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Results for “evolutionary biology”

Search indexed bioRxiv preprints in genomics, neuroscience, cell biology and bioinformatics. Read source abstracts and check manuscript versions; preprints are not peer reviewed.

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bioRxiv2026

A COJEC-chemotherapy resistant model of Th-ALK(F1174L)/MYCN neuroblastoma offers insights into tumour immune evasion and development of the bone marrow metastatic niche

Multi-agent COJEC chemotherapy is the main-stay of induction treatment for patients diagnosed with high-risk neuroblastoma. However, at least 10% of patients will be primary refractory to chemotherapy and only 50% achieve 5-year overall survival. The bone marrow is the most frequent site of metastasis in these patients. Novel approaches are required to improve response rates but the inter- and intra- patient tumour heterogeneity and dynamics of the neuroblastoma immune microenvironment makes anticipation of resistance phenotypes incredibly challenging. We present here a novel immunocompetent C57 Bl/6 model of Th-ALK(F1174L)/MYCN neuroblastoma, in which spontaneous abdominal tumours are driven by expression of mutant Anaplastic Lymphoma Kinase and over-expression of Mycn in the neural crest. We have used this model to generate a personalised dosing schedule inducing COJEC-chemotherapy resistance, in which individual mice receive chemotherapy cycles dependent upon the progression of their neuroblastoma tumours. Using both single cell RNA sequencing and spatial immunophenotyping gave us extraordinary precision in our comprehensive analysis of the tumour intrinsic and microenvironmental factors associated with COJEC resistance. We found that the resistance phenotype was driven by Cdk8 upregulation in adrenergic and mesenchymal tumour cells. Infiltration of immunosuppressive myeloid-derived immune cells and remodeling of the tumour-associated stroma further contributed to COJEC resistance. In the bone marrow we observed expansion of neutrophils and evidence of NETosis associated with micro-metastatic disease. Our results further endorse the development of CDK8-targeting therapeutics for neuroblastoma patients which might boost the anti-tumour immune response. Additional studies will be required to define the roles of neutrophils and neutrophil NETosis in neuroblastoma progression and metastasis. Our C57 Bl/6 model will be pivotal in future preclinical studies of immune-modulating therapeutics.

cancer biology↗

bioRxiv2026

The Anti-Cancer Effects of Selected Indigenous Medicinal Plants of the Arid Bioregion

Ethnopharmacological relevance: Australian Indigenous medicinal plants represent a valuable yet underexplored source of bioactive compounds with potential therapeutic relevance. The Iningai community of Central Queensland has traditionally used native plants to manage conditions associated with inflammation, pain, infection, and general illness. Scientific evaluation of these plants may provide evidence for their customary applications and identify bioactivities relevant to anticancer biodiscovery. Aim of the study: This study evaluated leaf and stem extracts of seven medicinal plants-Pittosporum angustifolium, Alphitonia excelsa, Calytrix microcoma, Geijera parviflora, Melaleuca uncinata, Gossypium australe, and Eucalyptus similis-traditionally used by the Iningai community, focusing on three biological processes relevant to cancer: oxidative stress, inflammation, and cellular proliferation. Materials and methods: Antioxidant activity was assessed using DPPH radical-scavenging and ferric reducing antioxidant power (FRAP) assays. Anti-inflammatory activity was evaluated in lipopolysaccharide (LPS)-stimulated THP-1 macrophage-like cells by profiling IFN-, TNF-, IL-6, IL-12, IL-18, and IL-23. Antiproliferative activity was assessed using MTT-based viability assays in human and murine liver cancer cell lines (Huh7, Hep3B, Hep-55.1c, and A52). Results: The extracts exhibited distinct biological activity profiles. G. parviflora stem and C. microcoma leaf extracts showed the strongest antioxidant activities, whereas P. angustifolium stem exhibited the weakest radical-scavenging capacity. Cytokine responses were extract-specific, with E. similis leaf extract demonstrating broad and pronounced suppression of multiple LPS-induced pro-inflammatory cytokines. Several extracts produced concentration-dependent reductions in liver cancer cell viability, with P. angustifolium stem exhibiting the most consistent and potent antiproliferative activity across the cell lines tested. Notably, strong antioxidant or anti-inflammatory activity did not necessarily correspond with antiproliferative activity. Conclusion: Australian Indigenous medicinal plant extracts demonstrated distinct antioxidant, immunomodulatory, and antiproliferative activities rather than uniform bioactivity across experimental systems. The divergent activities of G. parviflora, C. microcoma, E. similis, and P. angustifolium highlight the importance of integrated biological screening and support the value of Indigenous knowledge-guided biodiscovery. These plants represent promising sources for further investigation of selective bioactive compounds with potential relevance to anticancer drug discovery.

cancer biology↗

bioRxiv2026

Immune-metabolic-redox ecosystems define spatially organized tumor states in head and neck squamous cell carcinoma.

