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PubMed2026

Protein sorting and proteostasis mechanisms in CFTR-related exocrine pancreas dysfunction: A systematic narrative review.

The pancreas consists of exocrine and endocrine compartments. In the exocrine pancreas, cystic fibrosis transmembrane conductance regulator (CFTR) functions mainly in ductal epithelial cells as a chloride and bicarbonate channel. Its activity depends on proper protein folding, trafficking, and localization to the apical membrane. This systematic narrative review aims to synthesize the available evidence on the role of protein sorting machinery in CFTR channelopathies and its contribution to exocrine pancreatic dysfunction. A thorough search was conducted using PRISMA criteria on PubMed, Wiley Online Library, and Scopus for studies published in English between January 2000 and November 2025. Twenty studies that met the inclusion criteria were included in this review. Pathogenic CFTR variants impair protein folding, endoplasmic reticulum (ER) exit, and endosomal recycling, resulting in reduced apical membrane expression and stability. These defects disrupt the localization of associated transporters and secretory proteins, impair ductal bicarbonate secretion, alter zymogen handling, and promote acinar injury, although these claims are supported mainly by indirect experimental models and therefore require clinical confirmation. CFTR channelopathies in the exocrine pancreas encompass both ion transport defects and broader disruptions of protein sorting machinery. CFTR may contribute to the assembly, stabilization, or localization of selected apical transport complexes, and its loss can secondarily alter epithelial organization. Therapeutic approaches targeting both channel correction and intracellular trafficking may improve pancreatic function and mitigate disease progression.

Humans↗

PubMed2026

A systematic review of human avoidance learning: Cognition, computation, and methods.

Avoidance behaviour is fundamental for survival but can become maladaptive in clinical conditions. A large body of literature has accumulated on the dynamics of human avoidance learning. However, current theories and overviews do not provide an exhaustive account of this evidence. In this systematic review, we identify N = 116 studies on human avoidance learning. We analyse these studies with the goal of distilling robust empirical phenomena as a basis for theory-building, and examine their diagnostic value in differentiating between competing theories. We find that the evidence is difficult to reconcile with foundational two-factor and classical safety-signal accounts, and most strongly supports expectancy- and inference-based views, in which avoidance responses are selected with respect to represented consequences. At the same time, no current framework provides a complete account of the evidence: several findings point to an additional role for operant valuation, Pavlovian influences, and contextual or latent-state control over the expression of avoidance. Methodologically, we observe that the problem setting in the most common experimental paradigms is radically simpler than real-world avoidance and therefore unlikely to expose the limits of inferential or reflective mechanisms. Consequently, we argue that paradigms with greater computational demands and more realistic action affordances are required to identify the mechanisms underlying avoidance learning. Collectively, these insights provide a foundation for theoretical refinement, computational modelling, and methodological innovation, with implications for advancing interventions targeting maladaptive avoidance.

Humans↗

PubMed2026

Association between packed red blood cell transfusion and clinical deterioration in neonatal necrotizing enterocolitis: a systematic review and meta-analysis.

BACKGROUND: No systematic review has evaluated the existing evidence regarding the association between packed red blood cell (pRBC) transfusion and clinical worsening of necrotizing enterocolitis (NEC) in neonates. This systematic review and meta-analysis was conducted to address this knowledge gap. MATERIALS AND METHODS: We searched the Cochrane Library, EBSCO, Embase, Web of Science, Google Scholar, and PubMed for studies on pRBC transfusion and NEC published before May 10, 2025. Relevant articles were selected through title, abstract, and full-text screening. English-language case-control studies or cohort studies, or randomized controlled trials involving newborns with NEC that compared pRBC transfusion with no transfusion and reported changes in NEC clinical status were included. Review articles, systematic reviews, case reports, editorials, animal studies, duplicate publications, and studies with incomplete data were excluded. RESULTS: Five studies involving 971 neonates with NEC were included. The pooled analysis demonstrated a potential association between pRBC transfusion and clinical deterioration of NEC in neonates (odds ratio: 6.05, 95% confidence interval: 3.02-12.14). CONCLUSIONS: pRBC transfusion was associated with an exacerbation of NEC in neonates. However, these findings should be interpreted cautiously because of the small number of eligible studies included in this meta-analysis, and future large-scale, well-designed studies are needed to confirm the observed association.

