Biology subjects

Lutsik, P.

Publications and source records attributed to Lutsik, P..

At least 19 recordsLinked to original sources

bioRxiv2026

Hierarchical classification of hematologic malignancies using epigenetic and genetic information

Molecular testing in hematology requires different assays for disease subgroup identification, risk stratification and selection of appropriate treatment regimens. Yet, molecular tests are not necessarily standardized between diagnostic laboratories, resulting in varying turnaround times and potentially divergent results. To resolve this issue and enable single-assay molecular testing, we have developed a hierarchical classification framework that combines epigenetic and genetic data from whole genome nanopore sequencing (WGNS) with machine learning to determine disease entities, epigenetic subgroups (epitypes) and genetic aberrations in hematopoietic neoplasms. We curated DNA methylation data from 5,420 samples and trained a classifier allowing entity-level diagnostics featuring 21 conditions, including healthy controls, acute and chronic myeloid and lymphoid neoplasms. This classifier was subsequently combined with entity-specific epitype classifiers predicting 44 therapeutically or prognostically relevant states, followed by integration of genetic data. Benchmarking of the combined (epi-)genetic testing strategy using WGNS confirmed high accuracy in the detection of diagnostic groups and risk stratification, and identified diagnosis-defining molecular alterations that were not reported by standard-of-care work-up.

cancer biology↗

bioRxiv2026

Loss of the Y chromosome drives epigenetic and transcriptomic plasticity in lung adenocarcinoma

Loss of the Y chromosome (LOY) is associated with poor survival across multiple solid tumors, yet the underlying molecular mechanisms remain poorly understood. Here, we identify LOY as a central driver of lineage plasticity and epigenetic heterogeneity in lung adenocarcinoma. Integrating multi-omic profiling of primary samples with isogenic cellular models, we show that LOY triggers epithelial-to-mesenchymal transition (EMT). Mechanistically, LOY causes haploinsufficiency of dosage-sensitive regulators, leading to widespread DNA hypomethylation at EMT gene promoters, including THY1 and LOX. Single-cell multi-omic analyses demonstrate that LOY induces epigenetic heterogeneity, destabilizes the chromatin landscape, and increases lineage plasticity, enabling rapid cellular adaptation to metabolic and genotoxic stress. Moreover, LOY-induced plasticity facilitates tumor engraftment and metastatic dissemination in vivo. These findings establish Y-linked gene dosage as a critical guardian of epigenetic stability, providing a mechanistic rationale for how its loss amplifies phenotypic diversity and lineage plasticity, ultimately driving adverse clinical outcomes in LOY patients.

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↗

bioRxiv2025

Methylation reprogramming associated with aggressive prostate cancer and ancestral disparities

African men are disproportionately impacted by aggressive prostate cancer (PCa). Key to this disparity both genetic and environmental factors, alluding to epigenetic modifications. However, African-inclusive prostate tumour DNA methylation studies are lacking. Assembling a multi-geo-ancestral prostate tissue cohort, including men with (57 African, 48 European, 23 Asian) or without (65 African) PCa, we interrogate for genome-wide differential methylation. Overall, methylation appears to be driven by ancestry over geography (152 southern Africa, 41 Australia). African tumours show substantial heterogeneity, with universal hypermethylation indicating epigenetic silencing, encompassing PCa suppressor genes and enhancer-targeted binding motifs. Conversely, African tumour-associated heterochromatic hypomethylation suggests permissive chromatin remodelling, with developmental pathway activation via enhancer targets. Taken together, we show methylation aberrations favour metastatic growth, genomic instability and disease aggressiveness in African tumours, which we hypothesise is driven by extensive plasticity of intergenic regulatory regions.

genomics↗

bioRxiv2024

DNMT/G9a Complex Inhibition Uncovers Epigenetic Vulnerabilities and Induces IFN-Response in Acute Myeloid Leukemia

