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37 Publications visible to you, out of a total of 37
Topology-aware pathway analysis of spatial transcriptomics

Abstract (Expand)

Spatial transcriptomics (ST) has transformed genomics by mapping gene expression onto intact tissue architecture, uncovering intricate cellular interactions that bulk and single-cell RNA sequencing … often overlook. Traditional ST workflows typically involve clustering spots, performing differential expression analyses, and annotating results via gene-set methods such as overrepresentation analysis (ORA) or gene set enrichment analysis (GSEA). More recent spatially-aware techniques extend these approaches by incorporating tissue organization into gene-set scoring. However, because they operate primarily at the level of individual genes, they may overlook the connectivity and topology of biological pathways, limiting their capacity to trace the propagation of signaling events within tissue regions. In this study, we address that gap by translating gene expression into pathway-level activity using the Pathway Signal Flow (PSF) algorithm. PSF integrates expression data with curated interaction networks to compute numeric activity scores for each branch of a biological pathway, producing a functionally annotated feature space that captures downstream signaling effects as branch-specific activity values. We applied PSF to two public 10x Genomics Visium datasets (human melanoma and mouse brain) and compared clustering based on PSF-derived pathway activities from 40 curated Kyoto Encyclopedia of Genes and Genomes (KEGG) signaling pathways and gene expression with standard Seurat Louvain clustering and spatially aware methods (Vesalius, spatialGE). We observed good correspondence between PSF-based and expression-based clustering when spatially aware clustering methods were used. This suggests that branch-level pathway activities can themselves drive clustering and pinpoint spatially deregulated processes. To assess cluster-specific functional annotation, we compared PSF results to conventional ORA (based on marker genes) and GSDensity (based on cluster-specific gene sets). PSF identified a broader set of significant pathways with substantial overlap with both ORA and GSDensity, providing increased sensitivity due to its branch-level resolution. We further demonstrated that PSF-derived activity values can be used to detect spatially deregulated pathway branches, yielding results comparable to those obtained with spatially aware gene set analysis approaches such as GSDensity and spatialGE. The availability of pathway topology and branch-specific information also enabled the identification of potential intercellular communication via ligand-receptor interactions between deregulated pathways in adjacent tumor regions. To support interactive exploration of results, we developed the PSF Spatial Browser, an R Shiny application for visualizing pathway activities, gene expression patterns, and deregulated pathway networks.

Authors: Siras Hakobyan, Maria Schmidt, H. Binder, A. Arakelyan

Date Published: 14th Aug 2025

Publication Type: Journal

Telomere Maintenance Pathways in Lower-Grade Gliomas: Insights from Genetic Subtypes and Telomere Length Dynamics

Abstract (Expand)

Telomere maintenance mechanisms (TMMs) play a critical role in cancer biology, particularly in lower-grade gliomas (LGGs), where telomere dynamics and pathway activity remain poorly understood. In this … study, we analyzed TCGA-LGG and CGGA datasets, focusing on telomere length variations, pathway activity, and survival data across IDH subtypes. Additional validation was performed using the GEO COPD and GBM datasets, ensuring consistency in data processing and batch effect correction. Our analysis revealed significant differences in TEL pathway activation between Short- and Long-TL groups, emphasizing the central role of TERT in telomere maintenance. In contrast, ALT pathway activation displayed subtype-specific patterns, with IDH-wt tumors exhibiting the highest ALT activity, primarily driven by the RAD51 branch. Validation using CGGA data confirmed these findings, demonstrating consistent TEL and ALT pathway behaviors across datasets. Additionally, genetic subtype analysis revealed substantial telomere length variability associated with ATRX and IDH mutation status. Notably, IDHwt-ATRX WT tumors exhibited the shortest telomere length and the highest ALT pathway activity. These findings highlight distinct telomere regulatory dynamics across genetic subtypes of LGG and provide new insights into potential therapeutic strategies targeting telomere maintenance pathways.

