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PubMed2026

Clinical outcomes and genomic features of uncommon EGFR exon 19 deletion subtypes in osimertinib-treated non-small cell lung cancer.

BACKGROUND: Epidermal growth factor receptor (EGFR) exon 19 deletion subtypes may be associated with differential survival outcomes following EGFR-tyrosine kinase inhibitor treatment. However, evidence remains scarce, particularly regarding osimertinib, and the underlying biological mechanisms are poorly understood. We aimed to compare survival outcomes among EGFR exon 19 deletion subtypes in patients with non-small cell lung cancer (NSCLC) treated with osimertinib. METHODS: In this multicenter retrospective study, patients with NSCLC were stratified according to exon 19 deletion subtypes. Whole-exome sequencing data from the American Association for Cancer Research Genomics Evidence Neoplasia Information Exchange registry and Memorial Sloan Kettering Clinicogenomic Harmonized Oncologic Real-World Dataset were analyzed to investigate co-occurring genomic alterations. RESULTS: Overall, 111 patients with advanced EGFR exon 19 deletion-positive NSCLC were analyzed and 86.5% received osimertinib as first-line therapy. Patients with non-E746_A750del (n = 25) had shorter progression-free survival (PFS) than those with E746_A750del (n = 86) (median: 14.3 vs. 20.6 months; p < 0.05). Among non-E746_A750del subtypes, L747_A750delinsP (n = 4) had a particularly poor prognosis, with significantly worse survival than those with E746_A750del (median PFS: 3.5 vs. 20.6 months; p < 0.001, and median overall survival: 11.8 vs. 48.5 months; p < 0.001). In public database analyses, non-E746_A750del had a higher rate of RBM10 co-mutations, whereas L747_A750delinsP was characterized by frequent CDKN2A/B homozygous deletions and MYC amplifications. CONCLUSIONS: Non-E746_A750del was associated with poorer outcomes, with L747_A750delinsP potentially being a high-risk subtype. Differences in co-occurring genomic alterations may contribute to the prognostic heterogeneity among exon 19 deletion subtypes.

Humans↗

PubMed2026

Sparse Logistic Regression on Genomic Data for Prediction of Tumour Pathological Subtype.

The correct prediction of tumour subtype is critical for the treatment of cancer patients to maximise the chance of survival. The patients' genomic information, such as copy number alterations (CNA) profile, has increasingly become an important factor in the prediction to supplement the traditional pathological subtyping. The incorporation of the CNA information in a prediction model, such as logistic regression, faces two major statistical challenges: first, how to estimate the model parameters in the thousands and, second, how to deal with the correlation of CNA between genomic regions. To address them, we propose a sparse logistic regression model with random effects where some of its parameters are estimated to zero while the other parameters are non-zero. In effect, a variable selection is embedded in the modelling. To deal with the correlation of CNA across genomic regions, we extend further the model to incorporate an additional penalty in the corresponding likelihood function in the logistic regression. The results show that we can identify selected genomic regions that are informative to distinguish different tumour subtypes, while giving a good prediction ability. We illustrate the methodology using CNA dataset from a lung cancer cohort.

Journal Article↗

PubMed2026

Genomic wastewater surveillance of human and animal influenza A viruses in California during the 2024-2025 flu season.

