Biomedical subjects

Yang Yang

Publications and source records attributed to Yang Yang.

At least 19 recordsLinked to original sources

PubMed2026

Sex pheromone communication and its regulation by the sex determination pathway in cockroaches.

Sexual communication in animals orchestrates a series of interactive behaviors from locating and recognizing potential partners to courtship and final mating decisions and is thus critical for sexual reproduction and population fitness. Highly efficient communication between the sexes requires not only the production and emission of species-specific signals but also their precise detection and interpretation by the receiving individuals. Cockroaches, as one of the most evolutionarily ancient and successful group of insects, are quintessential chemical communicators that rely heavily on sex pheromones for sexual communication. They have long served as excellent model organisms in studies of chemical ecology. Although the biochemical characterization of sex pheromones in several species was largely accomplished during the last century, the past two decades have witnessed remarkable progress in understanding the molecular genetics of sex pheromone communication and its regulation, particularly driven by functional genomics. This review first provides an updated comparative survey of the pheromone components identified across distinct taxa. We then synthesize, but not limited to, recent advances in identification of key molecules controlling sex pheromone production, characterization of candidate chemosensory receptors and their neural processing pathways, and the regulatory roles of the sex determination cascade in shaping sexually dimorphic traits in both pheromone production and perception. Finally, we highlight key scientific questions that remain unsolved and propose future directions aimed at extending our mechanistic understanding of cockroach pheromone communication, as well as at developing behavior-based pest management strategies.

biosynthetic pathway↗

PubMed2026

The TANG cluster comprising ten nitrate transporter genes controls fruit sweetness and size in tomato.

Sucrose is a major transport form of photoassimilated carbon in tomato, Arabidopsis, and many other plant species, and plays a critical regulatory role in plant growth, development, and fruit quality. Plant vacuoles function as storage organelles, accumulating substantial quantities of metabolically inactive nitrates as a nitrogen reserve and soluble sugars as a carbon reserve. Consequently, the balance between nitrate and sucrose accumulation determines plant growth dynamics and fruit taste. In this study, we identified a gene cluster designated TANG (Total soluble solidsAccumulation viaNitrate transporterGene cluster), comprising ten nitrate transporter genes that are significantly associated with sucrose accumulation in tomato. This gene cluster mediates the transport of nitrate between the cytoplasm and vacuole, thereby influencing its storage. Functional disruption of TANG8, a member of the gene cluster, results in either enhanced sugar accumulation or increased fruit size. Selective disruption of multiple TANG cluster members yields fruits with elevated sweetness and increased fruit size in S. pimpinellifolium. The interaction between the TANG members and a tonoplast localized Sucrose Transporter 4 provides insight into the competitive accumulation of nitrate and sugar. The multiplex editing of a gene cluster provides a successful example of engineering crops with high quality and yield.

Gene cluster↗

PubMed2026

miR-197 Targets NLRP3 3' UTR and Correlates with NLRP3/Caspase-1/IL-18 Signaling in Hyperoxia-Stimulated Neonatal BPD Mouse Model.

Reduced circulating miR-197 was previously observed in preterm infants who later developed bronchopulmonary dysplasia (BPD), but its relationship with NLRP3 inflammasome signaling remains unclear. This study examined miR-197 expression, NLRP3 inflammasome-related markers, and the interaction between miR-197 and the NLRP3 3' UTR in a neonatal hyperoxia model. Neonatal C57BL/6J mice were exposed to 60% oxygen or room air from birth, and lung tissues were collected on postnatal days 1, 7, 14, and 21. Lung injury and alveolar development were assessed by histology, radial alveolar count, mean linear intercept, and lung wet-to-dry ratio. miR-197 and NLRP3 expression and NF-κB-, caspase-1-, and IL-18-related proteins were evaluated by RT-qPCR and Western blotting. A dual-luciferase reporter assay in MLE12 cells tested the interaction between miR-197 and the NLRP3 3' UTR. Hyperoxia increased lung wet-to-dry ratios and mean linear intercept, reduced radial alveolar count, and caused progressive alveolar simplification. miR-197 expression decreased, whereas NLRP3 mRNA increased, at all examined time points; NLRP3 protein and inflammasome-related protein changes were most evident from postnatal day 7 onward. The miR-197 mimic reduced luciferase activity in the wild-type but not mutant NLRP3 3' UTR reporter. These findings show that neonatal hyperoxia is associated with reduced miR-197 and increased NLRP3/inflammasome-related signaling and support a sequence-specific interaction between miR-197 and the NLRP3 3' UTR, although causal regulation in vivo requires further investigation.

