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PubMed2025

Efficacy of EGFR tyrosine kinase inhibitors in patients with non-small cell lung cancer with EGFR exon 19 insertions: clinical-genomic, preclinical analysis through LC-SCRUM-Asia (multi-institutional genomic screening registry).

BACKGROUND: EGFR exon 19 insertions (EGFRex19ins) are rare EGFR mutations. Their clinical-genomic characteristics and outcomes with EGFR-tyrosine kinase inhibitors (TKIs) remain uncertain. METHODS: We evaluated the clinical-genomic characteristics and outcomes of EGFR-TKIs for EGFRex19ins in the multi-institutional prospective lung cancer genomic screening project (LC-SCRUM-Asia). We also studied preclinical Ba/F3 models expressing EGFR-K745_E746insIPVAIK (Ba/F3-IPVAIK) to investigate their sensitivity to 1st-, 2nd-, 3rd-generation, and EGFR exon 20 insertion-active TKIs. RESULTS: In LC-SCRUM-Asia, 16,204 NSCLC patients were enrolled from March 2015 to December 2023. EGFRex19ins were detected in 13 samples (0.1 % of NSCLC). The median age was 72 years (range, 38-80); most patients were female (77 %), had adenocarcinoma (92 %), and were never-smokers (62 %). Twelve patients (93 %) had EGFR-K745_E746insIPVAIK, while one (7 %) had EGFR-K745_E746insVPVAIK. The most frequent co-mutation was TP53 (62 %); no patients had other driver alterations. Six patients (46 %) tested positive for EGFR exon 19 deletions with PCR-based Cobas EGFR test, likely due to cross-reactivity arising from sequence homology. Twelve patients received EGFR-TKIs; five (42 %) experienced partial response. In the preclinical study, Ba/F3-IPVAIK showed the highest sensitivity to 2nd-generation EGFR-TKIs compared to other EGFR-TKIs. Structural studies supported these consistent results. When broken down by EGFR-TKI generations, response rates for 1st-, 2nd-, and 3rd-generation TKIs were 50 % (1/2), 80 % (4/5), and 0 % (0/5), respectively. The median PFS for 1st-, 2nd-, and 3rd-generation TKIs were 8.7 (95 % CI, 7.4-NR), 14.7 (95 % CI, 8.0-NR), and 4.4 (95 % CI, 3.4-NR) months, respectively. CONCLUSION: Our preclinical, structural, and clinical findings indicate 2nd-generation EGFR-TKIs are more effective for EGFRex19ins compared to other TKIs.

Adult↗

PubMed2026

TargetQC: A targeted quality control framework for clinical genomic testing.

Reliable genetic testing depends on accurate assessment of sequencing quality in clinically relevant genomic regions that directly influence variant interpretation. We developed TargetQC, a flexible quality control framework that supports user-defined gene sets, coverage thresholds, and variant sets for evaluating sequencing performance across exome sequencing (ES) and genome sequencing (GS) platforms. TargetQC assesses exon and gene coverage, identifies regions meeting predefined coverage thresholds, evaluates variant detection accuracy, and measures sequencing quality at pathogenic variant sites. We applied TargetQC to the reference sample NA12878 and 665 clinical samples across five ES platforms and one GS platform. ES-VendorB and ES-VendorE achieved the most complete coverage of OMIM coding regions in NA12878, whereas ES-VendorD and ES-VendorE showed the highest coverage compliance in clinical samples. ES-VendorB and GS demonstrated the highest variant detection accuracy. TargetQC provides a practical framework for benchmarking sequencing performance and informing platform selection in clinical genomics.

exome sequencing↗

PubMed2026

Examining gaps in institutional policies for clinical genomic data sharing: A cross-jurisdictional study.

The sharing of data generated by clinical genetic and genomic testing without explicit consent is important for timely diagnosis and treatment. While many jurisdictions permit the sharing of identifiable data for direct clinical care, institutional policies vary in how clearly they specify key elements, including when sharing is permitted, what data are covered, and what safeguards apply. Greater clarity around these elements may support responsible data sharing while balancing timely care with transparency and appropriate protections. We conducted a mixed-methods content analysis of data-sharing and privacy policies from 33 clinical genomic institutions across 17 countries and regions. Using a predefined analytical framework, we assessed how policies document key governance elements relevant to sharing without explicit consent. Two independent reviewers extracted information about clinical contexts, data types, justifications, and protections. Although 70% of institutions described circumstances permitting data sharing without explicit consent, most policies did not clearly define the scope or governance of such sharing. Policies also rarely distinguished clinical from research or secondary use and inconsistently specified privacy and security safeguards. While sharing was commonly justified for clinical care (78.3%) or testing services (43.5%), data recipient roles and onward-sharing expectations were often left undefined. This uneven documentation could make it difficult for clinical teams and institutional decision-makers to identify and justify decisions about what is permitted and under what conditions. A guidance framework specifying core governance elements and corresponding protections could help institutions communicate their governance choices more clearly and support comparable baseline practices for responsible data sharing.

