Characterization of Exosome-Related Gene Risk Model to Evaluate the Tumor Immune Microenvironment and Predict Prognosis in Triple-Negative Breast Cancer

Qiu, Pengjun; Guo, Qiao‐Nan; Yao, Qingzhi; Chen, Jianpeng; Lin, Jianqing

doi:10.3389/fimmu.2021.736030

Cited by 31 publications

(24 citation statements)

References 70 publications

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“…Different immune infiltrations can lead to different outcomes in tumors (43,44). For example, activated CD4 + memory T cell infiltration has been shown to be associated with poor prognosis and immune therapy response in several cancers (45,46), as have activated mast cells (47)(48)(49). This indicates that SLC2A1 might play a vital role in regulating the tumor immune microenvironment, and affects the prognosis of tumors by regulating infiltrating immune cells.…”

Section: Discussionmentioning

confidence: 99%

SLC2A1 plays a significant prognostic role in lung adenocarcinoma and is associated with tumor immunity based on bioinformatics analysis

Wang¹,

Wen²,

Sun³

2022

Ann Transl Med

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Background The treatment of lung adenocarcinoma (LUAD) has been stuck in a bottleneck due to a number of factors. There is a pressing need for research into potential genetic markers to help drug development and improve the prognosis of patients. SLC2A1 has been reported in multiple LUAD-related prognosis prediction signatures . However, the role of SLC2A1 in the occurrence and development of LUAD and its impact on prognosis remain elusive. Methods The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) were used to acquire the samples. We used R to perform statistical analysis, Gene Set Enrichment Analysis (GSEA), immune infiltration and immune cell correlation analysis, drug sensitivity analysis, and visualization. The immune cell score was calculated using the Timer2.0 database. Prognostic analysis was performed using R, Gene Expression Profiling Interactive Analysis (GEPIA), and the Kaplan-Meier Plotter. Overall survival and progression free survival were the main outcome of prognosis analysis. Protein-protein interaction, disease-genetics analysis, and tissue-specific enrichment analyses were performed using Metascape. Results SLC2A1 was highly expressed in LUAD tissues. Univariate COX regression [hazard ratio (HR) =1.689, 95% confidence interval (CI): 1.242–2.249, P<0.001] and multivariate COX regression including age, gender, smoking, TNM stage and SLC2A1 expression (HR =1.567, 95% CI: 1.127–2.179, P=0.008) showed that SLC2A1 was an independent prognostic risk factor for LUAD. GSEA and Metascape analysis showed that SLC2A1 was strongly associated with the cell cycle, mitosis, lung tissue, and tumor recurrence. Immune correlation analysis showed that SLC2A1 was associated with two tumor infiltration immune cells: activated CD (cluster of differentiation)4 + memory T cells (r=0.31, P=0.003) and activated mast cells (r=−0.28, P=0.010). Moreover, patients with high SLC2A1 expression had higher immune checkpoint molecules and Tumor Immune Dysfunction and Exclusion (TIDE) scores, indicating poorer immunotherapy efficacy. Patients with high SLC2A1 expression were more sensitive to chemotherapy drugs and less sensitive to targeted drugs compared to those with low SLC2A1 expression. Conclusions The high expression of SLC2A1 in LUAD predicted poor prognosis and was closely related to tumor immunity, which could be used as an effective prognostic biomarker to provide a new strategy for clinical prognosis assessment and immunotherapy for LUAD.

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Section: Discussionmentioning

confidence: 99%

SLC2A1 plays a significant prognostic role in lung adenocarcinoma and is associated with tumor immunity based on bioinformatics analysis

Wang¹,

Wen²,

Sun³

2022

Ann Transl Med

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“…The results of our study also revealed that CXCL10 is highly expressed in pCR patients, indicating that a higher expression level of CXCL10 may result in pCR in BC patients. Several studies have shown that CXCL11, CXCL13, and CXCL14 biomarkers are closely related to chemotherapeutic resistance in BC (29)(30)(31)(32)(33). ESR1 encodes estrogen receptor α (ERα) and plays an important role in the tumorigenesis of BC (34).…”

Section: Discussionmentioning

confidence: 99%

Identification of immune-related biomarkers for predicting neoadjuvant chemotherapy sensitivity in HER2 negative breast cancer via bioinformatics analysis

