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A multi-factorial genetic model for prognostic assessment of high risk melanoma patients receiving adjuvant interferon.

ABSTRACT: PURPOSE: IFNa was the first cytokine to demonstrate anti-tumor activity in advanced melanoma. Despite the ability of high-dose IFNa reducing relapse and mortality by up to 33%, large majority of patients experience side effects and toxicity which outweigh the benefits. The current study attempts to identify genetic markers likely to be associated with benefit from IFN-a2b treatment and predictive for survival. EXPERIMENTAL DESIGN: We tested the association of variants in FOXP3 microsatellites, CTLA4 SNPs and HLA genotype in 284 melanoma patients and their association with prognosis and survival of melanoma patients who received IFNa adjuvant therapy. RESULTS: Univariate survival analysis suggested that patients bearing either the DRB1*15 or HLA-Cw7 allele suffered worse OS while patients bearing either HLA-Cw6 or HLA-B44 enjoyed better OS. DRB1*15 positive patients suffered also worse RFS and conversely HLA-Cw6 positive patients had better RFS. Multivariate analysis revealed that a five-marker genotyping signature was prognostic of OS independent of disease stage. In the multivariate Cox regression model, HLA-B38 (p?=?0.021), HLA-C15 (p?=?0.025), HLA-C3 (p?=?0.014), DRB1*15 (p?=?0.005) and CT60*G/G (0.081) were significantly associated with OS with risk ratio of 0.097 (95% CI, 0.013-0.709), 0.387 (95% CI, 0.169-0.889), 0.449 (95% CI, 0.237-0.851), 1.948 (95% CI, 1.221-3.109) and 1.484 (95% IC, 0.953-2.312) respectively. CONCLUSION: These results suggest that gene polymorphisms relevant to a biological occurrence are more likely to be informative when studied in concert to address potential redundant or conflicting functions that may limit each gene individual contribution. The five markers identified here exemplify this concept though prospective validation in independent cohorts is needed.

SUBMITTER: Wang E

PROVIDER: S-EPMC3404079 | biostudies-literature | 2012

REPOSITORIES: biostudies-literature

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A multi-factorial genetic model for prognostic assessment of high risk melanoma patients receiving adjuvant interferon.

Wang Ena E Zhao Yingdong Y Monaco Alessandro A Uccellini Lorenzo L Kirkwood John M JM Spyropoulou-Vlachou Maria M Panelli Monica C MC Marincola Francesco M FM Gogas Helen H

PloS one 20120724 7

<h4>Purpose</h4>IFNa was the first cytokine to demonstrate anti-tumor activity in advanced melanoma. Despite the ability of high-dose IFNa reducing relapse and mortality by up to 33%, large majority of patients experience side effects and toxicity which outweigh the benefits. The current study attempts to identify genetic markers likely to be associated with benefit from IFN-a2b treatment and predictive for survival.<h4>Experimental design</h4>We tested the association of variants in FOXP3 micro ...[more]

PMID: 22911710

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Project description:Adjuvant therapy of stage IIB/III melanoma with interferon reduces relapse and mortality by up to 33% but is accompanied by toxicity-related complications. Polymorphisms of the CTLA-4 gene associated with autoimmune diseases could help in identifying interferon treatment benefits. We previously genotyped 286 melanoma patients and 288 healthy (unrelated) individuals for six CTLA-4 polymorphisms (SNP). Previous analyses found no significant differences between the distributions of CTLA-4 polymorphisms in the melanoma population vs. controls, no significant difference in relapse free and overall survivals among patients and no correlation between autoimmunity and specific alleles. We report new analysis of these CTLA-4 genetic profiles, using Network Phenotyping Strategy (NPS). It is graph-theory based method, analyzing the SNP patterns. Application of NPS on CTLA-4 polymorphism captures allele relationship pattern for every patient into 6-partite mathematical graph P. Graphs P are combined into weighted 6-partite graph S, which subsequently decomposed into reference relationship profiles (RRP). Finally, every individual CTLA-4 genotype pattern is characterized by the graph distances of P from eight identified RRP's. RRP's are subgraphs of S, collecting equally frequent binary allele co-occurrences in all studied loci. If S topology represents the genetic "dominant model", the RRP's and their characteristic frequencies are identical to expectation-maximization derived haplotypes and maximal likelihood estimates of their frequencies. The graph-representation allows showing that patient CTLA-4 haplotypes are uniquely different from the controls by absence of specific SNP combinations. New function-related insight is derived when the 6-partite graph reflects allelic state of CTLA-4. We found that we can use differences between individual P and specific RRPs to identify patient subpopulations with clearly different polymorphic patterns relatively to controls as well as to identify patients with significantly different survival.

Project description:ObjectiveThe influence of body composition on the effectiveness of immune checkpoint inhibitors (ICIs) in patients with melanoma is still uncertain in clinical practice. Therefore, the objective of this study was to examine the potential association between body composition and clinical outcomes in patients with melanoma undergoing ICIs treatment.MethodsA systematic literature search was performed across several databases, including PubMed, Embase, Cochrane Library and Google Scholar, to gather relevant studies. The primary outcomes of interest were overall survival (OS) and progression-free survival (PFS), assessed by hazard ratios (HR). Secondary outcomes, such as adverse events (AE), were evaluated using odds ratios (OR).ResultsThis meta-analysis comprised ten articles involving a total of 1,283 patients. Systemic analysis of all collected evidence revealed that body composition, including low skeletal muscle index (SMI) (OS: HR = 1.66, 95% CI = 1.13-2.43, p = 0.010; PFS: HR = 1.28, 95% CI = 1.06-1.55, p = 0.009), high subcutaneous adipose tissue density (SMD) (OS: HR = 1.93, 95% CI = 1.09-3.44, p = 0.025; PFS: HR = 1.31, 95% CI = 1.06-1.63, p = 0.012), and sarcopenia (OS: HR = 1.25, 95% CI = 1.03-1.51, p = 0.022; PFS: HR = 1.25, 95% CI = 1.03-1.51, p = 0.022), were significantly associated with OS and PFS in melanoma patients treated with ICIs. However, these markers did not show a significant association with treatment-related adverse events. Interestingly, no significant correlation was found between visceral fat index (VFI) (OS: HR = 0.71, 95% CI = 0.29-1.76, p = 0.462; PFS: HR = 0.98, 95% CI = 0.93-1.02, p = 0.274) and OS or PFS in melanoma patients under ICIs treatment.ConclusionBody composition was found to be associated with decreased treatment response and lower long-term efficacy in patients with melanoma undergoing immune checkpoint inhibitor (ICI) therapy. However, it is important to note that body composition did not appear to contribute to increased incidence of adverse events in these patients.

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A multi-factorial genetic model for prognostic assessment of high risk melanoma patients receiving adjuvant interferon.

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A multi-factorial genetic model for prognostic assessment of high risk melanoma patients receiving adjuvant interferon.

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