Bioinformatics-based identification of key genes and pathways associated with colorectal cancer diagnosis,treatment, and prognosis

Colorectal cancer (CRC) is known to display a high risk of metastasis and recurrence. The main objective of our investigation was to shed more light on CRC pathogenesis by screening CRC datasets for the identification of key genes and signaling pathways, possibly leading to new approaches for the diagnosis and treatment of CRC. We downloaded the colorectal cancer datasets from the Gene Expression Omnibus (GEO) database site. We used GEO2R to screen for differentially expressed genes (DEGs) of which those with a fold change >1 were considered as up-regulated and those with a fold change <-1 were considered as down-regulated on the basis of a P < .05. “Gene ontology (GO)” and “Kyoto Encyclopedia of Genes and Genomes (KEGG)” data were analyzed by the “DAVID” software. The online search tool “STRING” was used to search for interacting genes or proteins and we used Cytoscape (v3.8.0) to generate a PPI network map and to identify key genes. Finally, survival analysis and stage mapping of key genes were performed using “GEPIA” with the aim of elucidating their potential impact on CRC. Our study revealed 120 intersecting genes of which 55 were up- and 65 were downregulated, respectively. GO analysis revealed that these genes were involved in cell proliferation, exosome secretion, G2/M transition, cytosol, protein binding, and protein kinase activity. KEGG pathway analysis showed that these genes were involved in cell cycle and mineral absorption. The Cytoscape PPI map showed 17 nodes and 262 edges, and 10 hub genes were identified by top 10 degrees. Survival analysis demonstrated that the AURKA, CCNB1, and CCNA2 genes were strongly associated with the survival rate of CRC patients. In addition, CCNB1, CCNA2, CDK1, CKS2, MAD2L1, and DLGAP5 could be correlated to pathological CRC staging. In this research, we identified key genes that may explain the molecular mechanism of occurrence and progression of CRC but may also contribute to an improvement in the clinical staging and prognosis of CRC patients.     

Bioinformatic analysis of differentially expressed profiles of lncRNAs and miRNAs with their related ceRNA network in endometrial cancer

Increasing evidence suggests that long non-coding riboneucleic acids (lncRNAs), as competing endogenous RNA (ceRNA), play a key role in the initiation, invasion, and metastasis of cancer. As a new hypothesis, the lncRNA-micro RNA (miRNA)-messenger RNA (mRNA), ceRNA regulatory network has been successfully constructed in a variety of cancers. However, lncRNA, which plays a ceRNA function in endometrial cancer (EC), is still poorly understood. In this study, we downloaded EC expression profiling from The Cancer Genome Atlas database and used the R software “edgeR” package to analyze the differentially expressed genes between EC and normal endometrium samples. Then, differentially expressed (DE) lncRNAs, miRNAs and mRNAs were selected to construct a lncRNA-miRNA-mRNA prognosis-related regulatory network based on interaction information. The Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathway enrichment analysis were performed on the genes in the network to predict the potential underlying mechanisms and functions of lncRNAs in EC. Kaplan–Meier method and the log-rank test were used for survival analysis. Based on the “ceRNA hypothesis,” we constructed a co-expression network of mRNA and lncRNA genes mediated by miRNA in the process of tumor genesis. Furthermore, we successfully constructed a dysregulated lncRNA-associated ceRNA network containing 96 DElncRNAs, 27 DEmiRNAs, and 74 DEmRNAs. Through Kaplan–Meier curve analysis, we found that 9 lncRNAs, 3 miRNAs, and 12 mRNAs were significantly correlated with the overall survival rate of patients among all lncRNAs, miRNAs, and mRNAs involved in ceRNA (P < .05). Our research provides a new perspective for the interaction among lncRNAs, miRNAs, and mRNA and lays the foundation for further research on the mechanism of lncRNAs in the occurrence of EC.     

