ABSTRACT
Background: Many investigations have revealed that alterations in m6A modification levels may be linked to coronary heart disease (CHD). However, the specific link between m6A alteration and CHD warrants further investigation. Methods: Gene expression profiles from the Gene Expression Omnibus (GEO) databases. We began by constructing a Random Forest model followed by a Nomogram model, both aimed at enhancing our predictive capabilities on specific m6A markers. We then shifted our focus to identify distinct molecular subtypes based on the key m6A regulators and to discern differentially expressed genes between the unique m6A clusters. Following this molecular exploration, we embarked on an in-depth analysis of the biological characteristics associated with each m6A cluster, revealing profound differences between them. Finally, we delved into the identification and correlation analysis of immune cell infiltration across these clusters, emphasizing the potential interplay between m6A modification and the immune system. Results: In this research, 37 important m6Aregulators were identified by comparing non-CHD and CHD patients from the GSE20680, GSE20681, and GSE71226 datasets. To predict the risk of CHD, seven candidate m6A regulators (CBLL1, HNRNPC, YTHDC2, YTHDF1, YTHDF2, YTHDF3, ZC3H13) were screened using the logistic regression model. Based on the seven possible m6A regulators, a nomogram model was constructed. An examination of decision curves revealed that CHD patients could benefit from the nomogram model. On the basis of the selected relevant m6A regulators, patients with CHD were separated into two m6A clusters (cluster1 and cluster2) using the consensus clustering approach. The Single Sample Gene Set Enrichment Analysis (ssGSEA) and CIBERSORT methods were used to estimate the immunological characteristics of two separate m6A Gene Clusters; the results indicated a close association between seven candidate genes and immune cell composition. The drug sensitivity of seven candidate regulators was predicted, and these seven regulators appeared in numerous diseases as pharmacological targets while displaying strong drug sensitivity. Conclusion: m6A regulators play crucial roles in the development of CHD. Our research of m6A clusters may facilitate the development of novel molecular therapies and inform future immunotherapeutic methods for CHD.
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Introduction: LAMA1, also known as laminin subunit α1, is a member of the laminin family, which is widely reported to be a key basement membrane molecule that affects various biological activities and is associated with many kinds of diseases. We aimed to investigate the association between LAMA1single-nucleotide polymorphisms and the occurrence and progression of esophageal squamous cell carcinoma in the Chinese population. Method: 2,186 participants were collected retrospectively between October 2008 and January 2017, including 1,043 ESCC patients and 1,143 noncancer patients. A 2 mL blood sample was obtained intravenously for the LDR for SNP analysis. The 6 SNP loci of LAMA1 were selected and examined. We analyzed the association of several genetic models of 6 LAMA1 SNP loci, sex, age, smoking and drinking status, and the occurrence of esophageal squamous cell carcinoma. Results: In the rs62081531 G > A locus, genotype GA was a protective factor for ESCC compared with GG (OR: 0.830, P=0.046), especially among the younger and nondrinkers. At rs607230 T > C, genotype TC was linked with a lower risk of ESCC compared with TT. (OR: 0.613, P=0.034). Haplotype Frequencies revealed that Ars62081531Grs621993Ars539713Trs566655Ars73938538Crs607230 (OR: 0.803, P=0.028) and Grs62081531Grs621993Ars539713Trs566655Crs73938538Crs607230 (OR: 0.679, P=0.010) were strongly associated with lower susceptibility of ESCC. Conclusion: The LAMA1 rs62081531, rs539713, rs566655, and rs607230 polymorphisms were demonstrated to be related to susceptibility to ESCC in the Chinese population. LAMA1 SNPs may have a significant impact on the occurrence of esophageal cancer and may serve as potential diagnostic biomarkers.
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Purpose: Gap junction protein (Connexin) family is the basic unit of cellular connection, whose multiple members were recently demonstrated to be associated with tumor progression. However, the expression pattern and prognostic value of connexin in lung adenocarcinoma (LUAD) have not yet been elucidated. Methods: Consensus cluster algorithm was first applied to determine a novel molecular subtype in LUAD based on connexin genes. The differentially expressed genes (DEGs) between two clusters were obtained to include in Cox regression analyses for the model construction. To examine the predictive capacity of the signature, survival curves and ROC plots were conducted. We implemented GSEA method to uncover the function effects enriched in the risk model. Moreover, the tumor immune microenvironment in LUAD was depicted by CIBERSORT and ssGSEA methods. Results: The integrated LUAD cohort (TCGA-LUAD and GSE68465) were clustered into two subtypes (C1 = 217 and C2 = 296) based on 21 connexins and the clinical outcomes of LUAD cases in the two clusters showed remarkable discrepancy. Next, we collected 222 DEGs among two subclusters to build a prognostic model using stepwise Cox analyses. Our proposed model consisted of six genes that accurately forecast patient outcomes and differentiate patient risk. GSEA indicated that high-risk group was involved in tumor relevant pathways were activated in high-risk group, such as PI3K/AKT signaling, TGF-ß pathway, and p53 pathway. Furthermore, LUAD cases with high-risk presented higher infiltration level of M2 macrophage and neutrophil, suggesting high-risk group were more likely to generate an immunosuppressive status. Conclusion: Our data identified a novel connexin-based subcluster in LUAD and further created a risk signature which plays a central part in prognosis assessment and clinical potency.
