EMBO Molecular Medicine

Despite considerable advances, the emergence of treatment resistance to tyrosine kinase inhibitors (TKIs) therapy remains a significant challenge in chronic myeloid leukemia (CML). Here, we report the first clinical case of resistance to combined ponatinib and asciminib therapy in a CML patient who relapsed with B lymphoblastic blast crisis. While at presentation the patient harbored the canonical e13a2 BCR::ABL1 fusion, at relapse his disease harbored the T315I mutation together with a novel e6a3 BCR::ABL1 fusion, arisen by internal deletion in the original translocated allele. Structural modeling and biochemical analyses demonstrated that deletion of exon 2-encoded residues of ABL1 destabilizes the autoinhibited conformation, resulting in a hyperactive kinase with increased propensity for B-cell differentiation. Functional studies revealed that both BCR::ABL1e6a3 and BCR::ABL1e6a3/T315I conferred resistance to ponatinib and asciminib, alone or in combination. BCR::ABL1e6a3 demonstrated enhanced sensitivity to active-state selective inhibitors dasatinib and bosutinib, whereas BCR::ABL1e6a3/T315I remained resistant. Combined drug sensitivity assays showed that axitinib restored inhibitory activity when combined with ponatinib or asciminib. Strikingly, a combination of axitinib and asciminib with low dose ponatinib fully suppressed enzymatic activity of BCR::ABL1e6a3/T315I and cellular proliferation. These data show that treatment with asciminib and ponatinib can select for mutations with notably elevated enzymatic activity, effectively targeted by an axitinib-based triple combination. These data highlight the remarkable mutability of the BCR::ABL1 kinase, including through novel isoforms and provides a strong rationale for the clinical assessment of a triple inhibitor combination as a strategy to overcome resistance to dual ponatinib and asciminib therapy.

Type 2 diabetes and prediabetes affect hundreds of millions of people globally, yet the metabolic networks underlying disease development remain poorly understood. Using untargeted liquid chromatography-mass spectrometry (LC-MS/MS), we profiled a total of 15,470 (900 known) serum metabolite features across the human diabetes spectrum (the most comprehensive coverage reported to date). Weighted coexpression network analysis of samples from people with normal glucose tolerance, prediabetes, and type 2 diabetes, collected at baseline and 2 hours after an oral glucose tolerance test, revealed tightly coregulated modules strongly associated with glycemic dysregulation, insulin resistance, and islet dysfunction. Notably, short-chain organic acids, particularly crotonic acid, emerged as hubs of the diabetes-associated networks, accumulating progressively with disease severity. Reanalysis of extracellular vesicle proteomics from the same cohort showed that 16.5% of circulating proteins were crotonylated, with 47.6% correlated with crotonic acid and other hub metabolites, establishing a metabolome-crotonylome axis as a novel mechanism in diabetes development.

Type 2 diabetes (T2D) is a heterogeneous disease shaped by genetic pathways related to insulin resistance and beta cell dysfunction, but how this heterogeneity is reflected molecularly remains unclear. We integrated partitioned polygenic scores (pPS) with proteomic and metabolomic profiling to define molecular signatures of T2D and their clinical relevance. We analyzed UK Biobank participants with genomic, proteomic, and metabolomic data. In a disease-free training subset, we used LASSO regression to identify multi-omic signatures associated with each pPS by jointly modeling proteins and metabolites. In an independent testing set, we constructed multi-omic scores and examined their associations with clinical traits and diabetes-related outcomes. Mediation analyses were used to investigate putative causal pathways. Key findings were evaluated in the Multi-Ethnic Study of Atherosclerosis (MESA). We identified distinct multi-omic signatures that capture the molecular architecture of T2D genetic risk across physiological subtypes. Compared with genetic scores alone, multi-omic pPS showed larger effect sizes and better disease discrimination. These scores recapitulated subtype-specific physiology and were associated with T2D risk. The Beta-Cell 2 multi-omic score showed marked stratification for insulin use, which was replicated in MESA, where it also predicted future insulin use. Mediation analyses implicated lipoprotein remodeling and fatty acid metabolism in the Lipodystrophy 1 cluster, accounting for up to 45% of the total effect of pPS on T2D risk. Integrating process-specific genetic risk with circulating multi-omic profiles reveals biologically distinct endotypes of T2D and supports a framework for improved patient stratification and risk assessment.

