肾透明细胞癌中长链非编码RNA SNHG12的生物信息学分析

目的:探讨长链非编码RNA(lncRNA)SNHG12在肾透明细胞癌(ccRCC)中的意义,并对SNHG12进行靶基因预测,为SNHG12在ccRCC中的进一步研究提供借鉴。方法:利用UALCAN数据库分析ccRCC中SNHG12的差异表达,并对SNHG12进行生存分析;利用RegRNA 2.0、HMDD、targetscan、starBase v3.0、microT-CDS平台预测SNHG12的靶基因,构建SNHG12-microRNAs-mRNAs调控网络;运用FunRich平台对预测的靶基因进行Gene Ontology(GO)分析和KEGG信号转导通路富集分析。结果:SNHG12在ccRCC中的表达明显增高,SNHG12高表达患者的总生存期较低表达患者明显缩短。SNHG12上存在3个与ccRCC相关的microRNAs(hsa-miR-138-5p、hsa-miR-454-3p、hsamiR-497-5p)的可能结合位点,从而调节下游的288个靶基因,构成SNHG12-microRNAs-mRNAs调控网络。在生物学过程中,microRNA靶基因高度富集到碱基、核苷、核苷酸和核酸代谢调节等过程。KEGG通路分析中,microRNA靶基因高度富集到内皮素、IFN-γ等介导的信号通路。结论:SNHG12在ccRCC中表达增高,有望成为ccRCC新的潜在生物学标志物。利用生物信息学方法进行靶基因预测,可为后续SNHG12在ccRCC中的机制研究提供方向。     

胃癌多药耐药相关microRNA的筛选和鉴定

目的:研究胃癌多药耐药相关microRNA并对其进行鉴定、靶基因预测和预测靶基因的生物信息学分析。方法:运用microRNA芯片对胃癌多药耐药细胞SGC7901/ADR和其亲本细胞SGC7901进行microRNA表达谱分析;采用实时定量PCR的方法对差异表达的miRNA进行验证;再运用生物信息学方法对差异表达的miRNA进行靶基因预测;再对预测的靶基因进行GO和KEGG通路分析。结果:与SGC7901相比SGC7901/ADR表达上调超过2倍的miRNA有6个,表达下调超过2倍的有11个。实时定量PCR对共同差异表达的microRNA进行验证显示与芯片结果的一致性。对这17个差异表达的miRNA进行靶基因预测,再对预测得到的靶基因进行GO和KEGG通路分析显示预测的靶基因参与了肿瘤相关通路、MAPK通路、Focal Adhesion通路等。结论:我们初步筛选得到了胃癌多药耐药相关miRNA并对其进行了生物信息学分析,为进一步地探索miRNA在胃癌多药耐药中的作用及其分子机制奠定了基础。     

基于RNA-seq的无量山乌骨鸡(Gallus gallus)肝脏脂代谢相关miRNAs的筛选

为研究无量山乌骨鸡(Gallus gallus)肝组织脂代谢相关miRNA (microRNA)在不同发育阶段的表达特征,本研究采集出壳当日(D1)和168日龄(D168)母鸡肝组织样品作为试验材料,利用DNBSEQ平台进行测序,采用DEGseq筛选差异表达的miRNA及其靶基因,随机选取9个差异表达miRNA进行RT-qPCR验证,KEGG通路分类筛选出脂代谢相关miRNA并进行聚类分析,预测脂代谢相关miRNA靶基因并进行GO和KEGG通路功能富集,构建脂代谢相关miRNA和靶基因关联网络。分析结果表明,筛选出106个差异表达miRNAs,包括54个上调miRNA和52个下调miRNA;聚类得到41个脂代谢相关的miRNAs;预测到38个靶基因,对靶基因的功能注释确定主要富集于甘油磷脂代谢、脂肪酸代谢和鞘脂代谢等脂质代谢相关通路,novel-gga-miR2311-5p-DGKZ、 novel-gga-miR2047-3p-ACACA、 novel-gga-miR866-3p-DGKH是脂代谢相关候选miRNA-mRNA关系对。研究提示无量山乌骨鸡肝组织miRNA在不同发育阶段的表...     

