Leveraging Maker Learning in STEM to Promote Children's Interest in Cancer Research: A Pilot Program.

Children's early awareness about cancer, through exposure to cancer biology and prevention strategies and research principles, is a promising focus of education and learning. It may also benefit the pipeline of people entering into science, technology, engineering, and math (STEM) careers. We describe an educational pilot program for elementary school students, using developmentally appropriate activities focused on cancer at a museum dedicated to children's maker-centered learning and STEM. The program was implemented through a public school in Washington, DC serving students underrepresented in STEM. Program conceptualization, museum and school engagement, and maker learning pedagogy are described, as well as curricular outcomes. A total of N = 111 students (44% female, 75% Black/African American, 5% Latine) participated in a day-long field trip. Museum educators, assisted by cancer center researchers, led a multipart workshop on cancer and the environment and hands-on rotation of activities in microbiology, immunology, and ultraviolet radiation safety; students then completed self-report evaluations. Results indicate that nearly all (> 95%) students practiced activities typical of a STEM professional at the program, and > 70% correctly answered factual questions about topics studied. Importantly, 87-94% demonstrated clear STEM interest, a sense of belonging in the field, and practice implementing skills for success in STEM (e.g., perseverance, imagination, teamwork). This pilot demonstrated acceptability and feasibility in delivering a cancer-focused curriculum to underserved elementary students using maker learning while favorably impacting key objectives. Future scale-up of this program is warranted, with the potential to increase students' motivation to engage in STEM and cancer research.

The orphan nuclear receptor estrogen-related receptor beta (ERRß) in triple-negative breast cancer.

PURPOSE: Triple-negative breast cancer (TNBC)/basal-like breast cancer (BLBC) is a highly aggressive form of breast cancer. We previously reported that a small molecule agonist ligand for the orphan nuclear receptor estrogen-related receptor beta (ERRß or ESRRB) has growth inhibitory and anti-mitotic activity in TNBC cell lines. In this study, we evaluate the association of ESRRB mRNA, copy number levels, and protein expression with demographic, clinicopathological, and gene expression features in breast tumor clinical specimens. METHODS: ESRRB mRNA-level expression and clinical associations were analyzed using RNAseq data. Array-based comparative genomic hybridization determined ESRRB copy number in African-American and Caucasian women. Transcription factor activity was measured using promoter-reporter luciferase assays in TNBC cell lines. Semi-automatic quantification of immunohistochemistry measured ERRß protein expression on a 150-patient tissue microarray series. RESULTS: ESRRB mRNA expression is significantly lower in TNBC/BLBC versus other breast cancer subtypes. There is no evidence of ESRRB copy number loss. ESRRB mRNA expression is correlated with the expression of genes associated with neuroactive ligand-receptor interaction, metabolic pathways, and deafness. These genes contain G/C-rich transcription factor binding motifs. The ESRRB message is alternatively spliced into three isoforms, which we show have different transcription factor activity in basal-like versus other TNBC cell lines. We further show that the ERRß2 and ERRßsf isoforms are broadly expressed in breast tumors at the protein level. CONCLUSIONS: Decreased ESRRB mRNA expression and distinct patterns of ERRß isoform subcellular localization and transcription factor activity are key features in TNBC/BLBC.

Estrogen-related receptor ß activation and isoform shifting by cdc2-like kinase inhibition restricts migration and intracranial tumor growth in glioblastoma.

