A Multi-Omic Approach for the Detection of Melanoma Brain Metastasis — The Association Specialists
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A Multi-Omic Approach for the Detection of Melanoma Brain Metastasis (21963)

Desiree Sexauer 1 2 , Russell Diefenbach 3 4 , Ashleigh Stewart 3 4 , Wei Yen Chan 3 4 , Anna L Reid 1 2 , Jenny H Lee 3 4 , Lydia Warburton 1 2 5 , Luisa M Pinnel 1 2 , Rebecca Auzins 1 2 , Pauline Zaenker 1 2 , Alexander M Menzies 4 6 7 , Richard A Scolyer 4 7 8 , Aaron B Beasley 4 6 , Helen Rizos 1 2 , Elin S Gray 3 4 , Georgina Long 3 5 9
  1. Centre for Precision Health, Edith Cowan University, Perth, Western Australia, Australia
  2. School of Medical and Health Sciences, Edith Cowan University, Perth, Western Australia, Australia
  3. Faculty of Medicine, Health and Human Sciences, Macquarie University, Sydney, New South Wales, Australia
  4. Melanoma Institute Australia, Sydney, New South Wales, Australia
  5. Department of Medical Oncology, Fiona Stanley Hospital, Murdoch, Western Australia, Australia
  6. Department of Medical Oncology, Royal North Shore Hospital and Mater Hospitals, Sydney, New South Wales, Australia
  7. Faculty of Medicine and Health, The University of Sydney, Sydney, New South Wales, Australia
  8. Tissue Pathology and Diagnostic Oncology, Royal Prince Alfred Hospital and NSW Health Pathology, Sydney, New South Wales, Australia
  9. , Melanoma Institute Australia, Sydney, New South Wales, Australia

Context: Many melanoma patients with brain metastases present with large symptomatic tumours, leading to significant morbidity and poor prognosis. Early detection of brain metastases when they are small and asymptomatic is crucial for improving outcomes.

Method: In this project, microRNA (miRNA), tumour-associated autoantibodies, and brain-derived cell-free DNA methylation data were obtained from 34 melanoma patients with intracranial and extracranial metastases and 62 patients with only extracranial metastases (discovery cohort). We assessed the miRNA expression profile of the discovery cohort using a QIAseq miRNA library kit, followed by sequencing on an Ion Torrent Platform. The trimmed mean of M-values (TMM) method was used to normalise the miRNA expression count data, and lowly expressed miRNAs were filtered out using the filterByExpr function of the edgeR package. Library sizes were recomputed after filtering. Differential expression analysis was performed using the quasi-likelihood method of the edgeR package in R (v3.42.4). Differential expression with ≥1.5-fold changes and FDR ≤ 0.01 was considered significant.

Results: After expression filtering, 336/2633 miRNAs remained for further analysis. Of these 336 miRNAs, only one (miRNA-1246) was significantly enriched (logFC=2.028, FDR=0.0013) in patients with intracranial metastasis. To validate this miRNA target of interest, a TaqMan MicroRNA Assay will be performed using an independent validation cohort.

Conclusion: miRNA-1246 has pro-oncogenic functions in multiple cancers and is implicated in neuroinflammatory conditions. Further analysis is required for validation. A multi-omic model based on RNA-seq, methylation, and tumour-associated autoantibody data will be developed for more precise screening and prognostic assessment in metastatic melanoma patients.