The Journal of Molecular Diagnostics

BackgroundColorectal cancer (CRC) is a leading cause of cancer mortality. While early detection improves outcomes, current non-invasive tests often lack sensitivity for early-stage CRC and advanced precancerous lesions (APL). Stool-based host messenger RNA (mRNA) biomarkers offer a promising approach, though the most clinically useful candidates remain undefined. MethodsWe screened for mRNA biomarkers by first using bioinformatic analysis of tissue RNA-seq datasets to identify candidate genes with strong and ubiquitous differential expression in CRC versus normal tissues. The top 135 computationally predicted biomarkers were evaluated using "gold standard" RT-PCR on clinical stool samples across two independent cohorts. ResultsSeveral biomarkers, including PPBP, MYC, MMP7, and TGFBI, exhibited strong predictive power. Integrating top-performing markers through machine learning yielded an AUC of 0.98 for CRC and 0.76 for APL detection. The optimized panel demonstrated 98% sensitivity for CRC and 50% for APL, with a specificity of 90%. ConclusionsThis study derives a high-performance mRNA-based stool test for non-invasive CRC screening. Our findings demonstrate that a multi-marker panel achieves exceptional sensitivity and good specificity, providing a viable tool for clinical diagnostics.

One of the current workhorses of next-generation sequencing in clinical molecular diagnostics laboratories for profiling somatic mutations in tumours are amplicon-based targeted sequencing panels. Many open-source somatic variant callers are available; however, their use in clinical applications remains under explored. Therefore, we integrated outputs of six variant callers (FreeBayes, MuTect2, Pisces, Platypus, VarDict and VarScan) into a Snakemake pipeline and evaluated tumour-only data from the HD789 commercial reference standard sequenced in triplicate on three different sequencing runs using the Illumina AmpliSeq Focus panel on MiSeq and NextSeq 2000. A 1:4 dilution sample was sequenced for evaluating limits of variant detection. The called variants were analysed along depth, allele frequency, and other sequencing metrics. The variant callers were evaluated by their level of concordance and performance on known somatic variants. FreeBayes consistently called the largest number of somatic variants in each sample but also included more potential artifacts. Overall, FreeBayes, VarScan, MuTect2, and Pisces had the best performance on HD789 data.

Background: Classification of central nervous system (CNS) tumors has become increasingly complex, raising concerns about the sustainability of comprehensive molecular diagnostics. We have evaluated nanopore whole genome sequencing (nWGS) as a single workflow to replace multiple diagnostic assays. Methods: We performed nWGS on DNA extracted from 90 adult CNS tumor samples (58 retrospective, 32 prospective) and compared the results to findings from standard of care (SoC) diagnostic work-up. Analysis was done through an automated workflow that consolidated diagnostically and therapeutically relevant genomic alterations, including copy-number variation, structural, and single-nucleotide variants, chromosomal aberrations, gene fusions, and methylation-based classification. Results: nWGS supported final diagnostic classification in all samples with >15% tumor cell content, requiring ~3 hours of hands-on library preparation, parallel sample processing, and sequencing times within 72 hours. Methylation-based classification was available within 1 hour and was concordant with the integrated final diagnosis in 89% of cases (80/90). All diagnostically relevant copy-number variations, single-nucleotide variants, and gene fusions were concordant with SoC testing. MGMT promoter methylation status matched in 94% of cases. In addition, nWGS identified prognostic and potentially actionable variants that were not reported or covered by SoC. Conclusions: nWGS delivers comprehensive genetic and epigenetic results with a fast turn-around compared to standard methods. This enables efficient, accurate, and scalable molecular diagnostics of CNS tumors using a single platform. This data supports its implementation in routine clinical practice and may be extended to other cancer types requiring complex genomic profiling.

Accurate detection of RNA splice variants is often hindered when transcripts lack large distinguishable exonic regions, making conventional PCR strategies challenging. We developed a simple melting temperature (Tm)-guided exon-exon junction (EEJ) RT-PCR method to enable variant-specific detection under these conditions. Uni-directional primers spanning exon-exon junctions were designed so that approximately each half anneals to adjacent exons. The Tm of each half-site was set >7{degrees}C below the annealing temperature, preventing stable binding to individual exons and enforcing junction-dependent amplification. The method was evaluated using HTRA1-AS1 long noncoding RNA variants that share overlapping exon sequences but differ in splice connectivity. HTRA1-AS1 comprises five variants, only one with a large distinguishable exon. Tm-guided EEJ primers robustly discriminated the remaining four variants. After optimization, amplification yielded sharp, single bands with minimal cross-reactivity. Compared with conventional designs, this approach reduced heteroduplex and heteroquadruplex formation, improving band clarity. Sanger sequencing confirmed junction specificity, and the method performed well in multiplex settings. Overall, Tm-guided EEJ RT-PCR is a cost-effective, high-resolution approach for detecting RNA variants lacking easily distinguishable exonic regions, readily compatible with standard RT-PCR and qPCR workflows.

