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 Immune Microenvironment-Related Genes Contribute to Clinical Prognosis in Patients with Triple-Negative Breast Cancer

2021 ◽  
Author(s):  
Dandan Feng ◽  
Jie Gao ◽  
Tianshu Yang ◽  
Yanli Ren ◽  
Wei Liu ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Survival Analysis ◽  
High Risk ◽  
Triple Negative Breast Cancer ◽  
Triple Negative ◽  
Disease Free Survival ◽  
Functional Enrichment ◽  
Clinical Prognosis ◽  
Network Analyses ◽  
Post Surgery

Abstract Background:Triple-negative breast cancer (TNBC) is a high-risk breast cancer subtype, which accounts for 15% to 20% of all breast cancers and generally has a poor prognosis. TNBC patients have high recurrence post-surgery and high risk of metastasis to other organs. The tumor microenvironment (TME) plays important roles in the carcinogenesis, development, and metastasis of tumors. Methods: This study aimed to investigate the effects of immune and stromal cell-related genes on TNBC prognosis. The ESTIMATE algorithm was used to calculate the immune/stromal scores of TNBC samples from the GEO database. The samples were divided into high- and low- score groups and the differential expression genes were identified using the limma package within R. Functional enrichment and protein-protein interaction (PPI) network analyses revealed that these genes are primarily involved in immune responses. Results:Survival analysis in both GSE21653 and KM-plotter website showed that 36 genes were significantly related to disease-free survival (DFS) of TNBC. Another survival analysis by R package survival in GSE58812 indicated that 14 genes of 36 were greatly interrelated to DFS of TNBC. Moreover, the expression levels of some of these genes were verified through immunohistochemical staining and RT-qPCR. Finally, four genes importantly associated with TNBC prognosis were identified with Cox-LASSO analysis. Time-dependent receiver-operating characteristic (ROC) analysis displayed an area under the curve (AUC) of 0.95 for one-year survival rate, indicating the four genes performed very well for prognosis prediction. Conclusions:In conclusion, we identified four genes, including BIRC3, CD8A, GNLY and TRIM22, that are possibly associated with the TME and are potential prognostic and therapeutic markers of TNBC.

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 < 0.0001 and p = 0.017, respectively), especially in patients with the triple-negative breast cancer (TNBC) subtype (p = 0.046 and p < 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 < 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.

scholarly journals A Novel Immune Checkpoint-Related Gene Signature to Predict Overall Survival and Immunotherapy Response in Triple-Negative Breast Cancer

2021 ◽  
Author(s):  
Jingyi Liu ◽  
Siyuan Tian ◽  
Yuwei Ling ◽  
Xinyi Zhang ◽  
Yan Li ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Triple Negative Breast Cancer ◽  
Immune Checkpoint ◽  
Triple Negative ◽  
Cox Regression ◽  
Expression Profiles ◽  
Expression Patterns ◽  
Molecular Taxonomy ◽  
Gene Signature ◽  
Cox Regression Analysis

Abstract Triple-negative breast cancer (TNBC) is a highly aggressive subtype of breast cancer that lacks effective therapeutic targets. Immunotherapy is considered as a novel treatment strategy for TNBC. However, only some patients could benefit from the treatment. Limited studies have comprehensively explored expression patterns and prognostic value of immune checkpoint genes (ICGs) in TNBC. In this study, we downloaded relevant ICGs expression profiles and clinical TNBC data from the Cancer Genome Atlas (TCGA) and the Molecular Taxonomy of Breast Cancer International Consortium (METABRIC) database. The least absolute shrinkage and selection operator (LASSO) Cox regression analysis was employed to develop a multi-gene signature for predicting the prognostic outcome. PDCD1, PDCD1LG2 and KIR3DL2 were identified as hub genes and incorporated into the model. This gene signature could stratify patients into two prognostic subgroups, and unfavorable clinical outcomes were observed in high-risk patients. The predictive performance was assessed by the receiver operating characteristic curves. Moreover, we also analyzed differences in immune status and therapeutic response between both groups. This novel gene signature may be served as a robust prognostic marker, but also an indicator reflecting immunotherapy response.

