Biology subjects

Jolly, M. K.

Publications and source records attributed to Jolly, M. K..

At least 19 recordsLinked to original sources

bioRxiv2026

MHC-I downregulation is associated with immune-evasion in breast cancers with heterogeneous activation of epithelial-mesenchymal plasticity

Cancer cell-intrinsic epithelial-mesenchymal plasticity (EMP) drives carcinoma progression through increased intratumoral heterogeneity and an immunosuppressive tumor microenvironment (TME). Specifically, EMP activation in murine mammary carcinomas results in exclusion of CD8+ T-cells and recruitment of immunosuppressive M2-like macrophages, resulting in resistance to anti-CTLA-4 immune checkpoint blockade (ICB) therapy. Notably, mixed E-qM tumors in which only 10% of cancer cells have activated EMP are resistant anti-CTLA-4 immune checkpoint blockade (ICB) therapy. This suggests that minority fractions of qM cancer cells could, in theory, exert immunosuppressive effects on surrounding E cancer and immune cells to shield the entire heterogeneous tumor against immune attack. However, this has not yet been demonstrated. Here, we use spatial transcriptomic profiling to demonstrate that mixed E-qM tumors assemble immunosuppressive cellular niches. Furthermore, E cancer cells within mixed E-qM tumors experience long-term MHC-I downregulation leading to resistance to elimination by CD8+ T-cells. This is associated with the exclusion of T-cells from the tumor core and a dysfunctional phenotype in the remaining CD8+ T-cells. qM cancer cells recruit immunosuppressive M2-like macrophages to mixed tumors, which further downregulates E cancer cell-intrinsic MHC-I levels. Finally, we demonstrate that human triple-negative breast cancers with increased EMP activation exclude T-cells from the tumor core. Together, these findings reveal that qM cancer cells modulate the immune infiltrate of mixed tumors, promoting MHC-I downregulation and evasion of immunological control by CD8+ T-cells.

cancer biology↗

bioRxiv2026

Cyclic Hypoxia drives Wnt5a-ROR1 stroma-tumor crosstalk promoting breast cancer growth

Tumor hypoxia can be stable, or cyclic based on proximity to vasculature, and affects not just the cancer cells, but also other cells in the tumor microenvironment (TME). Although cyclic hypoxia can affect cells in the tumor microenvironment differently from stable hypoxia, its effect on non-malignant cells in the tumor microenvironment (TME) is unclear. Here, using single cell RNA ATAC sequencing of multicellular co-culture model of triple-negative breast cancer (TNBC), comprising MDA-MB-231 cells, fibroblasts (Fbs), mesenchymal stromal cells (MSCs), endothelial cells, and macrophages, we systemically map the transcriptomic response shaped by dynamic oxygen regimes. Cyclic hypoxia induced a distinct transcriptional program compared to stable hypoxia in a cell type specific manner, regulating cell subpopulation proportions with key phenotypic implications. In TNBC, cyclic hypoxia reversed chronic hypoxia-induced cell cycle arrest, and reversed the enrichment of a highly mesenchymal WNT5A+/COL6+ subpopulation stabilized in hypoxia. Furthermore, cyclic hypoxia increased fibroblast activation, but suppressed MSC proliferation. Mechanistically, cyclic hypoxia coordinated paracrine WNT5A/B-ROR1 signaling between fibroblasts and TNBCs. In a mouse breast CAF-TNBC co-xenograft model, disrupting this cyclic hypoxia driven WNT5A-ROR1 stroma-cancer crosstalk reduced tumor growth in vivo. Together, our findings highlight dynamics in oxygen regimen as distinct microenvironmental cues, reprograming the TME compartments to accelerate cancer growth and invasion.

cancer biology↗

bioRxiv2026

Malignant and stromal partial EMT programmes and cetuximab outcome in head and neck cancer

