Biology subjects

Damaghi, M.

Publications and source records attributed to Damaghi, M..

At least 19 recordsLinked to original sources

bioRxiv2026

Acid Stress-induced plasma membrane ceramide arises from lysosome-plasma membrane fusion

Plasma membrane ceramide (PMCer) is a recognized cellular signal that regulates stress responses, such as chemotherapy and membrane damage, triggering apoptosis and plasma membrane repair. Acid sphingomyelinase (ASM) has been proposed to generate PMCer by directly hydrolyzing plasma membrane sphingomyelin into ceramide. However, the enzymatic requirements of ASM are difficult to reconcile with the extracellular environment on the outer leaflet of the plasma membrane. Here, we identify several cellular stress inducers, with acidic stress yielding a stronger response in PMCer generation. Using this inducer, we defined a lysosome-to-plasma membrane pathway for stress-induced PMCer generation. Acidic stress increased PMCer in an ASM-dependent manner, whereas ASM loss or catalytic inactivation abolished this response. Although secreted ASM was enzymatically active when tested in vitro, neither secreted nor exogenous recombinant ASM generated PMCer. Instead, acidic stress induced lysosomal exocytosis, while disruption of lysosomal fusion reduced PMCer accumulation. Modulating lysosomal ceramide translated into PMCer, showing that lysosomal ceramide is directly transferred into the plasma membrane. These findings redefine stress-related PMCer signaling through lysosomal ceramide exocytosis.

biochemistry↗

bioRxiv2026

Neutral Sphingomyelinase-2 Restrains TAZ to Suppress Breast Tumor Growth

Loss of tumor suppressor gene (TSG) activity is pervasive across cancers and linked to worse clinical outcomes, yet therapeutic efforts aimed at restoring TSGs have remained elusive. One underexplored avenue to address this problem is the targeting of metabolic signaling pathways that actively enforce tumor suppressive programs. Ceramide (Cer), the central hub of the sphingolipid (SL) metabolic network, has long been thought to have tumor suppressive functions, though its mechanistic roles remain incompletely defined. Here, we identify neutral sphingomyelinase-2 (nSMase2) as a critical mediator of Cer-dependent tumor suppression. We show that nSMase2 is frequently suppressed in breast cancer (BC) and its restoration inhibits tumorigenesis. Biologically, this was linked to the suppression of anchorage-independent growth (AIG) and to restraint of the HIPPO pathway effector TAZ, but not its paralog YAP. Taken together, these findings define a previously unrecognized metabolic tumor suppressor pathway, clarify ambiguities in both SL and HIPPO signaling networks, and highlight reactivation of nSMase2-Cer signaling as a potential therapeutic strategy in BC.

cancer biology↗

bioRxiv2026

Metabolic plasticity of sphingolipids governs cancer cell fitness in acidic tumor ecosystems

Cell state plasticity enables cancer cells to rapidly adapt to fluctuating microenvironments without requiring genetic alteration, shaping tumor evolution under stress. Extracellular acidosis is a persistent feature of solid tumors that impose strong selective pressure, yet how cancer cells maintain fitness under acute and chronic acidic conditions remains unclear. Here, we show that adaptation to acidosis is mediated by plastic rewiring of sphingolipid metabolism centered on ceramide turnover. Spatial multi-omics analysis of three-dimensional tumor models revealed enrichment of ceramides within acidic niches, consistent with a stress-induced phenotype. While acute acidosis promoted ceramide accumulation and reduced fitness, chronic exposure selected for cells capable of dynamically redistributing sphingolipid flux across multiple clearance pathways. Functional perturbation demonstrated that inhibition of individual pathways was insufficient to compromise survival, whereas simultaneous disruption of all ceramide clearance routes resulted in cell death, revealing a degenerate metabolic architecture. This network-level flexibility enables cancer cells to maintain fitness by switching between alternative metabolic states under acidic stress. Together, our findings identify sphingolipid metabolic plasticity as an adaptive strategy that supports tumor persistence in acidic ecosystems and suggest that targeting metabolic flexibility, rather than individual pathways, may provide a more effective therapeutic approach.

cancer biology↗

bioRxiv2025

Mdig shapes 3D chromatin architecture of immune checkpoint genes and limits metastasis of triple negative breast cancer cells