Epigenetic dysregulation is a hallmark of Acute Myeloid Leukemia (AML), with mutations in DNA Methyltransferases (e.g., DNMT3A) being frequent and promising therapeutic targets. DNMTs form complexes with Histone Methyltransferases (HMTs), driving gene silencing loop via chromatin methylation crosstalk. However, potential connections between this DNMTs/HMTs cooperative activity and oncogenic requirements across the AML mutational spectrum remain poorly understood. Here, we demonstrate that AMLs carrying DNMT3A and Nucleophosmin (NPM1) mutations exhibit a specific epigenetic vulnerability toward a complex formed by DNMTs and G9a, a specific histone H3 Lysine 9 Methyltransferase (H3K9-HMT). Dual inhibition of DNMT/G9a restores differentiation, reduces tumor growth, and spares healthy progenitors compared to standard hypomethylating agents. Mechanistically, DNMT/G9a regulates NPM1 stability, inhibits HOXA9/MEIS1 activity, and triggers interferons (IFN) response via viral mimicry pathways by modulating hypermethylated retrotransposons. Collectively, our data unravel specific epigenetic vulnerabilities within the complex AML mutational landscape and provide a compelling rationale for the design of personalized epigenetic therapies with enhanced efficacy and safer clinical outcomes.

cancer biology↗

bioRxiv2024

Acute Myeloid Leukemia with deletion 5q is an epigenetically distinct subgroup defined by heterozygous loss of KDM3B

Acute myeloid leukemia (AML) is a hematological malignancy characterized by a block in differentiation and accelerated proliferation of myeloid progenitor cells. Genes encoding for epigenetic regulators are among the most frequent targets for mutations and structural variations in AML, giving rise to profound epigenetic heterogeneity between and within tumors. Deletions of chromosome 5q [del(5q)] are among the most common copy number alterations in AML and are associated with extremely poor clinical outcome and therapy resistance, however the mechanisms linking del(5q) to leukemic progression are not understood. Analyzing DNA methylation profiles from 477 elderly AML patients using DNA methylome deconvolution, we discovered that del(5q) AML is an epigenetically distinct subgroup characterized by a signature of DNA hypermethylation, which we propose may be linked to dysregulation of H3K9me1/2 and overexpression of the leukemic stem cell marker, DNMT3B. Interrogation of the minimally deleted 5q region highlighted the H3K9me1/2 demethylase KDM3B as a likely target for haploinsufficiency in this subgroup. Our data suggest that del(5q) AML should be reconsidered as an epigenetically dysregulated subgroup, driven by heterozygous loss of KDM3B, and that the resulting imbalance of H3K9me1/2 may contribute to the progression of these aggressive leukemias.

cancer biology↗

bioRxiv2024

Pipeline Olympics: continuable benchmarking of computational workflows for DNA methylation sequencing data against an experimental gold-standard

DNA methylation is a widely studied epigenetic mark and a powerful biomarker of cell type, age, environmental exposures, and disease. Whole-genome sequencing following selective conversion of unmethylated cytosines into thymines via bisulfite treatment or enzymatic methods remains the reference method for DNA methylation profiling genome-wide. While numerous software tools facilitate processing of DNA methylation sequencing reads, a comprehensive benchmarking study has been lacking thus far. In this study, we systematically compared complete computational workflows for processing DNA methylation sequencing data using a dedicated benchmarking dataset generated with five genome-wide profiling protocols. As an evaluation reference, we employed highly quantitative locus-specific measurements from our preceding benchmark of targeted DNA methylation assays. Based on this experimental gold-standard assessment and several comprehensive metrics, we identified workflows that consistently demonstrated superior performance and revealed major workflow development trends. To facilitate the sustainability of our benchmark, we implemented an interactive workflow execution and data presentation platform, adaptable to user-defined criteria and seamlessly expandable to future software.

bioinformatics↗

bioRxiv2024

SRSF2 transcriptional function maintains genome integrity during cell division

Recurrent mutations in serine / arginine-rich splicing factor 2 (SRSF2), particularly the proline-to-histidine substitution at position 95 (P95H), have been proposed to drive neoplastic diseases. SRSF2 plays pivotal roles in pre-mRNA processing and gene transcription. However, the precise impact of these diverse functions of SRSF2 on cancer cell behaviour remains unclear. Here, we show that deletion or homozygous P95H mutation of SRSF2 both cause extensive DNA damage leading to cell cycle arrest in vitro and in vivo, regardless of cell genotype. We mechanistically demonstrate that SRSF2 is required for efficient bi-directional transcription of DNA replication and repair genes, independent of its function in splicing. In contrast, SRSF2 haploinsufficiency induces DNA damage without halting the cell cycle in cancer cells. Inducing the heterozygous Srsf2 P95H mutation leads to clonal expansion of epidermal cells in mouse skin, but tumor formation is inhibited following exposure to carcinogens. To survive carcinogen treatment, cells containing the Srsf2 P95H mutation undergo substantial transcription rewiring that restores bi-directional gene expression. Thus, our study reveals crucial roles of SRSF2 beyond splicing and underscores its importance in regulating transcription to orchestrate the cell cycle along with the DNA damage response.

