Biology subjects

Magnani, L.

Publications and source records attributed to Magnani, L..

18 recordsLinked to original sources

bioRxiv2026

Modelling human haematopoietic stem cell commitment ex vivo identifies IL-33 as a regulator of megakaryopoiesis

Commitment events to specific blood lineages arise from single hematopoietic stem cells (HSCs) and are influenced by stress, inflammation and disease. However, the understanding of how such events are regulated in human haematopoiesis is limited by the lack of tractable in vitro models. In this study, we introduce a novel Early Progenitor Differentiation (EPD) assay to study the initial lineage commitment of human 49+ HSCs, in a system faithfully recapitulating cell states observed in vivo. Combining single cell -omics approaches and single cell functional assays, we show that IL-33 acts directly on human 49f+ HSCs activating the MAPK pathway to enhance their commitment towards Megakaryocytic-Erythroid-Mast cell Progenitors and subsequently megakaryopoiesis. This occurs without affecting HSC self-renewal via accelerated establishment of chromatin programmes associated with Erythroid and Megakaryocyte and mast cells lineages. Our findings demonstrate the utility of the EPD model to identify molecular regulators of human HSC differentiation and uncover a new role of IL-33 in haematopoiesis.

cell biology↗

bioRxiv2026

Predicting how perturbations reshape cellular trajectories with PerturbGen

A major challenge in biology is predicting how cells transition between states over time and how perturbations disrupt these transitions. Understanding such dynamics is critical for identifying interventions that reverse pathological programs or reprogram cells toward desired states. Although recent computational approaches can predict single-cell perturbation responses in silico, they cannot predict responses across dynamic cell trajectories, for example how early perturbations reconfigure later cell states. To address this gap, we introduce PerturbGen, a generative foundation model trained on over 100 million single-cell transcriptomes that predicts perturbation responses along cellular trajectories. PerturbGen predicts how genetic perturbation at source state shapes downstream states, alters gene programs and trajectories across time, for example in differentiation or disease progression. We apply PerturbGen to three newly generated multi-condition human single-cell datasets spanning immune responses, hematopoiesis and skin development. In an in vivo immune challenge, PerturbGen predicts that knocking out an IL1B signal in myeloid cells attenuates later cytokine-interferon programs, with downstream changes consistent with a reversal of IL-1{beta} stimulation signature. In hematopoiesis, anchoring perturbation-induced programs to human genetics enables simulation of monogenic blood disorders, recapitulates established disease-associated biology whilst systematically revealing lineage-specific programs, including in lineages where this was not previously possible. In skin organoids, PerturbGen predicted that Wnt activation enhances stromal differentiation recapitulating the trajectory observed in human prenatal skin, findings that were functionally validated by experimentally activating Wnt signaling. Together, PerturbGen extends modeling of gene perturbations from static to dynamic cellular systems. We envision PerturbGen enabling the creation of in silico, trajectory-aware perturbation atlases and virtual cells across diverse biological scenarios, supporting optimization of disease models and prioritization of candidate molecular interventions for therapeutic discovery.

bioinformatics↗

bioRxiv2026

X-CODE: a dual RNA barcoding system for multi-platform clonal tracking and spatial phenotyping

Experimental dissection of clonal dynamics in complex tissues requires barcoding systems that are scalable, compatible with different analytical platforms, providing phenotypic and spatial resolution. Here we introduce X-CODE, a dual-expressed RNA barcoding system designed to enable high-complexity clonal tracking across sequencing-based, cytometric, and spatial imaging modalities within a unified experimental framework. X-CODE combines a combinatorial, probe-detectable long RNA barcode with a matched short sequencing barcode, enabling seamless integration of probe-based readouts with sequencing and barcode-guided clonal retrieval. We demonstrate robust X-CODE detection by mass cytometry and imaging-based platforms, including spatial RNA barcode readout using via a repurposed Akoya PhenoCycler-Fusion protocol. In addition, we show compatibility with MALDI mass spectrometry imaging for co-registration of clonal and metabolic information. We further demonstrate the feasibility of X-CODE detection within probe-based spatial transcriptomics using the 10x Genomics Xenium platform. Applied to an in vivo model of androgen deprivation in prostate cancer, X-CODE reveals clonal architecture, selection and clone-specific phenotypic and metabolic plasticity underlying castration resistance. Together, X-CODE provides a flexible and broadly accessible platform for integrated clonal analysis across spatial, phenotypic, and molecular dimensions.