Despite decades of progress in metastasis research, the identity of bona fide metastasis-driving genes remains elusive. By shifting the focus from individual genes to the three-dimensional (3D) architecture of the genome, we identify the mineral dust-induced gene (mdig) as a chromatin-topology regulator that suppresses immune-checkpoint activation and metastasis in triple-negative breast cancer (TNBC). Re-expression of mdig in mdig-knockout (KO) cells markedly reduced liver metastasis, whereas mdig loss activated epithelial-mesenchymal transition (EMT), T-cell exhaustion, and antigen-presentation pathways. Across multiple cancer types, high mdig expression predicted improved responses to immune checkpoint blockade (ICB). Mechanistically, mdig depletion derepressed inhibitory checkpoint genes, including PD-L1, PD-L2, LGALS9, and PLXNB1/2, accompanied by increased H3K9me3 and H3K36me3 at these loci. Hi-C profiling revealed that mdig maintains topologically associating domains (TADs) and long-range repressive loops at checkpoint loci; loss of mdig disrupted these structures, enabling coordinated activation of immune-evasion programs. Genome-wide analyses showed extensive TAD remodeling in mdig KO cells, with pronounced alterations on chromosome X. Collectively, these findings position mdig as a key chromatin-architectural regulator of immune evasion and metastatic behavior, underscoring its potential as a biomarker for ICB responsiveness in TNBC and beyond. Significance statementMetastasis remains the leading cause of cancer mortality, yet bona fide metastasis-driving genes remain difficult to define. By examining three-dimensional genome architecture rather than individual gene function, we identify mdig as a chromatin-topology regulator that restrains immune evasion and metastasis in triple-negative breast cancer. Loss of mdig disrupts TAD structures and long-range repressive loops at immune-checkpoint loci, enabling coordinated activation of EMT, antigen-presentation, and T-cell-exhaustion programs. Restoring mdig expression markedly reduces liver metastasis, and high mdig levels across cancers predict improved responses to immune-checkpoint blockade. These findings establish mdig as a key regulator of chromatin organization and a potential biomarker for immunotherapy responsiveness.

cancer biology↗

bioRxiv2025

Metabolic plasticity drives mechanisms of PARP inhibitor persistence in ovarian cancer

PARP inhibitors (PARPi) are the standard maintenance therapy for ovarian cancer, but the frequent emergence of resistance remains a major clinical challenge. Emerging evidence suggests that tumor cell plasticity is an important mechanism enabling this adaptive resistance. In this study, we combined both experimental and computational techniques to model this evolutionary process by long term treatment of the OVCAR3 ovarian cancer cell line with Olaparib (a PARPi). We then performed single-cell RNA sequencing (scRNAseq) on both naive and persistent cells to capture cancer cells heterogenous response. scRNAseq profiling suggested an adaptive metabolic reprogramming in response to long term Olaparib treatment. We then scored single cells for metabolic function, and persister cells were found to have reprogrammed their glutamine metabolism. To test these findings, both persister and naive cells were cultured in glutamine-deprived media and persister cells were found to have higher viability than the naive cells particularly when exposed to Olaparib. To test the cells capacity to switch their metabolic state toward glycolysis, we performed Seahorse mitochondrial and glycolytic stress tests. These analyses revealed that persister cells were less dependent on glutamine metabolism and instead exhibited increased glycolytic capacity compared to naive cells. This metabolic shift resulted in an acquired dependency on glucose, representing a potential therapeutic vulnerability. Together, these results indicate that prolonged Olaparib exposure promotes metabolic plasticity in ovarian cancer cells. To explore how this plasticity might be exploited therapeutically, we developed a proof-of-concept mathematical model that leverages metabolic state transitions to optimize treatment scheduling. ONE SENTENCE SUMMARYOvarian cancer cells exploit metabolic plasticity to increase their evolvability to persist PARP inhibitor treatment.

