Bioinformatics Analyses of Potential miRNA-mRNA Regulatory Axis in HBV-related Hepatocellular Carcinoma

Aims: We aimed to explore the crucial miRNA-mRNA axis through bioinformatics analysis and provide evidences for the development of pathophysiological mechanisms and new therapies for HBV-related HCC.Methods: MiRNA ({"type":"entrez-geo","attrs":{"text":"GSE76903","term_id":"76903"}}GSE76903) and mRNA ({"type":"entrez-geo","attrs":{"text":"GSE77509","term_id":"77509"}}GSE77509) dataset were used to screen differentially expressed miRNAs (DE-miRNAs) and differentially expressed mRNAs (DE-mRNAs) using R software. Overlapping genes between DE-mRNAs and target genes of DE-miRNAs were identified as candidate genes. Hub genes were obtained via cytohubba analysis. The expression at protein and mRNA levels and prognostic value of hub genes were evaluated based on The Cancer Genome Atlas (TCGA) data. Key miRNA-mRNA axes were constructed according to predicted miRNA-mRNA pairs. MiRNA expression and prognostic role were respectively identified using starBase v3.0 and Kaplan-Meier plotter database. Real-time PCR was performed to verify the expression of crucial miRNAs and mRNAs. Coexpression of crucial miRNA and mRNA were analyzed using starBase v3.0.Results: CDK1, CCNB1, CKS2 and CCNE1 were screened as hub genes, which were significantly upregulated at protein and mRNA levels. These up-regulated hub genes were also significantly associated with poor prognosis. Hsa-mir-195-5p/CDK1, hsa-mir-5589-3p/CCNB1 and hsa-let-7c-3p/CKS2 were screened as critical miRNA-mRNA axes. Critical miRNAs were decreased in HCC, which indicates unfavourable prognosis. QPCR results showed that crucial miRNAs were decreased, whereas critical mRNAs were increased in HBV-related HCC. A reverse relationship between miRNA and mRNA in crucial axis was further verified.Conclusion: This study identified several miRNA-mRNA axes in HBV-related HCC. Hsa-mir-195-5p/CDK1, hsa-mir-5589-3p/CCNB1 and hsa-let-7c-3p/CKS2 might serve as potential prognostic biomarkers and therapeutic targets for HBV-related HCC.     

Identification of colorectal cancer-associated macrophage biomarkers by integrated bioinformatic analysis

The aim of this study was to explore colorectal tumor-associated macrophage (TAM) biomarkers for early diagnosis and surveillance of colorectal cancer (CRC). We used bioinformatic methods to screen array expression data of CRC-related macrophages (GEO: {"type":"entrez-geo","attrs":{"text":"GSE29214","term_id":"29214"}}GSE29214) to detect the differentially expressed genes (DEGs) between CRC-related macrophages and normal control cells. We found 431 DEGs in TAMs compared with the control group; 399 were up-regulated and 32 were down-regulated. A functional enrichment analysis showed that the DEGs were involved in positive regulation of the ERK1 and ERK2 cascade, cell activation involved in the immune response, cytokine-mediated signaling pathway, and receptor activity, all of which were significantly enriched. We constructed a protein-protein interaction (PPI) network to identify hub genes. We identified 10 hub genes: ITGB2, ITGAM, C3AR1, PTAFR, C3, CYBB, FCER1G, PLAU, STOM, and GPR84, in the PPI network. We verified the results using array expression data of peripheral blood mononuclear cells (GEO: {"type":"entrez-geo","attrs":{"text":"GSE47756","term_id":"47756"}}GSE47756). The results showed that the expression trends of CYBB, PLAU, and STOM were consistent with those found in the {"type":"entrez-geo","attrs":{"text":"GSE29214","term_id":"29214"}}GSE29214 dataset. Further verification with The Cancer Genome Atlas and Human Protein Atlas showed that the high expression of PLAU in TAMs was statistically significant (P<0.05). We concluded that PLAU may be a biomarker of CRC-associated macrophages and may have prognostic and predictive significance for clinical utility in CRC management.     

