DTNA promotes HBV-induced hepatocellular carcinoma progression by activating STAT3 and regulating TGFβ1 and P53 signaling

Identification of macrophage-related molecular subgroups and risk signature in colorectal cancer based on a bioinformatics analysis

Macrophages play a crucial role in tumor initiation and progression, while macrophage-associated gene signature in colorectal cancer (CRC) patients has not been investigated. Our study aimed to identify macrophage-related molecular subgroups and develop a macrophage-related risk model to predict CRC prognosis. The mRNA expression profile and clinical information of CRC patients were obtained from TCGA and GEO databases. CRC patients from TCGA were divided into high and low macrophage subgroups based on the median macrophage score. The ESTIMATE and CIBERSORT algorithms were used to assess immune cell infiltration between subgroups. GSVA and GSEA analyses were performed to investigate differences in enriched pathways between subgroups. Univariate and LASSO Cox regression were used to build a prognostic risk model, which was further validated in the GSE39582 dataset. A high macrophage score subgroup was associated with poor prognosis, highly activated immune-related pathways and an immune-active microenvironment. A total of 547 differentially expressed macrophage-related genes (DEMRGs) were identified, among which seven genes (including RIMKLB, UST, PCOLCE2, ZNF829, TMEM59L, CILP2, DTNA) were identified by COX regression analyses and used to build a risk score model. The risk model shows good predictive and diagnostic values for CRC patients in both TCGA and GSE39852 datasets. Furthermore, multivariate Cox regression analysis showed that the risk score was an independent risk factor for overall survival in CRC patients. Our findings provided a novel insight into macrophage heterogeneity and its immunological role in CRC. This risk score model may serve as an effective prognostic tool and contribute to personalised clinical management of CRC patients.

A panel based on three-miRNAs as diagnostic biomarker for prostate cancer

Background: Prostate cancer (PCa) is one of the most prevalent malignancies affecting the male life cycle. The incidence and mortality of prostate cancer are also increasing every year. Detection of MicroRNA expression in serum to diagnose prostate cancer and determine prognosis is a very promising non-invasive modality. Materials and method: A total of 224 study participants were included in our study, including 112 prostate cancer patients and 112 healthy adults. The experiment consisted of three main phases, namely, the screening phase, the testing phase, and the validation phase. The expression levels of serum miRNAs in patients and healthy adults were detected using quantitative reverse transcription-polymerase chain reaction. Receiver operating characteristic (ROC) curves and the area under the curve (AUC) were used to evaluate the diagnostic ability, specificity, and sensitivity of the candidate miRNAs. Result: Eventually, three miRNAs most relevant to prostate cancer diagnosis were selected, namely, miR-106b-5p, miR-129-1-3p and miR-381-3p. We used these three miRNAs to construct a diagnostic panel with very high diagnostic potential for prostate cancer, which had an AUC of 0.912 [95% confidence interval (CI): 0.858 to 0.950; p < 0.001; sensitivity = 91.67%; specificity = 79.76%]. In addition, the three target genes (DTNA, GJB1, and TRPC4) we searched for are also expected to be used for prostate cancer diagnosis and treatment in the future.

JAK/STAT3 signaling in cardiac fibrosis: a promising therapeutic target

Cardiac fibrosis is a serious health problem because it is a common pathological change in almost all forms of cardiovascular diseases. Cardiac fibrosis is characterized by the transdifferentiation of cardiac fibroblasts (CFs) into cardiac myofibroblasts and the excessive deposition of extracellular matrix (ECM) components produced by activated myofibroblasts, which leads to fibrotic scar formation and subsequent cardiac dysfunction. However, there are currently few effective therapeutic strategies protecting against fibrogenesis. This lack is largely because the molecular mechanisms of cardiac fibrosis remain unclear despite extensive research. The Janus kinase/signal transducer and activator of transcription (JAK/STAT) signaling cascade is an extensively present intracellular signal transduction pathway and can regulate a wide range of biological processes, including cell proliferation, migration, differentiation, apoptosis, and immune response. Various upstream mediators such as cytokines, growth factors and hormones can initiate signal transmission via this pathway and play corresponding regulatory roles. STAT3 is a crucial player of the JAK/STAT pathway and its activation is related to inflammation, malignant tumors and autoimmune illnesses. Recently, the JAK/STAT3 signaling has been in the spotlight for its role in the occurrence and development of cardiac fibrosis and its activation can promote the proliferation and activation of CFs and the production of ECM proteins, thus leading to cardiac fibrosis. In this manuscript, we discuss the structure, transactivation and regulation of the JAK/STAT3 signaling pathway and review recent progress on the role of this pathway in cardiac fibrosis. Moreover, we summarize the current challenges and opportunities of targeting the JAK/STAT3 signaling for the treatment of fibrosis. In summary, the information presented in this article is critical for comprehending the role of the JAK/STAT3 pathway in cardiac fibrosis, and will also contribute to future research aimed at the development of effective anti-fibrotic therapeutic strategies targeting the JAK/STAT3 signaling.