Partial epithelial-to-mesenchymal transition (pEMT) was defined in single malignant cells of head and neck squamous cell carcinoma but is usually scored in bulk tumours. In three single-cell datasets, its laminin-332 and hemidesmosome genes were expressed by malignant cells (the malignant arm) and its fibrillar collagens and vimentin by fibroblasts (the stromal arm). In bulk tumours the stromal arm dominated co-expression, so standard pEMT scores mainly measure stroma. We recovered the malignant arm with a classifier trained on single cells and a 12-gene core. In 40 patients treated with platinum and cetuximab, both malignant measures were higher in those with long progression-free survival (area under the curve 0.78 and 0.82), and the stromal arm was not. The malignant arm was inseparable from the Basal subtype, whose score did as well or better in these patients (0.93) and in two xenograft panels. Bulk pEMT scores should be read by cell of origin.

cancer biology↗

bioRxiv2026

Impact of oxygen fluctuation and consumption on the dynamics of a reduced go-or-grow model for tumor cell invasion

We propose a minimal mathematical framework to describe the go-or-grow dynamics of tumor cells comprising two phenotypically distinct populations. One population is migratory and undergoes constant diffusion, while the other proliferates in an oxygen-dependent manner. The local oxygen concentration governs transitions between these phenotypes. We then ask whether the time scale of cyclic hypoxia, where oxygen is spatially homogeneous but fluctuates between normoxic and hypoxic levels over time, alters the dynamics of the reduced generalist model in the fast phenotype-switching regime compared with the full go-or-grow model. We observe that the reduced generalist phenotype model fails to capture the go-or-grow dynamics under rapid oxygen fluctuations. Our results predict that the tumor growth rate increases in the generalist-phenotype model under rapid oxygen fluctuations compared with tumors of the proposed go-or-grow model. We then explore whether oxygen consumption, which leads to spatial heterogeneity in oxygen concentration, plays a role in distinguishing the dynamics of the reduced model from the proposed go-or-grow model. We demonstrate that the tumor in the proposed go-or-grow model exhibits a higher growth rate than the tumor in the reduced generalist-phenotype model under a slow oxygen consumption rate.

systems biology↗

bioRxiv2026

A Nanomechanical Fingerprint of Centromeric Methylation Co-Localization in TNBC Chromosomal Instability

Centromeric heterochromatin is maintained by a self-reinforcing loop between DNA methylation (5mC) and histone H3 lysine 9 trimethylation (H3K9me3), yet whether this coupling is preserved at the level of individual chromosomes in cancer has been inaccessible to conventional epigenomic assays, which average signals across cell populations and cannot resolve single-chromosome heterogeneity. Here, we use antibody-functionalized atomic force spectroscopy to simultaneously map 5mC and H3K9me3 at the centromeres of individual metaphase chromosomes from non-tumorigenic, luminal, and triple-negative breast cancer (TNBC) cell models. Co-localized 5mC/H3K9me3 sites are mechanically stiffer than sites carrying either mark alone across the panel, revealing a cooperative biophysical signature of epigenetic crosstalk. Luminal chromosomes acquire the highest mark density, co-localization, and stiffness, whereas TNBC chromosomes show reduced density and diminished, though not absent, co-localization and stiffness, converging toward the low baseline of non-tumorigenic epithelium. TGF-{beta}1-induced epithelial-mesenchymal transition reproduces this attenuated phenotype in luminal cells, linking it directly to a process central to TNBC aggressiveness. These biophysical parameters classify cancer versus non-tumorigenic chromosomes with near-perfect, cross-validated accuracy, and further resolve the two TNBC subtypes using colocalization-derived features alone (macro-F1 = 0.933). These results establish the mechanical consequence of epigenetic mark co-localization as a single-chromosome-resolvable signature of centromeric organization, attenuated in aggressive breast cancer, and demonstrate a force-spectroscopy platform for mechano-epigenetic profiling of cancer chromosomes.

biophysics↗

bioRxiv2026

Endosomal pH Triggers Amyloid β Oligomerization and Maladaptive Phenotypic Plasticity in Alzheimers Disease

