Background Central nervous system (CNS) metastases represent a complication in solid tumors and often harbour unique genomic alterations diverging from those in primary tumor tissue or plasma; however, direct sampling of CNS lesions carries procedural risks, limiting its molecular profiling. The main aim of the present analysis was to assess the feasibility of Cerebrospinal Fluid (CSF) ctDNA profiling and to descriptively compare genomic alterations detected in matched tumor tissue, plasma, and CSF samples, including in patients with leptomeningeal metastases (LM). Patients and methods BrainStorm (NCT04109131) is a prospective, international, multicenter study enrolling patients at high risk of developing CNS metastases from different solid tumors. In the present analysis, we evaluated matched samples of tumor tissue, plasma, and CSF ctDNA from patients who developed CNS metastases. Tumor tissue was profiled using the OncoDEEP® 638-gene NGS panel, while matched plasma and CSF ctDNA were sequenced with OncoFOLLOW® tumor-informed panel (plus 50 hotspot genes). Descriptive statistics and Jaccard index-based concordance analyses were performed to compare mutational profiles across compartments. Results CSF ctDNA was detectable in 21 out of the 25 evaluable CSF samples (84%) and in 10 out of 11 patients with LM (91%). Overall concordance among genomic alterations in samples was 52% between tissue and plasma, 45% between tissue and CSF, and 75% between plasma and CSF. In the subset of 11 patients with LM, concordance was 39% (tissue-plasma), 42% (tissue-CSF) and 91% (plasma-CSF). Overall, seven alterations were identified exclusively in CSF (or CSF and tissue) but not in plasma, including variants in TP53, PIK3CA, and ERBB2. Conclusions These preliminary findings indicate that CSF ctDNA can provide a sensitive, compartment-specific molecular portrait of CNS disease, complementing plasma-based analyses, and supporting its integration as a minimally invasive tool to capture the evolving genomic landscape of CNS metastases. Clinical trial registration number NCT04109131
Background High-grade serous tubo-ovarian cancer (HGSOC) frequently presents with malignant ascites, a biologically relevant compartment rich in tumor cells. While circulating tumor cells (CTCs) in peripheral blood (PB) are often scarce, ascitic fluid (AF) may represent a more accessible and abundant source of tumor-derived material. This study evaluated the feasibility of isolating AF-derived CTCs using the CellSearch platform for subsequent molecular characterization. Methods Paired PB and AF samples from 12 HGSOC patients were collected at surgery and analyzed using the CellSearch system. After CTC enumeration, DNA was extracted from CellSearch cartridges containing AF-derived CTC-enriched fractions and subjected to next-generation sequencing (NGS) using a panel clinically validated for solid tumors. Associations between AF-derived CTC burden and clinical variables were explored. Results CTCs were detected in 100% of AF samples and in 50% of PB samples. AF contained markedly higher numbers of CTCs than PB, whereas the latter showed low or undetectable levels. AF-derived CTCs frequently formed multicellular aggregates, potentially leading to underestimation by automated counting. An optimized protocol for DNA extraction from post-processing CellSearch cartridges enabled successful downstream NGS analysis from CTC-enriched AF fractions. Tumor-specific TP53 mutations identified in AF-derived CTC-enriched fractions showed complete concordance with matched tumor tissue in all analyzed cases, supporting the feasibility of using these fractions for molecular characterization of the tumor. No significant associations were observed between AF-derived CTC burden and CA125, PCI, progression-free survival (PFS), or overall survival (OS), although higher CTC levels were associated with a trend toward shorter PFS. Conclusions Compared to PB, AF is a richer source of CTCs in HGSOC. Importantly, AF-derived CellSearch fractions enabled reliable molecular profiling through downstream NGS analysis, suggesting that this approach may be exploited to enrich for tumor-poor peritoneal washings usually considered for staging IC HGSOC. The complete mutational concordance between AF-derived CTCs and matched tumor tissue supports the biological validity of this approach and highlights its potential as a minimally invasive liquid biopsy for tumor characterization and longitudinal disease monitoring in advanced HGSOC.
