Identification of survival-related genes and a novel gene-based prognostic signature involving the tumor microenvironment of uveal melanoma

Lei, Shizhen; Zhang, Yi

doi:10.1016/j.intimp.2021.107816

Cited by 6 publications

(6 citation statements)

References 54 publications

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“…8 D). High-risk UMs were with worse prognosis and higher infiltrating levels of T cells CD8 and T cells gamma delta, indicating that the bad prognosis was might be partly caused by the high infiltration of these two types of immune cells, which was consistent with previous studies [ 34 , 35 ]. Notably, EEF1A2 was slightly positively correlated with T cells gamma delta and T cells CD8, whereas CTNNB1 was slightly negatively correlated with T cells CD8 and T cells gamma delta ( P < 0.05) (Additional file 2 : Figure S1).…”

Section: Resultssupporting

confidence: 91%

“…Moreover, T cells CD8 and T cells gamma delta infiltration levels were significantly higher in high-risk UM samples than low-risk ones ( P < 0.05). Consistent with previous reports [ 34 , 35 ], T cells gamma delta and T cells CD8 were identified to be related to poor prognosis in UM patients. The results indicated that the poor prognosis of high-risk patients might be partly caused by the high infiltration levels of T cells gamma delta and T cells CD8.…”

Section: Discussionsupporting

confidence: 91%

“…In the past five years, several studies tried to identify essential genes involved in the development of UM [ 29 , 31 , 32 , 34 , 35 , 52 – 54 ]. These studies identified different aspects of UM such as clinical and pathological status along with the TME.…”

Section: Discussionmentioning

confidence: 99%

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Integrative analysis identifies key genes related to metastasis and a robust gene-based prognostic signature in uveal melanoma

Lei

Zhang

2022

BMC Med Genomics

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Purpose Uveal melanoma (UM) is an aggressive intraocular malignancy, leading to systemic metastasis in half of the patients. However, the mechanism of the high metastatic rate remains unclear. This study aimed to identify key genes related to metastasis and construct a gene-based signature for better prognosis prediction of UM patients. Methods Weighted gene co-expression network analysis (WGCNA) was used to identify the co-expression of genes primarily associated with metastasis of UM. Univariate, Lasso-penalized and multivariate Cox regression analyses were performed to establish a prognostic signature for UM patients. Results The tan and greenyellow modules were significantly associated with the metastasis of UM patients. Significant genes related to the overall survival (OS) in these two modules were then identified. Additionally, an OS-predicting signature was established. The UM patients were divided into a low- or high-risk group. The Kaplan–Meier curve indicated that high-risk patients had poorer OS than low-risk patients. The receiver operating curve (ROC) was used to validate the stability and accuracy of the final five-gene signature. Based on the signature and clinical traits of UM patients, a nomogram was established to serve in clinical practice. Conclusions We identified key genes involved in the metastasis of UM. A robust five-gene‐based prognostic signature was constructed and validated. In addition, the gene signature-based nomogram was created that can optimize the prognosis prediction and identify possible factors causing the poor prognosis of high-risk UM patients.

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Section: Resultssupporting

confidence: 91%

Section: Discussionsupporting

confidence: 91%

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Integrative analysis identifies key genes related to metastasis and a robust gene-based prognostic signature in uveal melanoma

Lei

Zhang

2022

BMC Med Genomics

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“…The inflammatory phenotype of the uveal melanoma, the most common primary ocular cancer in adults, is associated with a poor outcome, correlated to a greater number of inflammatory cells populating mainly epithelioid-cell-type tumours, characterized by chromosome 3 loss [ 181 ], while the main population in its inflammatory milieu is represented by CD8+ T cells and macrophages [ 182 ].…”

Section: Inflammatory Microenvironment In Malignant Melanomamentioning

confidence: 99%

“…Moreover, variant D has an increased metastatic potential and several specific genetic aberrations (monosomy 3, chromosome 8q gain, and BAP1 loss), which seem to be correlated with its specific inflammatory phenotype [ 186 , 187 ]. Recent data regarding the specific immunological and genetic profile of uveal melanoma TME provide a gene-based prognostic signature, with possible impact on prognosis and on targeted therapy perspectives related to metastasis prevention [ 182 ].…”

Section: Inflammatory Microenvironment In Malignant Melanomamentioning

confidence: 99%

The Interplay between Tumour Microenvironment Components in Malignant Melanoma

et al. 2022

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Malignant melanoma has shown an increasing incidence during the last two decades, exhibiting a large spectrum of locations and clinicopathological characteristics. Although current histopathological, biochemical, immunohistochemical, and molecular methods provide a deep insight into its biological behaviour and outcome, melanoma is still an unpredictable disease, with poor outcome. This review of the literature is aimed at updating the knowledge regarding melanoma’s clinicopathological and molecular hallmarks, including its heterogeneity and plasticity, involving cancer stem cells population. A special focus is given on the interplay between different cellular components and their secretion products in melanoma, considering its contribution to tumour progression, invasion, metastasis, recurrences, and resistance to classical therapy. Furthermore, the influences of the specific tumour microenvironment or “inflammasome”, its association with adipose tissue products, including the release of “extracellular vesicles”, and distinct microbiota are currently studied, considering their influences on diagnosis and prognosis. An insight into melanoma’s particular features may reveal new molecular pathways which may be exploited in order to develop innovative therapeutic approaches or tailored therapy.

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Immunogenic profiling of metastatic uveal melanoma discerns a potential signature related to prognosis

Wang,

Liu,

Sun

et al. 2024

J Cancer Res Clin Oncol

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Background Uveal 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. Methods Two 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. Results The 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. Significance UM 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.

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Identification of survival-related genes and a novel gene-based prognostic signature involving the tumor microenvironment of uveal melanoma

Cited by 6 publications

References 54 publications

Integrative analysis identifies key genes related to metastasis and a robust gene-based prognostic signature in uveal melanoma

Integrative analysis identifies key genes related to metastasis and a robust gene-based prognostic signature in uveal melanoma

The Interplay between Tumour Microenvironment Components in Malignant Melanoma

Immunogenic profiling of metastatic uveal melanoma discerns a potential signature related to prognosis

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