Biology subjects

Polonen, P.

Publications and source records attributed to Polonen, P..

8 recordsLinked to original sources

bioRxiv2026

SOX11 stimulates γδ T-cell differentiation and synergizes with LMO2 and MYCN to drive γδ-like T-cell acute lymphoblastic leukemia

T-cell acute lymphoblastic leukemia (T-ALL) is a heterogeneous hematologic malignancy in which LMO2 {gamma}{delta}-like T-ALL represents a rare but clinically aggressive subtype associated with poor treatment response and inferior survival. Integrated transcriptomic analyses identified high SOX11 expression as a defining feature of high-risk LMO2 {gamma}{delta}-like T-ALL, where elevated SOX11 levels correlated with refractory disease and poor clinical outcome. To investigate the functional role of SOX11 in {gamma}{delta} T-cell biology and leukemogenesis, we generated a conditional R26-SOX11 mouse model enabling lineage-specific SOX11 overexpression in T-cell progenitors. SOX11 expression promoted expansion of the innate {gamma}{delta} T-cell compartment in thymus, spleen, and bone marrow, accompanied by transcriptional activation of {gamma}{delta} T-cell differentiation, activation, and cytotoxicity programs. However, SOX11 overexpression alone was insufficient to induce leukemia or confer thymocyte self-renewal capacity. In contrast, combined SOX11 and LMO2 overexpression markedly accelerated T-ALL development and strongly increased the incidence of {gamma}{delta}-like leukemias, thereby recapitulating the human high-risk LMO2 {gamma}{delta}-like T-ALL subtype. Mechanistically, SOX11 expanded the pre-leukemic DN3 thymocyte compartment in LMO2-driven mouse model while promoting differentiation toward the {gamma}{delta} lineage. Transcriptomic profiling identified activation of MYCN-associated transcriptional programs in SOX11/LMO2 pre-leukemic thymocytes. Consistently, MYCN was highly expressed in human LMO2 {gamma}{delta}-like T-ALL, and recurrent stabilizing MYCN P44L mutations were enriched in this subtype. Functional validation using genetic and transplantation-based mouse models demonstrated that SOX11 cooperates with MYCN to accelerate T-ALL onset. Together, these findings establish a cooperative SOX11-MYCN oncogenic axis driving {gamma}{delta}-like T-ALL and provide a novel preclinical model for investigating therapeutic vulnerabilities in this high-risk leukemia subtype.

cancer biology↗

bioRxiv2026

LDB1-dependent enhancer connectivity defines T-cell leukemia identities and masks metabolic vulnerabilities

Spatial enhancer connectivity is fundamental to proper gene regulation. Enhancer dysregulation has emerged as a hallmark of cancers, including T-cell acute lymphoblastic leukemias (T-ALL). T-ALL are aggressive malignancies characterized by marked transcriptional heterogeneity driven by distinct stages of developmental arrest and diverse noncoding alterations. How these cancers co-opt nuclear architecture to rewire enhancer connectivity remains poorly understood. Here, we report that the LDB1 chromatin architectural complex is an essential mediator of enhancer-oncogene looping that sustains oncogenic transcriptional programs across multiple T-ALL subtypes. Integrating bulk and single-cell transcriptomic data from patients with T-ALL and healthy hematopoietic controls, we show that the LDB1-dependent regulatory circuitry defines the molecular identities of distinct T-ALL subtypes while restricting plasticity toward alternative cell states. LDB1 loss dismantles chromatin looping among cell state-defining enhancers liberating them to form promiscuous interactions with nearby genes. This enhancer rewiring stimulates expression of key metabolic genes, creating a mevalonate pathway dependency exploitable with statin treatment. Our study establishes LDB1 as a central executor of T-ALL regulatory circuitry and more broadly illustrates chromatin rewiring as a source of targetable dependencies in cancer.

Cancer Biology↗

bioRxiv2023

Sequential drug treatment targeting cell cycle and cell fate regulatory programs blocks non-genetic cancer evolution in acute lymphoblastic leukemia

