A Comprehensive Analysis for Expression, Diagnosis, and Prognosis of m5C Regulator in Breast Cancer and Its ncRNA-mRNA Regulatory Mechanism.
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ABSTRACT:
SUBMITTER: Liu J
PROVIDER: S-EPMC9257136 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:BackgroundCholangiocarcinoma (CHOL) is a malignant tumor that originates in the extrahepatic bile duct and can extend from the hilar region to the lower end of the common bile duct. The prognosis of CHOL patients is particularly poor; therefore, in this study, we screened mRNAs correlated with N6-methyladenosine (m6A) to construct a risk model for prognosis in CHOL.MethodsThe TCGA-CHOL dataset was applied to obtain and analyze the coexpression of 1281 m6A-related mRNAs, from which 14 were selected for further analysis through univariate proportional hazards (cox) regression analysis. Aryl hydrocarbon receptor interacting protein (AIP), CCAAT/enhancer binding protein beta (CEBPB), syndecan1 (SDC1), vacuolar protein sorting 25 homolog (VPS25) and syntaxin binding protein 2 (STXBP2) were then screened out through the least absolute shrinkage and selection operator (LASSO) and multivariate Cox regression analysis to develop a precise m6A-related mRNA prognosis risk model (MRMRPM) with an area under curve (AUC) of 0.908 and 0.923 after 1 and 2 years, respectively. We divided the samples into high-risk and low-risk groups using the m6A-related mRNA prognosis risk model.ResultsKaplan-Meier analysis indicated poor overall survival (OS) for the high-risk group. Two Gene Expression Omnibus (GEO) datasets (GSE89748 and GSE107943) were used to validate the risk model. The results of drug sensitivity and immune cell infiltration analysis showed that the risk model could serve as a prognosis index of potential immunotherapeutic characteristics and drug sensitivity. Furthermore, the proportion of resting dendritic cells and regulatory T cells was positively associated with an increased expression of four m6A-related mRNAs - AIP, CEBPB, SDC1, and VPS25 - in the high-risk CHOL group.ConclusionsOur findings suggest that this model can be a prognostic indicator for CHOL patients.
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Project description:Great improvement has been made in the diagnosis and therapy of breast cancer patients. However, the identification of biomarkers for early diagnosis, prognosis, therapy assessment and monitoring, including drug resistance and the early detection of micro-metastases, is still lacking. Recently, circulating microRNAs (miRNAs), circulating freely in the blood stream or entrapped in extracellular vesicles (EVs), have been shown to have a potential diagnostic, prognostic or predictive power. In this review, recent findings are summarized, both at a preclinical and clinical level, related to miRNA applicability in the context of breast cancer. Different aspects, including clinical and technical challenges, are discussed, describing the potentialities of miRNA use in breast cancer. Even though more methodological standardized studies conducted in larger and selected patient cohorts are needed to support the effective clinical utility of miRNA as biomarkers, they could represent novel and accessible tools to be transferred into clinical practice.
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Project description:CXCL12-CXCR4-CXCR7 signaling promotes tumor growth and metastasis in breast cancer. Alternative splicing of CXCL12 produces isoforms with distinct structural and biochemical properties, but little is known about isoform-specific differences in breast cancer subtypes and patient outcomes. We investigated global expression profiles of the six CXCL12 isoforms, CXCR4, and CXCR7 in The Cancer Genome Atlas breast cancer cohort using next-generation RNA sequencing in 948 breast cancer and benign samples and seven breast cancer cell lines. We compared expression levels with several clinical parameters, as well as metastasis, recurrence, and overall survival (OS). CXCL12-?, -?, and -? are highly co-expressed, with low expression correlating with more aggressive subtypes, higher stage disease, and worse clinical outcomes. CXCL12-? did not correlate with other isoforms but was prognostic for OS and showed the same trend for metastasis and recurrence-free survival. Effects of CXCL12-? remained independently prognostic when taking into account expression of CXCL12,CXCR4, and CXCR7. These results were also reflected when comparing CXCL12-?, -?, and -? in breast cancer cell lines. We summarized expression of all CXCL12 isoforms in an important chemokine signaling pathway in breast cancer in a large clinical cohort and common breast cancer cell lines, establishing differences among isoforms in multiple clinical, pathologic, and molecular subgroups. We identified for the first time the clinical importance of a previously unstudied isoform, CXCL12-?.
