scholarly journals Immune Classification and Immune Landscape Analysis of Triple-Negative Breast Cancer

2021 ◽  
Vol 12 ◽  
Author(s):  
Shaojun Hu ◽  
Xiusheng Qu ◽  
Yu Jiao ◽  
Jiahui Hu ◽  
Bo Wang
Keyword(s):  
Breast Cancer ◽  
Triple Negative Breast Cancer ◽  
Drug Sensitivity ◽  
Triple Negative ◽  
Cox Regression ◽  
Landscape Analysis ◽  
Immune Gene ◽  
Immune Genes ◽  
New Perspective ◽  
Immune Related Genes

Background: To classify triple-negative breast cancer (TNBC) immunotyping using the public database, analyze the differences between subtypes in terms of clinical characteristics and explore the role and clinical significance of immune subtypes in TNBC immunotherapy.Methods: We downloaded TNBC data from the cBioPortal and GEO databases. The immune genes were grouped to obtain immune gene modules and annotate their biological functions. Log-rank tests and Cox regression were used to evaluate the prognosis of immune subtypes (IS). Drug sensitivity analysis was also performed for the differences among immune subtypes in immunotherapy and chemotherapy. In addition, dimension reduction analysis based on graph learning was utilized to reveal the internal structure of the immune system and visualize the distribution of patients.Results: Significant differences in prognosis were observed between subtypes (IS1, IS2, and IS3), with the best in IS3 and the worst in IS1. The sensitivity of IS3 to immunotherapy and chemotherapy was better than the other two subtypes. In addition, Immune landscape analysis found the intra-class heterogeneity of immune subtypes and further classified IS3 subtypes (IS3A and IS3B). Immune-related genes were divided into seven functional modules (The turquoise module has the worst prognosis). Five hub genes (RASSF5, CD8A, ICOS, IRF8, and CD247) were screened out as the final characteristic genes related to poor prognosis by low expression.Conclusions: The immune subtypes of TNBC were significantly different in prognosis, gene mutation, immune infiltration, drug sensitivity, and heterogeneity. We validated the independent role of immune subtypes in tumor progression and immunotherapy for TNBC. This study provides a new perspective for personalized immunotherapy and the prognosis evaluation of TNBC patients in the future.

scholarly journals Identification and development of an independent immune-related genes prognostic model for breast cancer

BMC Cancer ◽  
2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Lin Chen ◽  
Yuxiang Dong ◽  
Yitong Pan ◽  
Yuhan Zhang ◽  
Ping Liu ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Regression Analysis ◽  
Cox Regression ◽  
Gene Set Enrichment Analysis ◽  
Risk Scores ◽  
Validation Dataset ◽  
Immune Gene ◽  
Cox Regression Analysis ◽  
Immune Genes ◽  
Immune Related Genes

Abstract Background Breast cancer is one of the main malignant tumors that threaten the lives of women, which has received more and more clinical attention worldwide. There are increasing evidences showing that the immune micro-environment of breast cancer (BC) seriously affects the clinical outcome. This study aims to explore the role of tumor immune genes in the prognosis of BC patients and construct an immune-related genes prognostic index. Methods The list of 2498 immune genes was obtained from ImmPort database. In addition, gene expression data and clinical characteristics data of BC patients were also obtained from the TCGA database. The prognostic correlation of the differential genes was analyzed through Survival package. Cox regression analysis was performed to analyze the prognostic effect of immune genes. According to the regression coefficients of prognostic immune genes in regression analysis, an immune risk scores model was established. Gene set enrichment analysis (GSEA) was performed to probe the biological correlation of immune gene scores. P < 0.05 was considered to be statistically significant. Results In total, 556 immune genes were differentially expressed between normal tissues and BC tissues (p < 0. 05). According to the univariate cox regression analysis, a total of 66 immune genes were statistically significant for survival risk, of which 30 were associated with overall survival (P < 0.05). Finally, a 15 immune genes risk scores model was established. All patients were divided into high- and low-groups. KM survival analysis revealed that high immune risk scores represented worse survival (p < 0.001). ROC curve indicated that the immune genes risk scores model had a good reliability in predicting prognosis (5-year OS, AUC = 0.752). The established risk model showed splendid AUC value in the validation dataset (3-year over survival (OS) AUC = 0.685, 5-year OS AUC = 0.717, P = 0.00048). Moreover, the immune risk signature was proved to be an independent prognostic factor for BC patients. Finally, it was found that 15 immune genes and risk scores had significant clinical correlations, and were involved in a variety of carcinogenic pathways. Conclusion In conclusion, our study provides a new perspective for the expression of immune genes in BC. The constructed model has potential value for the prognostic prediction of BC patients and may provide some references for the clinical precision immunotherapy of patients.