Endosomal dysfunction is a presymptomatic hallmark of neurodegeneration. Recent evidence highlights dysregulation of endosomal pH as a central pathogenic hub in Alzheimer's disease (AD); however, the mechanisms linking pH shifts to neurodegeneration remain incompletely defined. Here, we use a quantitative model of endosomal acidification driven by proton pumping via the vacuolar ATPase, proton leak via the endosomal Na/H exchanger NHE6, and other ion-regulating elements. The model recapitulates how downregulation of NHE6 in AD promotes endosomal hyperacidification, potentially triggering maladaptive phenotypic plasticity, an initially adaptive response that becomes pathological. Analysis of human brain datasets reveals reciprocal enrichment of NHE6 in neurons and the related NHE9 in glia, with NHE6 co-expression networks enriched for synaptic signalling. Systematic curation of NHE6 patient variants indicates that loss-of-function is associated with late regression, consistent with progressive endosomal hyperacidification, supporting a conceptual framework where early compensation transitions to neurodegeneration. Mathematical analyses calibrated for neuronal endosomes reveal a saturable relationship between luminal pH and NHE6 dosage, with threshold-like behaviour below ~50% expression that hyperacidifies endosomes, correlating with AD severity. Our model suggests this pH shift may exponentially accelerate A{beta} oligomerization and enhance {beta}-secretase activity. Furthermore, A{beta} oligomerization estimates correlate with dysregulation of calcium signalling and synaptic dysfunction. Model findings are compared with experimental results from NHE6-null mice and a cell culture model of AD. Drawing parallels to cancer, we propose that endosomal pH serves as a conserved regulator of adaptive-to-maladaptive transitions. Restoring physiological endosomal pH may offer a therapeutic window to prevent irreversible neurodegeneration in AD.

neuroscience↗

bioRxiv2026

Regulatory stochasticity drives opposing phenotypic outcomes in cell-fate decision networks

Gene regulatory network models treat interaction parameters as fixed, although regulatory efficacy fluctuates. We asked how temporal fluctuations in interaction strength reshape phenotype occupancy in cell-fate decision GRN motifs. Across large parameter ensembles, anchored fluctuations largely preserved deterministic occupancies. Additive fluctuations increased occupancy of all-high co-expression states, particularly where high expression was accessible. In contrast, multiplicative fluctuations biased inhibitory interactions toward stronger repression and favored single-high states in a topology-dependent manner. Deterministic controls sampled from noise-induced parameter distributions did not fully reproduce these effects. A Boolean-limit analysis revealed an intrinsic upward bias: loss of repression increased expression regardless of regulator state, whereas stronger repression acted only when the regulator was present. Analyses of epithelial-mesenchymal plasticity and gonadal-fate networks showed increased occupancy of hybrid team-expression states under additive fluctuations. Thus, regulatory noise can reshape the developmental landscape in opposing directions, pushing cell-fate systems toward either progenitor-like or terminally differentiated states.

systems biology↗

bioRxiv2026

Gene Regulatory Networks that support Multi-Fate Cellular Decisions

AO_SCPLOWBSTRACTC_SCPLOWCell fate decisions are driven by gene regulatory networks (GRNs). While the mutually inhibitory toggle switch effectively models binary fate decisions, fully connected inhibitory networks with more than two nodes fail to capture multi-fate decisions due to the low prevalence of "single high states", where only a single master regulator is highly expressed. The goal of this study is to find network structures that support all single high states. We find that the only network that attains the highest possible prevalence of all single high states within the set of monotone Boolean (MB) models is completely disconnected. Since biological networks typically require connectivity, we investigate network structures that support equipotency, where all single high states have equal prevalence within MB models. Finally, we characterize the networks that support multistability between all single high states, finding that it is possible only in networks in which each node either has self-activations or is inhibited by every other network node. Our findings provide a theoretical framework for understanding the network design principles that can support simultaneous differentiation into multiple distinct cell types.