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Background: The σ1A subunit of the adaptor protein 1 (AP1S1) participates in various intracellular transport pathways, especially the maintenance of copper homeostasis, which is pivotal in carcinogenesis. It is therefore rational to presume that AP1S1 might also be involved in carcinogenesis. In this hospital-based case-control study, we investigated the genetic susceptibility to ESCC in relation to SNPs of AP1S1 among Chinese population. Methods: A database containing a total of 1303 controls and 1043 ESCC patients were retrospectively studied. The AP1S1 SNPs were analyzed based on ligation detection reaction (LDR) method. Then, the relationship between ESCC and SNPs of AP1S1 was determined with a significant crude P<0.05. Then the logistic regression analysis was used for the calculation for adjusted P in the demographic stratification comparison if a significant difference was observed in the previous step. Results: AP1S1 rs77387752 C>T genotype TT was an independent risk factor for ESCC, while rs4729666 C>T genotype TC and rs35208462 C>T genotype TC were associated with a lower risk for ESCC, especially in co-dominant model and allelic test for younger, male subjects who are not alcohol-drinkers nor cigarette smokers. Conclusion: AP1S1 rs77387752, rs4729666 and rs35208462 polymorphisms are associated with susceptibility to ESCC in Chinese individuals. AP1S1 SNPs may exert an important role in esophageal carcinogenesis and could serve as potential diagnostic biomarkers.
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Background: The most common subtype of lung cancer, called lung adenocarcinoma (LUAD), is also the largest cause of cancer death in the world. The aim of this study was to determine the importance of the METTL7A gene in the prognosis of patients with LUAD. Methods: This particular study used a total of four different LUAD datasets, namely TCGA-LUAD, GSE32863, GSE31210 and GSE13213. Using RT-qPCR, we were able to determine METTL7A expression levels in clinical samples. Univariate and multivariate Cox regression analyses were used to identify factors with independent effects on prognosis in patients with LUAD, and nomograms were designed to predict survival in these patients. Using gene set variation analysis (GSVA), we investigated differences in enriched pathways between METTL7A high and low expression groups. Microenvironmental cell population counter (MCP-counter) and single-sample gene set enrichment analysis (ssGSEA) methods were used to study immune infiltration in LUAD samples. Using the ESTIMATE technique, we were able to determine the immune score, stromal score, and estimated score for each LUAD patient. A competing endogenous RNA network, also known as ceRNA, was established with the help of the Cytoscape program. Results: We detected that METTL7A was down-regulated in pan-cancer, including LUAD. The survival study indicates that METTL7A was a protective factor in the prognosis of LUAD. The univariate and multivariate Cox regression analyses revealed that METTL7A was a robust independent prognostic indicator in survival prediction. Through the use of GSVA, several immune-related pathways were shown to be enriched in both the high-expression and low-expression groups of METTL7A. Analysis of the tumor microenvironment revealed that the immune microenvironment of the group with low expression was suppressed, which may be connected to the poor prognosis. To explore the ceRNA regulatory mechanism of METTL7A, we finally constructed a regulatory network containing 1 mRNA, 2 miRNAs, and 5 long non-coding RNAs (lncRNAs). Conclusion: In conclusion, we presented METTL7A as a potential and promising prognostic indicator of LUAD. This biomarker has the potential to offer us with a comprehensive perspective of the prediction of prognosis and treatment for LUAD patients.
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BACKGROUND: The TGF-ß signal pathways play a key role in the development and promotion of squamous cell carcinoma (SCC). The pathway is mediated by the SMAD family proteins that include SMAD3 and SMAD6. Our study aimed to evaluate the relationship between single nucleotide polymorphism (SNP) of SMAD3/SMAD6 and susceptibility to esophageal squamous cell carcinoma (ESCC) in the Chinese population. PATIENTS AND METHODS: This was a hospital-based case-control study compromised of 1043 ESCC patients and 1315 non-cancer patients. Seven SMAD3/SMAD6 (rs8028147, rs3743343, rs3743342, rs8025774, rs8031440, rs803167, and rs34643453) SNPs were selected and used to evaluate their correlation with ESCC susceptibility. Genetic model tests, stratified analyses, linkage disequilibrium analyses, and haplotype analyses were performed in our study. RESULTS: Participants with SMAD3 rs3743342 C>T, rs8025774 C>T, rs8031440 G>A or rs8031627 G>A had a significantly higher risk of ESCC. This was more evident in males, older patients (>63 years), smokers, and non-alcohol drinking participants. Linkage disequilibrium analyses further revealed that there were strong correlations between SMAD3 rs3743342 C>T, rs8025774 C>T, rs8031440 G>A, and rs8031627 G>A. In the same line, haplotype analyses revealed that SMAD3 ACCCGGSMAD6A and SMAD3AGCCGGSMAD6A were associated with less susceptibility to ESCC while SMAD3ATTTAASMAD6A was associated with a higher risk of ESCC. CONCLUSION: SNPs of SMAD3 were related to higher susceptibility to ESCC. As such, they may contribute to the development of viable strategies for early diagnosis and treatment of ESCC. However, more detailed association mechanisms between SMAD3/SMAD6 SNPs and ESCC need further experiments to prove.