基于转录组测序技术进行静原鸡差异miRNA与mRNA的关联分析

为探究静原鸡肌肉组织肌苷酸沉积过程的分子调控机制,本研究以静原鸡胸肌和腿肌组织作为试验材料,通过转录组测序技术,利用生物信息学分析方法筛选出差异表达miRNA及其靶基因.分析结果表明,静原鸡胸肌和腿肌组织的比较组合中有39个差异表达miRNAs(19个显著上调,20个显著下调).通过miRNA-mRNA互作网络分析可知,一个miRNA可以靶向多个mRNA参与调控多个靶基因的表达.GO富集分析表明,候选靶基因的功能主要富集于三个分支的单一生物过程、细胞内和结构分子活性等.KEGG通路注释表明,候选靶基因显著富集到碳代谢、蛋白酶体通路和氨基酸的生物合成等通路中.选取4个差异表达miRNA的与肌苷酸合成和代谢相关的候选靶基因(POLR2C,GMPR,IMPDH2和APRT)进行实时荧光定量PCR验证,结果表明,定量结果与转录组测序结果趋势一致.该研究结果为阐明地方鸡种肌苷酸特异性沉积过程中miRNA介导的靶基因与肉品风味的关系及其表达分析提供理论依据.     

家族性高胆固醇血症HDL-miRNAs调节血单核细胞功能机制

本研究通过生物信息学方法分析家族性高胆固醇血症患者外周血单核细胞差异表达基因、HDL载体差异表达miRNA及其生物学功能,研究差异HDL-miRNA与单核细胞差异基因的相关性,探讨HDL-miRNA调控外周血单核细胞功能机制,寻找动脉粥样硬化防治新靶点。运用R语言分析GEO数据库共享平台家族性高胆固醇血症外周血单核细胞基因及HDL-miRNA探针芯片得到差异基因及差异miRNA,利用miRwalk2. 0预测miRNA靶基因,并利用STRING进行蛋白互作分析,构建差异miRNA与差异基因之间的调控网络。运用GO及KEGG分析研究基因功能。利用GEO数据(GSE6054)筛选出834个差异表达基因,利用GEO数据(GSE25108)筛选出HDL上差异miRNA28个。交叉匹配得到由19个差异miRNA和56个差异基因组配对的74对miRNA-靶基因。GO富集分析56个差异基因主要富集于肾上腺素受体信号等分子功能。KEGG分析56个差异基因主要富集于造血谱系通路上。家族性高胆固醇血症差异HDL-miRNA与外周血单核细胞差异mRNA具有相关性,HDL-miRNA有通过调控血单核细胞功能的可能性,可能参与高胆固醇血症导致动脉粥样硬化过程。     

hsa-miR-342-3p生物信息学分析

通过生物信息学方法预测hsa-miR-342-3p靶基因及其功能机制。检索Pub Med有关hsa-miR-342-3p的研究报道并进行功能分析;检索miRBase获取hsa-miR-342-3p序列;通过Target Scan,Pictar和PITA数据库预测靶基因并取交集,对其进行组织和疾病特异性表达谱分析、功能富集分析(GO enrichment analysis)、信号转导通路富集分析(Pathway enrichment analysis)和蛋白质相互作用网络分析(PPI analysis)。结果发现:hsa-miR-342-3p序列在多物种间具有高度保守性;hsa-miR-342-3p在肾脏组织和急性淋巴细胞性白血病、乳腺癌疾病中表达水平较高(RPM≥1 000);预测得到14个hsa-miR-342-3p靶基因;靶基因分子功能分别富集于转化生长因子活性、DNA结合和蛋白激酶激活等(P0.05);hsa-miR-342-3p靶基因GO生物学过程主要集中于大分子代谢抑制,肺部组织发育、呼吸系统发育及管状组织发育建成(P0.05);细胞信号通路主要富集于TGF-Beta信号通路、细胞因子、受体作用信号通路及前列腺疾病信号通路(P0.01)。hsa-miR-342-3p在体内分布广泛,预测的靶向TGF-Beta信号通路可能在疾病发生中发挥重要调控作用,是具有潜在研究价值的生物学靶标。     