BACKGROUND: Wastewater genomic surveillance provides an opportunity to detect human and animal influenza A virus (IAV). We aimed to implement an IAV genomic surveillance framework agnostic to subtype, which enables recovery of IAV from multiple hosts and estimation of proportions across subtypes. METHODS: We conducted IAV genomic surveillance in wastewater during the 2024-2025 flu season at multiple sites in California and compared these data with available human clinical IAV sequences and test positivity. We applied a custom whole-genome, multi-host IAV probe enrichment panel and adapted our custom expectation-maximization (EM) algorithm to deconvolute IAV mixtures in wastewater and infer subtype relative abundances. Absolute IAV concentrations were quantified using RT-PCR-based assays. H5N1 wastewater and clinical sequences were further characterized by constructing a whole-genome maximum-likelihood phylogenetic tree. Finally, we performed variant analysis to examine amino acid substitutions detected in wastewater. FINDINGS: Our IAV probe enrichment method and EM algorithm successfully enriched all eight segments of three circulating IAV subtypes and accurately estimated subclade relative abundances for mixed IAV samples. Seasonal human H1N1pdm09 and H3N2 were detected throughout the study period from both wastewater and clinical sequencing data, with H1N1 subclades 6B.1A.5a.2a.1 and 6B.1A.5a.2a co-circulating, and H3N2 dominated by subclade 3C.2a1b.2a.2a.3a.1. Wastewater surveillance consistently detected H5N1 clade 2.3.4.4b across three monitored wastewater sites, while clinical H5N1 detections, from anywhere in CA, were sporadic and rare. Whole-genome phylogenetic analysis revealed that wastewater H5N1 sequences clustered with reference sequences associated with dairy cow and avian infections, while all human clinical H5N1 sequences clustered exclusively with reference sequences associated with dairy cow infections. Amino acid substitutions were identified across viral segments, and no mutations associated with mammalian adaptation were observed from wastewater samples. INTERPRETATION: When IAV concentrations were dominated by seasonal human subtypes rather than H5N1, subtype patterns aligned between wastewater and clinical data. While sequencing IAV in wastewater was unable to distinguish if H5N1 detections were due to human or animal infections, it was able to provide clade-level information about H5N1 found in wastewater that could be useful in the future. Wastewater genomic surveillance can complement clinical surveillance, increasing ability to detect all circulating IAV subtypes and enhancing public health preparedness from a One Health perspective.

Journal Article↗

PubMed2026

Hierarchical modeling of tumor subtypes in cell lines using large-scale genomic datasets.

Cancer cell lines (CLs) are widely used to study tumor biology and drug response, yet their translational relevance is often limited by inaccurate subtype annotations. Existing CL-tumor matching approaches are frequently constrained by flat classification schemes, weak subtype definitions, and the exclusion of normal tissue references, leading to potential confounding of tumor-specific and tissue-of-origin signals. To address these limitations, a hierarchical classification (HC) framework is presented in which CLs are aligned with patient tumors across biological resolutions, from organ to molecular subtype. Gene expression profiles from 802 CLs, 5,612 tumors from The Cancer Genome Atlas (TCGA) , and 8,939 non-cancerous tissues were integrated to separate oncogenic signals from tissue-specific signals. Node-specific features were selected using maximum relevance minimum redundancy, and balanced accuracies of 89% in cross-validation and 75%, and 80% on external datasets were achieved. Through the framework, 43 CLs were reassigned, and clinically relevant underrepresented subtypes were identified.

cancer cell lines↗

PubMed2026

Dissecting the shared genetic architecture between migraine subtypes and cardiovascular diseases: a multi-layered genomic analysis.