Background: Spatial organization is increasingly recognized as a key determinant of tumor-immune interactions in head and neck squamous cell carcinoma (HNSCC). The GSE300147 Xenium spatial transcriptomic resource generated by McCord and colleagues established a framework for mapping spatially coordinated T-cell states in HNSCC. However, how tumor-enriched epithelial immune states relate to metabolic, redox, and stress-adaptive transcript programs remains incompletely defined. Methods: A secondary, data-driven reanalysis of GSE300147 was performed, focusing on 17 confirmed HNSCC Xenium sections after exclusion of a non-HNSCC ameloblastoma specimen. A total of 1,148,244 cells were analyzed, including 558,867 EpCAM+ tumor-enriched epithelial cells. Tumor-enriched epithelial cells were classified into Hot, Intermediate, and Cold states using a Composite Hotness framework integrating T-cell inflammatory signature score, checkpoint-associated signaling, CD274 expression, IFN/antigen-presentation signature score (IFN/AP), and tumor-immune proximity. Six metabolic ecosystem states, neighborhood profiling, spatial permutation testing, and an integrated Immune-Metabolic-Redox Ecosystem Score (IMRES) were then applied. Results: Immune activation was spatially heterogeneous across HNSCC sections. Immune-hot tumor-enriched epithelial regions showed not only inflammatory, checkpoint-associated, and antigen-presentation signature scores, but also coordinated metabolic, oxidative-redox, and stress-response transcript programs. IMRES, derived from available immune, metabolic, redox, and stress-response transcript components represented in the Xenium panel, increased progressively from Cold to Intermediate to Hot tumor-enriched epithelial states and was associated with NFE2L2, GDF15, HLA-DRA, CD274, KEAP1, and MDM2. Integrating IMRES with Composite Hotness identified a distinct Hot+IMREShigh ecosystem comprising 106,874 tumor-enriched epithelial cells. This state showed the strongest immune-active and stress-adaptive features and was positioned closer to immune populations than expected by random assignment. An alternative rank-based robustness analysis reproduced the IMRES-associated ecosystem axis and correlated with the original module-based score (Spearman r = 0.597). Conclusions: This secondary reanalysis extends the original spatial T-cell framework by defining a complementary tumor-centered immune-metabolic-redox ecosystem in HNSCC. IMRES provides a transcript-derived framework for identifying Hot+IMREShigh neighborhoods where immune activation, checkpoint signaling, metabolic remodeling, and stress adaptation converge, providing a hypothesis-generating framework for studying immune resistance and therapeutic vulnerability.

cancer biology↗

bioRxiv2026

Differential expression of NEAT1 in the corneal endothelium increases susceptibility to oxidative stress in Fuchs Endothelial Corneal Dystrophy

Fuchs endothelial corneal dystrophy (FECD) is a disease of the corneal endothelium (CE) characterized by the loss of corneal endothelial cells (CECs) and guttae formation, ultimately resulting in corneal edema and vision loss. FECD primarily affects the central CE while sparing the peripheral CE, however the underlying mechanism contributing to the spatial differences remain unknown. Oxidative stress has been increasingly recognized as a key contributor to the pathogenesis of FECD, with CECs being particularly susceptible to damage from reactive oxygen species (ROS), high metabolic activity and ultraviolet induced DNA damage. The non-proliferative nature of CECs, along with the accumulation of oxidative damage can ultimately lead to CEC loss, a key feature of FECD. In this study, we induced oxidative stress with hydrogen peroxide (H2O2) on ex-vivo corneal specimens and observe increased cell death in the central region compared to the peripheral CE. To investigate these underlying differences, we performed bulk RNA sequencing (RNA-seq) on the central and peripheral regions of CE from FECD and normal cadaveric donors. Pathway analysis identified an enrichment of genes involved in collagen and extracellular matrix between the central and peripheral regions of CE in both normal and FECD, as well as between normal and FECD CE. Intriguingly, we identified the long non-coding RNA (lncRNA), NEAT1 as a top differentially expressed gene, with reduced expression in the central CE compared to the peripheral CE and lower expression in FECD compared with normal CE. Using corneal endothelial cell lines and ex-vivo specimens from FECD patients and normal cadavers, we found decreased NEAT1 expression levels in FECD and increased susceptibility to H2O2-induced oxidative stress. We observed that NEAT1 knockdown in normal and FECD cells exacerbated H2O2-mediated oxidative stress, and that NEAT1 overexpression protected FECD cells. We report in this study, a novel insight in the spatial differences in gene expression in the CE and identify reduced expression of NEAT1 in the central CE as a potential contributor to oxidative stress-related cell death in FECD. These findings provide novel insight into FECD pathogenesis and why FECD pathology preferentially affects the central CE. Antioxidants targeting NEAT1 signaling could be developed into novel therapeutics aimed at preventing FECD pathogenesis.

