Identification of Angiogenesis-Related Prognostic Biomarkers Associated With Immune Cell Infiltration in Breast Cancer

Tao, Dan; Wang, Ying; Zhang, Xin; Wang, Can; Yang, Dan; Chen, Jing; Long, Yanyan; Jiang, Yong; Zhou, Xian

doi:10.3389/fcell.2022.853324

Cited by 12 publications

(11 citation statements)

References 66 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Angiogenesis is the process of germination from existing blood vessels to form new ones, which plays a crucial role in the carcinogenesis of lung adenocarcinoma ( Wang Y. et al, 2019 ). Numerous studies have shown the prognostic value of ARGs in cancer ( Zheng et al, 2021 ; Cai et al, 2022 ; Tao et al, 2022 ), where Sun et al found that POSTN may ultimately affect the prognosis of patients with LUAD by altering the immune microenvironment ( Sun et al, 2022 ), and in our study, 55 ARGs associated with LUAD were obtained from 549 samples in the TCGA database. In addition, we also identified LUAD-related DE-lncRNAs and obtained 50 LUAD-related DE-lncRNAs.…”

Section: Discussionmentioning

confidence: 62%

Construction and validation of an angiogenesis-related lncRNA prognostic model in lung adenocarcinoma

et al. 2023

View full text Add to dashboard Cite

Background: There is increasing evidence that long non-coding RNAs (lncRNAs) can be used as potential prognostic factors for cancer. This study aimed to develop a prognostic model for lung adenocarcinoma (LUAD) using angiogenesis-related long non-coding RNAs (lncRNAs) as potential prognostic factors.Methods: Transcriptome data from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) were analyzed to identify aberrantly expressed angiogenesis-related lncRNAs in LUAD. A prognostic signature was constructed using differential expression analysis, overlap analysis, Pearson correlation analysis, and Cox regression analysis. The model’s validity was assessed using K-M and ROC curves, and independent external validation was performed in the GSE30219 dataset. Prognostic lncRNA-microRNA (miRNA)-messenger RNA (mRNA) competing endogenous RNA (ceRNA) networks were identified. Immune cell infiltration and mutational characteristics were also analyzed. The expression of four human angiogenesis-associated lncRNAs was quantified using quantitative real-time PCR (qRT-PCR) gene arrays.Results: A total of 26 aberrantly expressed angiogenesis-related lncRNAs in LUAD were identified, and a Cox risk model based on LINC00857, RBPMS-AS1, SYNPR-AS1, and LINC00460 was constructed, which may be an independent prognostic predictor for LUAD. The low-risk group had a significant better prognosis and was associated with a higher abundance of resting immune cells and a lower expression of immune checkpoint molecules. Moreover, 105 ceRNA mechanisms were predicted based on the four prognostic lncRNAs. qRT-PCR results showed that LINC00857, SYNPR-AS1, and LINC00460 were significantly highly expressed in tumor tissues, while RBPMS-AS1 was highly expressed in paracancerous tissues.Conclusion: The four angiogenesis-related lncRNAs identified in this study could serve as a promising prognostic biomarker for LUAD patients.

show abstract

Section: Discussionmentioning

confidence: 62%

Construction and validation of an angiogenesis-related lncRNA prognostic model in lung adenocarcinoma

et al. 2023

View full text Add to dashboard Cite

show abstract

“…In most tumors, microvascular formation is a prognostic marker for metastasis, recurrence, and survival [ 24 , 25 ]. Angiogenesis-related genes have been reported to be potential prognostic markers associated with BC, and integrating these genes has important implications for understanding and assessing tumor progression [ 1 , 26 , 27 , 28 , 29 , 30 ]. Among these genes, lncRNAs also play an essential role [ 26 , 28 , 31 ].…”

Section: Discussionmentioning

confidence: 99%

“…The construction of risk models for angiogenesis-related genes has been reported in BC; for example, Tao et al [ 30 ]. constructed a risk model consisting of four angiogenesis genes (TNFSF12, SCG2, COL4A3, and TNNI3) which showed good predictive performance in the prognosis of BC patients.…”

Section: Discussionmentioning

confidence: 99%

An Angiogenesis-Related lncRNA Signature Is Associated with Prognosis and Tumor Immune Microenvironment in Breast Cancer