MET overexpression and intratumor heterogeneity in esophageal squamous cell carcinoma

Esophageal squamous cell carcinoma (ESCC) is among the ten most frequent and deadly cancers, without effective therapies for most patients. More recently, drugs targeting deregulated growth factor signaling receptors have been developed, such as HGF-MET targeted therapy. We assessed MET and HGF genetic alterations and gene and protein expression profiles in ESCC patients from the Brazilian National Cancer Institute and publicly available datasets, as well as the intratumor heterogeneity of the alterations found. Our analyses showed that HGF and MET genetic alterations, both copy number and mutations, are not common in ESCC, affecting 5 and 6% of the cases, respectively. HGF showed a variable mRNA expression profile between datasets, with no alterations ({"type":"entrez-geo","attrs":{"text":"GSE20347","term_id":"20347"}}GSE20347), downregulation ({"type":"entrez-geo","attrs":{"text":"GSE45670","term_id":"45670"}}GSE45670), and upregulation in ESCC (our dataset and {"type":"entrez-geo","attrs":{"text":"GSE75241","term_id":"75241"}}GSE75241). On the other hand, MET was found consistently upregulated in ESCC compared to non-tumor surrounding tissue, with median fold-changes of 5.96 ({"type":"entrez-geo","attrs":{"text":"GSE20347","term_id":"20347"}}GSE20347), 3.83 ({"type":"entrez-geo","attrs":{"text":"GSE45670","term_id":"45670"}}GSE45670), 6.02 ({"type":"entrez-geo","attrs":{"text":"GSE75241","term_id":"75241"}}GSE75241), and 5.0 (our dataset). Among our patients, 84% of the tumors showed at least a two-fold increase in MET expression. This observation was corroborated by protein levels, with 55% of cases exhibiting positivity in 100% of the tumor cells. Intratumor heterogeneity was evaluated in at least four tumor biopsies from five patients and two cases showed a consistent increase in MET expression (at least two-fold) in all tumor samples. Our data suggested that HGF-MET signaling pathway was likely to be overactivated in ESCC, representing a potential therapeutic target, but eligibility for this therapy should consider intratumor heterogeneity.     

Screening of non-alcoholic steatohepatitis (NASH)-related datasets and identification of NASH-related genes

Non-alcoholic steatohepatitis (NASH) is a common liver disease in the western world. The mechanisms behind NASH formation are poorly understood, but there may be multiple targets considering the disease’s multifactorial nature. To explore the genes related to the pathogenesis of NASH, we downloaded clinical data and gene expression of NASH patients from the Gene Expression Omnibus database (GEO). We identified 281 genes with a common expression in two NASH-related datasets ({"type":"entrez-geo","attrs":{"text":"GSE89632","term_id":"89632"}}GSE89632 and {"type":"entrez-geo","attrs":{"text":"GSE83452","term_id":"83452"}}GSE83452), suggesting that they may be related to NASH. Further study showed that Angptl4, Foxo1, and Ttc39B might be essential for NASH progression, and these have been poorly studied. Therefore, we explored their roles in NASH. Our data show that these genes participate in the development of NASH through lipid metabolism. This suggests that the three genes can be used as therapeutic targets in NASH.     

Granzyme family acts as a predict biomarker in cutaneous melanoma and indicates more benefit from anti-PD-1 immunotherapy

The incidence of cutaneous melanoma (CM) increased since the 1970s, and also along with an unfavorable prognosis. CM patients have been verified benefits from immunotherapy, and granzymes (GZMs) comprise more than 90% of the cytolytic granules secreted by cytotoxic T lymphocytes and nature killer cell. Therefore, it is essential to evaluate the prognostic value of GZMs in CM. A total of 633 CM patients was enrolled to access the prognostic value of GZMs. The integrated prognostic value of five GZMs was validated in TCGA-SKCM, {"type":"entrez-geo","attrs":{"text":"GSE65904","term_id":"65904"}}GSE65904, {"type":"entrez-geo","attrs":{"text":"GSE53118","term_id":"53118"}}GSE53118, {"type":"entrez-geo","attrs":{"text":"GSE19234","term_id":"19234"}}GSE19234 and {"type":"entrez-geo","attrs":{"text":"GSE22153","term_id":"22153"}}GSE22153 cohorts. GZMscore, age, Breslow''s depth and tumor stage are the independent risk factors for CM patients, risk score based on these factors was calculated in TCGA-SKCM and {"type":"entrez-geo","attrs":{"text":"GSE65906","term_id":"65906"}}GSE65906 cohorts, which could polarize the CM patients to high- and low-risk groups with diverse prognosis. Patients in low-risk group obtained the activated immune signaling pathways and response, especially for the activated CD8+ T cells, and could benefit more from anti-PD-1 therapy. A higher tumor mutation burden was observed in low-risk group, especially for the mutation of BRAF. The protect function of GZMK was confirmed by CM cell lines, overexpression of GZMK in A375 and G361 cells suppresses cell proliferation, migration, but not cell apoptosis. All in all, we revealed the prognostic value of GZMs in CM patients, which could also act as a predicted value for the selection of responders of anti-PD-1 immunotherapy.     