BACKGROUND: Epidemiological studies have linked migraine to an increased risk of cardiovascular disease (CVD); however, the shared genetic basis and putative causal relationships between migraine subtypes and cardiovascular traits remain poorly understood. METHODS: Leveraging large-scale GWAS summary statistics for migraine phenotypes (overall migraine, migraine with aura [MA], and migraine without aura [MO]) from FinnGen R12, along with seven cardiovascular diseases from publicly available consortia, we conducted a multi-layered genetic analysis. This integrative framework encompassed genetic correlation [linkage disequilibrium score regression (LDSC) and high-definition likelihood (HDL)], cross-trait meta-analysis (CPASSOC and PLACO), Bayesian colocalization, summary-data-based Mendelian randomization (SMR) using GTEx v8 eQTL data, and bidirectional two-sample Mendelian randomization (MR). RESULTS: Significant genetic correlations were identified between migraine and multiple cardiovascular traits, with hypertension and coronary artery disease (CAD) showing the most robust associations. MA exhibited broader genetic overlap with cardiovascular diseases than MO, including a notably stronger correlation with ischemic stroke, whereas MO demonstrated a stronger correlation with hypertension. Cross-trait meta-analysis identified 160 pleiotropic loci across 17 of 21 trait pairs. Colocalization analysis confirmed 32 loci harboring shared causal variants, mapped to 13 candidate genes, of which 7 (PHACTR1, LRP1, SOX7, ABO, FHOD3, MEI1, XKR6) were further validated by SMR as exhibiting tissue-specific regulatory effects. Among these, PHACTR1 displayed the broadest pleiotropic profile across migraine phenotypes and vascular diseases. After MR-PRESSO outlier removal, bidirectional MR identified 10 MR-supported associations, two of which (genetic liability to hypertension on overall migraine, and CAD on MA) survived Bonferroni correction, all free of detectable horizontal pleiotropy. Genetic liability to hypertension was associated with increased migraine risk (OR = 1.90, 95% CI 1.25-2.90, P = 2.64 × 10⁻³), atherosclerotic diseases showed subtype-specific effects (inverse for MO, positive for MA), and, in the reverse direction, migraine was associated with increased ischemic stroke risk. CONCLUSIONS: This study provides a comprehensive and systematic characterization of the shared genetic architecture between migraine subtypes and cardiovascular diseases. By identifying pleiotropic genes and bidirectional putative causal relationships with subtype-specific patterns, our findings carry implications for the development of targeted therapeutics and subtype-specific cardiovascular risk stratification.

Humans↗

PubMed2026

Multiomics Integration Identifies a Molecular Subtype of Intrahepatic Cholangiocarcinoma With Enhanced Benefit From Adjuvant Therapy.

Intrahepatic cholangiocarcinoma (iCCA) is a molecularly heterogeneous liver cancer with a poor prognosis. Improved stratification is needed to guide postoperative therapy. In this study, we applied integrative multiomics analysis to classify iCCA and identify biomarkers predictive of adjuvant treatment benefit. Using publicly available datasets (including whole exome sequencing, RNA sequencing, proteomics, and phosphoproteomics from FU-iCCA cohort and a transcriptomic cohort GSE244807), we defined 3 robust molecular subtypes of iCCA. These subtypes exhibited distinct genomic alterations, pathway activation, and immune microenvironments, with significant differences in overall survival (OS). Through protein-protein interaction network analysis and consensus feature selection using 10 clustering algorithms, we prioritized 8 marker genes distinguishing the subtypes. A Cox proportional-hazards model constructed from these markers stratified patients into high- and low-risk groups. High-risk iCCA, characterized by elevated expression of markers such as CLDN18, MUC1, and MUC5AC, had significantly worse OS in the absence of adjuvant therapy. Notably, in an independent validation of 174 patients with iCCA who underwent resection (single-center cohort), high expression of any of these 3 markers were associated with markedly prolonged OS in patients who received adjuvant chemotherapy or chemoembolization, compared with those who did not. In contrast, marker-negative patients showed no clear benefit from adjuvant therapy. In conclusion, our multiomics approach identified a high-risk, mucin-enriched subtype of iCCA. CLDN18, MUC1, and MUC5AC emerge as candidate predictive biomarkers for adjuvant chemotherapy benefit in iCCA, warranting prospective validation to improve personalized postoperative management.

Humans↗

PubMed2026

Molecular Profiling Across 80,000 Patients With Lung Cancer.