Information Dissemination↗

PubMed2024

Deep-Learning Model for Tumor-Type Prediction Using Targeted Clinical Genomic Sequencing Data.

UNLABELLED: Tumor type guides clinical treatment decisions in cancer, but histology-based diagnosis remains challenging. Genomic alterations are highly diagnostic of tumor type, and tumor-type classifiers trained on genomic features have been explored, but the most accurate methods are not clinically feasible, relying on features derived from whole-genome sequencing (WGS), or predicting across limited cancer types. We use genomic features from a data set of 39,787 solid tumors sequenced using a clinically targeted cancer gene panel to develop Genome-Derived-Diagnosis Ensemble (GDD-ENS): a hyperparameter ensemble for classifying tumor type using deep neural networks. GDD-ENS achieves 93% accuracy for high-confidence predictions across 38 cancer types, rivaling the performance of WGS-based methods. GDD-ENS can also guide diagnoses of rare type and cancers of unknown primary and incorporate patient-specific clinical information for improved predictions. Overall, integrating GDD-ENS into prospective clinical sequencing workflows could provide clinically relevant tumor-type predictions to guide treatment decisions in real time. SIGNIFICANCE: We describe a highly accurate tumor-type prediction model, designed specifically for clinical implementation. Our model relies only on widely used cancer gene panel sequencing data, predicts across 38 distinct cancer types, and supports integration of patient-specific nongenomic information for enhanced decision support in challenging diagnostic situations. See related commentary by Garg, p. 906. This article is featured in Selected Articles from This Issue, p. 897.

Humans↗

PubMed2026

Assessing the readiness of Oxford Nanopore sequencing for clinical genomics applications.

Long-read sequencing (LRS) technologies, namely, Oxford Nanopore Technologies (ONT) and Pacific Biosciences (PacBio), have emerged as promising solutions to overcome the limitations of short-read sequencing (SRS). Nevertheless, the still higher sequencing error rates compared with SRS, need for customized pipelines, rapidly updating software, and incipient scalability continue to present challenges for adopting ONT in standard clinical practice. Here we assess the performance of ONT (R9 and R10 chemistries) in comparison to Illumina and MGI across 17 well-characterized reference samples with 11 clinical variants representing nine different genetic diseases. To enable this, we have implemented a production-ready pipeline including SNV, indel, STR, SV, and CNV detection, alongside reporting key summary metrics to ensure high-quality data at the production sequencing level. Our results show high accuracy of ONT across SNVs (F-score 0.978-0.983) and SVs (F-score = 0.75) but still weaknesses across indels (F-score 0.659-0.758). However, we highlight that ONT accurately detected all four pathogenic indels as well as the performance improvement in exons and with the newer R10 chemistry. We further demonstrated the importance of long reads to detect clinically impactful variants such as a FMR1 pathogenic expansion, often misclassified by SRS as being in the premutation range. Our multiplatform analysis and Sanger validation uncovered a 1 bp error in the Coriell annotation for a cystic fibrosis-causing indel in GM07829. This work underscores the growing readiness of ONT for clinical applications, highlighting both its advancements and its potential for broader adoption in clinical genomics and large-scale operations.

Humans↗

PubMed2025

An Integrated Clinical Genomic and Transcriptomic Subgrouping of Central Chondrosarcoma.

Central conventional chondrosarcoma, a malignant cartilage-producing bone tumor, is the second most common bone sarcoma. Chondrosarcomas are histologically graded, which is so far the best predictor of survival. Early mutations in isocitrate dehydrogenase 1 (IDH1) and IDH2 genes are frequent, leading to the production of the oncometabolite D-2-hydroxyglutarate, which affects DNA methylation, resulting in a preferred chondrogenic differentiation over osteogenic differentiation of mesenchymal stem cells, which are currently considered the precursor cells of chondrosarcoma. DNA methylation profiling has previously revealed distinct profiles between IDH-mutant and IDH-wild-type chondrosarcomas, but the presence of further DNA methylation subgroups indicates that classification based solely on IDH status is too simplistic. In this study, we aim to identify biological subgroups in a total of 116 chondrosarcomas by integrating clinical data, IDH mutation status, gene expression, and genome-wide loss of heterozygosity (LOH). Clinical associations were observed between several factors, including sex and histological grade, as well as tumor site and IDH mutation status. RNA sequencing and genome-wide LOH confirmed the distinction between IDH-wild-type and IDH-mutant chondrosarcomas, where the number of chromosome arms affected by LOH was significantly higher in IDH-wild-type tumors than in IDH-mutant tumors. However, no clear subgroups emerged within each IDH group. Further clustering on RNA expression of differentiation markers identified subgroups characterized by chondrogenic, osteogenic, resting chondrocyte, or dedifferentiated profiles. These different subgroups showed a specific clinical presentation and suggest different precursor cells. Instead of a simple dichotomy between IDH-mutant and IDH-wild-type, our integrated approach highlights interconnected clinical, genomic, and transcriptomic patterns that offer a more nuanced view of chondrosarcoma biology and might potentially guide treatment stratification.