Comprehensive analysis of prognostic immune-related genes in the tumor microenvironment of hepatocellular carcinoma (HCC)

Growing evidence supports that the tumor microenvironment plays a key role in the development and progression of tumors. But immune microenvironment of hepatocellular carcinoma (HCC) has not yet been fully explored. In the present investigation, the clinical value and prognostic significance of immune-related genes in HCC were investigated.The immune and stromal scores of HCC were calculated through the application of Estimation of Stromal and Immune cells in Malignant Tumor tissues using Expression data Algorithm based on the Cancer Genome Atlas database. Differentially expressed genes were identified using the “edgeR” package of the R software. Functional annotation and pathway enrichment were performed using “ggplots2” and “clusterProfiler” packages in R software. Protein-protein interaction network was constructed using STRING, and the hub genes were identified through the Cytoscape. Survival analysis was performed using Kaplan-Meier methods. Tumor Immune Estimation Resource algorithm was used to view the immune landscape of the microenvironment in HCC.Firstly, the immune and stromal scores of HCC were calculated and we found that the immune and stromal scores of HCC were closely related to the patients’ prognosis. Then the differentially expressed genes were identified respectively stratified by the median value of the immune and stromal scores, and the immune-related genes that related to the prognosis in HCC patients were further identified. Functional enrichment analysis and protein-protein interaction networks further showed that these genes mainly participated in immune-related biological process. In addition, dendritic cells were found to be the most abundant in the microenvironment of HCC through Tumor Immune Estimation Resource algorithm and were significantly associated with the patients’ prognosis. To robust the results, the immune-related genes were validated in an independent dataset from the Gene Expression Omnibus database.We arrived at a more comprehensive understanding of the microenvironment of HCC and extracted 7 immune-related genes that were significantly associated with the recurrence survival of HCC.     

AKT Network of Genes and Impaired Myocardial Contractility During Murine Acute Chagasic Myocarditis

Chagasic disease is associated with high morbidity in Latin America. Acute Chagasic myocarditis is consistently found in acute infections, but little is known about its contribution to chronic cardiomyopathy. The aim of the study was to phenotypically characterize two strains of mice with differential Chagas infection susceptibility and correlate strain myocarditis phenotypes with heart tissue gene expression. C57BL/6J and Balb/c mice were injected intraperitoneally with 0 or 150–200 tissue-derived trypomastigotes (Tulahuen strain). Echocardiograms, brain natriuretic peptide, and troponin were measured. Heart tissue was harvested for histopathological analysis and gene expression profiling on microarrays. Genes differently expressed between infected Balb/c and C57BL/6J mice were identified. Echocardiograms showed differences in Balb/c versus C57BL/6J infected mice in heart rate (413 versus 476 beats per minute; P = 0.0001), stroke volume (31.9 ± 9.3 versus 39.2 ± 5.5 μL; P = 0.03), and cardiac output (13.1 ± 3.5 versus 18.7 ± 3.2 μL/min; P = 0.002). Gene expression at 4 weeks analysis showed 32 statistically significant (q value < 0.05) differentially expressed genes between infected Balb/c and C57BL/6J mice that were enriched for genes related to the protein kinase B (AKT) pathway. These specific phenotypic features of cardiac response during acute Chagasic myocarditis may, in part, be related to host AKT network regulation.     

Differential expression of transfer RNA-derived small RNAs in IgA nephropathy

Background:IgA nephropathy (IgAN) is one of the most common forms of primary glomerulonephritis. Recent studies have indicated that small noncoding RNAs, such as tRNA-derived small RNAs (tsRNAs), might be novel biomarkers for glomerulonephritis. We therefore investigated the potential roles and possible functions of the tsRNAs in IgAN.Method:Peripheral blood mononuclear cells (PBMCs) were extracted from blood samples of the patients with IgAN and healthy control groups. The expression profiles of tsRNAs were assessed by small RNA sequencing (RNA-Seq) in PBMCs of the IgAN and control groups. Dysregulated tsRNAs were selected for validation by quantitative real-time polymerase chain reaction (qRT-PCR). Target gene prediction and enrichment were performed by bioinformatics analysis.Results:The results revealed that 143 significantly upregulated and 202 significantly downregulated tsRNAs were differentially altered in the IgAN group compared with the control group. Five upregulated tsRNAs (tRF-Val-AAC-007, tRF-Ala-AGC-063, tRF-Gln-CTG-010, tRF-Tyr-GTA-011 and tRF-Thr-AGT-007) and 3 downregulated tsRNAs (tiRNA-Val-TAC-004, tRF-Gly-CCC-005 and tRF-His-GTG-006) were selected for validation by qRT-PCR; the results were consistent with the sequencing data. Gene Ontology (GO) analysis revealed that the target genes predicted by upregulated tsRNAs were mostly enriched in “nucleic acid metabolic process," “intracellular part," and “ion binding," whereas the target genes predicted by downregulated tsRNAs were mostly enriched in “regulation of cellular component organization," “membrane-bound organelle," and “ion binding." Kyoto Encyclopedia of Genes and Genomes pathway analysis revealed that the target genes predicted by upregulated tsRNAs were mostly enriched in “herpes simplex virus 1 infection," whereas the target genes predicted by downregulated tsRNAs were mostly enriched in “circadian rhythmConclusions:The present study confirmed the differential expression of tsRNAs in patients with IgAN, and these dysregulated tsRNAs might be novel potential targets for the diagnosis and treatment of IgAN.     