INTRODUCTION: Biomarker testing is an essential component of optimal therapeutic management in NSCLC, enabling the use of both Food and Drug Administration-approved and emerging targeted therapies. Despite well-established biomarker testing guidelines and the availability of many approved targeted therapies, a substantial proportion of patients with advanced NSCLC are not benefiting from precision oncology. In this study, we analyze the distribution of actionable genomic alterations across histologic subtypes and clinicodemographic subgroups of NSCLC using data in 82,328 samples profiled with a single comprehensive genomic profiling assay, aiming to support universal molecular testing across all NSCLC subtypes to ensure equitable access to available therapeutics. METHODS: This is an observational retrospective analysis on histologically confirmed NSCLC cases tested with comprehensive genomic profiling by next-generation sequencing between 2014 and 2022 using Foundation One/Foundation CDx. All cases were centrally reviewed by board-certified anatomic pathologist to determine histologic type and subtype. RESULTS: A total of 82,328 patients with NSCLC were included. An actionable genomic alteration (GA) was found in 35.1% of the cases. Lung adenocarcinoma (LUAD) and adenosquamous carcinoma were more frequently associated with actionable GA (45.8% and 40.9%, respectively) as compared with sarcomatoid (29.1%), not otherwise specified (27.6%), large cell (21.1%), and squamous cell (6.5%) histologies. Sarcomatoid histology had the highest METex14 skipping mutation (mut) frequency (9.95% versus 2.43% in LUAD). Tumor mutation burden more than or equal to 10 mut/Mb was associated with histology (50.91% in large cell, 40.79% in not otherwise specified, 39.08% in squamous cell, and 36.30% in sarcomatoid versus 31.22% in LUAD and 29.22% in adenosquamous carcinoma). Patients with actionable GA had usually a low tumor mutation burden (80.88%). A significant correlation (p < 0.005) between age and actionable GA was reported for BRAF/ERBB2 muts, ALK/RET/ROS1 rearrangements, and MET amplification. EGFR actionable muts and KRAS G12C were more frequently observed in females, whereas no significant correlation between sex and other GA was observed. Finally, genetic ancestry analyses revealed a strong correlation for EGFR actionable muts and South/East Asia and America, but not for other GA. CONCLUSIONS: This is the largest NSCLC data set analyzed for biomarker distribution across histologies, age, sex, and genetic ancestry. This data set confirms sufficient enough biomarker prevalence across many histologic subtypes of NSCLC, providing reassurance that all NSCLC cases should be considered for biomarker workup.

Humans↗

PubMed2026

Evaluating sampling strategies for the detection of avian influenza viruses in the environment.

Highly pathogenic avian influenza (HPAI) viruses pose an increasing threat to wildlife, livestock and human health, underscoring the need for scalable and early-warning surveillance systems. Environmental RNA (eRNA) monitoring offers a non-invasive, cost-effective alternative to traditional host-based sampling by detecting viral genetic material shed into the environment. Despite its utility, the relative performance of different environmental sampling approaches for avian influenza virus (AIV) detection remains poorly resolved. Here, we conducted a longitudinal study with monthly sampling over approximately one year across two urban waterfowl ponds in Aotearoa New Zealand to evaluate four eRNA sampling strategies - fresh faeces, sediment, active-filtered water and passive-filtered water - for their ability to detect AIV. Using a combination of metagenomic sequencing and RT-qPCR, we show that all sample types can detect AIV, although detections were highly inconsistent across sampling methods, locations and time points. While metagenomic sequencing provided valuable genomic data, including subtype identification and phylogenetic context, RT-qPCR exhibited greater sensitivity, with active-filtered water yielding the highest detection rates, and is currently the more cost-effective approach for large-scale surveillance. Notably, AIV detections were asynchronous among sample types and frequently lacked temporal concordance, suggesting that environmental heterogeneity, RNA persistence, and methodological detection limits strongly influence surveillance outcomes. Despite these inconsistencies, phylogenetic analyses revealed that detected viruses belong to established Australasian lineages, highlighting the ability of environmental surveillance to capture ecologically relevant viral diversity. Our findings demonstrate that while eRNA-based surveillance holds substantial promise as a complementary tool for AIV monitoring, its effectiveness is highly dependent on the environmental sampling strategies and laboratory detection methods used.