cancer biology↗

bioRxiv2025

GLYATL1 is associated with metabolic and epigenetic changes and with endocrine resistance in luminal breast cancer

Estrogen receptor alpha (ER)-positive luminal breast cancer is commonly treated with aromatase inhibitors (AI) to block estrogen signaling; however, resistance frequently develops, limiting therapy success. We observed that GLYATL1 (Glycine-N-Acyltransferase Like 1) expression is upregulated in AI-resistant breast cancer cell models and in patients undergoing AI therapy, correlating with poorer survival. Here we demonstrate that GLYATL1 promotes resistance to estrogen deprivation by elevating succinate levels and altering epigenetic histone marks associated with active transcription. Knockdown or knockout of GLYATL1 reverses these effects and reduces proliferation under estrogen-deprived conditions. Notably, GLYATL1 expression is positively regulated by estrogen receptor alpha signaling independently of estrogen. These findings reveal GLYATL1 as a metabolic and epigenetic mediator of endocrine therapy resistance, suggesting it as a potential target to overcome AI resistance in luminal breast cancer.

cancer biology↗

bioRxiv2023

Epigenetic heritability of cell plasticity drives cancer drug resistance through one-to-many genotype to phenotype mapping

Cancer drug resistance is multi-factorial, driven by heritable (epi)genetic changes but also phenotypic plasticity. Here we dissect it by perturbing colorectal cancer patient-derived organoids longitudinally with drugs in sequence. Combining longitudinal tracking, single cell omics, evolutionary modelling, and machine leaning, we found that different targeted drugs select for distinct subclones, supporting rationally designed drug sequences. The cellular memory was encoded as a heritable epigenetic configuration, from which multiple transcriptional programmes could run, supporting a one-to-many (epi)genotype-to- phenotype map that explains how clonal expansions and plasticity manifest together. This may ensure drug resistance subclones can exhibit distinct phenotypes in changing environments while still preserving the cellular memory encoding for their selective advantage. Chemotherapies resistance was instead entirely driven by plasticity. Inducing further chromosomal instability before drug application changed clonal evolution but not convergent transcriptional programmes. Collectively, our data show how genetic and epigenetic alterations are selected to "permissive epigenome" enabling phenotypic plasticity.

cancer biology↗

bioRxiv2022

Genetic and epigenetic driven variation in regulatory regions activitycontribute to adaptation and evolution under endocrine treatment

Comprehensive profiling of hormone-dependent breast cancer (HDBC) has identified hundreds of protein-coding alterations contributing to cancer initiation1, 2, but only a handful have been linked to endocrine therapy resistance, potentially contributing to 40% of relapses1, 3-9. If other mechanisms underlie the evolution of HDBC under adjuvant therapy is currently unknown. In this work, we employ integrative functional genomics to dissect the contribution of cis-regulatory elements (CREs) to cancer evolution by focusing on 12 megabases of non-coding DNA, including clonal enhancers10, gene promoters, and boundaries of topologically associating domains11. Massive parallel perturbation in vitro reveals context-dependent roles for many of these CREs, with a specific impact on dormancy entrance12, 13 and endocrine therapy resistance9. Profiling of CRE somatic alterations in a unique, longitudinal cohort of patients treated with endocrine therapies identifies non-coding changes involved in therapy resistance. Overall, our data uncover actionable transient transcriptional programs critical for dormant persister cells and unveil new regulatory nodes driving evolutionary trajectories towards disease progression.

cancer biology↗

bioRxiv2021

Systems medicine dissection of chromosome 1q amplification reveals oncogenic regulatory circuits and informs targeted therapy in cancer