Humans↗

PubMed2026

Targeted variant analysis of feline mediastinal lymphoma using MassARRAY and clinical associations.

Lymphoma is the most commonly diagnosed cancer in cats. This study used the Agena MassARRAY to genotype 40 variants across 17 genes in feline mediastinal lymphoma. These variants have previously been identified in tumors, including T- and B-cell lymphomas, acute and chronic lymphocytic leukemias, and mast cell tumors, in humans, dogs, and cats, using various methods. They were selected based on high prevalence reported in prior oncology studies, potential relevance to targeted therapy, and suitability for multiplex PCR amplification. Pleural fluid samples were collected from 76 cats with mediastinal lymphoma, including 69 domestic shorthairs, two Persians, two Siamese, two Wichienmaat, and one Scottish Fold. The most prevalent variants were found in the BCL2, KIT, STAT3, and ZEB1 genes. Specifically, BCL2 c.83275986G > A and c.83275992G > T were present in 71.1% and 57.9%, respectively. In cats with variant-positive in KIT c.163965724C > CT significantly reduced (11 days) compared to wild-type cats (94 days) (p < 0.001). In cats with variant-positive in STAT3 c.42942437C > CA, resulted in shorter median survival compared to wild-type cats (18 days vs. 77 days, p = 0.006). The findings suggest that the variant panel could be useful for the genomic landscape of feline mediastinal lymphoma and warrant further validation.

Animals↗

PubMed2026

Comparative genomics and full-length transcriptome profiling of wing morphs in Tetrix grossus (Orthoptera: Tetrigidae).

Wing polymorphism represents a paradigmatic dispersal-reproduction trade-off, yet its molecular basis remains uncharacterised in the phylogenetically distant pygmy grasshoppers (Tetrigidae). Here we integrate comparative genomics across ten orthopteran species with full-length transcriptomics of long-winged (FL) and short-winged (FS) Tetrix grossus. OrthoFinder recovered 118 orthogroups specific to T. grossus. Against a backdrop of pronounced gene-family contraction (36 expansions versus 222 contractions; net -186, mirrored at the ancestral Tetrix node, +37/-140), we identified an ancestral, Tetrix-specific expansion of hormone-regulation (12 genes; fold enrichment 7.93) and lipid/carbohydrate-metabolic families organised into syntenic clusters, alongside 513 positively selected genes enriched for integrin-mediated cell adhesion (6 genes), a process relevant to epithelial and appendage morphogenesis. Full-length transcriptomics of one long-winged (FL) and one short-winged (FS) adult female detected 7530 (FL) and 7515 (FS) expressed genes, with 794 FL- and 776 FS-restricted transcriptome-derived SNP-associated genes. The FL morph was enriched for an EGFR/Ras-Rho developmental-patterning axis and neuromuscular flight genes, whereas the FS morph was enriched for insulin/peptide-hormone response and growth-regulatory loci. Overall, we present genomic resources and testable hypotheses concerning the evolution and regulation of wing morphs in Tetrigidae rather than a validated genetic architecture of wing-morph determination.

Animals↗

PubMed2026

Parallel evolutionary trajectories rewire enteropathogenic Escherichia coli adhesion to restore host attachment.