Ducks↗

PubMed2026

Arabidopsis TITAN-LIKE is required for U12-type intron splicing, especially of AT-AC subtypes.

Many eukaryotes possess two types of spliceosomes: the U2-dependent and U12-dependent spliceosomes. The U2-dependent spliceosome processes >99% of all introns, whereas the U12-dependent spliceosome acts on only ~0.3% of introns, one-third of which start with AT and end with AC, with the remainder having GT-AG termini. How the U12-dependent spliceosome splices two types of introns with different terminal sequences remains poorly understood. Human centrosomal AT-AC splicing factor (CENATAC) is a subunit of the U12-dependent spliceosome that is particularly required for the splicing of the AT-AC subtype. The Arabidopsis genome contains a single homolog, TITAN-LIKE (TTL), but its function in splicing remains unknown. Here, we generated ttl mutants and isolated two viable alleles, of which we analyzed one, designated ttl-142, to investigate TTL's function in splicing. ttl-142 carries a 42-nucleotide deletion that removes 14 amino acid residues from the predicted protein, and homozygous mutants exhibit morphological abnormalities. Most U12-dependent introns were less efficiently spliced in ttl-142 than in the wild type, with the splicing of AT-AC introns particularly suppressed. Splicing suppression in ttl-142 was more extensive than in a drol1 (defective repression of the OLE3:LUC1) mutant, which carries a mutation in a gene specifically required for AT-AC intron splicing. Conversely, fewer genes showed altered expression levels in ttl-142 than in drol1, and most differentially expressed genes differed between the two mutants. These results suggest that the phenotypes of ttl-142 and drol1 mutants may reflect the impairment of distinct spliceosomal functions.

Arabidopsis↗

PubMed1977

Morphological transformation of rat embryonic fibroblasts by abortive herpes simplex virus infection: increased transformation rate correlated to a defective viral genotype.

Rat embryo fibroblasts were abortively infected with various stocks of herpes simplex virus type 1 strain ANG at 42 degrees. In uninfected controls all of the cells died during an 8-day incubation period at the elevated temperature, whereas varying numbers of cells in the infected cultures survived and formed colonies during subsequent incubation for 3--4 weeks at 37 degrees. All of the survivors appeared to be morphologically transformed. Two types of survivors, epithelial- and spindle-like cells, which occurred at a ratio of approximately 1:1 in all assays, could be distinguished. The observed survival rates increased from about 1 x 10-7 to 3 x 10-5, corresponding to increasing fractions (0--50%) of a defective genotype present in the infecting virus stocks. The individual survival rates do not depend exclusively on the quantity of defective virions. The existence of different subtypes of defective genomes as a further parameter is discussed.

Animals↗

PubMed2026

Targeting cancer stem cells predicts response and reverses chemoresistance in ascites-derived ovarian cancer organoids.

BACKGROUND: Ovarian cancer (OC) is frequently diagnosed at an advanced stage, where tumor heterogeneity and rapid development of chemoresistance contribute to a poor prognosis. The lack of reliable predictive biomarkers further hinders the development of effective treatment strategies. Patient-derived organoids (PDOs) have recently emerged as promising preclinical models with the potential to predict therapeutic responses. METHODS: OC PDOs were generated from ascites samples representing diverse histological subtypes. Histological and genomic fidelity to parental tumors was confirmed through histopathological analysis and whole-exome sequencing. Drug sensitivity to cisplatin and poly (ADP-ribose) polymerase (PARP) inhibitors was evaluated and correlated with 1-year clinical outcomes. We also investigated the therapeutic efficacy of oncolytic herpes simplex virus 2 (OH2) both as a single agent and in combination with cisplatin. The expression of cancer stem cell (CSC) markers CD44 and ALDH1A1 under treatment conditions was analyzed using immunohistochemistry and flow cytometry. RESULTS: PDOs were successfully established with an 86.2% success rate. These PDOs faithfully recapitulated the histopathological and genomic features of their corresponding tumors, maintaining intratumoral heterogeneity, and were amenable to xenotransplantation. Drug sensitivity assays demonstrated that PDOs accurately predicted patient-specific responses to cisplatin and PARP inhibitors. OH2 exhibited direct cytotoxicity in both cisplatin-sensitive and cisplatin-resistant PDOs, reducing cell viability by 20-60%. Notably, the combination treatment with OH2 and cisplatin enhanced antitumor efficacy, resulting in a significant reduction of the CD44+CSC subpopulation. CONCLUSIONS: Ascites-derived OC PDOs represent a robust platform for individualized drug testing. The combination of OH2 and cisplatin offers a novel and effective strategy for circumventing chemoresistance in OC.