Background:Large extracellular vesicles (LEVs) are membrane-bound extracellular particles released by tumour cells into body fluids. Circulating LEVs carry tumour-associated biomaterials and are more abundant than circulating tumour cells (CTCs), representing a valuable liquid biopsy analyte. We evaluated the RareCyte® CTC platform's ability to identify LEVs in blood smears and explored associations with clinicopathological features in a metastatic breast cancer (MBC) cohort. Methods:MBC patient samples (N = 72) from a previously published prospective comparison study were retrospectively re-analysed to develop and validate an LEV identification and enumeration workflow. Correlations with CellSearch® tumour-derived extracellular vesicle (tdEV) counts and CTC counts were assessed using Spearman's rho. Between-platform comparisons were performed using Wilcoxon's signed-rank test Associations with overall survival (OS) were assessed using Kaplan-Meier analysis and Cox proportional hazards models. Overall survival was defined as the interval between blood collection and death from any cause. Results:Median LEV count [IQR] was 89 [53-208], with detectable LEVs in patients with low or absent CTC counts. LEV counts positively correlated with matched CTC counts (Spearman's ρ = 0.88, p < 0.001) and CellSearch tdEV counts (Spearman's ρ = 0.80, p < 0.001). Higher LEV counts were associated with significantly shorter overall survival (p = 0.04). RareCyte LEV counts were significantly higher than CellSearch tdEV counts, potentially reflecting methodological differences between enrichment workflows. In Cox analysis, higher LEV counts were associated with shorter OS (HR per 100 LEVs = 1.04, p = 0.0015), and CTCs were also significantly associated with OS. Conclusion:We developed an operational workflow for LEV detection and quantification using the RareCyte® CTC analysis platform. The inclusion of LEVs into CTC-based liquid biopsy analyses may provide complementary biomarker information, particularly in patients with low CTC burden.
Background:Circulating tumor DNA (ctDNA) dynamics have emerged as a promising biomarker of treatment response in oncology drug development. Early decreases in ctDNA levels after treatment initiation are associated with improved long-term outcomes in patients with advanced cancer. To be considered for regulatory decision-making, patient-level meta-analyses evaluating individual-(I-) and trial-(T-) associations between early ctDNA changes and clinical outcomes using randomized controlled trial (RCT) datasets are necessary. Methods:While not fit-for-purpose, the Friends of Cancer Research ctMoniTR Project patient-level dataset included 10 RCTs in advanced cancer that were aggregated. Cox proportional hazards models assessed I-associations between molecular response (MR) and overall survival (OS) or progression-free survival (PFS) using either 90% decrease (MR90) or clearance (MR100) as MR cutoffs. T-associations compared treatment effects on MR with treatment effects on OS or PFS. Results:In pooled analyses across all trials, MR90 and MR100 were significantly associated with improved OS (MR90 adjusted hazard ratio [aHR] = 0.51, 95% CI 0.44-0.59; MR100 aHR = 0.45, 95% CI 0.39-0.53; both p < 0.0001) and improved PFS (MR90 aHR = 0.62, 95% CI 0.54-0.71; MR100 aHR = 0.56, 95% CI 0.48-0.64; both p < 0.0001). Associations were generally consistent across cancer types and treatment modalities. Trial-level associations between MR and OS were weak (R2 ~ 0.08-0.13), whereas associations between MR and PFS were stronger, particularly in aNSCLC (R2 up to 0.74). Conclusions:Early decreases in ctDNA were consistently associated with improved clinical outcomes at the individual-level across advanced cancers. Although trial-level associations were modest, stronger relationships with PFS support continued prospective evaluation of ctDNA dynamics as potential early endpoints in oncology drug development. Additional work using datasets that prospectively included plasma collection for ctDNA analyses is warranted.