Differences in key genes in human alveolar macrophages between phenotypically normal smokers and nonsmokers: diagnostic and prognostic value in lung cancer

Objective: To explore the effect of smoking on gene expression in human alveolar macrophages and the value of identified key genes in the early diagnosis and prognosis of lung cancers. Methods: We downloaded three data sets ({"type":"entrez-geo","attrs":{"text":"GSE8823","term_id":"8823"}}GSE8823, {"type":"entrez-geo","attrs":{"text":"GSE2125","term_id":"2125"}}GSE2125, and {"type":"entrez-geo","attrs":{"text":"GSE3212","term_id":"3212"}}GSE3212) from the Gene Expression Omnibus (GEO) database, including 31 non-smoking and 33 smoking human alveolar macrophage samples. We identified common differentially expressed genes (DEGs), from which we obtained module genes and hub genes by using STRING and Cytoscape. Then we analyzed the protein-protein interaction (PPI) network of DEGs, hub genes, and module genes and used David online analysis tool to carry out functional enrichment analysis of DEGs and module genes. Results: A total of 85 differentially expressed genes was obtained, including 42 up-regulated genes and 43 down-regulated genes. The Human Protein Atlas and Survival analysis showed that GBP1, ITGAM, CSF1, SPP1, COL1A1, LAMB1 and THBS1 may be closely associated with the carcinogenesis and prognosis of lung cancer. Conclusion: DEGs, module, and hub genes identified in the present study help explain the effects of smoking on human alveolar macrophages and provide candidate targets for diagnosis and treatment of smoking-related lung cancer.     

Roles of the miR-139-5p/CCT5 axis in hepatocellular carcinoma: a bioinformatic analysis

Background: MiRNAs are pivotal regulators involved in proliferation, apoptosis, invasion, metastasis, epithelial-mesenchymal transition (EMT), angiogenesis, drug resistance and autophagy in hepatocellular carcinoma (HCC). The aim of this study was to investigate the influence of miR-139-5p and its target genes on the outcomes of HCC.Methods: Survival analysis of miR-139-5p in HCC was conducted in Kaplan-Meier plotter. Target genes of miR-139-5p were identified in TargetScan, miRTarBase and starBase. Gene Expression Omnibus (GEO) series were used for the validation of miR-139-5p target genes. Cox proportional regression model was also established.Results: In Kaplan-Meier plotter, 163 HCC patients were included. MiR-139-5p downregulation was significantly associated with unfavorable overall survival (OS) and disease-free survival (DFS) in HCC patients (all P < 0.001). MiR-139-5p was significantly downregulated in HCC tumors and human hepatoma cell lines (all P < 0.05). As a target gene of miR-139-5p, CCT5 was overexpressed in HCC tumor tissues and peripheral blood mononuclear cells (all P < 0.05). A negative correlation between CCT5 and miR-139-5p was found in TCGA dataset. CCT5 overexpression was significantly associated with worse OS in HCC patients (P < 0.001), which was validated in the {"type":"entrez-geo","attrs":{"text":"GSE14520","term_id":"14520"}}GSE14520 dataset (P = 0.017). CCT5 mRNA was significantly overexpressed in HCC patients with alpha-fetoprotein (AFP) > 300 ng/ml, BCLC staging B-C, TNM staging III and main tumor size > 5 cm (all P < 0.05). According to the Cox regression model of CCT5-interacting genes, HCC patients with high risk had poor OS compared to those with low risk in the TCGA dataset (P < 0.001), with the 1-year, 3-year, and 5-year ROC curves of an area under the curve (AUC) equal to 0.704, 0.662, and 0.631, respectively.Conclusions: MiR-139-5p suppresses HCC tumor aggression and conversely correlated with CCT5. The miR-139-5p/CCT5 axis might perform crucial functions in the development of HCC.     