scholarly journals Androgen Receptor Highjacks ErbB-2 Nuclear Function to Induce Triple Negative Breast Cancer Growth

2021 ◽  
Vol 5 (Supplement_1) ◽  
pp. A804-A804
Author(s):  
Agustina Roldán Deamicis ◽  
Robert H Oakley ◽  
Sergio Andonegui Helguera ◽  
Mariela B Lenze ◽  
Santiago Madera ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Androgen Receptor ◽  
Triple Negative Breast Cancer ◽  
Triple Negative ◽  
Cox Regression ◽  
Nuclear Migration ◽  
Subcellular Fractionation ◽  
Gene Signature ◽  
Dominant Negative ◽  
Cox Regression Analysis

Abstract Triple negative breast cancer (TNBC) has poor prognosis and neither established biomarkers nor therapeutic targets. On the one hand the androgen receptor (AR), a steroid hormone receptor (SR) which is expressed in 10-53% of TNBC and proved to be critical for BC proliferation, has been proposed as a new target in TNBC. On the other hand, we and others have shown that membrane ErbB-2 migrates to the nucleus (nuclear ErbB-2, NErbB-2) where it binds DNA at HER-2 associated sequences (HAS) to regulate BC proliferation and migration. Since we have previously shown a functional interplay between growth factors and SR signaling pathways in BC, we propose the existence of an interaction between AR and ErbB-2 which is involved in NErbB-2+/AR+ BC growth. The experimental model used was the human TNBC cell line MDA-MB-453 which displays high expression levels of AR and NErbB-2. By Western Blot (WB) we found that dihydrotestosterone (DHT) treatment for short times (minutes) did not regulate ErbB-2 phosphorylation status at residues Tyr1221/1222 and 1248 which were constitutively activated. However, DHT led to an increase in ErbB-2 phosphorylation at residue Tyr877 which we have proved to be required for ErbB-2 nuclear migration. The latter effect was blocked by the AR antagonist enzalutamide (enza). Blockage of Src activity with dasatinib inhibited DHT-induced ErbB-2 phosphorylation at Tyr877. By Immunofluorescence and confocal microscopy analyses and subcellular fractionation studies we demonstrated that DHT induced ErbB-2 nuclear migration which was inhibited by enza. By chIP we found that DHT induced ErbB-2 recruitment to a HAS site in ERK5, a gene involved in BC proliferation, and to a HAS site in FKBP5, a classical AR responsive gene. By WB we demonstrated that transfection with an ErbB-2 mutant which is unable to translocate to the nucleus and functions as a dominant negative inhibitor of ErbB-2 nuclear migration (hErbB-2ΔNLS), inhibited FKBP51 up-regulation by DHT. Finally, by microarray and bioinformatics analysis we identified 315 differentially expressed genes (DEGs) in the presence of DHT and NErbB-2 eviction. Enrichment analyses showed that the DEGs belonged to the immune response and interferon pathways. Kaplan-Meier analysis revealed that the expression of 6 genes was significantly associated with overall survival in TNBC patients from the METABRIC cohort: CXCL10, TAP1, STAT1, NMI, HLA-A and NLRC5. Multivariate Cox regression analysis identified the combined expression of the 6 genes as an independent predictor of better clinical outcome in TNBC (HR: 0.56, 95% CI 0.38-0.82, P = 0.003). In conclusion, our findings evidence that DHT-activated AR induces Src-mediated ErbB-2 rapid activation and its migration to the nucleus where it binds to HAS sites in the DNA. Moreover, based on the DEGs of NErbB-2 eviction in presence of DHT we identified a gene signature associated with favorable outcome in TNBC.

scholarly journals An 8-lncRNA Signature Predicts Survival of Triple-Negative Breast Cancer Patients Without Germline BRCA1/2 Mutation

