Front Genet. 2025 Feb 5;16:1562092. doi: 10.3389/fgene.2025.1562092. eCollection 2025.

NO ABSTRACT

PMID:39975655 | PMC:PMC11835967 | DOI:10.3389/fgene.2025.1562092

bioRxiv [Preprint]. 2025 Feb 1:2025.01.31.635970. doi: 10.1101/2025.01.31.635970.

ABSTRACT

Alzheimer's Disease (AD) is marked by the accumulation of pathology, neuronal loss, and gliosis and frequently accompanied by cognitive decline. Understanding brain cell interactions is key to identifying new therapeutic targets to slow its progression. Here, we used systems biology methods to analyze single-nucleus RNA sequencing (snRNASeq) data generated from dorsolateral prefrontal cortex (DLPFC) tissues of 424 participants in the Religious Orders Study or the Rush Memory and Aging Project (ROSMAP). We identified modules of co-regulated genes in seven major cell types, assigned them to coherent cellular processes, and assessed which modules were associated with AD traits such as cognitive decline, tangle density, and amyloid-β deposition. Coexpression network structure was conserved in the majority of modules across cell types, but we also found distinct communities with altered connectivity, especially when compared to bulk RNASeq, suggesting cell-specific gene co-regulation. These coexpression modules can also capture signatures of cell subpopulations and be influenced by cell proportions. Using a Bayesian network framework, we modeled the direction of relationships between the modules and AD progression. We highlight two key modules, a microglia module (mic_M46), associated with tangles; and an astrocyte module (ast_M19), associated with cognitive decline. Our work provides cell-specific molecular networks modeling the molecular events leading to AD.

PMID:39975342 | PMC:PMC11838413 | DOI:10.1101/2025.01.31.635970

MedComm (2020). 2025 Feb 18;6(3):e70112. doi: 10.1002/mco2.70112. eCollection 2025 Mar.

ABSTRACT

Central and peripheral extensive-stage small-cell lung cancer (ES-SCLC) are reported to be two distinct tumor entities, but their responses to the front-line therapies and underlying biological mechanisms remain elusive. In this study, we first compared the outcomes of central and peripheral ES-SCLC receiving front-line chemotherapy or chemo-immunotherapy with a cohort of 265 patients. Then we performed single-cell RNA sequencing (scRNA-seq) on nine treatment-naïve ES-SCLC samples to investigate potential mechanisms underlying the response differences. Under chemotherapy, the peripheral type had a lower objective response rate (44.8% vs. 71.2%, p = 0.008) and shorter progression-free survival (median 3.4 vs. 5.1 months, p = 0.001) than the central type. When comparing chemo-immunotherapy with chemotherapy, the peripheral type showed a greater potential to reduce progression (HR, 0.18 and 0.52, respectively) and death (HR, 0.44 and 0.91 respectively) risks than the central type. Concerning the scRNA-seq data, the peripheral type was associated with chemo-resistant and immune-responsive tumoral and microenvironmental features, including a higher expression level of MYC-Notch-non-neuroendocrine (MYC-Notch-non-NE) axis and a more potent antigen presentation and immune activation status. Our results revealed that central and peripheral ES-SCLC had distinct responses to front-line treatments, potentially due to differential activation statuses of the MYC-Notch-non-NE axis.

PMID:39974662 | PMC:PMC11836348 | DOI:10.1002/mco2.70112

ACS Pharmacol Transl Sci. 2025 Jan 24;8(2):460-469. doi: 10.1021/acsptsci.4c00597. eCollection 2025 Feb 14.