Female↗

PubMed2026

Epigallocatechin gallate is associated with PDGFRB downregulation and altered PI3K-AKT signaling in gastric cancer.

BACKGROUND: Gastric cancer (GC) remains a major cause of cancer-related mortality worldwide. Epigallocatechin gallate (EGCG), a natural polyphenol derived from green tea, exhibits anticancer properties; however, its molecular targets and regulatory mechanisms in GC are not fully elucidated. This study aimed to identify candidate EGCG-associated genes in GC and generate a hypothesis for future mechanistic investigation. METHODS: Differentially expressed genes (DEGs) in GC were identified and intersected with EGCG-associated targets retrieved from The Cancer Genome Atlas (TCGA) and GeneCards public databases. Least absolute shrinkage and selection operator (LASSO) regression and Cox proportional hazards analyses were performed to screen prognostically relevant genes. Diagnostic performance was evaluated using receiver operating characteristic (ROC) curves. Functional enrichment analysis was conducted to explore biological significance. Public single-cell RNA sequencing datasets were analyzed to determine the cellular localization of platelet-derived growth factor receptor beta (PDGFRB), while DepMap transcriptomic data were used to assess its expression across GC cell lines. In vitro assays, 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide (MTT), Transwell migration, and Western blotting, were performed to evaluate the biological effects of EGCG on GC-associated signaling pathways. RESULTS: Thirty-eight EGCG-associated DEGs were identified. Enrichment analysis revealed these genes were involved in cancer-associated pathways. LASSO-Cox modelling identified four candidate genes. Among them, PDGFRB was selected for further investigation based on its prognostic relevance and favorable diagnostic performance. PDGFRB expression was significantly higher in the TCGA genomically stable (GS) subtype than in the other molecular subtypes and was predominantly localized to cancer-associated fibroblasts (CAFs) and pericytes in single-cell RNA sequencing analysis. DepMap data demonstrated heterogeneous PDGFRB expression across GC cell lines. In vitro experiments showed that EGCG inhibited proliferation, migration, and invasion, reduced PDGFRB protein expression, and was associated with apoptosis-related protein changes and altered PI3K-AKT signaling. CONCLUSIONS: Our findings suggest that EGCG treatment was associated with reduced PDGFRB expression and altered PI3K-AKT signaling in GC cells. These findings identify PDGFRB as a candidate EGCG-associated gene and provide a hypothesis for future mechanistic investigation.

Gastric cancer (GC)↗

PubMed2026

The Pathogenesis of Epithelial Ovarian Cancer.

Epithelial ovarian cancer is not a single disease but a group of biologically distinct malignancies that include serous (high-grade and low-grade), endometrioid, clear cell, and mucinous carcinomas, along with other rare subtypes. Integrating clinicopathological analyses, genomic and multiomic data, and experimental investigations in model systems has revealed the pathogenesis of the various histologic subtypes. A unique feature of epithelial ovarian cancer is that most of these tumors are now recognized to arise not from ovarian tissue but from the fallopian tube or endometrium, the latter in the context of ovarian endometriosis. Studies of precursor lesions have revealed complex evolutionary trajectories and the earliest molecular events in their development. Recent single-cell and spatial technologies further elucidate the roles of intratumoral heterogeneity and the tumor microenvironment in disease progression. This review summarizes these advances from the perspective of tissue of origin and highlights their implications for prevention, early detection, and therapeutic development.