Understanding the biological and clinical impact of copy number aberrations (CNA) in cancer remains an unmet challenge. Genetic amplification of chromosome 1q (chr1q-amp) is a major CNA conferring adverse prognosis in several cancers, including the blood cancer, multiple myeloma (MM). Although several chr1q genes portend high-risk MM disease, the underpinning molecular aetiology remains elusive. Here we integrate patient multi-omics datasets with genetic variables to identify 103 adverse prognosis genes in chr1q-amp MM. Amongst these, the transcription factor PBX1 is ectopically expressed by genetic amplification and epigenetic activation of its own preserved 3D regulatory domain. By binding to reprogrammed super-enhancers, PBX1 directly regulates critical oncogenic pathways, whilst in co-operation with FOXM1, activates a proliferative gene signature which predicts adverse prognosis across multiple cancers. Notably, pharmacological disruption of the PBX1-FOXM1 axis, including with a novel PBX1 inhibitor is selectively toxic against chr1q-amp cancer cells. Overall, our systems medicine approach successfully identifies CNA-driven oncogenic circuitries, links them to clinical phenotypes and proposes novel CNA-targeted therapy strategies in cancer. SignificanceWe provide a comprehensive systems medicine strategy to unveil oncogenic circuitries and inform novel precision therapy decisions against CNA in cancer. This first clinical multi-omic analysis of chr1q-amp in MM identifies a central PBX1-FOXM1 regulatory axis driving high-risk prognosis, as a novel therapeutic target against chr1q-amp in cancer.

cancer biology↗

bioRxiv2021

Phenotypic plasticity and genetic control in colorectal cancer evolution

Cancer evolution is driven by natural selection acting upon phenotypic trait variation. However, the extent to which phenotypic variation within a tumour is a consequence of intra-tumour genetic heterogeneity remains undetermined. Here we show that colorectal cancer cells frequently have highly plastic phenotypic traits in vivo in patient tumours. We measured the degree to which trait variation reflects genetic ancestry by quantifying the phylogenetic signal of gene expression across 297 samples with multi-region paired whole genome and transcriptome sequencing collected from 27 primary colorectal cancers. Within-tumour phylogenetic signal for genes and pathways was detected only infrequently, suggesting that the majority of intra-tumour variation in gene expression programmes was not strongly heritable. Expression quantitative trait loci analyses (eQTL) identified a small number of putative mechanisms of genetic control of gene expression due to the cis-acting coding, non-coding and structural genetic alteration, but most gene expression variation was not explained by our genetic analysis. Leveraging matched chromatin-accessibility sequencing data, enhancer mutations with cis regulatory effects on gene expression were associated with a change in chromatin accessibility, indicating that non-coding variation can have phenotypic consequence through modulation of the 3D architecture of the genome. This study maps the evolution of transcriptional variation during cancer evolution, highlighting that intra-tumour phenotypic plasticity is pervasive in colorectal malignancies, and may play key roles in further tumour evolution, from metastasis to therapy resistance.

cancer biology↗

bioRxiv2021

Assessment of the evolutionary consequence of putative driver mutations in colorectal cancer with spatial multiomic data

Cancer genomic medicine relies on targeting driver genes. However, current catalogues of cancer drivers are mostly based on indirect measurements of mutation frequencies, positions or types, rather than their effect on clonal expansions in vivo. Moreover, non-genetic drivers are largely unknown, as are the epigenetic and transcriptomic effects of genetic drivers. Here we perform spatial computational inference on multiomic data with matched whole-genome sequencing, ATAC-seq and RNA-seq. Using 436 samples, we directly quantify the contribution, or lack thereof, of putative driver genes to subclonal expansions in vivo in 30 colorectal carcinomas (4-33 samples per patient, median=15). Although subclonal neutral evolution was widespread (13/26 cases with sufficient data), there were cases with clear evidence of subclonal selection (6/26) in which we measured epigenetic and transcriptomic differences between subclones in vivo. In 7/26 cases we could not distinguish between neutral or selective evolution with the available data. We identified expanding subclones that were not driven by known genetic alterations, and propose candidate epigenetic drivers. We identified the distinguishing patterns of genomic heterogeneity produced in fast, exponentially growing tumours (7/26) versus neoplasms growing only at the periphery (19/26), as well as identifying clonally intermixed (16/28 cases with sufficient data) versus segregated malignancies (10/28). Our model-based approach measures genetic and non-genetic subclonal selection, or lack thereof, in space and time and allows in vivo comparisons of the emergent phenotypic properties of subclones within human tumours.