Background:An integrated prognostic risk-score (RS) based on prognostic clinical factors and plasma copy number alterations (CNAs) across independent metastatic castration-resistant prostate cancer (mCRPC) cohorts was applied as a classifier to guide development of biomarker-enriched clinical trial designs. Design:Plasma CNAs prognostic for survival were combined into a prognostic score and integrated with clinical prognostic factors to derive an integrated RS in three independent mCRPC cohorts. Biomarker-enrichment trial designs were simulated across a spectrum of enrichment fractions and enrichment thresholds for the RS to consider 1:1 randomization of high RS patients to a study treatment arm or to receive standard treatment, with either a two or a three-year follow-up. The enrichment strategy was applied to improve the trial's ability to detect survival benefit at a Hazard Ratio 0.70; 80% power. Design trade-offs were assessed between the number of "high-risk" patients screened versus enrolled under varying enrichment thresholds and degrees of enrichment of the RS. Results:Pooled mCRPC patients (N = 561) showed RS values from 0.243 to 3.924 and a RS ≥ 1 (60th percentile) was associated with shorter survival. Elastic net models for 2- and 3-year survival were developed. At a threshold ≥1 with 2-year follow-up, a hybrid biomarker-enriched design (50% unselected, 50% high-risk) required screening 768 patients to enroll 219 per arm (n = 438), while maintaining adequate power. Conclusion:An integrated clinico-genomic classifier can guide an mCRPC enrichment strategy by enriching a cohort with 50% short-survival patients balancing sample size and screening needs to achieve adequate power in a biomarker-enriched design.
Although the tumor immune microenvironment has been studied in endometrial cancer, the systemic immune alterations associated with disease progression and their potential prognostic significance remain poorly defined. In this study, peripheral blood immune subsets were characterized by multiparametric flow cytometry in 67 patients with EC and 20 healthy controls, including dendritic cells, MDSCs, T-cell subsets, NK cells, and exhaustion and senescence associated markers. Immune profiles were similar between healthy controls and patients with early-stage disease, whereas advanced tumors showed marked changes, including dendritic cell expansion, reduced CD4+ T-cell proportions, and increased frequencies of CD8+CD27-CD28- and CD8+CD57+ populations. Among clinicopathologic features, MDSC levels were associated with tumor grade and myometrial infiltration, while regulatory T cells were increased in TP53-mutated and microsatellite-stable tumors. In the advanced cohort (n=31), non-responders frequently displayed elevated CD8+, CD8+CD27-CD28-, and CD8+CD57+ levels alongside decreased CD27+CD28+ proportions. In multivariable Cox models, higher baseline CD8+ (HR 1.13), CD8+ CD27-CD28- (HR 1.04), and CD8+CD57+ proportions (HR 1.07; all p<0.05) remained associated with shorter PFS in exploratory multivariable models, whereas higher CD27+CD28+ levels were associated with improved PFS. CD27-CD28- proportions were also linked to worse PFS by Kaplan-Meier analysis (HR 5.1, log-rank p=0.005). Longitudinal analysis (n=28) showed that senescent-like lymphocyte levels remained associated with progression across timepoints, whereas total CD8+ proportions diverged progressively. Together, these findings identify systemic immune remodeling as a characteristic of advanced endometrial cancer and support circulating immune profiling as a source of candidate prognostic markers warranting validation in larger prospective cohorts.
Background Immune checkpoint inhibitors (ICIs), alone or combined with chemotherapy, constitute the standard first-line treatment for advanced non-small cell lung cancer (NSCLC) without actionable oncogenic drivers. However, radiologic response assessment has limitations in capturing early biological treatment effects. Tumor-informed circulating tumor DNA (ctDNA) monitoring has emerged as a promising biomarker for early evaluation of treatment efficacy during immunotherapy. Methods We conducted a prospective, single-center, longitudinal observational study including patients with stage IV NSCLC treated with first-line pembrolizumab with or without platinum-based chemotherapy between December 2021 and December 2024. Personalized, tumor-informed ctDNA assays (Signatera™, Natera, Inc.) were designed from tumor tissue and matched normal blood samples and applied to serial plasma samples collected at baseline (prior to ICI initiation) and every six weeks on-treatment. Early ctDNA dynamics were assessed from baseline to the first on-treatment assessment (six weeks post-treatment initiation) and were correlated with radiologic response assessed by RECIST v1.1, objective response rate (ORR), and progression-free survival (PFS). Results Fifteen patients were enrolled; baseline ctDNA positivity was observed in 13 (87%) patients. Among patients with ctDNA positivity, 11 (85%) experienced a molecular response characterized by ctDNA decrease (n = 1) or clearance (n = 10), while 2 (15%) showed an increase. Early molecular response was strongly associated with radiologic response, with a significantly higher ORR among patients with ctDNA clearance or decrease compared with those with ctDNA increase (91% vs 0%, p = 0.038). Early ctDNA change correlated with percentage change in target lesion size (Spearman R = 0.81, p < 0.001). Longitudinal monitoring demonstrated sustained ctDNA clearance or decrease in patients with durable disease control, while ctDNA positivity preceded radiologic progression. Patient-level survival analysis showed longer progression-free survival intervals predominantly among patients with early ctDNA clearance or decrease. Conclusions Early clearance or decrease in ctDNA levels strongly predicted radiographic response in advanced NSCLC treated with first-line pembrolizumab with or without chemotherapy. ctDNA dynamics may complement radiological assessment and support more personalized, timely, and biologically informed treatment decisions in advanced NSCLC.
