Search bioRxiv⌕ Search

Biology subjects

Ho, J.

Publications and source records attributed to Ho, J..

At least 19 recordsLinked to original sources

Atypical BlaIR Two-Component System in Pseudomonas aeruginosa Regulates Virulence but not β-Lactam Resistance

With the rise of antimicrobial resistance, anti-virulence therapeutics are a viable alternative to circumvent resistance pressures. Hypothetical genes and proteins are an under-studied source of potential virulence factor targets. We performed bioinformatic analyses to identify conserved hypothetical genes enriched in pathogenic Pseudomonas aeruginosa but not in non-pathogenic strains. This analysis identified an atypical BlaIR system, which we named pvmSR, that regulated P. aeruginosa virulence in a Caenorhabditis elegans infection model. This is in contrast with the typical BlaIR system from Staphylococcus aureus, which regulates resistance to {beta}-lac-tam antibiotics. The{Delta} pvmSR mutant showed reduced virulence in a C. elegans slow-killing assay. To understand how PvmSR regulated virulence in vivo, we performed dual RNA-seq to analyze transcriptomic changes in both C. elegans and P. aeruginosa. We found that C. elegans responded to P. aeruginosa {Delta}pvmSR infection by decreasing expression of lysosome and phagocytosis pathways. In P. aeruginosa {Delta}pvmSR, we observed decreased gene expression of several known virulence factors including the hydrogen cyanide synthase, hcnC, and heparinase, hepP. Additionally, we observed dysregulation in genes important for quorum sensing and biofilm formation. Collectively, our findings indicated that PvmSR contributed to virulence regulation and may serve as a potential anti-virulence target.

microbiology↗

Tumor-specific Kinase Motif Enrichment Analysis Identifies Personalized Therapeutic Cancer Targets

Gastroenteropancreatic neuroendocrine tumors (GEP-NETs) are an uncommon and poorly understood malignancy with low mutational burden, lacking well-defined oncogenic drivers. GEP-NET mortality frequently results from extensive hepatic metastases. Accordingly, we interrogated phosphoproteomic data from GEP-NET liver metastases and patient-matched uninvolved liver to identify tumor-specific signaling and targetable tumor vulnerabilities using Kinase Motif Enrichment Analysis (KMEA), a new tool leveraging the recent Kinase Library compendium of the substrate motif specificity for nearly the entire human kinome. KMEA identified patient tumor-specific upregulation of mTOR or casein kinase 2 (CK2) activity that would be undiscoverable by standard personalized genomic and transcriptomic approaches. Striking concordance was observed between KMEA predictions for specific tumors, and their sensitivity to inhibitors of mTOR or CK2 using patient tumor-derived organoids. These findings reveal potential clinically-actionable protein kinases hyperactivated in GEP-NETs, and more broadly indicate a general method for personalized cancer treatment using phosphoproteomics and KMEA-derived kinase activity signatures.

cancer biology↗

GENETIC AND PHARMACOLOGIC ACTIVATION OF BECLIN1 PREVENTS ALDOSTERONE-INDUCED CARDIOVASCULAR DAMAGE

BackgroundAldosterone promotes endothelial dysfunction and cardiovascular injury through mineralocorticoid receptor (MR) activation. Autophagy is essential for endothelial homeostasis, yet its role in aldosterone-mediated vascular dysfunction remains unclear. We tested whether aldosterone impairs autophagic flux and whether restoring autophagy via Beclin1 (BCN1) activation protects vascular and cardiac function. MethodsEndothelial and vascular responses to aldosterone were assessed in wild-type mice, BCN1 gain-of-function mice (Becn1), and mice treated with spermidine or a BCN1- activating TB-peptide. Vascular function, nitric oxide (NO)/reactive oxygen species (ROS) production, autophagy markers, endothelial migration, and cardiac fibrosis were evaluated using wire myography, fluorescence assays, Western blotting, confocal microscopy, migration assays, and histology. ResultsAldosterone impaired endothelium-dependent relaxation, decreased NO, increased ROS, and disrupted autophagic flux in an MR-dependent manner, indicated by LC3 accumulation and reduced p62 and BCN1 expression. Spermidine restored endothelial function and normalized NO and ROS levels. BCN1 gain-of-function mice were protected from aldosterone-induced endothelial dysfunction and exhibited reduced coronary and myocardial fibrosis. TB-peptide activation of BCN1 enhanced autophagic flux, improved vascular function, decreased cardiac fibrosis, and rescued endothelial migration impaired by aldosterone. ConclusionsAldosterone induces endothelial dysfunction by suppressing autophagic flux through MR activation. Genetic or pharmacologic enhancement of BCN1-dependent autophagy restores endothelial homeostasis and prevents vascular and cardiac injury, identifying autophagy activation as a promising therapeutic approach for cardiovascular diseases associated with mineralocorticoid excess.