Authors: Meline Hakobyan, Hans Binder, Arsen Arakelyan

Date Published: 28th Apr 2025

Publication Type: Journal

The metabolic underpinnings of sebaceous lipogenesis.

Abstract (Expand)

Sebaceous glands synthesize and secrete sebum, a melange of lipids and other cellular products that safeguards the mammalian integument. Differentiating sebocytes delaminate from the basal membrane and … dislodge towards the gland's middle, where they eventually undergo a poorly understood death mode in which the whole cell becomes a secretion product (holocrine secretion). Supported by recent transcriptomics data, this review examines the idea that peripheral sebocytes have a remarkable ability to draw nutrients from the blood and become committed to unrestrainedly invest all available resources into synthetic processes for accomplishing sebum synthesis, thereby exploiting core metabolic fluxes as glycogen turnover, glutamine-directed anaplerosis, the pentose phosphate pathway and de novo lipogenesis. Finally, we propose that metabolic-driven processes are an important mechanistic component of holocrine secretion. A deeper understanding of these metabolic adaptations could indicate novel strategies for modulating sebum synthesis, a key pathogenic factor in acne and other skin diseases.

Authors: M. Schmidt, H. Binder, M. R. Schneider

Date Published: 27th Apr 2025

Publication Type: Journal

Assigning Transcriptomic Subtypes to Chronic Lymphocytic Leukemia Samples Using Nanopore RNA-Sequencing and Self-Organizing Maps.

Abstract (Expand)

Background/Objectives: Massively parallel sequencing technologies have advanced chronic lymphocytic leukemia (CLL) diagnostics and precision oncology. Illumina platforms, while offering robust performance, … require substantial infrastructure investment and a large number of samples for cost-efficiency. Conversely, third-generation long-read nanopore sequencing from Oxford Nanopore Technologies (ONT) can significantly reduce sequencing costs, making it a valuable tool in resource-limited settings. However, nanopore sequencing faces challenges with lower accuracy and throughput than Illumina platforms, necessitating additional computational strategies. In this paper, we demonstrate that integrating publicly available short-read data with in-house generated ONT data, along with the application of machine learning approaches, enables the characterization of the CLL transcriptome landscape, the identification of clinically relevant molecular subtypes, and the assignment of these subtypes to nanopore-sequenced samples. Methods: Public Illumina RNA sequencing data for 608 CLL samples were obtained from the CLL-Map Portal. CLL transcriptome analysis, gene module identification, and transcriptomic subtype classification were performed using the oposSOM R package for high-dimensional data visualization with self-organizing maps. Eight CLL patients were recruited from the Hematology Center After Prof. R. Yeolyan (Yerevan, Armenia). Sequencing libraries were prepared from blood total RNA using the PCR-cDNA sequencing-barcoding kit (SQK-PCB109) following the manufacturer's protocol and sequenced on an R9.4.1 flow cell for 24-48 h. Raw reads were converted to TPM values. These data were projected into the SOMs space using the supervised SOMs portrayal (supSOM) approach to predict the SOMs portrait of new samples using support vector machine regression. Results: The CLL transcriptomic landscape reveals disruptions in gene modules (spots) associated with T cell cytotoxicity, B and T cell activation, inflammation, cell cycle, DNA repair, proliferation, and splicing. A specific gene module contained genes associated with poor prognosis in CLL. Accordingly, CLL samples were classified into T-cell cytotoxic, immune, proliferative, splicing, and three mixed types: proliferative-immune, proliferative-splicing, and proliferative-immune-splicing. These transcriptomic subtypes were associated with survival orthogonal to gender and mutation status. Using supervised machine learning approaches, transcriptomic subtypes were assigned to patient samples sequenced with nanopore sequencing. Conclusions: This study demonstrates that the CLL transcriptome landscape can be parsed into functional modules, revealing distinct molecular subtypes based on proliferative and immune activity, with important implications for prognosis and treatment that are orthogonal to other molecular classifications. Additionally, the integration of nanopore sequencing with public datasets and machine learning offers a cost-effective approach to molecular subtyping and prognostic prediction, facilitating more accessible and personalized CLL care.

