Literature DB >> 33302400

Investigating Serum and Tissue Expression Identified a Cytokine/Chemokine Signature as a Highly Effective Melanoma Marker.

Marco Cesati1, Francesca Scatozza2, Daniela D'Arcangelo2, Gian Carlo Antonini-Cappellini2, Stefania Rossi3, Claudio Tabolacci3, Maurizio Nudo2, Enzo Palese2, Luigi Lembo2, Giovanni Di Lella2, Francesco Facchiano3, Antonio Facchiano2.   

Abstract

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.

Entities:  

Keywords:  Support Vector Machine; cytokines; machine learning; melanoma markers; principal component analysis

Year:  2020        PMID: 33302400      PMCID: PMC7762568          DOI: 10.3390/cancers12123680

Source DB:  PubMed          Journal:  Cancers (Basel)        ISSN: 2072-6694            Impact factor:   6.639


  50 in total

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2.  Serological landscape of cytokines in cutaneous melanoma.

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5.  Simultaneous endocrine expression and loss of melanoma markers in malignant melanoma metastases, a retrospective analysis.

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7.  PDGFR-alpha inhibits melanoma growth via CXCL10/IP-10: a multi-omics approach.

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Journal:  Oncotarget       Date:  2016-11-22

8.  Adipocytes promote tumor progression and induce PD-L1 expression via TNF-α/IL-6 signaling.

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9.  Clinical and prognostic value of tumor volumetric parameters in melanoma patients undergoing 18F-FDG-PET/CT: a comparison with serologic markers of tumor burden and inflammation.

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10.  TNF-alpha and metalloproteases as key players in melanoma cells aggressiveness.

Authors:  Stefania Rossi; Martina Cordella; Claudio Tabolacci; Giovanni Nassa; Daniela D'Arcangelo; Cinzia Senatore; Paolo Pagnotto; Roberta Magliozzi; Annamaria Salvati; Alessandro Weisz; Antonio Facchiano; Francesco Facchiano
Journal:  J Exp Clin Cancer Res       Date:  2018-12-28
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Journal:  Molecules       Date:  2021-06-13       Impact factor: 4.411

Review 3.  Chemokine Pathways in Cutaneous Melanoma: Their Modulation by Cancer and Exploitation by the Clinician.

Authors:  Rebecca Adams; Bernhard Moser; Sophia N Karagiannis; Katie E Lacy
Journal:  Cancers (Basel)       Date:  2021-11-10       Impact factor: 6.575

4.  Editorial on Special Issue "Advances and Novel Treatment Options in Metastatic Melanoma".

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5.  Expression of Autoimmunity-Related Genes in Melanoma.

Authors:  Francesca Scatozza; Antonio Facchiano
Journal:  Cancers (Basel)       Date:  2022-02-16       Impact factor: 6.639

6.  XIAP promotes melanoma growth by inducing tumour neutrophil infiltration.

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7.  Analysis of gene expression levels and their impact on survival in 31 cancer-types patients identifies novel prognostic markers and suggests unexplored immunotherapy treatment options in a wide range of malignancies.

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