Background Avoidable prostate biopsies remain a persistent weakness of prostate specific antigen (PSA)- and imaging-led prostate cancer (PCa) diagnosis. The key need is a non-invasive test that improves pre-biopsy risk stratification while remaining potentially translatable toclinical deployment. We developed and validated an end-to-end liquid-biopsy pipeline linking serum miRNA markers, routine clinical variables, machine learning, and CRISPR/Cas13a-based detection. Methods Candidate miRNAs were prioritized from GSE112264 by differential expression, Logistic Regression, and Least Absolute Shrinkage and Selection Operator analyses, cross-referenced with PCa tissue expression, and measured by qPCR in 712 biopsy-scheduled participants from Sun Yat-sen Memorial Hospital (SYSMH), Houjie Hospital of Dongguan (HHD), and Ganzhou People's Hospital (GPH). A three-miRNA PCa risk score (PCaRS) was trained in SYSMH and tested in internal, external, and prospective cohorts. PCaRS and independent clinical predictors were integrated using six machine-learning algorithms; the optimal model was selected by receiver operator characteristic and DeLong analyses. Finally, serum miRNAs in the prospective SYSMH-Pro cohort were quantified with polydisperse droplet digital CRISPR/Cas13a (PddCas13a) to assess whether a CRISPR/Cas13a readout could support a practical miRNA-based diagnostic workflow. Results Three serum miRNAs (miR-17-3p, miR-504-3p, and miR-6877-5p) were identified as diagnostic markers. PCaRS achieved stable discrimination across the SYSMH Train, SYSMH Test, HHD, and GPH cohorts [AUCs: 0.836 (0.790 - 0.881), 0.832 (0.773 - 0.907), 0.826 (0.721 - 0.932), and 0.820 (0.702 - 0.938), respectively]. PCaRS, f/tPSA, PSA Density, and Prostate Imaging Reporting and Data System score were independent predictors of PCa. Among six machine-learning models, the Support Vector Machine based composite model (PCaSVM) achieved the best performance, with AUCs of 0.939 (0.912 - 0.966), 0.899 (0.849 - 0.948), 0.886 (0.806 - 0.967), and 0.905 (0.834 - 0.976) in the four retrospective cohorts and 0.873 (0.772-0.975) in the prospective cohort. In the prospective cohort, a PddCas13a-derived score (PCaCas13aS) achieved an AUC of 0.831 (0.783 - 0.872), with no significant difference from the qPCR-based PCaRS. Conclusions The PCaSVM achieved satisfactory diagnostic performance, suggesting potential utility for non-invasive diagnosis of PCa. The PddCas13a-based quantitative detection of serum miRNAs presents a feasible approach for diagnosing PCa. Larger prospective multicenter studies are warranted to confirm biopsy-sparing clinical utility.