Humans↗

PubMed2026

Integrating clinical and genomic features to predict response to neoadjuvant therapy in microsatellite-stable rectal cancer.

BACKGROUND: Neoadjuvant therapy (NAT) has shifted rectal cancer management toward organ preservation. However, achieving a complete response (CR) for "watch-and-wait" strategies is hindered by high response heterogeneity. Although immunotherapy-combined NAT has expanded the candidate pools, the predictive significance of molecular alterations remains unclear. OBJECTIVES: This study aimed to evaluate clinical and genomic profiles of rectal cancer patients undergoing NAT to identify response predictors and to develop a nomogram for estimating CR probability. DESIGN: Retrospective, single-center cohort study. METHODS: This study included 437 patients with rectal adenocarcinoma at Fudan University Shanghai Cancer Center between December 2019 and March 2023. Patients underwent paired tumor and germline genomic sequencing (887-gene panel) before NAT. Logistic and Cox regression analyses were performed to identify clinical and genetic risk factors associated with tumor response and long-term survival. RESULTS: Of the 437 patients, 96.6% had microsatellite-stable (MSS) tumors. In the MSS locally advanced rectal cancer cohort (N = 307), the CR rate was 35.5%. Multivariate analysis identified immunotherapy-combined NAT (iTNT) (OR 4.41, 95% CI: 2.42-8.27), SYNE1 mutation (OR 2.12, 95% CI: 1.06-4.26), negative mesorectal fascia (MRF) status (OR 0.34, 95% CI: 0.17-0.66), and lower tumor location (OR 0.48, 95% CI: 0.27-0.84) as independent predictors of CR. KRAS mutation was the sole independent predictor of reduced disease-free survival (DFS; HR 1.93, 95% CI: (1.11-3.36), p = 0.020). KRAS G12D subtype was associated with the worst 2-year distant metastasis-free survival (71.3%) and exhibited a distinct predilection for lung metastasis. The clinical-genomic nomogram yielded strong discrimination (AUC = 0.705) and calibration, with favorable DCA net benefit. CONCLUSION: Clinical and genomic features jointly determine outcomes in MSS rectal cancer. SYNE1 mutation serves as a novel biomarker for CR, while KRAS mutations, especially the G12D subtype, identify patients at high risk for systemic relapse. The clinical-genomic nomogram facilitates individualized selection for organ-preservation strategies.

biomarker↗

PubMed2025

Amplification of Filovirus Genomes from Clinical Samples for Next Generation Sequencing.

Viral genome sequencing has become a critical tool in outbreak mitigation. Due to their small size relative to the host genome, viral genomes comprise a small fraction of next generation sequencing reads in clinical samples when using unbiased sequencing approaches. Long-range polymerase chain reaction facilitates the amplification of viral genomes from clinical and environmental samples with minimal primer sites, allowing researchers to target regions of the genome that are conserved across available variants. Here, we describe the amplification and sequencing of the Ebola virus genome from tissue samples collected from infected nonhuman primates. This protocol facilitates full viral genome recovery from as low as 103 median tissue culture infectious doses per milliliter.

High-Throughput Nucleotide Sequencing↗

PubMed2025

Invasive Streptococcus dysgalactiae subspecies equisimilis compared with Streptococcus pyogenes in Australia, 2011-23, and the emergence of a multi-continent stG62647 lineage: a retrospective clinical and genomic epidemiology study.