Cerebral malaria is a severe neurological complication of Plasmodium falciparum infection. Damage of the blood-brain barrier (BBB) and endothelial dysfunction are established drivers of the disease pathology, however, whether astrocytes, a major constituent of the BBB, influence the disease outcome remains unclear. Using the murine model of experimental cerebral malaria (ECM), we show that astrocytes decisively regulate the outcome of ECM and the deubiquitinating enzyme OTUD7B in astrocytes fosters the disease. Mice lacking astrocytic OTUD7B showed reduced brain pathology and were protected from ECM compared with wildtype littermate controls. Transcriptomic profiling of ex vivo-isolated astrocytes revealed reduced proinflammatory chemokines and cytokines in the absence of OTUD7B. Plasmodium infection-associated microvesicles triggered a pro-inflammatory response in astrocytes, which was dependent on OTUD7B. Mechanistically, OTUD7B cleaved K48-linked ubiquitin chains from TRAF3 and TRAF6 upon stimulation with microvesicles or activation of TLR3/TLR9 by plasmodial nucleic acids. The OTUD7B-dependent TRAF3 and TRAF6 stabilization led to sustained NF-{kappa}B and p38 MAP kinase signaling and CXCL10 expression. Therapeutic silencing of CNS Otud7b or Cxcl10 expression after disease onset protected mice from ECM, identifying the cerebral OTUD7B-Cxcl10 axis as an attractive therapeutic target.

Increased literature support the pathogenetic role of dysfunctional energetic metabolism in the setup and progression of organ damage and failure. Genetic diseases often offer the possibility to investigate pathogenetic mechanisms. In particular, excessive cardiac damage is the most frequent cause of mortality in Fabry disease (FD), a genetic condition caused by deficient -galactosidase A (GLA) activity, leading to globotriaosylceramide (Gb3) accumulation. Beyond Gb3 storage, metabolic alterations and mitochondrial dysfunction, supported by in vitro evidence or studies in other tissues, may contribute to FD cardiomyopathy. This study investigated, for the first time, the mechanisms of mitochondrial involvement in FD, its role in determining cardiac manifestations, and its potential as a therapeutic target. We used a humanized FD mouse model (R301Q-Tg/GLA knockout), along with derived embryonic fibroblasts and neonatal and adult cardiomyocytes, to assess mitochondrial function across the lifespan. FD cells showed impaired mitophagy, reduced mitochondrial respiration, and increased reactive oxygen species production. Importantly, this mitochondrial dysfunction exacerbated the lysosomal deficit in FD cells, forming a vicious cycle. In cardiomyocytes, these alterations progressed with age, leading to the accumulation of dysfunctional mitochondria, energetic failure, and, in adult hearts, terminal mitochondrial damage and apoptosis. These events ultimately result in cardiac remodeling and dysfunction, including hypertrophy and diastolic impairment. Indeed, L-arginine supplementation, which promotes NO/PGC-1-dependent mitochondrial rescue, prevented the development of cardiac abnormalities in FD mice. Our findings identify early mitochondrial dysfunction as a key driver of FD cardiomyopathy and support mitochondrial targeting, including L-arginine supplementation, as a promising adjuvant therapeutic strategy. The mechanistic link between lysosomal dysfunction, altered mitochondrial turnover, and energetic collapse emerges as a key targetable pathway in organ damage, extending beyond FD. Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=134 SRC="FIGDIR/small/718770v1_ufig1.gif" ALT="Figure 1"> View larger version (62K): org.highwire.dtl.DTLVardef@2a5c4borg.highwire.dtl.DTLVardef@1117767org.highwire.dtl.DTLVardef@1b634c5org.highwire.dtl.DTLVardef@1429b6c_HPS_FORMAT_FIGEXP M_FIG C_FIG Cardiac manifestations vs mitochondrial alterations in Fabry disease: the visible tip and the hidden base of the icebergCardiac manifestations in hR301Q Tg/KO mice become evident from 9 months of age. However, mitochondrial homeostasis is perturbed much earlier (neonatal to young stages), with impaired mitophagy, reduced mitochondrial respiration and membrane potential, increased ROS production and PGC-1 downregulation. At later stages, from 6 months of age, mitochondrial dysfunction progresses and begins to impact cellular energetics, as indicated by reduced ETC expression and the onset of energetic deficit (ATP reduction). The resulting energetic collapse, together with progressive mitochondrial leakage, leads to cardiomyocyte hypertrophy, apoptosis, and dysfunction, which become detectable from 9 months of age, when clinical signs emerge. These findings support a mechanistic model in which 1) lysosomal incompetence due to GLA deficit is the initiating event inducing impairment of mitophagy; 2) Unsuccessful mitophagy, induces downregulation of PGC-1a-dependent mitogenesis; 3) exhausted mitochondria accumulate, inducing energetic collapse (able to exacerbate lysosomal dysfunction and further perturb mitophagy in a vitious cycle); 4) ultimate mitochondrial leakage induces Cytochrome C release and apoptosis activation. This cascade of molecular events is responsible for clinical manifestations, and mitochondrial targeting prevents cardiac organ damage. Significance statementFabry disease is a rare genetic disorder in which cardiac complications are a major cause of death, yet underlying mechanisms remain unclear. Here, we identify mitochondrial dysfunction as an early pathogenic event associated with impaired mitophagy, whereby defective mitochondrial quality control both results from and exacerbates lysosomal dysfunction, creating a self-reinforcing cycle that drives disease progression. Using a humanized model, we demonstrate that mitochondrial dysfunction is a key determinant of cardiac phenotype in vivo, driving energetic failure, oxidative stress, and cardiac damage. Importantly, L-arginine treatment restores mitochondrial function and prevents cardiac abnormalities. Our findings define a broadly relevant pathogenic axis linking lysosomal dysfunction, mitophagy failure, and mitochondrial impairment, that lead to impaired energetic metabolism and consequent cardiac hypertrophy, independently from GB3 accumulation. The implications of our study go beyond Fabry disease and support the therapeutic targeting of cellular energy homeostasis to prevent and treat organ damage and failure in chronic diseases. IMPORTANTO_LIManuscripts submitted to Review Commons are peer reviewed in a journal-agnostic way. C_LIO_LIUpon transfer of the peer reviewed preprint to a journal, the referee reports will be available in full to the handling editor. C_LIO_LIThe identity of the referees will NOT be communicated to the authors unless the reviewers choose to sign their report. C_LIO_LIThe identity of the referee will be confidentially disclosed to any affiliate journals to which the manuscript is transferred. C_LI GUIDELINESO_LIFor reviewers: https://www.reviewcommons.org/reviewers C_LIO_LIFor authors: https://www.reviewcommons.org/authors C_LI CONTACTThe Review Commons office can be contacted directly at: office@reviewcommons.org

