scholarly journals Identification of ZG16B as a prognostic biomarker in breast cancer

Open Medicine ◽  
2020 ◽  
Vol 16 (1) ◽  
pp. 1-13
Author(s):  
Haotian Lu ◽  
Chunying Shi ◽  
Xinyu Liu ◽  
Chen Liang ◽  
Chaochao Yang ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Survival Analysis ◽  
Prognostic Biomarker ◽  
Cancer Cell Line ◽  
Zymogen Granule ◽  
Favorable Prognosis ◽  
Kaplan Meier ◽  
Different Types ◽  
Kaplan Meier Plotter ◽  
Low Expression

AbstractZymogen granule protein 16B (ZG16B) has been identified in various cancers, while so far the association between ZG16B and breast cancer hasn’t been explored. Our aim is to confirm whether it can serve as a prognostic biomarker in breast cancer. In this study, Oncomine, Cancer Cell Line Encyclopedia (CCLE), Ualcan, and STRING database analyses were conducted to detect the expression level of ZG16B in breast cancer with different types. Kaplan–Meier plotter was used to analyze the prognosis of patients with high or low expression of ZG16B. We found that ZG16B was significantly upregulated in breast cancer. Moreover, ZG16B was closely associated with foregone biomarkers and crucial factors in breast cancer. In the survival analysis, high expression of ZG16B represents a favorable prognosis in patients. Our work demonstrates the latent capacity of ZG16B to be a biomarker for prognosis of breast cancer.

scholarly journals CXCL2 as a Prognostic Marker in Breast Cancer is Associated with Immune Infiltration and Regulated by miR-215

2020 ◽  
Author(s):  
Jia-Xiang An ◽  
Ying-Ying Chen ◽  
Zhao-Sheng Ma ◽  
Wen-Jie Yu ◽  
Jin-Xi Hu ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Survival Time ◽  
Cancer Patients ◽  
Breast Cancer Patients ◽  
Clinical Prognosis ◽  
Immune Infiltration ◽  
Kaplan Meier ◽  
The Impact ◽  
Kaplan Meier Plotter ◽  
Low Expression

Abstract Background: CXCL2 is a part of chemokine superfamily, which encodes secretory proteins involved in immune regulation and inflammation. The correlation between CXCL2 and prognosis of different cancers, tumor infiltrating lymphocytes are not clear. Methods: We analyzed the expression of CXCL2 and its effect on clinical prognosis through Oncomine database, Tumor Immune Estimation Resource (TIMER) website, Kaplan-Meier plotter, PrognoScan database and Gene Expression Profiling Interactive Analysis (GEPIA). TIMER and GEPIA were used to analyze the correlation between CXCL2 and the gene marker of immune infiltration. StarBase was used to predict the miRNA that may regulate CXCL2. The relationship between miR-532-5p and CXCL2 was detected by qRT-PCR. Kaplan-Meier plotter was used to evaluate the impact of miR-532-5p on clinical prognosis. Results: PrognoScan, Kaplan-Meier plotter and GEPIA database analysis showed that low expression of CXCL2 was associated with poor disease-specific survival time (DSS), relapse-free survival time (RFS) and overall disease survival (OS) in breast cancer patients. In addition, low expression of CXCL2 was associated with poor OS and RFS in patients with lymph node positive breast cancer. CXCL2 expression was positively correlated with the infiltration of B cells, CD4+T and CD8+T cells, neutrophils and dendritic cells (DCs) in BRCA, mainly in Luminal breast cancer. MiR-532-5p can directly regulate CXCL2 expression. High miR-532-5p expression is significantly correlated with HER2 negative, grade 2 and 3 and poor OS in patients with HER+ER- breast cancer. Conclusion: CXCL2 is closely related to the prognosis and immune infiltration level of breast cancer patients, it can be regulated by miR-532-5p.

scholarly journals ACSL3 As a Potential Prognostic Biomarker in Patients With Breast Cancer

2021 ◽  
Author(s):  
Xiangyu Sun ◽  
Meng Li ◽  
Mozhi Wang ◽  
Mengshen Wang ◽  
Haoran Dong ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Cancer Patients ◽  
Potential Function ◽  
Prognostic Value ◽  
Prognostic Biomarker ◽  
Human Protein ◽  
Breast Cancer Patients ◽  
Kaplan Meier ◽  
Human Protein Atlas ◽  
Kaplan Meier Plotter