Animals↗

PubMed2026

Comprehensive Evaluation and Explainable Interpretation of Peptide-HLA Binding Prediction Tools.

Accurate prediction of peptide binding to human leukocyte antigen class I (HLA-I) molecules is critical for advancing immunological research, particularly in vaccine design and immunotherapy. However, limitations in model performance, interpretability, and dataset quality impede the widespread adoption of existing predictive tools. Here, we present a comprehensive evaluation of 17 HLA-I peptide binding prediction models, utilizing a meticulously curated dataset comprising over 290,000 peptides spanning 44 HLA-I alleles. We assessed model accuracy, robustness, and interpretability, employing explainability techniques such as SHAP (SHapley Additive exPlanations) and LIME (Local Interpretable Model-agnostic Explanations) to elucidate underlying prediction mechanisms. Our results reveal substantial performance disparities, with self-attention-based models, including STMHCpan and BigMHC, exhibiting superior accuracy. Notably, the capsule network model CapsNet-MHC_AN demonstrated robust performance. Models trained on eluted ligand datasets outperformed those relying on binding affinity data, underscoring the critical role of high-quality training data. Ensemble and multi-algorithm approaches further improved prediction reliability. These findings highlight the need for ongoing innovation in model architecture, integration of diverse and high-quality datasets, and incorporation of structural predictors to develop more accurate, interpretable, and clinically applicable HLA-I peptide binding prediction tools.

HLA-I binding↗

PubMed2026

Spatially resolved multi-omics analysis of indigenous Bacillus-fortified high-temperature Daqu.

Layer-dependent patterns associated with indigenous Bacillus fortification on high-temperature Daqu remain unclear. Here, six indigenous functional Bacillus strains were combined to fortify Daqu at three inoculation levels (QH4, QH5, QH6), with non-fortified as the control (CK). Upper, middle, and lower shelf-layer samples were profiled by physicochemical measurements, volatilomics, organic acid analysis, untargeted metabolomics, 16S/ITS amplicon sequencing, and metagenomics. PERMANOVA showed significant effects of treatment, spatial layer, and their interaction on physicochemical, volatile, bacterial, and fungal profiles (P = 0.001). Among the three inoculation levels, QH5 showed the most balanced performance: QH5_M exhibited the highest observed mean peak temperature (63.3 °C; +4.5 °C relative to CK_M), and its group-mean temperature remained ≥ 60 °C for seven consecutive days. Multi-omics analyses indicated coordinated, non-linear, and layer-dependent differences associated with indigenous Bacillus fortification, with QH5_M showing the most pronounced combined thermal, pyrazine, substrate, microbial, and predicted functional profile. These findings indicate that moderate indigenous Bacillus fortification was associated with distinct layer-dependent thermal and flavor profiles and coordinated microbial, metabolic, and predicted functional differences.

Bacillus↗

PubMed2026

Multidrug resistance and genomic characteristics of nontypeable Haemophilus influenzae isolates from the respiratory tract of pediatric patients.