2020 ◽  
Author(s):  
Minling Liu ◽  
Wei Dai ◽  
Mengyuan Zhu ◽  
Xueying Li ◽  
Shan Huang ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Overall Survival ◽  
Triple Negative Breast Cancer ◽  
Triple Negative ◽  
Cox Regression ◽  
Validation Cohort ◽  
Functional Enrichment ◽  
Biological Behavior ◽  
Risk Scores ◽  
Training Cohort

Abstract Background: Triple-negative breast cancer (TNBC) is a particular breast cancer subtype with poor prognosis due to its aggressive biological behavior and strong heterogeneity. TNBC with germline BRCA1/2 mutation (gBRCAm) have higher sensitivity to DNA damaging agents including platinum-based chemotherapy and PARP inhibitors. But the treatment of TNBC without gBRCAm remains challenging. This study aimed to develop a long non-coding RNA (lncRNA) signature of TNBC patients without gBRCAm to improve risk stratification and optimize individualized treatment.Methods: 98 TNBC patients without gBRCAm were acquired from The Cancer Genome Atlas (TCGA) database. The univariable Cox regression analysis and LASSO Cox regression model were applied to establish an lncRNA signature in the training cohort (N = 59). Then Kaplan–Meier survival curve and time-dependent ROC curve were used to validate the prognostic ability of the signature. The signature related mRNAs were identified using the Pearson correlation. Functional enrichment analysis of related mRNA was performed using the Metascape. The qPCR assay was performed to confirm the expressions and clinicopathological correlationsof two potential lncRNAs HAGLROS and TONSL-AS1 in 30 paired clinical triple-negative breast cancer samples without gBRCAm.Results:We developed an 8-lncRNA signature in the training cohort including HAGLROS, AL139002.1, AL391244.2, AP000696.1, AL391056.1, AL513304.1, TONSL-AS1 and AL031008.1. In both the training and validation cohort, patients with higher risk scores showed significantly worse overall survival compared to those with lower risk scores(P=0.00018 and P =0.0068 respectively). 1, 5, 8-year AUC in the training cohort were 1.000, 1.000 and 0.908 respectively, in the validation cohort were 0.785, 0.790 and 0.892 respectively indicating that our signature has a good prognostic capacity. Signature related mRNA mainly enriched in terms include RNA metabolic process, DNA repair pathways, and so on. Two potential lncRNAs HAGLROS and TONSL-AS1 were found frequently overexpressed in TNBC without gBRCAm, and significantly associated with tumor grade and invasion.Conclusions: We constructed a novel 8-lncRNA signaturewhich significantly associated with the overall survival of TNBC patients without gBRCAm. Among those 8lncRNAs, HAGLROS and TONSL-AS1 may be potential therapeutic targetswhich function needed further exploration.

scholarly journals Identification of Key Genes Affecting the Tumor Microenvironment and Prognosis of Triple-Negative Breast Cancer

2021 ◽  
Vol 11 ◽  
Author(s):  
Jiarong Yi ◽  
Wenjing Zhong ◽  
Haoming Wu ◽  
Jikun Feng ◽  
Xiazi Zouxu ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Tumor Microenvironment ◽  
Triple Negative Breast Cancer ◽  
Triple Negative ◽  
Enrichment Analysis ◽  
Functional Enrichment Analysis ◽  
The Cancer Genome Atlas ◽  
Functional Enrichment ◽  
Ppi Network ◽  
Key Genes

Although the tumor microenvironment (TME) plays an important role in the development of many cancers, its roles in breast cancer, especially triple-negative breast cancer (TNBC), are not well studied. This study aimed to identify genes related to the TME and prognosis of TNBC. Firstly, we identified differentially expressed genes (DEG) in the TME of TNBC, using Expression data (ESTIMATE) datasets obtained from the Cancer Genome Atlas (TCGA) and Estimation of Stromal and Immune cells in Malignant Tumor tissues. Next, survival analysis was performed to analyze the relationship between TME and prognosis of TNBC, as well as determine DEGs. Genes showing significant differences were scored as alternative genes. A protein-protein interaction (PPI) network was constructed and functional enrichment analysis conducted using the DEG. Proteins with a degree greater than 5 and 10 in the PPI network correspond with hub genes and key genes, respectively. Finally, CCR2 and CCR5 were identified as key genes in TME and prognosis of TNBC. Finally, these results were verified using Gene Expression Omnibus (GEO) datasets and immunohistochemistry of TNBC patients. In conclusion, CCR2 and CCR5 are key genes in the TME and prognosis of TNBC with the potential of prognostic biomarkers in TNBC.