Abstract Objective: To explore the expression pattern of long chain fatty acyl CoA synthetase 3 (ACSL3) in breast cancer, and evaluate the clinical significance of ACSL3 by analyzing potential function and prognostic value of ACSL3 in human breast carcinoma.Methods: The expression of ACSL3 in normal mammary tissues and breast tumor tissues was analyzed by GEPIA and Human Protein Atlas. The prognostic value of ACSL3 was evaluated by Kaplan–Meier plotter analysis. ACSL3 expression was analyzed by immunohistochemistry in 297 breast cancer patients from the First Hospital of China Medical University Furthermore, based on LinkedOmics database, analyses of GO and KEGG pathways were performed to identify the potential function of ACSL3. Tumor Immune Estimation Resource (TIMER) database was used to evaluate the association between ACSL3 and immune infiltration in breast cancer. Results: GEPIA and Human Protein Atlas indicated that ACSL3 was significantly upregulated in breast carcinomas. Kaplan-Meier plotter analysis showed that increased expression of ACSL3 mRNA was significantly associated with shorter overall survival (OS) and relapse-free survival (RFS) in breast cancer patients. Results from immunochemical staining showed that ACSL3 was obviously related to clinicopathological features of breast cancer, and ACSL3 was highly abundant in TNBC tumors. Moreover, survival analysis of breast cancer patients demonstrated that higher ACSL3 protein expression is unfavorable prognostic biomarker in breast cancer patients. Results from TIMER database indicated that ACSL3 expression was significantly correlated with infiltration level of multiple immune cells. Further studies are needed to explore underlying mechanism of the pro-tumor effects of ACSL3 expression.Conclusions: ACSL3 may not only serve as a reliable predictive biomarker of breast cancer but also have impact on the occurrence and progression of breast cancer. Thus, ACSL3 may be an emerging therapeutic target for the development of molecular-targeted therapeutic strategies for breast cancer.

scholarly journals Overexpressed pseudogene MT1L associated with tumor immune infiltrates and indicates a worse prognosis in BLCA

2021 ◽  
Vol 19 (1) ◽  
Author(s):  
Yanpeng Ding ◽  
Nuomin Liu ◽  
Mengge Chen ◽  
Yulian Xu ◽  
Sha Fang ◽  
...  
Keyword(s):  
Immune Cells ◽  
Biological Function ◽  
Prognostic Biomarker ◽  
Poor Survival ◽  
Common Cancer ◽  
Kaplan Meier ◽  
Cox Analysis ◽  
Kaplan Meier Plotter ◽  
Worse Prognosis

Abstract Background BLCA is a common cancer worldwide, and it is both aggressive and fatal. Immunotherapy (ICT) has achieved an excellent curative effect in BLCA; however, only some BLCA patients can benefit from ICT. MT1L is a pseudogene, and a previous study suggested that MT1L can be used as an indicator of prognosis in colorectal cancer. However, the role of MT1L in BLCA has not yet been determined. Methods Data were collected from TCGA, and logistic regression, Kaplan-Meier plotter, and multivariate Cox analysis were performed to demonstrate the correlation between the pseudogene MT1L and the prognosis of BLCA. To identify the association of MT1L with tumor-infiltrating immune cells, TIMER and TISIDB were utilized. Additionally, GSEA was performed to elucidate the potential biological function. Results The expression of MT1L was decreased in BLCA. Additionally, MT1L was positively correlated with immune cells, such as Tregs (ρ = 0.708) and MDSCs (ρ = 0.664). We also confirmed that MT1L is related to typical markers of immune cells, such as PD-1 and CTLA-4. In addition, a high MT1L expression level was associated with the advanced T and N and high grade in BLCA. Increased expression of MT1L was significantly associated with shorter OS times of BLCA patients (p < 0.05). Multivariate Cox analysis revealed that MT1L expression could be an independent prognostic factor in BLCA. Conclusion Collectively, our findings demonstrated that the pseudogene MT1L regulates the immune microenvironment, correlates with poor survival, and is an independent prognostic biomarker in BLCA.

scholarly journals Identification of Flap Endonuclease 1 With Diagnostic and Prognostic Value in Breast Cancer

