Ontology highlight
ABSTRACT:
PROVIDER: PRJNA788393 | ENA |
REPOSITORIES: ENA
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Project description:Early detection of hepatocellular carcinoma (HCC) remains challenging, as the currently recommended surveillance strategy based on ultrasound combined with alpha-fetoprotein (AFP) is limited by suboptimal sensitivity and accessibility. Cell-free DNA (cfDNA) provides a minimally invasive avenue for cancer detection. However, most existing cfDNA-based approaches either perform unreliably in low-input samples or require analytically complex workflows. Here, we systematically profiled serum cfDNA from individuals with HCC and without HCC and identified a high-abundance tumor-associated single cfDNA fragment at the FAM230F genomic region. Integrative analysis of liver assay for transposase-accessible chromatin with sequencing (ATAC-seq) revealed consistent tumor-specific chromatin accessibility at this locus, suggesting a tumor-derived origin. Structural characterization further demonstrated enrichment of G-quadruplex (G4) features within the target sequence, which may increase resistance to serum nuclease degradation and promote its preferential retention in circulation. Based on these properties, we established a qPCR-based detection workflow with clinical accessibility. In a validation cohort independent of the discovery cohort, a ΔCt cutoff of 2 was selected by maximizing the Youden index within the same cohort. The assay showed a sensitivity of 94.5% and a specificity of 90.5% for distinguishing HCC from non-HCC. Collectively, our study identifies FAM230F as a structurally stable tumor-associated cfDNA fragment and establishes a simple and scalable qPCR-based assay for HCC detection, providing a practical framework for translating cfDNA fragment analysis into clinical biomarkers.
2026-09-09 | GSE327857 | GEO
Project description:Background & Aims. Hepatocellular carcinoma (HCC), the most prevalent form of liver cancer, is growing in incidence but treatment options remain limited, particularly for late stage disease. As liver cirrhosis is the principal risk state for HCC development, markers to detect early HCC within this patient population are urgently needed. Perturbation of epigenetic marks, such as DNA methylation (5mC), is a hallmark of human cancers, including HCC. Identification of regions with consistently altered 5mC levels in circulating cell free DNA (cfDNA) during progression from cirrhosis to HCC could therefore serve as markers for development of minimally-invasive screens of early HCC diagnosis and surveillance. Methods. To discover DNA methylation derived biomarkers of HCC in the background of liver cirrhosis, we profiled genome-wide 5mC landscapes in patient cfDNA using the Infinium HumanMethylation450k BeadChip Array. We further linked these findings to primary tissue data available from TCGA and other public sources. Using biological and statistical frameworks, we selected CpGs that robustly differentiated cirrhosis from HCC in primary tissue and cfDNA followed by validation in an additional independent cohort. Results. We identified CpGs that segregate patients with cirrhosis, from patients with HCC within a cirrhotic liver background, through genome-wide analysis of cfDNA 5mC landscapes. Lasso regression analysis pinpointed a panel of probes in our discovery cohort that were validated in two independent datasets. A panel of five CpGs (cg04645914, cg06215569, cg23663760, cg13781744, and cg07610777) yielded AUROCs of 0.9525, 0.9714, and 0.9528 in cfDNA discovery and tissue validation cohorts 1 and 2, respectively. Conclusions. 5mC markers derived from cfDNA robustly identify HCC within a cirrhotic liver background indicating that further validation is warranted. Our finding that 5mC markers derived from primary tissue did not perform well in cfDNA, compared to those identified directly from cfDNA, reveals potential advantages of starting with cfDNA to discover high performing markers for liquid biopsy development.
2019-08-16 | GSE129374 | GEO
Project description:Early detection of hepatocellular carcinoma (HCC) remains challenging, as the currently recommended surveillance strategy based on ultrasound combined with alpha-fetoprotein (AFP) is limited by suboptimal sensitivity and accessibility. Cell-free DNA (cfDNA) provides a minimally invasive avenue for cancer detection. However, most existing cfDNA-based approaches either perform unreliably in low-input samples or require analytically complex workflows. Here, we systematically profiled serum cfDNA from individuals with HCC and without HCC and identified a high-abundance tumor-associated single cfDNA fragment at the FAM230F genomic region. Integrative analysis of liver assay for transposase-accessible chromatin with sequencing (ATAC-seq) revealed consistent tumor-specific chromatin accessibility at this locus, suggesting a tumor-derived origin. Structural characterization further demonstrated enrichment of G-quadruplex (G4) features within the target sequence, which may increase resistance to serum nuclease degradation and promote its preferential retention in circulation. Based on these properties, we established a qPCR-based detection workflow with clinical accessibility. In a validation cohort independent of the discovery cohort, a ΔCt cutoff of 2 was selected by maximizing the Youden index within the same cohort. The assay showed a sensitivity of 94.5% and a specificity of 90.5% for distinguishing HCC from non-HCC. Collectively, our study identifies FAM230F as a structurally stable tumor-associated cfDNA fragment and establishes a simple and scalable qPCR-based assay for HCC detection, providing a practical framework for translating cfDNA fragment analysis into clinical biomarkers.