Progranulin (PGRN) is a neurotrophic and anti-inflammatory factor produced mainly by neurons and microglia in the central nervous system. Progranulin haploinsufficiency causes frontotemporal dementia (FTD). In a previous study we showed that transgenic restoration of progranulin in neurons in progranulin knockout mice (NestinGrn KOBG knockout background) did not prevent the dementia-like phenotype. Here, we assessed if pharmacologic microglia depletion via PLX3397-diet (CSF1R-antagonist) had therapeutic value in these mice. Microglia depletion and spontaneous repopulation was confirmed in immunofluorescence and rtPCR studies. There was no difference in depletion or repopulation efficiency between NesGrn KOBG, PGRN KO and heterozygous (het) PGRN mice, but microglia repopulated faster than in control Grn-flfl mice, and the morphology of primary PGRN deficient microglia during repopulation was closer to homeostatic microglia, and it was accompanied by a remarkable restoration of dendritic spines and synaptic structures. Regardless of these positive effects, NesGrn KOBG and PGRN het mice experienced serious side effects during microglia depletion which peaked around the microglia nadir. Overactivity and excessive grooming escalated and caused serious skin lesions. Bulk transcriptomic and metabolomic studies in the brain taken 8 weeks after the end of PLX-diet clearly revealed differences between genotypes but mostly no lasting impact of PLX-diet, except for a further increase of proinflammatory genes, cathepsins and complement factors in PLX-treated groups. Cell type specific lipidomic studies revealed a time dependent switch not only in microglia but also astrocytes upon PLX3397 treatment. While nadir-microglia were triglyceride-laden, repopulated microglia returned to normal TG levels but were enriched in ether-bound phosphatidylcholines (PC-O) and lysophosphatidylglycerol species which are pro-inflammatory lipids; and astrocytes overtook the TG burden during repopulation. Our data suggest that microglia depletion may cause a deterioration in progranulin-deficiency.

