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PubMed2026

CAR-T Cell Therapy: Manufacturing Platforms and Clinical Consequences.

Chimeric antigen receptor (CAR) T-cell therapy has transformed hematological cancer care, yet variability in efficacy, durability, and safety cannot be explained solely by antigen selection or patient factors. We propose that manufacturing platforms are active biological determinants of outcome. Viral vectors, used in all licensed products, provide stable genomic integration and durable expression but are limited by cost, cargo capacity, and centralized production. Nonviral strategies, including transposons, CRISPR knock-ins, and messenger RNA delivery, enable faster, less-expensive manufacturing with larger payloads, while introducing distinct safety and persistence profiles. This review presents a three-layer mechanistic framework that reframes manufacturing as biology: integration biology determines genomic risk and transgene stability; clonal fitness shapes persistence, dominance, and exhaustion; and epigenomic imprinting, influenced by gene transfer method, cytokines, and culture stress, preconfigures functional trajectories. Clinical observations link platform choice to immune recovery, where prolonged B-cell aplasia and delayed T-cell reconstitution contribute to infection-related nonrelapse mortality, and hematopoietic reserve at apheresis emerges as a practical predictor. Finally, manufacturing is positioned as the key to democratizing cell therapy. Decentralized, nonviral production aligned with regulatory standards may enable equitable access and transition CAR-T therapy from innovation to sustainable global care.

Humans↗
PubMed2026

Nephropathies Associated with Sickle Cell Trait and How to Study Them.

Sickle cell trait (SCT), which carries a single point mutation in the hemoglobin-β (HBB) gene, has long been considered a benign condition. However, epidemiological evidence challenges this assumption, revealing that individuals with SCT face an elevated risk of renal dysfunction. However, this field of study remains ill-defined as it has focused on sickle cell disease (SCD), where renal complications are severe. As SCT is more prevalent than SCD, consequences of nephropathies in this group translate into a substantial and largely unaddressed public health burden. Clinical data, primarily observational, implicate age and sex in the development of SCT-associated nephropathies. These manifestations span glomerular hyperfiltration, tubular damage, hematuria, renal papillary necrosis, renal medullary carcinoma, and progression to chronic kidney disease, all complications that cluster disproportionately in older male individuals. Despite this, the mechanistic basis of SCT nephropathy, the thresholds at which renal injury becomes clinically significant, and the optimal strategies for early identification and prevention remain inadequately defined. In vitro studies have primarily focused on SCD blood cell biology, with SCT receiving comparatively little attention. Humanized murine models (i.e., Berkeley and Townes) have recapitulated some SCT-associated renal phenotypes but need to be more fully characterized. This review aims to provide an overview of the biology of sickle cell trait nephropathies, the gaps in our knowledge, and the model systems we can use to fill those gaps.

Journal Article↗
PubMed2026

A Multi-omics Regulated Cell Death Framework Defines Immune Phenotypes and Guides Precision Therapy in Colorectal Cancer.

Colorectal cancer (CRC) is molecularly and immunologically heterogeneous, contributing to variable treatment response. Because regulated cell death (RCD) intersects with tumor metabolism, immune regulation, and therapeutic susceptibility, we built an RCD-centered framework for CRC stratification. Multi-cohort transcriptomic data were used to infer RCD subtypes with non-negative matrix factorization (NMF) and non-negative least squares (NNLS). Genomic, bulk RNA-seq, single-cell RNA-seq, and spatial transcriptomic datasets were integrated to characterize subtype-associated biology. Machine-learning models were developed for immunotherapy response and survival-risk estimation. Candidate compounds were screened by GDSC2-based drug-sensitivity modeling and molecular docking, and FSTL3 was functionally assessed in vitro. The framework separated CRC samples into two RCD-related phenotypes resembling immune-hot and immune-cold states. RCD1 showed immune activation and higher mutational burden, whereas RCD2 showed immune-suppressed features, intratumoral heterogeneity, and aggressive biology. RCD-associated signatures showed potential for predicting immunotherapy response and survival risk. Dasatinib was prioritized for immune-cold, high-risk tumors, with preliminary evidence supporting its activity in CRC cells, while functional assays suggested a role for FSTL3 in growth, invasion, epithelial-mesenchymal transition, and apoptosis regulation. These findings suggest that RCD-based multi-omics analysis may refine CRC stratification and help generate therapeutic hypotheses.