systems biology↗

bioRxiv2026

Weak form Scientific Machine Learning for Systems Biology: A Tutorial on WENDy

Mechanistic ordinary differential equation models are widely used in systems biology to represent biochemical networks, population dynamics, cell-state transitions, and other biological processes; however, their predictive value depends critically on accurate parameter estimation from noisy and often sparse experimental data. In this tutorial, we present the Weak-form Estimation of Nonlinear Dynamics (WENDy) method as a forward-solver-free approach that reformulates parameter estimation as a covariance-corrected weak-form regression problem by integrating the model equations against compactly supported test functions. We present the background on the methodology through the lens of the familiar logistic equation, and we demonstrate applications of the method on real experimental data through two systems biology examples: a glycolytic oscillator with relatively dense time-course data and a sparse epithelial-mesenchymal cellstate transition model with multiple experimental replicates. Ultimately, using WENDy, we estimate interpretable biological parameters with uncertainty for systems with noisy and sometimes sparse available experimental data.

systems biology↗

bioRxiv2026

Hepatobiliary Progenitor-like Reprogramming in Liver Metastases

Metastatic progression requires cancer cells to adapt to the unique constraints of distant organ microenvironments, yet the mechanisms that drive organ-specific adaptations remain poorly understood. Here, we show that the liver actively rewrites metastatic cancer cell identity, driving tumor cells toward a hepatobiliary progenitor-like state. Through integrated transcriptomic, proteomic, metabolomic, and epigenomic analyses of patient-derived rapid-autopsy samples and experimental models, we identify this state as selectively enriched in liver metastases. It is characterized by co-activation of hepatic and biliary/progenitor regulators HNF4A and SOX9 and is observed across multiple epithelial cancers, indicating a conserved response to the hepatic niche. Mechanistically, hepatocyte-derived TGF-{beta} and hypoxia converge to activate a HIF-1-ACLY axis, increasing nuclear acetyl-coenzyme A availability and histone acetylation at hepatic lineage regulatory elements to drive hepatobiliary reprogramming. This coordinated niche-response program can be captured transcriptionally and is associated with inferior overall survival. Disruption of this pathway suppresses hepatic reprogramming and impairs liver metastatic fitness. These findings identify the liver as an active determinant of metastatic cell fate, linking microenvironmental signaling to metabolic and chromatin remodeling programs that enable lineage plasticity. More broadly, they reveal organ-specific reprogramming as a fundamental principle of metastasis and a therapeutic vulnerability in liver metastases.

cancer biology↗

bioRxiv2026

Endocrine therapy-specific lineage and partial epithelial-mesenchymal reprogramming defines divergent resistant cell-states in ER+ breast cancer

Acquired resistance to endocrine therapy remains a primary obstacle in the clinical management of estrogen receptor-positive (ER+) breast cancer. While resistance is frequently accompanied by transcriptional rewiring and lineage plasticity, how specific pharmacological modalities dictate divergent resistance trajectories remains poorly understood. Here, we integrate multi-omic profiling, spanning bulk and single-cell transcriptome, chromatin architecture (Hi-C), and the cistrome, to systematically compare the mechanisms involved in adaptive resistance to selective estrogen receptor modulators (SERMs, e.g., tamoxifen) and degraders (SERDs, e.g., fulvestrant), and the mechanism driven by constitutive ESR1 mutation, to characterize how mode of ER perturbation influences lineage identity and epithelial-mesenchymal state. We found that tamoxifen resistant (TamR) cells occupy a distinct transcriptional state characterized by coordinated luminal erosion, partial basal lineage activation, and stabilization of a partial epithelial-mesenchymal (pEMT) program. In contrast, fulvestrant resistant (FulR) cells primarily suppress ER signaling without extensive lineage reprogramming. Finally, ESR1 mutant cells recapitulate ligand-driven ER hyperactivation with limited engagement of mesenchymal and basal gene expression programs. Chromatin profiling further revealed that SERM resistance is accompanied by higher-order genome reorganization, including A-to-B compartment switching at luminal regulators such as GATA3 and ESR1, redistribution of ER and FOXA1 binding, and consequent activation of a pEMT program. Furthermore, we show that SERM-induced reprogramming is accompanied by a distinct mode of immune evasion where the reprogrammed cells do not engage classical T-cell exhaustion programs but instead exhibit coordinated loss of major histocompatibility complex (MHC) class I antigen presentation and establishment of a pro-tumorigenic signaling that strongly predicts adverse survival outcomes in patient cohorts. Together, these findings indicate that endocrine resistance does not converge on a single molecular endpoint but instead reflects drug-specific adaptive states defined by ER signaling context, lineage identity, and chromatin architecture. Our study establishes the basal-pEMT axis as a coordinated, epigenetically encoded module of SERM-induced plasticity and reframes endocrine resistance as a multidimensional evolutionary process shaped by therapeutic mechanisms of action.

