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

Ovarian cancer is the deadliest gynecological malignancy, and therapeutic options and mortality rates over the last three decades have largely not changed. Recent studies indicate that the composition of the tumor immune microenvironment (TIME) influences patient outcomes. To improve spatial understanding of the TIME, we performed multiplexed ion beam imaging on 83 human high-grade serous carcinoma tumor samples, identifying about 160,000 cells across 23 cell types. For 77 of these samples meeting inclusion criteria, we generated composition features based on cell type proportions, spatial features based on the distances between cell types, and spatial network features representing cell interactions and cell clustering patterns, which we linked to traditional clinical and immunohistochemical variables and patient overall survival (OS) and progression-free survival (PFS) outcomes. Among these features, we found several significant univariate correlations, including B-cell contact with M1 macrophages (OS hazard ratio HR=0.696, p=0.011, PFS HR=0.734, p=0.039). We then used high-dimensional random forest models to evaluate out-of-sample predictive performance for OS and PFS outcomes and to derive relative feature importance scores for each feature. The top model for predicting low or high PFS used TIME composition and spatial features and achieved an average AUC (area under the receiver-operating characteristic curve) score of 0.71. The 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.

International survey on invasive lobular breast cancer identifies priority research questions.

There is growing awareness of the unique etiology, biology, and clinical presentation of invasive lobular breast cancer (ILC), but additional research is needed to ensure translation of findings into management and treatment guidelines. We conducted a survey with input from breast cancer physicians, laboratory-based researchers, and patients to analyze the current understanding of ILC, and identify consensus research questions. 1774 participants from 66 countries respondents self-identified as clinicians (N = 413), researchers (N = 376), and breast cancer patients and advocates (N = 1120), with some belonging to more than one category. The majority of physicians reported being very/extremely (41%) to moderately (42%) confident in describing the differences between ILC and invasive breast cancer of no special type (NST). Knowledge of histology was seen as important (73%) and as affecting treatment decisions (51%), and most agreed that refining treatment guidelines would be valuable (76%). 85% of clinicians have never powered a clinical trial to allow subset analysis for histological subtypes, but the majority would consider it, and would participate in an ILC clinical trials consortium. The majority of laboratory researchers, reported being and very/extremely (48%) to moderately (29%) confident in describing differences between ILC and NST. They reported that ILCs are inadequately presented in large genomic data sets, and that ILC models are insufficient. The majority have adequate access to tissue or blood from patients with ILC. The majority of patients and advocates (52%) thought that their health care providers did not sufficiently explain the unique features of ILC. They identified improvement of ILC screening/early detection, and identification of better imaging tools as top research priorities. In contrast, both researchers and clinicians identified understanding of endocrine resistance and identifying novel drugs that can be tested in clinical trials as top research priority. In summary, we have gathered information from an international community of physicians, researchers, and patients/advocates that we expect will lay the foundation for a community-informed collaborative research agenda, with the goal of improving management and personalizing treatment for patients with ILC.

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 cancer's response to endocrine therapies and explore resistance mechanisms.

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.

WNT4 Regulates Cellular Metabolism via Intracellular Activity at the Mitochondria in Breast and Gynecologic Cancers.

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 α (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. Furthermore, 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, regulates the distinct metabolic phenotypes of ILC and gynecologic cancers. SIGNIFICANCE: WNT4 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.

The EstroGene Database Reveals Diverse Temporal, Context-Dependent, and Bidirectional Estrogen Receptor Regulomes in Breast Cancer.

As one of the most successful cancer therapeutic targets, estrogen receptor-α (ER/ESR1) has been extensively studied over the past few decades. Sequencing technological advances have enabled genome-wide analysis of ER action. However, comparison of individual studies is limited by different experimental designs, and few meta-analyses are available. Here, we established the EstroGene database through unified processing of data from 246 experiments including 136 transcriptomic, cistromic, and epigenetic datasets focusing on estradiol (E2)-triggered ER activation across 19 breast cancer cell lines. A user-friendly browser (https://estrogene.org/) was generated for multiomic data visualization involving gene inquiry under user-defined experimental conditions and statistical thresholds. Notably, annotation of metadata associated with public datasets 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. Temporal estrogen response metasignatures were defined, and the association of E2 response rate with temporal transcriptional factors, chromatin accessibility, and heterogeneity of ER expression was evaluated. Unexpectedly, harmonizing 146 E2-induced transcriptomic datasets uncovered a subset of genes harboring bidirectional E2 regulation, which was linked to unique transcriptional factors and highly associated with immune surveillance in the clinical setting. Furthermore, the context dependent E2 response programs were characterized in MCF7 and T47D cell lines, the two most frequently used models in the EstroGene database. Collectively, the EstroGene database provides an informative and practical resource to the cancer research community to uniformly evaluate key reproducible features of ER regulomes and unravels modes of ER signaling. SIGNIFICANCE: A resource database integrating 246 publicly available ER profiling datasets facilitates meta-analyses and identifies estrogen response temporal signatures, a bidirectional program, and model-specific biases.