A novel three-long noncoding RNA risk score system for the prognostic prediction of triple-negative breast cancer

2021 ◽  
Vol 15 (1) ◽  
pp. 43-55
Author(s):  
Chao Yuan ◽  
Hongjun Yuan ◽  
Li Chen ◽  
Miaomiao Sheng ◽  
Wenru Tang
Keyword(s):  
Breast Cancer ◽  
Risk Score ◽  
Triple Negative Breast Cancer ◽  
Long Noncoding Rna ◽  
Noncoding Rna ◽  
Triple Negative ◽  
Cox Regression ◽  
Characteristic Curve ◽  
Gene Expression Omnibus ◽  
Prognostic Prediction

Background: Triple-negative breast cancer (TNBC) is characterized by fast tumor increase, rapid recurrence and natural metastasis. We aimed to identify a genetic signature for predicting the prognosis of TNBC. Materials & methods: We conducted a weighted correlation network analysis of datasets from the Gene Expression Omnibus. Multivariate Cox regression was used to construct a risk score model. Results: The multi-factor risk scoring model was meaningfully associated with the prognosis of patients with TBNC. The predictive power of the model was demonstrated by the time-dependent receiver operating characteristic curve and Kaplan–Meier curve, and verified using a validation set. Conclusion: We established a long noncoding RNA-based model for the prognostic prediction of TNBC.

scholarly journals Prognostic Biomarkers on a Competitive Endogenous RNA Network Reveals Overall Survival in Triple-Negative Breast Cancer

2021 ◽  
Vol 11 ◽  
Author(s):  
Wenxing Qin ◽  
Feng Qi ◽  
Jia Li ◽  
Ping Li ◽  
Yuan-Sheng Zang
Keyword(s):  
Breast Cancer ◽  
Overall Survival ◽  
Triple Negative Breast Cancer ◽  
Prognostic Model ◽  
Triple Negative ◽  
Cox Regression ◽  
Critical Role ◽  
Differentially Expressed ◽  
Cerna Network ◽  
Competitive Endogenous Rna

The objective of this study was to construct a competitive endogenous RNA (ceRNA) regulatory network using differentially expressed long noncoding RNAs (lncRNAs), microRNAs (miRNAs), and mRNAs in patients with triple-negative breast cancer (TNBC) and to construct a prognostic model for predicting overall survival (OS) in patients with TNBC. Differentially expressed lncRNAs, miRNAs, and mRNAs in TNBC patients from the TCGA and Metabric databases were examined. A prognostic model based on prognostic scores (PSs) was established for predicting OS in TNBC patients, and the performance of the model was assessed by a recipient that operated on a distinctive curve. A total of 874 differentially expressed RNAs (DERs) were screened, among which 6 lncRNAs, 295 miRNAs and 573 mRNAs were utilized to construct targeted and coexpression ceRNA regulatory networks. Eight differentially expressed genes (DEGs) associated with survival prognosis, DBX2, MYH7, TARDBP, POU4F1, ABCB11, LHFPL5, TRHDE and TIMP4, were identified by multivariate Cox regression and then used to establish a prognostic model. Our study shows that the ceRNA network has a critical role in maintaining the aggressiveness of TNBC and provides comprehensive molecular-level insight for predicting individual mortality hazards for TNBC patients. Our data suggest that these prognostic mRNAs from the ceRNA network are promising therapeutic targets for clinical intervention.

scholarly journals Prognostic role of GPER/Ezrin in triple-negative breast cancer is associated with menopausal status

2019 ◽  
Vol 8 (6) ◽  
pp. 661-671 ◽  
Author(s):  
Shuang Ye ◽  
Yuanyuan Xu ◽  
Jiehao Li ◽  
Shuhui Zheng ◽  
Peng Sun ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Triple Negative Breast Cancer ◽  
Triple Negative ◽  
Cox Regression ◽  
Menopausal Status ◽  
Prognostic Significance ◽  
Multivariable Analysis ◽  
Survival Prognosis ◽  
Kaplan Meier