UNLABELLED: Nontypeable Haemophilus influenzae (NTHi) is a common colonizer of the human upper respiratory tract and one of the major pathogens responsible for pediatric respiratory tract infections. Given the increasing severity of its multidrug resistance (MDR), this study comprehensively investigated the genomic characteristics of circulating NTHi isolated from sputum and bronchoalveolar lavage fluid (BALF). A total of 104 H. influenzae isolates (69 from sputum; 35 from BALF) were collected from pediatric patients between January 2024 and January 2025. All isolates underwent whole-genome sequencing and antimicrobial susceptibility testing, followed by core/pan-genome phylogenetic analysis, multilocus sequence typing (MLST), and resistome profiling. Among them, 103 were identified as NTHi. We identified 29 known sequence types (STs) and 10 novel STs, with ST-107 (14.4%), ST-57 (10.6%), and ST-11 (8.7%) being the major circulating lineages. However, core-genome phylogenetic analysis provided a more granular view of the genetic variation within these identical STs. All the isolates showed high resistance to ampicillin (98.1%) and cefuroxime (84.6%). Genomically, the multidrug efflux pump gene hmrM was ubiquitous (100%). Ampicillin resistance was predominantly driven by blaTEM-1 carriage (77.9%), with minor contributions from chromosomal ftsI mutations. Fifteen plasmid replicons were predicted from 25 isolates, which highly coincided with the carriage of blaTEM-1 and other acquired resistance genes. This study demonstrates that MDR in pediatric NTHi is primarily driven by acquired resistance genes and chromosomal mutations, with specific resistant clones persisting and enriching under clinical antibiotic pressures. These findings underscore the importance of continuous high-resolution genomic surveillance in guiding rational antibiotic stewardship. IMPORTANCE: This study highlights the critical importance of high-resolution genomic surveillance in managing pediatric nontypeable Haemophilus influenzae (NTHi) infections. By utilizing whole-genome sequencing, we uncovered the pathogen's highly dynamic population structure and complex multidrug resistance (MDR) mechanisms. Crucially, our findings reveal a strong, non-random coupling between core genomic architectures, virulence factors, and MDR elements, driven by dual environmental and pharmacological pressures. This "virulence-MDR" co-evolutionary trend underscores the persistent clinical threat of locally adapted high-risk clones. These findings provide important insights for guiding rational clinical antibiotic stewardship, optimizing treatment strategies, and improving regional infection control.

Humans↗

PubMed2026

Cross-tissue Mendelian randomization prioritizes RAB27B as a brain-derived candidate protein for postpartum depression.

OBJECTIVE: Postpartum depression (PPD) is one of the most common and debilitating complications of childbirth, yet the candidate proteins linking genetic risk to disease remain poorly defined. Building on recent genome-wide association studies (GWAS), we sought to integrate cross-tissue proteogenomic data to identify candidate proteins for PPD and explore therapeutic opportunities. METHODS: We conducted two-sample Mendelian randomization (MR) using genome-wide significant cis-protein QTLs from brain (n = 608 proteins), cerebrospinal fluid (CSF; n = 214), and plasma (n = 612). PPD summary statistics were obtained from FinnGen R8 (13,657 cases, 236,178 controls) and replicated in an independent GWAS. Phenome-wide association (PheWAS) was used to assess pleiotropy. Potential therapeutic targets were evaluated through DSigDB drug repurposing, molecular docking, and molecular dynamics simulations. RESULTS: Among all proteins tested, RAB27B was the only brain-derived protein surpassing Bonferroni correction (OR = 1.60; 95% CI: 1.30-1.96; P = 6.6 × 10⁻⁶), whereas no significant proteins were identified in CSF or plasma. This association was replicated in an independent GWAS (OR = 1.27; 95% CI: 1.02-1.58; P = 0.037). PheWAS identified no pleiotropic associations at genome-wide significance. In silico drug repurposing identified pregnenolone as a candidate ligand with computationally predicted stable binding to RAB27B, providing a starting point for future experimental validation. CONCLUSION: This study provides the first cross-tissue proteogenomic evidence that RAB27B is a brain-derived, reproducible candidate protein genetically associated with PPD. By extending GWAS signals to functional protein-level mechanisms and therapeutic inference, our findings nominate RAB27B and pregnenolone as promising directions for postpartum psychiatric research.

Humans↗

PubMed2026

Dynamic balance of CRISPR-Cas immunity and resistance plasmid anti-immunity mediated by a bifunctional protein AcrIE10.

