Front Oncol. 2026 Aug 28;16:1907210. doi: 10.3389/fonc.2026.1907210. eCollection 2026.

ABSTRACT

Clonal evolution in hepatocellular carcinoma (HCC), esophageal squamous cell carcinoma (ESCC), and gastric cancer (GC) reflects the interaction of genetic diversification, cell-state plasticity, and tissue-specific selection. Multi-region and single-cell DNA sequencing resolve truncal and subclonal lineages, whereas single-cell and spatial transcriptomics, proteomics, and serial liquid biopsy characterize cellular states, ecological niches, and temporal dynamics. The three cancers differ in dissemination timing, dominant selective pressures, and biomarker maturity: early seeding is best supported in selected HCC cohorts, ESCC is strongly influenced by field cancerization and epithelial-stromal crosstalk, and GC follows subtype- and ecotype-dependent trajectories. We discuss the assumptions and sampling biases that constrain phylogenetic inference, the causal limits of cross-sectional tumor atlases, clonal hematopoiesis, and the incremental value of broad multi-omics over focused assays. Liquid-biopsy detection of minimal residual disease is prognostic, but treatment benefit from marker-guided intervention remains context dependent. Near-term translation requires standardized, decision-linked assays; adaptive therapy and evolutionary steering remain investigational.

PMID:42729528 | PMC:PMC13563159 | DOI:10.3389/fonc.2026.1907210

Open Res Eur. 2026 Apr 3;6:87. doi: 10.12688/openreseurope.23403.1. eCollection 2026.

ABSTRACT

BACKGROUND: Pancreatic cancer and ovarian cancer are very challenging to diagnose at early stages. The endoscopic retrieval of biopsy tissue from a suspected benign or malignant lesion is challenging due to the tissue's nature. Therefore, within the Instand-NGS4P framework, we developed Measurable Residual Disease (MRD) prototypes to analyze blood plasma samples, with the aim of cost-effectively supporting the differential diagnosis of suspected pancreatic or ovarian neoplasms.

METHODS: Our MRD prototypes examine blood plasma for mutations in cell-free DNA in specific genes associated with pancreatic neoplasms or ovarian neoplasms, respectively. Unique molecular identifiers (UMIs) are used to enable bioinformatic error correction. Ultra-deep sequencing is demonstrated on sequencing platforms from two different vendors (Illumina and MGI). We provide detailed information on bioinformatic processing of sequencing data to perform error-correction.

RESULTS: Using commercially available reference standards, we demonstrate stable mutation detection down to a variant allele frequency (VAF) of 0.1%. At a coverage of 4,000x duplex consensus reads, only two false positives were observed, which can be efficiently mitigated using an appropriate filtering strategy.

CONCLUSIONS: The technical usability of our MRD prototype has been clearly demonstrated for stable low-level VAF detection in commercial reference samples.

PMID:42728989 | PMC:PMC13560845 | DOI:10.12688/openreseurope.23403.1

J Mol Diagn. 2026 Sep 11:S1525-1578(26)00156-X. doi: 10.1016/j.jmoldx.2026.08.002. Online ahead of print.

ABSTRACT

Analysis of circulating tumor-DNA (ctDNA) provides a molecular assessment that can complement routine imaging in childhood cancer management. Detailed monitoring of ctDNA levels may provide information on treatment efficacy and resistance, minimal residual disease and allows for early detection of relapse. Here, tumor-informed ctDNA analysis was applied to 90 blood plasma samples collected from eight children with malignant tumors. Four to ten tumor-specific mutations per patient were assessed using SiMSen-Seq, a digital sequencing approach utilizing unique molecular identifiers (UMIs). The effects of individual SiMSen-Seq assays and plasma samples were evaluated in relation to their impact on background error rate, number of detected target molecules and mutant calling using different UMI family size cutoff settings. The use of at least two sequencing reads per UMI provided the best overall performance by generating the highest number of detected target molecules and hence the optimal chance to detect low-frequent mutations. Data were consistent between SiMSen-Seq assays and plasma samples, providing robust ctDNA profiling over time for all patients. In conclusion, the results show that optimal use of UMIs in tumor-informed ctDNA analysis enables sensitive molecular readout that can assist in management of childhood cancers.

PMID:42727690 | DOI:10.1016/j.jmoldx.2026.08.002

Endokrynol Pol. 2026 Sep 11. doi: 10.5603/ep.112817. Online ahead of print.