cancer biology↗

bioRxiv2026

Traveling Wave Analysis of a Go-or-Grow Invasion Model with ECM-Regulated Phenotypic Switching

Experimental studies show that tumor cells adopt migratory or proliferative phenotypes depending on the local extracellular matrix (ECM). In this work, we propose a minimal go-or-grow invasion model, comprising two specialist cell phenotypes: proliferating and migratory, with phenotypic switching and cell migration depending on local ECM density. Numerical simulations of this model reveal that the spatial arrangement of proliferative and migratory cells depends on the choice of phenotypic switching function. We then ask whether this specialist cell-phenotype model can be reduced to a generalist cell-phenotype model. We derive a relationship between the reduced model and go-or-grow model in the fast phenotypic switching regime. We observe that the reduced model captures the dynamics of the original model, for a range of realistic phenotypic switching functions. We analytically derive the minimum traveling wave speed of the reduced model in a homogeneous ECM bed. Moreover, using linear stability analysis on the go-or-grow model, we recover the same wave speed expression. In addition, we numerically explore how the key parameters influence the traveling wave speed profile. Our analysis indicated the counter-intuitive result that the wave speed is independent of the matrix degradation rate, and our simulations show that, at most, the speed is weakly dependent on this parameter.

systems biology↗

bioRxiv2026

Bidirectional coupling among EMT, AXL-RB1 signaling and lineage switch drives resistance to osimertinib and worse clinical outcomes in NSCLC

Acquired resistance to osimertinib remains a major barrier in EGFR-mutant lung adenocarcinoma (LUAD), and in many patients cannot be explained by secondary targetable mutations. This pattern highlights a central role for non-genetic plasticity programs, including epithelial-mesenchymal transition (EMT), drug tolerance, immune evasion, and lineage switch. Here, we used a systems-level framework to define how these processes are coordinated. We constructed a minimal gene regulatory network integrating core EMT regulators with AXL, RB1, PD-L1, and NF-{kappa}B, and analysed its emergent behaviour using dynamical simulations. The network resolved into two mutually inhibitory, self-reinforcing "teams": an epithelial/sensitive team centred on RB1, miR-200, miR-34, p53, and E-cadherin, and a mesenchymal/resistant team centred on ZEB1, SNAIL, AXL, PD-L1, and NF-{kappa}B. Simulations predicted a strong coupling between EMT and osimertinib resistance, which was validated across bulk transcriptomic datasets from NSCLC cell lines, EGFR-mutant patient cohorts, and perturbation experiments. Inducing EMT increased RB1-loss programs, whereas osimertinib exposure induced AXL and EMT programs, supporting bidirectional regulation and reinforcement. Single-cell and spatial transcriptomic analyses further showed that EMT, AXL, PD-L1 activity, and reduced RB1 signaling co-occur within tumors. Clinically, activation of individual axes such as EMT, RB1 loss, or PD-L1 upregulation was associated with worse outcomes, while combined activation produced markedly poorer survival than any single axis alone. Extending the network to incorporate lineage regulators further linked a partial LUAD-to-LUSC shift with EMT, RB1 loss, and resistance. Together, these findings identify a network topology that coordinates multiple plasticity programs driving osimertinib resistance and suggest that disrupting this cooperative architecture may offer a therapeutic strategy in EGFR-mutant LUAD.