2021 ◽  
Vol 11 ◽  
Author(s):  
Min Wu ◽  
Pan Zhang ◽  
Penghui Wang ◽  
Zhen Fang ◽  
Yaqin Zhu
Keyword(s):  
Breast Cancer ◽  
Prognostic Marker ◽  
Prognostic Value ◽  
Diagnostic Value ◽  
Roc Curve Analysis ◽  
Free Survival ◽  
Flap Endonuclease 1 ◽  
Normal Tissues ◽  
Kaplan Meier ◽  
Kaplan Meier Plotter

ObjectiveThis study aims to identify the potential value of flap endonuclease 1 (FEN1) as a diagnostic and prognostic marker for breast cancer (BC).MethodsELISA was used to measure serum FEN1 levels and ECLIA for CA153 and CEA levels. Receiver operating characteristic (ROC) curve analysis was used to evaluate the diagnostic value. Oncomine and UALCAN databases were used to analyze the differences in FEN1 mRNA and protein expressions. Kaplan-Meier Plotter database was then used to assess the prognostic value.ResultsBioinformatics analysis showed that the FEN1 mRNA and protein levels were significantly higher in BC tissues than in normal tissues. FEN1 was detected in culture medium of BC cell lines and serum FEN1 concentrations were significantly increased in BC patients than in cancer-free individuals. Besides, FEN1 exhibited higher diagnostic accuracy (AUC values&gt;0.800) than CA153 and CEA for distinguishing BC patients, especially early BC, from the healthy and benign groups, or individually. Additionally, serum FEN1 levels were significantly associated with the stage (P=0.001) and lymph invasion (P=0.016), and serum FEN1 levels were increased with the development of BC. Furthermore, serum FEN1 levels were significantly decreased in post-operative patients than in pre-operative patients (P=0.016). Based on the Kaplan-Meier Plotter database, the survival analysis indicated that FEN1 overexpression was associated with poor prognoses for overall survival (OS), relapse-free survival (RFS), and distant metastasis-free survival (DMFS) in BC patients.ConclusionFEN1 might be a novel diagnostic and prognostic marker for BC.

scholarly journals The Alterations and Potential Roles of MCMs in Breast Cancer

2021 ◽  
Vol 2021 ◽  
pp. 1-17
Author(s):  
Xinyu Liu ◽  
Ying Liu ◽  
Qiangshan Wang ◽  
Siqi Song ◽  
Lingjun Feng ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Gene Network ◽  
Relapse Free Survival ◽  
Minichromosome Maintenance ◽  
Free Survival ◽  
Oncomine Database ◽  
Kaplan Meier ◽  
Eukaryotic Dna ◽  
Coexpressed Genes ◽  
Kaplan Meier Plotter

The minichromosome maintenance (MCM) protein family plays a key role in eukaryotic DNA replication and has been confirmed to be associated with the occurrence and progression of many tumors. However, the expression levels, functions, and prognostic values of MCMs in breast cancer (BC) have not been clearly and systematically explained. In this article, we studied the transcriptional levels of MCMs in BC based on the Oncomine database. Kaplan-Meier plotter was used to analyze prognostic value of MCMs in human BC patients. Furthermore, we constructed a MCM coexpression gene network and performed functional annotation analysis through DAVID to reveal the functions of MCMs and coexpressed genes. The data showed that the expression of MCM2–8 and MCM10 but not MCM1 and MCM9 was upregulated in BC. Kaplan-Meier plotter analysis revealed that high transcriptional levels of MCM2, MCM4–7, and MCM10 were significantly related to low relapse-free survival (RFS) in BC patients. In contrast, high levels of MCM1 and MCM9 predicted high RFS for BC patients. This study suggests that MCM2, MCM4–7, and MCM10 possess great potential to be valuable prognostic biomarkers for BC and that MCM1 and MCM9 may serve as potential treatment targets for BC patients.

scholarly journals NaPi- II b as a potential diagnostic and prognostic biomarker in ovarian cancers

2018 ◽  
Author(s):  
Shoufeng Zhao ◽  
Zhipeng Wang
Keyword(s):  
Ovarian Cancer ◽  
Cancer Cell Line ◽  
Normal Tissues ◽  
Diagnosis And Prognosis ◽  
Kaplan Meier ◽  
Potential Biomarker ◽  
Tumor Types ◽  
First Time ◽  
Kaplan Meier Plotter ◽  
Normal Controls