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-α (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.

Mutual exclusivity of ESR1 and TP53 mutations in endocrine resistant metastatic breast cancer.

Both TP53 and ESR1 mutations occur frequently in estrogen receptor positive (ER+) metastatic breast cancers (MBC) and their distinct roles in breast cancer tumorigenesis and progression are well appreciated. Recent clinical studies discovered mutual exclusivity between TP53 and ESR1 mutations in metastatic breast cancers; however, mechanisms underlying this intriguing clinical observation remain largely understudied and unknown. Here, we explored the interplay between TP53 and ESR1 mutations using publicly available clinical and experimental data sets. We first confirmed the robust mutational exclusivity using six independent cohorts with 1,056 ER+ MBC samples and found that the exclusivity broadly applies to all ER+ breast tumors regardless of their clinical and distinct mutational features. ESR1 mutant tumors do not exhibit differential p53 pathway activity, whereas we identified attenuated ER activity and expression in TP53 mutant tumors, driven by a p53-associated E2 response gene signature. Further, 81% of these p53-associated E2 response genes are either direct targets of wild-type (WT) p53-regulated transactivation or are mutant p53-associated microRNAs, representing bimodal mechanisms of ER suppression. Lastly, we analyzed the very rare cases with co-occurrences of TP53 and ESR1 mutations and found that their simultaneous presence was also associated with reduced ER activity. In addition, tumors with dual mutations showed higher levels of total and PD-L1 positive macrophages. In summary, our study utilized multiple publicly available sources to explore the mechanism underlying the mutual exclusivity between ESR1 and TP53 mutations, providing further insights and testable hypotheses of the molecular interplay between these two pivotal genes in ER+ MBC.

Unlocking the Mysteries of Lobular Breast Cancer Biology Needs the Right Combination of Preclinical Models.

Preclinical model systems are essential research tools that help us understand the biology of invasive lobular carcinoma of the breast (ILC). The number of well-established ILC models is increasing but remain limited. Lower incidence of ILC, underrepresentation of patients with ILC in clinical trials, and intrinsic ILC tumor characteristics all contribute to this challenge. Hence, there is significant need to continually develop better model systems to recapitulate the essential characteristics of ILC biology, genetics, and histology, and empower preclinical therapeutic studies to be translated back into the clinic. In this Perspective, we highlight recent advances in in vivo experimental models, which recapitulate key features of ILC biology and disease progression and potentially reshape the future of ILC translational research. We assert that all existing in vitro and in vivo ILC preclinical models have their strengths and weaknesses, and that it is necessary to bridge key deficiencies in each model context as we move forward with ILC research. Thus, unlocking the mysteries of ILC will be best achieved by choosing the right combination of preclinical model systems.

Mediator of DNA Damage Checkpoint 1 (MDC1) Is a Novel Estrogen Receptor Coregulator in Invasive Lobular Carcinoma of the Breast.