LncRNA XIST acts as a MicroRNA-520 sponge to regulate the Cisplatin resistance in NSCLC cells by mediating BAX through CeRNA network

Background: In recent years, LncRNA acts as a member of competing endogenous RNA (ceRNA), playing an important role in drug resistance of lung cancer. The aim of this study was to identify potential biomarkers about cisplatin resistant lung cancer cells using a comprehensive ceRNA network.Methods: {"type":"entrez-geo","attrs":{"text":"GSE6410","term_id":"6410"}}GSE6410 (GPL-201) analyzed gene expression changes about cisplatin resistance in A549 NSCLC cells. {"type":"entrez-geo","attrs":{"text":"GSE43249","term_id":"43249"}}GSE43249 (GPL-14613) included noncoding RNA expression profiling derived from the cisplatin resistant A549 lung cells. GEO2R, an online analysis tool, analyzed the differentially expressed mRNAs and miRNAs (DEmRNAs and DEmiRNAs). To explore the functional enrichment implication of differentially expressed mRNAs, we used the GO (Gene ontology) and KEGG (Kyoto Encyclopedia of Genes and Genomes) pathway analysis. Through miRDB, Targetscan, Starbase and miRWalk, we found targeted miRNAs. The Kaplan-Meier curve method was used to show clinical survival analysis of targeted RNAs (P<0.05). The Starbase database predicted potential lncRNAs mediated targeted miRNAs. Eventually, the novel ceRNA network of lncRNAs, miRNAs, mRNA was constructed by cytoscape3.7.2.Results: 118 differentially expressed mRNAs were the basis of the mediated ceRNA network. DAVID and Kaplan-Meier picked out BAX, an apoptosis regulator. Venn diagram demonstrated 8 miRNAs commonly regulating BAX. Starbase predicted lncRNA XIST mediated miRNAs. Finally, lncRNA XIST may be a useful biomarker regulating cisplatin resistance in lung cancer cells and further, we explored the BAX may effect tumor-infiltrating immune cells.Conclusions: LncRNA XIST competitively bound to miRNA 520 in the regulation of cisplatin resistance by BAX, participating apoptosis in the p53 signaling pathway.     

Construction of ceRNA network and identification of two differentially expressed circRNAs in hepatocellular carcinoma by bioinformatic analysis

Covalently closed circular RNAs (circRNAs) display dysregulated expression in several types of cancer. However, their functions remain largely unclear. In this work, datasets {"type":"entrez-geo","attrs":{"text":"GSE125469","term_id":"125469"}}GSE125469 and {"type":"entrez-geo","attrs":{"text":"GSE128274","term_id":"128274"}}GSE128274 of hepatocellular carcinoma (HCC) were selected from Gene Expression Omnibus (GEO) database. To identify differentially expressed genes (DEGs) in HCC and adjacent tissues, we used R package DESeq for analysis. Then, 15 DEcircRNAs, 65 DEmiRNAs, and 2084 DEmRNAs were identified comparing HCC and normal tissues. Next, to predict the target relationship of circRNA-miRNA and miRNA-mRNA in DEGs, we use the databases CircInteractome and starBase v2.0 for analysis. Finally, the ceRNA network of circRNA-miRNA-mRNA was established by Cytoscape software based on 2 DEcircRNAs (hsa_circ_0007813 and hsa_circ_0089372), 2 DEmiRNAs, and 98 DEmRNAs. In addition, we conducted Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses of DEGs to explore the function of DEGs in HCC. Functional enrichment analyses indicated DEmRNAs might be associated with HCC occurrence and progression. In general, our research reveals an important role of ceRNA’s molecular mechanism in HCC.     

Integrated bioinformatics analysis for differentially expressed genes and signaling pathways identification in gastric cancer

Background: Gastric cancer (GC) has a high mortality rate in cancer-related deaths worldwide. Currently, the pathogenesis of gastric cancer progression remains unclear. Here, we identified several vital candidate genes related to gastric cancer development and revealed the potential pathogenic mechanisms using integrated bioinformatics analysis.Methods: Two microarray datasets from Gene Expression Omnibus (GEO) database integrated. Limma package was used to analyze differentially expressed genes (DEGs) between GC and matched normal specimens. DAVID was utilized to conduct Gene ontology (GO) and KEGG enrichment analysis. The relative expression of OLFM4, IGF2BP3, CLDN1 and MMP1were analyzed based on TCGA database provided by UALCAN. Western blot and quantitative real time PCR assay were performed to determine the protein and mRNA levels of OLFM4, IGF2BP3, CLDN1 and MMP1 in GC tissues and cell lines, respectively.Results: We downloaded the expression profiles of {"type":"entrez-geo","attrs":{"text":"GSE103236","term_id":"103236"}}GSE103236 and {"type":"entrez-geo","attrs":{"text":"GSE118897","term_id":"118897"}}GSE118897 from the Gene Expression Omnibus (GEO) database. Two integrated microarray datasets were used to obtain differentially expressed genes (DEGs), and bioinformatics methods were used for in-depth analysis. After gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichments analysis, we identified 61 DEGs in common, of which the expression of 34 genes were elevated and 27 genes were decreased. GO analysis displayed that the biological functions of DEGs mainly focused on negative regulation of growth, fatty acid binding, cellular response to zinc ion and calcium-independent cell-cell adhesion. KEGG pathway analysis demonstrated that these DEGs mainly related to the Wnt and tumor signaling pathway. Interestingly, we found 4 genes were most significantly upregulated in the DEGs, which were OLFM4, IGF2BP3, CLDN1 and MMP1. Then, we confirmed the upregulation of these genes in STAD based on sample types. In the final, western blot and qRT-PCR assay were performed to determine the protein and mRNA levels of OLFM4, IGF2BP3, CLDN1 and MMP1 in GC tissues and cell lines.Conclusion: In our study, using integrated bioinformatics to screen DEGs in gastric cancer could benefit us for understanding the pathogenic mechanism underlying gastric cancer progression. Meanwhile, we also identified four significantly upregulated genes in DEGs from both two datasets, which might be used as the biomarkers for early diagnosis and prevention of gastric cancer.     