Colorectal cancer↗
PubMed2026

A User-Friendly Protocol for Microinjection into Teleost Embryos to Study Gene Function.

Zebrafish (Danio rerio) and medaka (Oryzias latipes) are popular teleost models used in developmental biology and functional genomics. To achieve high-quality and reproducible microinjections, it is essential to have robust protocols for breeding, egg collection, and the precise delivery of genetic material. In this protocol, we present a comprehensive and optimized methodology for setting up breeding tanks under controlled photoperiod conditions to maximize egg yield while minimizing contamination. We provide detailed procedures for sex identification, pair selection, the use of grated breeding inserts, and methods to increase egg collection efficiency. We outline procedures for making injection gel beds, pulling needles, and calibration using one-microliter microcapillaries to achieve consistent nanoliter-scale injections. Our protocol outlines settings for the pico-liter injector that are optimized to deliver a precise amount per pulse with minimal variability. Finally, we demonstrate the application of these methods for gene knockdown using morpholino antisense oligonucleotides, gene knockout using CRISPR-Cas9, and gain-of-function mRNA overexpression experiments. Phenotypic assessments conducted at various developmental stages to evaluate gene-specific effects reveal consistent phenotypic outcomes between the morpholino and CRISPR-Cas9 approaches. This easy and comprehensive protocol enables efficient, precise, and scalable genetic manipulation of zebrafish and medaka embryos, thereby supporting advanced functional studies in developmental biology and disease modeling. To our knowledge, this is the first unified protocol for both zebrafish and medaka microinjection systems achieving 97.7% phenotype penetrance in CRISPR-Cas9 knockouts with precision together with a triple validation approach that confirms gene function across multiple techniques.

Animals↗
PubMed2026

Beyond antigen matching: compatibility intelligence theory for transfusion as an emergent biological system.

BACKGROUND: Despite major advances in serologic testing, extended phenotyping, and blood group genomics, clinically similar transfusion exposures may result in markedly different immune and clinical outcomes. Existing compatibility strategies do not fully explain this biological variability. OBJECTIVES: To examine transfusion compatibility as an emergent donor-recipient biological state and propose a systems-level conceptual framework that integrates established biological determinants into a testable model for future precision transfusion medicine. METHODS: This narrative review critically synthesizes current evidence from blood group genomics, recipient immunobiology, inflammation, disease-specific biology, transfusion medicine, and computational prediction. The proposed framework distinguishes Compatibility Intelligence Theory (CIT) as a biological interpretation from Precision Transfusion Intelligence (PTI) as its potential clinician-supervised translational application. RESULTS: The review argues that transfusion compatibility is shaped by interactions among donor genetics, recipient immune biology, inflammatory physiology, disease context, transfusion history, and longitudinal adaptation rather than by antigen matching alone. CIT provides an organizational framework for integrating these determinants, whereas PTI describes a possible clinician-supervised translation. To address current feasibility, the revised framework separates variables into routinely measurable, contextually available but incompletely standardized, and research-stage domains, and proposes a staged strategy for deriving rather than assuming their quantitative weights. Any clinical implementation would require comparative validation against current serologic, phenotypic, and genotype-based practice. CONCLUSIONS: Compatibility Intelligence Theory offers a testable systems-level framework for understanding transfusion compatibility without replacing established transfusion practices. The framework is not presented as a ready-to-use score: currently measurable variables can be organized for structured risk review, whereas inflammatory, immunogenetic, and multi-omic inputs require prospective standardization and validation. If future studies demonstrate incremental predictive and patient-centered benefit, CIT-informed PTI could support an adaptive, evidence-based extension of current precision transfusion practice.