2026-09-09 | GSE328835 | GEO
Project description:The early detection of tissue and organ damage associated with autoimmune diseases (AID) has been identified as key to improve long-term survival, but non-invasive biomarkers are lacking. Elevated cell-free DNA (cfDNA) levels have been observed in AID and inflammatory bowel disease (IBD), prompting interest to use cfDNA as a potential non-invasive diagnostic and prognostic biomarker. Despite these known disease-related changes in concentration, it remains impossible to identify AID and IBD patients through cfDNA analysis alone. By using unsupervised clustering on large sets of shallow whole-genome sequencing (sWGS) cfDNA data, we uncover AID- and IBD-specific genome-wide patterns in plasma cfDNA in both the obstetric and general AID and IBD populations. Supervised learning of the genome-wide patterns allows AID prediction with 50% sensitivity at 95% specificity. Importantly, the method can identify pregnant women with AID during routine non-invasive prenatal screening. Since AID pregnancies have an increased risk of severe complications, early recognition or detection of new onset AID can redirect pregnancy management and limit potential adverse events. This method opens up new avenues for screening, diagnosis and monitoring of AID and IBD.
2022-09-14 | E-MTAB-11607 | biostudies-arrayexpress
Project description:Background: The lack of highly sensitive and specific diagnostic biomarkers is a major contributor to the poor outcomes of patients with hepatocellular carcinoma (HCC). We sought to develop a non-invasive diagnostic approach using circulating cell-free DNA (cfDNA) for the early detection of HCC. Methods: Applying the 5hmC-Seal technique, we obtained genome-wide 5-hydroxymethylcytosines (5hmC) in cfDNA samples from 2,554 Chinese subjects: 1,204 HCC patients, 392 patients with chronic hepatitis B virus infection (CHB) or liver cirrhosis (LC), and 958 healthy individuals and patients with benign liver lesions. A diagnostic model for early HCC was developed through case-control analyses using the elastic net regularization for feature selection. Results: The 5hmC-Seal data from HCC patients showed a genome-wide distribution enriched with liver-derived enhancer marks. We developed a 32-gene diagnostic model that accurately distinguished early HCC (stage 0/A) based on the Barcelona Clinic Liver Cancer (BCLC) staging system from non-HCC (validation set: AUC = 88.4%; 95% CI, 85.8-91.1%), showing superior performance over α-fetoprotein (AFP). Besides detecting patients with early stage or small tumors (e.g., ≤ 2.0 cm) from non-HCC, the 5hmC model showed high capacity for distinguishing early HCC from high risk subjects with CHB or LC history (validation set: AUC = 84.6%; 95% CI, 80.6-88.7%), also significantly outperforming AFP. Furthermore, the 5hmC diagnostic model appeared to be independent from potential confounders (e.g., smoking/alcohol intake history). Conclusions: We have developed and validated a non-invasive approach with clinical application potential for the early detection of HCC that are still surgically resectable in high risk individuals.
2019-08-07 | GSE112679 | GEO
Project description:Background: Immunotherapy has increased the expected survival of patients with advanced HCC. However, objective radiological response to these therapies has been reported to occur in around 20% of patients. Our aim was to identify potential serological markers of response to ICIs. Methods: 25 patients with advanced HCC treated with immunotherapy were prospectively in-cluded. Cytokine and cfDNA/ctDNA levels were measured prior to first treatment administration (basal) and after 3 months of treatment. Basal ctDNA profiling was also analyzed. Results: Basal levels of CTLA-4, cfDNA and ctDNA were significantly different in patients presenting progres-sive disease as best radiological response. The percentage of patients with basal mutations in CDKN2A was significantly higher in patients presenting progressive disease and they have a significantly lower number of CNV. Levels at 3 months of starting the treatment of MCP-1, TNF-alpha, cfDNA and ctDNA were also significantly different between patients with and without progressive disease. Higher cfDNA and ctDNA levels were associated with a poorer overall survival. Conclusion: Analysis of cfDNA and cytokines could help to stratify patients according to expected response to immunotherapies.