scholarly journals An 8-lncRNA signature predicts the survival of triple-negative breast cancer patients without germline BRCA1/2 mutation

2021 ◽  
Vol 3 (3) ◽  
pp. 15-32
Author(s):  
Minling LIU ◽  
Wei DAI ◽  
Mengyuan ZHU ◽  
Xueying LI ◽  
Min WEI ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Overall Survival ◽  
Triple Negative Breast Cancer ◽  
Triple Negative ◽  
Cox Regression ◽  
The Cancer Genome Atlas ◽  
Risk Scores ◽  
Training Cohort ◽  
Cox Regression Analysis ◽  
Platinum Based Chemotherapy

Purpose: TNBC with germline BRCA1/2 mutation (gBRCAm) have higher sensitivity to DNA damaging agents including platinum-based chemotherapy and PARP inhibitors. But the treatment of TNBC without gBRCAm remains challenging. This study aimed to develop a long non-coding RNA (lncRNA) signature of TNBC patients without gBRCAm to improve risk stratification and optimize individualized treatment. Methods: 98 TNBC patients without gBRCAm were acquired from The Cancer Genome Atlas database. The univariable Cox regression analysis and LASSO Cox regression model were applied to establish an lncRNA signature in the training cohort. Then Kaplan–Meier survival curve and time-dependent ROC curve were used to validate the prognostic ability of the signature. The qPCR assay was performed to confirm the expressions and clinicopathological correlations of two potential lncRNAs HAGLROS and TONSL-AS1 in 30 paired clinical triple-negative breast cancer samples without gBRCAm. Results: We developed an 8-lncRNA signature in the training cohort including HAGLROS, AL139002.1, AL391244.2, AP000696.1, AL391056.1, AL513304.1, TONSL-AS1 and AL031008.1. Patients with higher risk scores showed significantly worse overall survival compared to those with lower risk scores (P=0.00018 and P =0.0068 respectively). 30 paired specimens of TNBC without gBRCAm in our center showed that two potential lncRNAs HAGLROS and TONSL-AS1 were found frequently overexpressed, and significantly associated with tumor grade and invasion. Conclusion: We constructed a novel 8-lncRNA signature which significantly associated with the overall survival of TNBC patients without gBRCAm. Among those 8 lncRNAs, HAGLROS and TONSL-AS1 may be potential therapeutic targets which function needed further exploration.

scholarly journals Construction and Validation of a Prognostic Risk Model for Triple Negative Breast Cancer Based on Autophagy-Related Genes

2021 ◽  
Author(s):  
Cheng Yan ◽  
Qingling Liu ◽  
Ruoling Jia
Keyword(s):  
Breast Cancer ◽  
Overall Survival ◽  
Regression Analysis ◽  
Triple Negative Breast Cancer ◽  
Triple Negative ◽  
Risk Model ◽  
Cox Regression ◽  
Risk Group ◽  
Lasso Regression ◽  
Cox Regression Analysis