Candidate pathways and genes for nasopharyngeal carcinoma based on bioinformatics study

Purpose: To reveal the potential microRNAs (miRNAs), genes, pathways and regulatory network involved in the process of nasopharyngeal carcinoma (NPC) by using the method of bioinformatics. Methods: Gene expression profiles {"type":"entrez-geo","attrs":{"text":"GSE12452","term_id":"12452"}}GSE12452 (31 NPC and 10 normal samples) and {"type":"entrez-geo","attrs":{"text":"GSE53819","term_id":"53819"}}GSE53819 (18 NPC and 18 normal samples), as well as miRNA expression profiles {"type":"entrez-geo","attrs":{"text":"GSE32960","term_id":"32960"}}GSE32960 (312 NPC and 18 normal samples) and {"type":"entrez-geo","attrs":{"text":"GSE36682","term_id":"36682"}}GSE36682 (62 NPC and 6 normal samples) were obtained from Gene Expression Omnibus database. The differentially expressed genes (DEGs) and miRNAs (DEmiRNAs) between NPC and normal samples were identified by using t-test based on MATLAB software (FDR < 0.01), followed by pathway enrichment analysis based on DAVID software (P-value < 0.1). Then, DEmiRNA-DEG regulatory network was constructed. Results: A total of 1254 DEGs and 107 DEmiRNAs were identified, respectively. Then, 16 pathways (including cell cycle) and 32 pathways (including pathways in cancer) were enriched by DEGs and target genes of DEmiRNAs, respectively. Furthermore, DEmiRNA-DEG regulatory network was constructed, containing 12 DEmiRNAs (including has-miR-615-3P) and 180 DEGs (including MCM4 and CCNE2). Conclusion: has-miR-615-3p might take part in the pathogenetic process of NPC through regulating MCM4 which is enriched in cell cycle. The DEmiRNAs identified in the present study might serve as new biomarkers for NPC.     

Analysis of microarray-identified genes and microRNAs associated with drug resistance in ovarian cancer

The aim of this study was to identify potential microRNAs and genes associated with drug resistance in ovarian cancer through web-available microarrays. The drug resistant-related microRNA microarray dataset GS54665 and mRNA dataset {"type":"entrez-geo","attrs":{"text":"GSE33482","term_id":"33482"}}GSE33482, {"type":"entrez-geo","attrs":{"text":"GSE28646","term_id":"28646"}}GSE28646, and {"type":"entrez-geo","attrs":{"text":"GSE15372","term_id":"15372"}}GSE15372 were downloaded from the Gene Expression Omnibus database. Dysregulated microRNAs/genes were screened with GEO2R and were further identified in SKOV3 (SKOV3/DDP) and A2780 (A2780/DDP) cells by real-time quantitative PCR (qRT-PCR), and then their associations with drug resistance was analyzed by comprehensive bioinformatic analyses. Nine microRNAs (microRNA-199a-5p, microRNA-199a-3p, microRNA-199b-3p, microRNA-215, microRNA-335, microRNA-18b, microRNA-363, microRNA-645 and microRNA-141) and 38 genes were identified to be differentially expressed in drug-resistant ovarian cancer cells, with seven genes (NHSL1, EPHA3, USP51, ZSCAN4, EPHA7, SNCA and PI15) exhibited exactly the same expression trends in all three microarrays. Biological process annotation and pathway enrichment analysis of the 9 microRNAs and 38 genes identified several drug resistant-related signaling pathways, and the microRNA-mRNA interaction revealed the existence of a targeted regulatory relationship between the 9 microRNAs and most of the 38 genes. The expression of 9 microRNAs and the 7 genes by qRT-PCR in SKOV3/DDP and A2780/DDP cells indicating a consistent expression profile with the microarrays. Among those, the expression of EPHA7 and PI15 were negatively correlated with that of microRNA-141, and they were also identified as potential targets of this microRNA via microRNA-mRNA interaction. We thus concluded that microRNA-141, EPHA7, and PI15 might jointly participate in the regulation of drug resistance in ovarian cancer and serve as potential targets in targeted therapies.     

