Biology subjects

Sikora, M. J.

Publications and source records attributed to Sikora, M. J..

16 recordsLinked to original sources

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

Advanced models of lobular breast cancer metastasis capture clinical organ tropism, endocrine response, and bone remodeling

Patients with invasive lobular carcinoma of the breast (ILC) are at high risk of long-term recurrence and metastatic progression with poor prognoses due to delayed detection and treatment-refractory disease. Unfortunately, few models are available to investigate metastatic ILC (mILC) and understand the unique metastatic patterns and phenotypes, including abdominal metastases, leptomeningeal disease, and mixed osteosclerotic/lytic bone metastases. Therefore, we expanded upon the previously established mammary intraductal (MIND) cell line xenograft model by supplementing mice with low-dose estradiol to promote disease progression. We observed spontaneous multi-organ spread from the mammary gland to common and mILC-specific tissues, with micro-metastatic disease as early as 12 weeks post-engraftment and macro-metastatic disease in 24-30 weeks, without the need for primary tumor resection. Primary and metastatic tumors remain highly endocrine responsive, allowing for the evaluation of novel therapeutics in the setting of disseminated metastasis. Derivative cell lines were isolated from various metastatic lesions, a total of 13 derivates from 7 sites across three hosts, and were found to have shared gene expression changes related to metabolism and intercellular signaling. Focusing on bone-derived variant cells as bone is the most common site for mILC to present, we found that bone-derived variant lines maintain multi-organ metastatic potential upon rechallenge by MIND or intratibial injection, despite increased aggressiveness and maintained endocrine response. Notably, bone lesions from either challenge route showed mixed osteosclerotic/lytic features characteristic to clinical ILC. Accordingly, we found that conditioned medium from ILC cells and the mILC bone-derived variants induce osteoblast differentiation and suppressed osteoclast differentiation in vitro, consistent with their effect on bone remodeling in vivo and in clinical disease. Together, the models developed herein can be utilized to understand the unique metastatic processes of mILC, and to investigate new therapeutic combinations in the setting of endocrine-responsive primary and metastatic ILC.

cancer biology↗

bioRxiv2025

CDH1 loss remodels gene expression and lineage identity in human mammary epithelial cells

Invasive lobular carcinoma (ILC) is a common subtype of breast cancer, molecularly defined by genetic loss of CDH1, and subsequent loss of cell adhesion protein E-cadherin, in [~]95% of ILC. Though CDH1 loss occurs early in ILC oncogenesis, it is unclear how this facilitates transformation. We modeled early CDH1 loss using "normal" human mammary epithelial cells (HMEC), i.e. finite lifespan cells reflecting early hyperplasia, and targeted E-cadherin signaling using antibodies versus causing genetic CDH1 loss using siRNA or CRISPR/Cas9-knockout. Transcriptome analysis across four HMEC models showed that the mode of E-cadherin targeting is critical for the subsequent phenotype. Antibody-mediated inhibition of cell-cell contacts induced gene signatures of epithelial-mesenchymal transition (EMT), consistent with the role of E-cadherin suppression during the EMT process. Conversely, genetic CDH1 loss - as in ILC oncogenesis - repressed EMT signatures, and instead remodeled gene expression toward a luminal epithelial phenotype. RNA-seq, single cell transcriptomics, flow cytometry, microscopy, and ATACseq analyses support that CDH1 loss induces lineage remodeling to a luminal state, which is mirrored in transcriptomic analysis of clinical ILC precursor lesions. By isolating luminal versus basal cells prior to CDH1 knockout, we found that CDH1 loss led to remodeling of lineage identity in both populations, converging on a new lineage homeostasis with a luminal progenitor-like phenotype. Consistent with the shift to a luminal progenitor phenotype, CDH1 loss enhanced proliferative capacity over the finite lifespan of the HMECs, highlighting a feature of early CDH1 loss that may contribute to clonal advantage during tumor initiation. Moreover, CDH1 loss enhanced anoikis resistance, a defining feature of ILC cells. Our findings support that genetic loss of CDH1 in mammary epithelial cells induces transcriptional and phenotypic changes consistent with lineage identity remodeling toward a luminal progenitor-like state, which may underpin the mechanism by which early CDH1 loss mediates ILC oncogenesis.

cancer biology↗

bioRxiv2024

Glutamate Transport Proteins and Metabolic Enzymes are Poor Prognostic Factors in Invasive Lobular Carcinoma