ABSTRACT

mRNA-based therapies can overcome several challenges faced by traditional therapies in treating a variety of diseases by selectively modulating genes and proteins without genomic integration. However, due to mRNA's poor stability and inherent limitations, nanoparticle (NP) platforms have been developed to deliver functional mRNA into cells. In cancer treatment, mRNA technology has multiple applications, such as restoration of tumor suppressors and activating antitumor immunity. Most of these applications have been evaluated using simple cell-line-based tumor models, which failed to represent the complexity, heterogeneity, and 3D architecture of patient tumors. This discrepancy has led to inconsistencies and failures in clinical translation. Compared to cell line models, patient-derived xenograft (PDX) models more accurately represent patient tumors and are better suitable for modeling. Therefore, for the first time, this study employed two different TNBC PDX tumors to examine the effects of the mRNA-NPs. mRNA-NPs are developed using EGFP-mRNA as a model and studied in TNBC cell lines, ex vivo TNBC PDX organotypic slice cultures, and in vivo TNBC PDX tumors. Our findings show that NPs can effectively accumulate in tumors after intravenous administration, protecting and delivering mRNA to PDX tumors with different genetic and chemosensitivity backgrounds. These studies offer more clinically relevant modeling systems for mRNA nanotherapies in cancer applications.

PMID:39974646 | PMC:PMC11833720 | DOI:10.1021/acsptsci.4c00597

Front Cell Neurosci. 2025 Feb 5;19:1457740. doi: 10.3389/fncel.2025.1457740. eCollection 2025.

ABSTRACT

BACKGROUND: Spinal cord injury (SCI) poses a substantial challenge in contemporary medicine, significantly impacting patients and society. Emerging research highlights a strong association between SCI and chronic pain, yet the molecular mechanisms remain poorly understood. To address this, we conducted bioinformatics and systems biology analyses to identify molecular biomarkers and pathways that link SCI to chronic pain. This study aims to elucidate these mechanisms and identify potential therapeutic targets.

METHODS: Through analysis of the GSE151371 and GSE177034 databases, we identified differentially expressed genes (DEGs) linked to SCI and chronic pain. This analysis uncovered shared pathways, proteins, transcription factor networks, hub genes, and potential therapeutic drugs. Regression analysis on the hub genes facilitated the development of a prognostic risk model. Additionally, we conducted an in-depth examination of immune infiltration in SCI to elucidate its correlation with chronic pain.

RESULTS: Analyzing 101 DEGs associated with SCI and chronic pain, we constructed a protein interaction network and identified 15 hub genes. Using bioinformatics tools, we further identified 4 potential candidate genes. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses revealed a strong correlation between SCI and chronic pain, particularly related to inflammation. Additionally, we examined the relationship between SCI and immune cell infiltration, discovering a significant link between SCI and T cell activation. This is notable as activated T cells can cause persistent inflammation and chronic pain. Lastly, we analyzed the hub genes to explore the transcription factor network, potential therapeutic drugs, and ceRNA networks.

CONCLUSION: The analysis of 15 hub genes as significant biological markers for SCI and chronic pain has led to the identification of several potential drugs for treatment.

PMID:39974584 | PMC:PMC11835904 | DOI:10.3389/fncel.2025.1457740

Med Rev (2021). 2024 Jul 2;5(1):66-75. doi: 10.1515/mr-2024-0030. eCollection 2025 Feb.

ABSTRACT

Long COVID, as currently defined by the World Health Organization (WHO) and other authorities, is a symptomatic condition that has been shown to affect an estimated 10 %-30 % of non-hospitalized patients after one infection. However, COVID-19 can also cause organ damage in individuals without symptoms, who would not fall under the current definition of Long COVID. This organ damage, whether symptomatic or not, can lead to various health impacts such as heart attacks and strokes. Given these observations, it is necessary to either expand the definition of Long COVID to include organ damage or recognize COVID-19-induced organ damage as a distinct condition affecting many symptomatic and asymptomatic individuals after COVID-19 infections. It is important to consider that many known adverse health outcomes, including heart conditions and cancers, can be asymptomatic until harm thresholds are reached. Many more medical conditions can be identified by testing than those that are recognized through reported symptoms. It is therefore important to similarly recognize that while Long COVID symptoms are associated with organ damage, there are many individuals that have organ damage without displaying recognized symptoms and to include this harm in the characterization of COVID-19 and in the monitoring of individuals after COVID-19 infections.

PMID:39974559 | PMC:PMC11834749 | DOI:10.1515/mr-2024-0030

Front Microbiol. 2025 Feb 5;16:1471121. doi: 10.3389/fmicb.2025.1471121. eCollection 2025.