Humans↗
PubMed2026

Harnessing Endogenous Plasticity Rather than Reprogramming of Mature Cells Will Advance Regenerative Medicine, Cancer Treatment and Rejuvenation.

The successful culture of human embryonic stem (hES) cells from inner cell mass cells of blastocyst stage 'spare' embryos in 1998, followed by induced pluripotent stem (iPS) cells in 2006, which allowed somatic cells to be reprogrammed to pluripotency using the Yamanaka factors, transformed regenerative biology and inspired extensive global efforts towards developing pluripotent stem cell-based applications. However, hES and iPS cells, as well as organoids generated from them, largely retain fetal-like characteristics, which limits their relevance for clinical translation. Concurrently, the prevailing assumption published in leading journals that adult tissues lack endogenous stem cells has led to the belief that mature cells dedifferentiate and reprogram during in vivo regeneration upon chronic injury, and that the appearance of embryonic/fetal markers in diabetes, heart failure, cancer, and many other chronic disease states reflects dedifferentiation of mature cells. We suggest that the prevailing concepts of dedifferentiation and reprogramming, both in vitro and in vivo, require careful re-evaluation. Adult somatic cells possibly do not truly dedifferentiate, neither in vitro nor in vivo. Instead, tissue-resident, pluripotent, very small embryonic-like stem cells (VSELs) in multiple organs account for the observed biology. In vitro "reprogramming" responses to Yamanaka factors likely reflect selective activation and expansion of VSELs/early progenitors rather than the dedifferentiation/ reprogramming of mature adult somatic cells. Likewise, the embryonic/fetal-like signatures reported in multiple disease states including cancer reflect expansion of immature tissue-specific progenitors that arise from VSELs but fail to differentiate normally due to a damaged microenvironment in vivo. Therapeutic strategies involving transplantation of MSCs, MUSE cells, or their secreted exosomes improve disease outcomes, possibly by restoring the damaged niche that supports functional tissue repair by VSELs. Although direct evidence to support this is lacking at present, recognising the central role of VSELs/progenitors and their niche in maintaining tissue homeostasis in vivo could resolve existing roadblocks and guide more effective endogenous regenerative therapies for diseased tissues and age-related dysfunctions.

Humans↗
PubMed2026

PGR expression as a pharmacogenomic companion biomarker to GENE70-derived genomic risk in ER-positive/HER2-negative breast cancer.

BACKGROUND: The biology of the estrogen receptor-positive (ER+) and human epidermal growth factor receptor 2-negative (HER2-) breast cancers is heterogeneous even when they are categorized by their risk via genomics. Transcriptomic PGR expression reflects endocrine pathway activity and may provide complementary biological information within established GENE70-derived genomic-risk categories. Whether this molecular marker improves the biological interpretation of genomic-risk stratification beyond conventional clinicopathological assessment remains uncertain. OBJECTIVES: The aim of this study was to determine whether transcriptomic PGR expression provides complementary biological and prognostic information within reconstructed GENE70-derived genomic-risk categories and refines the characterization of endocrine-related tumour biology in ER-positive/HER2-negative breast cancer. METHODS: This study analysed publicly available transcriptomic and clinical data from three cohorts: METABRIC (discovery cohort), GSE96058/SCAN-B cohort (validation cohort) and TCGA-BRCA cohort (molecular validation cohort). The GENE70-derived genomic-risk score was reconstructed for each cohort using matched genes. Cox regression, Kaplan-Meier analysis and subgroup comparisons were used to assess relationships between PGR expression, clinicopathologic variables, molecular features and survival outcomes. RESULTS: Across the three independent cohorts, low transcriptomic PGR expression was consistently associated with higher GENE70-derived genomic risk, increased MKI67 expression, reduced ESR1 expression and enrichment of the Luminal B subtype. Survival findings differed between cohorts. In the discovery METABRIC cohort, transcriptomic PGR expression showed heterogeneous associations with survival, particularly within GENE70-derived high-risk subgroups, whereas the external GSE96058/SCAN-B validation cohort demonstrated consistent associations between low PGR expression and poorer overall survival in both the overall ER-positive/HER2-negative population and GENE70-derived high-risk subgroups. CONCLUSION: These findings suggest that transcriptomic PGR provides complementary biological and prognostic information within GENE70-derived genomic-risk categories. However, because treatment response was not evaluated in the present study, the findings should not be interpreted as evidence of predictive or pharmacogenomic utility and prospective studies incorporating treatment-response analyses are required before such applications can be established.

