Identification of differentially expressed genes associated with ferroptosis in Crohn's disease.

Ferroptosis-related genes may play a critical regulatory role in the pathogenesis of Crohn's disease (CD). The purpose of the present study was to identify genes expressed in CD that are associated with ferroptosis, and to provide guidance in the diagnosis and therapy of CD. CD mRNA expression data were initially gathered from the Gene Expression Omnibus (GEO) database. GSE75214 and GSE102133 datasets were selected as the major targets and were analyzed for differentially expressed genes (DEGs). Subsequently, R software was used to analyze the common genes among the DEGs between CD and ferroptosis-related genes. Gene Ontology enrichment analysis and Kyoto Encyclopedia of Genes and Genome pathway analysis were conducted to identify related pathways and functions. Protein-protein interaction (PPI) analysis was performed to identify target genes. The DSigDB website was used to predict potential target drugs for hub genes. Reverse transcription-quantitative (RT-q) PCR was employed to detect the expression of these ferroptosis-related genes in clinical samples obtained from healthy controls and patients with CD. According to the two GEO datasets, 13 ferroptosis DEGs (11 upregulated genes and two downregulated genes) were identified in CD with thresholds of P<0.05 and |log2 fold change|>1, and were selected for further analysis. PPI analysis indicated the mutual effects among these genes and filtered out five hub genes. The top 10 potential targeted drugs were selected. The qPCR results showed that the expression levels of three genes, namely, IL-6, prostaglandin-endoperoxide synthase 2 (PTGS2) and dual oxidase 2 (DUOX2), were different between CD samples and healthy samples. This result was consistent with the results obtained from the bioinformatics analysis. In conclusion, bioinformatics analysis identified a total of 13 ferroptosis-associated genes in CD. Further verification by qPCR showed that IL-6, PTGS2 and DUOX2 may affect the process of CD by regulating ferroptosis. These findings might provide new biomarkers, diagnostic and therapeutic markers for CD.

Construction and analysis of a reliable five-gene prognostic signature for colon adenocarcinoma associated with the wild-type allelic state of the COL6A6 gene.

Background: Tumors emerge by acquiring a number of mutations over time. The first mutation provides a selective growth advantage compared to adjacent epithelial cells, allowing the cell to create a clone that can outgrow the cells that surround it. Subsequent mutations determine the risk of the tumor progressing to metastatic cancer. Some secondary mutations may inhibit the aggressiveness of the tumor while still increasing the survival of the clone. Meaningful mutations in genes may provide a strong molecular foundation for developing novel therapeutic strategies for cancer. Methods: The somatic mutation and prognosis in colon adenocarcinoma (COAD) were analyzed. The copy number variation (CNV) and differentially expressed genes (DEGs) between the collagen type VI alpha 6 chain (COL6A6) mutation (COL6A6-MUT) and the COL6A6 wild-type (COL6A6-WT) subgroups were evaluated. The independent prognostic signatures based on COL6A6-allelic state were determined to construct a Cox model. The biological characteristics and the immune microenvironment between the two risk groups were compared. Results: COL6A6 was found to be highly mutated in COAD at a frequency of 9%. Patients with COL6A6-MUT had a good overall survival (OS) compared to those with COL6A6-WT, who had a different CNV pattern. Significant differences in gene expression were established for 593 genes between the COL6A6-MUT and COL6A6-WT samples. Among them, MUC16, ASNSP1, PRR18, PEG10, and RPL26P8 were determined to be independent prognostic factors. The internally validated prognostic risk model, constructed using these five genes, demonstrated its value by revealing a significant difference in patient prognosis between the high-risk and low-risk groups. Specifically, patients in the high-risk group exhibited a considerably worse prognosis than did those in the low-risk group. The high-risk group had a significantly higher proportion of patients over 60 years of age and patients in stage III. Moreover, the tumor immune dysfunction and exclusion (TIDE) score and the expression of human leukocyte antigen (HLA) family genes were all higher in the high-risk group than that in the low-risk group. Conclusions: The allelic state of COL6A6 and the five associated DEGs were identified as novel biomarkers for the diagnosis and prognosis of COAD and may be therapeutic targets in COAD.