BACKGROUND: Streptococcus dysgalactiae subspecies equisimilis (SDSE) is closely related to Streptococcus pyogenes, with overlapping disease manifestations. We compared the clinical and genomic epidemiology of invasive SDSE with invasive S pyogenes across different settings in Australia and phylogenetically contextualised the SDSE sequences within a global cohort of genomes. METHODS: In this retrospective clinical and genomic epidemiology study, cases of invasive SDSE isolated from normally sterile sites were identified and whole-genome sequenced across five hospital networks in temperate southeast Australia (Melbourne and Sydney) and the tropical Top End of the Northern Territory. SDSE disease incidence, case demographics, clinical outcomes, and longitudinal lineage dynamics were compared between southeast Australia and the Top End and to co-collected invasive S pyogenes cases in each region. SDSE genomes and lineages were also contextualised within 1166 global SDSE sequences. Genomic transmission clusters (not necessarily direct transmission) were inferred between isolates from different individuals by single-linkage clustering at a single nucleotide polymorphism threshold of less than or equal to seven for SDSE and less than or equal to five for S pyogenes based on previous transmission analyses. FINDINGS: Between Jan 1, 2011, and Feb 28, 2023, there were 693 invasive SDSE cases and 995 invasive S pyogenes cases. Invasive SDSE occurred almost exclusively in adults. The overall invasive SDSE incidence in southeast Australia was similar to invasive S pyogenes (incidence rate ratio [IRR] 1·15, 95% CI 0·91-1·46; p=0·26) and increased over the study period (IRR 1·06 per year, 95% CI 1·05-1·08; p<0·0001) from 1·30 cases per 10 000 admissions in 2011 to 3·72 cases per 10 000 admissions in the first 2 months of 2023 (95% CI 2·13-6·07). In southeast Australia, where stringent COVID-19 non-pharmaceutical interventions (NPIs) were implemented between 2020 and 2021, the SDSE incidence plateaued during 2020-21 but did not significantly decline (IRR 1·09 compared with 2017-19, 95% CI 0·88-1·35; p=0·47). By contrast, S pyogenes incidence substantially declined in 2020-21 in southeast Australia (IRR 0·35 compared to 2017-19, 95% CI 0·22-0·52; p=0·017). In the Top End, SDSE incidence was lower than S pyogenes (IRR 0·24, 95% CI 0·19-0·31; p<0·0001). However, crude incidence remained higher than southeast Australia (crude IRR 1·24, 95% CI 1·07-1·42; p=0·0037) and disproportionately affected First Nations Australians in the Top End compared with non-First Nations individuals (IRR 3·36, 95% CI 2·33-4·85; p<0·0001). Comparing 2020-21 with 2017-19, there was no decline in SDSE (IRR 1·27, 95% CI 0·73-2·24; p=0·45) or S pyogenes (IRR 0·97, 95% CI 0·80-1·18; p=0·81) incidence in the Top End, which did not implement prolonged stringent COVID-19 NPIs. Analysing the available genomes of invasive cases and in lineages for which more than or equal to five invasive cases occurred, only 24 (6%) of 384 SDSE cases were assigned to genomic transmission clusters, compared with 271 (52%) of 524 S pyogenes cases. An stG62647 lineage encompassed 113 (26%) of 436 sequenced SDSE genomes. Analysis of available SDSE sequences from Australia, western Europe, and North America inferred concurrent international expansion of the stG62647 lineage in all three regions between 1990 and 2005. INTERPRETATION: We identified a substantial burden of invasive SDSE, dominated by the emergent stG62647 lineage. The contrasting epidemiology between species in the different Australian regions, during COVID-19 NPIs, and genomic infection patterns indicates transmission dynamic, pathogen population, and host-pathogen interaction differences between SDSE and S pyogenes and indicates implications for disease control measures. FUNDING: Australian National Health and Medical Research Council.

Humans↗

PubMed2025

AI-HOPE: an AI-driven conversational agent for enhanced clinical and genomic data integration in precision medicine research.

MOTIVATION: The growing complexity of clinical cancer research has fueled a surge in demand for automated bioinformatics tools capable of integrating clinical and genomic data to accelerate discovery efforts. RESULTS: We present the Artificial Intelligence Agent for High-Optimization and Precision Medicine (AI-HOPE), an AI-driven system that enables domain experts to conduct integrative data analyses through natural language interactions. Powered by Large Language Models, AI-HOPE interprets user instructions, converts them into executable code, and autonomously analyzes locally stored data. It supports flexible association studies, subset comparisons, clinical prevalence assessments and survival analyses. In addition, AI-HOPE enables global variable scans to identify features significantly associated with a user-defined outcome, making a powerful and intuitive tool for advancing precision medicine research. Importantly, its closed-system design prevents clinical data leakage. To demonstrate its utility, AI-HOPE was applied to The Cancer Genome Atlas data to address two clinical questions. First, it identified significant enrichment of TP53 mutations in late-stage colorectal cancer compared to early-stage cases. Second, it uncovered a strong association between KRAS mutations and poorer progression-free survival in FOLFOX-treated patients. These findings align with established literature and demonstrate AI-HOPE's ability to generate meaningful insights independently, without prior assumptions. By removing programming barriers and simplifying complex analyses, AI-HOPE bridges the gap between data complexity and research needs. With its scalable and adaptable framework, AI-HOPE has the potential to support diverse biomedical research fields, driving innovation and efficiency in translational studies. AVAILABILITY AND IMPLEMENTATION: The AI-HOPE software and demonstration data is available at https://github.com/Velazquez-Villarreal-Lab/AI-HOPE.

