Screening a novel signature and predicting the immune landscape of metastatic osteosarcoma in children via immune-related lncRNAs

Wei, Jie; Fang, Dalang; Huang, Cheng Kua; Hua, Shuliang; Lu, Xiaosheng

doi:10.21037/tp-21-226

Cited by 7 publications

(4 citation statements)

References 49 publications

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“…Three lncRNAs ( AC092171.5, MEG9, and AC002091.1 ) were screened for subsequent analysis. Guyugang et al ( Guo et al, 2021 ) found that AC092171.5 was expressed at lower levels in patients with high-risk lung adenocarcinoma, and Wei et al ( Wei et al, 2021 ) found that patients with high AC002091.1 expression in osteosarcoma had a better prognosis. In our study, MEG9 , AC092171.5 , and AC002091.1 were highly expressed in low-risk patients; these three lncRNAs may suppress pancreatic adenocarcinogenesis.…”

Section: Discussionmentioning

confidence: 99%

Prognostic Value of Drug Targets Predicted Using Deep Bioinformatic Analysis of m6A-Associated lncRNA-Based Pancreatic Cancer Model Characteristics and Its Tumour Microenvironment

Cao

Liu

et al. 2022

Front. Genet.

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The role of N6-methyladenosine (m6A)-associated long-stranded non-coding RNA (lncRNA) in pancreatic cancer is unclear. Therefore, we analysed the characteristics and tumour microenvironment in pancreatic cancer and determined the value of m6A-related lncRNAs for prognosis and drug target prediction. An m6A-lncRNA co-expression network was constructed using The Cancer Genome Atlas database to screen m6A-related lncRNAs. Prognosis-related lncRNAs were screened using univariate Cox regression; patients were divided into high- and low-risk groups and randomised into training and test groups. In the training group, least absolute shrinkage and selection operator (LASSO) was used for regression analysis and to construct a prognostic model, which was validated in the test group. Tumor mutational burden (TMB), immune evasion, and immune function of risk genes were analysed using R; drug sensitivity and potential drugs were examined using the Genomics of Drug Sensitivity in Cancer database. We screened 129 m6A-related lncRNAs; 17 prognosis-related m6A-related lncRNAs were obtained using multivariate analysis and three m6A-related lncRNAs (AC092171.5, MEG9, and AC002091.1) were screened using LASSO regression. Survival rates were significantly higher (p < 0.05) in the low-risk than in the high-risk group. Risk score was an independent predictor affecting survival (p < 0.001), with the highest risk score being obtained by calculating the c-index. The TMB significantly differed between the high- and low-risk groups (p < 0.05). In the high- and low-risk groups, mutations were detected in 61 of 70 samples and 49 of 71 samples, respectively, with KRAS, TP53, and SMAD4 showing the highest mutation frequencies in both groups. A lower survival rate was observed in patients with a high versus low TMB. Immune function HLA, Cytolytic activity, and Inflammation-promoting, T cell co-inhibition, Check-point, and T cell co-stimulation significantly differed in different subgroups (p < 0.05). Immune evasion scores were significantly higher in the high-risk group than in the low-risk group. Eight sensitive drugs were screened: ABT.888, ATRA, AP.24534, AG.014699, ABT.263, axitinib, A.443654, and A.770041. We screened m6A-related lncRNAs using bioinformatics, constructed a prognosis-related model, explored TMB and immune function differences in pancreatic cancer, and identified potential therapeutic agents, providing a foundation for further studies of pancreatic cancer diagnosis and treatment.

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Section: Discussionmentioning

confidence: 99%

Prognostic Value of Drug Targets Predicted Using Deep Bioinformatic Analysis of m6A-Associated lncRNA-Based Pancreatic Cancer Model Characteristics and Its Tumour Microenvironment

Cao

Liu

et al. 2022

Front. Genet.