cell biology↗

bioRxiv2024

EpiCHAOS: a metric to quantify epigenomic heterogeneity in single-cell data

Epigenetic heterogeneity is a fundamental property of biological systems, and is recognized as a potential driver of tumor plasticity and therapy resistance. Single-cell epigenomics technologies have been widely employed to study epigenetic variation between - but not within - cellular clusters. We introduce epiCHAOS: a quantitative metric of cell-to-cell heterogeneity, applicable to any single-cell epigenomics data type. After validation in synthetic datasets, we applied epiCHAOS to investigate global and region-specific patterns of epigenetic heterogeneity across diverse biological systems. EpiCHAOS provides an excellent approximation of stemness and plasticity in development and malignancy, making it a valuable addition to single-cell cancer epigenomics analyses.

bioinformatics↗

bioRxiv2024

Figeno: multi-region genomic figures with long-read support

SummaryThe vast amount of publicly available genomic data requires analysis and visualization tools. Here, we present figeno, an application for generating publication-quality FIgures for GENOmics. Figeno particularly focuses on multi-region views across genomic breakpoints and on long reads with base modifications. Additionally, we support epigenomic data including ATAC-seq, ChIP-seq or HiC, as well as whole genome sequencing data with copy numbers and structural variants. Availability and ImplementationFigeno is available as a python package with both a command line and graphical user interface. It can be installed via PyPI and the source code is available at https://github.com/CompEpigen/figeno. Supplementary informationSupplementary data is provided.

bioinformatics↗

bioRxiv2023

Oncogenic RAS-Pathway Activation Drives Oncofetal Reprogramming and Creates Therapeutic Vulnerabilities in Juvenile Myelomonocytic Leukemia

Aberrant fetal gene expression facilitates tumor-specific cellular plasticity by hijacking molecular programs of embryogenesis1. Persistent fetal gene signatures in childhood malignancies are typically explained by their prenatal origins2-6. In contrast, reactivation of fetal gene expression is considered a consequence of oncofetal reprogramming (OFR) in adult malignancies and is associated with aggressive disease7-10. To date, OFR has not been described in the context of childhood malignancies. Here, we performed a comprehensive multi-layered molecular characterization of juvenile myelomonocytic leukemia (JMML) and identified OFR as a hallmark of aggressive JMML. We observed that hematopoietic stem cells (HSCs) aberrantly express mixed developmental programs in JMML. Expression of fetal gene signatures combined with a postnatal epigenetic landscape suggested OFR, which was validated in a JMML mouse model, demonstrating that postnatal activation of RAS signaling is sufficient to induce fetal gene signatures. Integrative analysis identified the fetal HSC maturation marker CD52 as a novel therapeutic target for aggressive JMML. Anti-CD52 treatment depleted human JMML HSCs and disrupted disease propagation in vivo. In summary, this study implicates OFR, defined as postnatal acquisition of fetal transcription signatures, in the pathobiology of a childhood malignancy. We provide evidence for the direct involvement of oncogenic RAS signaling in OFR. Finally, we demonstrate how OFR can be leveraged for the development of novel treatment strategies. Highlights{blacksquare} Epigenomic and transcriptomic landscape of juvenile myelomonocytic leukemia (JMML) in the context of hematopoietic development. {blacksquare}The presence of fetal transcription signatures in childhood malignancies is not indicative of a developmental maturation block. {blacksquare}High-risk JMML is characterized by oncofetal reprogramming of postnatal hematopoietic stem cells (HSCs). {blacksquare}RAS-pathway mutations induce fetal-like gene expression signatures in murine postnatal HSCs. {blacksquare}The fetal maturation marker CD52 is a novel therapeutic target in high-risk JMML.

cancer biology↗

bioRxiv2023

MethylBERT: A Transformer-based model for read-level DNA methylation pattern identification and tumour deconvolution