Journal Article↗

PubMed2026

Concurrence of antibiotic resistance genes in plasmid genomes shape environmental resistomes.

Horizontal transfer of plasmid-associated antibiotic resistance genes (ARGs) plays a pivotal role in environmental antibiotic resistance dissemination. Here, we characterized ARG concurrence patterns in plasmid genomes and examined plasmid-associated ARGs across 106 environmental metagenomes. Approximately half of known ARG subtypes (257) occurred in plasmid genomes, and nearly one-quarter of plasmids carried ARGs, including "super plasmids" harboring over 20 ARG subtypes spanning 10 antibiotic categories. Aminoglycoside resistance genes (AmRGs) exhibited the highest concurrence frequency (CF) with other ARGs in plasmid genomes, followed by beta-lactam and sulfonamide resistance genes. Many high-risk ARGs preferentially coexisted with AmRGs (45.6% of total AmRGs CF). Environmental metagenomes revealed distinct plasmid-associated ARG profiles between polluted and relatively pristine environments, with significantly greater diversity and abundance under anthropogenic pollution. Five widespread ARG subtypes occurred across all environmental media, whereas polluted environments contained more unique ARGs. Co-occurrence networks identified AmRGs as "hubs" linking multiple ARG subtypes in environmental resistomes. Plasmid-ARG interaction networks further showed more complex potential plasmid-mediated concurrent dissemination in polluted environments. Collectively, use of aminoglycosides is more likely to cause co-transmission of multiple plasmid-related ARGs than other antibiotics, and CF of ARGs is proposed as an important supplementary factor for evaluating ARG dissemination under anthropogenic antibiotic stress.

Antibiotic resistance genes (ARGs)↗

PubMed2026

Expression patterns of potential targets for antibody-directed therapy in metastatic castration-resistant prostate cancer patients.

INTRODUCTION: Survival in metastatic castration-resistant prostate cancer (mCRPC) patients remains limited and treatment is complicated by tumor heterogeneity. As antibody-based therapeutics emerge, identifying actionable antigen targets and patient subgroups most likely to benefit is essential. MATERIALS & METHODS: Gene expression of 62 antibody-targetable proteins was analyzed in 296 mCRPC biopsies. These genes encode proteins targeted by approved or investigational antibody-based cancer therapeutics. Associations between target expression with genomic classifications and transcriptomic subtypes were evaluated. Target expression was also assessed in tumors with low expression of established mCRPC targets. Subgroup-specific targets were validated in an independent cohort and single-cell transcriptomics. RESULTS: Established targets KLK2, FOLH1 (PSMA) and STEAP1 showed the highest median expression across the cohort. Target expression did not correlate with genomic classifications, including homologous recombination deficiency, microsatellite instability, CDK12, TP53, PTEN or AR alterations Target expression did associate with transcriptomic subtypes: CRPC-AR (driven by androgen receptor-signaling) and CRPC-SCL (stem cell-like features, AP-1/YAP/TAZ-driven), displayed the highest expression of multiple targets, including KLK2, FOLH1, and SLC44A4. CRPC-NE (neuroendocrine phenotype) showed heterogeneous expression, with high CD46 expression, whereas CRPC-WNT (Wnt-signaling driven) generally showed low target expression. Notably, CD46 was highly expressed in tumors with low KLK2, FOLH1, and STEAP1 expression, a subgroup associated with poor prognosis. CONCLUSIONS: Although several antibody targets showed broad expression in mCRPC-tumors, expression varied by transcriptomic subtype. Subgroups such as CRPC-WNT expressed fewer targets, suggesting the need for alternative therapeutic strategies. CD46 emerged as a promising target, with wide expression across multiple subtypes, including clinically challenging CRPC-NE and mCRPC tumors lacking expression of established targets.