人胚胎干细胞定向中胚层细胞分化的miRNA-mRNA网络调控

胚胎来源的中胚层细胞可以分化为心血管、血液和肌肉组织等多种类型细胞,而应用人胚胎干细胞分化为中胚层细胞的体外模型可为研究中胚层及其衍生的细胞谱系的分子调控机制提供重要手段。miRNA调控基因的表达通过多条信号通路参与中胚层细胞分化,但其调控机制虽有相关研究却并未完全阐明,特别是从整体水平上探索基因与非编码RNA表达变化及其相互作用的网络调控。该研究根据生物信息学分析,构建通过调节多条信号通路参与人胚胎干细胞向中胚层分化的潜在miRNA-mRNA调控网络,以便更全面地阐明人胚胎干细胞的分化机制。通过基因芯片和二代测序(RNAseq)技术检测筛选人胚胎干细胞诱导分化为中胚层细胞过程差异表达的miRNA和基因,并应用生物信息学分析预测差异表达miRNA的靶基因,将靶基因与差异表达基因取交集获得目标基因。同时,对差异表达基因和目标基因进行GSEA富集、GO注释及KEGG富集分析。最后,构建miRNA-mRNA的调控网络和筛选出关键基因并检测关键基因的表达。该研究共筛选出287个差异表达的miRNA和739个差异表达基因,预测差异表达miRNA的靶基因为13 064个,13 064个靶基因与739个差异表达基因取交集共获得目标基因401个。GSEA和KEGG富集分析发现,多条参与中胚层分化的信号通路,主要涉及Wnt/β-catenin、TGF-β和Hippo三条重要的信号通路。通过构建miRNA-mRNA调控网络,结果显示100个miRNA靶向Wnt/β-catenin通路中的11个基因,59个miRNA靶向TGF-β通路中的7个基因,有106个miRNA靶向Hippo通路中的10个基因。通过RT-qPCR验证三条通路中关键基因的表达。因此,该研究揭示了在中胚层分化过程中,Wnt/β-catenin、TGF-β和Hippo信号通路起了重要的调控作用,可能通过与各种miRNA-mRNA相互作用形成复杂的网络调控系统,精确调控人胚胎干细胞定向分化为中胚层细胞。     

microRNA155在动脉粥样硬化发生过程中的网络调控机制

动脉粥样硬化(atherosclerosis,AS)是一种慢性进行性的血管炎症性疾病,其发病机制主要包括内皮细胞损伤,脂质浸润及炎症介质分泌等。microRNA155(miR-155)是参与AS炎性调控、免疫和自噬信号等通路的微小非编码RNA。系统性研究miR-155及其靶基因的网络调控机制,能全面理解miR-155在AS中的作用,促进其在临床诊断中的应用开发。利用miRNA靶基因预测数据库miRDB、miRmap和Starbase获取miR-155的靶基因集。R语言分析基因表达综合数据库(gene expression omnibus,GEO)共享平台动脉粥样硬化斑块差异表达基因(GSE24702),筛选出18 076个差异表达基因。利用基因集富集分析(gene set enrichment analysis,GSEA)分析,观察这些差异表达基因共同富集在IL6-JAK-STAT3信号通路、炎症反应和TNFα等炎症信号通路。与miR-155靶基因交叉匹配得到371个交集mRNA,其中159个在动脉粥样硬化斑块中上调,212个在动脉粥样硬化斑块中下调。基因本体(gene ontology,GO)及基因组数据库(kyoto encyclopedia of genes and genomes,KEGG)分析研究基因功能,GO富集分析371个差异基因主要富集炎症和凋亡信号通路的负调控等功能,KEGG分析371个差异基因主要富集TGFβ等炎症信号通路。蛋白相互作用网络(protein-protein interaction networks,PPI)分析获得关键节点基因是ARRB2、FBXO11、SOCS1、FBXO22、FBXO30、KRAS、RNF19A、TRIM32、HERC4、PJA1、RCHY1和DET1。本研究表明,miR-155主要通过调控炎症反应等相关信号通路影响斑块细胞炎症、自噬及凋亡等功能,进而影响动脉粥样硬化的各个进程。     