Precision Medicine↗

PubMed2026

An Updated Evidence Assessment of the Genetic Causes of Dilated Cardiomyopathy.

BACKGROUND: Evidence of the diverse genetic architecture of dilated cardiomyopathy (DCM) continues to emerge and requires reassessment of the clinical relevance of implicated disease genes. Building on the 2019-2020 Clinical Genome Resource evaluation, the DCM gene curation expert panel reconvened in 2024-2025 to conduct a reassessment of genes in DCM. METHODS: The Clinical Genome Resource semiquantitative clinical validity classification framework was applied with specifications to DCM to classify genes into categories on the basis of strength of published evidence for a DCM phenotype. Previously curated genes were reassessed, and newly reported gene-disease-mode of inheritance (MOI) relationships, termed "curations," were evaluated. RESULTS: Sixty-eight genes were evaluated, inclusive of 72 unique gene-disease-MOI relationships across 51 previously evaluated and 17 newly assessed genes. Thirty-five curations were classified as high evidence (16 Definitive, 10 Strong, 9 Moderate), increasing by 16 from the prior assessment. Nine newly assessed genes were classified as high evidence: BAG5, FLII, LMOD2, MYLK3, MYZAP, NRAP, PPA2, PPP1R13L, and RPL3L. Twelve genes (11 newly appraised) were rated as high evidence with an autosomal recessive (AR) MOI. Five reevaluated genes from 2019-2020 had clinically significant changes in classification. Except for JPH2, for which curation was modified to separate autosomal dominant and AR MOI curations, clinically significant changes involved upgrades from low- to high-evidence categories (PLEKHM2, PRDM16, TBX20, TNNI3K), demonstrating the robustness of the Clinical Genome Resource gene curation process over time. An additional 29 gene-disease-MOI curations were classified as Limited, including 6 newly evaluated genes and 1 new MOI for a previously evaluated gene, MYBPC3-AR; 4 were classified as No Known Disease Relationship, and remained Disputed. Four previously evaluated genes were curated for both AD and AR MOIs: JPH2 (AD-Strong, AR-Limited), LDB3 (AD-Limited, AR-Strong), MYBPC3 (AD-Limited, AR-Limited), and TNNI3 (AD- and AR- Strong). CONCLUSIONS: With substantial new evidence, the genetic architecture of DCM has rapidly expanded. This updated assessment of genes reported in DCM yielded 35 high-evidence curations, an increase from 19 only 5 years ago. The results of this evidence-based evaluation process inform clinical interpretation of genetic information in the care of DCM patients and families.

dilated cardiomyopathy↗

PubMed2025

Barriers and facilitators to implementing clinical genome-wide sequencing: A scoping review of the global landscape.

PURPOSE: The global demand for clinical genome-wide sequencing (GWS) continues to grow. This study describes the global landscape of genetic service delivery and the barriers and facilitators to implementing clinical GWS. METHODS: A scoping review was conducted using MEDLINE and Embase (January 2009-July 2025) to identify studies related to genetic service delivery, exome and genome sequencing, and implementation. RESULTS: Ninety-six articles representing 35 countries were analyzed using the updated Consolidated Framework for Implementation Research. The most frequently reported barriers were within the outer setting: insufficient Local Conditions (ie, genetics workforce shortage; 54/96, 56%), limited Financing (29/96, 30%), and lack of national Policies and Laws (regulations) for genomic testing (20/96, 21%). Negative Local Attitudes about genomics were reported as a barrier in 11 South American, Middle Eastern, Asian, and African countries. Identified outer setting facilitators included Partnerships and Connections between interested parties (eg, government, academic institutions; 14/96, 15%) and dedicated Funding for national genomics initiatives (6/96, 6%). CONCLUSION: This scoping review identified common barriers to implementing GWS across countries with varying capacities for delivering these services. Findings may help countries to anticipate barriers, leverage facilitators, and develop strategies for implementing genomic testing and services.

Humans↗

PubMed2026

Five decades of pneumococcal meningitis in Spain: a single-centre, clinical and genomic, retrospective, observational study.