Invasive Lobular Carcinoma (ILC) is a subtype of breast cancer characterized by distinct biological features, and limited glucose uptake coupled with increased reliance on amino acid and lipid metabolism. Our prior studies highlight the importance of glutamate as a key regulator of ILC tumor growth and therapeutic response. Here we examine the expression of four key proteins involved in glutamate transport and metabolism - SLC3A2, SLC7A11, GPX4, and GLUD1/2 - in a racially diverse cohort of 72 estrogen receptor-positive (ER+) ILC and 50 ER+ invasive ductal carcinoma, no special type (IDC/NST) patients with primary disease. All four proteins associate with increased tumor size in ILC, with three showing stronger associations in Black women, but not in IDC/NST. Among these three proteins in ILC, GLUD1/2 uniquely associates with ER expression in all women, while GLUD1/2 and SLC3A2 are enriched in hypertensive women. GLUD1/2 and GPX4 are upregulated in endocrine therapy-resistant ILC cell lines, and pharmacological inhibition of GLUD1 reduces ER protein levels and cell viability. Together, these findings support a potentially important role for glutamate metabolism in ILC and suggest GLUD1 and other glutamate-handling proteins as candidate targets for therapeutic intervention in ILC.

cancer biology↗

bioRxiv2024

EstroGene2.0: A multi-omic database of response to estrogens, ER-modulators, and resistance to endocrine therapies in breast cancer

Endocrine therapies targeting the estrogen receptor (ER/ESR1) are the cornerstone to treat ER-positive breast cancers patients, but resistance often limits their effectiveness. Understanding the molecular mechanisms is thus key to optimize the existing drugs and to develop new ER-modulators. Notable progress has been made although the fragmented way data is reported has reduced their potential impact. Here, we introduce EstroGene2.0, an expanded database of its precursor 1.0 version. EstroGene2.0 focusses on response and resistance to endocrine therapies in breast cancer models. Incorporating multi-omic profiling of 361 experiments from 212 studies across 28 cell lines, a user-friendly browser offers comprehensive data visualization and metadata mining capabilities (https://estrogeneii.web.app/). Taking advantage of the harmonized data collection, our follow-up meta-analysis revealed substantial diversity in response to different classes of ER-modulators including SERMs, SERDs, SERCA and LDD/PROTAC. Notably, endocrine resistant models exhibit a spectrum of transcriptomic alterations including a contra-directional shift in ER and interferon signaling, which is recapitulated clinically. Furthermore, dissecting multiple ESR1-mutant cell models revealed the different clinical relevance of genome-edited versus ectopic overexpression model engineering and identified high-confidence mutant-ER targets, such as NPY1R. These examples demonstrate how EstroGene2.0 helps investigate breast cancers response to endocrine therapies and explore resistance mechanisms.

cancer biology↗

bioRxiv2024

Estrogen regulation and functional role of FGFR4 in estrogen receptor positive breast cancer

BackgroundResistance to endocrine therapy is a major challenge of managing estrogen receptor positive (ER+) breast cancer. We previously reported frequent overexpression of FGFR4 in endocrine resistant cell lines and breast cancers that recurred and metastasized following endocrine therapy, suggesting FGFR4 as a potential driver of endocrine resistance. In this study, we investigated the role of FGFR4 in mediating endocrine resistance and explored the therapeutic potential of targeting FGFR4 in advanced breast cancer. MethodsA gene expression signature of FGFR4 activity was examined in ER+ breast cancer pre- and post-neoadjuvant endocrine therapy and the association between FGFR4 expression and patient survival was examined. A correlation analysis was used to uncover potential regulators of FGFR4 overexpression. To investigate if FGFR4 is necessary to drive endocrine resistance, we tested response to FGFR4 inhibition in long term estrogen deprived (LTED) cells and their paired parental cells. Doxycycline inducible FGFR4 overexpression and knockdown cell models were generated to examine if FGFR4 was sufficient to confer endocrine resistance. Finally, we examined response to FGFR4 monotherapy or combination therapy with fulvestrant in breast cancer cell lines to explore the potential of FGFR4 targeted therapy for advanced breast cancer and assessed the importance of PAM50 subtype in response to FGFR4 inhibition. ResultsA FGFR4 activity gene signature was significantly upregulated post neoadjuvant aromatase inhibitor treatment, and high FGFR4 expression predicted poorer survival in patients with ER+ breast cancer. Gene expression association analysis using TCGA, METABRIC and SCAN-B datasets uncovered ER as the most significant gene negatively correlated with FGFR4 expression. ER negatively regulates FGFR4 expression at both the mRNA and protein level across multiple ER+ breast cancer cell lines. Despite robust overexpression of FGFR4, LTED cells did not show enhanced responses to FGFR4 inhibition compared to parental cells. Similarly, FGFR4 overexpression, knockdown or hotspot mutations did not significantly alter response to endocrine treatment in ER+ cell lines, nor did FGFR4 and fulvestrant combination treatment show synergistic effects. The HER2-like subtype of breast cancer showed elevated expression of FGFR4 and an increased response to FGFR4 inhibition relative to other breast cancer subtypes. ConclusionsDespite ER-mediated upregulation of FGFR4 post endocrine therapy, our study does not support a general role of FGFR4 in mediating endocrine resistance in ER+ breast cancer. Our data suggests that specific genomic backgrounds such as HER2 expression may be required for FGFR4 function in breast cancer and should be further explored.

