Biology subjects

Bitler, B. G.

Publications and source records attributed to Bitler, B. G..

At least 19 recordsLinked to original sources

bioRxiv2026

Targeting MAT2A-S-adenosylmethionine (SAM) Axis Attenuates DNA Damage Response and Cancer Stemness to Increase Platinum Sensitivity in Ovarian Cancer

Abstract Metabolic and epigenetic reprogramming drives development of platinum resistance and disease recurrence in high-grade serous ovarian cancer (HGSC), a major clinical challenge in the field. S-adenosylmethionine (SAM) is the universal methyl group donor, synthesized by methionine adenosyltransferase 2A (MAT2A) from methionine. Prior studies have linked altered SAM-dependent DNA methylation to acquired platinum resistance in HGSC, connecting metabolism and epigenetic regulation. However, how MAT2A-driven SAM synthesis coordinates the metabolic-epigenetic remodeling axis to affect platinum sensitivity remains unclear. Here, we report that MAT2A-driven SAM synthesis is required for platinum-induced alterations in DNA methylation and the enrichment of ovarian cancer stem cells (OCSCs). We found that MAT2A upregulation correlated with poor progression-free survival in OC patients, and both pharmacological inhibition and genetic knockdown of MAT2A increased sensitivity to cisplatin. To investigate the underlying epigenetic mechanism, we profiled genome-wide changes in DNA methylation using OVCAR3 treated with cisplatin (15M, 16hr) and/or MAT2A siRNA (48hr), which showed that MAT2A knockdown reversed platinum-induced DNA methylation dynamics. Subsequent analysis revealed enrichment of pathways associated with platinum resistance, DNA repair, and stemness. Mechanistically, inhibiting MAT2A abrogated both the platinum-induced hypermethylation at promoter regions and the SAMTOR-mTOR-S6K-FANCD2 signaling axis, resulting in accumulated R-loops, attenuated DNA repair activation in response to platinum, and enhanced platinum-induced DNA damage and cell death. Using a functional DNA damage reporter assay, we directly showed that MAT2A knockdown reduced DNA repair through homologous recombination (HR) and non-homologous end joining (NHEJ) pathways. By detecting key DNA damage response kinases governing HR and NHEJ signaling, we further demonstrated that MAT2A inhibition abrogated DNA repair activation in response to platinum. Furthermore, single-sample Gene Set Enrichment Analysis of paired primary and recurrent tumors from HGSC patients revealed an association between MAT2A expression and increased OCSC features in recurrent tumors. In vitro, MAT2A inhibition prevented cisplatin-induced enrichment of OCSCs, reduced stemness markers, and inhibited spheroid-forming ability, all of which were rescued by SAM supplementation. Together, our study reveals a previously unrecognized mechanism linking metabolism to epigenetic regulation through platinum-induced remodeling and establishes the MAT2A-SAM axis as a promising therapeutic target to enhance platinum sensitivity by abrogating DNA damage response and OCSC enrichment and ultimately reduce OCSC-driven disease recurrence in HGSC.

cancer biology↗

bioRxiv2026

Cross-assay RNA modeling reveals cancer biomarkers

The clinical heterogeneity of cancer poses a major challenge for precision medicine. Limited cohort sizes across evolving assay platforms impede reliable biomarker discovery. Here, we systematically evaluate how to integrate data from four transcriptomics platforms: bulk and single-cell (sc) RNA sequencing (RNA-seq), NanoString, and microarray for predictive modeling in cancer. We use high-grade serous carcinoma (HGSC) of tube-ovarian origin as a model system, as it is highly heterogeneous in both biology and assay data. We find that using fold-change of gene expression in patients with matched pre- and post-neoadjuvant chemotherapy samples reduces inter-patient and inter-assay variability but is insufficient to overcome platform-specific biases. Microarray and scRNA-seq data exhibit systematic biases, while RNA-seq and NanoString show the most promise for combination into a single training cohort. To mitigate inter-assay limitations, we generate a new data set of HGSC tumor samples profiled with both RNA-seq and NanoString, and use it to identify the limits of detection and optimal harmonization strategies. Our approaches enable integration of cohorts for separate and combined RNA-seq and NanoString predictive models of disease recurrence (test-set AUROCs > 0.8), validated in external microarray cohorts. We leverage single-cell and bulk RNA-seq network-based analyses to provide mechanistic context for genes in the predictive models. Our models indicate that GBP4 expression is a key predictor of recurrence and marks immune remodeling towards cytotoxicity. We provide an interactive web portal to facilitate exploration of data and results. These findings guide cross-assay harmonization of transcriptomic data and enable improved predictive modeling in heterogeneous cancers. Statement of SignificanceWe present a framework for integrating RNA-seq, NanoString, microarray, and single-cell transcriptomic data for predictive modeling, enabling robust biomarker discovery in heterogeneous cancers and identifying GBP4 as a marker of immune remodeling.