Allogeneic hematopoietic stem cell transplantation (HSCT) is a life-saving treatment for hematologic malignancies, but long-term survivors present with lower muscle mass and functional capacity. In adult HSCT survivors 10-20 years after treatment, single nucleus RNA sequencing uncovered elevated XRRA1 expression levels in all muscle nuclei populations, which was retained in primary muscle stem cell cultures. HSCT survivors were characterized in vivo by impaired neuromuscular innervation that associated with muscle weakness, and lower muscle stem cell neurotrophic action. Despite these impairments, the molecular and physiological responses to heavy resistance training (HReT) were preserved in HSCT survivors, as demonstrated in a pre-registered clinical trial (ClinicalTrials.gov: NCT04922970). After 12 weeks of HReT, gains in muscle mass and strength were similar in HSCT survivors and healthy controls. In addition, we observed that [~]9% of muscle-resident immune cells persist into adulthood and that bone marrow derived cells do not adopt alternative cell fates in muscle tissue, resolving long-standing questions in human muscle biology. Together, these findings uncover molecular mechanisms of HSCT sequelae in muscle nuclei and muscle stem cells, which, importantly, can at least partly be overcome by mechanical loading. Given the growing population of HSCT survivors and the multitude of benefits of HReT for all organ systems, our findings support the importance of HReT in this population to promote healthspan.

The recent approval of KRAS inhibitors supports the therapeutic value of targeting mutant KRAS cancers. However, clinical efficacy is hindered by both primary and treatment-associated acquired resistance. We applied a CRISPR-Cas9 loss-of-function screen and identified loss of KEAP1 as a resistance mechanism to the KRASG12D-selective inhibitor MRTX1133 and the RAS(ON) multi-selective inhibitor RMC-7977 in pancreatic cancer models. RNA-sequencing analyses revealed a KEAP1KO transcriptome that is distinct from the ERK-, MYC-, and YAP/TAZ-TEAD-dependent transcriptional programs that drive KRAS inhibitor resistance, demonstrating a distinct mechanism of resistance. We then established a PDAC KEAP1-deficient (PKD) gene signature that was enriched in patients and preclinical models insensitive to KRAS inhibitor treatment. Finally, we observed that KEAP1-deficient cells exhibited elevated glutamine metabolism, and combination treatment with the glutamine antagonist DRP-104 (sirpiglenastat) enhanced KRAS inhibitor suppression of pancreatic and lung tumors. SIGNIFICANCEKEAP1 loss is associated with reduced response to KRAS inhibitor therapy. We demonstrate that KEAP1 loss-associated resistance can be overcome by pharmacologic inhibition of the KEAP1 loss-induced glutamine dependency, establishing a combination to enhance RAS inhibitor clinical efficacy.

Type 2 diabetes mellitus (T2DM) is a progressive metabolic disorder characterized by persistent hyperglycemia, insulin resistance, and chronic low-grade inflammation. Despite the widespread use of established therapies such as metformin, long-term glycemic control remains suboptimal, and disease progression is often not adequately prevented. This highlights the need for novel therapeutic strategies that address both metabolic dysfunction and the underlying immunometabolic components of the disease. In this study, GLX10 (GLXM100) was evaluated as a novel immune modulator in a high-fat diet (HFD) and low-dose streptozotocin (STZ)-induced rat model of T2DM over a 91-day period. Glycemic outcomes were assessed using terminal random blood glucose and oral glucose tolerance testing (OGTT), with glucose exposure quantified by area under the curve (AUC 0-120). Complementary in vitro investigations were performed in hepatic and macrophage cell models to assess cytocompatibility, nitric oxide production, and modulation of pro-inflammatory cytokines, including IL-6 and TNF-. GLX10 treatment resulted in a significant reduction in random blood glucose levels and a marked improvement in glucose tolerance compared to diabetic control animals. Importantly, GLX10 demonstrated greater improvement in OGTT AUC compared to metformin under the same experimental conditions, indicating enhanced dynamic glucose regulation. In vitro, GLX10 maintained viability in normal hepatic cells while significantly suppressing nitric oxide production and inflammatory cytokine outputs in macrophages, supporting a favorable safety and immune profile. Collectively, these findings demonstrate that GLX10 exerts robust antidiabetic activity through a dual mechanism involving metabolic regulation and suppression of inflammatory signaling. The integration of in vivo efficacy with supportive in vitro safety and mechanistic data provides a strong preclinical foundation and supports the further development of GLX10 as a promising therapeutic candidate for T2DM.