Targeted therapies exploiting vulnerabilities of cancer cells hold promise for improving patient outcome and reducing side-effects of chemotherapy. However, efficacy of precision therapies is limited in part because of the cellular heterogeneity of tumors. A better mechanistic understanding of how drug effect is linked to cancer cell state diversity is crucial for identifying effective combination therapies that can overcome the heterogeneity to prevent disease recurrence. Here, we characterized at the level of gene regulatory networks and at single-cell resolution the effect of G2/M cell cycle checkpoint inhibition in acute lymphoblastic leukemia (ALL) and demonstrate that WEE1 targeted therapy impinges on cell fate decision regulatory circuits. We found highest inhibition of recovery of proliferation in ALL cells with KMT2A-rearrangment (KMT2A-r), compared to cells of other leukemia subgroups. Single-cell transcriptome and chromatin accessibility profiling of (KMT2A::AFF1) RS4;11 cells treated with the WEE1 inhibitor AZD1775 revealed diversification of cell states at the fate decision points, with a fraction of cells exhibiting strong activation of p53-driven processes linked to induction of apoptosis and senescence, and disruption of a core KMT2A-RUNX1-MYC regulatory network through CDK1-mediated RUNX1 degradation. In RS4;11 cells and in patient-derived xenograft (PDX) model, we uncovered that in this cell state diversification induced by WEE1 inhibition, a subpopulation transitioned to a cell state characterized by activation of transcription factors regulating pre-B cell fate, lipid metabolism and pre-BCR signaling which supported a drug tolerance. Sequential treatment targeting the drug tolerant subpopulation with BCR-signaling inhibitors dasatinib, ibrutinib, or perturbing metabolism by fatostatin or AZD2014 after AZD1775 administration, effectively counteracted drug tolerance that drove recovery of leukemic cells. Collectively, our findings provide new insights into the tight connectivity of gene regulatory programs associated with cell cycle and cell fate regulation, and a rationale for sequential administration of WEE1 inhibitors with low toxicity inhibitors of pre-BCR signaling or metabolism.

cancer biology↗

bioRxiv2022

Integrative Analysis of Histological Textures and Lymphocyte Infiltration in Renal Cell Carcinoma using Deep Learning

Evaluating tissue architecture from routine hematoxylin and eosin-stained (H&E) slides is prone to subjectivity and sampling bias. Here, we extensively annotated [~]40,000 images of five tissue texture types and [~]25,000 images of lymphocyte quantity to train deep learning models. We defined histopathological patterns in over 400 clear-cell renal cell carcinoma H&E-stained slides of The Cancer Genome Atlas (TCGA) and resolved sampling and staining differences by harmonizing textural composition. By integrating multi-omic and imaging data, we profiled their clinical, immunological, genomic, and transcriptomic phenotypes. Histological grade, stage, adaptive immunity, the epithelial-to-mesenchymal transition signature and lower mutation burden were more common in stroma-rich samples. Histological proximity between the malignant and normal renal tissues was associated with poor survival, cellular proliferation, tumor heterogeneity, and wild-type PBRM1. This study highlights textural characterization to standardize sampling differences, quantify lymphocyte infiltration and discover novel histopathological associations both in the intratumoral and peritumoral regions.

cancer biology↗

bioRxiv2022

Pan-cancer scale screening reveals NRF2 associated immunoevasive characteristics in non-small cell lung cancer and squamous malignancies

The NRF2 pathway is frequently activated in various cancer types, yet a comprehensive analysis of its effects across different malignancies is currently lacking. We developed a robust NRF2 activity metric and utilized it to conduct a pan-cancer wide analysis of oncogenic NRF2 signaling. We identified a distinct immunoevasive phenotype where high NRF2 activity is associated with low interferon-gamma (IFN{gamma}), HLA-I expression and T-cell infiltration spanning non-small cell lung cancer (NSCLC) and squamous malignancies of head and neck area, cervix and esophagus. In squamous cell cancers, NRF2 overactive tumors comprise a molecular phenotype with SOX2/TP63 amplification, TP53 mutation and CDKN2A loss. These immune-cold NRF2 hyperactive diseases are associated with upregulation of immunomodulatory NAMPT, WNT5A, SPP1, SLC7A11 and SLC2A1 that represent candidate NRF2 target genes, suggesting direct modulation of the tumor immune milieu. Based on single-cell mRNA data, coupled with a priori information on intercellular ligand-receptor interactions, cancer cells of this subtype exhibit decreased expression of IFN{gamma} responsive ligands, and increased expression of immunosuppressive ligands NAMPT, SPP1 and WNT5A that mediate signaling in intercellular crosstalk. As we observed differential cytokine mRNA expression with IFN{gamma} treatment in NSCLC adenocarcinoma subtype, we explored the cytokine secretome in vitro. We found that secreted neutrophil chemoattractants interleukin-8 (CXCL8) and ENA-78 (CXCL5) are elevated in NRF2 overactive cells, suggesting contribution of immunosuppressive neutrophils in NRF2 driven immune escape. Importantly, as overactive NRF2 is associated with immune-cold characteristics, our results highlight the utility of NRF2 pathway activation as a putative biomarker for stratifying immune-checkpoint blockade responders and non-responders across NSCLC and squamous cancers. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=166 SRC="FIGDIR/small/489654v1_ufig1.gif" ALT="Figure 1"> View larger version (46K): org.highwire.dtl.DTLVardef@1f45782org.highwire.dtl.DTLVardef@9d40d0org.highwire.dtl.DTLVardef@a31a5org.highwire.dtl.DTLVardef@1418220_HPS_FORMAT_FIGEXP M_FIG C_FIG