bioinformatics↗

bioRxiv2026

On the predictability of progression-free survival in ovarian cancer from NanoString gene expression data

In the treatment of high grade serous ovarian cancer (HGSC), patients initially diagnosed with unresectable tumors are first treated with neoadjuvant chemotherapy (NACT) to reduce tumor burden prior to surgery. Analysis of matched pre- and post-NACT samples from the same patients enables the investigation of chemotherapy impacts and the biomarkers of progression. Although the tumor immune microenvironment (TIME) has increasingly been recognized as critical in shaping the development and progression of HGSC, we lack a comprehensive understanding of how chemotherapy remodels the TIME. Previous studies have found evidence for a general inflammatory response post-NACT, despite inconsistencies regarding which differentially expressed genes and pathways are implicated. We combine matched NanoString gene expression data from multiple sources to create a large dataset of matched pre- and post- NACT samples (N=83, with 29 novel to this study) and investigate reproducibility. Further, we use machine learning methods to investigate whether patient progression-free survival (PFS) can be predicted from the observed impact of chemotherapy on the TIME as represented by the comprehensive set of NanoString features. We find overall low predictability of PFS from all NanoString features, suggesting that previous results may have been limited by small sample size effects and that larger datasets are needed to identify more generalizable and translatable findings. We identify a set of differential expression features that are the most important for predicting patient outcomes that can be validated in future computational and biological studies. Author summaryA subset of patients with high grade serous ovarian cancer are treated with chemotherapy before surgery to reduce tumor burden. We investigate a large dataset of samples taken before and after chemotherapy. These matched samples enable an investigation of how the environment around tumors, for example immune cell infiltration, reacts to chemotherapy, providing insights into biomarkers for treatment response and treatments that could complement chemotherapy. This larger dataset only partially replicates results from previous studies, while also providing new insights. Machine learning models designed to predict the time to patient recurrence from available biomarkers indicate that they are not strongly predictive of patient outcomes, in contrast to past studies. These results suggest that larger datasets are needed. We identify a set of genes that change with chemotherapy and are indicative of and potentially useful for predicting time to disease recurrence and can be further investigated.

cancer biology↗

bioRxiv2026

Transcriptomic subtypes in high-grade serous ovarian cancer are driven by tumor cellular composition

High-grade serous ovarian carcinoma (HGSC) is an aggressive malignancy for which bulk transcriptomic subtypes are used to stratify tumors, interpret biology, and guide biomarker development. The four TCGA-derived subtypes, mesenchymal (C1.MES), immunoreactive (C2.IMM), proliferative (C5.PRO), and differentiated (C4.DIF), are consistently observed across cohorts. However, despite their prominence, these subtypes have not translated into therapeutic utility, and their biological basis remains unresolved. Here, we show that HGSC transcriptomic subtypes are largely determined by tumor cellular composition rather than intrinsic malignant transcriptional programs. By integrating controlled single-cell-derived pseudobulk simulations with deconvolution-based analysis of 1,834 primary HGSC tumors across RNA-seq and microarray cohorts, we demonstrate that subtype probabilities align along a composition-driven axis of stromal and immune variation. Cellular composition alone predicted subtype labels with high accuracy (ROC-AUC = 0.81-0.95) and explained a substantial fraction of subtype-associated transcriptomic variation, with the mesenchymal (C1.MES) subtype representing the most robust and reproducible example of composition-driven signal. Although a secondary, composition-independent expression signal is detectable, it does not define the dominant structure of subtype classification. These findings redefine HGSC transcriptomic subtypes as features of the tumor ecosystem rather than discrete malignant states. This reinterpretation has immediate implications for studies that use subtype labels to infer tumor-intrinsic biology and provides a generalizable framework for separating composition-driven and intrinsic signals in bulk tumor data. Significance StatementHGSC transcriptomic subtypes lack consistent clinical utility and remain biologically ambiguous. We show subtype assignments are largely driven by tumor cellular composition, and less so by distinct intrinsic tumor states.