2025-04-02 | GSE237791 | GEO
Project description:Nucleosomes are the basic unit of packaging of eukaryotic chromatin, and nucleosome positioning can differ substantially between cell types. Here, we sequence 14.5 billion plasma-borne cell-free DNA (cfDNA) fragments (700-fold coverage) to generate genome-wide maps of in vivo nucleosome occupancy. We identify 13 million local maxima of nucleosome protection, spanning 2.53 gigabases (Gb) of the human genome, whose positions and spacings correlate with nuclear architecture, gene structure and gene expression. We further show that short cfDNA fragments - poorly recovered by standard protocols - directly footprint the in vivo occupancy of DNA-bound transcription factors such as CTCF. The sequence composition of cfDNA has previously been used to noninvasively monitor cancer, pregnancy and organ transplantation, but a key limitation of this paradigm is its dependence on genotypic differences to distinguish between contributing tissues. We show that nucleosome spacing in gene bodies and cis-regulatory elements, inferred from cfDNA in healthy individuals, correlates most strongly with transcriptional and epigenetic features of lymphoid and myeloid cells, consistent with hematopoietic cell death as the normal source of cfDNA. We build on this observation to show how in vivo nucleosome footprints can be used to infer the cell types that contribute to circulating cfDNA in pathological states such as cancer. Because it does not rely on genotypic differences, this strategy may enable the noninvasive cfDNA-based monitoring of a much broader set of clinical conditions than is currently possible. Sequencing of cfDNA libraries from healthy individuals, pooled healthy individuals and individuals with disease for the identification of nucleosomes and protection from other DNA binding proteins.
2015-11-04 | E-GEOD-71378 | biostudies-arrayexpress
Project description:Prostate cancer (PCa) is one of the most common malignancies in men, with familial forms accounting for nearly 20% of cases. Early detection and risk stratification remain challenging, especially in individuals with a genetic predisposition. In this pilot study, we evaluated the feasibility and clinical relevance of an integrated multi-omic approach by performing whole-genome, strand-specific sequencing of circulating cell-free DNA (cfDNA) from eight patients with confirmed familial PCa. Through an integrated analysis pipeline, we identified 18,878 genetic variants, of which 2,276 were potentially pathogenic. Among these, 26 recurrent high-impact mutations—such as stop-gain and start-loss variants—were found in genes including MUC4, MCM9, and SKA3. Epigenomic profiling revealed widespread hypermethylation in these genes, suggesting transcriptional repression, while allele-specific methylation (ASM) was detected in TTC22, TEX51, WDR89, LAIR2, and SKA3, indicating functional interplay between somatic mutations and local epigenetic regulation. These findings demonstrate the potential of combining genetic and epigenetic data from cfDNA to uncover novel markers for improved stratification and personalized management of familial prostate cancer.
2026-06-15 | E-MTAB-15437 | biostudies-arrayexpress
Project description:As a non-invasive blood testing, the detection of cell-free DNA (cfDNA) methylation in plasma is raising increasing interest due to its diagnostic and biology applications. Although extensively used in cfDNA methylation analysis, bisulfite sequencing is less cost-effective. Through enriching methylated cfDNA fragments with MeDIP followed by deep sequencing, we aimed to characterize cfDNA methylome in cancer patients. In this study, we investigated the cfDNA methylation patterns in lung cancer patients by MeDIP-seq. MEDIPS package was used for the identification of differentially methylated regions (DMRs) between patients and normal ones. Overall, we identified 330 differentially methylated regions (DMRs) in gene promoter regions, 33 hypermethylation and 297 hypomethylation respectively, by comparing lung cancer patients and healthy individuals as controls. The 33 hypermethylation regions represent 32 genes. Some of the genes had been previously reported to be associated with lung cancers, such as GAS7, AQP10, HLF, CHRNA9 and HOPX. Taken together, our study provided an alternative method of cfDNA methylation analysis in lung cancer patients with potential clinical applications.
2019-03-31 | E-MTAB-7163 | biostudies-arrayexpress