Investigating serum and tissue expression identified a cytokine/chemokine signature as a highly effective melanoma marker

The identification of reliable and quantitative melanoma biomarkers may help an early diagnosis and may directly affect melanoma mortality and morbidity. The aim of the present study was to identify effective biomarkers by investigating the expression of 27 cytokines/chemokines in melanoma compared to healthy controls, both in serum and in tissue samples. Serum samples were from 232 patients recruited at the IDI-IRCCS hospital. Expression was quantified by xMAP technology, on 27 cytokines/chemokines, compared to the control sera. RNA expression data of the same 27 molecules were obtained from 511 melanoma- and healthy-tissue samples, from the GENT2 database. Statistical analysis involved a 3-step approach: analysis of the single-molecules by Mann–Whitney analysis; analysis of paired-molecules by Pearson correlation; and profile analysis by the machine learning algorithm Support Vector Machine (SVM). Single-molecule analysis of serum expression identified IL-1b, IL-6, IP-10, PDGF-BB, and RANTES differently expressed in melanoma (p < 0.05). Expression of IL-8, GM-CSF, MCP-1, and TNF-α was found to be significantly correlated with Breslow thickness. Eotaxin and MCP-1 were found differentially expressed in male vs. female patients. Tissue expression analysis identified very effective marker/predictor genes, namely, IL-1Ra, IL-7, MIP-1a, and MIP-1b, with individual AUC values of 0.88, 0.86, 0.93, 0.87, respectively. SVM analysis of the tissue expression data identified the combination of these four molecules as the most effective signature to discriminate melanoma patients (AUC = 0.98). Validation, using the GEPIA2 database on an additional 1019 independent samples, fully confirmed these observations. The present study demonstrates, for the first time, that the IL-1Ra, IL-7, MIP-1a, and MIP-1b gene signature discriminates melanoma from control tissues with extremely high efficacy. We therefore propose this 4-molecule combination as an effective melanoma marker

CTLA-4 gene variant -1661A>G may predict the onset of endocrine adverse events in metastatic melanoma patients treated with ipilimumab

The anti-CTLA-4 monoclonal antibody ipilimumab (IPI) was the first immune-checkpoint inhibitor approved for the treatment of metastatic melanoma (MM). Despite the current availability of more effective and less toxic anti-PD-1 agents, IPI remains used in monotherapy as adjuvant or second/third line setting and in combination with anti-PD-1 or other agents [1]. Immune-related adverse events (irAEs) likely associated with IPI treatment include endocrinopathies, mostly pituitary and, to a less extent, thyroid dysfunctions [2], [3]. Nowadays, no predictive biomarkers identify patients at risk of developing endocrine irAEs (endo-irAEs). Functional CTLA-4 single nucleotide variants (SNVs) are associated with susceptibility to autoimmune diseases including endocrinopathies [4]. These variants may influence the host immune response through alteration of CTLA-4 expression levels and inhibitory function in T cells [4]. We here report an observational and exploratory study showing, for the first time to our knowledge, the significant association of the CTLA-4 -1661A>G SNV (rs4553808) with the onset of endo-irAEs in MM patients treated with IPI. This SNV was the only one, out of the six we analysed (-1661A>G, -1577G>A, -658C>T, -319C>T, +49A>G, and CT60G>A) that showed a possible effect on endo-irAE occurrence