cancer biology↗

bioRxiv2025

Targeting RAD52 overcomes PARP inhibitor resistance in preclinical Brca2-deficient ovarian cancer model

AbstractBRCA-mutated ovarian cancer commonly develops resistance to poly (ADP-ribose) polymerase (PARP) inhibitors. Here, we investigated the DNA repair protein RAD52 as a potential target to overcome resistance. In analysis of The Cancer Genome Atlas datasets and immunohistochemistry of tissue microarrays, elevated RAD52 expression correlated with poor overall survival in patients with high-grade serous ovarian cancers. We tested two PARP inhibitor-resistant Brca2-deficient mouse ovarian cancer models, ID8-OR and HGS2-OR. HGS2- OR cells had higher RAD52 expression than parental lines. Rad52 knockout or knockdown restored PARP inhibitor sensitivity in both models. In syngeneic mice, ID8-OR cells in which Rad52 was knocked out yielded lower tumor burden and longer overall survival than control cells. Rad52 depletion impaired single-strand annealing and homologous recombination and led to accumulation of DNA double-strand breaks after PARP inhibitor treatment. RNA sequencing demonstrated that PARP inhibitor treatment induced Polq expression in Brca2- and Rad52-deficient cells, suggesting a switch to microhomology-mediated end joining. Finally, the RAD52 inhibitor D-I03 synergized with a PARP inhibitor to reduce cell viability and tumor burden and prolong survival. Collectively, our findings establish RAD52 as a promising therapeutic target to overcome PARP inhibitor resistance in BRCA2-mutated ovarian cancer and offer mechanistic insights to inform future clinical strategies.

cancer biology↗

bioRxiv2025

PARP1 and PARP2 are dispensable for DNA repair by microhomology-mediated end-joining during mitosis.

Poly ADP-ribose polymerase (PARP) inhibitors are standard of care treatment for cancers with homologous-recombination deficiencies. Yet, as tumors develop resistance, complementary strategies are emerging, including targeting microhomology-mediated end joining (MMEJ). Given that PARP1 is widely described as a key promoter of MMEJ, one would expect PARP inhibition to suppress MMEJ--potentially making MMEJ inhibition redundant. MMEJ was originally described as a backup pathway, with seminal work linking PARP1 to MMEJ conducted in NHEJ-deficient cells, where MMEJ can be reactivated in G1. However, we now appreciate that MMEJ is a mitotic repair mechanism, but the function of PARP1 in this context remains unclear. Here, we systematically explore the effect that PARP/PARPi have on MMEJ activity in cells with intact NHEJ. Surprisingly, PARP inhibition leads to elevated Pol{theta}-dependent MMEJ levels at ISceI-mediated DSBs, which we find is due to PARP1s regulation of competing pathways at these breaks. Importantly, we show that PARP is dispensable for MMEJ at double-ended DSBs and is expendable for repair of DSBs during mitosis. Altogether, this data shifts the understanding of PARPs role in MMEJ and DNA repair pathway choice. Moreover, we believe this data further strengthens a rationale for PARPi/MMEJi combinatorial drug treatment in HR-deficient cancers.

molecular biology↗

bioRxiv2024

Cannabidiol promotes apoptosis and downregulation of oncogenic factors

Patients with high-grade serous carcinoma of tubo-ovarian origin (HGSC) often experience significant side effects related to their disease and treatments, such as pain, discomfort, nausea, and vomiting. Over the last two decades, the use of cannabinoids (CBD) to manage pain and anxiety has become more mainstream. However, there is limited data on how CBD interacts with HGSC tumor cells or whether CBD impacts the effect of chemotherapy. Prior preclinical data has suggested the antitumor benefits of cannabinoids; however, the mechanism and data in ovarian cancer are limited. The objectives of this proposed research are to define the endocannabinoid system milieu in ovarian cancer, determine if CBD influences the growth of ovarian cancer cells, measure the cell viability when cannabinoids such as CBD are combined with standard-of-care therapies, and identify potential molecular pathways in which cannabinoids have a therapeutic effect. We conducted publicly available database searches, in vitro proliferation and apoptotic assays, functional protein signaling via reverse phase protein array analysis of CBD-treated cells using 2D cultured cells, and immunohistological analysis of ex vivo cultured patient-derived tumor slices treated with CBD. Our data suggests that CBD is unlikely to affect the growth of cancer cells at physiologic doses but promotes apoptosis and can have growth inhibitory effects at higher concentrations. The inhibitory effects seen at high dose concentrations are likely from the upregulation of apoptotic pathways and inhibition of oncogenic pathways. Overall, physiologic CBD levels have minimal impact on cancer cell growth or chemotherapy efficacy.