Despite targeting by CRISPR-Cas system, antimicrobial resistance plasmids are prevalent in clinical isolates of carbapenem-resistant Klebsiella pneumoniae which represent a major public health threat. A stable co-existence of plasmids and CRISPR-Cas systems is mediated by anti-CRISPR (Acr) proteins. Here, we report that previously identified AcrIE10 encoded by a resistance plasmid combines two functions: it inhibits CRISPR immunity by directly binding Cas7* subunit through its Acr domain, and acts as an Acr-associated (Aca) protein that self-represses the transcription of Acr locus. AcrIE10 is an example of an Aca protein that utilizes N-terminal ribbon-helix-helix (RHH) domain to specifically recognize the inverted repeat (IR) region in its own promoter. Crucially, a dimerization of AcrIE10 dimers is required for the effective binding to the IR and self-repression, while stoichiometry-dependent interaction with Cas7* facilitates transition to de-repressed state. These findings elucidate molecular mechanisms by which AcrIE10 operates as a dual functionAcr-Aca protein to achieve a delicate balance between host CRISPR-Cas immunity and plasmid anti-defense.

Klebsiella pneumoniae↗

PubMed2026

Exercise-induced chronic adaptations and pro-inflammatory cytokine levels (IL-1β, IL-6, and TNF-α) in patients with depression: A systematic review and exploratory meta-analysis of randomized controlled trials.

BACKGROUND: Depression is a leading cause of disability worldwide. Although exercise has been shown to alleviate depressive symptoms, potentially by affecting the body's inflammatory response, evidence in this area remains inconsistent. This study synthesized the most recent evidence from randomized controlled trials (RCTs) on the relationship between exercise-induced chronic adaptations and pro-inflammatory cytokine levels in patients with depression. METHODS: Eligible RCTs were identified from six electronic databases. Effect sizes were pooled using mean differences (MDs) and standardized mean differences (SMDs) with 95% confidence intervals (CIs). Two independent researchers assessed the certainty of evidence using the Grading of Recommendations, Assessment, Development, and Evaluation (GRADE) guidelines. RESULTS: The review included 21 RCTs involving 1572 participants, six of which were included in the meta-analysis. No evidence of efficacy was observed for the chronic effects of exercise on the levels of the pro-inflammatory cytokines interleukin-1-beta (IL-1β) (MD = -0.01, 95% CI [-0.06, 0.04], p = 0.79), interleukin-6 (IL-6) (SMD = -0.30, 95% CI [-0.64, 0.04], p = 0.08), and tumor necrosis factor-alpha (TNF-α) (SMD = -0.18, 95% CI [-0.50, 0.14], p = 0.27) in patients with depression. However, the pooled results for certain markers were not robust. The certainty of evidence for each outcome was very low owing to inconsistency, indirectness, and imprecision. CONCLUSIONS: Evidence for exercise improving pro-inflammatory cytokine levels in patients with depression during the chronic phase remains exploratory and uncertain. Well-designed, adequately powered studies incorporating a broader range of immune biomarkers and dynamic multi-time-point assessments are urgently needed to determine whether exercise-induced chronic adaptations can modulate inflammatory pathways in depression.

Humans↗

PubMed2026

Pan-cancer analysis identifies APOC1 as a TAM-derived modulator of adaptive immune resistance and predictor of therapeutic response.

BACKGROUND: Apolipoprotein C1 (APOC1) has been implicated in several malignancies, yet its expression patterns, clinical significance, and immunomodulatory roles across cancer types remain poorly characterized. METHODS: We performed a comprehensive multi-omic analysis of APOC1 across 33 cancer types integrating transcriptomic, proteomic, genomic, epigenomic, and pharmacogenomic data from TCGA, GTEx, CPTAC, and multiple independent external cohorts. Immune infiltration was assessed using seven complementary algorithms. Spatial transcriptomics and single-cell RNA sequencing were employed to determine the cellular source of APOC1 expression. RESULTS: APOC1 upregulation in most cancers was associated with cancer type-specific prognosis. After adjustment for clinical covariates and macrophage infiltration, high APOC1 remained an independent adverse factor in KIRC, LGG, and STAD. APOC1 expression positively correlated with genomic instability hallmarks, including homologous recombination deficiency and aneuploidy, with these associations largely independent of immune infiltration; in contrast, associations with tumor mutational burden were substantially confounded by macrophage abundance. Immune infiltration analysis revealed a pattern consistent with adaptive immune resistance: APOC1 correlated positively with immune-activating signatures (STAT1, MHC-II, TCR signaling) and immunosuppressive M2 macrophages and Tregs, yet negatively with anti-tumor effectors (activated NK cells, dendritic cells). Spatial transcriptomics and single-cell RNA sequencing identified tumor-associated macrophages (TAMs) as the primary cellular source of APOC1, with transcripts co-localizing with CD68 in tissue sections. APOC1 expression correlated with multiple immune checkpoint molecules and was elevated in responders to immune checkpoint blockade, consistent with an inflamed yet regulated tumor microenvironment. Pharmacogenomic analyses revealed that APOC1-high tumors display distinct drug response profiles, characterized by resistance to MAPK pathway inhibitors and potential sensitivity to the HDAC inhibitor Entinostat. CONCLUSION: This pan-cancer analysis establishes APOC1 as a context-dependent biomarker and a TAM-derived modulator of adaptive immune resistance, with prognostic and therapeutic implications across malignancies. APOC1-expressing TAMs represent a potential target for combination immunotherapy strategies.