cancer biology↗

bioRxiv2026

Time-dependent memory of hypoxia exposure influences tumor invasion dynamics

Cancer cells in hypoxic environments often proliferate less but exhibit enhanced migration relative to their normoxic counterparts. Recent in vitro and in silico studies have characterized the role of hypoxic memory - the ability of cancer cells to retain their hypoxic phenotype even when reoxygenated - in tumor invasion. However, the observations have been limited either to exposing cancer cells to hypoxia for a fixed duration or by assuming a fixed-time persistence of the hypoxic state upon reoxygenation independent of the duration of hypoxia exposure. Thus, time-dependent cell-state changes during hypoxia and their impact on hypoxic memory remains unclear. Here, we first analyze transcriptomic data from breast cancer samples to show that the genes upregulated at transcriptional level and hypomethylated at epigenetic level are enriched in cell invasion, indicating hypoxic memory-driven process of tumor invasion. Next, we used a computational model to investigate how the spatial-temporal dynamics of oxygen levels in a tumor drive time-dependent changes in hypoxic memory and influence tumor invasion dynamics. Our simulation results show that such dynamic hypoxic memory can drive enhanced tumor invasion over a fixed hypoxic memory by a) enriching hypoxic cell density at the tumor front, b) reducing sensitivity of hypoxic cell state to fluctuations in oxygen supply, and c) enhancing effective diffusion of hypoxic cells. Our results highlight the crucial role of dynamic hypoxic memory in shaping tumor invasion dynamics, underscoring the need to elucidate its underlying mechanisms in future studies.

systems biology↗

bioRxiv2026

A Unified Control of Cellular Differentiation: From Temporal Multistability to Spatial Pattern Formation in Gene Regulatory Networks

How genetically identical cells spontaneously break symmetry to assume divergent fates is a fundamental problem in developmental biology. While modern genomics has mapped the vast molecular repertoire involved in gene regulation, understanding the mechanism of cell state transitions that drive differentiation remains a formidable challenge. To address this, we use a reaction-kinetic framework to analyze recurring motifs of two and three competing master regulators. While typically such circuits are studied numerically, we show that assuming symmetry in nodes and interactions provides exact analytical description of the bifurcations governing cell fate transitions. We find that the possible cell fates across all considered topologies are dictated by a single dimensionless quantity, {beta}--the ratio of protein degradation to production rates. In the binary Toggle Switch (TS), decreasing {beta} destabilizes the symmetric (stem cell) state, giving rise to two asymmetric (differentiated) fates via a supercritical pitchfork bifurcation. In the three-component Toggle Triad (TT), low values of {beta} yield three asymmetric fates through subcritical pitchfork bifurcation, creating an intermediate range of {beta} where both symmetric and asymmetric fates are simultaneously stable. For the Self-Activating Toggle Switch (SATS), we identify a new parameter for the self-activation threshold ({theta}) and show that decreasing{theta} progressively stabilizes the uncommitted state, leading to a regime of tristability. Building on these temporal bifurcations, we next address the feasibility of spatial structure formation: can these multistable fates stably coexist within a spatial domain? Through a minimal model of cell-cell communication via free diffusion, we extend these motifs into reaction-diffusion systems, which reveals a direct role of network topology on spatial organization. We prove that any heterogeneous pattern in two-node circuits is inherently transient and unstable. In contrast, the three-node repressive network supports the stable spatial coexistence of differentiated phenotypes through pure diffusion, a phenomenon we analyze by studying heteroclinic interface solutions as building blocks. By reducing complex regulatory dynamics to tractable models with physically meaningful parameters, we establish a minimal framework which relates topology to cell fate. Finally, the effects of temporal multistability on pattern formation provide an excellent studying ground for morphogenesis, synthetic biology, and the overarching problem of spatiotemporal self-organization.