cancer biology↗

bioRxiv2024

Ablation of hematopoietic stem cell derived adipocytes reduces tumor burden in syngeneic mouse models of high-grade serous carcinoma

Hematopoietic stem cell-derived adipocytes (HSCDAs) are an adipose subtype derived from myeloid precursors that are distinct from conventional mesenchymal adipocytes (CMAs). We hypothesized that HSCDAs promote high grade serous carcinoma (HGSC), the most common form of ovarian cancer. Despite similar rates of differentiation, primary human HSCDAs from female donors showed marked transcriptional differences from CMAs, including downregulation of cell cycle and upregulation of lipid metabolic pathways. HSCDAs secreted greater amounts of inflammatory cytokines than CMAs. We also conducted two independent tumor studies using ID8 and SO syngeneic HGSC murine models in immunocompetent mice that were either HSCDA Proficient (HSCDA-Pro; can make both adipocyte subtypes) or Deficient (HSCDA-Def; can only make CMAs). Tumor burden trended lower in HSCDA-Def mice in both models. Relative to HSCDA-Pro mice, omental ID8 tumors from HSCDA-Def mice downregulated transcription of multiple metabolic pathways that were enriched in human HSCDA cells in vitro, suggesting that ablation of HSCDAs altered the tumor metabolic environment. Compared to HSCDA-Pro mice, tumors from HSCDA-Def mice had lower densities of dendritic cells (DC) and natural killer (NK) cells, as well as fewer DCs, NKs, and B-cells in proximity to tumor cells. Our data suggest that HSCDAs alter the peritoneal immune and metabolic environment to support HGSC progression. ONE SENTENCE SUMMARYHematopoietic stem cell derived adipocytes may alter the peritoneal metabolic and immune environment to establish a metastatic niche and support ovarian cancer progression.

cancer biology↗

bioRxiv2024

Claudin-4 remodeling of nucleus-cell cycle crosstalk maintains ovarian tumor genome stability and drives resistance to genomic instability-inducing agents.

During cancer development, the interplay between the nucleus and the cell cycle leads to a state of genomic instability, often accompanied by observable morphological aberrations. These aberrations can be controlled by tumor cells to evade cell death, either by preventing or eliminating genomic instability. In epithelial ovarian cancer (EOC), overexpression of the multifunctional protein claudin-4 is a key contributor to therapy resistance through mechanisms associated with genomic instability. However, the molecular mechanisms underlying claudin-4 overexpression in EOC remain poorly understood. Here, we altered claudin-4 expression and employed a unique claudin-4 targeting peptide (CMP) to manipulate the function of claudin-4. We found that claudin-4 facilitates genome maintenance by linking the nuclear envelope and cytoskeleton dynamics with cell cycle progression. Claudin-4 caused nuclei constriction by excluding lamin B1 and promoting perinuclear F-actin accumulation, associated with remodeling nuclear architecture, thus altering nuclear envelope dynamics. Consequently, cell cycle modifications due to claudin-4 overexpression resulted in fewer cells entering the S-phase and reduced genomic instability. Importantly, disrupting biological interactions of claudin-4 using CMP and forskolin altered oxidative stress cellular response and increased the efficacy of PARP inhibitor treatment. Our data indicate that claudin-4 protects tumor genome integrity by remodeling the crosstalk between the nuclei and the cell cycle, leading to resistance to genomic instability formation and the effects of genomic instability-inducing agents. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=122 SRC="FIGDIR/small/611120v1_ufig1.gif" ALT="Figure 1"> View larger version (16K): org.highwire.dtl.DTLVardef@7ed420org.highwire.dtl.DTLVardef@98949eorg.highwire.dtl.DTLVardef@1453a68org.highwire.dtl.DTLVardef@1fdab87_HPS_FORMAT_FIGEXP M_FIG O_FLOATNOGraphical abstractC_FLOATNO Claudin-4 plays a crucial role in remodeling the cytoskeleton, particularly influencing nuclear architecture. This remodeling appears to act as a regulatory mechanism, limiting the progression of ovarian cancer cells into the S-phase and correlating with reduced genomic instability in ovarian tumors. Moreover, since olaparib treatment triggered a cellular oxidative response, it is likely that this claudin-4-mediated remodeling contributes to resistance against the effects of the PARP inhibitor. C_FIG

cancer biology↗

bioRxiv2024

αKG-mediated carnitine synthesis promotes homologous recombination via histone acetylation