Chronological age is a potent determinant of clinical events, but it is conventionally treated as a linear function of time rather than a dynamic process shaped by genetics and tissue-specific senescence. Deep learning models derived from cardiovascular imaging offer an opportunity to quantify biological age across multiple domains and to examine the extent to which these measures capture shared or distinct vulnerabilities. Here, we applied deep learning to estimate biological age from electrocardiograms, cardiac MRI, carotid ultrasound, and retinal imaging, capturing electrical, structural, macrovascular, and microvascular domains in more than 100,000 UK Biobank participants. Genome-wide association and cross-trait heritability analyses showed that cardiovascular aging is not a singular process but a modular phenotype with distinct genetic determinants across modalities. Polygenic risk scores supported these distinct trajectories, showing that different biological age measures capture partly divergent biological processes with corresponding differences in clinical associations. Modality-specific genes also showcased distinct cell-type enrichment patterns. By deconvoluting aging into electrical, structural, macrovascular, and microvascular components, our results demonstrate that AI-derived age metrics capture distinct, disease-specific aging pathways. Ultimately, this modular framework positions deep learning-derived aging models not as holistic measures of health, but as domain-specific biomarkers of cardiovascular vulnerability.

Persistent detection of high-risk human papillomavirus (HPV) is required for cervical carcinogenesis, yet the metabolic phenotype associated with distinct HPV transition states remains incompletely defined. We analyzed vaginal metabolomics data from 71 HIV-negative, non-smoking, premenopausal women without other sexually transmitted infections, grouped by three-visit HPV trajectories: persistent negative (NNN, n=20), late incident positivity (NNP, n=9), conversion with persistence (NPP, n=13), clearance after prior positivity (PPN, n=16), and persistent positive (PPP, n=13). After detection-based filtering, 186 putative and 64 quantitatively estimated metabolites were retained for integrated univariate, multivariate, network, pathway, and machine learning analyses. Global class separation was weak by PERMANOVA and by five-class classification, indicating that the vaginal metabolome does not reorganize broadly across all HPV states. In contrast, trajectory-specific signals were reproducible. The strongest pairwise contrast was NNP versus PPP (best cross-validated ROC AUC 0.778; permutation p=0.039). Glycolic acid was the dominant single metabolite, particularly for NNP versus PPP (Mann-Whitney p=6.96x10^-4, FDR=0.0446, AUROC=0.902; detection 88.9% versus 15.4%; combined abundance+detection FDR=0.0010). Persistent positivity was characterized by a focused uracil-high, methyl-donor/redox-low signature, including lower glycolic acid, S-adenosylmethionine, NAD+, and betaine, together with higher uracil. Ratio mining further sharpened discrimination, with uracil/S-adenosylmethionine and uracil/creatinine among the best PPP classifiers, and glucose 1-phosphate/isovaleric acid-valeric acid strongly separating NNP from NPP. These data support a model in which HPV trajectory is encoded by targeted metabolic states rather than a diffuse HPV-positive versus HPV-negative metabolomic shift.

Glycosylation is a key structural modification of immunoglobulin G (IgG) that modulates its effector functions and has multiple roles in balancing inflammation. Altered IgG glycosylation has been reported in many diseases, often years before clinical manifestation, suggesting its causal role and biomarker potential. Here, we analyzed IgG glycome composition in 20,405 individuals from 42 different studies processed at the Genos Glycoscience Research Laboratory between 2008 and 2025. Across nearly all diseases, specific IgG glycome profiles reflected accelerated biological aging. Accelerated glycan aging was strongly associated with increased risk of all-cause mortality, independent of established clinical risk factors and potential confounders. Moreover, interventions known to reduce mortality risk, including hormone replacement therapy, therapeutic plasma exchange and caloric restriction, were associated with reversal of glycan aging. Given their role in modulating low-grade systemic inflammation, IgG glycans may represent a functional link between chronic inflammation, aging, disease susceptibility and all-cause mortality.