Comparative analysis of whole-transcriptome RNA expression of lung tissue of Chinese soft-shell turtle infected by Trionyx sinensis Hemorrhagic Syndrome Virus

Trionyx sinensis Hemorrhagic Syndrome Virus (TSHSV), the first aquatic arterivirus identified in China, causes severe mortality to T. sinensis. In this study, we sought to determine the functions of T. sinensis mRNAs and non-coding RNAs (ncRNAs) that were differentially expressed (DE) over different periods of TSHSV infection of T. sinensis lung. We used RT-qPCR to validate the sequencing results of select RNAs, confirming their reliable and referable nature. Gene Ontology (GO) annotation and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis were used to predict multiple biological functions and signaling pathways in various comparison groups (1-day versus mock, 3-day versus 1-day, and 5-day versus 3-day). Multiple types of differentially expressed RNA, including mRNA, lncRNA, circRNA, and miRNA, were associated with cardiac dysfunction, coagulation abnormalities, and arachidonic acid metabolism at day 1. Pre-inflammatory cytokines and inflammatory factors such as PLA2G4A, cPLA2, γ-GGT1, TNFRSF14, TCP11L2, PTER CYP2J2 and LTC4S, were noticeably regulated at the same time. On day 3, multiple GO terms and KEGG pathways were implicated, including those related to virus defense, apoptosis, pyroptosis, and inflammatory response. Notably, key genes such as RSAD2, TRIM39, STAT4, CASP1, CASP14, MYD88, CXCL3, CARD11, ZBP1, and ROBO4 exhibited significant regulation. The lncRNAs and circRNAs that targeted the genes involved in viral recognition (TLR5), apoptosis (CARD11), pyroptosis (ZBP1), inflammatory processes (NEK7, RASGRP4, and SELE) and angiogenesis (ROBO4) exhibited significant regulation. Significantly regulated miRNAs were primarily linked to genes involved in apoptosis (Let-7f-3p, miR-1260a, miR-455-3p), and inflammation (miR-146a, miR-125a, miR-17a, miR-301b, and miR-30a-3p). The findings could advance our understanding of the host immunological response to TSHSV and offer new ideas for developing effective strategies to prevent infection of T. sinensis.

Construction of an lncRNA model for prognostic prediction of bladder cancer

OBJECTIVE

We aimed to investigate the role and potential mechanisms of long non-coding RNAs (lncRNAs) in bladder cancer (BC), as well as determine their prognostic value.

METHODS

LncRNA expression data and clinical data from BC patients were downloaded from The Cancer Genome Atlas (TCGA) database. R software was used to carry out principal component analysis (PCA), differential analysis, and prognostic analysis. Lasso regression and multivariate Cox regression analyses were performed to identify potential prognostic genes. The expression of five identified genes and their correlation with prognosis were verified using TCGA and GSE13507 datasets. In addition, quantitative real-time polymerase chain reaction (qRT-PCR) was used to confirm the expression of these five genes in cell lines (two human BC cell lines and one human bladder epithelial cell line) and tissues (84 pairs of BC tissues and the corresponding paracancerous tissues). Risk scores that had been generated from the five genes and their prognostic ability were assessed by receiver operating characteristic (ROC) and Kaplan-Meier (KM) curves. Co-expressed genes were screened by WGCNA and analyzed by GO and KEGG, while functional enrichment and immune infiltration analyses were performed using STRING ( https://cn.string-db.org/ ) and TIMER2.0 ( http://timer.cistrome.org/ ) online tools, respectively.

RESULTS

CYP4F8, FAR2P1, LINC01518, LINC01764, and DTNA were identified as potential prognostic genes. We found that these five genes were differentially expressed in BC tissue, as well as in BC cell lines, and were significantly correlated with the prognosis of BC patients. KM analysis considering risk scores as independent parameters revealed differences in overall survival (OS) by subgroups. The ROC curve revealed that a combined model consisting of all five genes had good predictive ability at 1, 3, and 5 years. GO and KEGG analyses of 567 co-expressed genes revealed that these genes were significantly associated with muscle function.

CONCLUSION

LncRNAs can be good predictors of BC development and prognosis, and may act as potential tumor markers and therapeutic targets that may be beneficial in helping clinicians decide the most effective treatment strategies.

