Hepatocellular carcinoma surveillance relies on ultrasonography and alpha-fetoprotein, both limited in sensitivity for early-stage disease; aberrant methylation of circulating cell-free DNA (cfDNA) offers a promising blood-based approach. Reported here is the analytical validation of MethyLiverDx-Sigma (MLDx-s), an assay that detects methylated RNF135 and DNMT3A in bisulfite-converted plasma cfDNA by methylation-specific PCR with high-resolution melting (HRM), with GAPDH as an endogenous control. Performance was evaluated following CLSI EP05-A3, EP07, EP12-A2, and EP37. Precision of quantification cycle (Cq) and melting peak temperature (Tm) was assessed by variance-component analysis within one site and across two sites and two operators. Because precision studies used bulk bisulfite-converted reference DNA, the reported coefficients of variation (CVs) primarily characterize the PCR-HRM detection module; end-to-end variability in clinical plasma specimens may be higher. Interference and cross-reactivity were evaluated in low-positive and contrived-negative samples against reproducibility-derived limits, with dose-response testing of reactive substances. Detection was 100% at both levels, and every run met control-validity criteria. Cq repeatability CVs ranged from 0.53% to 1.68%, and total reproducibility CVs ranged from 1.10% to 2.37%; all Tm CVs were ≤0.20%. All 18 interferents and 16 microbial cross-reactants evaluated in low-positive samples met the predefined acceptance criteria. In negative samples, hemoglobin, SARS-CoV-2, and measles virus produced concentration-dependent non-specific amplification, and dose-response testing established their respective no-effect concentrations. These findings characterize the analytical precision and multisite reproducibility of the PCR-HRM detection module and the analytical specificity of MLDx-s, complementing its previously reported clinical performance for plasma-based HCC detection.
Background Blood-based biomarkers that complement established serum markers may improve molecular classification of non-small cell lung cancer (NSCLC). We evaluated whether SNORD54 and SNORD41 measured in a serum extracellular vesicle (EV)-enriched fraction provided incremental discrimination beyond carcinoembryonic antigen (CEA) and cytokeratin 19 fragment 21-1 (CYFRA21-1). Methods This single-center case-control biomarker-development study included serum samples from patients with histologically or cytologically confirmed NSCLC and contemporaneous healthy controls. Supporting expression evidence was assessed in paired lung adenocarcinoma and lung squamous cell carcinoma datasets and in 48 paired formalin-fixed, paraffin-embedded NSCLC specimens. Serum analyses included gene-specific cohorts and a common complete-case cohort with SNORD54, SNORD41, CEA, and CYFRA21-1 measurements. Logistic regression models were compared using paired DeLong tests. Model parsimony, adjustment for age, sex, and smoking, locked Stage I–II and Stage I subgroup analyses, U6-normalization sensitivity analyses, and 2000-resample bootstrap internal validation were performed. Results The complete-case cohort comprised 98 patients with NSCLC and 79 healthy controls. Adding SNORD54 to CEA and CYFRA21-1 increased the AUC from 0.851(95% confidence interval [CI], 0.795–0.907) to 0.951 (95% CI, 0.920–0.982; ΔAUC, 0.100; 95% CI, 0.050–0.150; P < 0.001). At the development-derived cutoff, the three-marker model achieved 85.7% sensitivity and 94.9% specificity. SNORD41 did not improve the SNORD54-containing model (ΔAUC, 0.0003; P = 0.480; likelihood-ratio P = 0.953) and increased both Akaike and Bayesian information criteria. With coefficients and the cutoff fixed from the overall cohort, the three-marker model achieved AUCs of 0.904 (95% CI, 0.843-0.964) for Stage I–II disease and 0.882 (95% CI, 0.804-0.960) for Stage I disease. SNORD54 remained informative after adjustment for age, sex, and smoking. The optimism-corrected AUC was 0.948. U6 Ct values differed between diagnostic groups; associations of both snoRNAs with case status persisted in sensitivity models accounting for U6 Ct. Conclusions SNORD54 measured in a serum EV-enriched fraction provided incremental discrimination beyond CEA and CYFRA21-1 in this NSCLC case-control cohort. The parsimonious SNORD54 + CEA + CYFRA21-1 model retained discrimination in locked early-stage subgroup analyses and showed limited apparent optimism after bootstrap correction. Independent validation in cohorts that include benign pulmonary nodules and other relevant lung diseases, together with standardized EV processing and validated RNA normalization, will define the clinical transportability of this three-marker panel.
