Biology subjects

Kesseli, J.

Publications and source records attributed to Kesseli, J..

7 recordsLinked to original sources

bioRxiv2026

Celiac disease patient derived iPSC small intestinal epithelial cells are more persistent under cytokine stimuli than healthy control cells

Background & AimsCeliac disease is a wheat-induced immune-mediated enteropathy. Intestinal organoid models for adult stem cell-based celiac disease exist, but planar intestinal models derived from celiac disease patients that would allow direct assessment from both sides of the epithelium have been lacking. We aimed to bridge this gap by setting up a two-dimensional in vitro model based on small intestinal epithelial cells (SIECs) derived from induced pluripotent stem cells (iPSC) from celiac disease patients. MethodsIPSCs from celiac disease and control patients were sequentially differentiated towards SIECs. The models applicability was tested under cytokine stimuli. ResultsCeliac disease and control patient iPSCs matured similarly towards SIECs. However, they had inherent gene expression differences in inflammation- and immune-related genes, such as IRF1 and HLA-DRB1. Both iPSC-SIECs responded in a SIEC-specific manner to the cytokine stimulation. The response in celiac disease iPSC-SIECs was attenuated compared with that of control iPSC-SIECs. ConclusionsThe data confirm that iPSC-derived SIECs represent an appropriate platform for studying inflammation-associated enteropathies, such as celiac disease, but also suggest that there might be inherent patient-specific or cell type-specific differences in the responses.

cell biology↗

bioRxiv2026

Hypoxia and Associated Acidosis Generate Cell-Type Specific Myeloid Responses in Glioblastoma

Hypoxia is a defining feature of glioblastoma (GBM), yet how it cooperates with hypoxia-associated acidosis to shape microglia and infiltrating monocyte-derived macrophages (MDM) remains poorly understood. We integrated cyclic immunohistochemistry, single-cell RNA sequencing, spatial transcriptomics, in vitro cell cultures, and DNA methylation profiling to outline hypoxia-driven responses in up to 136 GBMs. These hypoxic niches were selectively enriched for MDMs that activated carbonic anhydrase (CA) mediated pH buffering and other metabolic adaptation programs, enabling survival in acidic hypoxia, increasingly interacted with cancer cells, and show polarization toward immunosuppressive myeloid-derived suppressor cell (MDSC)-like states. In contrast, microglia were depleted in hypoxic areas, lacked compensatory CA isoenzymes, and developed TNF-linked stress responses and loss of homeostatic identity in acidic hypoxia. These findings identify metabolic adaptation to hypoxia-associated microenvironmental stress as a key determinant of GBM immune architecture, driving myeloid cell fates, spatial TME reorganization and the emergence of immunosuppressive tumor ecosystems.

cancer biology↗

bioRxiv2024

Androgen deprivation therapy-resistant club cells are linked to myeloid cell-driven immunosuppression in the prostate tumor microenvironment

Prostate cancer treatment resistance is a significant challenge facing the field. Genomic and transcriptomic profiling have partially elucidated the mechanisms through which cancer cells escape treatment, but their relation toward the tumor microenvironment (TME) remains elusive. Here we present a comprehensive transcriptomic landscape of the prostate TME at multiple points in the standard treatment timeline employing single-cell RNA-sequencing and spatial transcriptomics data from 110 patients. We identify club-like cells as a key epithelial cell subtype that acts as an interface between the prostate and the immune system. Tissue areas enriched with club-like cells have depleted androgen signaling and upregulated expression of luminal progenitor cell markers. Club-like cells display a senescence-associated secretory phenotype and their presence is linked to increased polymorphonuclear myeloid-derived suppressor cell (PMN-MDSC) activity. Our results indicate that club-like cells partake in inducing myeloid inflammation previously associated with androgen deprivation therapy resistance, providing a rationale for their therapeutic targeting.

cancer biology↗

bioRxiv2022

Spatial cumulant models enable spatially informed treatment strategies and analysis of local interactions in cancer systems