Humans↗
PubMed2026

Targeting SIRT6: the design and therapeutic implications of activators and inhibitors.

Sirtuin 6 (SIRT6) is an NAD+-dependent deacylase that maintains genomic stability, regulates metabolism, and influences aging, making it an attractive but challenging therapeutic target. Pharmacological modulation of SIRT6 holds promise for cancer and metabolic disorders, yet its context-dependent functions demand precise intervention strategies. Potent, selective, and drug-like chemical probes are therefore essential to dissect SIRT6 biology and to validate its therapeutic potential. This review critically evaluates recent medicinal chemistry advances in SIRT6 modulation. We focus on structure-guided design strategies and structure-activity relationships (SAR) that have transformed initial hits into optimized leads for both activators and inhibitors, highlighting the remaining challenges in achieving isoform selectivity and drug-like properties.

Sirtuins↗
PubMed2026

Ribosomal protein S3: a critical regulator of human disease mechanisms.

Ribosomal protein S3 (RPS3) is an essential structural component of the 40S ribosomal subunit, yet growing evidence highlights crucial extraribosomal roles in genome maintenance, cell-cycle control, and immune signaling. Dysregulation of RPS3 contributes to diverse human disorders, including cancer, inflammatory diseases, neurodegeneration, and resistance to antimicrobial and anticancer therapies. As a cofactor of NF-κB and a participant in DNA damage responses, RPS3 occupies a node that integrates stress signaling with transcriptional reprogramming, enabling both protective and pathological outcomes. The present review critically evaluates mechanistic insights into RPS3 biology, emphasizing recent findings that delineate its context-dependent effects, discrepancies across models, and remaining gaps that restrict translational applications. Understanding these complexities is essential to assess RPS3's potential as a biomarker and therapeutic target.

Humans↗
PubMed2026

Emerging Principles in Spatial Functional Genomics.

Spatial transcriptomic and proteomic atlases have enabled mapping of gene programs within intact tissues, but these measurements remain largely descriptive and do not define the mechanisms controlling tissue biology. Pooled CRISPR screening provides scalable causal interrogation of gene function but remains largely confined to dissociated systems that lack spatial context. In vivo spatial functional genomics (SFG) bridges these approaches by integrating genetic perturbations with in situ transcriptomic and proteomic readouts to measure gene function within intact tissue ecosystems. By preserving spatial organization, SFG enables interpretation of perturbations through effects on cell-cell interactions, diffusible signals, multicellular niches, and tissue architecture. Here, we outline key design axes of SFG: perturbation strategy, barcoding strategy, and phenotypic readout. We discuss computational challenges, including spatial autocorrelation, neighborhood dependence, and context-aware null modeling, and highlight how SFG reveals non-cell-autonomous, architecture-dependent mechanisms of gene function, advancing toward predictive models of tissue organization and gene function.

Genomics↗
PubMed2026

S-layer-phage interaction in Clostridioides difficile.

Successful infection by a bacteriophage requires the injection of the phage genome into the cytoplasm of the host bacterium. To achieve this, an infecting phage must traverse the layers of the host cell envelope, including the membrane(s) and the cell wall. This process is further complicated in bacterial species that produce a proteinaceous S-layer on the outermost surface of the cell. Surprisingly little is known about the mechanistic basis of these early stages in the phage lifecycle, and even less is known about infection of S-layer producing bacteria. Recent advances in structural biology, particularly in cryoEM, have dramatically improved our understanding of the structures of both bacterial S-layers and phage virions separately, but we still lack a molecular view combining both phage and S-layer in the process of infection. Here, we review our current understanding of phage-S-layer interactions, using the human pathogen Clostridioides difficile as an example host.