Background Bone metastases and following skeletal-related events (SREs) are frequent in metastatic breast cancer (MBC) and are a major cause of disability. Circulating tumor cells (CTCs) are prognostic in MBC and are more frequent in patients with bone metastases (BMs). We investigated whether CTCs could be quantitative predictive factors of SREs in this setting. Methods CTC analysis was performed using CellSearch technology within the first month of BM diagnosis and blood samples containing ≥5 CTCs/7.5 mL were considered positive. Patients were then prospectively followed-up until first onset of a SRE or death. Results In 145 BM-MBC patients, mean CTC number was 295/7.5 mL and 60% of patients had ≥5 CTCs. SREs occurred in 82 (57%) patients. After a median follow-up of 105 months, median time-to-SRE (TT-SRE), progression-free survival (PFS) and overall survival (OS) from CTC analysis were 18, 5, and 14 months, respectively. In multivariable analysis, CTCs ≥5 predicted a shorter TT-SRE (median ttSRE 11 vs 31 months, HR 2.08, 95%CI 1.26-3.40, p .004). CTC ≥5 were also an independent predictor of shorter PFS (HR 2.72, 95%CI 1.86-3.95, p < 0.0005) and worse OS (HR 3.16, 95%CI 2.183-4.576, p < 0.0005). Conclusion In this series of MBC patients with BMs and a long follow-up, the detection of CTCs in peripheral blood was not only associated with a worse prognosis in terms of PFS and OS, but was also predictive of an increased risk of skeletal-related events.
Circulating tumor DNA (ctDNA) assays are commonly described by fixed variant allele fraction (VAF)–based limits of detection. However, such metrics overlook a fundamental constraint: the finite number of analyzable DNA molecules in an individual plasma sample. As a result, nominal assay sensitivity may overestimate what is physically achievable in routine clinical specimens. Genome-equivalent (GE) distributions from three independent liquid-biopsy cohorts comprising 5238 plasma samples were integrated with a Poisson-based sampling model to estimate input-limited detectability for single-locus variants. For each sample, the lower limit of detection was defined as the minimum VAF associated with a 95% probability of observing at least 1, 3, 5, or 10 mutant molecules. GE input varied widely (median 5531; interquartile range 2784–13,060). Detection at 1% VAF was theoretically achievable for nearly all samples, but performance declined sharply at lower VAFs and with increasing evidentiary thresholds. At 0.1% VAF, 72% of samples supported detection of at least one mutant molecule, compared with 46%, 35%, and 21% for thresholds of at least 3, 5, and 10 molecules. At 0.01% VAF, fewer than 10% of samples met any detection criterion. These findings indicate that many clinical plasma samples are unlikely to support reliable single-locus detection at very low VAFs, independent of assay design. Sample-aware interpretation of ctDNA results that accounts for molecular input is therefore warranted.
Timely identification of treatment failure during immune checkpoint blockade remains a critical unmet need in oncology. We evaluated a tissue-free, methylation-based circulating tumor DNA (ctDNA) assay applied serially across 142 patients with advanced solid tumors receiving immune checkpoint inhibitor monotherapy or chemo-immunotherapy in two independent prospective cohorts. Blood was collected pre-treatment, C2D1, and C3D1. Molecular progression, mPD, was defined as an increase in ctDNA while on therapy. mPD stratified progression-free and overall survival across both cohorts (PFS HR 5.8 95% CI 3.4-9.9; OS HR 4.1 95%CI 2.3-7.0). Notably, incorporating ctDNA at C2 identified more molecular rebounders, and mPD was significant for OS in RECIST 6-month BOR stable disease subgroup where imaging is least informative (HR 8.4, 95% CI 1.4 to 48.7). Monitoring with ctDNA continued to predict progression after C3 and identified progression with median lead time of 62 days. These findings confirm prior studies that have shown that ctDNA is predictive for immunotherapy response and furthermore demonstrate the utility of a clinically practical molecular progression rule across the multiple cancer types treated by immune checkpoint inhibitors.