A robust gene expression signature for NASH in liver expression data

Non-Alcoholic Fatty Liver Disease (NAFLD) is a progressive liver disease that affects up to 30% of worldwide population, of which up to 25% progress to Non-Alcoholic SteatoHepatitis (NASH), a severe form of the disease that involves inflammation and predisposes the patient to liver cirrhosis. Despite its epidemic proportions, there is no reliable diagnostics that generalizes to global patient population for distinguishing NASH from NAFLD. We performed a comprehensive multicohort analysis of publicly available transcriptome data of liver biopsies from Healthy Controls (HC), NAFLD and NASH patients. Altogether we analyzed 812 samples from 12 different datasets across 7 countries, encompassing real world patient heterogeneity. We used 7 datasets for discovery and 5 datasets were held-out for independent validation. Altogether we identified 130 genes significantly differentially expressed in NASH versus a mixed group of NAFLD and HC. We show that our signature is not driven by one particular group (NAFLD or HC) and reflects true biological signal. Using a forward search we were able to downselect to a parsimonious set of 19 mRNA signature with mean AUROC of 0.98 in discovery and 0.79 in independent validation. Methods for consistent diagnosis of NASH relative to NAFLD are urgently needed. We showed that gene expression data combined with advanced statistical methodology holds the potential to serve basis for development of such diagnostic tests for the unmet clinical need.

IL-6/STAT3 Is a Promising Therapeutic Target for Hepatocellular Carcinoma

Hepatocellular carcinoma (HCC) is a common malignant tumor of which the occurrence and development, the tumorigenicity of HCC is involving in multistep and multifactor interactions. Interleukin-6 (IL-6), a multifunctional inflammatory cytokine, has increased expression in HCC patients and is closely related to the occurrence of HCC and prognosis. IL-6 plays a role by binding to the IL-6 receptor (IL-6R) and then triggering the Janus kinase (JAK) associated with the receptor, stimulating phosphorylation and activating signal transducer and activator of transcription 3 (STAT3) to initiate downstream signals, participating in the processes of anti-apoptosis, angiogenesis, proliferation, invasion, metastasis, and drug resistance of cancer cells. IL-6/STAT3 signal axes elicit an immunosuppressive in tumor microenvironment, it is important to therapy HCC by blocking the IL-6/STAT3 signaling pathway. Recent, some inhibitors of IL-6/STAT3 have been development, such as S31-201 or IL-6 neutralizing monoclonal antibody (IL-6 mAb), Madindoline A (Inhibits the dimerization of IL-6/IL-6R/gpl30 trimeric complexes), C188-9 and Curcumin (Inhibits STAT3 phosphorylation), etc. for treatment of cancers. Overall, consideration of the IL-6/STAT3 signaling pathway, and its role in the carcinogenesis and progression of HCC will contribute to the development of potential drugs for targeting treatment of liver cancer.

Bioinformatics analysis and verification of molecular targets in ovarian cancer stem-like cells

BACKGROUND

Epithelial ovarian cancer (EOC) is a lethal and aggressive gynecological malignancy. Despite recent advances, existing therapies are challenged by a high relapse rate, eventually resulting in disease recurrence and chemoresistance. Emerging evidence indicates that a subpopulation of cells known as cancer stem-like cells (CSLCs) exists with non-tumorigenic cancer cells (non-CSCs) within a bulk tumor and is thought to be responsible for tumor recurrence and drug-resistance. Therefore, identifying the molecular drivers for cancer stem cells (CSCs) is critical for the development of novel therapeutic strategies for the treatment of EOC.

METHODS

Two gene datasets were downloaded from the Gene Expression Omnibus (GEO) database based on our search criteria. Differentially expressed genes (DEGs) in both datasets were obtained by the GEO2R web tool. Based on log2 (fold change) >2, the top thirteen up-regulated genes and log2 (fold change) < -1.5 top thirteen down-regulated genes were selected, and the association between their expressions and overall survival was analyzed by OncoLnc web tool. Gene Ontology (GO) analysis, Kyoto Encyclopedia of Genes and Genomes (KEGG) and Reactome pathways analysis, and protein-protein interaction (PPI) networks were performed for all the common DEGs found in both datasets. SK-OV-3 cells were cultured in an adherent culture medium and spheroids were generated in suspension culture with CSCs specific medium. RNA from both cell population was extracted to validate the selected DEGs expression by q-PCR. Growth inhibition assay was performed in SK-OV-3 cells after carboplatin treatment.

RESULTS

A total of 200 DEGs, 117 up-regulated and 83 down-regulated genes were commonly identified in both datasets. Analysis of pathways and enrichment tests indicated that the extracellular matrix part, cell proliferation, tissue development, and molecular function regulation were enriched in CSCs. Biological pathways such as interferon-alpha/beta signaling, molecules associated with elastic fibers, and synthesis of bile acids and bile salts were significantly enriched in CSCs. Among the top 13 up-regulated and down-regulated genes, MMP1 and PPFIBP1 expression were associated with overall survival. Higher expression of ADM, CXCR4, LGR5, and PTGS2 in carboplatin treated SK-OV-3 cells indicate a potential role in drug resistance.

CONCLUSIONS

The molecular signature and signaling pathways enriched in ovarian CSCs were identified by bioinformatics analysis. This analysis could provide further research ideas to find the new mechanism and novel potential therapeutic targets for ovarian CSCs.