ABSTRACT

Since the beginning of their production and use, fossil fuels have affected ecosystems, causing significant damage to their biodiversity. Bacterial bioremediation can provide solutions to this environmental problem. In this study, the new species Isoptericola peretonis sp. nov. 4D.3T has been characterized and compared to other closely related species in terms of hydrocarbon degradation and biosurfactant production by in vitro and in silico analyses. Biosurfactants play an important role in microbial hydrocarbon degradation by emulsifying hydrocarbons and making them accessible to the microbial degradation machinery. The tests performed showed positive results to a greater or lesser degree for all strains. In the synthesis of biosurfactants, all the strains tested showed biosurfactant activity in three complementary assays (CTAB, hemolysis and E24%) and rhamnolipid synthesis genes have been predicted in silico in the majority of Isoptericola strains. Regarding hydrocarbon degradation, all the Isoptericola strains analyzed presented putative genes responsible for the aerobic and anaerobic degradation of aromatic and alkane hydrocarbons. Overall, our results highlight the metabolic diversity and the biochemical robustness of the Isoptericola genus which is proposed to be of interest in the field of hydrocarbon bioremediation.

PMID:39973932 | PMC:PMC11839211 | DOI:10.3389/fmicb.2025.1471121

In Silico Biol. 2025 Jan-Mar;16(1):14343207241306092. doi: 10.1177/14343207241306092.

ABSTRACT

Cellular adaptation to external signals is essential for biological functions, and it is an important field of interest in systems biology. This study examines the impact of cooperativity on the adaptation response of the Incoherent Feedforward Loop (IFFL) network motif to various signal profiles. Through comprehensive simulations, we studied how the IFFL motif responds to constant and pulse-type signals under varying levels of cooperativity. The results of our study demonstrate that positive cooperativity generally enhances the system's ability to adapt to different signal profiles. Nevertheless, given specific signal profiles, higher levels of cooperativity may decrease the system's adaptability. On the other hand, the adaptive response breaks down for negative cooperativity. For constant signals, increased positive cooperativity leads to a response with higher amplitude, and it accelerates the response time but delays the return time required to settle back down to the pre-stimulus state. Upon signal cessation, high positive cooperativity not only slows the system's response and return times but, in some cases, can lead to a complete temporary halt in response. For the pulse-like signal, cooperativity increases the maximum amplitude of the oscillatory response. These insights highlight the delicate balance between cooperativity and signal profile in cellular adaptation mechanisms involving the IFFL network motif.

PMID:39973888 | DOI:10.1177/14343207241306092

J Neuromuscul Dis. 2024 Dec 8:22143602241296276. doi: 10.1177/22143602241296276. Online ahead of print.

ABSTRACT

Up to 6% of the global population is estimated to be affected by one of about 10,000 distinct rare diseases (RDs). RDs are, to this day, often not understood, and thus, patients are heavily underserved. Most RD studies are chronically underfunded, and research faces inherent difficulties in analyzing scarce data. Furthermore, the creation and analysis of representative datasets are often constrained by stringent data protection regulations, such as the EU General Data Protection Regulation. This review examines the potential of federated learning (FL) as a privacy-by-design approach to training machine learning on distributed datasets while ensuring data privacy by maintaining the local patient data and only sharing model parameters, which is particularly beneficial in the context of sensitive data that cannot be collected in a centralized manner. FL enhances model accuracy by leveraging diverse datasets without compromising data privacy. This is particularly relevant in rare diseases, where heterogeneity and small sample sizes impede the development of robust models. FL further has the potential to enable the discovery of novel biomarkers, enhance patient stratification, and facilitate the development of personalized treatment plans. This review illustrates how FL can facilitate large-scale, cross-institutional collaboration, thereby enabling the development of more accurate and generalizable models for improved diagnosis and treatment of rare diseases. However, challenges such as non-independently distributed data and significant computational and bandwidth requirements still need to be addressed. Future research must focus on applying FL technology for rare disease datasets while exploring standardized protocols for cross-border collaborations that can ultimately pave the way for a new era of privacy-preserving and distributed data-driven rare disease research.

PMID:39973411 | DOI:10.1177/22143602241296276

J Neuromuscul Dis. 2024 Dec 20:22143602241304990. doi: 10.1177/22143602241304990. Online ahead of print.