Homologous recombination (HR) deficiency enhances sensitivity to DNA damaging agents commonly used to treat cancer. In HR-proficient cancers, metabolic mechanisms driving response or resistance to DNA damaging agents remain unclear. Here we identified that depletion of alpha-ketoglutarate (KG) sensitizes HR-proficient cells to DNA damaging agents by metabolic regulation of histone acetylation. KG is required for the activity of KG-dependent dioxygenases (KGDDs), and prior work has shown that changes in KGDD affect demethylases. Using a targeted CRISPR knockout library consisting of 64 KGDDs, we discovered that Trimethyllysine Hydroxylase Epsilon (TMLHE), the first and rate-limiting enzyme in de novo carnitine synthesis, is necessary for proliferation of HR-proficient cells in the presence of DNA damaging agents. Unexpectedly, KG-mediated TMLHE-dependent carnitine synthesis was required for histone acetylation, while histone methylation was affected but dispensable. The increase in histone acetylation via KG-dependent carnitine synthesis promoted HR-mediated DNA repair through site- and substrate-specific histone acetylation. These data demonstrate for the first time that HR-proficiency is mediated through KG directly influencing histone acetylation via carnitine synthesis and provide a metabolic avenue to induce HR-deficiency and sensitivity to DNA damaging agents.

cancer biology↗

bioRxiv2024

The spatial structure of the tumor immune microenvironment can explain and predict patient response in high-grade serous carcinoma

Despite ovarian cancer being the deadliest gynecological malignancy, there has been little change to therapeutic options and mortality rates over the last three decades. Recent studies indicate that the composition of the tumor immune microenvironment (TIME) influences patient outcomes but are limited by a lack of spatial understanding. We performed multiplexed ion beam imaging (MIBI) on 83 human high-grade serous carcinoma tumors -- one of the largest protein-based, spatially-intact, single-cell resolution tumor datasets assembled -- and used statistical and machine learning approaches to connect features of the TIME spatial organization to patient outcomes. Along with traditional clinical/immunohistochemical attributes and indicators of TIME composition, we found that several features of TIME spatial organization had significant univariate correlations and/or high relative importance in high-dimensional predictive models. The top performing predictive model for patient progression-free survival (PFS) used a combination of TIME composition and spatial features. Results demonstrate the importance of spatial structure in understanding how the TIME contributes to treatment outcomes. Furthermore, the present study provides a generalizable roadmap for spatial analyses of the TIME in ovarian cancer research.

cancer biology↗

bioRxiv2024

Claudin-4 modulates autophagy via SLC1A5/LAT1 as a tolerance mechanism for genomic instability in ovarian cancer.

Genome instability is key for tumor heterogeneity and derives from defects in cell division and DNA damage repair. Tumors show tolerance for this characteristic, but its accumulation is regulated somehow to avoid catastrophic chromosomal alterations and cell death. Claudin-4 is upregulated and closely associated with genome instability and worse patient outcome in ovarian cancer. This protein is commonly described as a junctional protein participating in processes such as cell proliferation and DNA repair. However, its biological association with genomic instability is still poorly-understood. Here, we used CRISPRi and a claudin mimic peptide (CMP) to modulate the cladudin-4 expression and its function, respectively in in-vitro (high-grade serous carcinoma cells) and in-vivo (patient-derived xenograft in a humanized-mice model) systems. We found that claudin-4 promotes a protective cellular-mechanism that links cell-cell junctions to genome integrity. Disruption of this axis leads to irregular cellular connections and cell cycle that results in chromosomal alterations, a phenomenon associated with a novel functional link between claudin-4 and SLC1A5/LAT1 in regulating autophagy. Consequently, claudin-4s disruption increased autophagy and associated with engulfment of cytoplasm-localized DNA. Furthermore, the claudin-4/SLC1A5/LAT1 biological axis correlates with decrease ovarian cancer patient survival and targeting claudin-4 in-vivo with CMP resulted in increased niraparib (PARPi) efficacy, correlating with increased tumoral infiltration of T CD8+ lymphocytes. Our results show that the upregulation of claudin-4 enables a mechanism that promotes tolerance to genomic instability and immune evasion in ovarian cancer; thus, suggesting the potential of claudin-4 as a translational target for enhancing ovarian cancer treatment.

