymph node biopsy (SLNB) procedure is a standard staging surgical procedure with prognostic value that identifies Stage III patients who can potentially benefit from targeted and immunotherapeutic agents in the adjuvant setting.9-10 However, the SLNB is negative up to 80% of the time and associated with surgical complications and high cost.9-11 CP-GEP was optimized to identify patients who are likely negative for sentinel lymph node and who could, thus, safely forgo the SLNB procedure, which would reduce potential surgical complications and healthcare costs.12-13 CP-GEP has been clinically validated in over 4,700 patients to predict nodal metastasis; validation has come from independent studies across different types of clinical institutions in the United States and Europe.1,4-8,12-18

Multiple studies have reported on long-term outcomes for 5-year recurrence-free survival (RFS), distant metastasis-free survival (DMFS), and overall survival (OS)/melanoma-specific survival (MSS) rates in CP-GEP low-risk and high-risk patients.5-8 These studies validated the CP-GEP's ability to stratify risk of cutaneous melanoma patients across stages I through III, including the SLNB-negative, early stage I/II patient population. Around 40% of melanoma patients who relapse or die initially have a diagnosis of  early stage I/II melanoma.7 A patient’s risk of recurrence is central to management choices, and accurate identification of a patient’s individual risk ensures the application of the most appropriate clinical management plan, with more aggressive strategies recommended for patients who are at a higher risk.7,10

The preferred specimen type is a room temperature or cooled (4°C), formalin-fixed, paraffin-embedded (FFPE) tissue block (or 5 slides [minimum 3], 10 microns each and 1 H&E section) from primary biopsy tumor tissue. Sending 10 slides of 4 to 6 microns each and 1 H&E section is acceptable.

A pathology report must accompany the submitted specimen. The following information is also required:

  • Specimen identifiers (case and block number)
  • Specimen site
  • Mitotic rate
  • Breslow thickness
  • Ulceration status
  • T-category 

Results will typically be available 3 to 5 days after the laboratory receives the specimen. Turnaround times may vary based on unforeseen circumstances. Test set-up is on Tuesdays, Thursdays, and Saturdays.

Please contact our dedicated Oncology client service team at 1.833.773.1441 or reach out to your local Dermpath Diagnostics, AmeriPath, or Quest Diagnostics Anatomic Pathology Client Services team.

References

  1. Bellomo D, Arias-Mejias SM, Ramana C, et al. Model combining tumor molecular and clinicopathologic risk factors predicts sentinel lymph node metastasis in primary cutaneous melanoma. JCO Precis Oncol. 2020;4:319-334. doi:10.1200/po.19.00206
  2. Gershenwald JE, Scolyer RA, Hess KR, et al: Melanoma staging: evidence-based changes in the American Joint Committee on Cancer Eighth Edition Cancer Staging Manual. CA Cancer J Clin 2017;67(6):472-492. doi:10.3322/caac.2140910
  3. National Comprehensive Cancer Network. NCCN Guidelines: Cutaneous Melanoma, Version 3 (2023) ME-F: 1 0f 3. Fort Washington US: NCCN. 2023
  4. Stassen RC, Mulder EEAP, Mooyart AL, et al. Clinical evaluation of the clinicopathologic and gene expression profile (CP-GEP) in patients with melanoma eligible for sentinel lymph node biopsy: a multicenter prospective Dutch study. European Journal of Surgical Oncology 2023. DOI:https://doi.org/10.1016/j.ejso.2023.107249
  5. Eggermont AMM, Bellomo D, Arias-Mejias SM et al. Identification of stage I/IIA melanoma patients at high risk for disease relapse using a clinicopathologic and gene expression model. Eur J Cancer. 2020;140:11-18. doi:10.1016/j.ejca.2020.08.029
  6. Mulder EEAP, Johnasson I, Grunhagen D et al. Using a clinicopathologic and gene expression (CP-GEP_ Model to identify stage I-II melanoma patients at risk of disease relapse. Cancers (Basel). 2022;14(12):2854. doi:10.3390/cancers14122854
  7. Amaral T, Sinnberg T, Chatziioannou E, et al. Identification of stage I/II melanoma patients at high risk for recurrence using a model combining clinicopathologic factors with gene expression profiling (CP-GEP). Euro J Cancer 2023;182:155-162. doi:10.1016/j.ejca.2022.12.021
  8. Yu WY, Meves A, Hill S, et al. Long-term survival of melanoma patients stratified by a clinicopathologic and gene expression profile (CP-GEP model): a multi-center United States cohort study. Society for Melanoma Research Annual Meeting 2023
  9. Morton DL, et al. Final trial report of sentinel-node biopsy versus nodal observation in melanoma. N. Engl. J. Med. 2014;370(7):599-609. doi:10.1056/NEJMoa1310460
  10. Centers for Medicare & Medicaid Services. MolDX: Melanoma risk stratification molecular testing. Accessed December 1, 2023. https://www.cms.gov/medicare-coverage-database/view/lcd.aspx?lcdid=37725&ver=38&proposedStatus=all&sortBy=title&bc=9%C2%A0
  11. Moody JA, Ali RF, Carbone AC, et al: Complications of sentinel lymph node biopsy for melanoma - a systematic review of the literature. Eur J Surg Oncol. 2017;43(2):270-277. doi:10.1016/j.ejso.2016.06.407
  12. Heiken TJ, Sadurni MB, Quattrocchi E, et al. Using the Merlin assay for reducing sentinel lymph node biopsy complications in melanoma: a retrospective cohort study. Int J Dermatol. 2022;61(7):848-854. DOI:10.1111/ijd.16056
  13. Thao V, Dholakia R, Moriarty JP, etc. Cost evaluation of the Merlin assay for predicting melanoma sentinel lymph node biopsy metastasis. Int J Dermatol. 2023;62(1):56-61. DOI:10.1111/ijd.16515
  14. Arias-Meijias SM, Quattrocchi E, Tempel D, et al. Primary cutaneous melanoma risk stratification using a clinicopathologic and gene expression model: a pilot study. Int J Dermatol 2020;59(11):e431-e433. doi:10.1111/ijd.14987
  15. Yousaf A, Tjien-Fooh FJ, Rentroia-Pacheo B, et al. Validation of CP-GEP (Merlin Assay) for predicting sentinel lymph node metastasis in primary cutaneous melanoma patients: a U.S. cohort study. Int J Dermatol. 2021:60(7):851-856. doi:10.1111/ijd.15594
  16. Mulder EEAP, Dwarkasing JT, Tempel D, et al. Validation of a clinicopathological and gene expression profile model for sentinel lymph node metastasis in primary cutaneous melanoma. Br J Dermatolo. 2021;184(5):944-951. doi:10.1111/bjd.19499
  17. Johanssen I, Temple D, Dwarkasing JT, et al. Validation of a clinicopathological and gene expression profile model to identify patients with cutaneous melanoma where sentinel lymph node biopsy is unnecessary. Eur J Surg Oncol. 2022;48(2):320-3325. doi:10.1016/j.ejso.2021
  18. Alexander Meves and Alexander MM Eggermont. Deselecting melanoma patients for sentinel lymph node biopsy during COVID-19: clinical utility of tumor molecular profiling. Mayo Clin Proc Innov Qual Outcomes. 2020;4(5):586-587. doi:10.1016/j.mayocpiqo.2020.05.009

 

This FAQ is provided for informational purposes only and is not intended as medical advice. A physician’s test selection and interpretation, diagnosis, and patient management decisions should be based on the physician’s education, clinical expertise, and assessment of the patient.

 

 

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