Background:Men of African ancestry experience a disproportionate burden of prostate cancer (PCa), with higher incidence and mortality than men of European ancestry. Although social determinants of health, barriers to care, and delayed diagnosis are key contributors to these disparities, ancestry- and context-related differences in sex hormone milieu and PCa-associated laboratory biomarkers remain insufficiently characterized. We investigated sex hormone profiles, PSA molecular forms, and derived hormone-to-biomarker ratios in cancer-free African migrant men living in Italy compared with White controls. Methods:This single-center prospective observational study included 87 cancer-free men: 40 Black men of African origin and 47 White controls. Serum total prostate-specific antigen (PSA), testosterone, estradiol, and the testosterone-to-estradiol ratio were compared between groups. Free PSA, [-2]proPSA, and the Prostate Health Index (PHI) were assessed in the subset of participants with available PSA molecular form measurements. Exploratory hormone-to-biomarker ratios were calculated by relating testosterone, estradiol, and the testosterone-to-estradiol ratio to total PSA, free PSA, [-2]proPSA, and PHI. Results:Total PSA levels did not significantly differ between Black men of African origin and White controls (median 1.22 vs. 1.10 ng/mL; P = 0.407). Testosterone concentrations were also comparable between groups (median 468.48 vs. 412.88 ng/dL; P = 0.362). Conversely, estradiol concentrations were significantly higher in Black men of African origin (median 32.29 vs. 21.53 pg/mL; P < 0.001; q < 0.001), while the testosterone-to-estradiol ratio was significantly lower (median 12.85 vs. 20.20; P < 0.001; q < 0.001). PHI and [-2]proPSA were significantly lower in Black men of African origin than in White controls (PHI: median 27.06 vs. 52.72, P = 0.004, q = 0.012; [-2]proPSA: median 8.90 vs. 23.80 pg/mL, P = 0.008, q = 0.021). Estradiol-to-PSA molecular-form ratios were consistently higher in Black men of African origin, particularly estradiol/free PSA, estradiol/[-2]proPSA, and estradiol/PHI, whereas the (testosterone-to-estradiol ratio)/total PSA was lower. Conclusions:Cancer-free African migrant men living in Italy showed a distinct biochemical phenotype characterized by higher estradiol levels and a lower testosterone-to-estradiol ratio, despite comparable total PSA and testosterone levels. The concomitantly lower PHI and [-2]proPSA values, together with higher estradiol-to-PSA-derived biomarker ratios, suggest that sex hormone balance may influence the context-aware interpretation of PCa biomarkers in this population.
Background:Plasma circulating tumour DNA (ctDNA) analysed using next generation sequencing (NGS) reflects the evolving tumour molecular landscape. However, barriers to routine adoption of NGS ctDNA analysis in clinical settings to detect breast cancer recurrence and therapy selection and monitoring include high costs, the need for highly trained personnel to perform complex workflows and specialised laboratories. DNAe is addressing this with its sample-to-result NGS-based LiDia-SEQ™ platform. This benchtop platform is simple to operate, rapid, fully automated and likely cost-effective. Materials and methods:A clinically relevant panel (DNAe panel) covering 127-point mutations on three key genes - ESR1, PIK3CA and TP53 was designed and optimised with commercially available reference material. Once sufficiently optimised, the panel was validated using 32 clinical samples from metastatic breast cancer patients in a side-by-side comparison with the Oncomine™ Breast cfDNA Assay. Results from the Oncomine assay were analysed with the Oncomine standard pipeline while results from the DNAe panel were analysed using DNAe's custom bioinformatics pipeline. Results:Out of the 32 clinical samples tested with the two panels, 12 samples had no mutations, and 20 samples contained mutations. Fifteen samples had mutations detected by both panels and five had a single mutation detected by one or the other panel. Conclusion:Using clinical samples, we show that the DNAe panel with analysis using DNAe's pipeline detects mutations comparably to the commercial Oncomine-Assay. This paves the way for development of the DNAe panel into a test for the LiDia-SEQ platform.
Liquid biopsy has emerged as a powerful approach for tracking tumor dynamics through circulating biomarkers such as cell-free tumor DNA (ctDNA), circulating tumor cells (CTCs), extracellular vesicles (EVs), microRNAs (miRNAs) and soluble proteins. Unlike tissue biopsy, which captures only a single tumor region at one moment, liquid biopsy enables repeated, minimally invasive sampling that reflects the molecular state of disease across all lesions. However, current detection methods based on next-generation sequencing and digital PCR require centralized laboratories, specialized personnel, and turnaround times of days to weeks. Electrochemical biosensors offer a fundamentally different path: compact, low-cost platforms that convert biorecognition events into electrical signals within minutes. This review examines the major electrochemical transduction modes and their compatibility with circulating biomarker classes, maps existing sensor platforms to the phases of cancer care from early detection through treatment monitoring and recurrence surveillance, and addresses the practical requirements for clinical implementation. Despite impressive analytical performance under controlled conditions, most electrochemical sensors have not progressed beyond proof-of-concept. Bridging this translational gap will require robust function in complex biological matrices, rigorous analytical and clinical validation, regulatory approval, and reproducible manufacturing. Meeting these challenges could position electrochemical biosensing as an accessible complement to existing molecular diagnostics in oncology.