Invasive lobular carcinoma (ILC) is the most common special histologic 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 antiestrogen-sensitive. We hypothesized ILC-specific ER coregulators mediate ER functions and antiestrogen resistance in ILC, and profiled ER-associated proteins by mass spectrometry. Three ER+ ILC cell lines (MDA MB 134VI, SUM44PE, and BCK4) were compared with ER+ invasive ductal carcinoma (IDC) line data, and we examined whether siRNA of identified proteins suppressed ER-driven proliferation in ILC cells. This identified mediator of DNA damage checkpoint 1 (MDC1), a tumor suppressor in DNA damage response (DDR), as a novel ER coregulator in ILC. We confirmed ER:MDC1 interaction was specific to ILC versus IDC cells, and found MDC1 knockdown suppressed ILC cell proliferation and tamoxifen resistance. Using RNA-sequencing, we found in ILC cells MDC1 knockdown broadly dysregulates the ER transcriptome, with ER:MDC1 target genes enriched for promoter hormone response elements. Importantly, our data are inconsistent with MDC1 tumor suppressor functions in DDR, but suggest a novel oncogenic role for MDC1 as an ER coregulator. Supporting this, in breast tumor tissue microarrays, MDC1 protein was frequently low or absent in IDC, but MDC1 loss was rare in ER+ ILC. ER:MDC1 interaction and MDC1 coregulator functions may underlie ER function in ILC and serve as targets to overcome antiestrogen resistance in ILC. IMPLICATIONS: MDC1 has novel ER coregulator activity in ILC, which may underlie ILC-specific ER functions, estrogen response, and antiestrogen resistance.

WNT4 Balances Development vs Disease in Gynecologic Tissues and Women's Health.

The WNT family of proteins is crucial in numerous developmental pathways and tissue homeostasis. WNT4, in particular, is uniquely implicated in the development of the female phenotype in the fetus, and in the maintenance of müllerian and reproductive tissues. WNT4 dysfunction or dysregulation can drive sex-reversal syndromes, highlighting the key role of WNT4 in sex determination. WNT4 is also critical in gynecologic pathologies later in life, including several cancers, uterine fibroids, endometriosis, and infertility. The role of WNT4 in normal decidualization, implantation, and gestation is being increasingly appreciated, while aberrant activation of WNT4 signaling is being linked both to gynecologic and breast cancers. Notably, single-nucleotide polymorphisms (SNPs) at the WNT4 gene locus are strongly associated with these pathologies and may functionally link estrogen and estrogen receptor signaling to upregulation and activation of WNT4 signaling. Importantly, in each of these developmental and disease states, WNT4 gene expression and downstream WNT4 signaling are regulated and executed by myriad tissue-specific pathways. Here, we review the roles of WNT4 in women's health with a focus on sex development, and gynecologic and breast pathologies, and our understanding of how WNT4 signaling is controlled in these contexts. Defining WNT4 functions provides a unique opportunity to link sex-specific signaling pathways to women's health and disease.

Making an IMPACT on career development for early- and mid-career faculty.

Nuclear receptors are critically important in normal and disease physiology. Recent advances have created opportunities to expand our success in nuclear receptor (NR) basic and translational research, but this field lacks a platform to lay the collaborative groundwork for aspiring and upcoming leaders in the field. Nuclear Receptor IMPACT (Interdisciplinary Meeting for Progress And Collaboration Together) is a new collaborative group designed specifically for early- and mid-career faculty who study nuclear receptors in their many forms. A unique goal of NR IMPACT is to also directly address career challenges for early- and mid-career faculty. NR IMPACT held an inaugural conference in September 2020 and developed a roadmap identifying five major structural and science policy challenges facing early- and mid-career faculty. NR IMPACT identified potential best practices, resources needed, and key action items to address these issues. NR IMPACT is a first-of-its-kind cohort dedicated to building a foundation for the scientific and professional growth of investigators studying nuclear receptors, and supporting new collaborations that will advance new paradigms in NR biology. Our unique focus on career development will enhance the success of current faculty and remove hurdles for new faculty, creating a robust pipeline of investigators with exciting new ideas to advance NR biology. The growth of NR IMPACT will build a strong peer-mentoring cohort that can be a unique resource for researchers and a prototype peer group for other disciplines.

Estrogen Regulation of mTOR Signaling and Mitochondrial Function in Invasive Lobular Carcinoma Cell Lines Requires WNT4.

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 cell type- and tissue-specific, and has not been explored in ILC. 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 phosphorylation of S6 Kinase. Additionally, ER and WNT4 control levels of MCL-1, which is associated with regulation of mitochondrial function. In this context, WNT4 knockdown led to decreased ATP production and increased mitochondrial fragmentation. WNT4 regulation of both mTOR signaling and MCL-1 were also observed in anti-estrogen resistant models of ILC. We identified that high WNT4 expression is associated with similar mTOR pathway activation in ILC and serous ovarian cancer tumors, suggesting that WNT4 signaling is active in multiple tumor types. The identified downstream pathways offer insight into WNT4 signaling and represent potential targets to overcome anti-estrogen resistance for patients with ILC.

