Dataset Information

DNA alteration-based classification of uveal melanoma gives better prognostic stratification than immune infiltration, which has a neutral effect in high-risk group.

ABSTRACT:

Background

In uveal melanomas, immune infiltration is a marker of poor prognosis. This work intended to decipher the biological characteristics of intra-tumor immune population, compare it to other established biomarkers and to patients' outcome.

Methods

Primary, untreated, and mainly large uveal melanomas with retinal detachment were analyzed using: transcriptomic profiling (n = 15), RT-qPCR (n = 36), immunohistochemistry (n = 89), Multiplex Ligation-dependent Probe Amplification (MLPA) for copy number alterations (CNA) analysis (n = 89), array-CGH (n = 17), and survival statistics (n = 86).

Results

Gene expression analysis divided uveal melanomas into two groups, according to the IFN?/STAT1-IRF1 pathway activation. Tumors with IFN?-signature had poorer prognosis and showed increased infiltration of CD8⁺ T lymphocytes and macrophages. Cox multivariate analyses of immune cell infiltration with MLPA data delineated better prognostic value for three prognostic groups (three-tier stratification) than two (two-tier stratification). CNA-based model comprising monosomy 3, 8q amplification, and LZTS1and NBL1 deletions emerged as the best predictor for disease-free survival. It outperformed immune cell infiltration in receiver operating characteristic curves. The model that combined CNA and immune infiltration defined risk-groups according to the number of DNA alterations. Immune cell infiltration was increased in the high-risk group (73.7%), where it did not correlate with patient survival, while it was associated with poorer outcome in the intermediate risk-group.

Conclusions

High degree of immune cell infiltration occurs in a subset of uveal melanomas, is interferon-gamma-related, and associated with poor survival. It allows for two-tier stratification, which is prognostically less efficient than a three-tier one. The best prognostic stratification is by CNA model with three risk-groups where immune cell infiltration impacts only some subgroups.

SUBMITTER: Narasimhaiah D

PROVIDER: S-EPMC6558590 | biostudies-literature | 2019 Jun

REPOSITORIES: biostudies-literature

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Publications

DNA alteration-based classification of uveal melanoma gives better prognostic stratification than immune infiltration, which has a neutral effect in high-risk group.

Narasimhaiah Deepti D Legrand Catherine C Damotte Diane D Remark Romain R Munda Marco M De Potter Patrick P Coulie Pierre G PG Vikkula Miikka M Godfraind Catherine C

Cancer medicine 20190425 6

<h4>Background</h4>In uveal melanomas, immune infiltration is a marker of poor prognosis. This work intended to decipher the biological characteristics of intra-tumor immune population, compare it to other established biomarkers and to patients' outcome.<h4>Methods</h4>Primary, untreated, and mainly large uveal melanomas with retinal detachment were analyzed using: transcriptomic profiling (n = 15), RT-qPCR (n = 36), immunohistochemistry (n = 89), Multiplex Ligation-dependent Probe Amplification ...[more]

PMID: 31025552

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Project description:BackgroundAge is associated with the prognosis of glioma patients, but there is no uniform standard of age-group classification to evaluate the prognosis of glioma patients. In this study, we aimed to establish an age group classification for risk stratification in glioma patients.Methods1502 patients diagnosed with gliomas at Nanfang Hospital between 2000 and 2018 were enrolled. The WHO grade of glioma was used as a dependent variable to evaluate the effect of age on risk stratification. The evaluation model was established by logistic regression, and the Akaike information criterion (AIC) value of the model was used to determine the optimal cutoff points for age-classification. The differences in gender, WHO grade, pathological subtype, tumor cell differentiation, tumor size, tumor location, and molecular markers between different age groups were analyzed. The molecular markers included GFAP, EMA, MGMT, P53, NeuN, Oligo2, EGFR, VEGF, IDH1, Ki-67, PR, CD3, H3K27M, TS, and 1p/19q status.ResultsThe proportion of men with glioma was higher than that of women with glioma (58.3% vs 41.7%). Analysis of age showed that appropriate classifications of age group were 0-14 years old (pediatric group), 15-47 years old (youth group), 48-63 years old (middle-aged group), and ≥ 64 years old (elderly group).The proportions of glioblastoma and large tumor size (4-6 cm) increased with age (p = 0.000, p = 0.018, respectively). Analysis of the pathological molecular markers across the four age groups showed that the proportion of patients with larger than 10% area of Ki-67 expression or positive PR expression increased with age (p = 0.000, p = 0.017, respectively).ConclusionsAppropriate classifications of the age group for risk stratification are 0-14 years old (pediatric group), 15-47 years old (young group), 48-63 years old (middle age group) and ≥ 64 years old (elderly group). This age group classification is effective in evaluating the risk of glioblastoma in glioma patients.

Dataset Information

DNA alteration-based classification of uveal melanoma gives better prognostic stratification than immune infiltration, which has a neutral effect in high-risk group.

Background

Methods

Results

Conclusions

Publications

DNA alteration-based classification of uveal melanoma gives better prognostic stratification than immune infiltration, which has a neutral effect in high-risk group.

Similar Datasets

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