physiology↗

Single-Cell Proteomics Reveals Heterogeneous and Bimodal Proteome Responses to DNA Damage

DNA damage response (DDR) involves coordinated activation of repair, checkpoint, and stress-adaptive signalling pathways following genomic toxicity. Bulk-cell proteomics, however, averages divergent responses across neighbouring cells, obscuring the characterisation of biologically meaningful proteome remodelling during genotoxic stress. This is particularly relevant to DDR, where a subset of cells undergo apoptosis, resulting in the sampling of dead cells that confound downstream biological interpretation. Here, we applied single-cell proteomics (SCP) to investigate the proteome response of U-2 OS cells to 6-thioguanine (6TG)-induced DNA damage. By filtering individual cells according to predefined morphological-, sampling- and biological-criteria, to ensure a matched comparison between control and DNA-damaged populations; 6TG treatment was found to activate canonical DDR, including mismatch repair and base excision repair, together with secondary stress responses linked to oxidative stress, mitochondrial dysfunction, inflammatory signalling and proteostasis. Using SCP, we were able to probe neighbouring cell-to-cell heterogeneity, revealing globally increased protein abundance variability following DNA-damage. Importantly, mismatch repair protein MSH3 exhibited amongst the largest abundance increases, concomitant with the greatest reduction in cell-to-cell abundance heterogeneity across all quantified proteins, highlighting it as the most robust and reproducible responder to 6TG-induced DNA damage. Furthermore, analysis of protein-abundance heterogeneity revealed proteins that exhibit bifurcated abundance states across neighbouring cells, with DNA damage inducing either the emergence or loss of these bimodal abundance distributions. Proteins linked to gene expression and protein synthesis were driven towards bifurcation into discrete high-low protein abundance states across neighbouring cells following DNA-damage. Conversely, 6TG abolished the intrinsic high-low abundance bimodality of several core-signalling, stress-signalling and trafficking proteins, suggesting their coordinated homogenisation in response to genotoxic stress. Collectively, these findings demonstrate the power of SCP to resolve the coordinated, yet heterogeneous, cellular response to DNA damage within a population of genetically identical cells.

cell biology↗

Contextualized phenovectors reveal a Drosophila serotonergic circuit controlling satiety

Distinguishing whether a neural circuit genuinely controls a holistic behavioral state, rather than merely producing isolated effects, is a central challenge in neuroscience. Feeding research illustrates the problem: decades of work have reached conflicting conclusions partly because individual behavioral features are assessed in isolation. Here we establish a contextualized ethomics approach that benchmarks optogenetic circuit manipulations against natural hunger-satiety transitions, using high-dimensional behavioral tracking in Drosophila and starvation as a ground-truth intervention. Applying this framework, we find that serotonergic neurons marked by the Tryptophan hydroxylase neuronal (Trhn) enhancer are both required for and instructive of a satiety-like state, whereas other feeding-related circuits produce only fragmentary behavioral changes. Intersectional dissection localized this control to Trhn neurons of the ventral nerve cord, which act through the sugar transporter Sut2 to sense nutrient state. This work strengthens our understanding of serotonergic feeding control and provides a generalizable framework for validating circuit-state relationships.

neuroscience↗

Honey bee (Apis mellifera) gut microbiome associations with viruses and pesticides across Canadian agroecosystems