Enteropathogenic Escherichia coli (EPEC) causes disease in children, presenting as chronic diarrhea that can impair physical and cognitive development. The attachment of typical EPEC (tEPEC) to the gut epithelium via bundle-forming pili (BFP) is a key factor in its virulence. Yet, infections by atypical EPEC (aEPEC), which lack BFP, have become increasingly common. To investigate how aEPEC recover host-attachment in the absence of BFP, we performed experimental evolution using a non-adherent E. coli, constructed to mimic the ancestor of aEPEC, and selected adherent progeny. Highly adherent variants evolved through phase-variable activation of type I fimbriae (T1F), followed by two alternative trajectories: bacterial filamentation, which increases T1F avidity, or point mutations in the T1F adhesin FimH that enhance ligand affinity. Extending our analysis to the genomes of 327 aEPEC strains isolated from infected patients revealed that similar FimH mutations are common. We further demonstrated experimentally that these naturally occurring variants often increase epithelial-attachment. Our findings implicate T1F in aEPEC pathogenesis and suggest it may be clinically relevant for anti-adhesion therapy. More broadly, these results indicate that impaired host-attachment can be rapidly compensated by upregulating and optimizing an alternative adhesin, and that combining experimental evolution with comparative genomics can reveal evolutionary trajectories occurring in nature.

Bacterial Adhesion↗

PubMed2026

Comparative genomic and proteomic analysis reveals orthogroup structured evolution of tick protease inhibitors.

Protease inhibitors (PIs) play central roles in regulating endogenous proteolysis and host-parasite interactions in ticks. However, the evolutionary architecture underlying their diversification across tick lineages remains insufficiently resolved. Here, we performed a genome-wide comparative analysis of predicted proteomes from 14 tick species to systematically characterize PI repertoires. In total, 4931 putative PIs were identified and grouped into 20 families using the MEROPS classification system. Further, PI families such as Antistasin, WAP-type, and Pacifastin, which have not previously been systematically reported in tick genomes, were classified. Orthogroup inference demonstrated that PI expansion is structured at the level of evolutionary lineages rather than uniformly across families. By stratifying orthogroups according to duplication burden and taxonomic conservation, we identified a broadly conserved single-copy core under strong purifying selection. Motif level analysis of serpin reactive center loops further revealed conservation of inhibitory specificity within single copy orthogroups and diversification of key functional residues in duplication-associated lineages. Integration of secretion prediction and tissue-resolved proteomics from Hyalomma anatolicum and Rhipicephalus microplus demonstrated that evolutionary stratification is reflected at the protein level. Together, these findings provide an orthogroup-resolved evolutionary framework linking duplication dynamics, molecular evolution, and tissue-level protein deployment. This integrative approach offers a systematic basis for prioritizing conserved and diversified PI lineages for future functional and anti-tick intervention studies.

Animals↗

PubMed2026

Characterizing Caregiver-Child Interactions Through a Transactional Lens: A Baseline Analysis of a Caregiver-Implemented Intervention.

PURPOSE: This study was motivated by the transactional model of development and examined the reciprocal influences that children and caregivers have on caregiver-child interactions (CCXs) prior to a caregiver-implemented intervention. We tested whether child communication characteristics were associated with caregiver strategy use and whether these strategies, in turn, influenced children's communication to understand how caregivers and children mutually shaped the language learning environment. METHOD: Caregiver-child dyads (N = 105) were participants in a randomized controlled trial. CCXs were collected when children were approximately 30 months of age, transcribed, and coded for four caregiver language facilitation strategies and child communication variables. RESULTS: Least Absolute Shrinkage and Selection Operator regression and postselection inference indicated that child communication characteristics in CCXs were associated with both the frequency and type of strategies caregivers used. Children's overall communication acts were significantly associated with caregiver use of vocabulary strategies, whereas children's vocabulary diversity was significantly associated with caregiver use of sentence strategies. Mixed-effects logistic regression demonstrated that all four caregiver strategies significantly increased the likelihood of spontaneous lexical overlap in subsequent child turns. CONCLUSIONS: Prior to the intervention, caregivers and children reciprocally shaped the language environment. This supports a transactional perspective and warrants further consideration of reciprocal influences when assessing the impact of caregiver-implemented interventions. SUPPLEMENTAL MATERIAL: https://doi.org/10.23641/asha.32995796.