APOC1↗

PubMed2026

Cefiderocol susceptibility rates in carbapenem-resistant Gram-negative bacteria in a comparative, multicenter surveillance study in China.

BACKGROUND: Cefiderocol is a siderophore cephalosporin with potent, broad spectrum of activity against carbapenem-resistant (CR) Gram-negative bacteria. The objective of this surveillance study was to assess cefiderocol susceptibility in molecularly characterized CR Gram-negative pathogens collected from hospitalized patients across China. METHODS: Susceptibility testing was performed by the broth microdilution method according to Clinical and Laboratory Standards Institute guidelines, using pre-prepared frozen 96-well microtiter Thermo Fisher plates. Susceptibilities to cefiderocol and most comparators were determined by Clinical and Laboratory Standards Institute breakpoints, to tigecycline by US Food and Drug Administration breakpoints, and to colistin by European Committee on Antimicrobial Susceptibility Testing criteria. Carbapenemases were identified by whole-genome sequencing and polymerase chain reaction. RESULTS: Of 149 CR Klebsiella pneumoniae, 95.3% were susceptible to cefiderocol (OXA-48-positive 100% [n = 15]; IMP-positive 100% [n = 9]; KPC-positive 95.4% [n = 108]; NDM-positive 88.2% [n = 17]) and against 103 NDM-positive CR Escherichia coli, cefiderocol susceptibility was 45.6%. Among comparator antibiotics, ceftazidime-avibactam was only active against K. pneumoniae carbapenemase-positive and OXA-48-positive K. pneumoniae isolates. Susceptibilities to tigecycline and colistin were between 22.2% and 97.1% and between 88.2% and 100% across CR Enterobacterales with different carbapenemases, respectively. High cefiderocol susceptibility rates were found for CR Pseudomonas aeruginosa (98.4%), CR Acinetobacter baumannii (99.6%), and Stenotrophomonas maltophilia (99.6%). Among comparator antibiotics, only colistin showed high activity against CR P. aeruginosa (99.2%) and CR A. baumannii (99.2%). CONCLUSIONS: Cefiderocol susceptibility rates were ≥88% against a collection of carbapenemase-positive CR Gram-negative isolates, except for lower susceptibility in NDM-positive CR E. coli isolates. Continuous monitoring of cefiderocol susceptibility is warranted.

Cefiderocol↗

PubMed2026

EPIC: multi-objective guided diffusion for epitope design in TCR-pMHC complexes.

MOTIVATION: T cell receptor (TCR) recognition of peptide-major histocompatibility complex (pMHC) complexes is central to adaptive immunity, yet rational design of immunogenic epitopes remains elusive due to complex triplet binding constraints and data scarcity. No existing method can generate epitopes satisfying simultaneous requirements for antigenicity, MHC presentation, and TCR specificity. RESULTS: We present EPIC, a multi-objective diffusion framework that decomposes TCR-pMHC binding into three biologically grounded sub-tasks, enabling training-free gradient guidance without end-to-end retraining. By integrating ESM-based classifiers with a peptide diffusion generator, EPIC leverages heterogeneous immunological interaction datasets to generate diverse, context-aware epitopes. EPIC-designed top-three epitopes achieve lower predicted interface energies compared to ground-truth epitopes in 78.31% of test cases, while maintaining 80.1% sequence novelty and comparable structural confidence. Generated epitopes exhibit 100% uniqueness, high diversity (64.05%), and high antigenicity scores (0.4723). To our knowledge, EPIC is the first computational framework capable of de novo epitope design while explicitly integrating the triplet constraints of TCR-pMHC binding. This paradigm shift from discovery to design unlocks new potential for personalized cancer vaccines, precision adoptive T cell therapy, and rapid response to emerging infectious diseases. AVAILABILITY AND IMPLEMENTATION: The source code of EPIC is available at https://github.com/Octopus125/EPIC and archived on Zenodo (DOI: 10.5281/zenodo.18537646).