BackgroundWe previously developed a benchmarking strategy using mixtures of homozygote and heterozygote DNAs as reference standards to simultaneously assess sensitivity and false positive (FP) error rates in targeted next-generation sequencing (T-NGS) and whole-exome sequencing (WES), revealing substantial variability across commercial platforms. However, optimal analytic conditions for clinical application remain undefined. MethodsWe systematically evaluated multiple sequencing kits and bioinformatics pipelines across various variant allele fraction (VAF) thresholds to identify conditions that maximize both sensitivity and specificity. Recurrent error-prone alleles were defined and filtered to enhance specificity. ResultsOptimal performance was achieved using the DRAGEN pipeline with recurrent FP allele filtering. For T-NGS, a 1% VAF cutoff yielded a 95% detection threshold of 2.99% and 1.21 FPs per megabase (FP/Mb); for WES, a 2% cutoff yielded a 95% threshold of 5.02% and 1.15 FP/Mb. These settings improved sensitivity >3-fold and reduced FP rates >96% versus suboptimal pipelines. Notably, VAF thresholds flattened sensitivity differences across platforms, obscuring key performance disparities--challenging assumptions that T-NGS is inherently more sensitive than WES. In-house and conventional pipelines undercalled up to 10% of true variants. Restricting reporting of 1-4% VAF variants to [~]1,000 predefined actionable sites enabled recovery of clinically relevant mutations while reducing FP risk >99%. ConclusionsThis study provides a quantitative framework for optimizing NGS performance. Our findings support actionable strategies to improve diagnostic accuracy in clinical genomics through tailored pipeline selection, VAF thresholding, and artifact filtering.

Whole-genome sequencing (WGS) enables comprehensive analysis of tumour genomes, but its use in formalin-fixed paraffin-embedded (FFPE) samples is limited by DNA fragmentation and low yields. Whole-genome amplification (WGA) methods such as multiple displacement amplification (MDA) can boost DNA availability but distort copy-number alteration (CNA) profiles. DNA ligation-mediated MDA (DLMDA) mitigates this bias by reconstituting fragmented templates, yet its performance in FFPE-derived DNA remains uncertain. We compared paired DLMDA pre-amplified (2h, 8h) and non-pre-amplified FFPE prostate tumour samples from 22 archival blocks (5, 15 and 20 years old). DLMDA increased DNA yield by 42- to 86-fold, with global CNA patterns largely preserved. However, DLMDA significantly reduced the number of detected CNA deletions and amplifications. These effects were independent of both block age and reaction time. CNA dropouts were randomly distributed across the genome, indicating that DLMDA does not introduce regional bias. Our results show that DLMDA enables robust DNA yield recovery and avoids false-positive CNA artefacts, but at the cost of reduced CNA sensitivity. While suitable for CNA screening pipelines through WGS, further improvements are required to minimise the false-negative risk and improve the techniques sensitivity for FFPE-based genomics.