Theoretical and applied cancer studies that use individual-based models (IBMs) have been limited by the lack of a mathematical formulation that enables rigorous analysis of these models. However, spatial cumulant models (SCMs), which have arisen from theoretical ecology, describe population dynamics generated by a specific family of IBMs, namely spatio-temporal point processes (STPPs). SCMs are spatially resolved population models formulated by a system of differential equations that approximate the dynamics of two STPP-generated summary statistics: first-order spatial cumulants (densities), and second-order spatial cumulants (spatial covariances). We exemplify how SCMs can be used in mathematical oncology by modelling theoretical cancer cell populations comprising interacting growth factor-producing and non-producing cells. To formulate model equations, we use computational tools that enable the generation of STPPs, SCMs and mean-field population models (MFPMs) from user-defined model descriptions (Cornell et al., 2019). To calculate and compare STPP, SCM and MFPM-generated summary statistics, we develop an application-agnostic computational pipeline. Our results demonstrate that SCMs can capture STPP-generated population density dynamics, even when MFPMs fail to do so. From both MFPM and SCM equations, we derive treatment-induced death rates required to achieve non-growing cell populations. When testing these treatment strategies in STPP-generated cell populations, our results demonstrate that SCM-informed strategies outperform MFPM-informed strategies in terms of inhibiting population growths. We thus demonstrate that SCMs provide a new framework in which to study cell-cell interactions, and can be used to describe and perturb STPP-generated cell population dynamics. We, therefore, argue that SCMs can be used to increase IBMs applicability in cancer research. Statements and DeclarationsThe authors have no competing interests to declare that are relevant to the content of this article.

cancer biology↗

bioRxiv2022

Integrative DNA methylation analysis of pediatric brain tumors reveals tumor type-specific developmental trajectories and epigenetic signatures of malignancy

Atypical teratoid/rhabdoid tumors (AT/RTs) are pediatric brain tumors known for their aggressiveness, exceptionally low mutation rate, and aberrant but still unresolved epigenetic regulation. To evaluate methylation associated regulation in AT/RTs, we compared them to medulloblastomas and choroid plexus tumors by integrating DNA methylation (507 samples), gene expression (120 samples), and public transcription factor (TF) binding data. We showed that elevated DNA methylation masks the binding sites of TFs driving neural development and is associated with reduced transcription for specific neural regulators in AT/RTs. Part of the hypermethylated sites behaved similarly in AT/RTs and pluripotent stem cells, revealing DNA methylation -driven halted cell differentiation. AT/RT-unique DNA hypermethylation was associated with polycomb repressive complex 2 members, like EZH2, and linked to suppressed genes with a role in neural development and tumorigenesis. The obtained results highlight and characterize these DNA methylation programs as drivers of AT/RT malignancy.

cancer biology↗

bioRxiv2022

The transcription factor network of E. coli steers global responses to shifts in RNAP concentration

The robustness and sensitivity of gene networks to environmental changes is critical for cell survival. How gene networks produce specific, chronologically ordered responses to genome-wide perturbations, while robustly maintaining homeostasis, remains an open question. We analysed if short- and mid-term genome-wide responses to shifts in RNA polymerase (RNAP) concentration are influenced by the known topology and logic of the transcription factor network (TFN) of Escherichia coli. We found that, at the gene cohort level, the magnitude of the single-gene, mid-term transcriptional responses to changes in RNAP concentration can be explained by the absolute difference between the genes numbers of activating and repressing input transcription factors (TFs). Interestingly, this difference is strongly positively correlated with the number of input TFs of the gene. Meanwhile, short-term responses showed only weak influence from the TFN. Our results suggest that the global topological traits of the TFN of E. coli shape which gene cohorts respond to genome-wide stresses.

systems biology↗

bioRxiv2020

Chromatin accessibility analysis uncovers regulatory element landscape in prostate cancer progression

Aberrant oncogene functions and structural variation alter the chromatin structure in cancer cells. While gene regulation by chromatin states has been studied extensively, chromatin accessibility and its relevance in aberrant gene expression during prostate cancer progression is not well understood. Here, we report a genome-wide chromatin accessibility analysis of clinical tissue samples of benign prostatic hyperplasia (BPH), untreated primary prostate cancer (PC) and castration-resistant prostate cancer (CRPC) and integrative analysis with transcriptome, methylome, and proteome profiles of the same samples to uncover disease-relevant regulatory elements and their association to altered gene expression during prostate cancer progression. While promoter accessibility is consistent during disease initiation and progression, at distal sites chromatin accessibility is variable enabling transcription factors (TFs) binding patterns that are differently activated in different patients and disease stages. We identify consistent progression-related chromatin alterations during the progression to CRPC. By studying the TF binding patterns, we demonstrate the activation and suppression of androgen receptor-driven regulatory programs during PC progression and identify complementary TF regulatory modules characterized by e.g. MYC and glucocorticoid receptor. By correlation analysis we assign at least one putative regulatory region for 62% of genes and 85% of proteins differentially expressed during prostate cancer progression. Taken together, our analysis of the chromatin landscape in PC identifies putative regulatory elements for the majority of cancer-associated genes and characterizes their impact on the cancer phenotype.

cancer biology↗