cancer biology↗

bioRxiv2021

The co-evolution of the genome and epigenome in colorectal cancer

Colorectal malignancies are a leading cause of cancer death. Despite large-scale genomic efforts, DNA mutations do not fully explain malignant evolution. Here we study the co-evolution of the genome and epigenome of colorectal tumours at single-clone resolution using spatial multi-omic profiling of individual glands. We collected 1,373 samples from 30 primary cancers and 9 concomitant adenomas and generated 1,212 chromatin accessibility profiles, 527 whole-genomes and 297 whole-transcriptomes. We found positive selection for DNA mutations in chromatin modifier genes and recurrent chromatin changes in regulatory regions of cancer drivers with otherwise no mutation. Genome-wide alterations in transcription factor binding accessibility involved CTCF, downregulation of interferon, and increased accessibility for SOX and HOX, indicating developmental genes reactivation. Epigenetic aberrations were heritable, distinguishing adenomas from cancers. Mutational signature analysis showed the epigenome influencing DNA mutation accumulation. This study provides a map of (epi)genetic tumour heterogeneity, with fundamental implications for understanding colorectal cancer biology.

cancer biology↗

bioRxiv2021

Unperturbed dormancy recording reveals stochastic awakening strategies in endocrine treated breast cancer cells

Hormone dependent breast cancer (HDBC) is the most commonly diagnosed tumor type in women. Adjuvant endocrine therapies (ET) have been the cornerstone in the clinical management of HDBC patients for over forty years. A vast proportion of HDBC patients incur long periods of clinical dormancy following ET, with tumour awakening appearing at a steady pace for up to 25 years (Pan et al., 2017). Extensive genomic studies have demonstrated that 15-30% of clinical relapses develop recurrent genomic changes which contribute to drug resistance (i.e. ESR1 activating mutations) (Bertucci et al., 2019; Magnani et al., 2017; Razavi et al., 2018). However, even in these cases, there is no conclusive evidence around the pre-existence vs. de novo nature of these events. We previously showed that ETs can trigger and select for dormancy in subpopulations of breast cancer(Hong et al., 2019). In this work we took two novel approaches to investigate the dormancy and awakening roadmap of HDBC cells in unprecedented detail. Firstly, we leveraged a rare cohort of n=5 patients which were treated with primary adjuvant ETs in the absence of surgery (TRACING-HT) to dissect the contribution of genomic aberrations to tumor awakening. Next, we developed a first of its kind evolutionary study in vitro to systematically annotate cancer cells adaptive strategies at single cell level in unperturbed systems during a period of several months (TRADITIOM). Collectively our data suggest that ETs steer HDBC cells into an inherently unstable dormant state. Over time, routes to awakening emerge sporadically and spontaneously in single lineages. Each dormant cell retains an intrinsic awakening probability which we propose is a function of epigenetic decay. Awakening occurs without an external trigger and involves multiple apparent endpoint phenotypes that cannot be fully explained by conventional Darwinian genetic selection processes. Finally, our data show that common genetic hits associated with resistance happen downstream of awakening. Overall, our data have uncovered previously unsuspected roles for stochastic nongenetic events during dormancy with profound clinical implications.

cancer biology↗

bioRxiv2020

VGLL1-directed TEAD activation drives endocrine therapy resistance in estrogen receptor positive breast cancer