DNA methylation (DNAm) is a key epigenetic mark that shows profound alterations in cancer. Read-level methylomes enable more in-depth DNAm analysis due to the broad coverage and preservation of rare cell-type signals, compared to array-based data such as 450K/EPIC array. Here, we propose MethylBERT, a novel Transformer-based model for read-level methylation pattern classification. MethylBERT identifies tumour-derived sequence reads based on their methylation patterns and genomic sequence. Using the read classification probability, the method estimates tumour cell fractions within bulk samples and provides an assessment of the model precision. In our evaluation, MethylBERT outperforms existing deconvolution methods and demonstrates high accuracy regardless of methylation pattern complexity, read length and read coverage. Moreover, we show its applicability to cell-type deconvolution as well as its potential for accurate non-invasive early cancer diagnostics using liquid biopsy samples. MethylBERT represents a significant advancement in read-level methylome analysis and enables accurate tumour purity estimation. The broad applicability of MethylBERT will enhance studies on both solid tumour tissues and circulating tumour DNA as well as non-cancerous bulk methylomes.

bioinformatics↗

bioRxiv2023

Altered enhancer-promoter interaction leads to MNX1 expression in pediatric acute myeloid leukemia with t(7;12)(q36;p13)

Acute myeloid leukemia (AML) with the t(7;12)(q36;p13) translocation occurs only in very young children and has a poor clinical outcome. The expected oncofusion between breakpoint partners (MNX1 and ETV6) has only been reported in a subset of cases. However, a universal feature is the strong transcript and protein expression of MNX1, a homeobox transcription factor that is normally not expressed in hematopoietic cells. Here, we map the translocation breakpoints on chromosomes 7 and 12 in affected patients to a region proximal to MNX1 and either introns 1 or 2 of ETV6. The frequency of MNX1 overexpression in pediatric AML (n=1556, own and published data) is 2.4% and occurs predominantly in t(7;12)(q36;p13) AML. Chromatin interaction assays in a t(7;12)(q36;p13) iPSC cell line model unravel an enhancer-hijacking event that explains MNX1 overexpression in hematopoietic cells. Our data suggest that enhancer-hijacking is a more common and overlooked mechanism for structural rearrangement-mediated gene activation in AML. Key pointsO_LIExpression analysis of over 1500 pediatric AML samples demonstrates MNX1 expression as a universal feature of t(7;12)(q36;p13) AML as well as in rare cases without t(7;12)(q36;p13) C_LIO_LIMNX1 is activated by an enhancer-hijacking event in t(7;12)(q36;p13) AML and not, as previously postulated, by the creation of a MNX1::ETV6 oncofusion gene. C_LI

cancer biology↗

bioRxiv2023

Decoding Single-Cell Multiomics: scMaui - A Deep Learning Framework for Uncovering Cellular Heterogeneity in Presence of Batch Effects and Missing Data

The recent advances in high-throughput single-cell sequencing has significantly required computational models which can address the high complexity of single-cell multiomics data. Meticulous single-cell multiomics integration models are required to avoid biases towards a specific modality and overcome the sparsity. Batch effects obfuscating biological signals must also be taken into account. Here, we introduce a new single-cell multiomics integration model, Single-cell Multiomics Autoencoder Integration (scMaui) based on stacked variational encoders and adversarial learning. scMaui reduces the dimensionality of integrated data modalities to a latent space which outlines cellular heterogeneity. It can handle multiple batch effects independently accepting both discrete and continuous values, as well as provides varied reconstruction loss functions to cover various assays and preprocessing pipelines. We show that scMaui accomplishes superior performance in many tasks compared to other methods. Further downstream analyses also demonstrate its potential in identifying relations between assays and discovering hidden subpopulations.

bioinformatics↗

bioRxiv2022

Mnx1 Induces Leukemia Transformation Through Altering Histone Methylation in a Model of Pediatric t(7;12) Acute Myeloid Leukemia.

Certain subtypes of acute myeloid leukemia (AML) in children have inferior outcome. One of these has a translocation t(7;12)(q36;p13) leading to a MNX1::ETV6 fusion along with high expression of MNX1. Here we identified the transforming event in this AML and possible ways of treatment. Only MNX1 was able to induce AML in mice, with similar gene expression and pathway enrichment to t(7;12) AML patient data. Importantly, this leukemia was only induced in immune incompetent mice using fetal but not adult hematopoietic stem and progenitor cells. The restriction in transforming capacity to cells from fetal liver is in alignment with t(7;12)(q36;p13) AML being mostly seen in infants. Expression of MNX1 led to increased histone 3 lysine 4 mono-, di- and trimethylation, reduction in H3K27me3, accompanied with changes in genome-wide chromatin accessibility and genome expression, likely mediated through MNX1 interaction with the methionine cycle and methyltransferases. MNX1 expression increased DNA damage, depletion of the Lin-/Sca1+/c-Kit+ population and skewing toward the myeloid lineage. These effects, together with leukemia development, was prevented by pretreatment with the S-adenosylmethionine analog Sinefungin. In conclusion, we have shown the importance of MNX1 in development of AML with t(7;12), supporting a rationale for targeting MNX1 and downstream pathways.