PurposeDiagnostic yield from exome and genome sequencing varies widely across studies. It remains unclear how much of this variation reflects patient-level factors (e.g., sex, clinical features, race/ethnicity, genetic ancestry) versus site-level practices such as sequencing modality or variant interpretation workflows. We aimed to quantify the contributions of these factors to diagnostic outcomes across five U.S. clinical sequencing sites. MethodsWe performed a cross-sectional analysis of 3,008 prenatal, neonatal, and pediatric cases from the NHGRI Clinical Sequencing Evidence-Generating Research (CSER) consortium (2017-2023). Clinical indications spanned neurodevelopmental, neurological, immunological, metabolic, craniofacial, skeletal, cardiac, prenatal, and oncologic presentations. Genetic ancestry was inferred from sequencing data, and variants were interpreted using ACMG/AMP guidelines to classify DNA-based diagnoses. Generalized linear mixed models were used to estimate associations between diagnostic yield and fixed effects (sex, prenatal status, isolated cancer, number of clinical indications, sequencing modality, race/ethnicity, and genetic ancestry), while modeling study site as a random effect to quantify between-site variation. ResultsThe overall diagnostic yield was 19.0%. Multiple clinical indications (OR=1.47, 95% CI 1.20-1.80, p<0.001) were associated with higher diagnostic yield, and male sex (OR=0.80, 95% CI 0.66-0.96, p=0.017) and prenatal status (OR=0.63, 95% CI 0.44-0.90, p=0.012) were associated with lower yield. Sequencing modality, race/ethnicity, genetic ancestry, and isolated cancer were not statistically significantly associated with diagnostic outcomes.. A model without fixed effects attributed [~]10% of variance in diagnostic yield to between-site differences. After adjusting for covariates, site-level variance decreased to 5.7%, indicating consistent variation across sites not explained by measured patient factors. ConclusionAcross five sites, patient-level clinical features influenced diagnostic yield, but substantial site-level variation remained even after adjustment. Differences in variant interpretation, or case-classification practices may contribute to this residual variability. Further efforts to increase consistency in exome- and genome-sequencing diagnostic workflows may help reduce inter-site differences.

ObjectiveTo evaluate the analytical and clinical performance of fetal fraction (FF) enriched genome-wide noninvasive prenatal testing (GW-NIPT) for detection of clinically relevant copy number variants (CNVs) down to 1 Mb. MethodsWe retrospectively analyzed 10,501 singleton pregnancies tested with FF enrichment-based GW-NIPT between August 2023 and July 2025. CNV analysis was performed using BinDel and WisecondorX. ResultsFF enrichment increased median FF to 24% (2.4-fold increase). Clinically relevant CNVs, including microdeletions and microduplications, were reliably detected down to 1 Mb. Performance was robust across all maternal body mass index (BMI) categories. The retest rate was 0.95%, resulting in a final no-call rate of 0.03% with no BMI-attributable failures. The workflow demonstrated high sensitivity, specificity, and positive predictive value for common aneuploidies, rare autosomal trisomies, sex chromosome aneuploidies, subchromosomal CNVs, and pathogenic mitochondrial DNA variants. ConclusionsFF enrichment enhances the analytical resolution of first-trimester GW-NIPT, enabling reliable detection of subchromosomal CNVs down to 1 Mb across diverse patient populations. This approach broadens the scope of prenatal screening while maintaining low test failure rates. All positive findings require confirmatory diagnostic testing and appropriate genetic counseling.

Latent tuberculosis infection (LTBI) remains a significant barrier to global TB control and elimination efforts. The QuantiFERON-TB Gold (QFT) assay is commonly used for the diagnosis of LTBI. However, blood collected in QFT tubes is seldom utilized for molecular and genetic analysis due to the presence of heparin and a dense gel barrier that hinders efficient DNA extraction. To address this limitation, we aimed to develop a method for directly isolating high-quality DNA from blood in QFT tubes, eliminating the need for additional blood sampling and enabling their use in both diagnostic and molecular workflows. In this study, DNA was extracted from blood in EDTA and QFT tubes using a hybrid approach that combined manual lysis with three commercial kits: Thermo Scientific GeneJET, QIAamp DNA Blood Kit, and FavorPrep Blood Genomic DNA Extraction Kit. DNA concentration and purity were measured with a Multiskan SkyHigh Microplate Spectrophotometer, while integrity was assessed through agarose gel electrophoresis. Two nucleic acid amplification techniques (NAATs), ARMS-PCR and whole exome sequencing (WES) were performed to validate applicability of extracted DNA for molecular biology applications. We did not find any differences in the quantity, quality, or application of PCR or sequencing for DNA extracted from EDTA or QFT tubes. The extracted DNA from both EDTA and QFT tubes exhibited A260/280 ratios of 1.7-1.9 and concentrations ranging from 4.9 to 118.5 {micro}g/mL, indicating an adequate yield and purity. Intact genomic DNA and PCR product bands on agarose gel indicated suitability for downstream applications. Additionally, WES produced 6.47-8.71 GB of data per sample, with 42.8-57.7 M reads and GC content between 49.29% and 52.54%. Sequencing metrics were consistently strong, with Q20 values exceeding 98.6% and Q30 values above 95%. Our study presents an optimized and reproducible protocol for extracting high-quality DNA from QFT tubes, producing DNA suitable for both PCR and sequencing technologies. This protocol provides a cost-effective and practical strategy to integrate LTBI diagnosis with genomic research, particularly beneficial in resource-limited settings. This study introduces a novel analytical workflow applicable to diagnostic laboratory settings, enabling the integration of routine LTBI immunodiagnostic testing with downstream genomic analysis. The approach supports improved utilization of clinical specimens in laboratory medicine and may facilitate future biomarker and precision diagnostics research.

