基于ceRNA网络识别登革热诊断标志物

通过比较登革热患者和健康人群转录组数据,识别差异基因,构建失调ceRNA网络,筛选关键基因富集分析,解析潜在生物学功能,助力登革热诊断标志物的研究。从GEO数据库下载登革热外周血芯片数据,识别差异基因并进行富集分析。结合miRNA-mRNA互作数据,利用超几何算法和皮尔森相关性计算方法识别登革热失调ceRNA互作对,使用Cytoscape软件可视化ceRNA网络与模块挖掘,对网络模块进行功能富集及外部数据验证表达模式。筛选出251个差异基因,发现其富集在细胞周期等生物学通路中。经外部数据验证,网络模块基因的表达趋势与训练集数据大致相同,表明模块基因在登革热疾病中的潜在诊断效能。本研究可为确定有效的疾病诊断分子标志物提供思路。     

乳腺癌早期筛查和诊断生物标志物研究进展

2020年全球乳腺癌(breast cancer,BC)新发病例达226万例,占全部肿瘤新发病例的11.7%,是全世界发病率最高的癌症。早期发现、早期诊断和早期治疗是降低乳腺癌死亡率及改善预后的关键。尽管乳房X光筛查被广泛用作乳腺癌筛查的工具,但其假阳性、辐射性和过度诊断仍是亟待解决的问题。因此,亟需开发易于获取且稳定可靠的生物标志物,用于乳腺癌无创筛查和诊断。近年来多项研究显示来自乳腺癌患者血液中的循环肿瘤细胞DNA(circulating tumor cell DNA,ctDNA)、癌胚抗原(carcinoembryonic antigen,CEA)、糖类抗原15-3(carbohydrate antigen 15-3,CA15-3)、细胞外囊泡(extracellular vesicles,EV)、循环miRNA和BRCA基因突变等生物标志物,以及来自人体尿液、呼出气体(volatile organic compounds,VOCs)和乳头吸出液(nipple aspirate fluid,NAF)中的磷脂、miRNA、苯乙酮和十六烷等多种生物标志物与乳腺癌早期筛查和诊断密切相关。本文综述了上述生物标志物在乳腺癌早期筛查和诊断中的应用。     

miRNA作为三阴乳腺癌潜在生物标志物的研究进展

三阴乳腺癌(triple-negative breast cancer,TNBC)是指雌激素受体(estrogen receptor,ER)、孕激素受体(progesterone receptor,PR)及人表皮生长因子受体-2(human epidermal growth factor receptor-2,HER-...     

乳腺癌免疫治疗：生物标志物、药物及疫苗

虽然近年来肿瘤的治疗取得较大进展,乳腺癌依旧是威胁女性健康的主要杀手。近年来,乳腺癌相关的免疫治疗取得较大进展,肿瘤浸润淋巴细胞(TILs)、程序性死亡受体 1(PD 1)及其配体PD L1、肿瘤突变负荷等肿瘤标志物对乳腺癌免疫治疗具有预测作用,并与乳腺癌的预后相关。免疫检查点抑制剂,例如PD-1/PD-L1及细胞毒性T淋巴细胞抗原4(CTLA 4)抑制剂在乳腺癌中取得极大进展,各期临床试验结果显示不同的效用。肿瘤疫苗的使用为乳腺癌免疫治疗的另一途径,虽然部分疫苗在临床试验中取得较好成效,但绝大多数仍需深入研究,乳腺癌免疫治疗之途仅为开端,依旧需要大量研究。本文简要介绍了乳腺癌免疫治疗相关的生物标志物、免疫检查点抑制剂以及肿瘤疫苗的研究进展。     