Background Thyroid cancer (TC) has traditionally been regarded as an indolent malignancy. However, it retains the potential for metastasis and lethality, underscoring its status as a malignant tumor. To explore the interplay between serum metabolite profiles, gut microbial communities, and TC metastasis, we conducted a comprehensive study. Methods Serum metabolites were analyzed using untargeted metabolomics methods to characterize the metabolic changes. Two diet-derived metabolites, creatine (Cr) and α-linolenic acid (ALA), were selected for in vitro validation. Finally, 16S rRNA gene sequencing was used to characterize the intestinal microbial composition and analyze the correlation between differential metabolites and differential intestinal microbiota. Results LC-MS analysis of serum metabolites identified Arginine and proline metabolism and Arginine biosynthesis as the primary metabolic pathways altered in TC metastasis. Both Cr and ALA effectively inhibited EMT, migration, and invasion of TC cell lines, TPC1 and FTC-133. The analysis of gut microbiota composition revealed that Cr and ALA showed significant correlations with the bacteria genera, Porphyromonas and Papillibacter. Conclusions This study highlights that TC metastasis is associated with significant alterations in the serum metabolite profiles of patients, and Cr and ALA play a role in inhibiting TC development. Furthermore, Cr and ALA were correlated with Porphyromonas and Papillibacter, implying their potential link with food-borne components and their connected impact on TC metastasis. The findings provide new insights into the role of metabolites and gut microbiota in TC progression, suggesting novel avenues for dietary intervention in cancer treatment.
BACKGROUND:Tissue-based immunohistochemistry (IHC) for programmed death-ligand 1 (PD-L1) remains the clinical standard for guiding immunotherapy selection in non-small cell lung cancer (NSCLC) but is constrained by intratumoral spatial heterogeneity and procedural sampling risks. Circulating soluble PD-1 (sPD-1) and soluble PD-L1 (sPD-L1) generated either through alternative mRNA splicing or by ADAM10/17-mediated proteolytic shedding offer minimally invasive liquid-biopsy alternatives that capture systemic immune dynamics in real time. METHODS:This review synthesizes clinical and translational data from prospective validation cohorts, surgical trials, and multi-center meta-analyses to evaluate the stage-stratified diagnostic utility, prognostic reliability, and treatment-response predictive value of sPD-1 and sPD-L1 across diverse therapeutic contexts. RESULTS:Cross-sectional baseline assessments show modest standalone diagnostic sensitivity due to significant absolute concentration overlaps between oncological cohorts and healthy controls. However, elevated pre-treatment sPD-L1 functions as a robust independent negative prognostic indicator of overall survival (OS) and a predictor of primary resistance to immune checkpoint inhibitors (ICIs) across advanced stages, while demonstrating no prognostic relevance under conventional cytotoxic chemotherapy. Longitudinally, an acute postoperative sPD-L1 increase of ≥20% at four months marks micro-metastatic persistence and predicts disease recurrence in early-stage surgical cohorts (Odds Ratio = 10.29). Conversely, sPD-1 demonstrates distinct stage-specific volatility; pre-treatment profiles lack stable prognostic indicators, but an early on-treatment plasma surge during anti-PD-1 monotherapy independently maps to prolonged progression-free survival and superior OS (Hazard Ratio = 0.24). Finally, composite liquid biosignatures (e.g., sCombo or joint bsPD-L1/MMP screening) significantly optimize predictive resolution over single-analyte measurements. CONCLUSIONS:Circulating sPD-L1 serves as a reliable negative indicator of therapeutic efficacy and surgical durability, whereas on-treatment tracking of sPD-1 captures protective host T-cell clonal reactivation. Cross-platform assay standardization and predefined cutoff validation remain essential thresholds before these liquid biomarkers can be implemented into standard clinical practice and thoracic surgery. Integrating these circulating checkpoints into high-throughput multi-omics platforms and AI-based analytics is a promising next step toward reproducible predictive signatures that could guide personalized treatment in thoracic oncology.
Background Retinal dystrophies (RD) are a heterogeneous group of genetic disorders leading to progressive vision loss. The notable gap in the genetics of RD is primarily due to unidentified disease genes and variants. Advanced genotyping technologies present significant opportunities for the identification of causative variants, thereby contributing to improved disease management. Methods This study investigates the genetic basis of RD in 12 families from Iran. Comprehensive ophthalmic evaluations were conducted for each participant, including visual acuity testing, slit-lamp examinations, and optical coherence tomography (OCT). Whole exome sequencing (WES) and computer-assisted data analysis were utilized for genotyping and identifying DNA variants. Exome enrichment was achieved using the Illumina TruSeq kit, and sequencing was performed on the Illumina NextSeq500 platform. Bioinformatic analysis involved variant calling and annotation, with stringent filtering based on established criteria. Variants were prioritized according to the American College of Medical Genetics and Genomics (ACMG) guidelines, and pathogenic variants were validated through Sanger sequencing, achieving a 100% concordance rate. Results We identified variants in all the families, including significant pathogenic variants in genes such as EYS. Several novel variants were also discovered, contributing to the expanding genetic landscape of RD. Additionally, variants in syndromic RD genes were identified, emphasizing the need for comprehensive genetic screening. Conclusions Our findings demonstrate the utility of WES in the molecular diagnosis of retinal dystrophies, highlighting the importance of functional validation of newly identified variants. This study contributes valuable insights into the genetic basis of RD. Our findings have the potential to enhance genetic counseling and improve the classification of subtypes in RD.