1The T2T-CHM13v2.0 reference genome added previously uncharacterized genomic sequences and improved the accuracy of repetitive stretches compared to former human genome assemblies. By comprehensive allelic variation analysis and read mapping statistics from sequencing reads aligned to hg38 and T2T-CHM13 assemblies in samples encompassing different sequencing designs and ethnicity groups, we observed that T2T-CHM13v2.0 assembly significantly reduces the reference mapping bias (RMB) and increases read mapping precision at clinically relevant sites, including BRCA1 pathogenic variants. Further, we report the presence of sequence dissimilarities among reference genomes in the proximity of ClinVar annotated variants, suggesting the need for data re-analysis and potential redesign of probes targeting clinically relevant regions. Overall, these findings support the implementation of T2T-CHM13 reference for the improvement of sequencing data analyses in the clinical genomic setting.

BackgroundDistinguishing benign proliferative nodules (PNs) from melanoma arising within congenital melanocytic nevi remains a major diagnostic challenge. Copy number alteration (CNA) analysis is widely used to support classification, but current criteria were developed using array comparative genomic hybridization (aCGH). The performance of alternative platforms such as shallow whole-genome sequencing (sWGS) and methylation arrays in this setting is poorly defined. ObjectivesThe objective of this study is to compare CNA profiles obtained from aCGH, sWGS, and methylation arrays in atypical nodules arising within congenital nevi, and to correlate these molecular findings with clinical outcomes. MethodsSixteen samples from fourteen patients were retrospectively analyzed using all three platforms. CNAs were cataloged, concordance across methods was quantified using the Jaccard index, and molecular classifications were compared. Clinical follow-up was reviewed to provide clinical context. ResultsaCGH detected 39 CNAs, sWGS 60, and methylation profiling 66. Concordance was highest between sWGS and methylation (mean Jaccard 0.67), followed by aCGH versus sWGS (0.64) and aCGH versus methylation (0.49). Cases with high aneuploidy demonstrated strong cross-platform agreement, whereas low-burden lesions exhibited greater variability between methods. Divergent molecular classifications were observed in six cases. ConclusionsWhile all methods reliably detect broad chromosomal changes, sWGS and methylation arrays identify many additional focal CNAs that may not align with CGH-based diagnostic criteria. Until platform-specific thresholds are established, aCGH remains the most conservative and clinically validated approach for evaluating proliferative nodules in congenital nevi. SIGNIFICANCEAccurate molecular classification of melanocytic proliferations in congenital nevi is essential but challenging, particularly in patients with multiple proliferative nodules. This study provides the first systematic comparison of aCGH, sWGS, and methylation-based CNA profiling in this setting. We show that higher-resolution platforms detect substantially more focal aberrations, which can lead to discordant and potentially overcalled malignancy assessments when applying CGH-derived criteria. Our findings highlight the need for platform-adapted diagnostic frameworks and support continued use of CGH as the most conservative and clinically validated method for risk stratification. GRAPHICAL ABSTRACT O_FIG O_LINKSMALLFIG WIDTH=118 HEIGHT=200 SRC="FIGDIR/small/26347388v1_ufig1.gif" ALT="Figure 1"> View larger version (27K): org.highwire.dtl.DTLVardef@1d7b155org.highwire.dtl.DTLVardef@1bb7081org.highwire.dtl.DTLVardef@d72e3forg.highwire.dtl.DTLVardef@11d3f0b_HPS_FORMAT_FIGEXP M_FIG C_FIG