Humans↗

PubMed2025

A prognostic signature for lung adenocarcinoma in people who have never smoked.

Knowledge of tumor cell dynamics can inform prognosis and treatment yet is largely lacking for lung adenocarcinoma in people who have never smoked (NS-LUAD). With RNA-seq data from 684 NS-LUAD and validation in an independent dataset, we identified three subtypes with distinct phenotypic traits and cell compositions. Additional genomic and histological data further characterized the subtypes. 'Steady', marked by low proliferation, high alveolar cell fraction, moderate-to-well differentiation, and fewer driver genes' alterations, is linked to prolonged survival and low immune evasion. 'Proliferative' shows high proliferation markers, TP53 mutations, and gene fusions. 'Chaotic', with high epithelial-to-mesenchymal transition markers, has the worst prognosis even within stage I tumors. Lacking known molecular or histological characteristics, this aggressive subtype is solely identified by transcriptomic data. A 60-gene signature recapitulates the overall classification and strongly predicts survival even within subgroups based on tumor stage or known genomic features, emphasizing its potential for improving NS-LUAD prognostication in clinical settings.

Journal Article↗

PubMed2026

Anatomical location defines distinct molecular subtypes of mucosal melanoma.

BACKGROUND: Mucosal melanoma (MM) is a rare and aggressive melanoma subtype that is understudied. The relationships between anatomical location, genomic alterations, stage at presentation, and survival remain incompletely characterized. METHODS: We carried out a retrospective single tertiary center study of 105 patients with histologically confirmed MM diagnosed between 1996 and 2025. Clinical and genomic data were analyzed to evaluate associations between anatomical location, mutational profile, stage at presentation, and survival outcomes, including melanoma-specific mortality. RESULTS: Lower-body tumors arising in the anus or genital areas were enriched for KIT and splicing factor 3 subunit B1 alterations, whereas NRAS mutations were distributed across anatomical regions. Among the two most common mutated genes, NRAS-mutant tumors were more likely than KIT-mutant tumors to present with metastatic disease [53% versus 19%; P = 0.046, odds ratio (OR) 4.7, 95% confidence interval (CI) 1.15-19.41]. Lower-body tumors were associated with worse overall survival (OS) than upper-body tumors (median 2.81 versus 8.40 years; OR = 0.05) and with higher melanoma-specific mortality. In multivariable analyses, upper-body location remained independently associated with improved OS (hazard ratio 0.14, 95% CI 0.05-0.36, P < 0.001). CONCLUSIONS: Anatomical location of MMs and genomic alterations define biologically and clinically distinct subtypes.

KIT mutation↗

PubMed2026

Genomic detection of highly pathogenic avian influenza H5N1 in Antarctic seabirds reveals connectivity with South American viral lineages.

Emerging avian viruses increasingly threaten Antarctic wildlife, raising concerns about ecosystem health and biodiversity. In this study, we conducted a comprehensive investigation of avian influenza virus (influenza A virus, IAV) in both resident and migratory birds inhabiting the South Shetland Islands, Antarctica. During the 2024-2025 austral summer, 278 samples were collected and screened using real-time RT-PCR targeting the IAV M gene. IAV RNA was detected in 30 samples, and eight of these were found to be positive for H5. Complete genome sequencing was performed on samples from a gentoo penguin (Pygoscelis papua) and a southern giant petrel (Macronectes giganteus), revealing the presence of highly pathogenic avian influenza virus H5N1, clade 2.3.4.4b. Phylogenetic analysis demonstrated that these viral genomes closely cluster with contemporary South American strains, indicating a direct connectivity between Antarctic seabirds and the broader H5N1 transmission network. Our findings highlight the heightened vulnerability of Antarctic ecosystems to emerging infectious diseases and emphasize the critical need for sustained genomic surveillance. These efforts are essential to monitor wildlife health, inform conservation strategies, and implement effective biosecurity measures to safeguard Antarctic biodiversity.

Animals↗