Fang

et al. 2022

Gland Surg

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Background: Neoadjuvant chemotherapy (NAC) is an important treatment for breast cancer (BC) patients.However, due to the lack of specific therapeutic targets, only 1/3 of human epidermal growth factor receptor 2 (HER2)-negative patients reach pathological complete response (pCR). Therefore, there is an urgent need to identify novel biomarkers to distinguish and predict NAC sensitive in BC patients.Methods: The GSE163882 dataset, containing 159 BC patients treated with NAC, was downloaded from the Gene Expression Omnibus (GEO) database. Patients with pathological complete response (pCR) and those with residual disease (RD) were compared to obtain the differentially expressed genes (DEGs).Functional enrichment analyses were conducted on these DEGs. Then, we intersect the DEGs and immunerelated genes to obtain the hub immune biomarkers, and then use the linear fitting model ("glm" package) to construct a prediction model composed of 9 immune biomarkers. Finally, the single sample gene set enrichment analysis (ssGSEA) algorithm was used to analyze immune cell invasion in BC patients, and the correlation between immune cell content and immune gene expression levels was analyzed.Results: Nine immune-related biomarkers were obtained in the intersection of DEGs and immune-related genes. Compared with RD patients, CXCL9, CXCL10, CXCL11, CXCL13, GZMB, IDO1, and LYZ were highly expressed in pCR patients, while CXCL14 and ESR1 were lowly expressed in pCR patients. After linear fitting of the multi-gene expression model, the area under the curve (AUC) value of the ROC curve diagnosis of pCR patients was 0.844. Immunoinfiltration analysis showed that compared with RD patients, 15 of the 28 immune cell types examined showed high-infiltration in pCR patients, including activated CD8 T cells, effector memory CD8 T cells, and activated CD4 T cells.Conclusions: This investigation ultimately identified 9 immune-related biomarkers as potential tools for assessing the sensitivity of NAC in HER2-negative BC patients. These biomarkers have great potential for predicting pCR BC patients.

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“…More recently, anti-tumor immunotherapy is attracting more and more attention in BC. Biomarker-driven therapies and immune checkpoint inhibitors are proving to be promising options for TNBC treatments ( 4 , 5 ). However, drug resistance in tumors is still a problem that cannot be ignored in TNBC treatment.…”

Section: Introductionmentioning

confidence: 99%

A pyroptosis-associated gene risk model for predicting the prognosis of triple-negative breast cancer

et al. 2022

Self Cite

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BackgroundPyroptosis is a novel identified form of inflammatory cell death that is important in the development and progression of various diseases, including malignancies. However, the relationship between pyroptosis and triple-negative breast cancer (TNBC) is still unclear. Therefore, we started to investigate the potential prognostic value of pyroptosis-associated genes in TNBC.MethodsThirty-three genes associated with pyroptosis were extracted from previous publications, 30 of which were identified in the Molecular Taxonomy of Breast Cancer International Consortium (METABRIC) cohort. On the basis of the 30 pyroptosis-related genes, patients with TNBC were divided into three subtypes through unsupervised cluster analysis. The prognostic value of each pyroptosis-associated gene was assessed, and six genes were selected by univariate and LASSO Cox regression analysis to establish a multigene signature. According to the median value of risk score, patients with TNBC in the training and validation cohorts were separated to high- and low-risk sets. The enrichment analysis was conducted on the differentially expressed genes (DEGs) of the two risk sets using R clusterProfiler package. Moreover, the ESTIMATE score and immune cell infiltration were calculated by the ESTIMATE and CIBERSORT methods. After that, the correlation among pyroptosis-associated risk score and the expression of immune checkpoint-associated genes as well as anti-cancer drugs sensitivities were further analyzed.ResultsIn the training and validation cohorts, patients with TNBC in the high-risk set were found in a lower survival rate than those in the low-risk set. Combined with the clinical characteristics, the pyroptosis-related risk score was identified as an independent risk factor for the prognosis of patients with TNBC. The enrichment analysis indicated that the DEGs between the two risk groups were mainly enriched by immune responses and activities. In addition, patients with TNBC in the low-risk set were found to have a higher value of ESTIMATE score and a higher rate of immune cell infiltration. Finally, the expression levels of five genes [programmed cell death protein 1 (PD-1); cytotoxic t-lymphocyte antigen-4 (CTLA4); lymphocyte activation gene 3 (LAG3); T cell immunoreceptor with Ig and ITIM domains (TIGIT)] associated with immune checkpoint inhibitors were identified to be higher in the low-risk sets. The sensitivities of some anti-cancer drugs commonly used in breast cancer were found closely related to the pyroptosis-associated risk model.ConclusionThe pyproptosis-associated risk model plays a vital role in the tumor immunity of TNBC and can be applied to be a prognostic predictor of patients with TNBC. Our discovery will provide novel insight for TNBC immunotherapies.

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Characterization of Exosome-Related Gene Risk Model to Evaluate the Tumor Immune Microenvironment and Predict Prognosis in Triple-Negative Breast Cancer

Cited by 31 publications

References 70 publications

SLC2A1 plays a significant prognostic role in lung adenocarcinoma and is associated with tumor immunity based on bioinformatics analysis

SLC2A1 plays a significant prognostic role in lung adenocarcinoma and is associated with tumor immunity based on bioinformatics analysis

Identification of immune-related biomarkers for predicting neoadjuvant chemotherapy sensitivity in HER2 negative breast cancer via bioinformatics analysis

A pyroptosis-associated gene risk model for predicting the prognosis of triple-negative breast cancer

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