Exploration of biomarkers in osteoarthritis based on bioinformatics

Osteoarthritis (OA) seriously affects human health and brings a heavy social burden. This study aimed to identify new biomarkers involved in OA. Differential expression analysis and gene set enrichment analysis were performed on the microarray data set of OA. Identify key genes from immune-related DEGs and verify their expression in the validation set. CIBERSORT was used to analyze the infiltration of immune cells. The correlation between key genes and immune cells were conducted. A total of 1779 DEGs were identified in {"type":"entrez-geo","attrs":{"text":"GSE82107","term_id":"82107"}}GSE82107. Gene set enrichment analysis results of top 4 for hallmark revealed the enrichment of DEGs were associated with genes in “HALLMARK_TNFA_SIGNALING_VIA_NFKB”, “HALLMARK_EPITHELIAL_MESENCHYMAL_TRANSITION”, “HALLMARK_INFLAMMATORY_RESPONSE” and “HALLMARK_HYPOXIA”. A total of 108 immune-related DEGs were identified from the overlap between 2498 immune-related genes and 1779 DEGs. The expression of top 6 immune-related DEGs including ADIPOQ, FABP4, FOS, IGLC1, IGLV1–44 and leptin were measured in the validation set, the results shown that IGLC1 and IGLV1–44 might play a key role in the synovial membrane of OA. A total of 8 kinds of cells including B cells memory, Plasma cells, T cells CD4 memory resting, T cells gamma delta, natural killer cells activated, macrophages M0, Mast cells resting and Mast cells activated have significant differences in infiltration between the OA group and the control group. Besides, the expressions of IGLC1 and IGLV1–44 are highly correlated. Our results indicated that IGLC1 and IGLV1–44 may play the role of immune-related biomarkers in OA.     

Aging-related changes in knee flexor muscle strength and cross-sectional area

Weakening muscle strength around the knee tends to render it vulnerable to aging-related damage. This study aimed to examine the association between knee flexor muscle strength and its cross-sectional area (CSA). We also evaluated aging-related changes in flexor muscle strength and CSA. We retrospectively analyzed 252 patients with acute-onset knee pain (<1 month) between September 2006 and August 2009 in accordance with the Strengthening the Reporting of Observational studies in Epidemiology statement. The CSA of each knee flexor muscle (biceps femoris, sartorius, gracilis, semitendinosus (ST), and semimembranosus (SM)) was measured on magnetic resonance imaging axial images at the suprapatellar level. We evaluated flexor muscle strength (peak torque in N.m) using a Cybex dynamometer at 60°/second and 180°/second and its correlation with CSA. In total, 252 patients (mean age, 34.5 years; range, 11 to 66 years; 184 men and 68 women) were included in this study. No significant intergroup differences in demographic data such as sex or body mass index were found. Mean CSA was 605.4 mm² for the SM, 444.7 mm² for the biceps femoris, 282 mm² for the sartorius, 55.4 mm² for the ST, and 34.1 mm² for the gracilis. Mean peak torques were 67.4 N.m and 52.7 N.m at 60°/second and 180°/second, respectively. CSA was positively correlated with flexion strengths of 60°/second (R = 0.363, P < .001) and 180°/second (R = 0.354, P < .001). Muscle strength was associated with CSA in all muscles but the gracilis (R = 0.056, P = .375). Flexion strength decreased significantly with aging from the thirties. Total CSA decreased with aging (r = −0.247, P < .001). The CSA of the biceps femoris, sartorius, SM, and ST decreased significantly, whereas that of the gracilis tended to decrease non-significantly with aging. Flexor muscle strength was associated with total muscle CSA on magnetic resonance imaging and the CSA of every muscle except the gracilis. Flexion strength decreased significantly with aging after the twenties, while total CSA decreased significantly with aging. The CSA of all flexor muscles decreased significantly with aging, whereas that of the gracilis decreased only slightly.     