cancer biology↗

bioRxiv2023

Regulation of interferon signaling by transposon exonization

SummaryInnate immune signaling is essential for clearing pathogens and damaged cells, and must be tightly regulated to avoid excessive inflammation or autoimmunity. Here, we found that the alternative splicing of exons derived from transposable elements is a key mechanism controlling immune signaling in human cells. By analyzing long-read transcriptome datasets, we identified numerous transposon exonization events predicted to generate functional protein variants of immune genes, including the type I interferon receptor IFNAR2. We demonstrated that the transposon-derived isoform of IFNAR2 is more highly expressed than the canonical isoform in almost all tissues, and functions as a decoy receptor that potently inhibits interferon signaling including in cells infected with SARS-CoV-2. Our findings uncover a primate-specific axis controlling interferon signaling and show how a transposon exonization event can be co-opted for immune regulation.

genomics↗

bioRxiv2023

Combination CDC-like kinase inhibition (CLK)/Dual-specificity tyrosine-regulated kinase (DYRK) and taxane therapy in CTNNB1-mutated endometrial cancer

SM08502 (cirtuvivint) is a novel pan CDC-like kinase (CLK) and Dual specificity tyrosine kinase (DYRK) inhibitor that targets mRNA splicing and is optimized for Wnt pathway inhibition. Previous evaluation of single agent CLK/DYRK inhibition (SM04690) demonstrated inhibition of tumor progression and {beta}-catenin/TCF transcriptional activity in CTNNB1-mutant endometrial cancer (EC). In-vitro analysis of SM08502 similarly decreases Wnt transcriptional activity and cellular proliferation while increasing cellular apoptosis. SM08502 is an active single-agent therapy with IC50s in the nanomolar range for all EC cell lines evaluated. Combination of SM08502 with paclitaxel has synergistic effect in vitro, as demonstrated by Combination Index <1, and inhibits tumor progression in four endometrial cancer models (HEC265, Ishikawa, Ishikawa-S33Y, and SNGM). In our in vivo mouse models, Ishikawa demonstrated significantly lower tumor volumes of combination vs SM08502 alone (Repeated Measures one-way ANOVA, p = 0.04), but not vs paclitaxel alone. HEC265, SNGM, and Ishikawa-S33Y tumors all had significantly lower tumor volumes with combination SM08502 and paclitaxel compared to single-agent paclitaxel (Repeated Measures one-way ANOVA, p = 0.01, 0.004, and 0.0008, respectively) or single-agent SM08502 (Repeated Measures one-way ANOVA, p = 0.002, 0.005, and 0.01, respectively) alone. Mechanistically, treatment with SM08502 increases alternative splicing (AS) events compared to treatment with paclitaxel. AS regulation is an important post-transcriptional mechanism associated with the oncogenic process in many cancers, including EC. Results from these studies have led to a Phase I evaluation of this combination in recurrent EC.

cancer biology↗

bioRxiv2023

SMASH: Scalable Method for Analyzing Spatial Heterogeneity of genes in spatial transcriptomics data

In high-throughput spatial transcriptomics (ST) studies, it is of great interest to identify the genes whose level of expression in a tissue covaries with the spatial location of cells/spots. Such genes, also known as spatially variable genes (SVGs), can be crucial to the biological understanding of both structural and functional characteristics of complex tissues. Existing methods for detecting SVGs either suffer from huge computational demand or significantly lack statistical power. We propose a non-parametric method termed SMASH that achieves a balance between the above two problems. We compare SMASH with other existing methods in varying simulation scenarios demonstrating its superior statistical power and robustness. We apply the method to four ST datasets from different platforms revealing interesting biological insights.

bioinformatics↗

bioRxiv2023

Combinatory EHMT and PARP inhibition induces an interferon response and a CD8 T cell-dependent tumor regression in PARP inhibitor-resistant models