Humans↗

PubMed2026

Molecular mechanisms of neuroendocrine regulation of molting in the Chinese mitten crab (Eriocheir sinensis): A transcriptomic analysis based on eyestalk ablation model.

Molting disability severely restricts the sustainable aquaculture of the Chinese mitten crab, yet the neuroendocrine mechanisms coordinating physiological responses remain poorly understood. Using unilateral eyestalk ablation to remove the primary source of molt-inhibiting hormone (MIH), we performed time-resolved transcriptomic profiling of the thoracic ganglion at 24 h (early premolt) and 48 h (ecdysis) post-ablation. We identified 2825 differentially expressed genes and uncovered a biphasic molecular response. At 24 h, the thoracic ganglion activates pathways associated with neuromuscular adaptation, oxidative stress, and cardiac muscle contraction. Notably, the arachidonic acid metabolism pathway is selectively rewired: cytochrome P450 ω-hydroxylases (CYP2J2, CYP4V2) are upregulated, while competing branches (epoxide hydrolase, cyclooxygenase) are suppressed, promoting local synthesis of the potent vasoconstrictor 20-HETE within the thoracic ganglion. This enzymatic switch provides a mechanistic link between MIH withdrawal and the local generation of elevated hemolymph pressure required for molting. By 48 h, the transcriptional program shifts toward chitin-based extracellular matrix remodeling, glycosphingolipid biosynthesis, and synaptic reorganization. Collectively, our findings redefine the thoracic ganglion as an active neuroendocrine integrator that translates reduced MIH signaling into phased physiological outputs, revealing a "neuro-endocrine-hemolymph pressure" regulatory axis. This study provides novel molecular targets (e.g., CYP2J2, CHS1, UGCG) for mitigating molting disability in E. sinensis aquaculture.

Animals↗

PubMed2026

Unveiling the power of TIIC: A prognostic tool for esophageal adenocarcinoma.

BACKGROUND: Esophageal adenocarcinoma (EAC) remains a lethal malignancy with limited prognostic tools for guiding immunotherapy. Tumor-infiltrating immune cells (TIICs) play a critical role in EAC prognosis and treatment response. METHODS: We integrated single-cell RNA sequencing and bulk transcriptome data from TCGA and GEO databases. TIIC-specific RNAs were identified via tissue specificity index calculation combined with machine learning feature selection. Twenty machine learning algorithms were benchmarked to construct an optimal TIIC signature score (TIIC-Score) based on the comprehensive C-index. Immunotherapy response, genomic mutation, and copy number variation were analyzed. Summary-data-based Mendelian randomization (SMR) and two-sample Mendelian randomization (MR) were performed to explore genetic associations. Core prognostic TIIC-related genes were functionally validated in esophageal cancer cell lines through loss-of-function assays. RESULTS: The TIIC-Score demonstrated robust prognostic value for 1-, 2-, and 3-year overall survival across multiple cohorts, outperforming 22 published models. High TIIC-Score was associated with poor survival and increased chromosomal instability. Mutation profiling revealed high frequencies of TP53 (78.2%), TTN (48.7%), and SYNE1 (30.8%). MR analysis identified a significant association between gastro-oesophageal reflux and EAC risk at SNP rs8130507. Functionally, CCNI was upregulated in esophageal cancer cells, and its knockdown suppressed malignant phenotypes while promoting apoptosis, supporting its pro-tumorigenic role. CONCLUSION: The TIIC-Score provides a novel prognostic framework for EAC that effectively stratifies patient risk and may help identify individuals most likely to benefit from immunotherapy.

Esophageal adenocarcinoma↗

PubMed2026

Artificial intelligence in treatment prediction for skeletal Class III malocclusion: A systematic review.

