Search PubMedSearch

PubMed · 39113023

Biomarkers related to m6A and succinic acid metabolism in papillary thyroid carcinoma.

Abstract

BACKGROUND: Studies have shown that m6A modification is related to the occurrence and development of papillary thyroid carcinoma (PTC). The disorder of succinic acid metabolism is associated with the occurrence and development of various tumors. However, there are few studies based on m6A and succinate metabolism-related genes (SMRGs) in PTC. METHODS: The TCGA-Thyroid carcinoma (THCA), GSE33630, 1159 SMRGs, and 23 m6A regulatory factors were collected from the online databases. Subsequently, the differentially expressed genes (DEGs) were selected between PTC (Tumor) and Normal samples. The overlapping genes among the DEGs, m6A, and SMRGs were applied to screen the biomarkers. Using the 3 machine-learning algorithms, the biomarkers were determined based on the overlapping genes. Next, the biomarkers were evaluated by the ROC curve and expression analysis in TCGA-THCA and GSE33630. Then, the overall survival (OS) differences were compared between the high-and low-expression biomarkers. Finally, immune infiltration analysis, molecular regulatory network, and drug prediction were performed based on the biomarkers. RESULTS: In TCGA-THCA, there were 2800 DEGs between and Normal samples, and then 7 overlapping genes were obtained. Importantly, ADK, TNFRSF10B, CYP7B1, FGFR2, and CPQ were determined as biomarkers with excellent diagnostic efficiency (AUC > 0.7). In PTC samples, ADK and TNFRSF10B were high-expressed while CYP7B1, FGFR2, and CPQ were low-expressed. Especially, the high-expression groups of ADK had a better prognosis, while the high-expression groups of CYP7B1, FGFR2, and CPQ had a worse prognosis. Afterward, immune infiltration analysis found that 16 immune cells had infiltration differences between the Tumor and Normal samples. Finally, transcription factor SP1 could regulate CYP7B1 and TNFRSF10B. Moreover, Navitoclax was a potential drug for PTC patients. CONCLUSION: Overall, we described 5 biomarkers associated with adverse prognosis of PTC, including ADK, TNFRSF10B, CYP7B1, FGFR2, and CPQ. All these biomarkers were involved in succinate metabolism and m6A modification of RNA. This set of biomarkers should be explored further for their diagnostic value in PTC. Investigations into the mechanistic role of alteration of succinate metabolism and m6A modification of RNA pathways in the pathophysiology of PTC are warranted.

Explore related subjects

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Minyu Li, Xiaodan Fu, Tianhan Zhou, Hui Han. 2024-08-07. Biomarkers related to m6A and succinic acid metabolism in papillary thyroid carcinoma.. https://doi.org/10.1186/s12920-024-01975-8

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related citations

Global Genomic Surveillance.

Global genomic surveillance has emerged as a foundational pillar of public health in the twenty-first century, enabling real-time tracking of pathogen evolution and informing outbreak response. This chapter examines the strategic architecture of global genomic surveillance, focusing on its application to arboviruses such as chikungunya virus (CHIKV). It explores the integration of genomic data with epidemiological, clinical, and environmental information within a One Health framework, while addressing critical challenges in governance, equity, and interoperability. The discussion covers the entire genomic surveillance workflow, from sample collection and sequencing to bioinformatic analysis and phylogenetic inference, and highlights the transformative role of artificial intelligence (AI) in predictive surveillance. By analyzing global initiatives, operational barriers, and emerging technologies, this chapter underscores the necessity of sustainable, equitable, and interoperable genomic systems to proactively address current and future infectious disease threats.

Humans

Systematic Dissection of Key Driver Perturbation Signatures in Single Cells via ECCITE-seq.

CRISPR screens, such as expanded CRISPR-compatible cellular indexing of transcriptomes and epitopes by sequencing (ECCITE-seq), enable the simultaneous measurement of transcriptomes, gRNA identity, and cell-surface protein expression at single-cell resolution to systematically interrogate gene function. This platform provides a powerful and scalable experimental approach for validating disease-associated regulators identified by large-scale association studies and other computational methods, including network-based analyses of multi-omics data. Here, as an example application, we describe an ECCITE-seq framework to characterize the transcriptomic consequences of perturbing multiple neuronal key driver genes associated with Alzheimer's disease (AD) in human-induced pluripotent stem cell (hiPSC)-derived neurons. More broadly, by integrating customized pooled gRNA libraries with different CRISPR effectors across multiple cell types, this approach allows for the assessment of the regulatory impact of candidate genes implicated in development and disease processes.

Humans

Identification of Genome-Wide Chromatin Structural Aberration in Cancer by Hi-C Analysis.

Aberrant three-dimensional genome organization is a hallmark of cancer, often driving oncogene activation through mechanisms such as enhancer hijacking. High-throughput chromosome conformation capture (Hi-C) maps these interactions on a genome-wide scale. Unlike earlier dilution-based methods, in situ Hi-C performs proximity ligation within intact nuclei, minimizing random ligation noise and enabling fine-scale structure detection. This chapter describes an optimized in situ Hi-C protocol tailored for cancer cell lines using MboI digestion and biotin-mediated pull-down to generate high-complexity libraries. We further outline a computational workflow that extends beyond standard topological mapping of compartments and topologically associating domains to identify cancer-specific aberrations. Specifically, we focus on detecting chromosomal rearrangements (structural variants) and characterizing the distinct circular topology of extrachromosomal DNA. This integrated experimental and analytical framework provides the necessary tools to dissect the spatial dysregulation underlying tumor evolution.

Humans