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Identification of an Immunogenic Subset of Metastatic Uveal Melanoma.

ABSTRACT: PURPOSE:Uveal melanoma is a rare melanoma variant with no effective therapies once metastases develop. Although durable cancer regression can be achieved in metastatic cutaneous melanoma with immunotherapies that augment naturally existing antitumor T-cell responses, the role of these treatments for metastatic uveal melanoma remains unclear. We sought to define the relative immunogenicity of these two melanoma variants and determine whether endogenous antitumor immune responses exist against uveal melanoma. EXPERIMENTAL DESIGN:We surgically procured liver metastases from uveal melanoma (n = 16) and cutaneous melanoma (n = 35) patients and compared the attributes of their respective tumor cell populations and their infiltrating T cells (TIL) using clinical radiology, histopathology, immune assays, and whole-exomic sequencing. RESULTS:Despite having common melanocytic lineage, uveal melanoma and cutaneous melanoma metastases differed in their melanin content, tumor differentiation antigen expression, and somatic mutational profile. Immunologic analysis of TIL cultures expanded from these divergent forms of melanoma revealed cutaneous melanoma TIL were predominantly composed of CD8(+) T cells, whereas uveal melanoma TIL were CD4(+) dominant. Reactivity against autologous tumor was significantly greater in cutaneous melanoma TIL compared with uveal melanoma TIL. However, we identified TIL from a subset of uveal melanoma patients which had robust antitumor reactivity comparable in magnitude with cutaneous melanoma TIL. Interestingly, the absence of melanin pigmentation in the parental tumor strongly correlated with the generation of highly reactive uveal melanoma TIL. CONCLUSIONS:The discovery of this immunogenic group of uveal melanoma metastases should prompt clinical efforts to determine whether patients who harbor these unique tumors can benefit from immunotherapies that exploit endogenous antitumor T-cell populations. Clin Cancer Res; 22(9); 2237-49. ©2015 AACR.

SUBMITTER: Rothermel LD

PROVIDER: S-EPMC4854785 | biostudies-literature | 2016 May

REPOSITORIES: biostudies-literature

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Identification of an Immunogenic Subset of Metastatic Uveal Melanoma.

Rothermel Luke D LD Sabesan Arvind C AC Stephens Daniel J DJ Chandran Smita S SS Paria Biman C BC Srivastava Abhishek K AK Somerville Robert R Wunderlich John R JR Lee Chyi-Chia R CC Xi Liqiang L Pham Trinh H TH Raffeld Mark M Jailwala Parthav P Kasoji Manjula M Kammula Udai S US

Clinical cancer research : an official journal of the American Association for Cancer Research 20151228 9

<h4>Purpose</h4>Uveal melanoma is a rare melanoma variant with no effective therapies once metastases develop. Although durable cancer regression can be achieved in metastatic cutaneous melanoma with immunotherapies that augment naturally existing antitumor T-cell responses, the role of these treatments for metastatic uveal melanoma remains unclear. We sought to define the relative immunogenicity of these two melanoma variants and determine whether endogenous antitumor immune responses exist aga ...[more]

PMID: 26712692

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Project description:BackgroundUveal melanoma (UM) is an aggressive intraocular malignant tumor. The present study aimed to identify the key genes associated with UM metastasis and established a gene signature to analyze the relationship between the signature and prognosis and immune cell infiltration. Later, a predictive model combined with clinical variables was developed and validated.MethodsTwo UM gene expression profile chip datasets were downloaded from TCGA and GEO databases. Immune-related genes (IRGs) were obtained from IMPORT database. First, these mRNAs were intersected with IRGs, and weighted gene co-expression network analysis (WGCNA) was used to identify the co-expression of genes primarily associated with metastasis of UM. Univariate Cox regression analysis screened the genes related to prognosis. LASSO-Cox established a risk score to distinguish high-risk group and low-risk group. Then the GSEA enrichment pathway and immune cell infiltration of the two groups were compared. And combined with clinical variables, a predictive model was constructed. The time-dependent receiver operating characteristic (ROC) curve, calibration curve, and decision curve analysis (DCA) curve were used to verify the stability and accuracy of the final predictive model, and a nomogram was then drawn.ResultsThe MEblack, MEpurple, and MEblue modules were significantly associated with the metastasis of UM patients (P value < 0.001, = 0.001, = 0.022, respectively). Four genes (UBXN2B, OTUD3, KAT8, LAMTOR2) were obtained by Pearson correlation analysis, weighted gene correlation network analysis (WGCNA), univariate Cox, and LASSO-Cox. And a novel prognostic risk score was established. Immune-related prognostic signature can well classify UM patients into high-risk and low-risk groups. Kaplan-Meier curve showed that the OS of high-risk patients was worse than that of low-risk patients. In addition, the risk score played an important role in evaluating the signaling pathway and immune cell infiltration of UM patients in high-risk and low-risk groups. Both the training set and validation set of the model showed good predictive accuracy in the degree of differentiation and calibration (e.g., 1-year overall survival: AUC = 0.930 (0.857-1.003)). Finally, a nomogram was established to serve in clinical practice.SignificanceUM key gene signature and prognosis predictive model might provide insights for further investigation of the pathogenesis and development of UM at the molecular level, and provide theoretical basis for determining new prognostic markers of UM and immunotherapy.

Dataset Information

Identification of an Immunogenic Subset of Metastatic Uveal Melanoma.

Publications

Identification of an Immunogenic Subset of Metastatic Uveal Melanoma.

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