Clostridioides difficile↗
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

Loss, persistence and reversal of phenotypic traits.

The irreversibility of complex trait loss has long been a tenet of evolutionary biology. However, this idea is increasingly at odds with the numerous documented exceptions across the Tree of Life. We synthesise this growing body of evidence across a diverse array of taxa and traits, exploring the evolutionary conditions that enable evolutionary reversal. By integrating macroevolutionary, genetic, and developmental information, we argue that trait reversal is commonly fostered by some form of persistence in the generative developmental pathway of the lost trait. We identify three overarching modes of trait reversal and support them with multiple case studies: by pleiotropy (the involvement of the same generative components in other traits and/or functions), by plasticity (environment-dependent expression of the trait) and by hemiplasy (persistence in another lineage, followed by reticulate evolution). We also examine important affinities between trait reversal and evolutionary novelties, undermining a neat distinction between what is old and what is new in evolution. This survey may provide a useful framework for future explorations of the developmental mechanisms underlying these still overlooked macroevolutionary dynamics.

Phenotype↗
PubMed2026

Metabolic engineering of Candida yeasts for biotechnological applications.

Candida yeasts represent a versatile yet underexploited platform for industrial biotechnology. These yeasts utilize a remarkably broad range of carbon sources, particularly for hydrophobic carbon sources, coupled with robust growth and diverse biosynthetic capacities, making them promising hosts for sustainable production of chemicals, fuels, and proteins. Despite these advantages, industrial deployment of Candida species has been hindered by concerns regarding opportunistic pathogenicity and the historical lack of efficient genetic manipulation tools, leading to a substantial gap between metabolic potential and practical utilization. Recent advances in functional genomics, genome editing, and systems metabolic engineering are rapidly overcoming these barriers, enabling more precise and efficient strain development. In this review, we systematically summarize recent progress in the metabolic engineering of Candida species as microbial cell factories, with particular emphasis on expanding genetic toolkits, utilizting renewable and non-conventional carbon sources, and biosynthesizing high-value compounds. In addition, we propose a biosafety-oriented classification framework to support their safe industrial deployment. Finally, we discuss current challenges and emerging opportunities, emphasizing that the synergy of synthetic biology and artificial intelligence-driven design holds the key to unlocking the biotechnological potential of Candida yeasts.

Candida↗
PubMed2026

Predictive evolutionary genomics: principles, validation, and practice.

Climate change and habitat loss are driving rapid evolutionary responses in populations world-wide, which creates an urgent need for evolutionary forecasting in conservation and agriculture. Such forecasting can be categorized into three time scales: trait-based models that use multivariate quantitative genetic equations to project correlated phenotypic responses up to c. 20 generations, allele-based analyses that model allele frequency dynamics up to 100 generations, and composite adaptation scores that aggregate many small effects to yield predictions across longer horizons. However, these approaches have remained largely disconnected. Here, we present a Bayesian framework that integrates these three complementary approaches for evolutionary prediction. Our framework combines genomic, phenotypic, and environmental data to yield probabilistic predictions with explicit uncertainty. We show how predictive evolutionary forecasts can be validated with experimental evolution, field experimentation, historical specimens, and reciprocal transplants. These validated forecasts can help advance conservation and agricultural programmes by helping predict which populations are at risk of future extinction, optimizing breeding programmes for future climates, and planning ecosystem management under environmental change. By supporting a shift towards more predictive approaches in evolutionary biology, this framework may help improve our ability to manage biodiversity and food security in a changing world.

Genomics↗
PubMed2026

Ancient DNA and Human Physiology.

