scholarly journals Comprehensive Analysis of Innate Immunophenotyping Based on Immune Score Predicting Immune Alterations and Prognosis in Breast Cancer Patients

Genes ◽  
2021 ◽  
Vol 13 (1) ◽  
pp. 88
Author(s):  
Weiguang Liu ◽  
Lingling Xia ◽  
Zhengmiao Xia ◽  
Liming Chen
Keyword(s):  
Breast Cancer ◽  
Cancer Immunotherapy ◽  
Cancer Patients ◽  
Immune Checkpoint ◽  
Immune Cell ◽  
Risk Model ◽  
Innate Immune ◽  
Immune Cell Infiltration ◽  
Breast Cancer Patients ◽  
Score Model

Breast cancer is the most common cancer, with the highest mortality rate and the most diagnosed cancer type in women worldwide. To identify the effect innate immune checkpoint for breast cancer immunotherapy, the innate immune prognostic biomarkers were selected through the ICI score model and the risk model in breast cancer patients. Moreover, the reliability and accuracy of the ICI score model and the risk model were further examined through the analysis of breast cancer prognosis and immune cell infiltration. The pan cancer analysis further confirmed and selected CXCL9 as the key innate immune checkpoint for breast cancer immunotherapy and identified three small molecular drugs for target CXCL9 through molecular docking analysis. In summary, CXCL9 significantly correlated with the prognostic of breast cancer and immune cell infiltration and could be innate immune checkpoint for breast cancer immunotherapy.

PD-1+ immune cell infiltration inversely correlates with survival of operable breast cancer patients

2014 ◽  
Vol 63 (4) ◽  
pp. 395-406 ◽  
Author(s):  
Shenyou Sun ◽  
Xiaochun Fei ◽  
Yan Mao ◽  
Xiumin Wang ◽  
David H. Garfield ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Cancer Patients ◽  
Immune Cell ◽  
Operable Breast Cancer ◽  
Cell Infiltration ◽  
Immune Cell Infiltration ◽  
Breast Cancer Patients

scholarly journals Molecular and Clinical Characterization of LAG3 in Breast Cancer Through 2994 Samples

2021 ◽  
Vol 12 ◽  
Author(s):  
Qiang Liu ◽  
Yihang Qi ◽  
Jie Zhai ◽  
Xiangyi Kong ◽  
Xiangyu Wang ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Cancer Immunotherapy ◽  
Cancer Patients ◽  
Immune Cell ◽  
Immune Checkpoints ◽  
Cell Populations ◽  
Breast Cancer Patients ◽  
Correlation Pattern ◽  
Potential Biomarker

Despite the promising impact of cancer immunotherapy targeting CTLA4 and PD1/PDL1, numerous cancer patients fail to respond. LAG3 (Lymphocyte Activating 3), also named CD233, serves as an alternative inhibitory receptor to be targeted in the clinic. The impacts of LAG3 on immune cell populations and coregulation of immune responses in breast cancer remain largely unknown. To characterize the role of LAG3 in breast cancer, we investigated transcriptome data and associated clinical information derived from 2,994 breast cancer patients. We estimated the landscape of the relationship between LAG3 and 10 types of cell populations of breast cancer. We investigated the correlation pattern between LAG3 and immune modulators in pancancer, particularly the synergistic role of LAG3 with other immune checkpoint members in breast cancer. LAG3 expression was closely related to the malignancy of breast cancer and may serve as a potential biomarker. LAG3 may play an important role in regulating the tumor immune microenvironment of T cells and other immune cells. More important, LAG3 may synergize with CTLA4, PD1/PDL1, and other immune checkpoints, thereby contributing more evidence to improve combination cancer immunotherapy by simultaneously targeting LAG3, PD1/PDL1, and CTLA4.

scholarly journals ITGA3 Is Associated With Immune Cell Infiltration and Serves as a Favorable Prognostic Biomarker for Breast Cancer

2021 ◽  
Vol 11 ◽  
Author(s):  
Yue Li ◽  
Fan Li ◽  
Xiaoyu Bai ◽  
Yanlei Li ◽  
Chunsheng Ni ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Cancer Patients ◽  
Immune Cells ◽  
Immune Cell ◽  
Genomic Analysis ◽  
Tumor Infiltrating Lymphocytes ◽  
Diagnostic Value ◽  
Cell Infiltration ◽  
Immune Cell Infiltration ◽  
Breast Cancer Patients