ABSTRACT

BACKGROUND: Oculopharyngeal muscular dystrophy (OPMD) is a rare, late-onset, slowly progressive neuromuscular disorder characterized by ptosis, dysphagia, and proximal limb weakness. Emerging clinical trials require rapidly accessible and sensitive biomarkers to evaluate OPMD disease progression and potential response to future treatments.

OBJECTIVE: This cross-sectional study was designed to identify candidate circulating protein and imaging biomarkers of OPMD severity for future use in clinical trials.

METHODS: Twenty-five individuals with OPMD (age 63.3 ± 10.5 years; GCN copy number of 13 in PABPN1) were assessed using the 7k SOMAScan assay to profile the plasma proteome, and MRI to quantify replacement of muscle by fat. OPMD severity was first categorized using the clinical presence/absence of limb weakness, and protein signals were considered distinguishing if they differed by more than 30% between subgroups and had statistically significant P-values after correcting for multiple comparisons. Distinguishing proteins were contrasted with age-matched controls (n = 10). OPMD severity was also treated as a continuous variable using fat fraction of the soleus muscle, and proteins were considered distinguishing if the slope of relationship between protein signal and soleus fat fraction differed significantly from zero after correcting for multiple comparisons. Pathway analyses were conducted using Metascape and the Database for Annotation, Visualization, and Integrated Discovery webtools.

RESULTS: Eighteen plasma proteins distinguished OPMD on both indicators of severity. Pathway analyses identified skeletal muscle tissue, phagocytosis/engulfment, and extracellular matrix organization as enriched ontology clusters in OPMD with limb weakness. The most distinguishing plasma protein signals (ACTN2, MYOM2, CA3, APOBEC2, MYL3, and PDLIM3) were over 200% higher in OPMD with limb weakness than OPMD without limb weakness as well as controls, and correlated strongly with percent of fatty replacement of soleus (r = 0.89 ± 0.04).

CONCLUSIONS: The candidate biomarkers identified contribute to the ongoing search for sensitive and accessible biomarkers of OPMD progression, prognosis, and monitoring.

PMID:39973404 | DOI:10.1177/22143602241304990

Biophys J. 2025 Feb 18:S0006-3495(25)00107-9. doi: 10.1016/j.bpj.2025.02.016. Online ahead of print.

ABSTRACT

Humans have three known ATP-binding cassette (ABC) transporters in the inner mitochondrial membrane (ABCB7, ABCB8, and ABCB10). ABCB10, the most studied of them thus far, is essential for normal red blood cell development and protection against oxidative stress, and it was recently found to export biliverdin, a heme degradation product with antioxidant properties. The molecular mechanism underlying the function of ABC-transporters remains controversial. Their nucleotide binding domains (NBDs) must dimerize to hydrolyze ATP, but capturing the transporters in such conformation for structural studies has been experimentally difficult, especially for ABCB10 and related eukaryotic transporters. Purified transporters are commonly studied in detergent micelles, or after their reconstitution in nanodiscs, usually at non-physiological temperature and using non-hydrolysable ATP analogs or mutations that prevent ATP hydrolysis. Here, we have used Luminescence Resonance Energy Transfer (LRET) to evaluate the effect of experimental conditions on the NBDs dimerization of ABCB10. Our results indicate that all conditions used for determination of currently available ABCB10 structures have failed to induce NBDs dimerization. ABCB10 in detergent responded only to MgATP at 37oC, whereas reconstituted protein shifted towards dimeric NBDs more easily, including in response to MgAMP-PNP and even present NBDs dimerization with MgATP at room temperature. The nanodisc's size affects the nucleotide-free conformational equilibrium of ABCB10 and the response to ATP in absence of magnesium, but for all analyzed sizes (scaffold proteins MSP1D1, MSP1E3D1, and MSP2N2), a conformation with dimeric NBDs is clearly preferred during active ATP hydrolysis (MgATP, 37oC). These results highlight the sensitivity of this human ABC transporter to experimental conditions and the need for a more cautious interpretation of structural models obtained under far from physiological conditions. A dimeric NBDs conformation that has been elusive in prior studies, seems to be dominant during MgATP hydrolysis at physiological temperature.