The role of G protein-coupled estrogen receptor 1 (GPER) signaling, including promotion of Ezrin phosphorylation (which could be activated by estrogen), has not yet been clearly identified in triple-negative breast cancer (TNBC). This study aimed to evaluate the prognostic value of GPER and Ezrin in TNBC patients. Clinicopathologic features including age, menopausal status, tumor size, nuclear grade, lymph node metastasis, AJCC TNM stage, and ER, PR and HER-2 expression were evaluated from 249 TNBC cases. Immunohistochemical staining of GPER and Ezrin was performed on TNBC pathological sections. Kaplan–Meier analyses, as well as logistic regressive and Cox regression model tests were applied to evaluate the prognostic significance between different subgroups. Compared to the GPER-low group, the GPER-high group exhibited higher TNM staging (P = 0.021), more death (P < 0.001), relapse (P < 0.001) and distant events (P < 0.001). Kaplan–Meier analysis showed that GPER-high patients had a decreased OS (P < 0.001), PFS (P < 0.001), LRFS (P < 0.001) and DDFS (P < 0.001) than GPER-low patients. However, these differences in prognosis were not statistically significant in post-menopausal patients (OS, P = 0.8617; PFS, P = 0.1905; LRFS, P = 0.4378; DDFS, P = 0.2538). There was a significant positive correlation between GPER and Ezrin expression level (R = 0.508, P < 0.001) and the effect of Ezrin on survival prognosis corresponded with GPER. Moreover, a multivariable analysis confirmed that GPER and Ezrin level were both significantly associated with poor DDFS (HR: 0.346, 95% CI 0.182–0.658, P = 0.001; HR: 0.320, 95% CI 0.162–0.631, P = 0.001). Thus, overexpression of GPER and Ezrin may contribute to aggressive behavior and indicate unfavorable prognosis in TNBC; this may correspond to an individual’s estrogen levels.

scholarly journals Analysis of CK5/6 and EGFR and Its Effect on Prognosis of Triple Negative Breast Cancer

2021 ◽  
Vol 10 ◽  
Author(s):  
Zhen Wang ◽  
Lei Liu ◽  
Ying Li ◽  
Zi’an Song ◽  
Yi Jing ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Regression Analysis ◽  
Neoadjuvant Chemotherapy ◽  
Triple Negative Breast Cancer ◽  
Triple Negative ◽  
Cox Regression ◽  
Multivariate Logistic Regression Analysis ◽  
Pathological Examination ◽  
Cox Regression Analysis ◽  
Tumor Stages

BackgroundTriple-negative breast cancer (TNBC) is considered to be higher grade, more aggressive and have a poorer prognosis than other types of breast cancer. Discover biomarkers in TNBC for risk stratification and treatments that improve prognosis are in dire need.MethodsClinical data of 195 patients with triple negative breast cancer confirmed by pathological examination and received neoadjuvant chemotherapy (NAC) were collected. The expression levels of EGFR and CK5/6 were measured before and after NAC, and the relationship between EGFR and CK5/6 expression and its effect on prognosis of chemotherapy was analyzed.ResultsThe overall response rate (ORR) was 86.2% and the pathological complete remission rate (pCR) was 29.2%. Univariate and multivariate logistic regression analysis showed that cT (clinical Tumor stages) stage was an independent factor affecting chemotherapy outcome. Multivariate Cox regression analysis showed pCR, chemotherapy effect, ypT, ypN, histological grades, and post- NAC expression of CK5/6 significantly affected prognosis. The prognosis of CK5/6-positive patients after NAC was worse than that of CK5/6-negative patients (p=0.036). Changes in CK5/6 and EGFR expression did not significantly affect the effect of chemotherapy, but changes from positive to negative expression of these two markers are associated with a tendency to improve prognosis.ConclusionFor late-stage triple negative breast cancer patients receiving NAC, patients who achieved pCR had a better prognosis than those with non- pCR. Patients with the change in expression of EGFR and CK5/6 from positive to negative after neoadjuvant chemotherapy predicted a better prognosis than the change from negative to positive group.