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Project description:BackgroundThe incidence of thyroid cancer, whose local recurrence and metastasis lead to death, has always been high and the pathogenesis of papillary thyroid carcinoma (PTC) has not been clearly elucidated. Therefore, the research for more accurate prognosis-related predictive biomarkers is imminent, and a key gene can often be a prognostic marker for multiple tumors.MethodsGene expression profiles of various cancers in the TCGA and GTEx databases were downloaded, and genes significantly associated with the prognosis of THCA were identified by combining differential analysis with survival analysis. Then, a series of bioinformatics tools and methods were used to analyze the expression of the gene in each cancer and the correlation of each expression with prognosis, tumor immune microenvironment, immune neoantigens, immune checkpoints, DNA repair genes, and methyltransferases respectively. The possible biological mechanisms were also investigated by GSEA enrichment analysis.Results656 differentially expressed genes were identified from two datasets and 960 DEGs that were associated with disease-free survival in THCA patients were screened via survival analysis. The former and the latter were crossed to obtain 7 key genes, and the gene with the highest risk factor, ASF1B, was selected for this study. Differential analysis of multiple databases showed that ASF1B was commonly and highly expressed in pan-cancer. Survival analysis showed that high ASF1B expression was significantly associated with poor patient prognosis in multiple cancers. In addition, ASF1B expression levels were found to be associated with tumor immune infiltration in THCA, KIRC, LGG, and LIHC, and with tumor microenvironment in BRCA, LUSC, STAD, UCEC, and KIRC. Further analysis of the relationship between ASF1B expression and immune checker gene expression suggested that ASF1B may regulate tumor immune patterns in most tumors by regulating the expression levels of specific immune checker genes. Finally, GSEA enrichment analysis showed that ASF1B high expression was mainly enriched in cell cycle, MTORC1 signaling system, E2F targets, and G2M checkpoints pathways.ConclusionsASF1B may be an independent prognostic marker for predicting the prognosis of THCA patients. The pan-cancer analysis suggested that ASF1B may play an important role in the tumor micro-environment and tumor immunity and it has the potential of serving as a predictive biomarker for multiple cancers.
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Project description:Osteoarthritis (OA) is a common orthopedic degenerative disease, leading to high disability in activities of daily living. There remains an urgent need to identify the underlying mechanisms and identify new therapeutic targets in OA diagnosis and treatment. Circular RNAs (circRNAs) play a role in the development of multiple diseases. Many studies have reported that circRNAs regulate microRNAs (miRNAs) through an endogenous competitive mechanism. However, it remains unclear if an interplay between circRNAs, miRNAs, and target genes plays a deeper regulatory role in OA. Four datasets were downloaded from the GEO database, and differentially expressed circRNAs (DECs), differentially expressed miRNAs (DEMs), and differentially expressed genes (DEGs) were identified. Functional annotation and pathway enrichment analysis of DEGs and DECs were carried out to determine the main associated mechanism in OA. A protein–protein network (PPI) was constructed to analyze the function of, and to screen out, hub DEGs in OA. Based on the artificial intelligence prediction of protein crystal structures of two hub DEGs, TOP2A and PLK1, digitoxin and oxytetracycline were found to have the strongest affinity, respectively, with molecular docking. Subsequently, overlapping DEMs and miRNAs targeted by DECs obtained target DEMs (DETMs). Intersection of DEGs and genes targeted by DEMs obtained target DEGs (DETGs). Thus, a circRNA–miRNA–mRNA regulatory network was constructed from 16 circRNAs, 32 miRNAs, and 97 mRNAs. Three hub DECs have the largest number of regulated miRNAs and were verified through in vitro experiments. In addition, the expression level of 16 DECs was validated by RT-PCR. In conclusion, we constructed a circRNA–miRNA–mRNA regulatory network in OA and three new hub DECs, hsa_circ_0027914, hsa_circ_0101125, and hsa_circ_0102564, were identified as novel biomarkers for OA.
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Project description:BackgroundBreast carcinoma has become a nonnegligible public health problem in China with its increasing incidence and mortality in woman. As a early event regulating tumorigenesis and development, DNA methylation became one of the focuses of current carcinoma researches on potential diagnostic and therapeutic targets.MethodsIn this study, we comprehensively analyzed the gene expression data and DNA methylation data of breast carcinoma and adjacent normal tissues samples in the Gene Expression Omnibus database. Influences of tumor stage, adjuvant therapy, hormone therapy, and chemotherapy on CpG methylation level were explored by linear regression analysis. Correlations between methylation and gene expression levels were determined by spearman rank correlation analysis. Log-rank test was applied for determining significance of associations between CpG sites methylation level and breast cancer patients' Kaplan-Meier survival.ResultsA total of 229 CpG sites were found to be significantly associated with tumor stage or treatment, and eight of which were potential markers that affect the survival of breast carcinoma and negatively correlated with their genes' expression levels.ConclusionsWe reported eight CpG sites as potential breast cancer prognosis signatures through comprehensively analyzed gene expression and DNA methylation datasets, and excluding influences of tumor stage and treatment. This should be helpful for breast cancer early diagnosis and treatment.
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