BackgroundITGA3 is a member of the integrin family, a cell surface adhesion molecule that can interact with extracellular matrix (ECM) proteins. The purpose of this study was to explore the significance of ITGA3 expression in the prognosis and clinical diagnosis of breast cancer patients.MethodsOncomine, the Human Protein Atlas (HPA) and UALCAN were used to analyze the expression of ITGA3 in various cancers. PrognoScan, GEPIA, Kaplan–Meier plotter and Easysurv were utilized to analyze the prognosis of ITGA3 in certain cancers. Based on TCGA data, a receiver operating characteristic (ROC) curve was used to evaluate the diagnostic performance of ITGA3 expression. cBio-Portal and MethSurv were used to evaluate the genomic mechanism. LinkedOmics, NetworkAnalyst and Metascape were used to build the signaling network. TIMER is a web server for comprehensive analysis of tumor infiltrating immune cells and tumor infiltrating lymphocytes (TILs).ResultsThe expression of ITGA3 in normal breast tissues was greater than that in breast cancer tissues at both the mRNA and protein levels. High expression of ITGA3 was associated with better prognosis of breast cancer patients. ROC analysis indicated that ITGA3 had significant diagnostic value. Genomic analysis revealed that promoter methylation of ITGA3 leads to transcriptional silencing, which may be one of the mechanisms underlying ITGA3 downregulation in BRCA. Immune infiltration analysis showed that ITGA3 may be involved in the recruitment of immune cells.ConclusionsThis study identified ITGA3 as a novel biomarker to estimate the diagnosis and prognosis of breast cancer. In addition, ITGA3 is involved in ECM regulation and immune cell infiltration.

scholarly journals Molecular and Clinical Characterization of LAG3 in Breast Cancer Through 2994 Samples

2020 ◽  
Author(s):  
Qiang Liu ◽  
Yihang Qi ◽  
Jie Zhai ◽  
Xiangyi Kong ◽  
Xiangyu Wang ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Immune Response ◽  
Cancer Immunotherapy ◽  
Cancer Patients ◽  
Immune Cell ◽  
Immune Checkpoints ◽  
Cell Populations ◽  
Potential Biomarker ◽  
The Impact

Abstract Background Despite the promising impact of cancer immunotherapy targeting CTLA4 and PD1/PDL1, a large number of cancer patients fail to respond. LAG3 (Lymphocyte Activating 3), also named CD233, is a protein Coding gene served as alternative inhibitory receptors to be targeted in the clinic. The impact of LAG3 on immune cell populations and co-regulation of immune response in breast cancer remained largely unknown. Methods To characterize the role of LAG3 in breast cancer, we investigated transcriptome data and associated clinical information derived from a total of 2994 breast cancer patients. Results We observed that LAG3 was closely correlated with major molecular and clinical characteristics, and was more likely to be enriched in higher malignant subtype, suggesting LAG3 was a potential biomarker of triple-negative breast cancer. Furthermore, we estimated the landscape of relationship between LAG3 and ten types of cell populations in breast cancer. Gene ontology analysis revealed LAG3 were strongly correlated with immune response and inflammatory activities. We investigated the correlation pattern between LAG3 and immune modulators in pan-cancer, especially the synergistic role of LAG3 with other immune checkpoints members in breast cancer. Conclusions LAG3 expression was closely related to malignancy of breast cancer and might serve as a potential biomarker; LAG3 might plays an important role in regulating tumor immune microenvironment, not only T cells, but also other immune cells. More importantly, LAG3 might synergize with CTLA4, PD1/ PDL1 and other immune checkpoints, thereby lending more evidences to combination cancer immunotherapy by targeting LAG3, PD1/PDL1, and CTLA4 together.

Immune-related gene based prognostic signature for the risk stratification analysis of breast cancer

2021 ◽  
Vol 16 ◽  
Author(s):  
Dongqing Su ◽  
Qianzi Lu ◽  
Yi Pan ◽  
Yao Yu ◽  
Shiyuan Wang ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Regression Analysis ◽  
Cancer Patients ◽  
Risk Score ◽  
Cox Regression ◽  
Enrichment Analysis ◽  
Gene Set Enrichment Analysis ◽  
Breast Cancer Patients ◽  
Cox Regression Analysis ◽  
Score Model

Background: Breast cancer has plagued women for many years and caused many deaths around the world. Method: In this study, based on the weighted correlation network analysis, univariate Cox regression analysis and least absolute shrinkage and selection operator, 12 immune-related genes were selected to construct the risk score for breast cancer patients. The multivariable Cox regression analysis, gene set enrichment analysis and nomogram were also conducted in this study. Results: Good results were obtained in the survival analysis, enrichment analysis, multivariable Cox regression analysis and immune-related feature analysis. When the risk score model was applied in 22 breast cancer cohorts, the univariate Cox regression analysis demonstrated that the risk score model was significantly associated with overall survival in most of the breast cancer cohorts. Conclusion: Based on these results, we could conclude that the proposed risk score model may be a promising method, and may improve the treatment stratification of breast cancer patients in the future work.

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