Integrated regulatory mechanisms of miRNAs and targeted genes involved in colorectal cancer

Purpose: CRC (Colorectal cancer) is a lethal cancer for death worldwide and the underlying pathological mechanisms for CRC progression remain unclear. We aimed to explore the regulatory mechanism of CRC and provide novel biomarkers for CRC screening. Methods: Downloading from GEO (Gene Expression Omnibus) database, Microarray data {"type":"entrez-geo","attrs":{"text":"GSE44861","term_id":"44861"}}GSE44861 were consisted of 111 colon tissues samples including 55 from adjacent noncancerous tissues and 56 from tumors tissues. After data pre-processing, up- and down regulated DEGs (differentially expressed genes) were identified using Bayes moderated t-test. Then DIVAD (Database for Annotation, Visualization and Integrated Discovery) was recruited to perform functional analysis for DEGs. Thereafter, PPI (protein-protein interaction) network was constructed by mapping DEGs into STRING (Search Tool for the Retrieval of Interacting Genes) database. Further, PPI modules were constructed and the protein domains of DEGs in the modules were analyzed. Moreover, miRNA regulatory network was established through GSEA (gene set enrichment analysis) method. Results: In summary, 96 up- and 212 down-regulated DEGs were identified. Totally, ten DEGs with high degrees in the constructed PPI network were selected, in which COLL1A1, PTGS2 and ASPN were also identified as crucial genes in PPI modules. Furthermore, COLL1A1 was predicted to be targeted by miR-29, while PTGS2 and ASPN were both predicted to be regulated by miR-101 and miR-26. Conclusion: COL11A1 might involve in the progression of CRC via being targeted by miR-29, whereas PTGS2 and ASPN were both regulated by miR-101 and miR-26. Moreover, ASPN may be supposed as a novel biomarker for CRC detection and prevention.     

Upregulation of Heat Shock Proteins (HSPA12A,HSP90B1, HSPA4, HSPA5 and HSPA6) in Tumour Tissues Is Associated with Poor Outcomes from HBV-Related Early-Stage Hepatocellular Carcinoma

Background: Heat shock proteins (HSPs) are overexpressed in human hepatocellular carcinoma (HCC) tissue and correlate with aggressiveness and prognosis of HCC.Methods: Using the {"type":"entrez-geo","attrs":{"text":"GSE14520","term_id":"14520"}}GSE14520 microarray expression profile from Gene Expression Omnibus, we compared HSP gene expression between tumour and non-tumour tissues and correlated this with outcomes in HCC patients.Results: We analysed 220 hepatitis B virus (HBV)-related HCC patients and 25 HSPs in this study. With the exception of HSPA4L, HSPA12A and HSPB8, members of the HSP family, including HSPH1, HSPBP1, HSPA1A, HSPA1B, HSPA1L, HSPA2, HSPA4, HSPA5, HSPA8, HSPA9, HSPAA1, HSPAB1, HSPA14, HSPB11, HSPA13, HSP90B1 and HSPBAP1, were all overexpressed in tumour tissues (all P < 0.001). In contrast, HSPB6, HSPB7, HSPA6, HSPB2 and HSPB3 were upregulated in non-tumour tissues (all P < 0.001). Multivariate analysis showed that cirrhosis (HR = 5.282, 95% CI = 1.294-21.555, P = 0.02), Barcelona Clinic liver cancer (BCLC) staging (HR = 2.151, 95% CI = 1.682-2.750, P < 0.001), HSPA12A (HR = 1.042, 95% CI = 1.003-1.082, P = 0.033) and HSP90B1 (HR = 1.001, 95% CI = 1.000-1.001, P = 0.011) were negatively associated with survival of HBV-related HCC patients. Furthermore, advanced BCLC staging (HR = 1.797, 95% CI = 1.439-2.244, P < 0.001) was also associated with earlier recurrence of HCC. The high expression of HSPA4 (HR = 1.002, 95% CI = 1.000-1.004, P = 0.019), HSPA5 (HR = 1.0, 95% CI = 1.0-1.0, P = 0.046) and HSPA6 (HR = 1.008, 95% CI = 1.001-1.015, P = 0.021) was similarly associated with HCC recurrence.Conclusions: The expression of most HSPs was higher in tumour tissues than in non-tumour tissues. High BCLC staging scores, advanced cirrhosis and the overexpression of HSPA12A and HSP90B1 might be associated with poor survival from HCC, whereas high levels of HSPA4, HSPA5 and HSPA6 might be associated with earlier recurrence of HCC.     