基于生物信息学筛选染料木素抗骨肉瘤靶基因

染料木素是一种天然的小分子物质,在多种肿瘤中显示出抗肿瘤作用,探究染料木素作用于骨肉瘤的靶基因。从DrugBank下载与染料木素有关的靶基因,分别导入string数据库中进行分析,用Cytoscape作出蛋白质相互作用(PPI)网络,同时用插件Cytohubb分析PPI,获得25个关键基因,再用WebGestalt分析25个基因的KEGG通路,选取与骨肉瘤相关通路的靶基因,得到的靶基因用HCMDB数据库验证,最后用miRDB预测靶基因的miRNA并在GSE65071数据库中进行验证。一共筛选出13个与染料木素有关的靶基因,选择其中药理作用不明的11个基因进行后续分析,string数据库中获得284个与11个靶基因有关的基因,使用WebGestalt分析25个关键基因,随后选取NF-kappaB和Rap1信号通路的靶基因在HCMDB数据库中进行验证,最后使用miRDB和GES65071数据库得到hsa-miR-23b-3p,hsa-miR-23a-3p,hsa-miR-141-3p和hsa-miR-200a-3p。研究显示CXCL8,CXCL12,LPAR1和CNR1;hsa-miR-23b-3p,hsa-miR-23a-3p,hsa-miR-141-3p和hsa-miR-200a-3p可能成为骨肉瘤的治疗靶基因。     

Screening and identification of autophagy-related biomarkers for oral squamous cell carcinoma (OSCC) via integrated bioinformatics analysis

Increasing evidences have showed that autophagy played a significant role in oral squamous cell carcinoma (OSCC). Purpose of our study was to explore the prognostic value of autophagy-related genes (ATGs) and screen autophagy-related biomarkers for OSCC. RNA-seq and clinical data were downloaded from The Cancer Genome Atlas (TCGA) database following extracting ATG expression profiles. Then, differentially expressed analysis was performed in R software and a risk score model according to ATGs was established. Moreover, comprehensive bioinformatics analyses were used to screen autophagy-related biomarkers which were later verified in OSCC tissues and cell lines. A total of 232 ATGs were extracted, and 37 genes were differentially expressed in OSCC. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis demonstrated that these genes were mainly located in autophagosome membrane and associated with autophagy. Furthermore, the risk score on basis of ATGs was identified as potential independent prognostic biomarker. Moreover, ATG12 and BID were identified as potential autophagy-related biomarkers of OSCC. This study successfully constructed a risk model, and the risk score could predict the prognosis of OSCC patients accurately. Moreover, ATG12 and BID were identified as two potential independent prognostic autophagy-related biomarkers and might provide new OSCC therapeutic targets.     

Novel Biomarkers for Non-functioning Invasive Pituitary Adenomas were Identified by Using Analysis of microRNAs Expression Profile

The microRNAs (miRNAs) are involved in multiple pathological processes among various types of tumors. However, the functions of miRNAs in benign brain tumors are largely unexplored. In order to explore the pathogenesis of the invasiveness in non-functional pituitary adenoma (NFPA), the miRNAs expression profile was analyzed between invasive and non-invasive non-functional pituitary adenoma by miRNAs microarray. Six most significant differentially expressed miRNAs were identified including four upregulated miRNAs hsa-miR-181b-5p, hsa-miR-181d, hsa-miR-191-3p, and hsa-miR-598 and two downregulated miRNAs hsa-miR-3676-5p and hsa-miR-383. The functions and corresponding signaling pathways of differentially expressed miRNAs were investigated by bioinformatics techniques, including Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis. The result of GO analysis indicates regulation of voltage-gated potassium channel activity, positive regulation of sodium ion transport, positive regulation of GTPase activity, negative regulation of Notch signaling pathway, etc. KEGG pathway reveals a series of biological processes, including prolactin signaling pathway, endocrine and other factor-regulated calcium reabsorption, fatty acid metabolism, neuroactive ligand-receptor interaction, etc. The miRNAs hsa-miR-181a-5p was verified by quantitative real-time PCR, and the expression level was in accordance with the microarray result. Our result can provide the evidence on featured miRNAs which play a prominent role in pituitary adenoma as effective biomarkers and therapeutic targets in the future.     

肾透明细胞癌Caki-1细胞系差异表达基因的生物信息学分析

目的比较肾透明细胞癌Caki-1细胞系与正常肾上皮细胞系ASE-5063中的差异表达基因（DEGs）,寻找潜在的肾透明细胞癌特异性分子标志物。 方法利用GEO数据库自带的GEO2R在线分析工具分析基因芯片GSE78179,将筛选出的DEGs分别导入Metascape、STRING以及Cytoscape进行综合分析并筛选出核心基因。最后使用FunRich等软件对筛选出的核心基因进行GO和KEGG富集分析。 结果共筛选出562个DEGs,其中上调基因345个,下调基因217个。进一步使用MCODE筛选出36个关键基因,GO功能分析发现这些基因与细胞粘附分子活性、趋化因子活性、细胞通讯和信号转导等密切相关;KEGG通路富集结果则表明差异基因主要集中在趋化因子信号通路、TNF信号通路以及NF-κB信号通路等多种与肿瘤相关的通路上。 结论运用生物信息学方法筛选出肾透明细胞癌Caki-1细胞系中DEGs,其中数个核心基因广泛参与多种肿瘤的病理进程,但尚未在肾透明细胞癌有相关研究报道,提示其可能是治疗肾透明细胞癌的潜在靶点。     