Hyperphosphorylated tau is a central pathological feature of Alzheimers disease and related tauopathies, and antibodies targeting the pSer396/pSer404 epitope region represent a promising therapeutic strategy. However, direct comparisons of pSer396- and pSer404-selective antibodies and the impact of humanization on their functional properties remain limited. We generated two new monoclonal antibodies (mAbs), 9E (pSer404-specific) and G10 (pSer396-specific), and evaluated them alongside 4E6 (pSer404) and PHF-1 (pSer396) in murine and partially humanized chimeric formats. Antibodies were assessed in mixed cortical cultures using extracellular (PHF + Ab) and intracellular (PHF [->] Ab) paradigms. Efficacy in preventing tau-induced toxicity and seeding differed substantially among antibodies and was variably altered by chimerization, despite identical variable regions. Antibodies targeting pSer404 were more effective than those targeting pSer396, and antibodies that preferentially bound soluble pathological tau species in competition ELISA were consistently more efficacious, whereas neuronal uptake was comparable across variants. To define structural determinants of phospho-epitope recognition, we determined the crystal structures of the Fab regions of 9E, G10, and PHF-1, and additionally solved the co-crystal structure of Fab PHF-1 in complex with a pSer396 tau peptide at 2.55 [A] resolution. The PHF-1 complex reveals a heavy-chain-dominant binding mode in which pSer396 is anchored within an electropositive pocket and Tyr394 adopts a flipped conformation that stabilizes a {beta}-strand-like motif, consistent with a phosphorylation-dependent conformational switch. These findings demonstrate that epitope selectivity, aggregate preference, structural binding mode, and Fc context collectively govern antibody efficacy, and that humanization can substantially alter therapeutic properties.

The spinocerebellar ataxias (SCAs) are a clinically heterogenous group of neurodegenerative disorders that affect movement, vision, speech and balance. Here, we reassign the linkage of SCA30 to 14q32.13 based on a cumulative LOD score >12. Within this interval we identified a 331 kb duplication, absent in population controls and not observed in >800 unrelated individuals with genetically unresolved cerebellar ataxia. RNASeq analysis of patient-derived lymphoblastoid cell lines revealed a splice-mediated chimeric transcript resulting from the duplication event. This transcript joined exon 1 of CLMN to exon 2 of SYNE3. In silico translation predicted that this chimeric transcript would produce a short N-terminal peptide corresponding to exon 1 of CLMN and the usually untranslated region of exon 2 of SYNE3 fused to the complete and in-frame SYNE3 protein. Transient overexpression of SYNE3 or the CLMN::SYNE3 fusion protein, in both HeLa cells and mouse primary cortical neurons, resulted in equivalent cellular outcomes including altered nuclear morphology and chromosomal DNA fragmentation. SYNE3 forms part of the linker of nucleoskeleton and cytoskeleton complex and is not usually expressed in cerebellar Purkyn[e] neurons while, CLMN has a Purkyn[e] specific expression pattern within the brain. Our data suggests that ectopic expression of SYNE3 in cerebellar Purkyn[e] neurons, mediated by the CLMN promoter, leads to cerebellar atrophy and causes spinocerebellar ataxia in the SCA30 family. This is an example of Mendelian disease arising from a novel, chimeric transcript with a likely dominant negative effect. Chimeric transcripts are commonly associated with cancers, but they are not often associated with monogenic disorders. Detection of chimeric transcripts as part of structural variant analysis could increase the genetic diagnostic yield of Mendelian disorders.