The honey bee (Apis mellifera) gut microbiome plays a central role in host health, yet its variation across agricultural landscapes remains poorly resolved. This study investigates how major environmental stressors, particularly pesticide exposure and RNA virus loadings, shape the honey bee gut microbiome in a large-scale field study conducted across Canada, spanning diverse agroecosystems from British Columbia to Quebec. We identify consistent associations between specific bacterial taxa and major RNA viruses, including enrichment of Serratia marcescens with SBV and depletion of Bombella intestini with BQCV. Pesticide exposure is likewise linked to reproducible shifts in key microbial taxa. Together, these findings reveal that interacting stressors jointly shape the bee gut microbiome and enable prediction of microbiome responses in agroecosystems. HighlightsDistinct associations identified between gut bacteria and major bee RNA viruses (BQCV, SBV, LSV, IAPV) Pesticide exposure is linked to reproducible shifts in key microbial taxa Combined virus-pesticide effects form coordinated clusters that predict microbiome variation and specific bacterial responses Integrated modeling demonstrates that environmental stressors can jointly explain microbiome structure beyond crop effects Graphical abstractSchematic overview of potential links between pesticide exposure and RNA virus infection and their effects on the bee gut bacterial community. Solid arrows indicate associations supported by the present study, whereas dashed arrows indicate hypothesized or unresolved interactions. Associations between the presence of specific bee RNA viruses (left) or pesticide residues (right) and changes in the relative abundance of particular gut taxa (pink {uparrow}, increased; blue {downarrow}, decreased). The pesticide subtype is indicated by the icon in the cell (leaf - herbicide, hyphae - fungicide and insect - insecticide). Several bacterial taxa showed reproducible associations with specific viral or pesticide variables, including Bombella intestini, Serratia marcescens, Melissococcus plutonius, Paenibacillus alvei, Apibacter sp. wkB309, and Gilliamella sp. A7. Abbreviations: BQCV Black queen cell virus; LSV, Lake Sinai virus; SBV, Sacbrood virus; IAPV, Israeli acute paralysis virus. (p/n/b) indicate the sample matrix in which the pesticide was detected, namely pollen, nectar, and bee tissue, respectively. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=133 SRC="FIGDIR/small/731697v1_ufig1.gif" ALT="Figure 1"> View larger version (40K): org.highwire.dtl.DTLVardef@cb92a4org.highwire.dtl.DTLVardef@1087045org.highwire.dtl.DTLVardef@102cabforg.highwire.dtl.DTLVardef@4ce2f1_HPS_FORMAT_FIGEXP M_FIG C_FIG

microbiology↗

Comparative Proteomics Across Tissues and Crop Agroecosystems Reveals Agricultural Stressor Responses in the Western Honey Bee

Maintaining honey bee health in crop production systems is increasingly difficult because worker bees encounter multiple chemical and biological pressures from pesticides and pathogens. How these field-realistic pressures affect molecular physiology across functionally distinct tissues remains poorly understood. Here, we tested whether tissue-resolved proteomics could separate stable tissue-specific patterns from crop-associated molecular changes. To do this, we profiled abdomen, gut, and head proteomes from honey bees collected across four Canadian crop ecosystems over two consecutive years, and integrated these data with pesticide-residue and pathogen-load measurements. Proteomic variation was structured by both tissue identity and crop environment. Tissue-specific proteomic profiles were characterized across samples, whereas crop-associated effects were detected in both years and were stronger in 2021, the second year of the study. Tissue-specific enrichment and network analyses linked the abdomen to lipid catabolism and ubiquitin-proteasome proteostasis, the gut to central carbon metabolism, membrane transport, vesicle trafficking, and cytoskeletal organization, and the head to neurosensory and mitochondrial functions, together with amino-sugar metabolism and vesicle-associated quality-control modules. Among the measured pesticide residues, boscalid was the most reproducible chemical correlate of proteomic variation, with the strongest signal in the gut. Cross-year validation associated boscalid exposure with reduced abundance of gut proteins involved in mitochondrial metabolism, protein quality control, vesicle trafficking, nutrient transport, and biosynthetic pathways. Additionally, integrated proteome-transcriptome-microbiome factor analysis further identified gut-centered components associated with measured stressor variables and linked protein-level variation to coordinated transcriptomic and microbial shifts. Independent-year validation showed that compact crop-associated protein signatures detected in 2020 were also present in 2021. Together, these results show that honey bee tissues maintain stable proteomic identities while showing tissue- and year-specific responses to pesticide and pathogen pressures encountered in crop ecosystems. The gut proteome may specifically provide a sensitive molecular indicator of pesticide-associated perturbation under field conditions.