PurposeAntibodies to Epstein-Barr virus (EBV) proteins can predict nasopharyngeal carcinoma (NPC) risk. We previously defined a prototype EBNA1 protein panel and multiplex immunoblot assay that distinguishes NPC risk several years pre-diagnosis. Assay throughput and specificity are critical to effectively implement a population-level screening program. Here, we developed a strip test assay - EBNA1 SeroStrip-HT - with an objective to increase throughput and maximize specificity. Experimental DesignEBNA1 full-length (FL) and glycine-alanine repeat deletion mutants (dGAr) were purified from insect and mammalian cells to screen serum IgA/IgG from prospective cohorts in Singapore and Shanghai, China, with known time intervals to NPC diagnosis. Twenty pre-diagnostic sera within 4 years to diagnosis were compared to 96 healthy controls using a nested case-control study design. ResultsIgA to mammalian-derived EBNA1 dGAr achieved 85.0% sensitivity and 94.8% specificity (AUC, 0.939) for NPC status. IgA to insect-derived EBNA1 dGAr showed the same sensitivity (85.0%) and similar specificity (93.8%) (AUC, 0.941). IgA to insect-derived EBNA1 FL had a higher 90% sensitivity, but lower 91.7% specificity (AUC, 0.940). Combining EBNA1 FL and dGAr results showed that subjects positive for both proteins had a 243.67 odds ratio for NPC incidence compared to double-negative scores. ConclusionThis study demonstrated the efficacy of EBNA1 SeroStrip-HT for NPC risk assessment and stratification in high- and intermediate-risk populations, yielding high accuracy and a 12-fold increased throughput over the prototype. The insect system was appropriate for large-scale production of purified EBNA1. Larger, geographically diverse cohorts are warranted to confirm these results, especially in low-incidence populations.

Plasma cell-free DNA (cfDNA) is a central analyte in liquid biopsy applications spanning prenatal testing, oncology, and epigenomic profiling. To minimize contamination by high-molecular-weight genomic DNA (gDNA) released from nucleated blood cells, standard pre-analytical workflows typically mandate a double-centrifugation protocol prior to cfDNA extraction. This requirement has limited the use of many existing plasma biorepositories that were prepared using only a single low-speed centrifugation step. In this study, we evaluated whether single-spun plasma is sufficient for accurate cfDNA analysis when samples are processed under controlled conditions. Using paired single- and double-spun plasma aliquots derived from the same early-pregnancy maternal blood samples collected in EDTA tubes, we performed whole-genome DNA methylation sequencing and assessed cfDNA integrity across multiple orthogonal dimensions. These included cell-type proportion deconvolution using large and small DNA methylation reference signatures, CpG-level methylation rate estimation with explicit variance modeling, beta-binomial-corrected correlation analyses across libraries, cfDNA fragment length profiling, and genotype-based fetal fraction estimation. Across all analyses, we found no evidence that a second high-speed centrifugation step improved accuracy, reduced technical variability, or enhanced analytical fidelity. Cell-type proportion estimates and CpG-level methylation rates were statistically indistinguishable between single- and double-spun plasma, fragment length distributions were nearly identical, and fetal fraction estimates showed near-perfect concordance. Together, these results demonstrate that a single low-speed centrifugation step is sufficient for high-fidelity cfDNA methylation, fragmentomic, and genotyping analyses. Our findings support the expanded use of legacy single-spun plasma collections for liquid biopsy research and assay development and motivate a re-evaluation of rigid double-centrifugation requirements in cfDNA workflows.

Copy number variants (CNV) contribute significantly to the pathogenic variation associated with developmental disorders. CNV detection is often not included in standard exome sequencing (ES) analysis. Complementary methods such as chromosomal microarray are typically offered in diagnostic laboratories to diagnose pathogenic CNV. In this study, we aimed to develop an optimal approach for incorporating CNV detection within our ES analysis process for the Deciphering Developmental Disorders in Africa (DDD-Africa) cohort. We analyzed ES data from 505 probands with a developmental disorder, applying a CNV detection approach that assessed data generated using the tools CANOES and XHMM. When available, parental ES data was used to assess inheritance patterns. We confirmed a diagnosis in 42/505 (8,3%) patients with 44 pathogenic CNV identified in the probands. There were 31 deletions and 13 duplications. Among the 27 probands with parental data, all identified CNV were de novo. The addition of CNV analysis to our ES analysis pipeline resulted in an 8.3% increase in diagnostic yield in the DDD-Africa cohort without additional laboratory cost. This approach offers a feasible approach which is likely to reduce analytical cost and is suitable for low- and middle-income countries where funding and resources for genomic medicine initiatives are limited.