cell biology↗

bioRxiv2026

ENPP3 expressed by HER2-positive breast cancer cells is associated with good prognosis by restraining epithelial-to-mesenchymal phenotype

Background Ectonucleotide pyrophosphatase/phosphodiesterase 3 (ENPP3/CD203c) is largely studied as a marker of mast cells and basophils. By depleting extracellular ATP, it prevents excessive activation of mast cells and basophils, hence reducing inflammation and allergic reactions. Recent findings have also shown that Enpp3 can deplete cGAMP, another molecule involved in STING activation and IFN-mediated pro-inflammation. Little is still known regarding the role of Enpp3 in non-immune cells although a few reports have described its expression in healthy tissues and tumors. Methods In silico analysis were performed to investigate the expression levels and the prognostic value of Enpp3 in breast cancer, together with ovarian, prostate and colon carcinoma. ENPP3 expression was evaluated in formalin-fixed, paraffin-embedded tumor samples of breast cancer patients by immunohistochemistry, and in mouse mammary cancer cell lines by western blots. Cells were treated with EGFR ligands to stimulate the EGFR/HER2 axis. A mouse-derived mammary cancer cell line was engineered by CRISPR/Cas9 to introduce a GFP sequence under the control of the Enpp3 promoter. GFP-positive and -negative cells were sorted and analyzed by gene expression profiling to identify genes and pathways associated with Enpp3 expression. Finally, wild type and Enpp3 knockout cells were injected in the fat pad of Wsh mice, which do not have mast cells, to evaluate the growth of the tumors which were further analyzed by immunohistochemistry. Results We provide evidence that HER2-positive cells express higher levels of ENPP3 in samples of breast cancer patients. Moreover, in vitro models confirmed that HER2 expression and EGFR stimulation result in up-regulation of Enpp3. We identified pathways that can concur to Enpp3 expression and showed that in vivo the absence of Enpp3 promotes tumor growth and development of tumors with a marked epithelial-to-mesenchymal phenotype. Finally, in a small cohort of HER2-positive breast cancer patients, we found that ENPP3 expression correlates with increased relapse-free survival. Conclusions Despite its potential immunosuppressive role, our findings support the notion that ENPP3 expression is promoted by HER2 in breast cancer, and that it is endowed with a positive prognostic value.

cancer biology↗

bioRxiv2026

Multiscale modelling of drug-host-pathogen interaction: quantifying drug and immune contributions to treatment response

Background and Objective: Predicting treatment outcomes in infectious diseases requires accounting for the interplay between drug effects, pathogen dynamics, and host immunity. Integrating pharmacological and immunological approaches into a single simulation environment remains a fundamental challenge in both theory and practice. We aimed to develop and validate a multiscale in silico framework coupling these processes, and to quantify their respective contributions to bacterial clearance. Methods: We present the Drug-Host-Pathogen Interaction (DHPI) framework, combining three independent mechanistic components: a physiologically based pharmacokinetic model of drug disposition, a pharmacokinetic-pharmacodynamic model of drug-induced bacterial killing, and a stochastic agent-based model of the immune response. Continuous concentration profiles are time-averaged onto the agent-based time grid, assigned to bacterial phenotypic states, and converted into per-agent killing probabilities, so that drug-mediated and immune-mediated death events are recorded separately at each step. The framework was applied to simulate symptomatic pulmonary tuberculosis. Phenotype-specific drug-efficacy parameters were inferred using Approximate Bayesian Computation from historical clinical data on eight weeks of 600 mg rifampicin monotherapy, and validated against independent early bactericidal activity data over a disjoint time window. Results: The calibrated framework reproduced the observed decline in bacterial load, and matched reported early bactericidal activity over the first week. In a virtual cohort of symptomatic patients, drug-mediated killing accounted for 81-88% and immune-mediated killing for 12-19% of total bacterial elimination over the 60-day treatment course, while the dormant, granuloma-contained fraction rose from 0.20-0.29 in the first week to 0.85-0.89 at treatment completion. Over a follow-up of up to 50 years, patients reaching clinical cure had accumulated more memory lymphocytes during treatment than those progressing to clinical failure or death; moreover, the final outcome depended on the immune changes occurring during therapy rather than on the initial disease stage. Conclusions: The results show that the DHPI framework can reproduce treatment dynamics observed in patients and enable the analysis of how therapy reshapes host immune responses and subsequent disease trajectories. By explicitly representing drug-host-pathogen interactions, it provides a mechanistic basis for in silico treatment simulations and for the study of long-term immune consequences of antimicrobial therapy.