bioinformatics↗

Compact adenine base editors to enable therapeutic rescue of Duchenne muscular dystrophy

Adenine base editors (ABEs) have emerged as a powerful gene-editing technology enabling precise and programmable adenine-to-guanine substitutions across the genome. However, their translation into in vivo therapeutics is limited by delivery challenges, as their size exceeds the packaging capacity of adeno-associated virus (AAV). Here, we report the discovery, structural characterization, and engineering of two compact, highly active ABEs built on novel deaminases and Cas9d nucleases, enabling all-in-one, single-vector AAV delivery. Applying these compact ABEs to Duchenne muscular dystrophy (DMD), we demonstrate efficient disruption of conserved splice-acceptor sites at dystrophin exons 45 and 51 in human skeletal muscle cells, enabling therapeutically relevant exon skipping. Together, these ABEs help expand the therapeutic reach of base editing towards diverse tissue types and disease targets.

bioengineering↗

A mushroom-body output neuron that mediates octopamine-driven and hunger-motivated feeding in Drosophila

Feeding behavior requires the integration of environmental cues, metabolic signals, and internal states through neuromodulatory networks, yet the role of specific neuromodulatory neurons and how they are coordinated in controlling feeding remains unclear. Using automated feed-tracking and optogenetics in Drosophila melanogaster, we found that activation of two octopaminergic neurons (VPM3/4) increases food consumption. Both VPM neurons form direct synapses with a mushroom-body output neuron MBON11, which, through opto-activation and opto-inhibition, can exert bidirectional control over food intake, with sexually dimorphic effects. Epistasis experiments demonstrated that octopamine-driven feeding requires functional MBON11 output. Additionally, we found that the dopaminergic PPL101 neurons, which also synapse with MBON11, are required for hunger-driven feeding. Ethomic analysis contextualized with natural hunger and satiety provided a holistic view of how different neuron types linked to the mushroom-body influence feeding behaviors. This analysis revealed that MBON11 interventions best recapitulate natural hunger-satiety transitions. These findings revealed a circuit where two neuromodulatory neuron types with distinct unidirectional feeding effects--octopaminergic VPM3/4 (instructive but not required) and dopaminergic PPL101 (required but not instructive)--converge onto MBON11, a neuron whose activity is both required for and instructive of hunger-related feeding. This circuit arrangement may represent an architecture for integrating multiple motivational signals in feeding regulation. Key pointsO_LIWhen activated, octopaminergic VPM3 and VPM4 cells drive increased food consumption, effects that require octopamine signaling and are dependent on MBON11 function. C_LIO_LIOctopaminergic neuronal activity is not required for hunger-driven feeding. C_LIO_LIReceiving direct synaptic inputs from VPM3 and 4, MBON11 neurons bidirectionally control feeding, and broadly phenocopy natural hunger-satiety transitions. C_LIO_LIDopaminergic PPL101 neurons that synapse onto MBON11 are required for hunger-motivated feeding. C_LIO_LIMBON11 appears to integrate octopaminergic and dopaminergic signals, and regulate the feeding behavioral state. C_LI

neuroscience↗

Getting over ANOVA: Estimation graphics for multi-group comparisons

Data analysis in experimental science mainly relies on null-hypothesis significance testing, despite its well-known limitations. A powerful alternative is estimation statistics, which focuses on effect-size quantification. However, current estimation tools struggle with the complex, multi-group comparisons common in biological research. Here we introduce DABEST 2.0, an estimation framework for complex experimental designs, including shared-control, repeated-measures, two-way factorial experiments, and meta-analysis of replicates.