T-cell lymphomas are often histologically indistinguishable from benign T-cell infiltrates. Clonality testing is frequently required for diagnosis. It lacks the spatial context and is slow and expensive, relying on complex, multiplexed PCR reactions, interpreted by experienced scientists or pathologists. We previously published details of a pair of highly specific monoclonal antibodies against the two alternatively used, but very similar, T-cell receptor {beta} constant regions, TCR{beta}1 and TCR{beta}2. We demonstrated the feasibility of immunohistochemical detection of TCR{beta}1 and TCR{beta}2 in formalin-fixed, paraffin-embedded (FFPE) tissue as a novel diagnostic strategy for T-cell lymphomas. Here we validate an improved pairing of TCR{beta}1/2 rabbit monoclonal antibodies, and demonstrate their utility for single and double immunostaining, including with a chimeric mouse anti-TCR{beta}2 antibody. Finally, we show that this staining is amenable to automated cell counting, permitting accurate calculation of the TCR{beta}2:TCR{beta}1 ratio.

Although several ancillary tests are available in limited laboratories, diagnosis of microphthalmia (MiT)/TFE family translocation renal cell carcinoma (tRCC) could be challenging due to diverse and overlapping tumor morphology and the lack of reliable biomarkers. GPNMB has been recently identified as a diagnostic marker for various renal neoplasms with FLCN/TSC/mTOR-TFE alterations. However, the sensitivity and specificity of GPNMB immunostain are suboptimal and the result interpretation in ambiguous cases could be difficult. To search additional biomarkers that could improve the screening sensitivity and predict genetic aberrations in FLCN/TSC/mTOR-TFE pathway in renal tumors, we performed bioinformatic analysis of publicly available cancer databases and found GPR143, a transmembrane protein regulated by MiT transcription factors, was highly expressed in a subset of renal cell carcinomas (RCCs). In two the Cancer Genome Atlas (TCGA) kidney cancer cohorts, RCCs with high levels of GPR143 expression were enriched for renal neoplasms with FLCN/TSC/mTOR-TFE alterations. Similar to GPNMB labeling, GPR143 immunostain was positive in the majority of tRCC cases and renal tumors with FLCN/TSC/mTOR alterations, suggesting that GPR143 could function as another surrogate marker for FLCN/TSC/mTOR-TFE alterations in certain renal tumors. Interestingly, despite the concordant GPR143 and GPNMB immunoreactivity in most renal neoplasms with FLCN/TSC/mTOR-TFE alterations, diffuse GPR143 immunostain was observed in some cases with negative or focal GPNMB labeling. Taken together, our results indicate GPR143 could serve as a useful adjunct marker to improve the sensitivity for screening renal tumors with FLCN/TSC/mTOR-TFE alterations.

BackgroundCirculating tumor DNA (ctDNA) detection after curative-intent surgery is being used to identify minimal residual disease (MRD) in colorectal cancer (CRC). However, MRD classification is dependent on analytical sensitivity, and the impact of detection threshold on observed post-operative positivity remains incompletely characterized. We evaluated MRD positivity in stage I-III CRC using a CRISPR-based plasma sequencing assay, MUTE-Seq. MethodsPatients were prospectively enrolled and analyzed using customized tumor-informed panels applied to baseline and post-operative plasma samples collected at 4-week and 3-month. We report preliminary results from 39 plasma samples obtained from the first 14 patients. MRD positivity was assessed across multiple hypothetical detection thresholds (1-100 ppm). ResultsAll 14 patients (100%) had detectable mutations at baseline. Mutation-positive call number significantly decreased after surgery (baseline vs 4-week, p = 0.006; baseline vs 3-month, p = 0.004), and ctDNA concentration likewise declined (baseline vs 4-week, p = 0.002; baseline vs 3-month, p = 0.003). Among stage II-III patients, MRD positivity at 4-week was 20% at a 100-ppm threshold but increased to 70% at 10 ppm and 100% at 1 ppm. At 3-month, MRD positivity was 11% at a 100-ppm threshold and 78% at 1 ppm. At both time points, approximately 80% of MRD-positive stage II-III patients harbored ctDNA levels below 100 ppm, and half of these cases were below 15 ppm. Two patients (one stage I and one stage II) developed recurrence; both were MRD-positive at 4-week and demonstrated increasing mutation-positive calls at 3-month, with a median radiologic lead time of 4 months. ConclusionsPost-operative MRD classification in CRC is strongly influenced by analytical sensitivity. A substantial proportion of residual disease signals reside below the conventional ctDNA detection threshold of 100 ppm, supporting the clinical relevance of ultrasensitive ctDNA detection.