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↗

bioRxiv2023

Co-regulator activity of Mediator of DNA Damage Checkpoint 1 (MDC1) is associated with DNA repair dysfunction and PARP inhibitor sensitivity in lobular carcinoma of the breast

Invasive lobular carcinoma of the breast (ILC) is typically estrogen receptor (ER)-positive and presents with biomarkers of anti-estrogen sensitive disease, yet patients with ILC face particularly poor long-term outcomes with increased recurrence risk, suggesting endocrine response and ER function are unique in ILC. ER is co- regulated by the DNA repair protein Mediator of DNA Damage Checkpoint 1 (MDC1) specifically in ILC cells, driving distinct ER activity. However, this novel MDC1 activity is associated with dysfunctional canonical DNA repair activity by MDC1, but without typical features of DNA repair deficiency. To understand reciprocal activities of MDC1, we profiled the MDC1 interactome and found MDC1-associated proteins in ILC cells mirror a "BRCA-like" state lacking key homologous recombination (HR) proteins, consistent with HR dysfunction but distinct from classic "BRCAness". HR dysfunction in ILC cells is supported by single-cell transcriptome and DNA repair activity analyses, with DNA repair signaling and functional data, showing dysfunctional induction and resolution of HR. In parallel, ILC tumor data are consistent with a distinct form of HR dysfunction via impaired HR resolution, lacking BRCA-like genomic scarring but showing elevated signatures of PARP inhibitor sensitivity. We demonstrate this HR dysfunction can be exploited using PARP inhibition, and found that talazoparib treatment produced a durable growth suppression both in vitro and in multiple ILC xenografts in vivo. ILC-specific ER:MDC1 activity creates a new context for ER and MDC1 function in ILC, at the cost of a DNA repair dysfunction, which may be therapeutically targetable. SignificanceILC is rarely associated with biomarkers of HR deficiency, and as such patients are rarely eligible for treatment with PARP inhibitors. Our work suggests ILC presents with a previously unappreciated form of HR dysfunction, linked to ILC-specific genomic activity of ER and MDC1, which imparts sensitivity to PARP inhibition.

cancer biology↗

bioRxiv2023

EstroGene database reveals diverse temporal, context-dependent and directional estrogen receptor regulomes in breast cancer

As one of the most successful cancer therapeutic targets, estrogen receptor- (ER/ESR1) has been extensively studied in decade-long. Sequencing technological advances have enabled genome-wide analysis of ER action. However, reproducibility is limited by different experimental design. Here, we established the EstroGene database through centralizing 246 experiments from 136 transcriptomic, cistromic and epigenetic datasets focusing on estradiol-treated ER activation across 19 breast cancer cell lines. We generated a user-friendly browser (https://estrogene.org/) for data visualization and gene inquiry under user-defined experimental conditions and statistical thresholds. Notably, documentation-based meta-analysis revealed a considerable lack of experimental details. Comparison of independent RNA-seq or ER ChIP-seq data with the same design showed large variability and only strong effects could be consistently detected. We defined temporal estrogen response metasignatures and showed the association with specific transcriptional factors, chromatin accessibility and ER heterogeneity. Unexpectedly, harmonizing 146 transcriptomic analyses uncovered a subset of E2-bidirectionally regulated genes, which linked to immune surveillance in the clinical setting. Furthermore, we defined context dependent E2 response programs in MCF7 and T47D cell lines, the two most frequently used models in the field. Collectively, the EstroGene database provides an informative resource to the cancer research community and reveals a diverse mode of ER signaling.

cancer biology↗

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↗

bioRxiv2020

Mediator of DNA damage checkpoint 1 (MDC1) is a novel estrogen receptor co-regulator in invasive lobular carcinoma of the breast