Aims in the genomic era, the advent of next generation sequencing (NGS) technologies has rapidly transformed the clinical paradigm of NSCLC patients who could benefit from a wide series of clinically approved biomarker driven therapies. Among them, KRAS p.G12C hotspot mutation became part of the mandatory testing gene panel by electing NSCLC patients to sotorasib. Epigenomic signatures, including hypermethylation of CpGs islands, may be relevant in tailoring therapeutic algorithms in oncogene addicted NSCLC patients. Here we aimed to dynamically track KRAS p.G12C genomic variations by integrating methylation profile in a longitudinal series of n=91 liquid biopsy samples from n=22 p.G12C positive NSCLC patients treated with sotorasib. A combined NGS panel (Avida Duo Methyl Reagent Kit, Avida Biomed) simultaneously evaluating n=105 cancer-related genes and calculating methylation index (MI) score among 3400 differentially methylated regions (DMRs) was adopted, correlating molecular data with clinical outcomes. Overall, exon 2 p.G12C KRAS mutation was detected in 40.9%, 15.8% and 70.6% baseline, T1 and TP samples, respectively. MI was successfully measured in all instances. Of note, exon 2 p.G12C KRAS mutation and MI score highlighted a trend simultaneously moving forward T1 point (r = 0.68, p = 0.06) and TP (r = 0.87, p = 0.000103). Methylation signature may be combined with genomic analysis to personalize therapeutic strategies for KRAS p.G12C mutated NSCLC patients. “Multiomic” analysis of tumor-informative molecular targets (genomic profile, methylation status) lay the basis for dynamic fingerprints of NSCLC patients preventing early relapses and augmenting clinical benefits of targeted therapies.
Background:Radiomics and liquid biopsy represent minimally invasive approaches to assess disease characteristics in solid tumors. We integrated computed tomography (CT) radiomics and circulating tumor DNA (ctDNA) analysis to enhance prognostic stratification and longitudinal monitoring in patients with advanced non-small cell lung cancer (NSCLC). Methods:This study prospectively enrolled 91 patients with advanced NSCLC. Baseline molecular profiling was performed on both tumor tissue and plasma ctDNA using targeted next-generation sequencing. Radiomic features were extracted from baseline CT lung lesions using PyRadiomics, and radiomic scores (RS) were developed using LASSO-regularized Cox models. A subgroup of 21 patients with actionable molecular alterations underwent longitudinal CT scans and liquid biopsies during targeted therapy. Clinical, radiomic, and molecular associations with overall survival (OS) and disease-free survival (DFS) were evaluated using log-rank tests and included in multivariable models. Results:Overall concordance between tissue and ctDNA (n = 67 patients) was 85%. In the combined clinical-radiomic-genetic model (C-index: 0.73), the RS (p < 0.001) and the presence of actionable alterations (p = 0.041) were independent OS predictors. For DFS, the integrated model achieved a cross-validated C-index of 0.77, outperforming the clinical-only model (0.59). In patients with EGFR-mutant NSCLC, detectable baseline ctDNA was significantly associated with a higher risk of disease progression (p = 0.018). In this subgroup, the combined clinical-radiogenomic model achieved a cross-validated C-index of 0.80 for DFS. Longitudinal analysis showed that 17 of 21 patients achieved molecular clearance of ctDNA at the first follow-up, correlating with treatment response. Conclusions:Integrating radiomics with liquid biopsy provides a more robust prognostic assessment of advanced NSCLC than clinical or molecular data alone. This multi-modal approach may offer a minimally invasive strategy for personalized risk stratification and monitoring of treatment response in patients with NSCLC.Clinicaltrials.gov identifier: NCT06331975.
The most common ocular neoplasia among children is retinoblastoma. Currently, the diagnosis of this disease is essentially clinical, taking a biopsy is contraindicated owing to the high risk of causing metastasis. Therefore, it is imperative the development of a method to diagnose this disease through a non-invasive fashion. We choose tears as they fulfill the former precept. Through proteomic analysis we observed 52 up regulated and 48 down regulated proteins among retinoblastoma cases as compared to healthy children. Among these proteins, we identified several previously associated with retinoblastoma such as apolipoprotein A-1 (APOA1). We confirmed up regulation of APOA1 and S100 binding calcium A9 (S100A9) which revealed faithful concordance to the predicted values from mass spectrometry.