BACKGROUND: Pneumococcal meningitis remains a major threat, with high fatality rates and long-term sequelae, despite advances in vaccination and treatment. We aimed to examine the associations between pneumococcal serotypes, Global Pneumococcal Sequence Cluster (GPSC), antimicrobial resistance, source of infection, and clinical outcomes in adults with pneumococcal meningitis. METHODS: In this single-centre, clinical and genomic, retrospective, observational study, we analysed all laboratory-confirmed cases of adult pneumococcal meningitis recorded at Hospital Universitari de Bellvitge, Spain. Clinical data were obtained from a prospectively maintained clinical database and linked to microbiological and genomic data by unique patient identifiers. Clinical sources of infection were classified as cerebrospinal fluid leakage, acute otitis media, or haematogenous origin. Disease severity was defined as shock at presentation, sequelae as any persistent neurological deficit at discharge, and mortality as death within 30 days. Serotype data were available for 265 isolates, and whole-genome sequencing was done on 200 viable isolates. For outcome analyses, patients who did not receive dexamethasone were excluded. Serotype, GPSCs, antimicrobial susceptibility, phylogenetic, and genome-wide association study (GWAS) data were analysed to assess determinants of meningitis source, disease severity, sequelae, and 30-day mortality. FINDINGS: 387 adult patients (median age 58 years [IQR 45-68]; 54% male) with pneumococcal meningitis were recorded between Jan 1, 1974, and Dec 31, 2023. Acute otitis media was the most frequent source of pneumococcal meningitis (174 [45%] of 387 cases) and was mainly caused by serotype 3 (pneumococcal conjugate vaccine [PCV]13; GPSC12). The 30-day case-fatality rate in this group was 17 (10%) of 174 (95% CI 5·8-15·2). Haematogenous episodes accounted for 104 (27%) of 387 cases and had a significantly higher 30-day case-fatality rate (50 [48%] of 104; 95% CI 38·2-58·1; p<0·0001) with a higher frequency of serotype 4. Cerebrospinal fluid leakage accounted for 105 (27%) of 387 cases and had the lowest 30-day case-fatality rate (nine [9%] of 105; 95% CI 4·0-15·6) and broader serotype diversity. The introduction of PCV7 and PCV13 resulted in declines in vaccine-targeted serotypes and β-lactam resistance. Whole-genome sequencing identified 60 distinct GPSCs. Among prevalent lineages, GPSC16 (20 [10%] of 200; serotypes 19A and 23F) and GPSC6 (18 [9%] of 200; serotypes 9V, 11A, and 14) were associated with β-lactam resistance. GWAS did not identify genetic variants significantly associated with severity, sequelae, or mortality. INTERPRETATION: This longitudinal study provides a comprehensive view of adult pneumococcal meningitis over five decades, revealing changes in sources of infection, serotype distribution, pneumococcal lineages, and antimicrobial resistance patterns over time. Lineage-level findings suggested variability in clinical outcomes, underscoring the importance of continued genomic surveillance and supporting consideration of broader vaccine targets. GPSC12 predominance and its association with mortality and more severe outcomes highlight the need for preventive measures against serotype 3, although these findings require confirmation in larger multicentre cohorts. FUNDING: Instituto de Salud Carlos III, cofunded by European Social Fund, and the Centro de Investigación Biomédica en Red de Enfermedades Respiratorias, and the Centro de Investigación Biomédica en Red de Enfermedades Infecciosas, both at the Instituto de Salud Carlos III.

Journal Article↗

PubMed2026

Clinical and genomic features of mitis group streptococcal bacteremia in patients with febrile neutropenia.

BACKGROUND: Viridans group streptococci (VGS) can cause the life-threatening viridans streptococcal shock syndrome (VSSS) in patients with febrile neutropenia (FN). The Mitis group, a major subgroup of VGS, is frequently implicated in these severe infections, but its specific clinical and genomic characteristics remain incompletely characterized, particularly in patients with FN. This study aimed to systematically describe these features in this population. METHODS: In this single-center retrospective study, we compared the clinical data and whole-genome sequencing (WGS) results of Mitis group streptococcal isolates from patients with and without FN. Virulence-associated and antimicrobial resistance genes were initially screened using a reference-based approach, followed by assembly-based reanalysis and manual sequence validation. RESULTS: Compared with the non-FN cohort (n = 34), the FN cohort (n = 61) was significantly younger, had a higher prevalence of hematologic malignancy, and more frequently presented with primary bacteremia. VSSS occurred exclusively in the FN group (11.5%) and was associated with high mortality (14-day mortality, 42.9%), which did not correlate with in vitro antimicrobial susceptibility. Genomic analyses revealed marked diversity among isolates. Initial screening suggested variable detection of several virulence-associated loci, including pavA, slrA, and rfb-related loci; however, subsequent assembly-based analyses indicated that many apparent absences were attributable to extreme allelic divergence rather than true gene loss. No single virulence determinant clearly segregated with clinical severity. CONCLUSIONS: Mitis group bacteremia in patients with FN appears to be characterized by distinct clinical features and marked genomic diversity. Our findings suggest that the development of severe disease, including VSSS, may not be explained by microbial factors alone and potentially reflects complex host-pathogen interactions. CLINICAL TRIAL: Not applicable.