systems biology↗

bioRxiv2026

A replicated patient-specific component of tumour telomere length across two pan-cancer cohorts

Bulk telomere length measured from tumour sequencing is routinely interpreted as a property of the cancer cells. However, a tumour specimen is a mixture, and the patient who supplies it has a telomere length of their own. Here I re-analyse published pan-cancer telomere estimates and ask how much of a tumour's telomere length is patient-specific. A calibration step comes first. Whole-genome and low-pass estimates recover the known cross-sectional attrition of leukocyte telomeres with age, at 26.6 bp per year in blood normals, whereas whole-exome estimates do not. After adjustment for cancer type, sequencing centre and sex, the exome slope is minus 0.6 bp per year. In 684 blood-normal aliquots sequenced by both assays, the whole-genome estimate declines at 38.9 bp per year, whereas the exome estimate from the same DNA shows no detectable decline. The difference between assays is 41.5 bp per year, with P = 3 x 10^-10. Because exome data constitute 78.6% of the original resource, downstream analyses use only whole-genome and low-pass libraries. Within those data, tumour telomere length tracks the patient's matched-normal telomere length. The Spearman correlation is 0.395 in TCGA, with positive associations in 22 of 23 cancer types. This finding replicates in PCAWG using a different telomere estimator, with a correlation of 0.472 and positive associations in all 24 histologies examined. Adjustment for cancer type, sequencing centre and library type leaves a regression coefficient of 0.385. The association is also stable after adjustment for age, sex, tumour purity, leukocyte fraction, ploidy, sequencing coverage and continental ancestry, with coefficients ranging from 0.406 to 0.429. Pure normal-cell admixture is rejected as the sole explanation. Under a two-compartment mixture model, the coefficient for host telomere length is expected to equal 1 and the host-by-purity interaction to equal minus 1. These restrictions are jointly rejected with P = 0.001. Tumour purity, leukocyte fraction and age each explain only about 1 to 3% of within-cohort variance and do not alter the cross-cancer ranking. By contrast, the between-cohort coefficient is not directly interpretable. Its apparent near one-to-one relationship with tissue-associated telomere length depends strongly on which tissue supplies the matched-normal reference and on the statistical spread of that predictor, falling to 0.44 when organ-matched solid tissue is used. Bulk tumour telomere length is therefore a composite phenotype containing a replicated patient-specific component. Telomere biomarker studies should include matched-normal telomere length as a covariate rather than treating tumour telomere length as exclusively tumour-intrinsic.

cancer biology↗

bioRxiv2026

Both environmental filtering and intraspecific variation shape small mammals' elementomes

The biogeochemical niche hypothesis (BNH) proposes the multi-elemental composition of organisms - their elementome - as a new ecological dimension. However, which ecological factors shape elementome assembly remains little known, especially in animals. Here, we studied the mandibular elementome of two sympatric small mammals - Apodemus flavicollis and Clethrionomys glareolus - to assess how intraspecific variability (ontogenetic changes in body mass and sex under the vertebrate bone hypothesis; VBH) and environmental filtering (season and habitat) shape essential and non-essential elementome assembly. Species showed moderate elementome segregation and seasonal niche partitioning, with implications for coexistence. Ontogenetic body mass predicted elemental variation and calcium substitution, with several hypermetric scalings in autumn indicating strong departures from mass-invariant homeostasis. Finally, our results suggest a dichotomy: essential elementomes were mainly driven by intraspecific variation, whereas non-essential elementomes were rather shaped by environmental filtering. Our results position animal elementomes as an integrative ecological dimension linking organismal biology, species interactions, and environmental filtering across individuals, populations, and species.

ecology↗