cancer biology↗

bioRxiv2024

Human and bats genome robustness under COSMIC mutational signatures

Carcinogenesis is an evolutionary process, and mutations can fix the selected phenotypes in selective microenvironments. Both normal and neoplastic cells are robust to the mutational stressors in the microenvironment to the extent that secure their fitness. To test the robustness of genes under a range of mutagens, we developed a sequential mutation simulator, Sinabro, to simulate single base substitution under a given mutational process. Then, we developed a pipeline to measure the robustness of genes and cells under those mutagenesis processes. We discovered significant human genome robustness to the APOBEC mutational signature SBS2, which is associated with viral defense mechanisms and is implicated in cancer. Robustness evaluations across over 70,000 sequences against 41 signatures showed higher resilience under signatures predominantly causing C-to-T (G-to-A) mutations. Principal component analysis indicates the GC content at the codons wobble position significantly influences robustness, with increased resilience noted under transition mutations compared to transversions. Then, we tested our results in bats at extremes of the lifespan-to-mass relationship and found the long-lived bat is more robust to APOBEC than the short-lived one. By revealing robustness to APOBEC ranked highest in human (and bats with much more than number of APOBEC) genome, this work bolsters the key potential role of APOBECs in aging and cancer, as well as evolved countermeasures to this innate mutagenic process. It also provides the baseline of the human and bat genome robustness under mutational processes associated with aging and cancer. HighlightsO_LISinabro, the sequential mutation simulator, facilitates measuring the robustness of human protein-coding sequences under all COSMIC mutational signatures. C_LIO_LIRobustness under APOBEC mutational signatures showed the largest mean and standard deviation in the human genome. C_LIO_LIRobustness to mutational signatures analysis reveals the role of APOBECs is complementary to cancer in the evolvability of cancer cells in later stages. C_LIO_LIPrincipal component analysis indicates that the GC content at the codons wobble position significantly influences robustness. C_LIO_LIA long-lived bat (Myotis myotis) has higher robustness to APOBECs than a short-lived one (Molossus molossus) than humans. C_LI

genomics↗

bioRxiv2024

Eco-evolutionary Guided Pathomic Analysis to Predict DCIS Upstaging

Cancers evolve in a dynamic ecosystem. Thus, characterizing cancers ecological dynamics is crucial to understanding cancer evolution and can lead to discovering novel biomarkers to predict disease progression. Ductal carcinoma in situ (DCIS) is an early-stage breast cancer characterized by abnormal epithelial cell growth confined within the milk ducts. In this study, we show that ecological analysis of hypoxia and acidosis biomarkers can significantly improve prediction of DCIS upstaging. First, we developed a novel eco-evolutionary designed approach to define habitats in the tumor intraductal microenvironment based on oxygen diffusion distance. Then, we identified cancer cells with metabolic phenotypes attributed to their habitats, including CA9 for hypoxia responding phenotype, and LAMP2b for acid adapted phenotype. Traditionally these markers have shown limited predictive capabilities for DCIS progression, if any. However, when analyzed from an ecological perspective, their power to differentiate between non-upstaged and upstaged DCIS increased significantly. Second, we discovered distinct niches with spatial patterns of these biomarkers and used the distribution of such niches to predict patient upstaging. The niches were characterized by pattern analysis of both cellular and spatial features. With a 5-fold validation on the biopsy cohort, we trained a random forest classifier to achieve the area under curve (AUC) of 0.74. Our results affirm the importance of tumor ecological features in eco-evolutionary-designed approaches for novel biomarkers discovery. SignificanceOur results affirm the importance of spatial and ecological features in eco-evolutionary-designed biomarkers discovery studies in the era of digital pathology.

cancer biology↗

bioRxiv2023

Evolvability of cancer-associated genes under APOBEC3A/B selection

Evolvability is an emergent hallmark of cancer that depends on intra-tumor heterogeneity and, ultimately, genetic variation. Mutations generated by APOBEC3 cytidine deaminases can contribute to genetic variation and the consequences of APOBEC activation differ depending on the stage of cancer, with the most significant impact observed during the early stages. However, how APOBEC activity shapes evolutionary patterns of genes in the host genome and differential impacts on cancer-associated and non-cancer genes remain unclear. Analyzing over 40,000 human protein-coding transcripts, we identified distinct distribution patterns of APOBEC3A/B TC motifs between cancer-related genes and controls, suggesting unique associations with cancer. Studying a bat species with many more APOBEC3 genes, we found diverse motif patterns in orthologs of cancer genes compared to controls, similar to humans and suggesting APOBEC evolution to reduce impacts on the genome rather than the converse. Simulations confirmed that APOBEC-induced heterogeneity enhances cancer evolution, shaping clonal dynamics through bimodal introduction of mutations in certain classes of genes. Our results suggest that a major consequence of the bimodal distribution of APOBEC affects greater cancer heterogeneity. HighlightsO_LIUsing a measure of the extent which genes are affected by APOBEC activity, we found that many genes are maximally robust in the human genome. Interestingly, the distribution in the genome of a bat that has many APOBEC genes was similar. C_LIO_LIIn contrast, when analyzing the subset of cancer-associated genes the distribution is bimodal with many genes appearing to susceptible to APOBEC activity. C_LIO_LIAnalysis of orthologs of human genes and other species showed a wide range in the extent to which APOBEC affects genes having the same function. C_LIO_LIThe bimodal distribution of susceptibility to APOBEC drives greater heterogeneity in simulated clonal evolution of cancer. C_LI

cancer biology↗

bioRxiv2023

Adaptive therapy for ovarian cancer: An integrated approach to PARP inhibitor scheduling