In skeletal Class III patients, treatment options range from orthodontics to orthognathic surgery. Choosing the optimal approach requires a comprehensive clinical evaluation, which may be supported by AI tools. The aim of this study was to assess the performance of AI models in predicting the need for orthognathic surgery and in identifying predictors influencing treatment decisions. A PRISMA-guided electronic database search (PubMed, Web of Science; 2009-2024; English/French) was performed to identify studies using machine learning (ML) or deep learning (DL) on cephalometric and clinical data. After screening and assessment for eligibility, 15 studies were critically appraised. Model performance was summarized using accuracy, sensitivity, specificity, and the area under the curve (AUC). ML algorithms (particularly Random Forest and XGBoost) and DL models (ResNet-based convolutional neural networks (CNNs)) achieved high accuracy for predicting surgical need. Frequently selected predictors included Wits appraisal, ANB angle, the maxillomandibular ratio (Mx/Md), overjet, and the divergence of the lower gonial angle. AI methods show promise for assisting treatment decisions in Class III malocclusion, with Random Forest and XGBoost performing well on tabular cephalometric data and CNNs on imaging. Larger, multicentre datasets and external validation are needed to improve reliability, address bias, and support clinical implementation.

Humans↗

PubMed2026

Tissue-derived extracellular matrix hydrogels instruct epigenetic adaptation in metastatic colonization.

The extracellular matrix (ECM) plays a central role in regulating tumor progression and metastatic colonization by providing biochemical and mechanical signals that shape cancer cell fate. However, most organoid culture systems rely on basement membrane extracts that fail to reproduce the tissue-specific extracellular environments encountered during metastasis. Here, we develop tissue-derived decellularized matrix hydrogels to reconstruct organ-specific microenvironments and investigate epigenetic adaptation to ECM cues during metastatic colonization. Patient-derived colorectal cancer organoids cultured in colon-derived matrices exhibited enhanced maintenance of stem-like phenotypes and colon-specific chromatin accessibility landscapes compared with cultures grown in basement membrane extracts, demonstrating improved physiological relevance for primary tumor modeling. When exposed to matrices derived from secondary organs, the organoids showed distinct growth phenotypes accompanied by rapid, tissue-dependent chromatin accessibility remodeling, indicating that ECM composition alone can reshape regulatory programs governing metastatic adaptation. Notably, liver-derived matrices selectively activated hepatocyte nuclear factor 4 alpha (HNF4A)-associated transcriptional networks and created a context-specific dependence on c-MET signaling for survival. Functional perturbation of HNF4A or c-MET signaling confirmed that both are required for organoid formation specifically within the liver matrix environment. Together, these findings establish tissue-derived matrix hydrogels as instructive bioactive materials that actively regulate cancer cell epigenetic states and reveal microenvironment-specific therapeutic vulnerabilities during early metastatic colonization.

Journal Article↗

PubMed2026

BIOCARD framework: integrating fecal bile acids, lipids, and metabolites to assess response to a cardiovascular health intervention.

Cardiovascular disease (CVD) remains a leading cause of morbidity and mortality, particularly in under-resourced populations. Although nutritional interventions are important for CVD prevention, their outcomes are commonly evaluated using conventional clinical and behavioral indicators, which may not fully capture early molecular responses. In this study, we developed the BIOCARD framework, an exploratory fecal multi-omics platform integrating bile acids, lipids, and metabolites to evaluate intervention outcomes related to cardiovascular health. Fecal samples were collected from caregiver-child participants enrolled in a 10-week randomized controlled trial comparing a multicomponent garden-based intervention (SHA) with an education-only control group (MSP). Fecal polar metabolites, lipids, and bile acids were analyzed by UHPLC-HRMS-based approaches and integrated with conventional health indicators. Traditional clinical indicators in the present study showed limited sensitivity for detecting intervention-related differences. In contrast, fecal multi-omics analyzes revealed intervention-associated differences in metabolites, lipids, and bile acids, with children showing more apparent molecular variation than parents. Network analysis further revealed associations between selected molecular features and cardiovascular-related indicators, including blood pressure, body fat, skin carotenoids, and Healthy Eating Index scores. Together, these findings suggest that the BIOCARD framework may serve as an exploratory molecular approach to complement traditional outcome measures and improve the evaluation of nutritional interventions for cardiovascular health.