ABSTRACTOvarian cancer (OC) is commonly diagnosed at an advanced stage due to a lack of effective biomarkers and specificity required for accurate clinical diagnosis. The purpose of this study was to estimate the diagnosis and prognosis of the NaPi- II b in ovarian cancer. Herein, by performing data mining using the databases of Oncomine and Cancer Cell Line Encyclopedia (CCLE), we are for the first time to report that the expression level of NaPi- II b transcripts in a variety of tumor types compared with the normal controls. Based on Kaplan-Meier plotter, we investigated the prognostic values of NaPi- II b specifically high expressed in OC patients. The results of the Oncomine analysis showed that relative expression of NaPi- II b was distinctly high in OC tissues vs. normal tissues. CCLE analysis indicated that the expression of NaPi- II b in OC cell lines expressed the highest level in all cancer lines. In overall survival (OR) analysis, NaPi- II b mRNA high expressions were correlated to worse OR in OC patients. These results indicate that NaPi- II b may be a novel potential biomarker for determining the diagnosis and predicting the prognosis of OC.

scholarly journals Nomogram Models Based on Gene Expression in Prediction of Breast Cancer Bone Metastasis

2021 ◽  
Author(s):  
Teng-di Fan ◽  
Di-kai Bei ◽  
Song-wei Li
Keyword(s):  
Breast Cancer ◽  
Gene Expression ◽  
Bone Metastasis ◽  
Gene Signature ◽  
Functional Enrichment ◽  
Training Set ◽  
Hub Genes ◽  
Kaplan Meier ◽  
Patient Prognosis ◽  
Kaplan Meier Plotter

Abstract Objective: To design a weighted co-expression network and build gene expression signature-based nomogram (GESBN) models for predicting the likelihood of bone metastasis in breast cancer (BC) patients. Methods: Dataset GSE124647 was used as a training set, and GSE14020 was taken as a validation set. In the training cohort, limma package in R was adopted to obtain differentially expressed genes (DEGs) between BC non-bone metastasis and bone metastasis patients, which were used for functional enrichment analysis. After weighted co-expression network analysis (WGCNA), univariate Cox regression and Kaplan-Meier plotter analyses were performed to screen potential prognosis-related genes. Then, GESBN models were constructed and evaluated. Further, the expression levels of genes in the models were explored in the training set, which was validated in GSE14020. Finally, the prognostic value of hub genes in BC was explored. Results: A total of 1858 DEGs were obtained. WGCNA result showed that the blue module was most significantly related to bone metastasis and prognosis. After survival analyses, GAJ1, SLC24A3, ITGBL1, and SLC44A1 were subjected to construct a GESBN model for overall survival. While GJA1, IGFBP6, MDFI, ITGFBI, ANXA2, and SLC24A3 were subjected to build a GESBN model for progression-free survival. Kaplan-Meier plotter and receiver operating characteristic analyses presented the reliable prediction ability of the models. Besides, GJA1, IGFBP6, ITGBL1, SLC44A1, and TGFBI expressions were significantly different between the two groups in GSE124647 and GSE14020. The hub genes had a significant impact on patient prognosis. Conclusion: Both the four-gene signature and six-gene signature could accurately predict patient prognosis, which may provide novel treatment insights for BC bone metastasis.

Gasdermin D as a potential prognosis and treatment response prediction biomarker for invasive breast cancer.

2021 ◽  
Vol 39 (15_suppl) ◽  
pp. e12548-e12548
Author(s):  
Xianghou Xia ◽  
Wenjuan Yin ◽  
Jiefei Mao ◽  
Jiejie Hu ◽  
Dehong Zou ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Cancer Patients ◽  
Invasive Breast Cancer ◽  
Response Prediction ◽  
Chemotherapy Response ◽  
Breast Cancer Patients ◽  
Free Survival ◽  
Kaplan Meier ◽  
Kaplan Meier Plotter ◽  
Treatment Response Prediction