The Capacity of the Ovarian Cancer Tumor Microenvironment to Integrate Inflammation Signaling Conveys a Shorter Disease-free Interval.

PURPOSE: Ovarian cancer has one of the highest deaths to incidence ratios across all cancers. Initial chemotherapy is effective, but most patients develop chemoresistant disease. Mechanisms driving clinical chemo-response or -resistance are not well-understood. However, achieving optimal surgical cytoreduction improves survival, and cytoreduction is improved by neoadjuvant chemotherapy (NACT). NACT offers a window to profile pre- versus post-NACT tumors, which we used to identify chemotherapy-induced changes to the tumor microenvironment. EXPERIMENTAL DESIGN: 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 (756 genes/14 housekeeping genes, NanoString Technologies), and performed reverse phase protein array (RPPA) on a subset of matched tumors. We examined cytokine levels in pre-NACT ascites samples (n = 39) by ELISAs. A tissue microarray with 128 annotated ovarian tumors expanded the transcriptional, RPPA, and cytokine data by multispectral IHC. RESULTS: The most upregulated gene post-NACT was IL6 (16.79-fold). RPPA data were concordant with mRNA, consistent with elevated immune infiltration. Elevated IL6 in pre-NACT ascites specimens correlated with a shorter time to recurrence. Integrating NanoString (n = 12), RPPA (n = 4), and cytokine (n = 39) studies identified an activated inflammatory signaling network and induced IL6 and IER3 (immediate early response 3) post-NACT, associated with poor chemo-response and time to recurrence. CONCLUSIONS: Multiomics profiling of ovarian tumor samples pre- and post-NACT provides unique insight into chemo-induced changes to the tumor microenvironment. We identified a novel IL6/IER3 signaling axis that may drive chemoresistance and disease recurrence.

Differential Regulation and Targeting of Estrogen Receptor α Turnover in Invasive Lobular Breast Carcinoma.

Invasive lobular breast carcinoma (ILC) accounts for 10% to 15% of breast cancers diagnosed annually. Evidence suggests that some aspects of endocrine treatment response might differ between invasive ductal carcinoma (IDC) and ILC, and that patients with ILC have worse long-term survival. We analyzed The Cancer Genome Atlas dataset and observed lower levels of ESR1 mRNA (P = 0.002) and ERα protein (P = 0.038) in ER+ ILC (n = 137) compared to IDC (n = 554), and further confirmed the mRNA difference in a local UPMC cohort (ILC, n = 143; IDC, n = 877; P < 0.005). In both datasets, the correlation between ESR1 mRNA and ERα protein was weaker in ILC, suggesting differential post-transcriptional regulation of ERα. In vitro, 17ß-estradiol (E2) decreased the rate of degradation and increased the half-life of ERα in ILC cell lines, whereas the opposite was observed in IDC cell lines. Further, E2 failed to induce robust ubiquitination of ERα in ILC cells. To determine the potential clinical relevance of these findings, we evaluated the effect of 2 selective estrogen receptor downregulators (SERDs), ICI 182,780 and AZD9496, on ERα turnover and cell growth. While ICI 182,780 and AZD9496 showed similar effects in IDC cells, in ILC cell lines, AZD9496 was not as effective as ICI 182,780 in decreasing ERα stability and E2-induced proliferation. Furthermore, AZD9496 exhibited partial agonist activity in growth assays in ILC cell lines. Our study provides evidence for a distinct ERα regulation by SERDs in ILC cell lines, and therefore it is important to include ILC models into preclinical and clinical testing of novel SERDs.

Wnt family member 4 (WNT4) and WNT3A activate cell-autonomous Wnt signaling independent of porcupine O-acyltransferase or Wnt secretion.