cancer biology↗

bioRxiv2020

Signaling input from divergent pathways subverts malignant B-cell transformation

Malignant transformation typically involves multiple genetic lesions whose combined activity gives rise to cancer1. Our analysis of 1,148 patient-derived B-cell leukemia (B-ALL) samples revealed that individual mutations did not promote leukemogenesis unless they converged on one single oncogenic pathway characteristic for the differentiation status of these transformed B cells. Specifically, we show here the JAK/STAT5 signaling pathway supports the developmental stage-specific expansion of pro-B ALL whereas the ERK-pathway that of pre-B ALL. Mutations that were not aligned with the central oncogenic driver would activate divergent pathways and subvert malignant transformation. Oncogenic lesions in B-ALL frequently mimic survival and proliferation signals downstream of cytokine receptors (through activation of STAT5)2-7 or the pre-B cell receptor (through activation of ERK)8-13. STAT5- (372 cases) and ERK- (386 cases) activating lesions were frequently found but only co-occurred in [~]3% (37) of cases (P=2.2E-16). Single-cell mutation and phosphoprotein analyses revealed that even in these rare cases, oncogenic STAT5- or ERK-activation were mutually exclusive and segregated to competing clones. STAT5 and ERK engaged opposing biochemical and transcriptional programs orchestrated by MYC and BCL6, respectively. Genetic reactivation of the divergent (suppressed) pathway came at the expense of the principal oncogenic driver and reversed malignant transformation. Conversely, Cre-mediated deletion of divergent pathway components triggered leukemia-initiation and accelerated development of fatal disease. Thus, persistence of divergent signaling pathways represents a powerful barrier to malignant transformation while convergence on one principal driver defines a key event during leukemia-initiation. Proof-of-concept studies in patient-derived B-ALL cells revealed that pharmacological reactivation of suppressed divergent circuits strongly synergized with direct inhibition of the principal oncogenic driver. Hence, pharmacological reactivation of divergent pathways can be leveraged as a previously unrecognized strategy to deepen treatment responses and to overcome drug-resistance. Current treatment approaches for drug-resistant cancer are focused on drug-combinations to suppress the central oncogenic driver and multiple alternative pathways14-17. Here, we introduce a concept based on inhibition of the principal driver combined with pharmacological reactivation of divergent pathways.

cancer biology↗

bioRxiv2019

Immunogenomic landscape of hematological malignancies

Understanding factors that shape the immune landscape across hematological malignancies is essential for immunotherapy development. Here, we integrated over 8,000 transcriptomes and over 1,000 samples with multilevel genomic data of hematological cancers to investigate how immunological features are linked to cancer subtypes, genetic and epigenetic alterations, and patient survival. Infiltration of cytotoxic immune cells was associated with distinct microenvironmental responses and driver alterations in different cancers, such as TP53 in acute myeloid leukemia and DTX1 in diffuse large B cell lymphoma. Epigenetic modification of CIITA regulating antigen presentation, cancer type-specific immune checkpoints such as VISTA in myeloid malignancies, and variation in cancer antigen expression further contributed to immune heterogeneity. Prognostic models highlighted the significance of immunological properties in predicting survival. Our study represents the most comprehensive effort to date to link immunology with cancer subtypes and genomics in hematological malignancies, providing a resource to guide future studies and immunotherapy development.

immunology↗

bioRxiv2018

Data-driven characterization of molecular phenotypes across heterogenous sample collections

The existing large gene expression data repositories hold enormous potential to elucidate disease mechanisms, characterize changes in cellular pathways, and to stratify patients based on their molecular profile. To achieve this goal, integrative resources and tools are needed that allow comparison of results across datasets and data types. We propose an intuitive approach for data-driven stratifications of molecular profiles and benchmark our methodology using the dimensional reduction algorithm t-SNE with multi-center and multi-platform data representing hematological malignancies. Our approach enables assessing the contribution of biological versus technical variation to sample clustering, direct incorporation of additional datasets to the same low dimensional representation of molecular disease subtypes, comparison of sample groups between separate t-SNE representations, or maps, and characterization of the obtained clusters based on pathway databases and additional multi-omics data. In the example application, our approach revealed differential activity of SAM-dependent DNA methylation pathway in the acute myeloid leukemia patient cluster characterized with CEBPA mutations that accordingly was validated to have globally elevated DNA methylation levels.

bioinformatics↗