scholarly journals THER-06. GENOMIC AND IMMUNE CHARACTERIZATION OF TRIPLE NEGATIVE BREAST CANCER BRAIN METASTASES

2019 ◽  
Vol 1 (Supplement_1) ◽  
pp. i11-i12
Author(s):  
Benjamin Vincent ◽  
Maria Sambade ◽  
Shengjie Chai ◽  
Marni Siegel ◽  
Luz Cuaboy ◽  
...  
Keyword(s):  
Breast Cancer ◽  
T Cell ◽  
Brain Metastases ◽  
T Cell Receptor ◽  
Triple Negative Breast Cancer ◽  
Triple Negative ◽  
Cell Receptor ◽  
Gene Signature ◽  
Specific Response ◽  
Immune Gene

Abstract INTRODUCTION: Approximately 50% of patients with metastatic triple negative breast cancer (TNBC) will develop brain metastases (BM). Routinely treated with radiotherapy and/or surgery, survival is generally less than one year. There are no approved systemic therapies to treat TNBC BM. We characterized the genomic and immune landscape of TNBC BM to foster the development of effective brain permeable anti-cancer agents, including immunotherapy. EXPERIMENTAL PROCEDURES: A clinically-annotated BCBM biobank of archival tissues was created under IRB approval. DNA (tumor/normal) and RNA (tumor) were extracted from TNBC primaries and BM; whole exome (WES) and RNA sequencing (RNASeq) was performed. Mutations were determined from WES as those co-identified by two variant callers (Strelka|Cadabra). Immune gene signature expression, molecular subtype identification, and T cell receptor repertoires were inferred from RNAseq. RESULTS: 32 TNBC patient tissues (14 primaries, 18 BCBM, 6 primary-BCBM matched), characterized as basal-like by PAM50, were analyzed. Top exome mutation calls included ten genes in ≥19% of BCBMs including TP53, ATM, and PIK3R1, and four genes in ≥18% of primaries including TP53 and PIK3R1. Many immune gene signatures were lower in BM compared to primaries including B cell, dendritic cell, regulatory T cell, and IgG cluster (p&lt; 0.05). A signature of PD-1 inhibition responsiveness was higher in BM compared with primaries (p&lt; 0.05). BCBM T cell receptor repertoires showed higher evenness and lower read count (both p &lt; 0.01) compared to primaries. CONCLUSIONS: TNBC BM compared to primaries that metastasize to the brain show lower immune gene signature expression, higher PD-1 inhibition response signature expression, and T cell receptor repertoire features less characteristic of an active antigen-specific response. Mutations common to TNBC BM and primaries include TP53 and PIK3R1. Given that non-BCBM (i.e. lung and melanoma) show response to checkpoint inhibitors, these findings collectively support further study of immunotherapy for TNBC BM.

scholarly journals Nomogram Personalizes and Visualizes the Overall Survival of Patients with Triple-Negative Breast Cancer Based on the Immune Genome

2020 ◽  
Vol 2020 ◽  
pp. 1-16
Author(s):  
Peipei Wang ◽  
Yang Fu ◽  
Yueyun Chen ◽  
Qing Li ◽  
Ye Hong ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Overall Survival ◽  
T Cells ◽  
Risk Score ◽  
Triple Negative Breast Cancer ◽  
Triple Negative ◽  
Novel Therapy ◽  
Immune Biomarkers ◽  
Poorly Differentiated ◽  
Immune Related Genes

Background. Triple-negative breast cancer (TNBC) is usually poorly differentiated, highly invasive, susceptible to distant metastasis, and less responsive to endocrine and targeted therapy. However, immunotherapy is a promising treatment for TNBC patients recently. Methods. The prognostic value of immune-related genes (IRGs) was explored by using RNA sequencing and microarray data of 123 and 107 TNBC patients from TCGA and GEO databases, respectively. Results. In TCGA database, GO and KEGG pathway analysis of 119 differential IRGs indicated that they actively participate in the interaction of cytokines and receptors. A nomogram model constructed by the prognosis-related CCL25, IL29, TDGF3, GPR44, and GREM2 in the IRGs could personalize and visualize the 1-, 2-, 3-, 4-, and 5-year overall survival (OS) of TNBC patients. Moreover, TNBC patients could be defined as low-risk ( risk   score < 194 ) or high-risk ( risk   score ≥ 194 ) cohorts based on the risk score derived from the nomogram model. The results could be validated by the GSE58812 dataset. Furthermore, the risk score was an independent risk factor for TNBC patients ( HR = 1.019 , 95% CI 1.012-1.027, p < 0.001 ) and was positively related to stage ( p = 0.017 ). Interestingly, the risk score could reflect the infiltration of B cells, CD4+ T cells, CD8+ T cells, dendritic cells, and neutrophils. Conclusion. These findings provided a reference for personalized OS prediction in TNBC patients and might be potential immune biomarkers for designing novel therapy.