Identification ACTA2 and KDR as key proteins for prognosis of PD‐1/PD‐L1 blockade therapy in melanoma

Programmed cell death protein 1 (PD‐1) /programmed cell death ligand 1 (PD‐L1) blockade is an important therapeutic strategy for melanoma, despite its low clinical response. It is important to identify genes and pathways that may reflect the clinical outcomes of this therapy in patients. We analyzed clinical dataset {"type":"entrez-geo","attrs":{"text":"GSE96619","term_id":"96619"}}GSE96619, which contains clinical information from five melanoma patients before and after anti‐PD‐1 therapy (five pairs of data). We identified 704 DEGs using these five pairs of data, and then the number of DEGs was narrowed down to 286 in patients who responded to treatment. Next, we performed KEGG pathway enrichment and constructed a DEG‐associated protein‐protein interaction network. Smooth muscle actin 2 (ACTA2) and tyrosine kinase growth factor receptor (KDR) were identified as the hub genes, which were significantly downregulated in the tumor tissue of the two patients who responded to treatment. To confirm our analysis, we demonstrated similar expression tendency to the clinical data for the two hub genes in a B16F10 subcutaneous xenograft model. This study demonstrates that ACTA2 and KDR are valuable responsive markers for PD‐1/PD‐L1 blockade therapy.     

Comprehensive analysis of key lncRNAs in HCV-positive hepatocellular carcinoma

IntroductionHepatocellular carcinoma (HCC) is one of the most common cancers worldwide. Despite the therapeutic advances in HCC in the past few decades, the mortality rate of HCC is still high. Hepatitis C (HCV) infection is one of the major etiological risk factors of HCCs. However, the underlying mechanisms of HCV-induced hepatocarcinogenesis remain largely unclear.Material and methodsOur study represented the comprehensive analysis of differentially expressed lncRNAs in HCV-positive HCC for the first time by analyzing the public dataset {"type":"entrez-geo","attrs":{"text":"GSE17856","term_id":"17856"}}GSE17856. Co-expression network and gene ontology (GO) analysis revealed the functions of those differentially expressed lncRNAs.ResultsWe identified 256 upregulated lncRNAs and 198 downregulated lncRNAs in HCV- positive HCC compared to the normal liver tissues. Co-expression network and GO analysis showed that these lncRNAs were involved in regulating metabolism, energy pathways, proliferation and the immune response. Seven lncRNAs (LOC341056, CCT6P1, PTTG3P, LOC643387, LOC100133920, C3P1 and C22orf45) were identified as key lncRNAs and co-expressed with more than 100 differentially expressed genes (DEGs) in HCV-related HCC. Kaplan-Meier analysis showed that higher expression levels of LOC643387, PTTG3P, LOC341056, CCT6P1 and lower expression levels of C3P1 and C22orf45 were associated with shorter survival time in the TCGA dataset.ConclusionsWe believe that this study can provide novel potential therapeutic and prognostic biomarkers for HCV-positive HCC.     

Identification and validation of redox-immune based prognostic signature for hepatocellular carcinoma

