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Plasma markers for identifying patients with metastatic melanoma.

ABSTRACT: With the rising incidence of melanoma, more patients are undergoing surveillance for disease recurrence. Our purpose was to study levels of proteins that might be secreted in the blood of patients with metastatic melanoma that can be used for monitoring these individuals.Genome-wide gene expression data were used to identify abundantly expressed genes in melanoma cells that encode for proteins likely to be present in the blood of cancer patients, based on high expression levels in tumors. ELISA assays were employed to measure proteins in plasma of 216 individuals; 108 metastatic melanoma patients and 108 age- and gender-matched patients with resected stage I/II disease split into equal-sized training and test cohorts.Levels of seven markers, CEACAM (carcinoembryonic antigen-related cell adhesion molecule), ICAM-1 (intercellular adhesion molecule 1), osteopontin, MIA (melanoma inhibitory activity), GDF-15 (growth differentiation factor 15), TIMP-1 (tissue inhibitor of metalloproteinase 1), and S100B, were higher in patients with unresected stage IV disease than in patients with resected stage I/II disease. About 81% of the stage I/II patients in the training set had no marker elevation, whereas 69% of the stage IV patients had elevation of at least one marker (P < 0.0001). Receiver operating characteristic curves for the markers in combination in these two patient populations had an area under curve (AUC) of 0.79 in the training set and 0.8 in the test set. A CART (Classification and Regression Trees) model developed in the training set further improved the AUC in the test set to 0.898.Plasma markers, particularly when assessed in combination, can be used to monitor patients for disease recurrence and can compliment currently used lactate dehydrogenase and imaging studies; prospective validation is warranted.

SUBMITTER: Kluger HM

PROVIDER: S-EPMC3415234 | biostudies-literature | 2011 Apr

REPOSITORIES: biostudies-literature

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Plasma markers for identifying patients with metastatic melanoma.

Kluger Harriet M HM Hoyt Kathleen K Bacchiocchi Antonella A Mayer Tina T Kirsch Jonathan J Kluger Yuval Y Sznol Mario M Ariyan Stephan S Molinaro Annette A Halaban Ruth R

Clinical cancer research : an official journal of the American Association for Cancer Research 20110412 8

<h4>Purpose</h4>With the rising incidence of melanoma, more patients are undergoing surveillance for disease recurrence. Our purpose was to study levels of proteins that might be secreted in the blood of patients with metastatic melanoma that can be used for monitoring these individuals.<h4>Methods</h4>Genome-wide gene expression data were used to identify abundantly expressed genes in melanoma cells that encode for proteins likely to be present in the blood of cancer patients, based on high exp ...[more]

PMID: 21487066

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Project description:Malignant melanoma (MM) is a malignant tumor originating from melanocytes, with high aggressiveness, high metastasis and extremely poor prognosis. MM accounts for 4% of skin cancers and 80% of mortality, and the median survival of patients with metastatic melanoma is only about 6 months, with a five-year survival rate of less than 10%. In recent years, the incidence of melanoma has gradually increased and has become one of the serious diseases that endanger human health. Competitive endogenous RNA (ceRNA) is the main model of the mechanism by which long chain non-coding RNAs (lncRNAs) play a regulatory role in the disease. LncRNAs can act as a "sponge", competitively attracting small RNAs (micoRNAs; miRNAs), thus interfering with miRNA function, and affect the expression of target gene messenger RNAs (mRNAs), ultimately promoting tumorigenesis and progression. Bioinformatics analysis can identify potentially prognostic and therapeutically relevant differentially expressed genes in MM, finding lncRNAs, miRNAs and mRNAs that are interconnected through the ceRNA network, providing further insight into gene regulation and prognosis of metastatic melanoma. Weighted co-expression networks were used to identify lncRNA and mRNA modules associated with the metastatic phenotype, as well as the co-expression genes contained in the modules. A total of 17 lncRNAs, six miRNAs, and 11 mRNAs were used to construct a ceRNA interaction network that plays a regulatory role in metastatic melanoma patients. The prognostic risk model was used as a sorter to classify the survival prognosis of melanoma patients. Four groups of ceRNA interaction triplets were finally obtained, which miR-3662 might has potential implication for the treatment of metaststic melanoma patients, and futher experiments confirmed the regulating relationship and phenotype of this assumption. This study provides new targets to regulate metastatic process, predict metastatic potential and indicates that the miR-3662 can be used in the treatment of melanoma.

Dataset Information

Plasma markers for identifying patients with metastatic melanoma.

Publications

Plasma markers for identifying patients with metastatic melanoma.

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