Toxicity and emerging drug resistance are important challenges in PARP inhibitor (PARPi) treatment of ovarian cancer. Recent research has shown that evolutionary-inspired treatment algorithms which adapt treatment to the tumors treatment response (adaptive therapy) can help to mitigate both. Here, we present a first step in developing an adaptive therapy protocol for PARPi treatment by combining mathematical modelling and wet-lab experiments to characterize the cell population dynamics under different PARPi schedules. Using data from in vitro Incucyte Zoom time-lapse microscopy experiments and a step-wise model selection process we derive a calibrated and validated ordinary differential equation model, which we then use to test different plausible adaptive treatment schedules. Our model can accurately predict the in vitro treatment dynamics, even to new schedules, and suggests that treatment modifications need to be carefully timed, or one risks losing control over tumour growth, even in the absence of any resistance. This is because our model predicts that multiple rounds of cell division are required for cells to acquire sufficient DNA damage to induce apoptosis. As a result, adaptive therapy algorithms that modulate treatment but never completely withdraw it are predicted to perform better in this setting than strategies based on treatment interruptions. Pilot experiments in vivo confirm this conclusion. Overall, this study contributes to a better understanding of the impact of scheduling on treatment outcome for PARPis and showcases some of the challenges involved in developing adaptive therapies for new treatment settings.

cancer biology↗

bioRxiv2021

Dynamics of fibril collagen remodeling by tumor cells using individual cell-based mathematical modeling

Many solid tumors are characterized by dense extracellular matrix (ECM) composed of various ECM fibril proteins that provide structural support and biological context for the residing cells. The growing tumor cell colonies are capable of remodeling the ECM structure in tumor immediate vicinity to form specific microenvironmental niches. The changes in fibril patterns of the collagen (one of the ECM proteins) surrounding the tumor can be visualized experimentally using both histology and fluorescent imaging. In particular, three diverse tumor associated collagen signatures (TACS) were identified and related to tumor behavior, such as benign growth or invasion. Here we will use an off-lattice hybrid agent-based model (MultiCell-LF) to identify the rules of cell-ECM interactions that guide the development of various patterns of alignment of the ECM fibrils.

systems biology↗

bioRxiv2020

Cycling hypoxia selects for constitutive HIF stabilization

Tumors experience temporal and spatial fluctuations in oxygenation. Hypoxia inducible transcription factors (HIF-) in tumor cells are stabilized in response to low levels of oxygen and induce angiogenesis to re-supply oxygen. HIF- stabilization is typically facultative, induced by hypoxia and reduced by normoxia. In some cancers, however, HIF- stabilization becomes constitutive even under normoxia, a condition known as pseudohypoxia. Herein, we develop a mathematical model that predicts the effects of fluctuating levels of oxygen availability on stabilization of HIF- and its client proteins based on fitness. The model shows that facultative regulation of HIF- always promotes greater cell fitness than constitutive regulation. However, cell fitness is nearly identical regardless of HIF- regulation strategy when there are rapid periodic fluctuations in oxygenation. Furthermore, the model predicts that stochastic changes in oxygenation favor facultative HIF- regulation. We conclude that rapid and regular cycling of oxygenation levels selects for pseudohypoxia.

cancer biology↗

bioRxiv2020

Omics integration analyses reveal the early evolution of malignancy in breast cancer

BackgroundThe majority of cancer evolution studies are done on individual-based approaches that neglect population dynamics necessity for the global picture of cancer evolution in each cancer type. Here, we conducted a population-based study in breast cancer to understand the timing of malignancy evolution and its correlation to the genetic evolution of pathological stages. ResultsIn an omics integrative approach, we integrated gene expression and genomic aberration data for pre-invasive (DCIS, early-stage) and post-invasive (IDC, late-stage) samples and investigated the evolutionary role of further genetic changes in late stages compared to the early ones. We found that single genetic alterations (SGAs) and copy number alterations (CNAs) conspire together for the fine-tuning of the operating signaling pathways of tumors in forward and backward evolution manners. The forward evolution applies to new genetic changes that boost the efficiency of selected signaling pathways. The backward evolution, which we detected for CNAs, is a mean to reverse unwanted SGAs of earlier stages. Analyses of the integrated point mutation and gene expression data show that (i) our proposed fine-tuning concept is also applicable in metastasis, and (ii) metastasis diverges from primary tumor sometimes at the DCIS stage. ConclusionsOur results indicate that malignant potency of breast tumors is constant over pre and post invasive pathological stages. Indeed, further genetic alterations in later stages do not establish de novo malignancy routes; however, they serve to fine-tune antecedent signaling pathways.