The mitotic spindle-related seven-gene predicts the prognosis and immune microenvironment of lung adenocarcinoma.

PURPOSE: Abnormalities in the mitotic spindle have been linked to a variety of cancers. Data on their role in the onset, progression, and treatment of lung adenocarcinoma (LUAD) need to be explored. METHODS: The data were retrieved from The Cancer Genome Atlas (TCGA), Gene Expression Omnibus (GEO), and Molecular Signatures Database (MSigDB), for the training cohort, external validation cohort, and the hallmark mitotic spindle gene set, respectively. Mitotic spindle genes linked to LUAD prognosis were identified and intersected with differentially expressed up-regulated genes in the training cohort. Nomogram prediction models were built based on least absolute shrinkage and selection operator (LASSO) regression, univariate cox, and multivariate cox analyses. The seven-gene immunological score was examined, as well as the correlation of immune checkpoints. The DLGAP5 and KIF15 expression in BEAS-2B, A549, H1299, H1975, and PC-9 cell lines was validated with western blot (WB). RESULTS: A total of 965 differentially expressed up-regulated genes in the training cohort intersected with 51 mitotic spindle genes associated with LUAD prognosis. Finally, the seven-gene risk score was determined and integrated with clinical characteristics to construct the nomogram model. Immune cell correlation analysis revealed a negative correlation between seven-gene expression with B cell, endothelial cell (excluding LMNB1), and T cell CD8 + (p < 0.05). However, the seven-gene expression was positively correlated with multiple immune checkpoints (p < 0.05). The expression of DLGAP5 and KIF15 were significantly higher in A549, H1299, H1975, and PC-9 cell lines than that in BEAS-2B cell line. CONCLUSION: High expression of the seven genes is positively correlated with poor prognosis of LUAD, and these genes are promising as prospective immunotherapy targets.

The structural maintenance of chromosomes 5 is a possible biomarker for individualized treatment of colorectal cancer.

BACKGROUND: Although the understanding of resistance to oxaliplatin (OXA) chemotherapy in colorectal cancer (CRC) has been sought for many years, drug tolerance remains a major challenge for cancer therapy. Revealing the molecular mechanism of OXA resistance could help to explain the poor prognosis of patients. METHODS: Gene expression omnibus (GEO) database was searched, GSE83129, which contains RNA profiling in metastatic CRC patients treated first-line with OXA, was chosen for the following analysis. Differential expressed genes (DEGs) between the adenocarcinoma and adjacent_normal team, respectively, in the OXA responders and no-responders were analyzed. The Gene Ontology (GO) and hub genes in the protein-protein interaction (PPI) network were used for the molecular mechanism of OXA resistance. Tumor-related databases were used for the clinical relevance of the structural maintenance of chromosomes 5 (SMC5) in CRC. The in vitro assays were used to detect the molecular function of SMC5 in CRC cells. Quantitative real-time PCR (qRT-PCR) and western blot were used to detect the expression of the structural maintenance of chromosomes 5/6 (SMC5/6) complex components upon OXA and raltitrexed (RTX) treatment. CCK-8 was used to detect the cell viability of cells with different treatment. RESULTS: SMC5 was downregulated in CRC tissues of OXA no-response patients. Lower expression of SMC5 was correlated with a poor prognosis in CRC patients, improved this gene expression, inhibited the CRC cell growth and invasion in vitro. Furthermore, SMC5 was downregulated upon OXA treatment in CRC cells, while RTX would reverse its expression, and the combination of these two drugs restored the SMC5 level to the normal situation. Finally, RTX treatment enhanced the OXA cytotoxicity. CONCLUSION: SMC5 is a tumor suppressor, that low expression of this gene is benefit for the development of CRC. Combination treatment with RTX and OXA may be more suitable for those OXA no-responders with lower SMC5.

