Increased effort is needed in the development of reliable predictive biomarkers for stage III melanoma, according to a review published in the International Journal of Molecular Sciences.1
Gene expression analysis and the identification of a single gene or a signature correlated with patients’ outcomes could lead to improved patient stratification. Research has shown an association between mRNA-signatures and prognosis in patients with stage III melanoma. MicroRNAs (miRNAs) have been used in the identification of high-risk patients who may benefit from adjuvant therapy. In addition, circulating tumor DNA also may have important clinical implications, as research has shown that it is associated with shorter progression-free survival.
In a recent study of circulating tumor cells (CTCs), Lucci and colleagues found that 1 or more CTCs per 7.5 mL of blood can independently predict disease relapse at 6 months from baseline, as well as up to 54 months of follow-up. DNA methylation and programmed death ligand 1 (PD-L1) status have also shown promise as potential biomarkers.2
The prognostic significance of B-Raf proto-oncogene serine/threonine-protein kinase (BRAF) mutations has been investigated in a number of studies, but the role of BRAF in predicting patient outcomes in melanoma is controversial, according to the study authors. A majority of studies have found an association of BRAF mutation with poor clinical outcome. García-Silva et al found that extracellular vesicles (EV) derived from exudative seroma (ES) may be a useful surrogate marker for melanoma progression and could be used to detect melanoma-specific mutations.3
“EVs could be a promising source of mutant DNA and should be considered for the development of next-generation liquid biopsy approaches,” according to the study authors.
Radiomics is an emerging and promising technology, as recent research has shown that radiomic images may be predictive biomarkers for immunotherapy response and an important tool for managing patients with cancer.
“A multidisciplinary approach integrating biology with bioinformatics and computational science is fundamental in order to discover novel predictive and prognostic biomarkers with the aim of personalizing the treatment of each patient,” stated the study authors.
- Tonella L, Pala V, Ponti R, et al. Prognostic and predictive biomarkers in stage III melanoma: current insights and clinical implications. Int J Mol Sci. 2021;22(9):4561. doi:10.3390/ijms22094561
- Lucci A, Hall CS, Patel SP, et al. Circulating tumor cells and early relapse in node-positive melanoma. Clin Cancer Res. 2020;26(8):1886-1895. doi:10.1158/1078-0432.CCR-19-2670
- García-Silva S, Benito-Martín A, Sánchez-Redondo S, et al. Use of extracellular vesicles from lymphatic drainage as surrogate markers of melanoma progression and BRAFV600E mutation. J Exp Med. 2019;216(5):1061-1070. doi:10.1084/jem.20181522