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. 2019 Feb 5;14(2):e0211504.
doi: 10.1371/journal.pone.0211504. eCollection 2019.

Characterisation and Validation of Mel38; A Multi-Tissue microRNA Signature of Cutaneous Melanoma

Free PMC article

Characterisation and Validation of Mel38; A Multi-Tissue microRNA Signature of Cutaneous Melanoma

Ryan Van Laar et al. PLoS One. .
Free PMC article


Background: Histopathologic examination of melanocytic neoplasms can be challenging and subjective, with no specific circulating or tissue-based biomarkers currently available. Recently, a circulating 38-microRNA profile of melanoma (Mel38) was described. In this study, Mel38 expression and its impact on downstream mRNA regulation in solid tissue is examined.

Methods: Mel38 was applied to archival, clinically-annotated, solid-tissue genomic datasets representing benign naevi, primary and metastatic melanoma. Statistical analysis of the signature in relation to disease status, patient outcome and molecular pathways was performed.

Results: Mel38 is able to stratify genomic data from solid tissue biopsies on the basis of disease status and differences in melanoma-specific survival. Experimentally-verified messenger-RNA targets of Mel38 also exhibit prognostic expression patterns and represent key molecular pathways and events in melanoma development and progression.

Conclusion: The Mel38 microRNA profile may have diagnostic and prognostic utility in solid tissue as well as being a robust circulating biomarker of melanoma.

Conflict of interest statement

RVL is an employee of Geneseq Biosciences, a Melbourne (Australia) based start-up company that has applied for provisional patent protection on the genomic algorithm and methods described in this and previous studies [10]. International patent application No. PCT/AU2018/051050, patent name: “A method of diagnosis, staging and monitoring of melanoma using microRNA gene expression”. Geneseq Biosciences are developing an assay based on the microRNA signature described in this and previous studies (Melaseq™). Authors ML and SF are functioning in an unpaid advisory role and report no other competing interests. This does not alter our adherence to PLOS ONE policies on sharing data and materials.


Fig 1
Fig 1. Multidimensional scaling of 52 FFPE samples of benign naevi, primary and metastatic melanoma based on their expression of a 27-microRNA subset of the Mel38 signature.
X, Y and Z axis correspond to the first 3 principal components present in the 52 sample x 27 microRNA-expression dataset.
Fig 2
Fig 2. Individual value plots of FFPE-microRNA classification scores, grouped by disease status.
Scores were generated using a support vector machine algorithm trained on the 27-microRNA subset of the Mel38 signature. Mean and 95% confidence intervals of each group shown.
Fig 3
Fig 3
(A) Kaplan Meier analysis of stage III melanoma patients in the high-risk vs standard risk group, as defined by a cross validated prognostic model (Log rank P-value = 0.061) (B) Multivariate cox proportional hazards regression of microRNA risk group, adjusted for patient age at specimen collection. Mel38 significantly stratifies patients for 5-year MSS independent to age at diagnosis (P = 0.046).
Fig 4
Fig 4. Melanoma KEGG molecular pathway (KEGG ID: hsa05218).
Red circles indicate mRNAs (protein coding) genes known to be regulated by one or more of the Mel38 microRNAs. P-value of Mel38-mRNA vs KEGG melanoma pathway overlap: P = 1.3 x 10−11.
Fig 5
Fig 5
Prognostic stratification of 191 melanoma patients according to Mel38-mRNA expression profiles vs. melanoma-specific-survival (A) Kaplan Meier analysis. Log rank test P = 0.0028 (B) Multivariate cox proportional-hazards regression subgroup plot. Survival differences between the mRNA high vs low risk group is statistically significant (P = 0.0008, Hazard ratio (HR): 2.49), while the difference between the medium and low risk group approached significance (P = 0.055, HR: 1.62), when adjusted for age, gender and stage. Disease stage results are vs the ‘general’ metastasis category.

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Grant support

The authors received no specific funding for this work. Geneseq Biosciences provided support in the form of salary for author RVL but did not have any additional role in the study design, data collection and analysis, decision to publish, or preparation of the manuscript. The specific roles of these authors are articulated in the ‘author contributions’ section.