bioinformatics↗

Promiscuous Metal Site in Hepatitis B Virus X Protein Binds anFe-S Cluster

The Hepatitis B virus (HBV) regulatory protein HBx is essential for viral replication and pathogenesis, yet its cofactor specificity and ligand environment remain poorly defined. Although HBx binds either an Fe-S cluster or Zn, its intrinsic disorder and mutational tolerance have hindered its precise characterization. Here, we integrate chemoproteomics with HYSCORE spectroscopy to identify the metal-coordinating ligands in HBx. Histidine coordination is excluded, while C61, C69, C143, and C148 emerge as primary cysteine ligands for the Fe-S cluster, with C137 acting as a conditional ligand. These residues also bind Zn and are associated with HBx transactivation and clinically relevant variants. HBx engages the host cytosolic Fe-S machinery and displays sensitivity to Fe-S-targeting reagents, behavior consistent with Fe-S cluster acquisition and lability. Together, these findings suggest that HBx functionally behaves as an Fe-S cluster-associated protein, highlighting a potentially druggable vulnerability in HBV replication. Significance StatementFe-S clusters are emerging as key cofactors in viral replication but are often mistaken for Zn due to O2-sensitivity and shared cysteine coordination. The Hepatitis B virus HBx protein, essential for viral replication and hepatocarcinogenesis, has long been mechanistically intractable, with debate over its metallocofactor. Here, we provide evidence that HBx coordinates an Fe-S cluster, placing it within the growing family of viral Fe-S-cluster-containing proteins. Using chemoproteomics, we identify its cysteine ligands, overcoming limitations of mutational analysis in disordered proteins. Although HBx binds both an Fe-S cluster and Zn, its interaction with human Fe-S assembly factors suggests a functional link to Fe-S cluster biology, while its sensitivity to TEMPOL and NO reveals a potentially druggable vulnerabilityin HBx.

biochemistry↗

Cilia.io: Computer vision and machine learning reveal spatial patterns of cilia beating dynamics in the spinal cord

Motile cilia coordinate fluid flows that are essential for normal tissue physiology and function. Cilia display diverse beating waveforms, and while pronounced defects are strongly associated with motile ciliopathies, more subtle alterations may also influence disease manifestations. Finer quantification of ciliary dynamics is critical for a full understanding of cilia-associated disorders, but the heterogeneity of cilia beating dynamics makes accurate and robust characterization challenging. Because existing tools have proven to be limiting in noisy in vivo environments, we developed Cilia.io, a machine learning (ML)-based quantification tool that uses state-of-the-art vision transformers to segment cilia out of the background based on their biological features. Cilia.io enables fast, accurate, and reproducible quantification of motile cilia morphodynamics and outperforms existing tools. Indeed, using Cilia.io, we discovered distinct regional differences in ciliary waveforms in the zebrafish spinal cord. The ability of Cilia.io to capture subtle ciliary defects was further demonstrated by analyzing a novel allele in the ciliopathy gene bbs2 that causes a highly heterogeneous scoliosis phenotype. In these mutants, only dorsal cilia displayed altered beating dynamics, while ventral cilia remained largely unaffected. Our new tool therefore represents a substantial advance on existing methods and suggests that additional fine-scale analyses of ciliary beating will be important for understanding organismal phenotypes and cilia-driven disease.

developmental biology↗

A simple circuit to sustain intact tumor microenvironments for complex drug interrogations

Deep learning and large language models can integrate complex datasets to uncover biological insights that are often undetectable through conventional analyses. With application to translational cancer research, these computational tools have positioned 3D patient-derived tumor avatars front and center as crucial data input sources. However, a major challenge remains: the lack of standardization in media composition in 3D patient-derived tumor models unpredictably affects cell behavior and limit the utility beyond predicting treatment responses. To address this unmet need, we developed a simple, reproducible perfusion circuit system to approximate in vivo physiology using autologous patient plasma. With peritoneal metastases and core needle biopsies across multiple tumor histologies, we demonstrate preservation of the tumor microenvironment for up to 48 hours using multi-modal interrogation techniques. With proof-of-concept experiments, we display the systems ability to unveil complex drug-dependent biology within this time window. Standardizable, physiologically relevant platforms for 3D patient-derived tumor avatars will yield unprecedented insights through the integration of data from broad groups of patients and the use of an expanding armamentarium of artificial intelligence capabilities.

cancer biology↗

Circadian phosphotimer generates time cues through PER dimerization-mediated trans-phosphorylation