scholarly journals A Novel Platelet-Related Gene Signature for Predicting the Prognosis of Triple-Negative Breast Cancer

2022 ◽  
Vol 9 ◽  
Author(s):  
Jindong Xie ◽  
Yutian Zou ◽  
Feng Ye ◽  
Wanzhen Zhao ◽  
Xinhua Xie ◽  
...  
Keyword(s):  
Breast Cancer ◽  
High Risk ◽  
Triple Negative Breast Cancer ◽  
Triple Negative ◽  
Cox Regression ◽  
Risk Group ◽  
Gene Signature ◽  
The Cancer Genome Atlas ◽  
Functional Enrichment ◽  
Clinical Prognosis

Regarded as the most invasive subtype, triple-negative breast cancer (TNBC) lacks the expression of estrogen receptors (ERs), progesterone receptors (PRs), and human epidermal growth factor receptor 2 (HER2) proteins. Platelets have recently been shown to be associated with metastasis of malignant tumors. Nevertheless, the status of platelet-related genes in TNBC and their correlation with patient prognosis remain unknown. In this study, the expression and variation levels of platelet-related genes were identified and patients with TNBC were divided into three subtypes. We collected cohorts from The Cancer Genome Atlas (TCGA) and the Gene Expression Omnibus (GEO) databases. By applying the least absolute shrinkage and selection operator (LASSO) Cox regression method, we constructed a seven-gene signature which classified the two cohorts of patients with TNBC into low- or high-risk groups. Patients in the high-risk group were more likely to have lower survival rates than those in the low-risk group. The risk score, incorporated with the clinical features, was confirmed as an independent factor for predicting the overall survival (OS) time. Functional enrichment analyses revealed the involvement of a variety of vital biological processes and classical cancer-related pathways that could be important to the ultimate prognosis of TNBC. We then built a nomogram that performed well. Moreover, we tested the model in other cohorts and obtained positive outcomes. In conclusion, platelet-related genes were closely related to TNBC, and this novel signature could serve as a tool for the assessment of clinical prognosis.

scholarly journals High Expression of microRNA-223 Indicates a Good Prognosis in Triple-Negative Breast Cancer

2021 ◽  
Vol 11 ◽  
Author(s):  
Li Chen ◽  
Xiuzhi Zhu ◽  
Boyue Han ◽  
Lei Ji ◽  
Ling Yao ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Triple Negative Breast Cancer ◽  
Triple Negative ◽  
Cox Regression ◽  
Molecular Subtype ◽  
External Validation ◽  
Disease Free Survival ◽  
The Cancer Genome Atlas ◽  
Locked Nucleic Acid ◽  
Tnbc Subtype

PurposeMicroRNAs can influence many biological processes and have shown promise as cancer biomarkers. Few studies have focused on the expression of microRNA-223 (miR-223) and its precise role in breast cancer (BC). We aimed to examine the expression level of miR-223 and its prognostic value in BC.MethodsTissue microarray (TMA)-based miRNA detection in situ hybridization (ISH) with a locked nucleic acid (LNA) probe was used to detect miR-223 expression in 450 BC tissue samples. Overall survival (OS) and disease-free survival (DFS) were compared between two groups using the Kaplan-Meier method and Cox regression model.ResultsOS and DFS were prolonged in the high miR-223 expression group compared to the low miR-223 expression group (p &lt; 0.0001 and p = 0.017, respectively), especially in patients with the triple-negative breast cancer (TNBC) subtype (p = 0.046 and p &lt; 0.001, respectively). Univariate and multivariate Cox regression analyses revealed that TNM stage (p = 0.008), the molecular subtype (p = 0.049), and miR-223 (p &lt; 0.001) were independently associated with OS and DFS. External validation was performed with the METABRIC and The Cancer Genome Atlas (TCGA) databases via online webtools and was consistent with the data described above.ConclusionsThis study provides evidence that high miR-223 expression at diagnosis is associated with improved DFS and OS for BC patients, especially those with the TNBC subtype. miR-223 is a valid and independent prognostic biomarker in BC.

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