Purpose:National Comprehensive Cancer Network (NCCN) Central Nervous System (CNS) Guidelines recommend utilizing next-generation sequencing (NGS) to enable comprehensive genomic profiling (CGP) as standard of care for molecular characterization of CNS malignancies. The restrictive nature of the blood-brain barrier (BBB) makes plasma-based liquid biopsy an ineffective alternative, however cerebrospinal fluid (CSF)-based liquid biopsy offers a minimally invasive alternative for genomic assessment. This study aimed to evaluate the clinician perspective of clinical utility of Belay's CSF-based genomic assay, Summit™ 2.0, and to assess how clinicians use test results in routine clinical practice. Methods:Clinical utility was assessed using clinician-reported survey responses from cases where Summit™ 2.0 testing was ordered for patients with known or suspected CNS disease. Survey questions evaluated indications for testing, test positivity, impact on clinical decision-making, report clarity, and perceived overall utility. Results:The survey response rate was 52% (95 surveys sent). Among 49 surveyed cases, 74% yielded positive genomic findings. Clinicians most frequently ordered testing to address diagnostic uncertainty or inform clinical management, with treatment selection as a less frequent primary indication. Clinical utility was reported in 86% of cases including those with negative findings, of which some results were useful for confirming existing diagnoses or management strategies. Clinicians also reported high confidence in the clarity and usability of test reports. Conclusion:Clinician-reported outcomes indicate that Summit™ 2.0 CSF-based genomic testing influenced clinical decision-making, including treatment selection, diagnostic clarification, confirmation of expected diagnoses, and care planning and provides meaningful information that supports diagnostic evaluation and management of CNS tumors.
Gastric cancer remains one of the leading causes of cancer-related mortality worldwide, largely due to its late-stage diagnosis. Liquid biopsy has emerged as a promising, minimally invasive method for early cancer detection, leveraging circulating biomarkers such as nucleic acids, extracellular vesicles, and tumor cells. Objective This systematic review aimed to evaluate the emerging role of liquid biopsy as a diagnostic tool for the early detection of primary gastric cancer, focusing on the past five years of published research. Methods Following PRISMA guidelines and based on the PICO framework, a comprehensive literature search was conducted across PubMed and Scopus databases, yielding 620 articles. After screening and eligibility assessment, 16 studies were included. Quality evaluation was performed using the QUADAS-2 tool and Analytical Validation Summaries. Results The included studies demonstrated consistently high diagnostic performance of various liquid biopsy-derived biomarkers. Notably, circulating non-coding RNAs-particularly miRNAs, circRNAs, lncRNAs, and tsRNAs-showed high sensitivity and specificity in early-stage gastric cancer detection. DNA methylation signatures, cfDNA fragmentomics, lipidomic profiles, and folate receptor-positive CTCs, also emerged as valuable diagnostic modalities. Most studies reported area under the curve (AUC) values exceeding 0.85, with several outperforming conventional serum markers, such as CEA and CA19-9. Conclusions Liquid biopsy holds significant promise as a non-invasive, accurate diagnostic approach for early gastric cancer. RNA-based and cfDNA-based biomarkers, in particular, exhibit strong potential for integration into routine screening protocols. Further large-scale, prospective validation studies are warranted to support clinical translation and standardization.
Liquid biopsy (LB) has emerged as a minimally invasive approach to characterize tumor biology and support treatment decision-making across gastrointestinal (GI) malignancies. Advances in circulating biomarkers have expanded its potential clinical applications. While colorectal cancer appears closest to clinical implementation, with ctDNA increasingly integrated into adjuvant and metastatic decision-making, applications in other GI tumors remain largely exploratory. Emerging approaches, including cfDNA methylation profiling, multi-omic assays, and circulating protein or metabolite analyses, have shown promising early signals but require prospective validation. This review summarizes key LB findings presented at ESMO 2025, highlighting translational relevance, current limitations, and future directions for clinical integration.