The circadian clock generates autonomous molecular rhythms that regulate sleep cycles, chronotypes, daily physiology, and expression patterns of almost the entire genome. Temporal phosphorylation of PERIOD (PER) proteins creates a phosphotimer that is critical for clock function. Although previous studies show that PER stably binds the casein kinase CK1, cis-acting phosphorylation of PER by CK1 is not compatible with slow PER phosphorylation extended over 24 hrs. So how can PER phosphorylation be programmed in a slow and controlled manner? Here, we show that the timing cues are encoded by PER-PER dimerization-mediated trans-phosphorylation, which enables the necessary time delay in phosphorylation and slow phosphorylation. When PER dimerization is disrupted, PER phosphorylation and circadian rhythms are severely compromised. In mouse models with point mutations in the PER dimerization domain, circadian period is shortened to [~]20 hrs, and the phase of wake/sleep cycles is dramatically advanced, switching a nocturnal animal to a half diurnal animal.

neuroscience↗

An in vivo parallelized reporter assay to uncover tissue-specific splicing regulatory sequences in a multicellular animal

Introns play a critical role in regulating alternative splicing. However, identifying functional intronic motifs is challenging due to their short and degenerate sequence composition. Massively parallel reporter assays have provided insights into cis-regulatory logic governing alternative splicing, but these approaches are generally performed in cell culture, limiting their ability to capture tissue-specific contexts. Here, we implemented in vivo Parallelized Reporter Assays in C. elegans neurons and muscle cells to screen for intronic enhancer and silencer motifs among thousands of randomized sequences. We identified nearly 200 sequences regulating splicing in these tissues. We uncovered core sub-sequences with tissue-biased enhancing and silencing activity, including motifs recognized by well-characterized RNA-binding proteins, and orphan motifs with no obvious cognate binding protein. Mapping our PRA-derived motifs to native introns flanking tissue-biased alternative exons revealed their conservation across nematodes, supporting their functional relevance. Additionally, individual intronic regions frequently contained diverse combinations of these motifs, indicative of complex engagement of these sequences by RNA-binding proteins. Finally, we performed targeted mutagenesis of PRA-derived intronic enhancers flanking a neuronal microexon, identifying key cis-regulatory determinants of microexon splicing. Together, our study provides a framework to explore the role of intronic regions in tissue-specific splicing regulation within a multicellular organism. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=107 SRC="FIGDIR/small/670696v1_ufig1.gif" ALT="Figure 1"> View larger version (24K): org.highwire.dtl.DTLVardef@84d5daorg.highwire.dtl.DTLVardef@f3f625org.highwire.dtl.DTLVardef@a53739org.highwire.dtl.DTLVardef@ccbb03_HPS_FORMAT_FIGEXP M_FIG C_FIG

molecular biology↗

A Rapid Multiplex LAMP Assay for Point-of-Care Detection of CT, NG, TV, and Fluoroquinolone Resistance in NG

Rapid point-of-care (POC) diagnostics are essential tools for improving timely treatment and reducing the transmission of sexually transmitted infections (STIs). The STI NG Plus Assay is a rapid multiplex LAMP (loop-mediated isothermal amplification) NAAT (nucleic acid amplification test) capable of simultaneously detecting Chlamydia trachomatis (CT), Neisseria gonorrhoeae (NG), Trichomonas vaginalis (TV), and fluoroquinolone resistance-associated mutations in NG (gyrA S91F). In this study, we assessed the STI NG Plus assay primer design and analytical sensitivity. Using a bioinformatically optimized primer design pipeline and empirical screening, the assay demonstrated high inclusivity and specificity, with no cross-reactivity to 48 urogenital organisms or the human genome. Analytical sensitivity testing showed reliable detection of all targets in both lysis buffer and clinical matrix. Limits of detection were lower than those of an existing FDA-cleared test. The assays robustness, speed, and sensitivity support its potential for decentralized STI testing with integrated antimicrobial resistance profiling.

molecular biology↗

Single-Cell RNA Sequencing and Inferred Protein Activity Analysis Reveal a Distinct Tumor Phenotype in Early-Onset Colorectal Cancer Patients

