Development of a novel immune-related lncRNA signature as a prognostic classifier for endometrial carcinoma

Liu, Jinhui; Mei, Jie; Wang, Yichun; Chen, Xucheng; Pan, Jiadong; Tong, Laigen; Zhang, Yan

doi:10.7150/ijbs.51207

Cited by 29 publications

(31 citation statements)

References 32 publications

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“…In severe aplastic anemia (SAA) patients, the decreased expression of AF117829.1 upregulates the activity of CD8 + T lymphocytes, which means lncRNA may be associated with the regulation of the immune microenvironment ( Li et al, 2021 ). POC1B-AS1 is also a risk factor in the prognostic model of endometrial carcinoma ( Liu J. et al, 2021 ). In psoriasis, CCDC18-AS1, regarded as immune-related lncRNA, can be a potential diagnostic biomarker ( Fan et al, 2021 ).…”

Section: Discussionmentioning

confidence: 99%

A Prognostic Pyroptosis-Related lncRNAs Risk Model Correlates With the Immune Microenvironment in Colon Adenocarcinoma

Xia

Yan

Shen

2021

Front. Cell Dev. Biol.

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Recent studies have indicated that long non-coding RNAs (lncRNAs) may participate in the regulation of tumor cell proptosis. However, the connection between lncRNA expression and pyroptosis remains unclear in colon adenocarcinoma (COAD). This study aims to explore and establish a prognostic signature of COAD based on the pyroptosis-related lncRNAs. We identify 15 prognostic pyroptosis-related lncRNAs (ZNF667-AS1, OIP5-AS1, AL118506.1, AF117829.1, POC1B-AS1, CCDC18-AS1, THUMPD3-AS1, FLNB-AS1, SNHG11, HCG18, AL021707.2, UGDH-AS1, LINC00641, FGD5-AS1 and AC245452.1) from the TCGA-COAD dataset and use them to construct the risk model. After then, this pyroptosis-related lncRNA signature is validated in patients from the GSE17536 dataset. The COAD patients are divided into low-risk and high-risk groups by setting the median risk score as the cut-off point and represented differences in the immune microenvironment. Hence, we construct the immune risk model based on the infiltration levels of ssGSEA immune cells. Interestingly, the risk model and immune risk model are both independent prognostic risk factors. Therefore, a nomogram combined risk score, immune risk score with clinical information which is meaningful in univariate and multivariate Cox regression analysis is established to predict the overall survival (OS) of COAD patients. In general, the signature consisted of 15 pyroptosis-related lncRNAs and was proved to be associated with the immune landscape of COAD patients.

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Section: Discussionmentioning

confidence: 99%

A Prognostic Pyroptosis-Related lncRNAs Risk Model Correlates With the Immune Microenvironment in Colon Adenocarcinoma

Xia

Yan

Shen

2021

Front. Cell Dev. Biol.

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“…Previously, for example, Dong et al developed a 7-lncRNA signature for predicting UCEC prognosis; 24 Liu et al identified 13 immune-related lncRNAs closely related to UCEC overall survival. 25 For now, no molecular subtyping system based on immunerelated lncRNAs has been reported.…”

Section: Impact Statementmentioning

confidence: 99%

Identifying immune subtypes of uterine corpus endometrial carcinoma and a four-paired-lncRNA signature with immune-related lncRNAs

Zeng

2021

Exp Biol Med (Maywood)

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Uterine corpus endometrial carcinoma (UCEC) is the third most frequent gynecological malignancies in the female reproductive system. Long non-coding RNAs (lncRNAs) are closely involved in tumor progression. This study aimed to develop an immune subtyping system and a prognostic model based on lncRNAs for UCEC. Paired lncRNAs and non-negative matrix factorization were applied to identify immune subtypes. Enrichment analysis was conducted to assess functional pathways, immune-related genes, and cells. Univariate and multivariate Cox regression analysis were performed to analyze the relation between lncRNAs and overall survival (OS). A prognostic model was constructed and optimized by least absolute shrinkage and selection operator (LASSO) and Akaike information criterion (AIC). Two immune subtypes (C1 and C2) and four paired-prognostic lncRNAs closely associated with overall survival were identified. Some immune features, sensitivity of chemotherapy and immunotherapy, and the relation with immune escape showed variations between two subtypes. A nomogram established based on prognostic model and clinical features was effective in OS prediction. The immune subtyping system based on lncRNAs and the four-paired-lncRNA signature was predictive of UCEC prognosis and can facilitate personalized therapies such as immunotherapy or RNA-based therapy for UCEC patients.

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“…[13]. [14], [15].In this study, we constructed for the rst time a lncRNA model including 8 immune-related lncRNAs, and veri ed the accuracy of this model as a marker for the survival status of soft tissue sarcoma. First, we analyzed the transcriptome data of TCGA SARC and obtained the lncRNA co-expressed with immune genes.…”

Section: Discussionmentioning

confidence: 96%

Establishment of a 8 Immune-Related LncRNA Signature for Predicting the Prognosis of Soft Tissue Sarcoma

Liu

2021

Preprint

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Background: Soft tissue sarcoma is relatively rare and highly heterogeneous, which brings great difficulties to treatment. Long non-coding RNA acts a vital role in the occurrence and progression of soft tissue sarcoma, especially in the tumor-related immune process, which has become a hot spot of current research. Therefore, we are committed to developing lncRNA markers related to immunity to promote the treatment and prognosis of patients with soft tissue sarcoma.Methods：Based on the TCGA-SARC and GTEx data set, we screened out 8 prognostic-related immune lncRNAs and constructed a nomogram, which was verified in the test set. Furthermore, immune infiltration analysis was carried out on patients of high and low risk.Results: Based on the results of Pearson's correlation coefficient, we obtained 859 immune-related lncRNAs. After difference analysis, we finally determined 54 different lncRNAs. Univariate and multivariate cox regression analysis finally determined 8 immune-related lncRNAs to construct prognostic models and nomograms to predict the prognosis of STS patients. The above results have been verified in external data sets, indicating that this model has good predictive ability. Gene Set Enrichment Analysis and ESTIMATE analysis showed obviously differences exist in the immune infiltration status and immune cell subtypes of high- and low-risk patients.Conclusion: We constructed an immune-related lncRNA pattern to predict the survival status of soft tissue sarcoma patients.

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Development of a novel immune-related lncRNA signature as a prognostic classifier for endometrial carcinoma

Cited by 29 publications

References 32 publications

A Prognostic Pyroptosis-Related lncRNAs Risk Model Correlates With the Immune Microenvironment in Colon Adenocarcinoma

A Prognostic Pyroptosis-Related lncRNAs Risk Model Correlates With the Immune Microenvironment in Colon Adenocarcinoma

Identifying immune subtypes of uterine corpus endometrial carcinoma and a four-paired-lncRNA signature with immune-related lncRNAs

Establishment of a 8 Immune-Related LncRNA Signature for Predicting the Prognosis of Soft Tissue Sarcoma

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