cancer biology↗

bioRxiv2022

Dynamic DNA methylation reveals novel cis-regulatory elements in murine hematopoiesis

BackgroundThe differentiation of hematopoietic stem and progenitor cells (HSPCs) to terminally differentiated immune cells is accompanied by large-scale remodeling of the DNA methylation landscape. While significant insights into the molecular mechanisms of hematopoietic tissue regeneration were derived from mouse models, profiling of DNA methylation changes has been hampered by high cost or low resolution using the methods available. This problem has been overcome by the recent development of the Infinium Mouse Methylation BeadChip (MMBC) array, facilitating methylation profiling of the mouse genome at single CpG resolution at affordable cost. ResultsWe extended the RnBeads package to provide a computational framework for the analysis of MMBC data. This framework was applied to a newly generated MMBC reference map of mouse hematopoiesis encompassing nine different cell types. The analysis of dynamically regulated CpG sites showed progressive and unidirectional DNA methylation changes from HSPCs to differentiated hematopoietic cells and allowed the identification of lineage- and cell type-specific DNA methylation programs. Comparison to previously published catalogues of cis-regulatory elements (CREs) revealed 12,856 novel putative CREs which were dynamically regulated by DNA methylation (mdCREs). These mdCREs were predominantly associated with patterns of cell type-specific DNA hypomethylation and could be identified as epigenetic control regions regulating the expression of key hematopoietic genes during differentiation. ConclusionsWe established a publicly available analysis pipeline for MMBC datasets and provide a DNA methylation atlas of mouse hematopoiesis. This resource allowed us to identify novel putative CREs involved in hematopoiesis and will serve as a platform to study epigenetic regulation of normal and malignant hematopoiesis.

genomics↗

bioRxiv2021

Systematic evaluation of cell-type deconvolution pipelines for sequencing-based bulk DNA methylomes

DNA methylation analysis by sequencing is becoming increasingly popular, yielding methylomes at single-base pair resolution. It has tremendous potential for cell-type heterogeneity analysis with intrinsic read-level information. Although diverse deconvolution methods were developed to infer cell-type composition based on bulk sequencing-based methylomes, the systematic evaluation has not been performed yet. Here, we thoroughly benchmark six previously published methods: Bayesian epiallele detection (BED), DXM, PRISM, csmFinder+coMethy, ClubCpG and MethylPurify, together with two array-based methods, MeDeCom and Houseman, as a comparison group. Sequencing-based deconvolution methods consist of two main steps, informative region selection and cell-type composition estimation, thus each was individually assessed. With these sophisticated evaluation, we demonstrate the method achieving the highest performance in different types of samples. We found that cell-type deconvolution performance is influenced by different factors depending on the number of cell types within the mixture. Finally, we propose a best-practice deconvolution strategy for sequencing data and limitations which need to be handled.

bioinformatics↗

bioRxiv2021

Diverse routes of Club cell evolution in lung adenocarcinoma

The high plasticity of lung epithelial cells, has for many years, confounded the correct identification of the cell-of-origin of lung adenocarcinoma (LUAD), one of the deadliest malignancies worldwide. Here, we address the cell-of-origin of LUAD, by employing lineage-tracing mouse models combined with a CRISPR/Cas9 system to induce an oncogenic Eml4-Alk rearrangement in virtually all epithelial cell types of the lung. We find that Club cells give rise to lung tumours with a higher frequency than AT2 cells. Based on whole genome methylome, we identified that tumours retain an epigenetic memory derived from their originating cell type but also develop a tumour-specific pattern regardless of their origin. Single-cell transcriptomic analyses identified two trajectories of Club cell evolution which are similar to the ones used during lung regeneration, providing a link between lung regeneration and cancer initiation. On both routes, tumours lose their Club cell identity and gain an AT2- like phenotype. Together, this study highlights the role of Club cells in LUAD initiation and unveils key mechanisms conferring LUAD heterogeneity.

cancer biology↗