Humans↗

PubMed2026

The ASH HematOmics Program supports integrative analysis of genomic and clinical data in hematologic diseases.

The increasing availability of genomic and transcriptomic sequencing has uncovered diverse genomic alterations and distinct gene expression profiles driving hematologic diseases, yet a data integration and sharing platform dedicated to hematology remains lacking. We developed the American Society of Hematology (ASH) HematOmics Program (ASHOP; ashop.hematology.org), a resource for exploring somatic alterations and gene fusions, transcriptomic results, and clinical data from 5960 patients spanning B-cell precursor and T-cell acute lymphoblastic leukemia, acute myeloid leukemia, myelodysplastic syndromes, and chronic lymphocytic leukemia. Users can explore genomic alteration landscapes and comutation patterns via lollipop and matrix plots and analyze significantly altered genes in user-defined subcohorts. Transcriptomes can be explored through interactive uniform manifold approximation and projections, clustering, differential expression, and pathway enrichment. Genomic, transcriptomic features, and clinical outcomes can be correlated in a user-driven manner or combined to precisely define study cohorts. We illustrate the following 4 use cases of ASHOP: (1) stratification of DUX4-rearranged B-cell leukemias into Early/Multipotent and Committed subgroups with distinct outcomes, (2) characterization of HOXA/HOXB expression patterns in acute myeloid leukemias, (3) correlating mutational burden with mismatch repair deficiency and mutational signatures, and (4) investigation of TP53 alteration landscape. ASHOP is an open-access resource to inform genomic and transcriptomic data interpretation for hematologic malignancies and will expand to support additional diseases and data modalities from the ASH community.

Humans↗

PubMed2025

Genomic and clinical epidemiology of SARS-CoV-2 in coastal Kenya: insights into variant circulation, reinfection, and multiple lineage importations during a post-pandemic wave.

BACKGROUND: Between November 2023 and March 2024, coastal Kenya experienced another wave of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infections detected through our continued genomic surveillance. Herein, we report the clinical and genomic epidemiology of SARS-CoV-2 infections from 179 individuals (a total of 185 positive samples) residing in the Kilifi Health and Demographic Surveillance System (KHDSS) area (~ 900 km2). METHODS: We analyzed genetic, clinical, and epidemiological data from SARS-CoV-2 positive cases across pediatric inpatient, health facility outpatient, and homestead community surveillance platforms. Phylogenetic analyses were performed using maximum-likelihood and Bayesian frameworks. Temporal trends were summarized, comparisons conducted using Kruskal-Wallis and Wilcoxon tests, and associations examined using univariate and multivariable logistic regression models. RESULTS: Sixteen SARS-CoV-2 lineages within 3 subvariants [XBB.2.3-like (58.4%), JN.1-like (40.5%), and XBB.1-like (1.1%)] were identified. The symptomatic infection rate was estimated at 16.0% (95% CI, 11.1-23.9%) based on community testing regardless of symptom status and did not differ across the subvariants (p = 0.13). The most common infection symptoms in community cases were cough (49.2%), fever (27.0%), sore throat (7.3%), headache (6.9%), and difficulty in breathing (5.5%). One case succumbed to the infection. Genomic analysis of the virus from serial positive samples confirmed repeat infections among 5 participants under follow-up (median interval 21 days, range 16-95 days); in 4 participants, the same virus lineage was responsible in both episodes, whereas 1 participant had a different lineage in the second compared with the first episode. Phylogenetic analysis including > 18,000 contemporaneous global sequences provided evidence for at least 38 independent virus introduction events into the study area (KHDSS) during the wave, the majority likely originating in North America and Europe. CONCLUSIONS: Our study highlights that coastal Kenya, like most other localities, continues to face new SARS-CoV-2 infection waves characterized by circulation of new variants, multiple lineage importations, and reinfections. Locally, the virus may circulate unrecognized, as most infections are asymptomatic in part due to high population immunity after several waves of infection. Our findings highlight the need for sustained SARS-CoV-2 surveillance to inform appropriate public health responses, such as scheduled vaccination for populations at risk of severe infection.

COVID-19↗

PubMed2025

Temporal and geographical lineage dynamics of invasive Streptococcus pyogenes in Australia from 2011 to 2023: a retrospective, multicentre, clinical and genomic epidemiology study.