evolutionary biology↗

bioRxiv2020

The Harsh Microenvironment in Early Breast Cancer Select for a Warburg Phenotype

The harsh microenvironment of ductal carcinoma in situ (DCIS) exerts strong evolutionary selection pressures on cancer cells. We hypothesize that the poor metabolic conditions near the ductal center foment the emergence of a Warburg Effect (WE) phenotype, wherein cells rapidly ferment glucose to lactic acid, even in normoxia. To test this hypothesis, we subjected pre-malignant breast cancer cells to different microenvironmental selection pressures using combinations of hypoxia, acidosis, low glucose, and starvation for many months, and isolated single clones for metabolic and transcriptomic profiling. The two harshest conditions selected for constitutively expressed WE phenotypes. RNA-seq analysis of WE clones identified the transcription factors NF[kcy]B and KLF4 as potential inducers of the WE phenotype. NF[kcy]B was highly phosphorylated in the glycolytic clones. In stained DCIS samples, KLF4 expression was enriched in the area with the harshest microenvironmental conditions. We simulated in vivo DCIS phenotypic evolution using a mathematical model calibrated from the in vitro results. The WE phenotype emerged in the poor metabolic conditions near the necrotic core. We propose that harsh microenvironments within DCIS select for a Warburg phenotype through constitutive transcriptional reprogramming, thus conferring a survival advantage and facilitating further growth and invasion.

cancer biology↗

bioRxiv2020

Frequency-dependent interactions determine outcome of competition between two breast cancer cell lines

Tumors are highly dynamic ecosystems in which diverse cancer cell subpopulations compete for space and resources. These complex, often non-linear interactions govern continuous spatial and temporal changes in the size and phenotypic properties of these subpopulations. Because intra-tumoral blood flow is often chaotic, competition for resources may be a critical selection factor in progression and prognosis. Here, we quantify resource competition using 3D spheroid cultures with MDA-MB-231 and MCF-7 breast cancer cells. We hypothesized that MCF-7 cells, which primarily rely on efficient aerobic glucose metabolism, would dominate the population under normal pH and low glucose conditions; and MDA-MB-231 cells, which exhibit high levels of glycolytic metabolism, would dominate under low pH and high glucose conditions. In spheroids with single populations, MCF-7 cells exhibited equal or superior intrinsic growth rates (density-independent measure of success) and carrying capacities (density-dependent measure of success) when compared to MDA-MB-231 cells under all pH and nutrient conditions. Despite these advantages, when grown together, MCF-7 cells do not always outcompete MDA-MB-231 cells. MDA-MB-231 cells outcompete MCF-7 cells in low glucose conditions and coexistence is achieved in low pH conditions. Under all conditions, MDA-MB-231 has a stronger competitive effect (frequency-dependent interaction) on MCF-7 cells than vice-versa. This, and the inability of growth rate or carrying capacity when grown individually to predict the outcome of competition, suggests a reliance on frequency-dependent interactions and the need for competition assays. We frame these results in a game-theoretic (frequency-dependent) model of cancer cell interactions and conclude that competition assays can demonstrate critical density-independent, density-dependent and frequency-dependent interactions that likely contribute to in vivo outcomes. HighlightsDemonstrate how mixed-culture spheroids must be used to characterize competition between two cancer cell lines. Competition alters growth dynamics of cancer cells. Competition growth models can be used to quantify density-independent, density-dependent and frequency-dependent effects on competition. Competition affects tumor progression and structure, making it key to understanding tumor development and evolution.

cancer biology↗

bioRxiv2019

Mix & Match: Phenotypic coexistence as a key facilitator of solid tumour invasion

