Search PubMedSearch

PubMed · 40008902

Multiple features of cell-free mtDNA for predicting transarterial chemoembolization response in hepatocellular carcinoma.

Abstract

BACKGROUND: Transarterial chemoembolization (TACE) is the primary treatment modality for advanced HCC, yet its efficacy assessment and prognosis prediction largely depend on imaging and serological markers that possess inherent limitations in terms of real-time capability, sensitivity, and specificity. Here, we explored whether multiple features of cell-free mitochondrial DNA (cf-mtDNA), including copy number, mutations, and fragmentomics, could be used to predict the response and prognosis of patients with HCC undergoing TACE treatment. METHODS: A total of 60 plasma cell-free DNA samples were collected from 30 patients with HCC before and after the first TACE treatment and then subjected to capture-based mtDNA sequencing and whole-genome sequencing. RESULTS: Comprehensive analyses revealed a clear association between cf-mtDNA multiple features and tumor characteristics. Based on cf-mtDNA multiple features, we also developed HCC death and progression risk prediction models. Kaplan-Meier curve analyses revealed that the high-death risk or high-progression-risk group had significantly shorter median overall survival (OS) and progression-free survival than the low-death risk or low-progression-risk group (all p<0.05). Moreover, the change in cf-mtDNA multiple features before and after TACE treatment exhibited an exceptional ability to predict the risk of death and progression in patients with HCC (log-rank test, all p<0.01; HRs: 0.36 and 0.33, respectively). Furthermore, we observed the consistency of change between the cf-mtDNA multiple features and copy number variant burden before and after TACE treatment in 40.00% (12/30) patients with HCC. CONCLUSIONS: Altogether, we developed a novel strategy based on profiling of cf-mtDNA multiple features for prognosis prediction and efficacy evaluation in patients with HCC undergoing TACE treatment.

Explore related subjects

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Miao Dang, Siyuan Wang, Fan Peng, Runjiao Zhang, Huanmin Jiao, Huanqin Zhang, Haiying Dong, Hongxin Zhang, Jinliang Xing, Xu Guo, Yang Liu. 2025-02-26. Multiple features of cell-free mtDNA for predicting transarterial chemoembolization response in hepatocellular carcinoma.. https://doi.org/10.1097/hc9.0000000000000652

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