Receptors, Antigen, T-Cell↗

PubMed2026

Widespread Molecular Imprints in the Serum Proteome of COVID-19 Convalescents Uncovering Immune System Sequelae.

Post-COVID-19 sequelae have become an emerging global health issue, but the mechanisms for the sustained susceptibility of convalescents to the sequelae remain poorly understood. Here we report the use of a restricted open-search approach to explore the molecular imprints of SARS-CoV-2 infection left on the proteome of 412 COVID-19 patients and convalescences. A total of 827 non-standard amino acid variations, chemically modified residues as well as post-translational modifications, termed non-coded amino acids (ncAAs), are found spreading over 29,814 sites in patient's serum proteins. Markedly, widespread ncAAs are induced and sustainedly imprinted on the serum proteome predominately perturbing the immunoglobulin-mediated immune response, complement activation and coagulation regulation even 12 months after recovery. Sustained amino acid variations and chemical modifications are found in the complementary‑determining regions (CDRs) of the variable region of immunoglobulin contributing to the interactions between the emerging antibody and antigens; durable chemical amino acid modifications found in the hyper ncAA-modified regions of the constant region of immunoglobulin important for the interaction with the complement and regulatory receptors. In the complement system, inducible ncAAs are memorized in the components essential for the complement activation, amplification cascades and membrane attack processes. Thus, the workflow described in this study can be used to identify the molecular imprints of viral infection at the proteomic scale, particularly the specific antibodies and the immune targets left in COVID-19 patients and convalescents.

Humans↗

PubMed2026

Deep learning-based multimodal pathogenomics integration for precision cancer prognosis.

BACKGROUND: Recent studies have revealed valuable prognostic insights in haematoxylin and eosin (H&E)-stained histological sections and transcriptomic profiles, suggesting potential applications in machine learning. However, existing methods lack sufficient intra- and inter-modal interactions, and face challenges in clinical validation due to incomplete multimodal data. METHODS: We proposed PathoGems (PathoGenomics-based integrative survival prediction), a weakly-supervised, interpretable multimodal learning framework that integrates histology and genomic profiles for precise cancer prognosis prediction. To evaluate the robustness of PathoGems, we initially curated a dataset of 1965 cases across four cohorts from The Cancer Genome Atlas (TCGA), including breast, colorectal, glioblastoma, and esophageal cancers. For external validation, PathoGems was further evaluated on four independent cohorts, consisting of 76 breast cancer and 41 esophageal squamous cell carcinoma cases from Zhejiang Cancer Hospital, as well as 102 colorectal cancer and 58 glioblastoma cases from the Clinical Proteomic Tumor Analysis Consortium (CPTAC). RESULTS: PathoGems effectively stratified patients into favorable and unfavorable risk groups, revealing significant differences in histological patterns, genomic features, and overall survival (log-rank test, p < 0.05). Moreover, the model’s predictions are further supported by visualization and transcriptomic analysis, enhancing interpretability and reliability. CONCLUSIONS: By fusing histological and clinicogenomic multimodal models, PathoGems will provide a solid foundation for developing an innovative tool that aids clinicians in making informed decisions and selection personalized treatment strategies for cancer patients.

Humans↗

PubMed2025

Panorama of Chromosomal Instability in Lung Cancer.