Invasive lobular carcinoma (ILC) is the most common histological subtype of breast cancer, and nearly all ILC tumors express estrogen receptor alpha (ER). However, clinical and laboratory data suggest ILC are strongly estrogen-driven but not equally sensitive to anti-estrogen therapies. We hypothesized that ILC-specific ER transcriptional co-regulators mediate ER functions in ILC and anti-estrogen resistance, and profiled ER-associated proteins by mass spectrometry. Three ER+ ILC cell lines, MDA MB 134VI, SUM44PE, and BCK4, were compared to published data from ER+ invasive ductal carcinoma (IDC) cell lines, and we examined whether siRNA knockdown of identified proteins suppressed ER-driven proliferation in ILC cells. This approach found mediator of DNA damage checkpoint 1 (MDC1), a key tumor suppressor in DNA damage response (DDR), as a putative novel ER co-regulator in ILC. We confirmed ER:MDC1 interaction was specific to ILC cell lines versus IDC cells, and found MDC1 knockdown suppressed ILC cell proliferation and suppressed tamoxifen resistance in MDA MB 134VI. Using RNA-sequencing, we found that in ILC cells, MDC1 knockdown broadly dysregulates the estrogen-driven ER transcriptome, with ER:MDC1 target genes enriched for hormone-response-elements in their promoter regions. Importantly, our data are inconsistent with MDC1 regulating ER via MDC1 DDR and tumor suppressor functions, but instead suggest a novel oncogenic role for MDC1 in mediating ER transcriptional activity as a co-regulator. Supporting this, in breast tumor tissue microarrays MDC1 protein was frequently low or absent in IDC or ER-ILC, but MDC1 loss is rare in ER+ ILC. ER:MDC1 interaction and MDC1 co-regulator functions may underlie cell type-specific ER functions in ILC, and serve as important biomarkers and therapeutic targets to overcome anti-estrogen resistance in ILC.

cancer biology↗

bioRxiv2020

The capacity of the ovarian cancer tumor microenvironment to integrate inflammation signaling conveys a shorter disease-free interval

Ovarian cancer has one of the highest deaths to incidence ratios across all cancers. Initial chemotherapy is typically effective, but most patients will develop chemo-resistant disease. Mechanisms driving clinical chemo-response and -resistance in ovarian cancer are not well understood. However, achieving optimal surgical cytoreduction improves survival, and cytoreduction is improved by neoadjuvant platinum/taxane-based chemotherapy (NACT). NACT offers a window to profile pre-versus post-therapy tumor specimens, which we used to identify chemotherapy-induced changes to the tumor microenvironment. We hypothesized changes in the immune microenvironment correlate with tumor chemo-response and disease progression. We obtained matched pre- and post-NACT archival tumor tissues from patients with high-grade serous ovarian cancer (patient n=6). We measured mRNA levels of 770 genes (NanoString), and performed reverse phase protein array (RPPA) on a subset of matched tumors. We examined cytokine levels in additional pre-NACT ascites samples (n=39) by multiplex ELISA. A tissue microarray with 128 annotated ovarian tumors expanded the transcriptional, RPPA, and cytokine data by multi-spectral immunohistochemistry. In NanoString analyses, transcriptional profiles segregated based on pre- and post-NACT status. The most upregulated gene post-NACT was IL6 (17.1-fold, adjusted p = 0.045). RPPA data were highly concordant with mRNA, consistent with elevated immune infiltration. Elevated IL-6 in pre-NACT ascites specimens correlated with a shorter time to recurrence. Integrating NanoString, RPPA, and cytokine studies identified an activated inflammatory signaling network and induced IL6 and IER3 (Immediate Early Response 3) post-NACT, associated with poor chemo-response and decreased time to recurrence. Taken together, multi-omic profiling of ovarian tumor samples before and after NACT provides unique insight into chemo-induced changes to the tumor and microenvironment. We integrated transcriptional, proteomic, and cytokine data and identified a novel IL-6/IER3 signaling axis through increased inflammatory signaling which may drive ovarian cancer chemo-resistance.

cancer biology↗

bioRxiv2019

Estrogen controls mTOR signaling and mitochondrial function via WNT4 in lobular carcinoma