Glioblastoma (GBM) is the most prevalent primary brain cancer, with poor prognosis and limited therapeutic options available. The genetic and cellular heterogeneity characteristic of GBM contributes to poor response rates. Activating mutations of the epidermal growth factor receptor (EGFR) gene are among the most frequent alterations in GBM, occurring in roughly half of cases. Despite the prevalence of EGFR mutations, EGFR inhibition has shown limited success in GBM. The transcription factor C/EBP{beta} is a master regulator of the mesenchymal transformation in GBM, an aggressive state characterized by increased invasiveness and resistance to chemotherapy. Lucicebtide is a C/EBP{beta} antagonist peptide with demonstrated single agent activity in patients with recurrent GBM that is currently being evaluated in a clinical trial in combination with radiation and temozolomide in patients with newly-diagnosed GBM (NCT04478279), with emerging data supporting clinical activity in that setting. Here we show that in the TCGA-GBM dataset, patients with EGFR mutations display significant enrichment of a high C/EBP{beta} activity signature. Functionally, genetic inactivation of EGFR by CRISPR results in synthetic lethality in the presence of lucicebtide in GBM cell lines, and synergistic in vitro cytotoxicity and suppression of C/EBP{beta} target gene expression was observed in combination experiments with lucicebtide and EGFR inhibitors. Finally, enhanced anti-tumor activity was demonstrated in vivo in the combination setting, as combined subpharmacologic dose levels of lucicebtide and the EGFR inhibitor osimertinib potently suppressed GBM xenograft growth. These data identify EGFR and C/EBP{beta} dependencies in GBM and support lucicebtide combination with EGFR inhibitors as a potential therapeutic option for a sizable fraction of GBM patients.

Metabolic dysfunction and proteinopathy are hallmarks of many neurodegenerative diseases, yet their mechanistic interplay remains poorly understood. Here, we demonstrate that amyloid precursor protein (APP) processing in cortical neurons is disrupted upon loss of Nicotinamide mononucleotide adenylyltransferase 2 (NMNAT2), the NAD-synthesizing enzyme in neurons, resulting in accumulation of APP C-terminal fragments (APP-CTFs). Knockdown (KD) of the NAD hydrolase sterile alpha and TIR motif-containing protein 1 (SARM1) restores APP-CTF levels in NMNAT2 knockout (KO) neurons to wild-type levels, whereas NAD supplementation yields modest rescue. Redox profiling indicates that NMNAT2 loss reduces NAD/NADH redox potential when APP-CTF starts accumulating. Seahorse metabolic flux analysis shows that NMNAT2 deficiency induces early glycolytic impairment, followed by deficits in mitochondrial respiration. Notably, SARM1 KD, but not NAD supplementation, rescues mitochondrial function in NMNAT2 KO neurons. Temporal profiling of NMNAT2 KO neurons revealed a biphasic pattern in APP-CTF accumulation, with an initial gradual increase followed by a marked acceleration, paralleling the transition from an initially small number to a substantially greater number of differentially expressed proteins. Pathway enrichment analysis of proteomic changes suggests JNK/MAPK signaling is upregulated in the early phase, with late-phase downregulation of mitochondrial function and upregulation of endoplasmic reticulum stress and unfolded protein response pathways. Collectively, these findings demonstrate that neuronal NAD depletion drives a progressive, SARM1-dependent disruption of redox homeostasis and proteostasis, resulting in impaired APP processing. The NMNAT2-SARM1 axis emerges as a critical pathway linking metabolic stress to proteinopathy, positioning SARM1 as a key mediator of neurodegenerative dysfunction.

KIF18A inhibition has emerged as a therapeutic strategy for chromosomally unstable cancers, but clinical development is limited by the absence of a deployable predictive biomarker. Here we identify strong, diffuse p16INK4a expression, a well-established surrogate marker of Rb-pathway inactivation, as a predictive biomarker of response to KIF18A inhibition, and show that Rb-pathway inactivation marks a biologically distinct subset of cancers sensitive to this therapeutic approach. In sensitive models, low Rb activity is associated with robust spindle assembly checkpoint signaling and prolonged mitotic arrest following KIF18A inhibition. Weakening the spindle assembly checkpoint in this context is sufficient to confer resistance. Across three independent pan-cancer sensitivity datasets generated with distinct KIF18A inhibitors, Rb-pathway altered models were significantly more sensitive than histology-matched Rb-intact comparators, with the strongest association observed in cancers harboring direct RB1 loss or inactivating mutation. Guided by this mechanism, we retrospectively analyzed p16INK4a expression by immunohistochemistry (IHC) in pre-treatment tumor biopsies from 79 heavily pre-treated high-grade serous ovarian cancer patients across three dose-escalation or expansion cohorts and treated with two different KIF18A inhibitors (sovilnesib and VLS-1488) sharing a common mechanism of action. p16INK4a-high tumors showed substantially higher objective response rates than their p16INK4a-low counterparts (36.0% versus 2.2%; P = 0.0002) and markedly longer progression-free survival (median 24.3 versus 7.9 weeks; hazard ratio, 0.16; P < 0.0001). These findings establish p16INK4a as a mechanistically-based, clinically implementable biomarker of clinical response to KIF18A inhibition that is poised to support pan-cancer development of KIF18A inhibitors guided by Rb-pathway inactivation.