联合TCGA和GEO数据库筛选乳腺癌易感基因

本研究是利用公共基因芯片数据库筛选乳腺癌的预后基因,预测和探索这些基因在乳腺癌进展中的可能机制和临床价值.首先,我们筛选了公共基因芯片数据库(gene expression omnibus,GEO)GSE22820和癌症基因组图谱(the cancer genome atlas,TCGA)乳腺癌数据库的重叠差异表达基因,联合R语言分析乳腺癌组织与癌旁正常组织差异表达的基因;其次,基于STRING数据库及Cytoscape软件构建蛋白质相互作用网络图,分析并识别了中枢基因和前3个模块;之后进行了更多的功能分析,包括基因本体(gene ontology,GO)和京都基因与基因组百科全书(kyoto encyclopedia of genes and genomes,KEGG)通路分析以及基因集富集分析(gene set enrichment analysis,GSEA),以研究这些基因的作用以及潜在的潜在机制;最后进行了Kaplan-Meier分析和Cox比例风险分析,以阐明这些基因的诊断和预后效果.相关数据分析表明15个基因的表达水平与生存预后相关,高表达基因患者的总生存时间短于低表达患者(P＜0.05);Cox比例风险分析表明UBE2T、ER-CC6L和RAD51这3个基因是预后生存的独立因素(P＜0.05);GSEA分析表明在UBE2T、ERCC6L和RAD51基因中细胞周期、基础转录因子和卵母细胞减数分裂明显富集.最终,我们得出结论,这3种基因标志物的高表达是乳腺癌预后不良因素,可作为预测乳腺癌患者转移和预后的有效生物标志物.     

高血压性心脏病生物标志物的筛选：基于中国重庆市7家医疗机构的数据分析研究*

目的: 筛选高血压性心脏病（HHD）的影响因素,建立HHD的预测模型,为HHD的发生提供预警。方法: 选取中国重庆市某医科院校数据研究院平台2016年1月1日至2019年12月31日主要诊断为高血压性心脏病和高血压患者。通过单因素分析、多因素分析筛选HHD的影响因素,采用R语言分别构建Logistics模型、随机森林（RF）模型和极限梯度上升（XGBoost）模型。结果: 单因素分析筛选出60项差异指标,多因素分析筛选出18项差异指标（P<0.05）。Logistics模型、RF模型、XGBoost模型曲线下面积（AUC）分别为0.979、0.983和0.990。结论: 本文建立的3种HHD预测模型结果稳定,其中XGBoost模型对于HHD的发生具有良好的诊断效应。     

基于TCGA和GEO数据库的胃癌lncRNA筛选与ceRNA网络构建

胃癌(gastric cancer,GC)是我国最常见的恶性肿瘤之一,严重危害人类健康。胃癌发病机制复杂,缺乏特异性预后生物标志物。长链非编码RNA (long non-coding RNA,lncRNA)可作为竞争性内源RNA (competing endogenous RNA,ceRNA),影响microRNA (miRNA)与mRNA的结合,从而影响胃癌的发生、发展。基于TCGA和GEO数据库的转录组数据,筛选GC 中差异表达的 lncRNAs,并构建基于 6 条 lncRNAs(HAGLROS、TMEM92-AS1、LINC01745、HOXC-AS3、SEMA3B-AS1、FEZF1-AS 1)的lncRNA-miRNA-mRNA网络。网络核心基因的KEGG/GO富集和蛋白质互作分析结果显示,lncRNA可能通过miRNA海绵吸附作用,调控胃癌的发生、发展与转移。AC011352.1、AC087636.1、AC093627.1、GAS1RR与胃癌患者的预后相关性具有统计学意义(P<0.05),并可能成为胃癌患者潜在的预后生物标志物。     

铅中毒的暴露生物标志物

铅是严重威胁人类健康的一种环境污染物,尤其对儿童神经系统的发育以及学习记忆等产生不良的影响。因此,铅毒性的早期预防、早期诊断以及早期治疗尤为重要。生物标志物是公共卫生领域尤其是环境医学领域的一个研究热点,选择合适的生物标志物对于开展铅毒性的生物监测,实现铅生物效应的早期预警、早期干预等都具有重要的作用。本文就现有的主要铅暴露生物标志物的现状作一归纳。     

铅中毒的暴露生物标志物

铅是严重威胁人类健康的一种环境污染物,尤其对儿童神经系统的发育以及学习记忆等产生不良的影响.因此,铅毒性的早期预防、早期诊断以及早期治疗尤为重要.生物标志物是公共卫生领域尤其是环境医学领域的一个研究热点,选择合适的生物标志物对于开展铅毒性的生物监测,实现铅生物效应的早期预警、早期干预等都具有重要的作用.本文就现有的主要铅暴露生物标志物的现状作一归纳.     