ABSTRACT

The incidence of thyroid cancer has increased dramatically over the past four decades, making it the most common endocrine malignancy worldwide. Although well-differentiated thyroid carcinomas generally exhibit excellent survival rates following standard surgical and radioactive iodine interventions, the clinical management of high-risk variants, recurrent disease, and indeterminate nodules remains a significant challenge. Historically, the evaluation of thyroid nodules has relied on B-mode ultrasonography and fine-needle aspiration biopsy (FNAB). However, spatial and temporal tumor heterogeneity, coupled with the high rate of indeterminate cytology (Bethesda Categories III and IV), often leads to unnecessary diagnostic thyroidectomies. In recent years, liquid biopsy has emerged as a promising diagnostic approach, offering a non-invasive, dynamic, and comprehensive method for disease monitoring. This comprehensive review evaluates the biological mechanisms and clinical utility of circulating tumor DNA (ctDNA), circulating tumor cells (CTCs), extracellular vesicles (EVs), and non-coding RNAs in thyroid oncology. Furthermore, it explores the clinical role of commercial molecular diagnostic panels (e.g., Afirma GSC, ThyroSeq v3) in guiding surgical decisions. This review highlights the diagnostic synergy achieved when these molecular biomarkers are integrated with advanced radiological modalities - including strain elastography, quantitative region-of-interest (ROI) analysis, ACR TI-RADS, and cross-sectional volumetric tracking - as well as nuclear medicine techniques like technetium-99m MIBI scintigraphy. Emerging applications of artificial intelligence and radiomics in image analysis, alongside the concept of minimal residual disease monitoring, are also discussed. Ultimately, we emphasize the need for a multidisciplinary team (MDT) approach in translating these multi-omics and multimodal imaging data into precision medicine, while acknowledging current limitations and charting future directions.

PMID:42725427 | DOI:10.5603/ep.112817

Front Oncol. 2026 Aug 27;16:1919279. doi: 10.3389/fonc.2026.1919279. eCollection 2026.

ABSTRACT

Lung Cancer (LC) continues to be the biggest cause of cancer-related deaths around the world, mostly because of delayed diagnosis. Even if tissue biopsies and circulating tumor DNA (ctDNA) tests have revolutionized clinical management of LC patients, their effectiveness is restricted in settings with lower tumor burden, molecular heterogeneity, and bias in sampling approaches. In this scenario, the epigenetic profiling of cell-free DNA (cfDNA) stands out as a promising, less invasive approach, accurately detect cancer traces. Evidence from stage I-II disease and CT-detected pulmonary nodules supports the diagnostic potential of cfDNA methylation, although further validation in prospective screening cohorts remains necessary. Beyond genomic alterations, cfDNA epigenetic changes, including DNA methylation, chromatin organization, nucleosome positioning, and fragmentation patterns, reflect multi-dimensional complexity of tumor biology. These properties convey both the functional status and the origin of the circulating DNA fragments, accelerating for tumor integrating genomic analysis. Within this group, DNA methylation is the biologically robust and clinically well-established epigenetic marker, as alterations in methylation linked to cancer often occur in the early stages of tumorigenesis and are commonly found across different cancer cell types. Here, we explored the biological and clinical relevance of the epigenetic landscape of cfDNA in LC patients, particularly focusing on DNA methylation-based biomarkers and their evolving applications towards early diagnosis and post-surgical monitoring of minimal residual disease (MRD). We aimed to comprehensively overview analytical approaches for cfDNA methylation analysis, including targeted and genome-wide profiling strategies, and discuss their integration with machine learning (ML) and multi-omics frameworks in order to improve diagnostic performance and clinical applicability in LC management.

PMID:42724581 | PMC:PMC13559918 | DOI:10.3389/fonc.2026.1919279

Front Oncol. 2026 Aug 26;16:1909934. doi: 10.3389/fonc.2026.1909934. eCollection 2026.

ABSTRACT

Circulating tumor DNA (ctDNA), a core component of liquid biopsy, demonstrates significant potential in the field of neoadjuvant therapy for solid tumors. This review systematically examines the role of ctDNA across the pre-, intra-, and post-neoadjuvant treatment phases, with a focus on its value in predicting therapeutic efficacy, assessing early treatment response, detecting minimal residual disease (MRD), and monitoring for recurrence. By synthesizing the latest clinical research data and advancements in molecular detection technologies, this article aims to elucidate how ctDNA is facilitating a shift towards more precise, dynamic, and individualized paradigms in neoadjuvant therapy for solid tumors. Furthermore, it analyzes the current challenges and future directions for integrating ctDNA analysis into clinical practice to optimize patient management and outcomes. Throughout, clinically validated applications are explicitly distinguished from those that remain investigational, and key unresolved questions are highlighted.

PMID:42719676 | PMC:PMC13555526 | DOI:10.3389/fonc.2026.1909934