Euchromatic histone lysine methyltransferases 1 and 2 (EHMT1/2), which catalyze demethylation of histone H3 lysine 9 (H3K9me2), contribute to tumorigenesis and therapy resistance through unknown mechanisms of action. In ovarian cancer, EHMT1/2 and H3K9me2 are directly linked to acquired resistance to poly-ADP-ribose polymerase (PARP) inhibitors and are correlated with poor clinical outcomes. Using a combination of experimental and bioinformatic analyses in several PARP inhibitor resistant ovarian cancer models, we demonstrate that combinatory inhibition of EHMT and PARP is effective in treating PARP inhibitor resistant ovarian cancers. Our in vitro studies show that combinatory therapy reactivates transposable elements, increases immunostimulatory dsRNA formation, and elicits several immune signaling pathways. Our in vivo studies show that both single inhibition of EHMT and combinatory inhibition of EHMT and PARP reduces tumor burden, and that this reduction is dependent on CD8 T cells. Together, our results uncover a direct mechanism by which EHMT inhibition helps to overcome PARP inhibitor resistance and shows how an epigenetic therapy can be used to enhance anti-tumor immunity and address therapy resistance.

cancer biology↗

bioRxiv2022

A Platform-Independent Framework for Phenotyping of Multiplex Tissue Imaging Data

Multiplex imaging is a powerful tool to analyze the structural and functional states of cells in their morphological and pathological contexts. However, hypothesis testing with multiplex imaging data is a challenging task due to the extent and complexity of the information obtained. Various computational pipelines have been developed and validated to extract knowledge from specific imaging platforms. A common problem with customized pipelines is their reduced applicability across different imaging platforms: Every multiplex imaging technique exhibits platform-specific characteristics in terms of signal-to-noise ratio and acquisition artifacts that need to be accounted for to yield reliable and reproducible results. We propose a pixel classifier-based image preprocessing step that aims to minimize platform-dependency for all multiplex image analysis pipelines. Signal detection and noise reduction as well as artifact removal can be posed as a pixel classification problem in which all pixels in multiplex images can be assigned to two general classes of either I) signal of interest or II) artifacts and noise. The resulting feature representation maps contain pixel-accurate representations of the input data, but exhibit signifi-cantly increased signal-to-noise ratios with normalized pixel values as output data. We demonstrate the validity of our proposed image preprocessing approach by comparing the results of two well-accepted and widely-used image analysis pipelines.

bioinformatics↗

bioRxiv2022

WNT4 executes estrogen regulation of cellular metabolism via intracellular activity at the mitochondria

Wnt ligand WNT4 is critical in female reproductive tissue development, with WNT4 dysregulation linked to related pathologies including breast cancer (invasive lobular carcinoma, ILC) and gynecologic cancers. WNT4 signaling in these contexts is distinct from canonical Wnt signaling yet inadequately understood. We previously identified atypical intracellular activity of WNT4 (independent of Wnt secretion) regulating mitochondrial function, and herein examine intracellular functions of WNT4. We further examine how convergent mechanisms of WNT4 dysregulation impact cancer metabolism. In ILC, WNT4 is co-opted by estrogen receptor (ER) via genomic binding in WNT4 intron 1, while in gynecologic cancers, a common genetic polymorphism (rs3820282) at this ER binding site alters WNT4 regulation. Using proximity biotinylation (BioID), we show canonical Wnt ligand WNT3A is trafficked for secretion, but WNT4 is localized to the cytosol and mitochondria. We identified DHRS2, mTOR, and STAT1 as putative WNT4 cytosolic/mitochondrial signaling partners. Whole metabolite profiling, and integrated transcriptomic data, support that WNT4 mediates metabolic reprogramming via fatty acid and amino acid metabolism. Further, ovarian cancer cell lines with rs3820282 variant genotype are WNT4-dependent and have active WNT4 metabolic signaling. In protein array analyses of a cohort of 103 human gynecologic tumors enriched for patient diversity, germline rs3820282 genotype is associated with metabolic remodeling. Variant genotype tumors show increased AMPK activation and downstream signaling, with the highest AMPK signaling activity in variant genotype tumors from non-White patients. Taken together, atypical intracellular WNT4 signaling, in part via genetic dysregulation, regulate the distinct metabolic phenotypes of ILC and gynecologic cancers. SignificanceWNT4 regulates breast and gynecologic cancer metabolism via a previously unappreciated intracellular signaling mechanism at the mitochondria, with WNT4 mediating metabolic remodeling. Understanding WNT4 dysregulation by estrogen and genetic polymorphism offers new opportunities for defining tumor biology, precision therapeutics, and personalized cancer risk assessment.

cancer biology↗