Resistance to endocrine therapies (ET) is common in estrogen receptor (ER) positive breast cancer and most relapsed patients die with ET-resistant disease. While genetic mutations provide explanations for some relapsed patients1, mechanisms of resistance remain undefined in many cases. Drug-induced epigenetic reprogramming provides possible routes to resistance2. By analysing histone H3 lysine 27 acetylation (H3K27ac) profiles in models of ET resistance, we discovered that selective ER down-regulators (SERDs) such as fulvestrant promote epigenetic activation of VGLL1, a co-activator for TEAD transcription factors. We show that VGLL1, acting via TEADs, promotes expression of genes that drive growth of fulvestrant-resistant breast cancer cells. Pharmacological disruption of VGLL1/TEAD4 interaction inhibits VGLL1/TEAD transcriptional programmes to block growth of the resistant cells and prevents growth. Among the VGLL1/TEAD-regulated genes, we identify EGFR, whereby VGLL1-directed EGFR upregulation sensitises fulvestrant-resistant breast cancer cells to EGFR inhibitors. Taken together, our findings identify VGLL1 as a transcriptional driver in ET resistance and advance new therapeutic possibilities for relapsed ER+ breast cancer patients.

cancer biology↗

bioRxiv2020

Time-resolved profiling reveals ATF3 as a novel mediator of endocrine resistance in breast cancer

Breast cancer is one of the leading causes of death for women worldwide. Patients whose tumors express Estrogen Receptor (ER) account for around 70% of cases and are mostly treated with targeted endocrine therapy. However, 40% of these tumors eventually relapse due to resistance development and further treatment of these patients is highly ineffective. In this study we profiled the early phases of the resistance development process to uncover drivers of this phenomenon. Time-resolved analysis revealed that ATF3, a member of the ATF/CREB family of transcription factors, acts as a novel regulator of the response to therapy via rewiring of central signaling processes towards the adaptation to endocrine treatment. ATF3 was found to be essential in controlling crucial processes such as proliferation, cell cycle and apoptosis during the early response to treatment through the regulation of MAPK/AKT signaling pathways. Its essential role was confirmed in vivo in a mouse model and elevated expression of ATF3 was verified in patient datasets, adding clinical relevance to our findings. This study proposes ATF3 as a novel mediator of endocrine resistance development in breast cancer and elucidates its role in the regulation of downstream pathways activities.

cancer biology↗

bioRxiv2020

Invasive breast tumors are characterized by the presence of crystalline nanoparticles

The presence of calcifications on mammograms is a widely used diagnostic marker for breast cancer. While the clinicopathological analysis of breast tissue is well-developed, an in-depth characterisation of the properties of calcifications at the micro and nano scale remained elusive. In this work, we use nano-analytical methods to investigate the calcification present in healthy breast tissue, as well as in benign and malignant breast tumour tissue biopsies. While polycrystalline apatite with lower crystallinity can be found in all breast tissue samples, we show that magnesium-containing nano and micro spherical particles are found only in malignant invasive breast cancers. These particles concentration increases with cancer progression. The discovery of these spherical particles provides new insights into the characteristics of breast calcification associated with malignant tumours and opens new research pathways to a better understanding of breast tumours and their microenvironment in general.

cancer biology↗

bioRxiv2019

Exploiting evolutionary herding to control drug resistance in cancer

Drug resistance mediated by clonal evolution is arguably the biggest problem in cancer therapy today. However, evolving resistance to one drug may come at a cost of decreased growth rate or increased sensitivity to another drug due to evolutionary trade-offs. This weakness can be exploited in the clinic using an approach called evolutionary herding that aims at controlling the tumour cell population to delay or prevent resistance. However, recapitulating cancer evolutionary dynamics experimentally remains challenging. Here we present a novel approach for evolutionary herding based on a combination of single-cell barcoding, very large populations of 108-109 cells grown without re-plating, longitudinal non-destructive monitoring of cancer clones, and mathematical modelling of tumour evolution. We demonstrate evolutionary herding in non-small cell lung cancer, showing that herding allows shifting the clonal composition of a tumour in our favour, leading to collateral drug sensitivity and proliferative fitness costs. Through genomic analysis and single-cell sequencing, we were also able to determine the mechanisms that drive such evolved sensitivity. Our approach allows modelling evolutionary trade-offs experimentally to test patient-specific evolutionary herding strategies that can potentially be translated into the clinic to control treatment resistance.

