Dataset Information

SLC25A25-AS1 over-expression could be predicted the dismal prognosis and was related to the immune microenvironment in prostate cancer.

ABSTRACT: It has been established that long-chain coding RNA (lncRNA) SLC25A25-AS1 is associated with cancer progression. However, the roles and mechanisms of SLC25A25-AS1 in prostate cancer (PC) have not been reported in the literature. The present study explored the relationship between SLC25A25-AS1 expression and PC progression via comprehensive analysis. The pan-cancer expression of SLC25A25-AS1 was identified using data from The Cancer Genome Atlas (TCGA) database and tissue specimens from our hospital. The expression levels of SLC25A25-AS1 in various subgroups based on the clinical features were identified. The prognostic value of SLC25A25-AS1 and SLC25A25-AS1 co-expressed lncRNAs in PC patients was assessed by survival analysis and ROC analysis, and prognosis-related risk models of SLC25A25-AS1 were constructed. The relationship between SLC25A25-AS1 and the PC immune microenvironment was investigated using correlation analysis. SLC25A25-AS1 expression in PC was significantly increased and correlated with the T stage, clinical stage, Gleason score (GS), and dismal prognosis. SLC25A25-AS1 overexpression exhibited good performance in evaluating the prognosis of PC patients. The area under the curves (AUCs) of the 1-, 3-, and 5-year overall survival (OS) for SLC25A25-AS1 was 1, 0.876, and 0.749. Moreover, the AUCs for the 1-, 3-, and 5-year progress free interval (PFI) for SLC25A25-AS1 were 0.731, 0.701, and 0.718. SLC25A25-AS1 overexpression correlated with the infiltration of CD8 T cells, interstitial dendritic cells (IDC), macrophages and other cells. AC020558.2, ZNF32-AS2, AP4B1-AS1, AL355488.1, AC109460.3, SNHG1, C3orf35, LMNTD2-AS1, and AL365330.1 were significantly associated with SLC25A25-AS1 expression, and short OS and PFI in PC patients. The risk models of the SLC25A25-AS1-related lncRNAs were associated with a dismal prognosis in PC. Overall, SLC25A25-AS1 expression was increased in PC and related to the prognosis and PC immune microenvironment. The risk model of SLC25A25-AS1 have huge prospect for application as prognostic tools in PC.

SUBMITTER: Zhao YY

PROVIDER: S-EPMC9632290 | biostudies-literature | 2022

REPOSITORIES: biostudies-literature

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SLC25A25-AS1 over-expression could be predicted the dismal prognosis and was related to the immune microenvironment in prostate cancer.

Zhao Ying-Ying YY Xiang Qian-Ming QM Chen Jia-Li JL Zhang Li L Zheng Wei-Long WL Ke Di D Shi Rong-Shu RS Yang Kong-Wu KW

Frontiers in oncology 20221020

It has been established that long-chain coding RNA (lncRNA) SLC25A25-AS1 is associated with cancer progression. However, the roles and mechanisms of SLC25A25-AS1 in prostate cancer (PC) have not been reported in the literature. The present study explored the relationship between SLC25A25-AS1 expression and PC progression <i>via</i> comprehensive analysis. The pan-cancer expression of SLC25A25-AS1 was identified using data from The Cancer Genome Atlas (TCGA) database and tissue specimens from our ...[more]