Identification of pyroptosis-related gene signature for predicting prognosis of patients with pancreatic cancer using bioinformatics

Pancreatic cancer, a common digestive system malignancy, is dubbed the “king of cancers”. The role of pyrophosis-related genes (PRGs) in pancreatic cancer prognosis is yet unknown. In pancreatic cancer and normal tissue, we discovered 9 PRGs that are expressed differently in pancreatic cancer and healthy tissue. Based on the differential expression of PRGs, 2 clusters of pancreatic cancer cases could be identified. The 2 groups had significant disparities in total survival time. The prognostic model of a 5-PRGs signature was created using least absolute shrinkage and selection operator (LASSO) method. The median risk score was used to split pancreatic cancer patients in The Cancer Genome Atlas (TCGA) cohort into 2 groups: low risk and high risk. Patients classified as low-risk had significantly higher survival rates than those classified as high-risk (P < .01). The same results were obtained by validating them against the Gene Expression Omnibus database (P = .030). Cox regression statistical analysis showed that risk score was an independent predictor of overall survival in pancreatic cancer patients. Functional enrichment analysis revealed that apoptosis, cell proliferation, and cell cycle-related biological processes and signaling pathways were enriched. Additionally, the immunological status of the high-risk group worsened. In conclusion, a novel pyroptosis-related gene signature can be used to predict pancreatic cancer patient prognosis.     

Expression of immediate-early genes reveals functional compartments within ocular dominance columns after brief monocular inactivation

Visual inputs from the 2 eyes in most primates activate alternating bands of cortex in layer 4C of primary visual cortex, thereby forming the well-studied ocular dominance columns (ODCs). In addition, the enzymatic reactivity of cytochrome oxidase (CO) reveals “blob” structures within the supragranular layers of ODCs. Here, we present evidence for compartments within ODCs that have not been clearly defined previously. These compartments are revealed by the activity-dependent mRNA expression of immediate-early genes (IEGs), zif268 and c-fos, after brief periods of monocular inactivation (MI). After a 1–3-h period of MI produced by an injection of tetrodotoxin, IEGs were expressed in a patchy pattern that included infragranular layers, as well as supragranular layers, where they corresponded to the CO blobs. In addition, the expressions of IEGs in layer 4C were especially high in narrow zones along boundaries of ODCs, referred to here as the “border strips” of the ODCs. After longer periods of MI (>5 h), the border strips were no longer apparent. When either eyelid was sutured, changes in IEG expression were not evident in layer 4C; however, the patchy pattern of the expression in the infragranular and supragranular layers remained. These changes of IEG expression after MI indicate that cortical circuits involving the CO blobs of the supragranular layers include aligned groups of neurons in the infragranular layers and that the border strip neurons of layer 4C are highly active for a 3-h period after MI.     

A Prognostic Nomogram for Hepatocellular Carcinoma Based on Wound Healing and Immune Checkpoint Genes

Background and AimsWound healing and tumor progression share some common biological features; however, how variations in wound healing patterns affect hepatocellular carcinoma (HCC) prognosis remains unclear.MethodsWe analyzed the wound healing patterns of 594 HCC samples from The Cancer Genome Atlas (TCGA) and the International Cancer Genome Consortium (ICGC) and correlated them with immune infiltration and the expression levels of immune checkpoint genes. A risk score, which we named the “heal.immune” score, was established via stepwise Cox estimation. We constructed a nomogram based on age, sex, TNM stage, and heal.immune score and explored its predictive value for HCC prognosis. Seventy-four clinical patients were enrolled in this study, and all were from Huashan Hospital of Fudan University between 2015 and 2017 to serve as an independent validation group.ResultsWe identified two distinct wound healing patterns in HCC. The biological processes of healing cluster 1 (C1) are related to metabolism, while those of healing cluster 2 (C2) are related to the inflammatory response and immune cell accumulation. A total of 565 wound healing-related genes (based on Gene Ontology) and 25 immune checkpoint genes were considered. By analyzing differentially expressed genes and implementing a stepwise Cox estimation analysis, six genes with p values less than 0.02 in a multivariate Cox estimation were chosen as the “heal.immune” gene set (FCER1G, PLAT, ITGA5, CCNB1, CD86 and CD40). The “heal.immune” gene set, as an OS risk factor, was further validated in Fudan cohort. We constructed a nomogram to predict the 1-, 3- and 5-year overall survival (OS) in the TCGA cohort. The area under curve vales of the receiver characteristic operator curves were 0.82, 0.76 and 0.73 in the training group and 0.84, 0.76 and 0.72 in the test group.ConclusionsWe established a prognostic nomogram based on the heal.immune gene signature, which includes six wound healing- and immunity-related genes. This nomogram accurately predicts the OS of HCC patients.     

