Unlocking the power of small RNA-seq in melanoma.

Why microRNAs matter in cancer

MicroRNAs (miRNAs) are short, non-coding RNAs of around 18–24 nucleotides that regulate gene expression at the post-transcriptional level. By directing Argonaute proteins to complementary mRNA targets, they can repress translation or trigger degradation. In cancer, dysregulated miRNAs function as either oncogenes or tumor suppressors, which makes them highly attractive biomarkers of disease state and progression. Their inherent stability in biofluids such as plasma and serum, often protected within extracellular vesicles or protein complexes, adds to their appeal, enabling reliable detection in minimally invasive “liquid biopsies.”

A recent study by Love et al. (2024) leveraged these properties to validate two melanoma-specific miRNA signatures, MEL38 and MEL12, using small RNA sequencing NEXTFLEX Small RNA Sequencing Kit V4 Discover  on both formalin-fixed paraffin-embedded (FFPE) tissue and plasma samples. MEL38 is a 38-miRNA diagnostic panel designed to distinguish benign nevi from invasive melanoma, while MEL12 is a 12-miRNA prognostic panel intended to predict survival outcomes and stratify samples by risk.

From hybridization-based analysis to small RNA-seq

Unlike conventional RNA-seq workflows that capture long transcripts, small RNA-seq is optimized for short RNA species such as miRNAs, piRNAs, Y-RNA fragments and tRNA-derived fragments. The process typically involves extraction of RNA, adapter ligation, reverse transcription and amplification, followed by high-throughput sequencing on short-read platforms. Data are processed with bioinformatic pipelines tailored for adapter trimming, alignment, and quantification of annotated small RNAs.

Compared to the NanoString® hybridization-based platform, sequencing provides greater dynamic range, nucleotide-level resolution, and the ability to identify novel isoforms or isomiRs. This makes small RNA-seq not only a validation tool for existing biomarkers but also an engine for expanding the catalogue of small RNAs implicated in cancer biology. The MEL38 and MEL12 signatures were initially developed with NanoString® technology, but the Love study asked whether small RNA-seq could not only reproduce but also enhance their performance across tissue and plasma.

Small RNA-seq matches and extends performance

When directly compared, small RNA-seq matched NanoString® analysis in tissue samples and slightly exceeded it in plasma, highlighting its robustness and sensitivity across diverse sample types.

In FFPE tissue, MEL38 achieved perfect separation of melanoma from benign lesions, with an area under the curve (AUC) of 1.0 (P < 0.001). In plasma, accuracy was nearly as high, with an AUC of 0.99. For prognostic assessment, MEL12 stratified samples into low-, intermediate-, and high-risk groups with hazard ratios ranging from 1.8 to 2.2 compared to the low-risk group. These findings were independent of established variables such as stage and were validated not only in plasma but also in large external datasets. Importantly, in The Cancer Genome Atlas melanoma cohort, MEL12 outperformed alternative genomic classifiers based on mRNA expression or protein arrays, underscoring the distinctive predictive power embedded in miRNA signatures.

Conclusions

By validating MEL38 and MEL12 with small RNA-seq, Love et al. demonstrate that miRNA panels are powerful, reproducible, and relevant biomarkers for melanoma. This study not only confirms the value of these specific signatures but also establishes small RNA-seq as a robust platform for biomarker validation and discovery. With its ability to profile stable and informative small RNAs in multiple sample types, small RNA-seq offers a transformative route toward precision oncology.