PMID:39973007 | DOI:10.1016/j.bpj.2025.02.016

Phys Rev E. 2025 Jan;111(1-1):014420. doi: 10.1103/PhysRevE.111.014420.

ABSTRACT

The folding of cellular monolayers pervades embryonic development and disease, and is often caused by cell shape changes such as cell wedging. However, the function and mechanical role of different active cellular changes in different regions of folding tissues remain unclear in many cases, at least partially because the quantification of out-of-plane mechanical stresses in complex three-dimensional tissues has proved challenging. The gastrulationlike inversion process of the green alga Volvox provides a unique opportunity to overcome this difficulty: Combining laser ablation experiments and a mechanical model, we infer the mechanical properties of the curved tissue from its unfurling on ablation. We go on to reproduce the tissue shapes at different developmental timepoints quantitatively using our mechanical model. Strikingly, this reveals out-of-plane stresses associated with additional cell shape changes away from those regions where cell wedging bends the tissue. Moreover, the fits indicate an adaptive response of the tissue to these stresses. In this way, our paper provides not only the experimental and theoretical framework to quantify out-of-plane stresses in tissue folding, but it also shows how additional cell shape changes can provide another source of out-of-plane stresses in development complementing cell wedging.

PMID:39972828 | DOI:10.1103/PhysRevE.111.014420

Equine Vet J. 2025 Feb 19. doi: 10.1111/evj.14490. Online ahead of print.

ABSTRACT

BACKGROUND: Equine osteoarthritis (OA) is predominantly diagnosed through clinical examination and radiography, leading to detection only after significant joint pathology. The pathogenesis of OA remains unclear and while many medications modify the disease's inflammatory components, no curative or reversal treatments exist. Identifying differentially abundant metabolites and proteins correlated with osteoarthritis severity could improve early diagnosis, track disease progression, and evaluate responses to interventions.

OBJECTIVES: To identify molecular markers of osteoarthritis severity based on histological and macroscopic grading.

STUDY DESIGN: Cross-sectional study.

METHODS: Post-mortem synovial fluid was collected from 58 Thoroughbred racehorse joints and 83 joints from mixed breeds. Joints were histologically and macroscopically scored and categorised by OA and synovitis grade. Synovial fluid nuclear magnetic resonance metabolomic and mass spectrometry proteomic analyses were performed, individually and combined.

RESULTS: In Thoroughbreds, synovial fluid concentrations of metabolites 2-aminobutyrate, alanine and creatine were elevated for higher OA grades, while glutamate was reduced for both Thoroughbreds and mixed breeds. In mixed breeds, concentrations of three uncharacterised proteins, lipopolysaccharide binding protein and immunoglobulin kappa constant were lower for higher OA grades; concentrations of an uncharacterised protein were higher for OA grade 1 only, and apolipoprotein A1 concentrations were higher for OA grades 1 and 2 compared with lower grades. For Thoroughbreds, gelsolin concentrations were lower for higher OA grades, and afamin was lower at a higher synovitis grade. Correlation analyses of combined metabolomics and proteomics datasets revealed 58 and 32 significant variables for Thoroughbreds and mixed breeds, respectively, with correlations from -0.48 to 0.42 and -0.44 to 0.49.

MAIN LIMITATIONS: The study's reliance on post-mortem assessments limits correlation with clinical osteoarthritis severity.

CONCLUSIONS: Following stratification of equine OA severity through histological and macroscopic grading, synovial fluid metabolomic and proteomic profiling identified markers that may support earlier diagnosis and progression tracking. Further research is needed to correlate these markers with clinical osteoarthritis severity.

PMID:39972657 | DOI:10.1111/evj.14490

ACS Nano. 2025 Feb 19. doi: 10.1021/acsnano.4c16949. Online ahead of print.