Porcupine O-acyltransferase (PORCN) is considered essential for Wnt secretion and signaling. However, we observed that PORCN inhibition does 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, here we overexpressed WNT4 or WNT3A in breast cancer, ovarian cancer, and fibrosarcoma cell lines. Conditioned media from these lines and co-culture systems were used to assess the dependence of Wnt secretion and activity on the critical Wnt secretion proteins PORCN and Wnt ligand secretion (WLS) mediator. We observed that WLS is universally required for Wnt secretion and paracrine signaling. In contrast, the dependence of WNT3A secretion and activity on PORCN varied across the cell lines, and WNT4 secretion was PORCN-independent in all models. Surprisingly, WNT4 did not exhibit 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 Wnt secretion. The PORCN-independent, cell-autonomous Wnt signaling demonstrated here may be critical in WNT4-driven cellular contexts or in those that are considered to have dysfunctional Wnt signaling.

FGFR4 overexpression and hotspot mutations in metastatic ER+ breast cancer are enriched in the lobular subtype.

Invasive lobular carcinoma (ILC) is an understudied subtype of breast cancer that requires novel therapies in the advanced setting. To study acquired resistance to endocrine therapy in ILC, we have recently performed RNA-Sequencing on long-term estrogen deprived cell lines and identified FGFR4 overexpression as a top druggable target. Here, we show that FGFR4 expression also increases dramatically in endocrine-treated distant metastases, with an average fold change of 4.8 relative to the paired primary breast tumor for ILC, and 2.4-fold for invasive ductal carcinoma (IDC). In addition, we now report that FGFR4 hotspot mutations are enriched in metastatic breast cancer, with an additional enrichment for ILC, suggesting a multimodal selection of FGFR4 activation. These data collectively support the notion that FGFR4 is an important mediator of endocrine resistance in ILC, warranting future mechanistic studies on downstream signaling of overexpressed wild-type and mutant FGFR4.

Activation of Wnt signaling promotes olaparib resistant ovarian cancer.

Epithelial ovarian cancer (EOC) has one of the highest death to incidence ratios among all cancers. High grade serous ovarian carcinoma (HGSOC) is the most common and deadliest EOC histotype due to the lack of 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, recent studies have observed a significant benefit in non-HRD HGSOCs. However, all HGSOC patients are likely to acquire resistance. Therefore, there is an urgent clinical need to understand PARPi resistance and to introduce novel combinatorial therapies to manage PARPi resistance and extend HGSOC disease-free intervals. In a panel of HGSOC cell lines, we established matched olaparib sensitive and resistant cells. Transcriptome analysis of the matched olaparib-sensitive vs -resistant cells revealed activation of the Wnt signaling pathway and consequently increased TCF transcriptional activity in PARPi-resistant cells. Forced activation of canonical Wnt signaling in several PARPi-sensitive cells via WNT3A reduced olaparib and rucaparib sensitivity. PARPi resistant cells were sensitive to inhibition of Wnt signaling using the FDA-approved compound, pyrvinium pamoate, which has been shown to promote downregulation of ß-catenin. In both an HGSOC cell line and a patient-derived xenograft model, we observed that combining pyrvinium pamoate with olaparib resulted in a significant decrease in tumor burden. This study demonstrates that Wnt signaling can mediate PARPi resistance in HGSOC and provides a clinical rationale for combining PARP and Wnt inhibitors.

Frequent amplifications of ESR1, ERBB2 and MDM4 in primary invasive lobular breast carcinoma.

Invasive lobular carcinoma (ILC) is the second most common histological subtype of breast cancer following invasive ductal carcinoma (IDC). To identify potential genetic drivers of ILC progression, we used NanoString nCounter technology to investigate the DNA copy number (CN) in 70 well-curated primary ILC samples. We confirmed prior observations of frequent amplification of CCND1 (33%), and MYC (17%) in ILC, but additionally identified a substantial subset of ILCs with ESR1 and ERBB2 (19%) amplifications. Of interest, tumors with ESR1 CN gains (14%) and amplification (10%) were more likely to recur compared to those with normal CN. Finally, we observed that MDM4 (MDMX) was amplified in 17% of ILC samples. MDM4 knockdown in TP53 wild-type ILC cell lines caused increased apoptosis, decreased proliferation associated with cell cycle arrest, and concomitant activation of TP53 target genes. Similar effects were seen in TP53 mutant cells, indicting a TP53-independent role for MDM4 in ILC. To conclude, amplification of ESR1 and MDM4 are potential genetic drivers of ILC. These amplifications may represent actionable, targetable tumor dependencies, and thus have potential clinical implications and warrant further study.