Authors: A. Arakelyan, T. Sirunyan, G. Khachatryan, S. Hakobyan, A. Minasyan, M. Nikoghosyan, M. Hakobyan, A. Chavushyan, G. Martirosyan, Y. Hakobyan, H. Binder

Date Published: 13th Mar 2025

Publication Type: Journal

Single-cell transcriptomics and epigenomics point to CD58-CD2 interaction in controlling primary melanoma growth and immunity.

Abstract

Not specified

Authors: A. Stubenvoll, M. Schmidt, J. Moeller, M. A. L. Chango, C. Schultz, O. Antoniadou, H. Loeffler-Wirth, S. Bernhart, F. Grosse, B. Thier, A. Paschen, U. Anderegg, J. C. Simon, M. Ziemer, C. T. Schoeder, H. Binder, M. Kunz

Date Published: 15th Jan 2025

Publication Type: Journal

Unveiling Iso- and Aniso-Hydric Disparities in Grapevine-A Reanalysis by Transcriptome Portrayal Machine Learning.

Abstract (Expand)

Mechanisms underlying grapevine responses to water(-deficient) stress (WS) are crucial for viticulture amid escalating climate change challenges. Reanalysis of previous transcriptome data uncovered … disparities among isohydric and anisohydric grapevine cultivars in managing water scarcity. By using a self-organizing map (SOM) transcriptome portrayal, we elucidate specific gene expression trajectories, shedding light on the dynamic interplay of transcriptional programs as stress duration progresses. Functional annotation reveals key pathways involved in drought response, pinpointing potential targets for enhancing drought resilience in grapevine cultivation. Our results indicate distinct gene expression responses, with the isohydric cultivar favoring plant growth and possibly stilbenoid synthesis, while the anisohydric cultivar engages more in stress response and water management mechanisms. Notably, prolonged WS leads to converging stress responses in both cultivars, particularly through the activation of chaperones for stress mitigation. These findings underscore the importance of understanding cultivar-specific WS responses to develop sustainable viticultural strategies in the face of changing climate.

Authors: T. Konecny, A. Asatryan, M. Nikoghosyan, H. Binder

Date Published: 6th Sep 2024

Publication Type: Journal

Pan-cancer analysis of telomere maintenance mechanisms.

Abstract (Expand)

Telomeres, protective caps at chromosome ends, maintain genomic stability and control cell lifespan. Dysregulated telomere maintenance mechanisms (TMMs) are cancer hallmarks, enabling unchecked cell … proliferation. We conducted a pan-cancer evaluation of TMM using RNA sequencing data from The Cancer Genome Atlas for 33 different cancer types and analyzed the activities of telomerase-dependent (TEL) and alternative lengthening of telomeres (ALT) TMM pathways in detail. To further characterize the TMM profiles, we categorized the tumors based on their ALT and TEL TMM pathway activities into five major phenotypes: ALT (high) TEL (low), ALT (low) TEL (low), ALT (middle) TEL (middle), ALT (high) TEL (high), and ALT (low) TEL (high). These phenotypes refer to variations in telomere maintenance strategies, shedding light on the heterogeneous nature of telomere regulation in cancer. Moreover, we investigated the clinical implications of TMM phenotypes by examining their associations with clinical characteristics and patient outcomes. Specific TMM profiles were linked to specific survival patterns, emphasizing the potential of TMM profiling as a prognostic indicator and aiding in personalized cancer treatment strategies. Gene ontology analysis of the TMM phenotypes unveiled enriched biological processes associated with cell cycle regulation (both TEL and ALT), DNA replication (TEL), and chromosome dynamics (ALT) showing that telomere maintenance is tightly intertwined with cellular processes governing proliferation and genomic stability. Overall, our study provides an overview of the complexity of transcriptional regulation of telomere maintenance mechanisms in cancer.

Authors: M. Hakobyan, H. Binder, A. Arakelyan

Date Published: 2nd Jul 2024

Publication Type: Journal

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