Dataset Information

Identification and validation of immunogenic cell death-related score in uveal melanoma to improve prediction of prognosis and response to immunotherapy.

ABSTRACT:

Background

Immunogenic cell death (ICD) could activate innate and adaptive immune response. In this work, we aimed to develop an ICD-related signature in uveal melanoma (UVM) patients and facilitate assessment of their prognosis and immunotherapy.

Methods

A set of machine learning methods, including non-negative matrix factorization (NMF) method and least absolute shrinkage and selection operator (LASSO) logistic regression model, and bioinformatics analytic tools were integrated to construct an ICD-related risk score (ICDscore). CIBERSORT and ESTIMATE algorithms were used to evaluate the infiltration of immune cells. The Genomics of Drug Sensitivity in Cancer (GDSC), cellMiner and tumor immune dysfunction and exclusion (TIDE) databases were used for therapy sensitivity analyses. The predictive performance between ICDscore with other mRNA signatures was also compared.

Results

The ICDscore could predict the prognosis of UVM patients in both the training and four validating cohorts. The ICDscore outperformed 19 previously published signatures. Patients with high ICDscore exhibited a substantial increase in immune cell infiltration and expression of immune checkpoint inhibitor-related genes, leading to a higher response rate to immunotherapy. Furthermore, the downregulation of poly (ADP-ribose) polymerase family member 8 (PARP8), a critical gene involved in the development of the ICDscore, resulted in decreased cell proliferation and slower migration of UVM cells.

Conclusion

In conclusion, we developed a robust and powerful ICD-related signature for evaluating the prognosis and benefits of immunotherapy that could serve as a promising tool to guide decision-making and surveillance for UVM patients.

SUBMITTER: Li X

PROVIDER: S-EPMC10449274 | biostudies-literature | 2023 May

REPOSITORIES: biostudies-literature

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Publications

Identification and validation of immunogenic cell death-related score in uveal melanoma to improve prediction of prognosis and response to immunotherapy.

Li Xiaoyan X Kang Jing J Yue Jing J Xu Dawei D Liao Chunhua C Zhang Huina H Zhao Jin J Liu Qiongwen Q Jiao Jinke J Wang Lin L Li Guoyin G

Aging 20230503 9

<h4>Background</h4>Immunogenic cell death (ICD) could activate innate and adaptive immune response. In this work, we aimed to develop an ICD-related signature in uveal melanoma (UVM) patients and facilitate assessment of their prognosis and immunotherapy.<h4>Methods</h4>A set of machine learning methods, including non-negative matrix factorization (NMF) method and least absolute shrinkage and selection operator (LASSO) logistic regression model, and bioinformatics analytic tools were integrated ...[more]

PMID: 37142279

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Project description:IntroductionUveal melanoma (UM) is the most common primary intraocular malignant tumor in adults, and the main treatment for UM is currently surgery and plaque brachytherapy. UM is highly susceptible to metastasis, which eventually occurs in nearly half of all patients; once metastasis occurs, patients have a poor prognosis and the condition is difficult to treat. Therefore, the identification of new and effective UM biomarkers is vital for the application of therapeutic strategies. Immunogenic cell death (ICD) is a type of regulatory cell death that activates adaptive immune responses and generates long-term immunological memory. ICD can promote antitumor immunity, which may be a potential immunotherapeutic strategy for UM.MethodsThe data of UM from the Cancer Genome Atlas (TCGA) was used as a training set and the data from Gene Expression Omnibus (GEO) was used as a validation set. To determine the expression pattern of ICD-related genes in UM, survival analysis and difference analysis was conducted. The ICD-related risk signature was constructed by employing the least absolute shrinkage and selection operator (LASSO) Cox regression. Subsequently, immune profile and somatic mutation analysis were performed. In addition, cell experiments were performed to verify the role of immunogenic cell death-related genes in UM.ResultsIn this study, we analyzed the relationship between ICD-related gene expression and UM patient prognosis, somatic mutations, and the tumor immune microenvironment. Importantly, we constructed a 5-gene ICD-related risk signature and confirmed it as a novel prognostic biomarker in UM patients. We found that the high-risk group had more immune cell infiltration and a worse prognosis than the low-risk group. In cellular experiments, we confirmed the high expression of FOXP3 inMUM2B andOCM-1A cell lines and that knockdown of FOXP3 markedly inhibited the proliferation of UM tumor cells.DiscussionICD-related genes play a critical role in the tumor immune microenvironment. Our results may contribute to the development of effective immunotherapies.

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.

Project description:PurposeUveal 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 designWe 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.ResultsDespite 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.ConclusionsThe 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.

Dataset Information

Identification and validation of immunogenic cell death-related score in uveal melanoma to improve prediction of prognosis and response to immunotherapy.

Background

Methods

Results

Conclusion

Publications

Identification and validation of immunogenic cell death-related score in uveal melanoma to improve prediction of prognosis and response to immunotherapy.

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