联合TCGA和GEO数据库构建和分析胃癌中circRNA相关的ceRNA网络

环状RNA (circular RNA, circRNA)是一类呈闭环状结构的竞争性内源RNA (competing endogenous RNA, ceRNA),其通过竞争性地吸附微RNA (microRNA, mi RNA)来调节基因表达。circRNA失调与癌细胞的增殖、分化和侵袭等密切相关。本研究基于生物信息学分析和多数据库的联合应用,以ceRNA为切入点探析胃癌中circRNA潜在的致病机制,以期为胃癌提供潜在的临床诊疗靶点,并为胃癌的科学研究提供新思路。首先,通过挖掘胃癌差异表达的circRNA、mi RNA和m RNA构建circRNA-miRNA-mRNA ceRNA网络;随后,利用网络拓扑属性分析确定核心的节点,并根据这些核心的节点从原始的ceRNA网络中提取子网;最后,对子网进行功能学分析和生存分析,分析网络行使的生物学功能并挖掘预后相关的基因。结果显示:共挖掘了6个核心节点(hsa_circ_0008468、hsa_circ_0005822、hsa_circ_0025842、hsa-miR-940、hsa-miR-944及hsa-miR-515-5p);从原始的ceRNA网络中提取了包含8对circRNA-miRNA和539个mi RNA-m RNA关系对的子网络。功能富集结果表明子网涉及癌症相关的多个生物学过程,包括代谢途径、cAMP信号通路、pathways in cancer信号通路等,生存分析发现子网中ACO2、E2F8、GHR、ITIH5等14基因与预后显著相关,这表明3个核心circRNA介导的ceRNA网络与胃癌的发生发展及预后密切相关。     

Feasibility of Breast Cancer Screening by PIXE Analysis of Hair

To reveal the role of key elements present in the hair of breast cancer patients on cancer development, the levels of a number of elements in scalp hair samples of 82 people including healthy individuals, people suffering from benign breast disease, and breast cancer patients were measured by PIXE analysis. Pellets of hair samples were prepared and bombarded by 2.2 MeV proton beam of a 3-MV Van de Graaff accelerator. The number of incident ions hitting the sample was indirectly measured using the RBS spectrum of a thin Ag film placed in the beam path. The concentrations of S, Cl, K, Ca, Fe, and Cu in the hair of healthy individuals were in agreement with those observed in the hair of hyperplasia and cancer patients within standard deviations. However, a lower average level of zinc was found in samples from hyperplasia and breast cancer patients. Strong positive correlations were found between iron and potassium as well as between calcium and potassium in the cancer patients. These results could be of significance in the screening for breast cancer.     

Circulating microRNAs as Specific Biomarkers for Breast Cancer Detection

Background

We previously showed microRNAs (miRNAs) in plasma are potential biomarkers for colorectal cancer detection. Here, we aimed to develop specific blood-based miRNA assay for breast cancer detection.

Methodology/Principal Findings

TaqMan-based miRNA profiling was performed in tumor, adjacent non-tumor, corresponding plasma from breast cancer patients, and plasma from matched healthy controls. All putative markers identified were verified in a training set of breast cancer patients. Selected markers were validated in a case-control cohort of 170 breast cancer patients, 100 controls, and 95 other types of cancers and then blindly validated in an independent set of 70 breast cancer patients and 50 healthy controls. Profiling results showed 8 miRNAs were concordantly up-regulated and 1 miRNA was concordantly down-regulated in both plasma and tumor tissue of breast cancer patients. Of the 8 up-regulated miRNAs, only 3 were significantly elevated (p<0.0001) before surgery and reduced after surgery in the training set. Results from the validation cohort showed that a combination of miR-145 and miR-451 was the best biomarker (p<0.0001) in discriminating breast cancer from healthy controls and all other types of cancers. In the blind validation, these plasma markers yielded Receiver Operating Characteristic (ROC) curve area of 0.931. The positive predictive value was 88% and the negative predictive value was 92%. Altered levels of these miRNAs in plasma have been detected not only in advanced stages but also early stages of tumors. The positive predictive value for ductal carcinoma in situ (DCIS) cases was 96%.