Newly Developed Graft Failure Detected Using Computed Tomography Within 1 Year After Coronary Artery Bypass Grafting Surgery: One Single-Center Experience.

BACKGROUND: Newly developed graft failure negatively affects the short- and long-term outcomes of patients who experience coronary artery bypass grafting (CABG) surgery. This study explored the value of transit time flow measurement (TTFM) parameters for predicting the risk of newly developed graft failure that occurs within 1 year after CABG, as well as investigated the relationship between newly developed graft failure and adverse cardiovascular events. METHODS: A total of 134 patients who underwent CABG and had CT angiography (CTA) data (1 year post-operatively) were divided into two groups: the patient group, in which patients did not have newly developed graft failure, and the occluded group, in which patients developed newly developed graft failure between 1 and 12 months after CABG. The patency rate of grafts in different targets was analyzed. The correlations between graft failure and TTFM parameters and between graft failure and the occurrence of adverse cardiovascular events were investigated. RESULTS: The overall rate of newly developed graft failure was 7.2%, the venous graft failure was 10.8%, and the arterial graft failure was 0.7%. The occluded group had a higher pulse index (PI) (2.9 vs. 2.4, P = 0.007), a lower mean graft flow (MGF) (20 vs. 25 ml/min, P = 0.028), and a lower diastolic flow fraction (DF) (63.5 vs. 70%, P = 0.019) than the patent group. The cut-off value for predicting newly developed graft failure was PI > 2.75 (P = 0.007), MGF < 23.5 ml/min (P = 0.03), and DF < 65.5% (P = 0.019). Compared with the patent group, the newly developed graft failure group had higher rates of recurrent angina (13.6 vs. 0.9%, P = 0.0014) and revascularization intervention (9.1 vs. 0% P = 0.026). However, there were no differences in death, cardiac death, myocardial infarction, and cerebral infarction after CABG operation between these two groups (P > 0.05). CONCLUSIONS: A high PI and low MGF and DF are risk factors for newly developed graft failure. The patients with newly developed graft failure had higher rates of recurrent angina and revascularization intervention. TTFM parameters may be used to predict the occurrence of newly developed graft failure in patients after CABG surgery.

Pulmonary adenofibroma with central liquefaction necrosis: A case report.

Pulmonary adenofibroma (PAF) is a rare benign tumor. Computed tomography (CT) imaging of PAF show well-defined, homogeneous and solitary nodules. To the best of our knowledge, there is no report of PAF presenting with central liquefaction necrosis on CT images. The present study reports the case of a 70-year-old man who was hospitalized due to an inguinal hernia without respiratory symptoms. Chest CT scan revealed a tumor (~6.5x5.5x4.4 cm) in the lower lobe of the left lung, characterized by uneven density and unclear boundary with the pleura. Contrast-enhanced scan revealed that the lesion was slightly enhanced and liquefaction necrosis appeared in its center. Wedge resection was performed using video-assisted thoracic surgery. Histopathological and immunohistochemical examination confirmed the diagnosis of PAF.

A Four-Gene Prognostic Signature Based on the TEAD4 Differential Expression Predicts Overall Survival and Immune Microenvironment Estimation in Lung Adenocarcinoma.