Profound misregulation of muscle-specific gene expression in facioscapulohumeral muscular dystrophy

Facioscapulohumeral muscular dystrophy (FSHD) is a neuromuscular disorder characterized by an insidious onset and progressive course. The disease has a frequency of about 1 in 20,000 and is transmitted in an autosomal dominant fashion with almost complete penetrance. Deletion of an integral number of tandemly arrayed 3.3-kb repeat units (D4Z4) on chromosome 4q35 is associated with FSHD but otherwise the molecular basis of the disease and its pathophysiology remain obscure. Comparison of mRNA populations between appropriate cell types can facilitate identification of genes relevant to a particular biological or pathological process. In this report, we have compared mRNA populations of FSHD and normal muscle. Unexpectedly, the dystrophic muscle displayed profound alterations in gene expression characterized by severe underexpression or overexpression of specific mRNAs. Intriguingly, many of the deregulated mRNAs are muscle specific. Our results suggest that a global misregulation of gene expression is the underlying basis for FSHD, distinguishing it from other forms of muscular dystrophy. The experimental approach used here is applicable to any genetic disorder whose pathogenic mechanism is incompletely understood.     

Expression patterns of long non-coding RNAs in peripheral blood mononuclear cells of non-segmental vitiligo

Objective:We explored the patterns of long non-coding RNA (lncRNA) expression in peripheral blood mononuclear cells (PBMCs) from patients with non-segmental vitiligo.Methods:We used high-throughput RNA sequencing technology to generate sequence data from five patients with non-segmental vitiligo alongside five normal healthy individuals, and then performed bioinformatics analyses to detect the differential expression of lncRNA in PBMCs. Gene Ontology (GO) and pathway analyses were performed for functional annotation, and quantitative real-time polymerase chain reaction (qRT-PCR) was used to verify gene expression. Target miRNAs and mRNAs of differentially expressed lncRNAs were predicted using bioinformatics analysis.Results:A total of 292 lncRNAs were differentially expressed in non-segmental vitiligo (fold change ≥ 2.0, P < .05), of which 171 were upregulated and 121 were downregulated. Six differentially expressed lncRNAs were selected, namely ENST00000460164.1, ENST00000393264.2, NR_-046211.1, NR_-135491.1, NR_-135320.1, and ENST00000381108.3, for validation by qRT-PCR. The results showed that ENST00000460164.1 and NR_-046211.1 were highly expressed in PBMCs of non-segmental vitiligo. An lncRNA-miRNA-mRNA network containing two lncRNAs, 17 miRNAs, and 223 mRNAs was constructed.Conclusion:Our results revealed patterns of differentially expressed lncRNAs in the PBMCs of non-segmental vitiligo individuals. ENST00000460164.1, and NR_-046211.1 may be potential biomarkers and drug targets for the treatment of non-segmental vitiligo.     

KIF4A as a novel prognostic biomarker in cholangiocarcinoma

Cholangiocarcinoma (CCA) is one of the most common malignant tumors. Although gene-targeted therapies have significantly improved the outcome of many cancers, the results are still not satisfactory for patients with CCA. Owing to the lack of an effective biomarker for guiding clinical treatment and monitoring prognosis in patients with CCA, the purpose of this study was to identify a new biomarker that could help predict the outcome of patients with CCA using bioinformatics tools.Gene expression data were collected from three publicly available datasets, comprising 263 patients with CCA and 22 healthy controls. Differentially expressed genes were obtained using the limma package (FDR < 0.05, |Log₂FC|>1), and the respective protein–protein interaction revealed five relevant genes in the STRING dataset (TOP2A, BUB1, RRM2, TYMS, and KIF4A). The immunohistochemistry and PCR were used to analyze the difference in KIF4A expression in CCA.Kinesin Family Member 4A (KIF4A) was the only gene significantly associated with overall patient survival (P .035), with higher KIF4A expression being associated with poor survival rates. Moreover, KIF4A was significantly correlated with the infiltration of activated memory T cells (P = .0198) and activated mast cells (P = .008) in the tumor microenvironment. Increase in KIF4A expression affected the infiltration degree of the immune cells, which may be involved in the regulation of immune tolerance by CCA cells. The results indicated that the expression of KIF4A in CCA was higher than that in paracancerous tissues.Taken together, these findings suggest that KIF4A could be a potential new biomarker in CCA for predicting the response of patients to targeted immunotherapies.