PMID: 36338724

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Project description:BackgroundCuproptosis plays a crucial role in cancer, and different subtypes of cuproptosis have different immune profiles in prostate adenocarcinoma (PRAD). This study aimed to investigate immune genes associated with cuproptosis and develop a risk model to predict prognostic characteristics and chemotherapy/immunotherapy responses of patients with PRAD.MethodsThe CIBERSORT algorithm was used to evaluate the immune and stromal scores of patients with PRAD in The Cancer Genome Atlas (TCGA) cohort. Validation of differentially expressed genes DLAT and DLD in benign and malignant tissues by immunohistochemistry, and the immune-related genes of DLAT and DLD were further screened. Univariable Cox regression were performed to select key genes. Least absolute shrinkage and selection operator (LASSO)-Cox regression analyse was used to develop a risk model based on the selected genes. The model was validated in the TCGA, Memorial Sloan-Kettering Cancer Center (MSKCC) and Gene Expression Omnibus (GEO) datasets, as well as in this study unit cohort. The genes were examined via functional enrichment analysis, and the tumor immune features, tumor mutation features and copy number variations (CNVs) of patients with different risk scores were analysed. The response of patients to multiple chemotherapeutic/targeted drugs was assessed using the pRRophetic algorithm, and immunotherapy was inferred by the Tumor Immune Dysfunction and Exclusion (TIDE) and immunophenoscore (IPS).ResultsCuproptosis-related immune risk scores (CRIRSs) were developed based on PRLR, DES and LECT2. High CRIRSs indicated poor overall survival (OS), disease-free survival (DFS) in the TCGA-PRAD, MSKCC and GEO datasets and higher T stage and Gleason scores in TCGA-PRAD. Similarly, in the sample collected by the study unit, patients with high CRIRS had higher T-stage and Gleason scores. Additionally, higher CRIRSs were negatively correlated with the abundance of activated B cells, activated CD8+ T cells and other stromal or immune cells. The expression of some immune checkpoints was negatively correlated with CRIRSs. Tumor mutational burden (TMB), mutant-allele tumor heterogeneity (MATH) and copy number variation (CNV) scores were all higher in the high-CRIRS group. Multiple chemotherapeutic/targeted drugs and immunotherapy had better responsiveness in the low-CRIRS group.ConclusionOverall, lower CRIRS indicated better response to treatment strategies and better prognostic outcomes.

Project description:Background: Abnormal expression of lncRNA is closely related to the occurrence and metastasis of osteosarcoma. The tumor immune microenvironment (TIM) is considered to be an important factor affecting the prognosis and treatment of osteosarcoma. This study aims to explore the effect of immune-related lncRNAs (IRLs) on the prognosis of osteosarcoma and its relationship with the TIM. Methods: Ninety-five osteosarcoma samples from the TARGET database were included. Iterative LASSO regression and multivariate Cox regression analysis were used to screen the IRLs signature with the optimal AUC. The predict function was used to calculate the risk score and divide osteosarcoma into a high-risk group and low-risk group based on the optimal cut-off value of the risk score. The lncRNAs in IRLs signature that affect metastasis were screened for in vitro validation. Single sample gene set enrichment analysis (ssGSEA) and ESTIMATE algorithms were used to evaluate the role of TIM in the influence of IRLs on osteosarcoma prognosis. Results: Ten IRLs constituted the IRLs signature, with an AUC of 0.96. The recurrence and metastasis rates of osteosarcoma in the high-risk group were higher than those in the low-risk group. In vitro experiments showed that knockdown of lncRNA (AC006033.2) could increase the proliferation, migration, and invasion of osteosarcoma. ssGSEA and ESTIMATE results showed that the immune cell content and immune score in the low-risk group were generally higher than those in the high-risk group. In addition, the expression levels of immune escape-related genes were higher in the high-risk group. Conclusion: The IRLs signature is a reliable biomarker for the prognosis of osteosarcoma, and they alter the prognosis of osteosarcoma. In addition, IRLs signature and patient prognosis may be related to TIM in osteosarcoma. The higher the content of immune cells in the TIM of osteosarcoma, the lower the risk score of patients and the better the prognosis. The higher the expression of immune escape-related genes, the lower the risk score of patients and the better the prognosis.

Dataset Information

SLC25A25-AS1 over-expression could be predicted the dismal prognosis and was related to the immune microenvironment in prostate cancer.

Publications

SLC25A25-AS1 over-expression could be predicted the dismal prognosis and was related to the immune microenvironment in prostate cancer.

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