Conclusions

These results suggested that these circulating miRNAs could be a potential specific biomarker for breast cancer screening.     

Observed and Predicted Risk of Breast Cancer Death in Randomized Trials on Breast Cancer Screening

BackgroundThe role of breast screening in breast cancer mortality declines is debated. Screening impacts cancer mortality through decreasing the number of advanced cancers with poor diagnosis, while cancer treatment works through decreasing the case-fatality rate. Hence, reductions in cancer death rates thanks to screening should directly reflect reductions in advanced cancer rates. We verified whether in breast screening trials, the observed reductions in the risk of breast cancer death could be predicted from reductions of advanced breast cancer rates.ResultsThe observed and predicted RR of breast cancer death were 0.72 (0.56–0.94) and 0.98 (0.77–1.24) in the HIP trial, and 0.79 (0.78–1.01) and 0.90 (0.80–1.01) in the Age trial. In the TCT, the observed RR was 0.73 (0.62–0.87), while the predicted RR was 0.89 (0.75–1.05) if overdiagnosis was assumed to be negligible and 0.83 (0.70–0.97) if extra cancers were excluded.ConclusionsIn breast screening trials, factors other than screening have contributed to reductions in the risk of breast cancer death most probably by reducing the fatality of advanced cancers in screening groups. These factors were the better management of breast cancer patients and the underreporting of breast cancer as the underlying cause of death. Breast screening trials should publish stage-specific fatalities observed in each group.     

Identification and Validation of Oncologic miRNA Biomarkers for Luminal A-like Breast Cancer

Introduction

Breast cancer is a common disease with distinct tumor subtypes phenotypically characterized by ER and HER2/neu receptor status. MiRNAs play regulatory roles in tumor initiation and progression, and altered miRNA expression has been demonstrated in a variety of cancer states presenting the potential for exploitation as cancer biomarkers. Blood provides an excellent medium for biomarker discovery. This study investigated systemic miRNAs differentially expressed in Luminal A-like (ER+PR+HER2/neu-) breast cancer and their effectiveness as oncologic biomarkers in the clinical setting.

Methods

Blood samples were prospectively collected from patients with Luminal A-like breast cancer (n = 54) and controls (n = 56). RNA was extracted, reverse transcribed and subjected to microarray analysis (n = 10 Luminal A-like; n = 10 Control). Differentially expressed miRNAs were identified by artificial neural network (ANN) data-mining algorithms. Expression of specific miRNAs was validated by RQ-PCR (n = 44 Luminal A; n = 46 Control) and potential relationships between circulating miRNA levels and clinicopathological features of breast cancer were investigated.

Results

Microarray analysis identified 76 differentially expressed miRNAs. ANN revealed 10 miRNAs for further analysis (miR-19b, miR-29a, miR-93, miR-181a, miR-182, miR-223, miR-301a, miR-423-5p, miR-486-5 and miR-652). The biomarker potential of 4 miRNAs (miR-29a, miR-181a, miR-223 and miR-652) was confirmed by RQ-PCR, with significantly reduced expression in blood of women with Luminal A-like breast tumors compared to healthy controls (p = 0.001, 0.004, 0.009 and 0.004 respectively). Binary logistic regression confirmed that combination of 3 of these miRNAs (miR-29a, miR-181a and miR-652) could reliably differentiate between cancers and controls with an AUC of 0.80.

Conclusion

This study provides insight into the underlying molecular portrait of Luminal A-like breast cancer subtype. From an initial 76 miRNAs, 4 were validated with altered expression in the blood of women with Luminal A-like breast cancer. The expression profiles of these 3 miRNAs, in combination with mammography, has potential to facilitate accurate subtype-specific breast tumor detection.