Humans↗

PubMed2026

Mendelian randomisation for rheumatology: beyond hype-what it's good for, what it can't do, and how to read it critically.

Mendelian randomisation (MR) has become abundant in the literature, with variation in quality and frequent overinterpretation of causality. This creates a problem for clinical readers, reviewers, and editors: some MR studies can sharpen causal thinking, prioritise drug targets, and challenge misleading observational claims, whereas others are little more than automated exposure-outcome scans with causal claims disproportionate to the evidence. MR can strengthen causal inference when randomised trials are impractical and conventional observational studies are vulnerable to confounding, reverse causation, or selection bias. In rheumatology, credible MR can contribute to questions about disease aetiology, modifiable risk factors, therapeutic target validation, adverse-effect anticipation, and phenotype validation. However, its interpretation depends on whether the exposure is plausibly instrumentable, whether the genetic instruments are biologically defensible, whether assumptions are interrogated in ways appropriate to the design, and whether findings are triangulated with clinical, observational, experimental, and mechanistic evidence. Instead of recapitulating all methodological issues of MR, this review aims to help rheumatologists distinguish robust MR from weak or overinterpreted analyses quickly. We provide an accessible framework for reading and triaging MR studies in rheumatology. Papers that use poorly justified instruments, treat medication use as drug-target evidence, interpret genetic liability as diagnosis, rely on mechanical sensitivity analyses, ignore prior evidence or ask no clinically meaningful question can often be passed over by readers. The goal is not to discourage MR in rheumatology, but to raise the standard; useful MR should clarify causal reasoning rather than simply generate another statistically significant association.

Journal Article↗

PubMed2026

A mechanism-guided framework for prioritizing membrane-interaction anti-Vibrio peptides from peptidomics data.

A mechanism-guided framework for prioritizing membrane-interaction antimicrobial peptide candidates from proteomics-derived peptide mixtures is presented. The framework integrates conservative machine-learning-based antimicrobial peptide (AMP) screening with a literature-derived membrane-interaction plausibility (MAP) assessment and a data-driven membrane-interaction ranking function (AIPx), followed by structural visualization for interpretability. MAP encodes physicochemical characteristics commonly associated with peptide-membrane interaction and provides a graded plausibility assessment. Building upon this physicochemically interpretable framework, AIPx ranks peptides using feature weights calibrated from experimentally characterized anti-Vibrio peptides, where minimum inhibitory concentration (MIC) values are used as a coarse-grained ranking reference rather than a direct prediction target. In a peptidomics-based peptide fractionation study targeting Vibrio spp., AIPx exhibited a consistent relationship with experimentally observed antibacterial activity. Distributional analysis revealed that peptide fractions exhibiting high anti-Vibrio activity are characterized by enrichment of high-ranking peptides rather than by AMP abundance alone. By structuring AMP identification and prioritization as sequential stages, the MAP + AIPx framework enables interpretable and experimentally actionable candidate selection by reducing biologically implausible candidates. The framework facilitates species-oriented prioritization of AMP candidates, addressing a key challenge in antimicrobial peptide discovery where activity may depend on target-specific membrane characteristics. Moreover, the approach is extensible through species-specific calibration and supports interpretable, mechanism-informed prioritization in antimicrobial peptide discovery.

Proteomics↗

PubMed2026

Genome-wide characterization of the TGF-β superfamily identifies bmp15, gdf9, and gsdf as sex-biased candidate regulators of gonadal differentiation in the synchronous hermaphrodite Plectropomus leopardus.