Abstract Background: Autophagy plays an important role in triple negative breast cancer (TNBC). However, the prognostic value of autophagy-related genes (ARGs) in TNBC remains unknown. In this study, we established a survival model to evaluate the prognosis of TNBC patients using ARGs signature.Methods: A total of 222 autophagy-related genes were downloaded from The Human Autophagy Database. The RNA-sequencing data and corresponding clinical data of TNBC were obtained from the TCGA database. Differential gene expression of ARGs (DE-ARGs) between normal samples and TNBC samples was determined by the EdgeR software package. Then, univariate Cox, Lasso, and multivariate Cox regression analyses were performed. According to the Lasso regression results based on univariate Cox, we identified a prognostic signature for overall-survival (OS), which was further validated by using GEO cohort. We also found an independent prognostic marker that can predict the clinicopathological features of TNBC. Furthermore, a nomogram was drawn to predict the survival probability of TNBC patients, which could help in clinical decision for TNBC treatment. Finally, we validated the requirement of a ARG in our model for TNBC cell survival and metastasis.Results: There are 43 differentially expressed ARGs (DE-ARGs) were identified between normal and tumor samples. A risk model for OS using CDKN1A, CTSD, CTSL, EIF4EBP1, TMEM74 and VAMP3 by Lasso regression analysis was established based on univariate Cox regression analysis. Overall survival of TNBC patients was significantly shorter in the high-risk group than in the low-risk group for both the training and validation cohorts. Using the Kaplan-Meier curves and ROC curves, we demonstrated the accuracy of the prognostic model. Multivariate Cox regression analysis was used to verify risk score as independent predictor. Then a nomogram was proposed to predict 1-, 3-, and 5-year survival for TNBC patients. The calibration curves showed great accuracy of the model for survival prediction. Finally, we found that depletion of EIF4EBP1, one of ARGs in our model, significantly reduced cell proliferation and metastasis of TNBC cells. Conclusion: An autophagy-related prognosis model in TNBCs was constructed using ARGs signature containing CDKN1A, CTSD, CTSL, EIF4EBP1, TMEM74 and VAMP3. It could serve as an independent prognostic biomarker in TNBC.

scholarly journals Identification of prognostic immune-related lncRNA signature predicting the overall survival for colorectal cancer

2021 ◽  
Author(s):  
Jianxin Li ◽  
Ting Han ◽  
Xin Wang ◽  
Yinchun Wang ◽  
Qingqiang Yang
Keyword(s):  
Colorectal Cancer ◽  
Overall Survival ◽  
High Risk ◽  
Cox Regression ◽  
Risk Group ◽  
Enrichment Analysis ◽  
High Risk Group ◽  
The Cancer Genome Atlas ◽  
Functional Enrichment ◽  
Regression Analyses

Abstract Background Long non-coding RNA (lncRNA) is an important regulator of gene expression and serves fundamental role in immune regulation. The present study aimed to develop a novel immune-related lncRNA signature to accurately assess the prognosis of patients with colorectal cancer (CRC). Methods Transcriptome data and clinical information of patients with CRC were downloaded from The Cancer Genome Atlas (TCGA), and the immune-related mRNAs were extracted from immunomodulatory gene datasets IMMUNE RESPONSE and IMMUNE SYSTEM PROCESS based on the Molecular Signatures Database (MSigDB). Then, the immune-related lncRNAs were identified by a correlation analysis between immune-related mRNAs and lncRNAs. Subsequently, univariate, lasso and multivariate Cox regression were used to identify an immune-related lncRNA signature in training cohort, and the predict ability of the signature was further confirmed in the testing cohort and the entire TCGA cohort. Finally, the lncRNA-mRNA co-expression network was established to explore the biological role of the immune-related lncRNA signature. Results In total, 272 Immune-related lncRNAs were identified, five of which were applied to construct an immune-related lncRNA signature based on univariate, lasso and multivariate Cox regression analyses. The signature divided patients with CRC into low- and high-risk groups, and patients with CRC in high-risk group had poorer overall survival than those in low-risk group. Univariate and multivariate Cox regression analyses confirmed that the signature could be an independent prognostic factor in human CRC. Furthermore, functional enrichment analysis revealed that the immune-related lncRNA signature was significantly enriched in immune process and tumor classical pathways. Conclusions The present study revealed that the novel immune-related lncRNA signature could be exploited as underlying molecular biomarkers and therapeutic targets for the patients with CRC.

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