Combination of Hotspot Mutations With Methylation and Fragmentomic Profiles to Enhance Multi‐Cancer Early Detection

Cancer Medicine, Journal Year: 2025, Volume and Issue: 14(1)

Published: Jan. 1, 2025

ABSTRACT Background Multi‐cancer early detection (MCED) through a single blood test significantly advances cancer diagnosis. However, most MCED tests rely on type of biomarkers, leading to limited sensitivity, particularly for early‐stage cancers. We previously developed SPOT‐MAS, multimodal ctDNA‐based assay analyzing methylation and fragmentomic profiles detect five common Despite its potential, SPOT‐MAS exhibited moderate sensitivities This study investigated whether integrating hotspot mutations into could enhance rates. Method A targeted amplicon sequencing approach was profile 700 in cell‐free DNA integrated the assay, creating single‐blood draw workflow. workflow, namely Plus retrospectively validated cohort 255 non‐metastatic patients (breast, colorectal, gastric, liver, lung) 304 healthy individuals. Results Hotspot were detected 131 (51.4%) patients, with highest rates liver (96.5%), followed by colorectal (59.3%) lung (53.7%). Lower found cancers low tumor mutational burden, such as breast (31.3%) gastric (41.9%) In contrast, demonstrated higher these (51.6% 62.9% gastric). The combination predictions improved detection, achieving an overall sensitivity 78.5% at specificity 97.7%. Enhanced observed (81.36%) (82.9%). Conclusion integration genetic epigenetic alterations enhances various Further validation larger cohorts is necessary support broader clinical applications.

Language: Английский

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Integrating multi‐omics features enables non‐invasive early diagnosis and treatment response prediction of diffuse large B‐cell lymphoma

Clinical and Translational Medicine, Journal Year: 2025, Volume and Issue: 15(1)

Published: Jan. 1, 2025

Abstract Background Multi‐omics features of cell‐free DNA (cfDNA) can effectively improve the performance non‐invasive early diagnosis and prognosis cancer. However, multimodal characterization cfDNA remains technically challenging. Methods We developed a comprehensive multi‐omics solution (COMOS) to specifically obtain an extensive fragmentomics landscape, presented by breakpoint characteristics nucleosomes, CpG islands, DNase clusters enhancers, besides typical methylation, copy number alteration cfDNA. The COMOS was tested on 214 plasma samples diffuse large B‐cell lymphoma (DLBCL) matched healthy controls. Results For diagnosis, improved area under curve (AUC) value .993 compared with individual omics model, sensitivity 95% at 98% specificity. Detection achieved 91% 99% specificity in early‐stage patients, while AUC values model were 0.942, 0.968, 0.989, 0.935, 0.921, 0.781 0.917, respectively, lower In treatment response cohort, yielded superior 88% 86% (AUC, 0.903). has excellent prediction. Conclusions Our study provides approach high accuracy for DLBCL, showing great potential future clinical application. Key points A Integrated could be used DLBCL. evaluate efficacy R‐CHOP before DLBCL treatment.

Language: Английский

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Genomic and fragmentomic landscapes of cell-free DNA for early cancer detection

Nature reviews. Cancer, Journal Year: 2025, Volume and Issue: unknown

Published: March 4, 2025

Language: Английский

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Systematically Evaluating Cell‐Free DNA Fragmentation Patterns for Cancer Diagnosis and Enhanced Cancer Detection via Integrating Multiple Fragmentation Patterns

Advanced Science, Journal Year: 2024, Volume and Issue: 11(30)

Published: June 17, 2024

Cell-free DNA (cfDNA) fragmentation patterns have immense potential for early cancer detection. However, the definition of varies, ranging from entire genome to specific genomic regions. These not been systematically compared, impeding broader research and practical implementation. Here, 1382 plasma cfDNA sequencing samples 8 types are collected. Considering that within open chromatin regions is more susceptible fragmentation, 10 as features employed machine learning techniques evaluate their performance examined. All demonstrated discernible classification capabilities, with end motif showing highest diagnostic value cross-validation. Combining cross independent validation results revealed incorporated both fragment length coverage information exhibited robust predictive capacities. Despite potential, power these unstable. To address this limitation, an ensemble classifier via integrating all developed, which notable improvements in detection tissue-of-origin determination. Further functional bioinformatics investigations on significant feature intervals model its impressive ability identify critical regulatory involved pathogenesis.