Invasion of healthy tissue is a defining feature of malignant tumours. Traditionally, invasion is thought to be driven by cells that have acquired all the necessary traits to overcome the range of biological and physical defences employed by the body. However, in light of the ever-increasing evidence for geno- and phenotypic intra-tumour heterogeneity an alternative hypothesis presents itself: Could invasion be driven by a collection of cells with distinct traits that together facilitate the invasion process? In this paper, we use a mathematical model to assess the feasibility of this hypothesis in the context of acid-mediated invasion. We assume tumour expansion is obstructed by stroma which inhibits growth, and extra-cellular matrix (ECM) which blocks cancer cell movement. Further, we assume that there are two types of cancer cells: i) a glycolytic phenotype which produces acid that kills stromal cells, and ii) a matrix-degrading phenotype that locally remodels the ECM. We extend the Gatenby-Gawlinski reaction-diffusion model to derive a system of five coupled reaction-diffusion equations to describe the resulting invasion process. We characterise the spatially homogeneous steady states and carry out a simulation study in one spatial dimension to determine how the tumour develops as we vary the strength of competition between the two phenotypes. We find that overall tumour growth is most extensive when both cell types can stably coexist, since this allows the cells to locally mix and benefit most from the combination of traits. In contrast, when inter-species competition exceeds intra-species competition the populations spatially separate and invasion arrests either: i) rapidly (matrix-degraders dominate), or ii) slowly (acid-producers dominate). Overall, our work demonstrates that the spatial and ecological relationship between a heterogeneous population of tumour cells is a key factor in determining their ability to cooperate. Specifically, we predict that tumours in which different phenotypes coexist stably are more invasive than tumours in which phenotypes are spatially separated.

cancer biology↗

bioRxiv2019

Collagen Production and Niche Engineering: A Novel Strategy for Cancer Cells to Survive Acidosis and Evolve

Ductal Carcinoma in situ (DCIS) is an avascular disease characterized by profound acidosis. Pre-malignant cells within this niche must adapt to acidosis to survive and thrive. A component of this acid-adaptation involves extracellular matrix remodeling leading to niche construction and remodeling. Using discovery proteomics, we identified that collagen producing enzyme PLODs are upregulated in acid-adapted breast cancer cells. Second harmonic generation microscopy showed significant collagen deposition within DCIS lesions of patients. In vitro analyses identified that acid-adaptation involves production of rare collagens that can be regulated by Ras and SMAD pathway. Secretome analysis showed upregulation ECM remodeling enzymes such as TGM2 and LOXL2. Comparison of acid induced collagens in vitro and in patient data showed correlation between rare collagens production and survival of patients. We conclude acidosis induces collagen production by cancer cells and promote growth independent of basal membrane attachment. The independently produced collagen can be used for niche construction and engineering as an adaptation strategy of cancer cells to survive and evolve.

cancer biology↗

bioRxiv2019

Lymph Nodes Inhibit T-cell Effector Functions Locally by Establishing Acidic Niches

Lymph nodes are an essential component of the adaptive immune response where antigen-presenting cells are closely housed with their cognate effector cells. Protection of lymph node resident cells from activated immune cells in such close quarters would need to be robust and reversible. Effector functions of T-cells are profoundly and reversibly inhibited by an acidic microenvironment. The underlying mechanisms of this inhibition are unknown, but may relate to glycolysis, which is obligatory for expression of effector functions. Here, we demonstrate that acidification rapidly and potently inhibits monocarboxylate transporter-dependent lactic acid efflux, which dually inhibits glycolysis by end-product accumulation and by reducing cytoplasmic pH. Based on the robustness of these responses, we propose that acid-evoked T-cell inhibition is physiologically important, and that lymph nodes are a natural site for such modulation. Using multiple imaging techniques, we show that paracortical T-zones of lymph nodes are highly acidic. We further show that T-cells can be activated by dendritic cells at low pH, and their effector functions are restored rapidly upon increasing pH. Thus, we describe a novel physiological mechanism whereby activated T-cells are kept in stasis by acidosis whilst resident in lymph nodes.

physiology↗

bioRxiv2018

Connecting the Microenvironmental Niche to Treatment Response in Ovarian Cancer

Ovarian cancer has the highest mortality rate of all gynecologic cancers, which may be attributed to an often late stage diagnosis, when the cancer is already metastatic, and rapid development of treatment resistance. We propose that the metastatic disease could be better characterized by observing interactions within the microenvironmental niche of the primary site that shapes the tumors early phenotypic progression. We present a mechanistic mathematical model of ovarian cancer that considers spatial interactions between tumor cells and several key stromal components. We demonstrate how spatial biomarker imaging data from the primary tumor can be analyzed to define a patient-specific microenvironment in the mathematical model. We then show preliminary results, using this model, that demonstrate how differences in the niche composition of a tumor affects phenotypic evolution and treatment response.

cancer biology↗