e12548 Background: Pyroptosis is a type of inflammatory cell death mediated by gasdermins. Pyroptosis is critical for macrophage against pathogen infection. Recently growing evidences show that pyroptosis may affect development and progression of many cancers. We aim to explore the expression and related function of pyroptosis executioner Gasdermin D (GSDMD) in breast cancer. Methods: We investigated the expression level of GSDMD using TNM plotter and Breast Cancer landscape proteome with TCGA, GTEx and TARGET databases, and the prognostic value of GSDMD in invasive breast cancer using Kaplan-Meier plotter with TCGA, GEO and EGA databases. The treatment response prediction values of GSDMD in invasive breast were calculated using ROC-plotter with GEO database. Further validation of the prognostic value and chemotherapy response prediction value of GSDMD were carried out with immunohistochemical staining on tissues from 165 cases of breast cancer patients receiving neoadjuvant chemotherapy in our cancer center. Results: TNM plotter and breast cancer landscape proteome portal analysis shows that overall expression level of GSDMD in invasive breast cancer tissue is 1.67 folds higher than it is in breast normal tissues ( p=1.05*e-06). Expression of GSDMD in LuminalB subtype (p=0.019) and Her2 subtype(p=0.04) is significantly higher than it is in TNBC subtype. Calculations with Kaplan-Meier plotter show expression of GSDMD is negatively correlated with overall survival(OS), HR=0.61(0.4−0.95) p=0.027 and relapse free survival (RFS), HR =0.65(0.58−0.63), p=8.7*e-14 and distant metastasis free survival (DMFS) HR =0.75(0.61−0.91), p=0.0038 in breast cancer patients. ROC-plotter calculations show high GSDMD expression is a powerful endocrine therapy (AUC=0.731 p=6*e-09 ) and chemotherapy response (AUC=0.64 p=8*e-05 ) predictor based on 5-year RFS in overall breast cancer patients. Our IHC staining analysis shows consistent prognostic and chemotherapy prediction value of GSDMD expression in TNBC patients. Conclusions: In conclusion, our findings suggest that high expression of GSDMD is positively correlated with prognosis and therapeutic response in breast cancer. GSDMD is a promising prognostic marker and therapeutic response predictor in invasive breast cancer.

scholarly journals Expression and Prognostic Characteristics of m6 A RNA Methylation Regulators in Breast Cancer

2020 ◽  
Vol 11 ◽  
Author(s):  
Bo Zhang ◽  
Yanlin Gu ◽  
Guoqin Jiang
Keyword(s):  
Breast Cancer ◽  
Gene Expression ◽  
Cancer Patients ◽  
High Expression ◽  
Cancer Gene ◽  
Breast Cancer Patients ◽  
Rna Methylation ◽  
Kaplan Meier ◽  
Her 2 ◽  
Kaplan Meier Plotter

PurposeN6-methyladenosine (m6A) is the most prevalent modification in mRNA methylation which has a wide effect on biological functions. This study aims to figure out the efficacy of m6A RNA methylation regulator-based biomarkers with prognostic significance in breast cancer.Patients and MethodsThe 23 RNA methylation regulators were firstly analyzed through ONCOMINE, then relative RNA-seq transcriptome and clinical data of 1,096 breast cancer samples and 112 normal tissue samples were acquired from The Cancer Gene Atlas (TCGA) database. The expressive distinction was also showed by the Gene Expression Omnibus (GEO) database. The gene expression data of m6A RNA regulators in human tissues were acquired from the Genotype-Tissue Expression (GTEx) database. The R v3.5.1 and other online tools such as STRING, bc-GeneExminer v4.5, Kaplan-Meier Plotter were applied for bioinformatics analysis.ResultsResults from ONCOMINE, TCGA, and GEO databases showed distinctive expression and clinical correlations of m6A RNA methylation regulators in breast cancer patients. The high expression of YTHDF3, ZC3H13, LRPPRC, and METTL16 indicated poor survival rate in patients with breast cancer, while high expression of RBM15B pointed to a better survival rate. Both univariate and multivariate Cox regression analyses revealed that age and risk scores were related to overall survival (OS). Univariate analysis also delineated that stage, tumor (T) status, lymph node (N) status, and metastasis (M) status were associated with OS. From another perspective, Kaplan-Meier Plotter platform showed that the relatively high expression of YTHDF3 and LRPPRC and the relatively low expression of RBM15B, ZC3H13, and METTL16 in breast cancer patients had worse Relapse-Free Survival (RFS). Breast Cancer Gene-Expression Miner v4.5 showed that LRPPRC level was negatively associated with ER and PR expression, while METTL16, RBM15B, ZC3H13 level was positively linked with ER and PR expression. In HER-2 (+) breast cancer patients, the expression of LRPPRC, METTL16, RBM15B, and ZC3H13 were all lower than the HER-2 (−) group.ConclusionThe significant difference in expression levels and prognostic value of m6A RNA methylation regulators were analyzed and validated in this study. This signature revealed the potential therapeutic value of m6A RNA methylation regulators in breast cancer.

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