Gao

Wang

et al. 2023

JPM

View full text Add to dashboard Cite

Angiogenesis is crucial in the development and progression of tumors. This study examined the relationship between angiogenesis-related lncRNAs (AR-lncRNAs) and breast cancer (BC) immunity and prognosis. We used univariate Cox regression analysis to obtain AR-lncRNAs closely related to BC prognosis. Cluster analysis of BC patients was performed using non-negative matrix factorization (NMF) analysis according to the expression of AR-lncRNAs that were prognostically relevant. An AR-lncRNA risk model (AR-lncM) was created using LASSO regression analysis to predict the prognosis and survival of BC patients. Subsequently, the effect of LINC01614 on cell migration and invasion was verified by Transwell and Western blot assays, and the CCK-8 assay detected its impact on cell sensitivity to tamoxifen. Finally, we obtained 17 AR-lncRNAs from the TCGA database that were closely associated with the prognosis of BC patients. Based on the expression of these AR-lncRNAs, BC patients were divided into five clusters using NMF analysis. Cluster 1 was found to have a better prognosis, higher expression of immune checkpoints, and higher levels of immune cell infiltration. Furthermore, an AR-LncM model was created using ten prognostic-related AR-lncRNAs. The model’s risk predictive performance was validated using survival analysis, timeROC curves, and univariate and multivariate Cox analysis. The most interesting gene in the model, LINC01614, was found to regulate epithelial-mesenchymal transition (EMT) and tamoxifen sensitivity in BC cells, implying that LINC01614 could be a potential therapeutic target for BC patients.

show abstract

“…High RASGRP1 expression was demonstrated to be associated with a better prognosis in breast cancer [ 32 ]. It was found that SCG2 can predict prognosis in breast cancer [ 33 ], nonsmall cell lung cancer [ 34 ], and colorectal cancer [ 35 ]. Previous reports demonstrated that SCGB1A1 is a tumor suppressor that is downregulated in human lung cancer [ 36 – 38 ].…”

Section: Discussionmentioning

confidence: 99%

A Novel Inflammatory Response-Related Gene Signature Predicts Immune Status and Prognosis of Breast Cancer

Zhao

Xie

Gong

et al. 2022

Journal of Oncology

View full text Add to dashboard Cite

Purpose. Breast cancer is the most common type of cancer and the leading cause of cancer-related death in women worldwide. In this study, we aimed to construct an inflammatory response-related gene model for predicting the immune status and prognosis of breast cancer patients. Methods. We obtained the inflammatory response-related genes from the Molecular Signatures Database. Furthermore, we used univariate Cox regression analysis, the least absolute shrinkage and selection operator (LASSO) regression analysis, and multivariate Cox regression to construct an inflammatory response-related gene signature (IRGS) model based on dataset obtained from The Cancer Genome Atlas (TCGA). Patients were consequently categorized into high-risk and low-risk groups. Kaplan–Meier analysis was used to compare the overall survival (OS) of high-risk and low-risk groups. Following that, we validated the model using a dataset (GSE96058) acquired from Gene Expression Omnibus (GEO) database. Univariate and multivariate Cox analyses were used to determine the independent prognostic value of the IRGS in the TCGA and GSE96058 cohorts. A nomogram was constructed to predict the OS in the TCGA cohort. Further, we used Gene Set Enrichment Analysis (GSEA), CIBERSORT, and single-sample Gene Set Enrichment Analysis (ssGSEA) to evaluate the associations of IRGS with immune-associated pathways and immune infiltration. Finally, the relationship between the expression of the signature genes and drug sensitivity was conducted using Pearson correlation analysis. Results. We established an IRGS to stratify breast cancer patients into the low-risk and high-risk groups. In both the training and validation sets, patients in the high-risk group had significantly shorter OS than those in the low-risk group. The risk score was significantly correlated with the clinical characteristics and could be used as a tool to predict the prognosis of breast cancer. Moreover, we found that the IRGS risk score was an independent predictor of OS in breast cancer patients, and a nomogram model based on IRGS risk score and other clinical factors could effectively predict the prognosis of breast cancer patients. Furthermore, the IRGS risk score was correlated with immune characteristics and was inversely associated with the abundance of immune cell infiltration. Patients with a low IRGS risk score had higher expression levels of immune checkpoint genes, suggesting that IRGS can be used as a potential indicator for immunotherapy. Finally, we found that the expression levels of prognostic genes were significantly correlated with tumor cell sensitivity to chemotherapeutic drugs. Conclusion. Overall, these findings suggest that the IRGS can be used to predict the prognosis and immune status of breast cancer patients and provide new therapeutic targets for the treatment of these patients.

show abstract

Identification of Angiogenesis-Related Prognostic Biomarkers Associated With Immune Cell Infiltration in Breast Cancer

Cited by 12 publications

References 66 publications

Construction and validation of an angiogenesis-related lncRNA prognostic model in lung adenocarcinoma

Construction and validation of an angiogenesis-related lncRNA prognostic model in lung adenocarcinoma

An Angiogenesis-Related lncRNA Signature Is Associated with Prognosis and Tumor Immune Microenvironment in Breast Cancer

A Novel Inflammatory Response-Related Gene Signature Predicts Immune Status and Prognosis of Breast Cancer

Contact Info

Product

Resources

About