BACKGROUND: Defining the temporal dynamics of invasive Streptococcus pyogenes (group A Streptococcus) and differences between hyperendemic and lower-incidence regions provides crucial insights into pathogen evolution and, in turn, informs preventive measures. We aimed to examine the clinical and temporal lineage dynamics of S pyogenes across different disease settings in Australia to improve understanding of drivers of pathogen diversity. METHODS: In this retrospective, multicentre, clinical and genomic epidemiology study, we identified cases of invasive S pyogenes infection from normally sterile sites between Jan 1, 2011, and Feb 28, 2023. Data were collected from five hospital networks across low-incidence regions in temperate southeast Australia and the hyperendemic, tropical, and largely remote Top End of the Northern Territory of Australia. The crude incidence rate ratio (IRR) of bloodstream S pyogenes infection comparing the Top End and southeast Australia and in First Nations people compared with non-First Nations people was estimated by quasi-Poisson regression. We estimated odds ratios (ORs) of intensive care unit (ICU) admission, in-hospital mortality, and 30-day mortality for the Top End versus southeast Australia using logistic regression. Retrieved and successfully sequenced isolates were assigned lineages at whole-genome resolution. Temporal trends in the composition of co-circulating lineages were compared between the two regions. We used an S pyogenes-specific multistrain simulated transmission model to examine the relationship between host population-specific parameters and observed pathogen lineage dynamics. The prevalence of accessory genes (those present in 5-95% of all genomes) was compared across geographies and temporal periods to investigate genomic drivers of diversity. FINDINGS: We identified 500 cases of invasive S pyogenes infection in patients in the Top End and 495 cases in patients in southeast Australia. The crude IRR of bloodstream infection for the Top End compared with southeast Australia was 5·97 (95% CI 4·61-7·73) across the entire study period; in the Top End, infection disproportionately affected First Nations people compared with non-First Nations people (5·41, 4·28-6·89). The odds of in-hospital mortality (OR 0·43, 95% CI 0·26-0·70), 30-day mortality (0·38, 0·23-0·63), and ICU admission (0·42, 0·30-0·59) were lower in the Top End than in southeast Australia. Longitudinal lineage analysis of 642 S pyogenes genomes identified waves of replacement with distinct lineages in the Top End, whereas southeast Australia had a small number of dominant lineages that persisted and cycled in frequency. The transmission model qualitatively reproduced a similar pattern of replacement with distinct lineages when using a high transmission rate, small population size, and high levels of human movement-characteristics similar to those of communities in the hyperendemic Top End. Using a lower transmission rate, larger population size, and lower levels of migration similar to those of communities in urbanised southeast Australia, the transmission model qualitatively reproduced a pattern of dominant lineages that cycled in frequency. Despite distinct circulating lineages, the prevalence of accessory genes in the bacterial population was maintained across geographies and temporal periods. INTERPRETATION: In a hyperendemic setting, the replacement of distinct S pyogenes lineages occurred in waves, which could be linked to the disproportionate burden of disease and sparse human population in this setting. The maintenance of bacterial gene frequency could be consistent with multilocus selection. These findings suggest that lineage-specific interventions-such as vaccines under development-should consider disease setting and, without broad cross-protection, might lead to lineage replacement. FUNDING: National Health and Medical Research Council, and Leducq Foundation.

Humans↗

PubMed2026

Mapping the de-implementation of traditional diagnostic tests in pediatric acute lymphoblastic leukemia.

INTRODUCTION: Advances in cancer diagnostics raise questions about when and how to de-implement traditional approaches; however, these processes remain poorly described. At St. Jude Children's Research Hospital (SJCRH), routine conventional cytogenetics for pediatric acute lymphoblastic leukemia (ALL) diagnosis was de-implemented in 2018 following adoption of clinical genomics. This study aimed to map this process to inform future diagnostic de-implementation initiatives. METHODS: Interviews were conducted with SJCRH staff involved or impacted by cytogenetics de-implementation. Data were analyzed using thematic and rapid qualitative analysis informed by the Consolidated Framework for Implementation Research. Member-checking was used to verify and refine process maps, which were subsequently reviewed by an external expert panel, representing diverse settings, through focus group discussions. RESULTS: Thirteen SJCRH clinicians participated. De-implementation was described as successful, with no negative impact on patient outcomes. Decision-making began with internal correlation studies that demonstrated superior diagnostic performance of clinical genomics. De-implementation was viewed as a natural evolution that improved molecular classification, resource allocation, and workflow efficiency. Perceived risks included loss of cytogenetics competency, delayed turnaround time, and career insecurity, all addressed institutionally. Lessons learned highlighted the importance of deliberate discussion about logic and evidence supporting de-implementation. Fifteen external experts offered suggestions to improve process map generalizability, highlighting institutional- and system-level considerations. CONCLUSION: De-implementation of cytogenetics in ALL in favor of clinical genomics was successful at SJCRH. This study offers an example of diagnostic de-implementation in cancer care and proposes a structured approach to guide future efforts. De-implementation should be considered alongside introduction of novel diagnostic approaches.

cancer diagnostics↗