Ancient DNA (aDNA) enables the reconstruction of chronologically sampled genomes from ancient humans, animals, plants, pathogens, and microorganisms, as well as environmental DNA, providing a record of biological changes through time. Improvements in short and degraded DNA extraction methods and low-cost sequencing now enable the generation of broad, cross-regional datasets that expand evolutionary analyses from past population demography to biological mechanisms. By tracking temporal shifts of allele frequencies, integrating functional genomics resources (e.g., gene expression, chromatin structure variation), modeling population demography to separate selection from genetic drift, and aligning genetic changes with archaeological, cultural, and climatic data, aDNA has the potential to link sequence variation to physiological function within their temporal and environmental contexts. In this review, we summarize illustrative case studies from aDNA research spanning complex traits, dietary adaptations, and responses to pathogens and other environmental changes, showing how human biology has evolved under multiple selective pressures through time. These dated signals help triage experimental work and expose mechanisms that are rare or absent in living cohorts. Although some challenges remain, such as geographic and temporal sampling disparities, limitations in data resolution and variant detection, and genotype-phenotype uncertainties, rapid methodological progress and stronger ethical frameworks are expanding what can be inferred, making aDNA a promising tool for refining physiological pathways, their timing, and their drivers.

Humans↗
PubMed2026

Review: The African turquoise killifish as a model for the integrative physiology of vertebrate aging.

With increasing emphasis on extending healthy lifespan, aging research requires vertebrate models that permit efficient mechanistic investigation and intervention testing within practical time and cost constraints. The African turquoise killifish (Nothobranchius furzeri) has attracted growing attention because it combines an exceptionally short life cycle with an intact vertebrate physiological context and an expanding genetic toolkit, enabling relatively rapid evaluation of candidate aging interventions and mechanistic analysis across molecular, tissue, and organismal levels. This review assesses N. furzeri from an integrative-physiology perspective, focusing on germline-soma interactions, gut microbiota-host crosstalk, nutrient sensing and metabolic remodeling, temperature responsiveness, and AMPK-mTOR-linked programs. It also examines expanding genome-engineering and reporter approaches that support mechanistic and tissue-resolved investigation of these physiological processes. Building on recent reviews of killifish biology, disease modeling, regeneration, and the hallmarks of aging, we synthesize evidence across major intervention domains, distinguish established phenotypic effects from incompletely resolved mechanisms, and highlight functional endpoints, methodological standardization, and the appropriate interpretation of the model's translational relevance. Together, these features position N. furzeri as a strategically useful vertebrate platform for rapid mechanistic testing, intervention evaluation, and prioritization of aging-related pathways. Future progress will require improved methodological standardization, tissue-resolved causal studies, and question-driven cross-species validation where appropriate.

Animals↗
PubMed2026

The impact of sex, age, and genetic ancestry on DNA methylation across tissues.

Understanding the consequences of individual DNA methylation variation is crucial for advancing our knowledge of human biology and disease, yet the collective impact of individual traits on DNA methylation and their downstream effects on gene expression across human tissues remains poorly understood. Here, we quantify the contributions of sex, age, genetic ancestry, and BMI on autosomal DNA methylation variation across nine human tissues and 424 individuals from the Genotype-Tissue Expression project. We show that genetic ancestry and age have a greater impact on DNA methylation compared with sex, with aging effects being more widespread but less pronounced. On average, <10% of the gene expression variation in sex, age, and ancestry is mediated by DNA methylation differences, with ancestry showing the largest proportion of mediation. We further show that ancestry-associated DNA methylation differences accumulate at CpG sites with extreme methylation states and are largely under genetic control. The female autosomal genome exhibits consistent hypermethylation across tissues at Polycomb-repressed regions. Ultimately, we show that age-related Polycomb target hypermethylation is observed across multiple tissues but not in the gonads. Our multi-individual, multitissue approach defines the key drivers of human DNA methylation variation in healthy conditions, establishing a baseline for the interpretation of DNA methylation changes in disease contexts.

Humans↗