ABSTRACT

Fast and cost-effective microbial classification is crucial for clinical diagnosis, environmental monitoring, and food safety. However, traditional methods encounter challenges including intricate procedures, skilled personnel needs, and sophisticated instrumentations. Here, we propose a cost-effective microbe classification system, also termed freeze-thaw-induced floating pattern of AuNPs (FTFPA), coupled with artificial intelligence, which is capable of identifying microbes at a cost of $0.0023 per sample. Specifically, FTFPA utilizes AuNPs for coincubation with microbes, resulting in distinct patterns upon freeze-thawing due to their weak interaction. These patterns are digitized to train models that distinguish nine microbes in various tasks. The positive sample detection model achieved an F1 score of 0.976 (n = 194), while the multispecies classification task reached a macro F1 score of 0.859 (n = 1728). To address scalability and lightweight requirements across diverse classification scenarios, we categorized microbes based on species classification levels. The macro F1 score of the hierarchical model (n = 5184), order level model (n = 5184), Enterobacteriales level model (n = 2550), and Bacillales level model (n = 1974) was 0.854, 0.907, 0.958, and 0.843. In summary, our method is user-friendly, requiring only simple equipment, is easy to operate, and convenient, providing a platform for microbial identification.

PMID:39972564 | DOI:10.1021/acsnano.4c16949

Diabetol Metab Syndr. 2025 Feb 19;17(1):63. doi: 10.1186/s13098-025-01630-x.

ABSTRACT

Posttraumatic stress disorder (PTSD) patients have a high comorbidity with type 2 diabetes (T2D). Whether PTSD influences the risk of diabetes is still not known. We used GWAS data from European ancestry of PTSD (23,121 cases and 151,447 controls) and T2D (80,154 cases and 853,816 controls) to investigate the bidirectional associations between PTSD and T2D by the Mendelian randomization (MR) analysis. We showed that PTSD was causally associated with higher odds of T2D (OR = 1.04, 95% CI: 1.01-1.06, P = 0.0086), but not vice versa. Our study suggests that PTSD may increase the risk of T2D. PTSD sufferers should be screened for T2D and its precursor known as metabolic syndrome.

PMID:39972391 | DOI:10.1186/s13098-025-01630-x

Nature. 2025 Feb;638(8051):E23-E29. doi: 10.1038/s41586-024-08497-4.

NO ABSTRACT

PMID:39972229 | DOI:10.1038/s41586-024-08497-4

Nature. 2025 Feb 19. doi: 10.1038/s41586-025-08586-y. Online ahead of print.

ABSTRACT

Neoantigen vaccines are under investigation for various cancers, including epidermal growth factor receptor (EGFR)-driven lung cancers1,2. We tracked the phylogenetic history of an EGFR mutant lung cancer treated with erlotinib, osimertinib, radiotherapy and a personalized neopeptide vaccine (NPV) targeting ten somatic mutations, including EGFR exon 19 deletion (ex19del). The ex19del mutation was clonal, but is likely to have appeared after a whole-genome doubling (WGD) event. Following osimertinib and NPV treatment, loss of the ex19del mutation was identified in a progressing small-cell-transformed liver metastasis. Circulating tumour DNA analyses tracking 467 somatic variants revealed the presence of this EGFR wild-type clone before vaccination and its expansion during osimertinib/NPV therapy. Despite systemic T cell reactivity to the vaccine-targeted ex19del neoantigen, the NPV failed to halt disease progression. The liver metastasis lost vaccine-targeted neoantigens through chromosomal instability and exhibited a hostile microenvironment, characterized by limited immune infiltration, low CXCL9 and elevated M2 macrophage levels. Neoantigens arising post-WGD were more likely to be absent in the progressing liver metastasis than those occurring pre-WGD, suggesting that prioritizing pre-WGD neoantigens may improve vaccine design. Data from the TRACERx 421 cohort3 provide evidence that pre-WGD mutations better represent clonal variants, and owing to their presence at multiple copy numbers, are less likely to be lost in metastatic transition. These data highlight the power of phylogenetic disease tracking and functional T cell profiling to understand mechanisms of immune escape during combination therapies.

PMID:39972134 | DOI:10.1038/s41586-025-08586-y

Nature. 2025 Feb 19. doi: 10.1038/s41586-025-08588-w. Online ahead of print.