Lung cancer is a highly heterogeneous disease primarily driven by tobacco smoking. About 20% of lung cancers occur among patients who have never smoked (LCINS) with differences in patient ancestry, sex, tumor histology, and clinical features. Our understanding of chromosomal instability in lung cancer, especially LCINS, is still limited. Here, we perform a comprehensive study of 182,429 somatic structural variations (SVs) detected in 1,209 whole-genome sequenced lung cancers, of which 864 LCINS. SVs are more abundant in tumors from patients who have smoked (LCSS); however, they are more complex and play more important roles in tumorigenesis in LCINS. EGFR mutations and KRAS mutations profoundly and independently shape the SV landscape. EGFR-mutant tumors have higher SV burden and more cancer-driving SVs. In contrast, KRAS mutations are associated with lower SV burden and less driver SVs. We decompose 16 SV signatures for both complex and simple SVs that likely represent divergent molecular mechanisms. The SV breakpoints have distinct distributions across the genome depending on the signatures due to mutagenic mechanisms and positive selection. Many established cancer-driving genes are recurrently rearranged by multiple SV signatures suggesting functional convergence of these genome instability mechanisms.

Journal Article↗

PubMed2025

Stratifying Lung Adenocarcinoma Risk with Multi-ancestry Polygenic Risk Scores in East Asian Never-Smokers.

BACKGROUND: Lung adenocarcinoma (LUAD) in never-smokers is a major public health burden, especially among East Asian women. Polygenic risk scores (PRSs) are promising for risk stratification but are primarily developed in European-ancestry populations. We aimed to develop and validate single- and multi-ancestry PRSs for East Asian never-smokers to improve LUAD risk prediction. METHODS: PRSs were developed using genome-wide association study summary statistics from East Asian (8,002 cases; 20,782 controls) and European (2,058 cases; 5,575 controls) populations. Single-ancestry models included PRS-25, PRS-CT, and LDpred2; multi-ancestry models included LDpred2+PRS-EUR128, PRS-CSx, and CT-SLEB. Performance was evaluated in independent East Asian data from the Female Lung Cancer Consortium (FLCCA) and externally validated in the Nanjing Lung Cancer Cohort (NJLCC). We assessed predictive accuracy via AUC, with 10-year and (age 30-80) absolute risks estimates. RESULTS: The best multi-ancestry PRS, using East Asian and European data via CT-SLEB (clumping and thresholding, super learning, empirical Bayes), outperformed the best East Asian-only PRS (LDpred2; AUC=0.629, 95% CI:0.618,0.641), achieving an AUC of 0.640 (95% CI:0.629,0.653) and odds ratio of 1.71 (95% CI:1.61,1.82) per SD increase. NJLCC Validation confirmed robust performance (AUC =0.649, 95% CI: 0.623, 0.676). The top 20% PRS group had a 3.92-fold higher LUAD risk than the bottom 20%. Further, the top 5% PRS group reached a 6.69% lifetime absolute risk. Notably, this group reached the average population 10-year LUAD risk at age 50 (0.42%) by age 41, nine years earlier. CONCLUSIONS: Multi-ancestry PRS approaches enhance LUAD risk stratification in East Asian never-smokers, with consistent external validation, suggesting future clinical utility.

East Asian never smokers↗

PubMed2025

Midkine attenuates amyloid-β fibril assembly and plaque formation.

Proteomic profiling of Alzheimer disease (AD) brains has identified numerous understudied proteins, including midkine (MDK), that are highly upregulated and correlated with amyloid-β (Aβ) from the early disease stage but their roles in disease progression are not fully understood. Here, we present that MDK attenuates Aβ assembly and influences amyloid formation in the 5xFAD amyloidosis mouse model. MDK protein mitigates fibril formation of both Aβ40 and Aβ42 peptides according to thioflavin T fluorescence, circular dichroism, negative-stain electron microscopy and nuclear magnetic resonance analyses. Knockout of the Mdk gene in 5xFAD increased amyloid formation and microglial activation in the brain. Further comprehensive mass-spectrometry-based profiling of the whole proteome and detergent-insoluble proteome in these mouse models indicated significant accumulation of Aβ and Aβ-correlated proteins, along with microglial components. Thus, our structural and mouse model studies reveal a protective role of MDK in counteracting amyloid pathology in AD.

Animals↗

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↗