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“…Wei et al. ( 64 ) detected a correlation between immune-related genes and long noncoding RNAs to compare the different landscapes of immune-related long noncoding RNA pairs in localized and metastatic osteosarcoma. A significant difference in immune infiltration was observed between localized and metastatic osteosarcoma, and the high abundance of activated MCs indicated unsatisfactory outcomes.…”

Section: Cellsmentioning

confidence: 99%

Immune Microenvironment in Osteosarcoma: Components, Therapeutic Strategies and Clinical Applications

et al. 2022

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Osteosarcoma is a primary malignant tumor that tends to threaten children and adolescents, and the 5-year event-free survival rate has not improved significantly in the past three decades, bringing grief and economic burden to patients and society. To date, the genetic background and oncogenesis mechanisms of osteosarcoma remain unclear, impeding further research. The tumor immune microenvironment has become a recent research hot spot, providing novel but valuable insight into tumor heterogeneity and multifaceted mechanisms of tumor progression and metastasis. However, the immune microenvironment in osteosarcoma has been vigorously discussed, and the landscape of immune and non-immune component infiltration has been intensively investigated. Here, we summarize the current knowledge of the classification, features, and functions of the main infiltrating cells, complement system, and exosomes in the osteosarcoma immune microenvironment. In each section, we also highlight the complex crosstalk network among them and the corresponding potential therapeutic strategies and clinical applications to deepen our understanding of osteosarcoma and provide a reference for imminent effective therapies with reduced adverse effects.

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“…CCR5AS is an immune-related lncRNA which has important value in the prognosis of melanoma [24]. The expression of AC002091.1 is correlated with the prognosis of metastatic osteosarcoma in children [25]. TRG−AS1 has been shown to be an important driver of cancer development in hepatocellular carcinoma, lung cancer, and tongue squamous cell carcinoma [26][27][28].…”

Section: Discussionmentioning

confidence: 99%

Construction of a Novel kidney renal clear cell carcinoma microenvironment-related lncRNA pair Signature

Gou

et al. 2022

Preprint

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Background: Kidney Renal clear cell carcinoma (KIRC) is a malignant neoplasm originating in the tubular epithelium and is the most common pathologic type of renal carcinoma, accounting for approximately 80% of cases. Tumor microenvironment (TME) has been proved to play a key role in the development of tumor, including KIRC. A number of studies have focused on tumor TME-related genes, but have ignored the key role of TME-related lncRNAs in disease. Method:In this article, we obtained 6 TME-related genes by using ESTIMATE and CIBERSORT computational methods from 611 cases which are downloaded from the TCGA Kidney Renal Clear Cell Carcinoma database. And then we performed coexpression analysis between 6 TME-related genes and lncRNAs to find differently expressed TME-related lncRNAs(TMErlncRNAs). The matrix of TMErlncRNA pairs was established by a cyclic comparison of each lncRNA pair expression level. Univariate and multivariate Cox regressions and LASSO regression analysis were used to construct the hazard model. We have sifted 10 lncRNA pairs that were included in this model. TCGA cohort was divided into high- and low-risk groups, according to the Akaike Information Criterion (AIC) values of the receiver operating characteristic (ROC) curve. Then, we tested and verified our model through various clinical settings: tumor-infiltrating immune cells, clinical-pathological characteristics and reactiveness to immunotherapy. Results: Based on the 6 differently expressed TME-related genes, we sifted and constructed a 10-TME-related lncRNA pair signature. The area under the receiver operator characteristic (ROC) curve (AUC) of the signature was 0. 766, showing a promising prediction value for KIRC, and the cut-off point was recognized as 0. 862. Subsequent analysis showed that our signature is closely associated with clinical pathological characteristics, overall survival, specify tumor infiltration status, and reactiveness to immunotherapy in patients with KIRC. Conclusion: We constructed a novel kidney renal clear cell carcinoma TME-related lncRNA pair signature with promising clinical prediction value in KIRC, which might provide new insights for clinical decision-making and precision medicine.

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Screening a novel signature and predicting the immune landscape of metastatic osteosarcoma in children via immune-related lncRNAs

Cited by 7 publications

References 49 publications

Prognostic Value of Drug Targets Predicted Using Deep Bioinformatic Analysis of m6A-Associated lncRNA-Based Pancreatic Cancer Model Characteristics and Its Tumour Microenvironment

Prognostic Value of Drug Targets Predicted Using Deep Bioinformatic Analysis of m6A-Associated lncRNA-Based Pancreatic Cancer Model Characteristics and Its Tumour Microenvironment

Immune Microenvironment in Osteosarcoma: Components, Therapeutic Strategies and Clinical Applications

Construction of a Novel kidney renal clear cell carcinoma microenvironment-related lncRNA pair Signature

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