Background: TEA domain transcription factor 4 (TEAD4) is a member of the transcriptional enhancer factor (TEF) family of transcription factors, which is studied to be linked to the tumorigenesis and progression of various forms of cancers, including lung adenocarcinoma (LUAD). However, the specific function of this gene in the progression of LUAD remains to be explored. Method: A total of 19 genes related to the Hippo pathway were analyzed to identify the significant genes involved in LUAD progression. The TCGA-LUAD data (n = 585) from public databases were mined, and the differentially expressed genes (DEGs) in patients with the differential level of TEAD4 were identified. The univariate Cox regression, zero LASSO regression coefficients, and multivariate Cox regression were performed to identify the independent prognostic signatures. The immune microenvironment estimation in the two subgroups, including immune cell infiltration, HLA family genes, and immune checkpoint genes, was assessed. The Gene Set Enrichment Analysis (GSEA) and GO were conducted to analyze the functional enrichment of DEGs between the two risk groups. The potential drugs for the high-risk subtypes were forecasted via the mode of action (moa) module of the connectivity map (CMap) database. Results: TEAD4 was found to be significantly correlated with poor prognosis in LUAD-patients. A total of 102 DEGs in TEAD4-high vs. TEAD4-low groups were identified. Among these DEGs, four genes (CPS1, ANLN, RHOV, and KRT6A) were identified as the independent prognostic signature to conduct the Cox risk model. The immune microenvironment estimation indicated a strong relationship between the high TEAD4 expression and immunotherapeutic resistance. The GSEA and GO showed that pathways, including cell cycle regulation, were enriched in the high-risk group, while immune response-related and metabolism biological processes were enriched in the low-risk group. Several small molecular perturbagens targeting CFTR or PLA2G1B, by the mode of action (moa) modules of the glucocorticoid receptor agonist, cyclooxygenase inhibitor, and NFkB pathway inhibitor, were predicted to be suited for the high-risk subtypes based on the high TEAD4 expression. Conclusion: The current study revealed TEAD4 is an immune regulation-related predictor of prognosis and a novel therapeutic target for LUAD.

Chromatin Separation Regulators Predict the Prognosis and Immune Microenvironment Estimation in Lung Adenocarcinoma.

Background: Abnormal chromosome segregation is identified to be a common hallmark of cancer. However, the specific predictive value of it in lung adenocarcinoma (LUAD) is unclear. Method: The RNA sequencing and the clinical data of LUAD were acquired from The Cancer Genome Atlas (TACG) database, and the prognosis-related genes were identified. The Kyoto Encyclopedia of Genes and Genomes (KEGG) and Gene Ontology (GO) were carried out for functional enrichment analysis of the prognosis genes. The independent prognosis signature was determined to construct the nomogram Cox model. Unsupervised clustering analysis was performed to identify the distinguishing clusters in LUAD-samples based on the expression of chromosome segregation regulators (CSRs). The differentially expressed genes (DEGs) and the enriched biological processes and pathways between different clusters were identified. The immune environment estimation, including immune cell infiltration, HLA family genes, immune checkpoint genes, and tumor immune dysfunction and exclusion (TIDE), was assessed between the clusters. The potential small-molecular chemotherapeutics for the individual treatments were predicted via the connectivity map (CMap) database. Results: A total of 2,416 genes were determined as the prognosis-related genes in LUAD. Chromosome segregation is found to be the main bioprocess enriched by the prognostic genes. A total of 48 CSRs were found to be differentially expressed in LUAD samples and were correlated with the poor outcome in LUAD. Nine CSRs were identified as the independent prognostic signatures to construct the nomogram Cox model. The LUAD-samples were divided into two distinct clusters according to the expression of the 48 CSRs. Cell cycle and chromosome segregation regulated genes were enriched in cluster 1, while metabolism regulated genes were enriched in cluster 2. Patients in cluster 2 had a higher score of immune, stroma, and HLA family components, while those in cluster 1 had higher scores of TIDES and immune checkpoint genes. According to the hub genes highly expressed in cluster 1, 74 small-molecular chemotherapeutics were predicted to be effective for the patients at high risk. Conclusion: Our results indicate that the CSRs were correlated with the poor prognosis and the possible immunotherapy resistance in LUAD.

Identification of Immune-Related Gene Signature in Stanford Type A Aortic Dissection.