The transforming growth factor-β (TGF-β) superfamily plays conserved roles in vertebrate reproduction and gonadal sex differentiation. However, its genomic repertoire and sex-biased expression patterns remain unclear in the leopard coral grouper (Plectropomus leopardus), a species with synchronous hermaphroditism. Here, we performed a genome-wide identification of the TGF-β superfamily, identifying 42 genes from the chromosome-level genome. Phylogenetic and synteny analyses indicated that segmental duplication under purifying selection contributed to family expansion. Expression profiling across multiple tissues and four gonadal developmental stages (undifferentiated, 120 dph; early differentiated, 15 months; mature testis, 3 years; mature ovary, 3 years) identified eight gonad-enriched genes, among which bmp15 and gdf9 exhibited pronounced female-biased expression, with transcripts localized exclusively to the oocyte cytoplasm, particularly in stage II-III oocytes. In contrast, gsdf showed male-biased expression and was localized in spermatogenic cells of the testis. These reciprocal expression patterns indicate that bmp15/gdf9 and gsdf are candidate factors associated with gonadal sex differentiation. Our study provides the first comprehensive characterization of the TGF-β superfamily in P. leopardus and highlights bmp15, gdf9, and gsdf as candidate sex-differentiation factors in this hermaphroditic species.

Animals↗

PubMed2026

A genome-wide coverage-based pipeline for the identification of host-derived candidate DNA biomarkers from cell-free blood.

We have created a new data-analysis pipeline for the discovery of host-specific candidate DNA biomarkers derived from sequencing data of cell-free blood. Unlike approaches that rely on specific molecular or genetic signatures, our method leverages the coverage distribution of cell-free DNA sequences mapped to a reference genome, applying statistical analyses to identify informative short genomic regions for biomarker discovery. The pipeline is applicable to diverse diseases and can be used to analyze cell-free DNA sequences from plasma or serum to identify candidate biomarkers that are characteristic of disease states in mammals. Core functionalities were developed in Java and integrated with open-source software tools for the preprocessing of raw sequencing data, complemented by Python scripts for the machine-learning analysis and statistical validation. The pipeline is designed for HPC use and users can access the pipeline through a Galaxy workflow, which offers a user-friendly web interface for input selection prior to execution and analysis progress monitoring. Performance tests, carried out using duplicate sets of COVID-19 samples and controls, showed linear scalability of execution time with an increasing dataset size, as well as a substantial reduction in execution time through parallelized computation, whereby each HPC node is used to process the data of one chromosome. Further statistical tests confirmed the quality of the pipeline's results by showing that the set of identified candidate biomarkers remained stable across varying dataset sizes.

Biomarkers↗

PubMed2026

Real-World Efficacy and Safety of Standard-of-Care Chimeric Antigen Receptor T-Cell (CART) and Bispecific T-Cell Engager (TCE) Therapies in Relapsed/Refractory Multiple Myeloma (RRMM).

We aimed to evaluate the real-world (RW) efficacy and safety of standard-of-care CART versus TCE therapies in relapsed/refractory myeloma (RRMM), to assess utilization, outcomes, and tolerability of these therapies in a RW oncology in the US. Data were derived from the US-based, electronic health record-derived deidentified Flatiron Health Research Database, 2021-2024. A total of 419 patients (CART n = 220; TCE n = 199) with a confirmed diagnosis of myeloma who received CART or TCE as a standard-of-care treatment after at least 2 prior lines of therapy were included. Patients in the CART cohort were younger, had better ECOG PS, and a higher receipt of a prior autologous stem cell transplant versus bispecific TCE cohort. In CART versus TCE cohort, the overall response rates (ORR) were 83.3% versus 66.3%, median duration of response 7.9 months versus 4.3 months, progression free survival (PFS) 13.6 months versus 10.5 months, and overall survival (OS) of 29.8 months versus 21.9 months, respectively. A higher percentage of hematologic toxicity, infections, and cytokine release syndrome (CRS) were noted in the CART versus TCE cohort. This study provides insights on the RW effectiveness of CART versus TCE in the treatment of RRMM; highlights the differences in patient selection, clinical responses, treatment duration, and toxicity profiles.

CART↗