The mRNA–miRNA–lncRNA Regulatory Network and Factors Associated with Prognosis Prediction of Hepatocellular Carcinoma

The aim of this study was to identify novel prognostic mRNA and microRNA (miRNA) biomarkers for hepatocellular carcinoma (HCC) using methods in systems biology. Differentially expressed mRNAs, miRNAs, and long non-coding RNAs (lncRNAs) were compared between HCC tumor tissues and normal liver tissues in The Cancer Genome Atlas (TCGA) database. Subsequently, a prognosis-associated mRNA co-expression network, an mRNA–miRNA regulatory network, and an mRNA–miRNA–lncRNA regulatory network were constructed to identify prognostic biomarkers for HCC through Cox survival analysis. Seven prognosis-associated mRNA co-expression modules were obtained by analyzing these differentially expressed mRNAs. An expression module including 120 mRNAs was significantly correlated with HCC patient survival. Combined with patient survival data, several mRNAs and miRNAs, including CHST4, SLC22A8, STC2, hsa-miR-326, and hsa-miR-21 were identified from the network to predict HCC patient prognosis. Clinical significance was investigated using tissue microarray analysis of samples from 258 patients with HCC. Functional annotation of hsa-miR-326 and hsa-miR-21-5p indicated specific associations with several cancer-related pathways. The present study provides a bioinformatics method for biomarker screening, leading to the identification of an integrated mRNA–miRNA–lncRNA regulatory network and their co-expression patterns in relation to predicting HCC patient survival.     

Serum exosomal miR-210 as a potential biomarker for clear cell renal cell carcinoma

Exosomal microRNAs (miRNAs) are suggested to reflect molecular changes occurring in their cells of origin and are potential indicators in the early detection of cancers. This study aimed to determine whether certain exosomal miRNAs from tumor tissue can be used as noninvasive biomarkers for clear cell renal cell carcinoma (ccRCC). Based on ccRCC miRNA expression profiles and the literature, we selected six miRNAs (miR-210, miR-224, miR-452, miR-155, miR-21, and miR-34a) and analyzed their expression in tissues, sera, and serum exosomes through quantitative real-time polymerase chain reaction in hypoxia-induced (with CoCl₂) renal cell lines. miR-210, miR-224, miR-452, miR-155, and miR-21 were upregulated in tumor tissues compared with normal tissues. Serum miR-210 and miR-155 levels were higher in patients with ccRCC than in healthy controls (HCs). Furthermore, only exosomal miR-210 was significantly upregulated in patients with ccRCC than in HCs. Moreover, receiver operating characteristic (ROC) curve analysis revealed an area under the ROC curve of 0.8779 (95% confidence interval, 0.7987-0.9571) and a sensitivity and specificity of 82.5% and 80.0%, respectively. Moreover, exosomal miR-210 was upregulated at an advanced stage, and Fuhrman grade and metastasis decreased significantly one month after surgery. Acute hypoxia exposure activates miR-210 and release of exosomes with upregulated miR-210 in both normal and tumor RCC cell lines and interferes with vacuole membrane protein 1 mRNA expression, especially in the metastatic ccRCC cell line. In conclusion, Serum exosomal miR-210 originating from tumor tissue has potential as a novel noninvasive biomarker for the detection and prognosis of ccRCC.     