ABSTRACT

The survival of malignant cells within tumours is often seen as depending on ruthless competition for nutrients and other resources1,2. Although competition is certainly critical for tumour evolution and cancer progression, cooperative interactions within tumours are also important, albeit poorly understood3,4. Cooperative populations at all levels of biological organization risk extinction if their population size falls below a critical tipping point5,6. Here we examined whether cooperation among tumour cells may be a potential therapeutic target. We identified a cooperative mechanism that enables tumour cells to proliferate under the amino acid-deprived conditions found in the tumour microenvironment. Disruption of this mechanism drove cultured tumour populations to the critical extinction point and resulted in a marked reduction in tumour growth in vivo. Mechanistically, we show that tumour cells collectively digest extracellular oligopeptides through the secretion of aminopeptidases. The resulting free amino acids benefit both aminopeptidase-secreting cells and neighbouring cells. We identified CNDP2 as the key enzyme that hydrolyses these peptides extracellularly, and loss of this aminopeptidase prevents tumour growth in vitro and in vivo. These data show that cooperative scavenging of nutrients is key to survival in the tumour microenvironment and reveal a targetable cancer vulnerability.

PMID:39972131 | DOI:10.1038/s41586-025-08588-w

Nature. 2025 Feb 19. doi: 10.1038/s41586-024-08508-4. Online ahead of print.

ABSTRACT

A fundamental challenge for cancer vaccines is to generate long-lived functional T cells that are specific for tumour antigens. Here we find that mRNA-lipoplex vaccines against somatic mutation-derived neoantigens may solve this challenge in pancreatic ductal adenocarcinoma (PDAC), a lethal cancer with few mutations. At an extended 3.2-year median follow-up from a phase 1 trial of surgery, atezolizumab (PD-L1 inhibitory antibody), autogene cevumeran1 (individualized neoantigen vaccine with backbone-optimized uridine mRNA-lipoplex nanoparticles) and modified (m) FOLFIRINOX (chemotherapy) in patients with PDAC, we find that responders with vaccine-induced T cells (n = 8) have prolonged recurrence-free survival (RFS; median not reached) compared with non-responders without vaccine-induced T cells (n = 8; median RFS 13.4 months; P = 0.007). In responders, autogene cevumeran induces CD8+ T cell clones with an average estimated lifespan of 7.7 years (range 1.5 to roughly 100 years), with approximately 20% of clones having latent multi-decade lifespans that may outlive hosts. Eighty-six percent of clones per patient persist at substantial frequencies approximately 3 years post-vaccination, including clones with high avidity to PDAC neoepitopes. Using PhenoTrack, a novel computational strategy to trace single T cell phenotypes, we uncover that vaccine-induced clones are undetectable in pre-vaccination tissues, and assume a cytotoxic, tissue-resident memory-like T cell state up to three years post-vaccination with preserved neoantigen-specific effector function. Two responders recurred and evidenced fewer vaccine-induced T cells. Furthermore, recurrent PDACs were pruned of vaccine-targeted cancer clones. Thus, in PDAC, autogene cevumeran induces de novo CD8+ T cells with multiyear longevity, substantial magnitude and durable effector functions that may delay PDAC recurrence. Adjuvant mRNA-lipoplex neoantigen vaccines may thus solve a pivotal obstacle for cancer vaccination.

PMID:39972124 | DOI:10.1038/s41586-024-08508-4

Nat Commun. 2025 Feb 19;16(1):1763. doi: 10.1038/s41467-025-57031-1.

ABSTRACT

Regulatory sequences encode crucial gene expression signals, yet the sequence characteristics that determine their functionality across species remain obscure. Deep generative models have demonstrated considerable potential in various inverse design applications, especially in engineering genetic elements. Here, we introduce DeepCROSS, a generative artificial intelligence framework for the inverse design of cross-species and species-preferred 5' regulatory sequences in bacteria. DeepCROSS constructs a meta-representation using 1.8 million regulatory sequences from thousands of bacterial genomes to depict the general constraints of regulatory sequences, employs artificial intelligence-guided massively parallel reporter assay experiments in E. coli and P. aeruginosa to explore the potential sequence space, and performs multi-task optimization to obtain de novo regulatory sequences. The optimized regulatory sequences achieve similar or better performance to functional natural regulatory sequences, with high success rates and low sequence similarities with the natural genome. Collectively, DeepCROSS efficiently navigates the sequence-function landscape and enables the inverse design of cross-species and species-preferred 5' regulatory sequences.

PMID:39971994 | DOI:10.1038/s41467-025-57031-1