Motor neuron (MN) loss is a hallmark of neurodegenerative disorders, yet its assessment remains variable, confounding mechanistic and therapeutic interpretation. To address this, we conducted a systematic review and meta-analysis of spinal muscular atrophy (SMA) mouse studies, revealing 60% variability in reported MN loss, largely attributable to nonspecific spinal cord sampling. Using a whole-segment approach with tissue clearing, MN tracing, and multimodal imaging, we confirmed segment-dependent differences in MN counts. Common MN markers (SMI-32, Nissl) lacked specificity, whereas choline acetyltransferase (ChAT) provided robust labeling in murine and human spinal cords. Deep learning-based whole-mount segmentation enabled unbiased MN quantification and validated manual counts. Integrating analysis with computational modeling established segment sampling as a key driver of variability and revealed degeneration patterns: widespread MN loss in amyotrophic lateral sclerosis (ALS), selective MN loss in severe SMA, and preservation in mild SMA models. These findings establish a framework for reproducible MN quantification. HighlightsO_LISpinal cord segment-specific analysis reduces variability and allows accurate MN quantification C_LIO_LIChAT is the most reliable MN marker in murine and human spinal cords C_LIO_LIDeep learning-based segmentation enables unbiased MN quantification in intact spinal cords C_LIO_LIMN degeneration is widespread in ALS but restricted to pools innervating proximal muscles in severe SMA C_LI

BackgroundThere is a close correlation between neuroendocrine regulation and pulpitis progression. This study aims to identify key neuroendocrine regulation-related genes in pulpitis, providing insights for its treatment. MethodsGSE77459 and GSE92681 datasets were used to validate experimental findings. Key neuroendocrine regulation-related genes were identified via Cytoscape plugin cytoHubba and expression validation. Gene set enrichment analysis, RNA-binding protein regulatory networks, post-translational modifications, molecular regulatory networks, and drug prediction were performed. Key gene expression was experimentally verified in clinical samples. ResultsTop 10 genes were obtained via cytoHubba; 4 (IL6R, OSM, IL1RN, CCL4) with significant differences between pulpitis and control samples and consistent trends in both datasets were identified as key genes. Gene set enrichment analysis showed key genes participate in pathways like cytokine-cytokine receptor interaction. Related RNA-binding proteins were ELAVL1 and HNRNPA1, with phosphorylation as the main post-translational modification. Core regulatory microRNAs included miR-519, miR-765, miR-23, and regulatory factors included FOXC1, PRRX2. Targeted drugs (e.g., sarilumab, haloperidol decanoate, cyclosporine) were predicted, and clinical sample verification confirmed consistent expression trends. Conclusion4 key neuroendocrine regulation-related genes were identified, which may have clinical significance for the diagnosis and treatment of pulpitis.

Obesity and Type 2 Diabetes (T2D) are heterogeneous metabolic disorders whose molecular diversity is incompletely defined. We analyzed circulating proteomic profiles from 129 individuals belonging to Control, Obesity, and T2D groups and applied complementary machine-learning approaches, including random forest, multinomial logistic regression with LASSO regularization, support vector machines, and ensemble voting to identify proteins distinguishing the clinical groups. Convergent model outputs revealed a partially overlapping panel of discriminative proteins. Model performance was evaluated in an independent dataset from the Human Protein Atlas (n=834) comprising healthy individuals, patients with Obesity, T2D, or other metabolic diseases. Unsupervised clustering further identified multiple proteomic subgroups within each clinical category, indicating substantial intragroup heterogeneity. Bootstrap random forest with null-model benchmarking highlighted stable cluster-discriminative proteins. These findings demonstrate that integrating circulating proteomics with machine learning can resolve molecular heterogeneity in Obesity and T2D and nominate candidate biomarkers for metabolic disease stratification.