Construction of a paclitaxel-related competitive endogenous RNA network and identification of a potential regulatory axis in pancreatic cancer

BackgroundIncreasing numbers of studies have elucidated the role of competitive endogenous RNA (ceRNA) networks in carcinogenesis. However, the potential role of the paclitaxel-related ceRNA network in the innate mechanism and prognosis of pancreatic cancer has not been identified.MethodsComprehensive bioinformatics analyses were performed to identify drug-related miRNAs (DRmiRNAs), drug-related mRNAs (DRmRNAs) and drug-related lncRNAs (DRlncRNAs) and construct a ceRNA network. The ssGSEA and CIBERSORT algorithms were utilized for immune cell infiltration analysis. Additionally, we validated our paclitaxel-related ceRNA regulatory axis at the gene expression level; functional experiments were conducted to explore the biological functions of the key genes.ResultsA total of 182 mRNAs, 13 miRNAs, and 53 lncRNAs were confirmed in the paclitaxel-related ceRNA network. In total, 6 mRNAs, 4 miRNAs, and 6 lncRNAs were identified to establish a risk signature and exhibited optimal prognostic effects. The mRNA signature can predict the abundance of immune cell infiltration and the sensitivity of different chemotherapeutic drugs and may also have a guiding effect in immune checkpoint therapy. A potential PART1/hsa-mir-21/SCRN1 axis was confirmed according to the ceRNA theory and was verified by qPCR. The results indicated that PART1 knockdown markedly increased hsa-mir-21 expression but inhibited SCRN1 expression, weakening the proliferation and migration abilities.ConclusionsWe hypothesized that the paclitaxel-related ceRNA network strongly influences the innate mechanism, prognosis, and immune infiltration of pancreatic cancer. Our risk signatures can accurately predict survival outcomes and provide a clinical basis.     

Construction of a lncRNA/pseudogene-hsa-miR-30d-5p-GJA1 regulatory network related to metastasis of pancreatic cancer

Pancreatic cancer, the most lethal malignant tumor, is notorious for its poor prognosis and metastatic potential. Non-coding RNAs (ncRNAs) are reported to play key roles in cancer metastasis. In this study, miRNA and gene expression profiles between metastatic pancreatic cancer cell M8 and its parental cell BxPC.3 were determined. Using differential expression analysis, survival analysis, target gene prediction, pathway enrichment analysis, intersection analysis and correlation analysis, hsa-miR-30d-5p/GJA1 axis was identified as the most potential pathway involved in metastasis of pancreatic cancer. Subsequently, two upstream lncRNAs (HELLPAR and OIP-AS1) and four upstream pseudogenes (AC093616.1, AC009951.1, TMEM183B and PABPC1P4) of hsa-miR-30d-5p/GJA1 axis were predicted and were then identified via assessment of RNA-RNA expression relationship. Furthermore, CTNNA1, CTNNB1 and CTNND1 were regarded as three crucial molecules to be participated in hsa-miR-30d-5p/GJA1-mediated metastatic potential in pancreatic cancer. In conclusion, we established a novel lncRNA/pseudogene-hsa-miR-30d-5p-GJA1 regulatory network linked to metastasis of pancreatic cancer.     

拟南芥在盐胁迫环境下SOS转录调控网络的构建及分析

研究拟南芥在高浓度盐处理环境下的基因调控网络, 有助于了解其在盐胁迫环境下保持正常生长的防御机制。针对目前广泛研究的SOS (Salt Overly Sensitive)耐盐机制, 文章整合公共数据库中盐胁迫相关的拟南芥基因组表达谱芯片, 通过反向工程方法构建了拟南芥在盐胁迫状态下的SOS转录调控网络。所获得的调控网络包含70个盐胁迫相关且高度互作的互作基因, 其中27个转录因子为主要调控节点。进而根据SOS核心基因的表达特性, 所得调控网络内的不同表达模式得到了鉴别。     

Establishment of optimal regulatory network of colorectal cancer based on p42.3 protein

Objective: to establish regulatory network of colorectal cancer involving p42.3 protein and to provide theoretical evidence for deep functional exploration of p42.3 protein in the onset and development of colorectal cancer. Methods: with protein similarity algorithm, reference protein set of p42.3 cell apoptosis was built according to structural features of p42.3. GO and KEGG databases were used to establish regulatory network of tumor cell apoptosis involving p42.3; meanwhile, the largest possible working pathway that involves p42.3 protein was screened out based on Bayesian network theory. Besides, GO and KEGG were used to build regulatory network on early diagnosis gene markers for colorectal cancer including WWOX, K-ras, COX-2, p53, APC, DCC and PTEN, at the same time, a regulatory network of colorectal cancer cell apoptosis which involves p42.3 was established. Results: cell apoptotic regulatory network that p42.3 participates in primarily consists of Bcl-2 family genes and the largest possible pathway is p42.3 → FKBP → Bcl-2 centered as FKBP protein. Combined with colorectal cancer regulatory network that involves early diagnosis gene markers, it can be predicted that p42.3 is most likely to regulate the colorectal cancer cell apoptosis through FKBP → Bcl-2 → Bax → caspase-9 → caspase-3 pathway. Conclusion: the colorectal cancer apoptosis network based on p42.3 established in the study provides theoretical evidence for deep exploration of p42.3 regulatory mechanism and molecular targeting treatment of colorectal cancer.     

枯草芽孢杆菌转录调控网络的连接结构及分解

对枯草芽孢杆菌（Bacillus subtilis）转录调控网络的全局连接性质进行分析之后,基于一种自上而下的思路,将重点放在最大弱连通体,提出了基于距离的分解方法,并对得出的模块进行了明确的生物学功能定义。研究结果表明基于距离的分解方法对于标识转录调控网络中的生物学功能模块十分有效.