Invasive lobular carcinoma of the breast (ILC) is strongly estrogen-driven and represents a unique context for estrogen receptor (ER) signaling. In ILC, ER controls the expression of the Wnt ligand WNT4, which is critical for endocrine response and anti-estrogen resistance. However, signaling mediated by WNT4 is poorly understood. We utilized reverse phase protein array (RPPA) to characterize ER and WNT4-driven signaling in ILC cells and identified that WNT4 mediates downstream mTOR signaling via S6K. Additionally, independent of mTOR/S6K, ER and WNT4 control levels of MCL-1, which alters mitochondrial function. In this context, WNT4 knockdown caused decreased ATP production and increased mitochondrial fragmentation. WNT4 regulation of both mTOR signaling and MCL-1 were also observed in antiestrogen resistant models of ILC. Further, we identified that high WNT4 expression is associated with similar mTOR pathway activation in serous ovarian cancer tumors, suggesting that WNT4 signaling is important in multiple tumor types. The identified downstream pathways offer insight in to WNT4 signaling and represent potential targets to overcome anti-estrogen resistance for patients with ILC.

cancer biology↗

bioRxiv2018

Targeting Wnt Signaling To Overcome PARP Inhibitor Resistance

Epithelial ovarian cancer (EOC) has one of the highest deaths to incidence ratios. High grade serous ovarian carcinoma (HGSOC) is the most common and deadliest EOC histotype because of the lack of secondary therapeutic options following debulking surgery and platinum/taxane-based chemotherapies. For recurrent chemosensitive HGSOC, poly(ADP)-ribose polymerase inhibitors (PARPi; olaparib, rucaparib, or niraparib) represent an emerging treatment strategy. While PARPi are most effective in homologous recombination DNA repair-deficient (HRD) HGSOCs, more recent studies have observed a significant clinical benefit in non-HRD HGSOCs. However, all HGSOC patients are likely to acquire resistance to PARPi. Therefore, there is an urgent clinical need to better understand PARPi resistance, and to introduce novel combinatorial therapies to overcome PARPi resistance and extend HGSOC disease-free intervals. Utilizing a two BRCA2-mutated and one BRCA-wildtype HGSOC cell lines that are olaparib sensitive, we established resistant cells. Transcriptome analysis of the matched olaparib-sensitive versus resistant cells did not detect BRCA2 reversion mutations, but revealed activation of Wnt/TCF signaling pathway, as TCF transcriptional activity was significantly increased in PARPi-resistant cells. In parallel, forced activation of Wnt signaling in PARPi-sensitive cells via WNT3A stimulation reduced response to PARPi. In a recurrent-HGSOC PARPi insensitive patient-derived xenograft model there was an increase in a Wnt/TCF transcriptional target. PARPi resistant cells were sensitive to inhibition of Wnt signaling using the FDA-approved compound, pyrvinium pamoate, which has been shown to inhibit Wnt signaling. We observed that combining pyrvinium pamoate with olaparib resulted in a significant decrease in tumor burden and number of tumor nodules. This study demonstrates that Wnt signaling can mediate PARPi resistance in HGSOC and provides a clinical rationale for combining PARPi and Wnt inhibitors.

cancer biology↗

bioRxiv2018

WNT4 and WNT3A activate cell autonomous Wnt signaling independent of secretion

The enzyme PORCN is considered essential for Wnt secretion and signaling, however, we observed PORCN inhibition did not phenocopy the effects of WNT4 knockdown in WNT4-dependent breast cancer cells. This suggests a unique relationship between PORCN and WNT4 signaling. To examine the role of PORCN in WNT4 signaling, WNT4 or WNT3A were over-expressed in breast and ovarian cancer, and fibrosarcoma cell lines. Conditioned medium from these lines, and co-culture systems, were used to assess the dependence of Wnt secretion and activity on critical Wnt secretion proteins PORCN and WLS. We observed that WLS was universally required for Wnt secretion and paracrine signaling. In contrast, the dependence of WNT3A secretion and activity on PORCN varied across cell lines, and WNT4 secretion was PORCN-independent in all models. Surprisingly, WNT4 did not present paracrine activity in any tested context. Absent the expected paracrine activity of secreted WNT4, we identified cell autonomous Wnt signaling activation by WNT4 and WNT3A, independent of PORCN or secretion. The PORCN-independent, cell-autonomous Wnt signaling demonstrated herein may be critical in WNT4-driven cellular contexts, or those that are otherwise considered to have dysfunctional Wnt signaling.\n\nSummary StatementWnt proteins can mediate an atypical mode of cell-autonomous signaling, distinct from paracrine signaling, that is independent of both palmitoylation by PORCN and Wnt secretion.

cell biology↗