Colorectal cancer (CRC) diagnosed before age 50 years (early-onset CRC, EO-CRC) is rising at an alarming rate, yet its molecular and microenvironmental drivers remain poorly understood. EO-CRC is highly heterogeneous, and while subtle differences from late-onset CRC (LO-CRC) have been reported, their full extent remains unresolved due to the limited scope of previous studies. Here, we integrate public data with in-house clinical samples profiled by single-cell RNA sequencing (scRNA-seq) and multiplex immunofluorescence (mIF) to compare EO-CRC and LO-CRC. Additionally, we employ gene regulatory network-based protein activity inference (VIPER), enabling a more precise characterization of key regulatory proteins driving tumor-stroma interactions. Our analysis reveals that EO-CRC and LO-CRC have a largely similar immune composition, challenging previous reports of an "immune-cold" phenotype in EO-CRC. However, we identify distinct stromal differences, including a significant enrichment of fibroblasts in EO-CRC. Notably, we define a previously unrecognized epithelial subpopulation in EO-CRC, marked by high expression of toll-like receptor 4 (TLR4) and C-C chemokine receptor type 5 (CCR5)--key mediators of inflammation-driven tumor progression and fibroblast recruitment. These findings suggest that EO-CRC may be driven by a tumor-intrinsic inflammatory phenotype with enhanced stromagenesis, providing new insights into potential mechanisms underlying its increasing incidence in young adults.

cancer biology↗

Increasing Stemness Drives Prostate Cancer Progression, Plasticity, Therapy Resistance and Poor Patient Survival

BackgroundCancer progression is often accompanied by dedifferentiation and acquisition of stem cell-like properties (stemness). In prostate cancer (PCa), lineage plasticity and therapy resistance remain major clinical challenges, yet a unified quantitative transcriptomic framework connecting stemness, androgen receptor (AR) signaling, castration resistance, and disease progression across the PCa continuum is lacking. MethodsWe integrated 87,339 transcriptomic profiles from 33 preclinical and clinical datasets spanning the PCa continuum from normal prostate and treatment-naive primary PCa (Pri-PCa) to PCa treated with neoadjuvant ADT (nADT) and metastatic castration-resistant PCa (mCRPC), with single-cell RNA-seq analyses encompassing 115,197 cells. Cancer stemness was quantified using a transcriptome-derived mRNA-based Stemness Index (mRNAsi; hereafter Stemness), and a 12-gene PCa-Stem signature was developed to capture PCa-specific stemness. Stemness, PCa-Stem, canonical AR activity (c_AR-A), castration-reprogrammed AR activity (cr_AR-A), RB1-loss, PTEN-loss, and MYC activity signatures were quantified across cohorts. Functional validation included MYC inhibition and representative PCa-Stem signature gene depletion in PCa models. Clinical prognostic significance was evaluated in independent patient cohorts. ResultsThe Stemness score and c_AR-A increased concordantly during early prostate tumorigenesis but diverged with PCa progression: as Gleason grade increased, c_AR-A declined while Stemness continually increased. mCRPC exhibited the highest Stemness and lowest c_AR-A, a pattern recapitulated in Pten/Rb1/Trp53-deficient mouse models. Global Stemness increased progressively across the PCa continuum, was enriched in aggressive PAM50-LumB and PCS1 subtypes, associated with proliferative and lineage plasticity programs, and predicted poor patient survival. The newly derived 12-gene PCa-Stem signature provided a PCa-specific molecular representation of Stemness and tracked disease progression and poor patient survival. Network analyses identified a coordinated mitotic regulatory program linking MYC activity, RB1-loss, cr_AR-A, and the PCa-Stem signature. Spatial and single-cell transcriptomic analyses localized the PCa-Stem program to lineage plasticity-related epithelial cells and demonstrated progressive expansion of PCa-Stem epithelial cells during PCa progression. Functional perturbation of representative PCa-Stem signature genes, as well as genetic and pharmacological MYC inhibition, consistently suppressed Stemness-associated phenotypes in diverse PCa models. ConclusionsCancer Stemness quantitatively captures PCa aggressiveness, lineage plasticity, treatment resistance, disease progression, and poor patient survival. cr_AR-A, RB1 loss, and MYC activation cooperate to reinforce the high-Stemness state and therapy resistance in mCRPC. Collectively, our work establishes a trajectory-integrated transcriptomic framework defining cancer Stemness as a quantifiable molecular and clinical determinant of PCa aggressiveness, lineage plasticity, disease progression, therapy resistance and patient survival.

cancer biology↗