Language: Английский

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Circulating tumor DNA methylation detection as biomarker and its application in tumor liquid biopsy: advances and challenges

MedComm, Journal Year: 2024, Volume and Issue: 5(11)

Published: Nov. 1, 2024

Abstract Circulating tumor DNA (ctDNA) methylation, an innovative liquid biopsy biomarker, has emerged as a promising tool in early cancer diagnosis, monitoring, and prognosis prediction. As noninvasive approach, overcomes the limitations of traditional tissue biopsy. Among various biomarkers, ctDNA methylation garnered significant attention due to its high specificity detection capability across diverse types. Despite immense potential, clinical application faces substantial challenges pertaining sensitivity, specificity, standardization. In this review, we begin by introducing basic biology common techniques methylation. We then explore recent advancements faced biopsies. This includes progress screening identification molecular subtypes, monitoring recurrence minimal residual disease (MRD), prediction treatment response prognosis, assessment burden, determination origin. Finally, discuss future perspectives applications. comprehensive overview underscores vital role enhancing diagnostic accuracy, personalizing treatments, effectively progression, providing valuable insights for research practice.

Language: Английский

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A deep-learning model for quantifying circulating tumour DNA from the density distribution of DNA-fragment lengths

Nature Biomedical Engineering, Journal Year: 2025, Volume and Issue: unknown

Published: March 7, 2025

Language: Английский

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EM-DeepSD: A Deep Neural Network Model Based on Cell-Free DNA End-Motif Signal Decomposition for Cancer Diagnosis

Diagnostics, Journal Year: 2025, Volume and Issue: 15(9), P. 1156 - 1156

Published: May 1, 2025

Background and Objectives: The accurate discrimination between patients with without cancer using their cell-free DNA (cfDNA) is crucial for early diagnosis. end-motifs of cfDNA serve as significant biomarkers, offering compelling prospects This study proposes EM-DeepSD, a signal decomposition deep learning framework based on end-motifs, which aimed at improving the accuracy diagnosis adapting to different sequencing modalities. Materials Methods: included 146 diagnosed 122 non-cancer controls. EM-DeepSD comprises three core modules. Initially, it utilizes module decompose reconstruct input end-motif profiles, thereby generating multiple regular subsequences that optimize subsequent modeling process. Subsequently, both machine are employed improve Furthermore, this paper compares performance existing benchmarked methods demonstrate its superiority. Based framework, we developed EM-DeepSSA model compared two across datasets. Results: In internal validation set, outperformed benchmark (area under curve (AUC), 0.920; adjusted p value < 0.05). Meanwhile, also exhibited best independent external testing sets were subjected 5-hydroxymethylcytosine (5hmCS) broad-range (BR-cfDNA-Seq), respectively (test set-1: AUC = 0.933; test set-2: 0.956; Conclusions: summary, present new can achieve high classification in applicable

Language: Английский

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Mining nucleic acid “omics” to boost liquid biopsy in cancer

Cell Reports Medicine, Journal Year: 2024, Volume and Issue: 5(9), P. 101736 - 101736

Published: Sept. 1, 2024

Language: Английский

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Biomarkers in high grade serous ovarian cancer

Biochimica et Biophysica Acta (BBA) - Reviews on Cancer, Journal Year: 2024, Volume and Issue: unknown, P. 189224 - 189224

Published: Nov. 1, 2024

Language: Английский

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Prospective validation study: a non-invasive circulating tumor DNA-based assay for simultaneous early detection of multiple cancers in asymptomatic adults

BMC Medicine, Journal Year: 2025, Volume and Issue: 23(1)

Published: Feb. 14, 2025

Non-invasive multi-cancer early detection (MCED) tests have shown promise in enhancing cancer detection. However, their clinical utility across diverse populations remains underexplored, limiting routine implementation. This study aims to validate the of a multimodal non-invasive circulating tumor DNA (ctDNA)-based MCED test, SPOT-MAS (Screening for Presence Of Tumor by Methylation And Size). We conducted multicenter prospective study, K-DETEK (ClinicalTrials.gov identifier: NCT05227261), involving 9057 asymptomatic individuals aged 40 years or older 75 major hospitals and one research institute Vietnam. Participants were followed 12 months. 9024 eligible participants, 43 (0.48%) tested positive ctDNA. Among these, 17 confirmed with malignant lesions various primary organs through standard-of-care (SOC) imaging biopsy, 9 cases matching our tissue origin (TOO) predictions. resulted predictive value 39.53% (95%CI 26.37–54.42) TOO accuracy 52.94% 30.96–73.83). 8981 participants (99.52%) who negative, 8974 cancer-free during 12-month period after testing, yielding negative 99.92% (95% CI 99.84–99.96). The test demonstrated an overall sensitivity 70.83% 50.83–85.09) specificity 99.71% 99.58–99.80) detecting types, including those without SOC screening options. presents validation lower middle-income country, demonstrating potential Our findings indicate that could be valuable additions national programs, particularly regions where such initiatives are currently limited. ClinicalTrials.gov ID: NCT05227261. Date registration: 07/02/2022.

Language: Английский

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