|
|
|
题名
|
作者
|
年代
|
出处
|
被引量
|
| 1 | Hypoxia-induced factor-1 alpha upregulates vascular endothelial growth factor C to promote lymphangiogenesis and angiogenesis in breast cancer patients显示文摘Hypoxia-induced factor-1 alpha(HIF-1α)affects many effector molecules and regulates tumor lymphangiogenesis and angiogenesis during hypoxia.The aim of this study was to investigate the role of HIF-1αin the regulation of vascular endothelial growth factor C(VEGF-C)expression and its effect on lymphangiogenesis and angiogenesis in breast cancer.Lymphatic vessel density(LVD),microvessel density(MVD)and the expressions of HIF-1αand VEGF-C proteins were evaluated by immunohistochemistry in 75 breast cancer samples.There was a significant correlation between HIF-1αand VEGF-C(P=0.014,r=0.273,Spearman's coefficient of correlation).HIF-1αand VEGF-C overexpression was significantly correlated with higher LVD(P=0.003 and P=0.017,respectively),regional lymph nodal involvement(P=0.002 and P=0.004,respectively)and advanced tumor,node,metastasis(TNM)classification(P=0.001 and P=0.01,respectively).Higher MVD was observed in the group expressing higher levels of HIF-1αand VEGF-C(P=0.033 and P=0.037,respectively).Univariate analysis showed shorter survival time in patients expressing higher levels of HIF-1αand VEGF-C.HIF-1αwas also found to be an independent prognostic factor of overall survival in multivariate analysis.The results suggest that HIF-1αmay affect VEGF-C expression,thus acting as a crucial regulator of lymphangiogenesis and angiogenesis in breast cancer.This study highlights promising potential of HIF-1αas a therapeutic target against tumor lymph node metastasis. | Xiaojian Ni Yingchun Zhao Jingjing Ma Tiansong Xia Xiaoan Liu Qiang Ding Xiaoming Zha Shui Wang | 2013 | The Journal of Biomedical Research2013，27，6： | 10 |
| 2 | Isolation and identification of lactic acid bacteria from Tarag in Eastern Inner Mongolia of China by 16S rRNA sequences and DGGE analysis显示文摘 | Wenjun Liu Qiuhua Bao Jirimutu Manjun Qing Siriguleng Xia Chen Ting Sun Meihua Li Jiachao Zhang Jie Yu Menghe Bilige Tiansong Sun Heping Zhang | 2011 | Microbiological Research2011，，2： | 2 |
| 3 | Value of negatively correlated miR-205-5p/HMGB3 and miR-96-5p/FOXO1 on the diagnosis of breast cancer and benign breast diseases显示文摘Background:MicroRNA(miRNA)and mRNA levels in matching specimens were used to identify miRNA–mRNA interactions.We aimed to integrate transcriptome,immunophenotype,methylation,mutation,and survival data analyses to examine the profiles of miRNAs and target mRNAs and their associations with breast cancer(BC)diagnosis.Methods:Based on the Gene Expression Omnibus(GEO)database and The Cancer Genome Atlas(TCGA),differentially expressed miRNAs and targeted mRNAs were screened from experimentally verified miRNA-target interaction databases using Pearson's correlation analysis.We used real-time quantitative reverse transcription polymerase chain reaction to verify BC and benign disease samples,and logistic regression analysis was used to establish a diagnostic model based on miRNAs and target mRNAs.Receiver operating characteristic curve analysis was performed to test the ability to recognize the miRNA-mRNA pairs.Next,we investigated the complex interactions between miRNA-mRNA regulatory pairs and phenotypic hallmarks.Results:We identified 27 and 359 dysregulated miRNAs and mRNAs,respectively,based on the GEO and TCGA databases.Using Pearson's correlation analysis,10 negative miRNA-mRNA regulatory pairs were identified after screening both databases,and the related miRNA and target mRNA levels were assessed in 40 BC tissues and 40 benign breast disease tissues.Two key regulatory pairs(miR-205-5p/High mobility group box 3(HMGB3)and miR-96-5p/Forkhead Box O1(FOXO1))were selected to establish the diagnostic model.They also had utility in survival and clinical analyses.Conclusions:A diagnostic model including two miRNAs and their respective target mRNAs was established to distinguish between BC and benign breast diseases.These markers play essential roles in BC pathogenesis. | Jiaying Li Shuang Peng Xuan Zou Xiangnan Geng Tongshan Wang Wei Zhu Tiansong Xia | 2023 | Cancer Pathogenesis and Therapy2023，1，3： | 0 |
| 4 | An inflammatory-related genes signature based model for prognosis prediction in breast cancer显示文摘Background:Breast cancer has become the most common malignant tumor in the world.It is vital to discover novel prognostic biomarkers despite the fact that the majority of breast cancer patients have a good prognosis because of the high heterogeneity of breast cancer,which causes the disparity in prognosis.Recently,inflammatory-related genes have been proven to play an important role in the development and progression of breast cancer,so we set out to investigate the predictive usefulness of inflammatory-related genes in breast malignancies.Methods:We assessed the connection between Inflammatory-Related Genes(IRGs)and breast cancer by studying the TCGA database.Following differential and univariate Cox regression analysis,prognosis-related differentially expressed inflammatory genes were estimated.The prognostic model was constructed through the Least Absolute Shrinkage and Selector Operation(LASSO)regression based on the IRGs.The accuracy of the prognostic model was then evaluated using the Kaplan-Meier and Receiver Operating Characteristic(ROC)curves.The nomogram model was established to predict the survival rate of breast cancer patients clinically.Based on the prognostic expression,we also looked at immune cell infiltration and the function of immune-related pathways.The CellMiner database was used to research drug sensitivity.Results:In this study,7 IRGs were selected to construct a prognostic risk model.Further research revealed a negative relationship between the risk score and the prognosis of breast cancer patients.The ROC curve proved the accuracy of the prognostic model,and the nomogram accurately predicted survival rate.The scores of tumorinfiltrating immune cells and immune-related pathways were utilized to calculate the differences between the low-and high-risk groups,and then explored the relationship between drug susceptibility and the genes that were included in the model.Conclusion:These findings contributed to a better understanding of the function of inflammatory-related genes in breast cancer,and the prognostic risk model provides a potentially promising prognostic strategy for breast cancer. | JINGYUE FU RUI CHEN ZHIZHENG ZHANG JIANYI ZHAO TIANSONG XIA | 2023 | Oncology Research2023，31，2： | 0 |
您所在的机构暂未开通此部分的功能，请联系管理员