systems biology↗

bioRxiv2026

Hierarchical organization in sparse gene regulatory networks shapes structural coherence and emergent regulatory coordination

How large-scale regulatory coordination in biological systems emerges from local signed and directed interactions in sparse gene regulatory networks (GRNs) remains an unanswered fundamental question. We introduce the coherence matrix, a topology-based framework that captures the consistency of regulatory influence between gene pairs by integrating information across all direct and indirect paths. Analysis of synthetic networks reveals that structural coherence - a metric derived from the coherence matrix - dictates global coordination: while highly coherent motifs maintain aligned regulatory coordination across widely varying network sparsity values, motifs with low coherence allow such coordination only at biologically unrealistic sparsity values. Our investigation of six whole-organism GRNs and further analysis of synthetic networks highlighted that hierarchical organization in GRNs a dense middle layer enriched in feedback loops that mediates coordination between input and output layers - serves as a structural buffer to allow regulatory coordination even for sparse networks. Finally, comparison with Escherichia coli transcriptomic modules further shows that the coherence matrix accurately predicts the sign of coordinated gene contribution, emphasizing its biological application, while also serving as a unifying descriptor integrating local interactions and global network architecture to explain the emergent regulatory coordination.

systems biology↗

bioRxiv2026

Early detection of sudden transitions in Notch signalling

Identifying sudden transitions during phenotypic decision-making of complex biological systems can be crucial for our ability to control a cellular state. Yet, prior determination of these sudden transitions or tipping points remains challenging, as biological systems often exhibit only subtle early changes, which are often masked by inherent noise or rapid transition dynamics. Using Notch signaling as a model, we systematically analyze dynamical transitions in Notch-Delta (ND), Notch-Delta-Jagged (NDJ), and Fringe-mediated NDJ systems for both one and two-cell contexts. In the one-cell ND system, critical slowing down (CSD)-based early warning signals (EWSs) reliably capture transitions between sender (S) and receiver (R) states and remain robust to variation in forcing rate. We further find that flickering is a precursor to transitions in one-cell NDJ system. In contrast, flickering does not occur in the two-cell Notch model due to the presence of a supercritical bifurcation. Our analysis also offers insight into how NICD (Notch Intracellular Domain)-driven and Fringe-mediated asymmetries, along with the strength of external signals, control the emergence of flickering. Overall, this study identifies sudden transitions in Notch signaling under demographic noise and can be extended to other noisy biological systems, with potential applications in drug development and targeted therapeutic interventions.

systems biology↗

bioRxiv2026

Systems-level analysis identifies IRF6 as an inhibitor of epithelial-mesenchymal transition

BackgroundEpithelial-mesenchymal transition (EMT) and its reverse process Mesenchymal-Epithelial Transition (MET) are crucial during metastasis and therapy resistance. While the dynamics and master regulators of EMT are well-studied, the transcription factors that can prevent EMT or promote MET are relatively less understood. ResultsHere, by integrating bulk and spatial transcriptomic data analysis from cell lines and patient samples, with mechanism-based dynamical modelling, we identify IRF6 as a factor that strongly associates with an epithelial phenotype and is often inhibited during EMT. In vitro experiments in multiple cancer cell lines demonstrate the progression to a mesenchymal phenotype upon IRF6 knock-down, suggesting a role as an inhibitor of EMT. Finally, we observe that IRF6 expression levels correlates with worse patient survival in a subset of solid tumour types. ConclusionOur integrated computational-experimental systems-level analysis suggests that IRF6 is frequently downregulated during EMT and can also prevent the progression towards a complete EMT, underscoring its role as an MET stabilizing factor.

systems biology↗