Background: Gastric cancer surveillance in CDH1 pathogenic variant carriers is challenging, as predictors of localized (stage T1a) and advanced (stage >T1a) signet ring cell carcinoma (SRCC) are not well defined. We established the Group of investigAtors STriving toward Research In CDH1 (GASTRIC) consortium to identify clinicopathological factors associated with localized and advanced SRCC. Methods: A retrospective observational study (1998-2025) of CDH1 carriers across twelve academic centers was performed. Clinical, endoscopic, and pathological data were compared between carriers with and without SRCC on endoscopy, and between those with advanced versus localized or no cancer on gastrectomy specimens. Results: Overall, 390 CDH1 carriers from 235 families were included. Presence of SRCCs on endoscopy was significantly associated with thickened folds, nodularity, masses, and intestinal metaplasia, while gastritis was negatively associated. Of 196 carriers (52.4%) undergoing gastrectomy, 11 (5.6%) had advanced cancers, 10(90.9%) of which showed endoscopic abnormalities. Identification of SRCC on baseline endoscopy was the most sensitive feature for advanced disease (0.81) but had moderate specificity (0.74), whereas masses and thickened folds were highly specific (0.99 and 0.96, respectively) but less sensitive. Negative predictive values were high (0.94-1.0), while positive predictive values were modest (0.13-0.66). On multivariate analysis, masses and SRCC foci on baseline endoscopy were independent predictors of advanced disease. Conclusion: Among CDH1 carriers, absence of endoscopic findings was reassuring, whereas significance of detected endoscopic and pathological abnormalities was less certain. Advanced cancer occurred in a small number of carriers, with endoscopic abnormalities in nearly all cases. Endoscopic surveillance might be an alternative to surgery in carriers without worrisome mucosal findings.

BackgroundSingle-cell RNA sequencing (scRNA-seq) has become essential for understanding disease biology, yet its application in clinical trials is often limited by logistical challenges associated with the handling of biospecimens. Newly developed protocols aim to address these limitations by enabling profiling of fixed tissue. These new solutions need to be benchmarked against well-established protocols to assess their performance and suitability for clinical research. ResultsWe systematically compared different scRNA-seq protocols in a set of samples commonly analysed in clinical trials. The 10X Genomics GEM-X Flex Gene Expression assay (GEM-X Flex), in combination with the "chop-fix" preprocessing protocol, demonstrated superior performance to the standard GEM-X Universal Gene Expression solution when applied to both primary tumor tissue fragments and FFPE blocks. Moreover, the quality of the data obtained from GEM-X Flex applied to FFPE blocks outperformed that of single-nuclei RNA sequencing (snRNA-seq) from frozen biopsies, more robustly capturing the biological signals associated with the mechanism of action of a drug evaluated in an internal clinical trial. ConclusionsGEM-X Flex generates reliable, comprehensive transcriptomic data from both fixed tissue and clinical biopsies. By overcoming some of the limitations of fresh and frozen tissue analysis, this protocol offers a robust solution for the broad implementation of scRNA-seq in clinical trials.

Current clinical management of multiple myeloma (MM) relies on bone marrow (BM) biopsies for minimal residual disease (MRD) assessment. While BM biopsies are the gold standard, their invasive nature and potential to miss extramedullary or patchy disease necessitate sensitive, non-invasive liquid biopsy platforms. In this study, we evaluated the analytical performance of the CellSearch CMMC assay to determine its utility for deep-MRD monitoring. Using a standard 4 mL whole blood input, the assay achieves a WBC-normalized sensitivity of 2.45 x 10-7, supported by a limit of quantitation of 5 cells per run. Given this high analytical sensitivity, the assay provides a robust negative predictive value, rendering false-negative findings highly unlikely in populations with detectable peripheral disease. These findings characterize the CellSearch CMMC assay as a highly sensitive, analytically validated platform for non-invasive deep-MRD level longitudinal surveillance monitoring. When integrated into a clinical workflow that accounts for its specificity profile, the platform offers a patient-friendly complement to serial BM biopsies, with the potential to reduce their frequency in appropriate clinical contexts.