cancer biology↗

bioRxiv2018

Single-cell Transcriptomics reveals multi-step adaptations to endocrine therapy

Resistant tumours are thought to arise from the action of Darwinian selection on genetically heterogenous cancer cell populations. However, simple clonal selection is inadequate to describe the late relapses often characterising luminal breast cancers treated with endocrine therapy (ET), suggesting a more complex interplay between genetic and non-genetic factors. Partially, this is due to our limited understanding on the effect of ET at the single cell level. In the present study, we dissect the contributions of clonal genetic diversity and transcriptional plasticity during the early and late phases of ET at single-cell resolution. Using single-cell RNA-sequencing and imaging we disentangle the transcriptional variability of plastic cells and define a rare sub-population of pre-adapted (PA) cells which undergoes further transcriptomic reprogramming and copy number changes to acquire full resistance. PA cells show reduced oestrogen receptor activity but increased features of quiescence and migration. We find evidence for sub-clonal expression of this PA signature in primary tumours and for dominant expression in clustered circulating tumour cells. We propose a multi-step model for ET resistance development and advocate the use of stage-specific biomarkers.

cancer biology↗

bioRxiv2018

SREBP1 drives KRT80-dependent cytoskeletal changes and invasive behavior in endocrine resistant ERα breast cancer

Approximately 30% of women diagnosed with ER breast cancer relapse with metastatic disease following adjuvant treatment with endocrine therapies1,2. The connection between acquisition of drug resistance and invasive potential is poorly understood. In this study, we demonstrate that the type II keratin topological associating domain (TAD)3 undergoes epigenetic reprogramming in cells that develop resistance to aromatase inhibitors (AI), leading to keratin 80 (KRT80) upregulation. In agreement, an increased number of KRT80-positive cells are observed at relapse in vivo while KRT80 expression associates with poor outcome using several clinical endpoints. KRT80 expression is driven by de novo enhancer activation by sterol regulatory element-binding protein 14 (SREBP1). KRT80 upregulation directly promotes cytoskeletal rearrangements at the leading edge, increased focal adhesion maturation and cellular stiffening, which collectively promote cancer cell invasion. Shear-wave elasticity imaging of prospective patients shows that KRT80 levels correlate with stiffer tumors in vivo. Collectively, our data uncover an unpredicted and potentially targetable direct link between epigenetic and cytoskeletal reprogramming promoting cell invasion in response to chronic AI treatment.

cancer biology↗

bioRxiv2017

Enhancers mapping uncovers phenotypic heterogeneity and evolution in patients with luminal breast cancer.

The degree of intrinsic and interpatient phenotypic heterogeneity and its role in tumour evolution is poorly understood. Phenotypic divergence can be achieved via the inheritance of alternative transcriptional programs1,2. Cell-type specific transcription is maintained through the activation of epigenetically-defined regulatory regions including promoters and enhancers1,3,4. In this work, we annotated the epigenome of 47 primary and metastatic oestrogen-receptor (ER)-positive breast cancer specimens from clinical samples, and developed strategies to deduce phenotypic heterogeneity from the regulatory landscape, identifying key regulatory elements commonly shared across patients. Highly shared regions contain a unique set of regulatory information including the motif for the transcription factor YY1. In vitro work shows that YY1 is essential for ER transcriptional activity and defines the critical subset of functional ER binding sites driving tumor growth in most luminal patients. YY1 also control the expression of genes that mediate resistance to endocrine treatment. Finally, we show that H3K27ac levels at active enhancer elements can be used as a surrogate of intra-tumor phenotypic heterogeneity, and to track expansion and contraction of phenotypic subpopulations throughout breast cancer progression. Tracking YY1 and SLC9A3R1 positive clones in primary and metastatic lesions, we show that endocrine therapies drive the expansion of phenotypic clones originally underrepresented at diagnosis. Collectively, our data show that epigenetic mechanisms significantly contribute to phenotypic heterogeneity and evolution in systemically treated breast cancer patients.

cancer biology↗