The intimate interaction between redox signaling and immunity has been widely revealed. However, the clinical application of relevant therapeutic is unavailable due to the absence of validated markers that stratify patients. Here, we identified novel biomarkers for prognosis prediction in hepatocellular carcinoma (HCC). Prognostic redox-immune-related genes for predicting overall survival (OS) of HCC were identified using datasets from TCGA, LIRI-JP, and {"type":"entrez-geo","attrs":{"text":"GSE14520","term_id":"14520"}}GSE14520. LASSO Cox regression was employed to construct the signature model and generate a risk score in the TCGA cohort. The signature contained CDO1, G6PD, LDHA, GPD1L, PPARG, FABP4, CCL20, SPP1, RORC, HDAC1, STC2, HDGF, EPO, and IL18RAP. Patients in the high-risk group had a poor prognosis compared to the low-risk group. Univariate and multivariate Cox regressions identified this signature as an independent factor for predicting OS. Nomogram constructed by multiple clinical parameters showed good performance for predicting OS indicated by the c-index, the calibration curve, and AUC. GSEA showed that oxidoreductase activity and peroxisome-related metabolic pathways were enriched in the low-risk group, while glycolysis activity and hypoxia were higher in the high-risk group. Furthermore, immune profiles analysis showed that the immune score and stromal score were significantly decreased in the high-risk group in the TCGA cohort. There was a considerably lower infiltration of anti-tumor immune cells while a higher proportion of pro-tumor immune cells in silico. Immune markers were distinctly expressed between the subgroups, and redox-sensitive immunoregulatory biomarkers were at higher levels in the high-risk group. Altogether, we identified a redox-immune prognostic signature. A more severe redox perturbation-driven immunosuppressive environment in the high-risk group stratified by the signature may account for poor survival. This may provide a clue to the combined therapy targeting redox and immune in HCC.     

Identification of Key Genes and Pathways associated with Endometriosis by Weighted Gene Co-expression Network Analysis

Background: Endometriosis is a common gynecological disorder with high rates of infertility and pelvic pain. However, its pathogenesis and diagnostic biomarkers remain unclear. This study aimed to elucidate potential hub genes and key pathways associated with endometriosis in ectopic endometrium (EC) and eutopic endometrium (EU).Material and Method: EC and EU-associated microarray datasets were obtained from the gene expression omnibus (GEO) database. Gene set enrichment analysis was performed to obtain further biological insight into the EU and EC-associated genes. Weighted gene co-expression network analysis (WGCNA) was performed to find clinically significant modules of highly-correlated genes. The hub genes that belong to both the weighted gene co-expression network and protein-protein interaction (PPI) network were identified using a Venn diagram.Results: We obtained EC and EU-associated microarray datasets {"type":"entrez-geo","attrs":{"text":"GSE7305","term_id":"7305"}}GSE7305 and {"type":"entrez-geo","attrs":{"text":"GSE120103","term_id":"120103"}}GSE120103. Genes in the EC were mainly enriched in the immune response and immune cell trafficking, and genes in the EU were mainly enriched in stress response and steroid hormone biosynthesis. PPI networks and weighted gene co-expression networks were constructed. An EC-associated blue module and an EU-associated magenta module were identified, and their function annotations revealed that hormone receptor signaling or inflammatory microenvironments may promote EU passing through the oviducts and migrating to the ovarian surfaces, and adhesion and immune correlated genes may induce the successful ectopic implantation of the endometrium (EC). Twelve hub genes in the EC and sixteen hub genes in the EU were recognized and further validated in independent datasets.Conclusion: Our study identified, for the first time, the hub genes and enrichment pathways in the EC and EU using WGCNA, which may provide a comprehensive understanding of the pathogenesis of endometriosis and have important clinical implications for the treatment and diagnosis of endometriosis.     

Identification of a tumor microenvironment-associated prognostic gene signature in bladder cancer by integrated bioinformatic analysis

Bladder cancer is a common malignancy in the urinary system. Stromal and immune cells in tumor microenvironments, including those in the bladder cancer microenvironment, can serve as prognostic markers. However, the complex processes of bladder cancer necessitate large-scale evaluation to better understand the underlying mechanisms and identify biomarkers for diagnosis and treatment. We used the Estimation of STromal and Immune cells in MAlignant Tumors using Expression data algorithm to assess the association between stromal and immune cell-related genes and overall survival of patients with bladder cancer. We also identified and evaluated differentially expressed genes between cancer and non-cancer tissues from The Cancer Genome Atlas. Patients were categorized into different prognosis groups according to their stromal/immune scores based on differential gene expression. In addition, the prognostic value of the differentially expressed genes was assessed in a separate validation cohort using the Gene Expression Omnibus microarray dataset {"type":"entrez-geo","attrs":{"text":"GSE13507","term_id":"13507"}}GSE13507, which identified nine genes (TNC, CALD1, PALLD, TAGLN, TGFB1I1, HSPB6, RASL12, CPXM2, and CYR61) associated with overall survival. Multivariate regression analysis showed that three genes (TNC, CALD1, and PALLD) were possible independent prognostic markers for patients with bladder cancer. Multiple gene set enrichment analysis of individual genes showed strong correlations with stromal and immune interactions, indicating that these nine genes may be related to carcinogenesis, invasion, and metastasis of bladder cancer. These findings provide useful insight into the molecular mechanisms of bladder cancer development, and suggest candidate biomarkers for prognosis and treatment.