Fifteen hub genes associated with progression and prognosis of clear cell renal cell carcinoma identified by coexpression analysis

Renal cell carcinoma (RCC) is the most common type of renal tumor, and the clear cell renal cell carcinoma (ccRCC) is the most frequent subtype. In this study, our aim is to identify potential biomarkers that could effectively predict the prognosis and progression of ccRCC. First, we used The Cancer Genome Atlas (TCGA) RNA-sequencing (RNA-seq) data of ccRCC to identify 2370 differentially expressed genes (DEGs). Second, the DEGs were used to construct a coexpression network by weighted gene coexpression network analysis (WGCNA). Moreover, we identified the yellow module, which was strongly related to the histologic grade and pathological stage of ccRCC. Then, the functional annotation of the yellow module and single-samples gene-set enrichment analysis of DEGs were performed and mainly enriched in cell cycle. Subsequently, 18 candidate hub genes were screened through WGCNA and protein–protein interaction (PPI) network analysis. After verification of TCGA’s ccRCC data set, Gene Expression Omnibus (GEO) data set (GSE73731) and tissue validation, we finally identified 15 hub genes that can actually predict the progression of ccRCC. In addition, by using survival analysis, we found that patients of ccRCC with high expression of each hub gene were more likely to have poor prognosis than those with low expression. The receiver operating characteristic curve showed that each hub gene could effectively distinguish between localized and advanced ccRCC. In summary, our study indicates that 15 hub genes have great predictive value for the prognosis and progression of ccRCC, and may contribute to the exploration of the pathogenesis of ccRCC.     

Identification of a three-miRNA signature as a novel potential prognostic biomarker in patients with clear cell renal cell carcinoma

Current studies suggest that some microRNAs (miRNAs) are associated with prognosis in clear cell renal cell carcinoma (ccRCC). In this paper, we aimed to identify a miRNAs signature to improve prognostic prediction for ccRCC patients. Using ccRCC RNA-Seq data of The Cancer Genome Atlas (TCGA) database, we identified 177 differentially expressed miRNAs between ccRCC and paracancerous tissue. Then all the ccRCC tumor samples were divided into training set and validation set randomly. Three-miRNA signature including miR130b, miR-18a, and miR-223 were constructed by the least absolute shrinkage and selection operator (LASSO) Cox regression model in training set. According to optimal cut-off value of three-miRNA signature risk score, all the patients could be classified into high-risk group and low-risk group significantly. Survival of patients was significantly different between two groups (hazard ratio, 5.58, 95% confidence interval, 3.17-9.80; P < 0.0001), and three-miRNA signature performed favorably prognostic and predictive accuracy. The results were further validated in the validation set and total set. Multivariate Cox regression analyses and subgroup analyses showed that three-miRNA signature was an independent prognostic factor. Two nomograms that integrated three-miRNA signature and three clinicopathological risk factors were constructed to predict overall survival and disease-free survival after surgery for ccRCC patients. Functional enrichment analysis showed the possible roles of three-miRNA signature in some cancer-associated biological processes and pathways. In conclusion, we developed a novel three-miRNA signature that performed reliable prognostic for patient survival with ccRCC, it might facilitate ccRCC patients counseling and individualize management.     

基于生物信息学分析寻找胰腺癌新的诊断和治疗靶点

胰腺癌作为一种消化系统高度恶性的肿瘤性疾病,其发生和进展的分子机制仍不确定。为寻找与胰腺癌发生和进展有关的新的有效治疗靶点和潜在的生物标志物。利用GEO数据库中的GEO2R在线工具对胰腺癌组织和正常对照组织的基因表达进行差异分析并对差异表达基因(DEGs)进行GO功能和KEGG通路富集分析。然后通过GEPIA数据库中胰腺癌的转录数据对候选基因的表达进行验证。Kaplan-Meier法分析各候选基因的预后价值。利用starBase数据库中的7个预测程序对候选基因上游潜在的miRNAs进行预测。此外,还使用miRNet和starBase预测了hsa-miR-20b-5p的上游lncRNAs并利用lncATLAS数据库对潜在的lncRNAs进行亚细胞定位。在本研究中,我们发现胰腺癌组织中LAMA3基因的转录水平明显高于健康对照组织。同时,LAMA3的过表达与胰腺癌患者较差的临床预后相关。随后,预测了21个可能靶向LAMA3的潜在上游miRNAs。在预测到的miRNA-mRNA调控轴中,has-miR-20b-5p-LAMA3轴在胰腺癌的发生和进展中具有较高的潜力。进一步研究发现,FGD5-AS1潜在的抑制has-miR-20b-5p-LAMA3调控轴的作用可能能够在胰腺癌中作为诊断和治疗的有效靶点。FGD5-AS1-has-miR-20b-5p-LAMA3调控网络在胰腺癌发生和发展中的具有关键作用,可作为胰腺癌临床诊断和治疗的潜在靶点和生物标志物。