Background: Stanford type A aortic dissection (ATAAD) is a common life-threatening event in the aorta. Recently, immune disorder has been linked to the risk factors that cause ATAAD at the molecular level. However, the specific immune-related gene signature during the progression is unclear. Methods: The GSE52093 and GSE98770 datasets related to ATAAD from the Gene Expression Omnibus (GEO) database were acquired. The immune gene expression levels were analyzed by single sample gene set enrichment analysis (ssGSEA). The correlations between gene networks and immune scores were determined by weighted gene correlation network analysis (WGCNA). The different immune subgroups were finally divided by consensus clustering. The differentially expressed genes (DEGs) were identified and subsequent functional enrichment analyses were conducted. The hub genes were identified by protein-protein interaction (PPI) network and functional similarities analyses. The immune cell infiltration proportion was determined by the CIBERSORT algorithm. Results: According to the ssGSEA results, the 13 ATAAD samples from the GEO database were divided into high- and low-immune subgroups according to the ssGSEA, WGCNA, and consensus clustering analysis results. Sixty-eight immune-related DEGs (IRDEGs) between the two subgroups were enriched in inflammatory-immune response biological processes, including leukocyte cell-cell adhesion, mononuclear cell migration, and myeloid leukocyte migration. Among these IRDEGs, 8 genes (CXCR4, LYN, CCL19, CCL3L3, SELL, F11R, DPP4, and VAV3) were identified as hub genes that represented immune-related signatures in ATAAD after the PPI and functional similarities analyses. The proportions of infiltrating CD8 T cells and M1 macrophages were significantly higher in ATAAD patients in the immune-high group than the immune-low group. Conclusion: Eight immune-related genes were identified as hub genes representing potential biomarkers and therapeutic targets linked to the immune response in ATAAD patients.

m6A regulator-mediated RNA methylation modification patterns are involved in immune microenvironment regulation of coronary heart disease.

Background: Although the roles of m6A modification in the immune responses to human diseases have been increasingly revealed, their roles in immune microenvironment regulation in coronary heart disease (CHD) are poorly understood. Methods: The GSE20680 and GSE20681 datasets related to CHD were acquired from the Gene Expression Omnibus (GEO) database. A total of 30 m6A regulators were used to perform LASSO regression to identify the significant genes involved in CHD. Unsupervised clustering analysis was conducted using the m6A regulators to distinguish the m6A RNA methylation patterns in patients with CHD. The differentially expressed genes (DEGs) and biological characteristics, including GO and KEGG enrichment results, were assessed for the different m6A patterns to analyse the impacts of m6A regulators on CHD. Hub genes were identified, and subsequent microRNAs-mRNAs (miRNAs-mRNAs) and mRNAs-transcriptional factors (mRNA-TFs) interaction networks were constructed by the protein and protein interaction (PPI) network method using Cytoscape software. The infiltrating proportion of immune cells was assessed by ssGSEA and the CIBERSORT algorithm. Quantitative real-time PCR (qRT-PCR) was performed to detect the expression of the significant m6A regulators and hub genes. Results: Four of 30 m6A regulators (HNRNPC, YTHDC2, YTHDF3, and ZC3H13) were identified to be significant in the development of CHD. Two m6A RNA methylation clusters were distinguished by unsupervised clustering analysis based on the expression of the 30 m6A regulators. A total of 491 genes were identified as DEGs between the two clusters. A PPI network including 308 mRNAs corresponding to proteins was constructed, and 30 genes were identified as hub genes that were enriched in the bioprocesses of peptide cross-linking, keratinocyte differentiation. Twenty-seven hub genes were found to be related to miRNAs, and seven hub genes were found to be related to TFs. Moreover, among the 30 hub genes, eight genes were found to be upregulated in CHD, and three were found to be downregulated in CHD compared to the normal people. The high m6A modification pattern was associated with a higher infiltrated abundance of immune cells. Conclusion: Our findings demonstrated that m6A modification plays crucial roles in the diversity and complexity of the immune microenvironment in CHD.