Glioblastoma (GBM; grade 4 glioma) is a highly aggressive and incurable tumor. GBM has recently been characterized as highly dependent on alternative splicing, a critical driver of tumor heterogeneity and plasticity. Estrogen-related receptor ß (ERR-ß) is an orphan nuclear receptor expressed in the brain, where alternative splicing of the 3' end of the pre-mRNA leads to the production of 3 validated ERR-ß protein products: ERR-ß short form (ERR-ßsf), ERR-ß2, and ERR-ß exon 10 deleted. Our prior studies have shown the ERR-ß2 isoform to play a role in G2/M cell cycle arrest and induction of apoptosis, in contrast to the function of the shorter ERR-ßsf isoform in senescence and G1 cell cycle arrest. In this study, we sought to better define the role of the proapoptotic ERR-ß2 isoform in GBM. We show that the ERR-ß2 isoform is located not only in the nucleus but also in the cytoplasm. ERR-ß2 suppresses GBM cell migration and interacts with the actin nucleation-promoting factor cortactin, and an ERR-ß agonist is able to remodel the actin cytoskeleton and similarly suppress GBM cell migration. We further show that inhibition of the splicing regulatory cdc2-like kinases in combination with an ERR-ß agonist shifts isoform expression in favor of ERR-ß2 and potentiates inhibition of growth and migration in GBM cells and intracranial tumors.-Tiek, D. M., Khatib, S. A., Trepicchio, C. J., Heckler, M. M., Divekar, S. D., Sarkaria, J. N., Glasgow, E., Riggins, R. B. Estrogen-related receptor ß activation and isoform shifting by cdc2-like kinase inhibition restricts migration and intracranial tumor growth in glioblastoma.

Key regulators of lipid metabolism drive endocrine resistance in invasive lobular breast cancer.

BACKGROUND: Invasive lobular breast carcinoma (ILC) is a histological subtype of breast cancer that is characterized by loss of E-cadherin and high expression of estrogen receptor alpha (ERα). In many cases, ILC is effectively treated with adjuvant aromatase inhibitors (AIs); however, acquired AI resistance remains a significant problem. METHODS: To identify underlying mechanisms of acquired anti-estrogen resistance in ILC, we recently developed six long-term estrogen-deprived (LTED) variant cell lines from the human ILC cell lines SUM44PE (SUM44; two lines) and MDA-MB-134VI (MM134; four lines). To better understand mechanisms of AI resistance in these models, we performed transcriptional profiling analysis by RNA-sequencing followed by candidate gene expression and functional studies. RESULTS: MM134 LTED cells expressed ER at a decreased level and lost growth response to estradiol, while SUM44 LTED cells retained partial ER activity. Our transcriptional profiling analysis identified shared activation of lipid metabolism across all six independent models. However, the underlying basis of this signature was distinct between models. Oxysterols were able to promote the proliferation of SUM44 LTED cells but not MM134 LTED cells. In contrast, MM134 LTED cells displayed a high expression of the sterol regulatory element-binding protein 1 (SREBP1), a regulator of fatty acid and cholesterol synthesis, and were hypersensitive to genetic or pharmacological inhibition of SREBPs. Several SREBP1 downstream targets involved in fatty acid synthesis, including FASN, were induced, and MM134 LTED cells were more sensitive to etomoxir, an inhibitor of the rate-limiting enzyme in beta-oxidation, than their respective parental control cells. Finally, in silico expression analysis in clinical specimens from a neo-adjuvant endocrine trial showed a significant association between the increase of SREBP1 expression and lack of clinical response, providing further support for a role of SREBP1 in the acquisition of endocrine resistance in breast cancer. CONCLUSIONS: Our characterization of a unique series of AI-resistant ILC models identifies the activation of key regulators of fatty acid and cholesterol metabolism, implicating lipid-metabolic processes driving estrogen-independent growth of ILC cells. Targeting these changes may prove a strategy for prevention and treatment of endocrine resistance for patients with ILC.

Identifying protein interaction subnetworks by a bagging Markov random field-based method.

Identification of differentially expressed subnetworks from protein-protein interaction (PPI) networks has become increasingly important to our global understanding of the molecular mechanisms that drive cancer. Several methods have been proposed for PPI subnetwork identification, but the dependency among network member genes is not explicitly considered, leaving many important hub genes largely unidentified. We present a new method, based on a bagging Markov random field (BMRF) framework, to improve subnetwork identification for mechanistic studies of breast cancer. The method follows a maximum a posteriori principle to form a novel network score that explicitly considers pairwise gene interactions in PPI networks, and it searches for subnetworks with maximal network scores. To improve their robustness across data sets, a bagging scheme based on bootstrapping samples is implemented to statistically select high confidence subnetworks. We first compared the BMRF-based method with existing methods on simulation data to demonstrate its improved performance. We then applied our method to breast cancer data to identify PPI subnetworks associated with breast cancer progression and/or tamoxifen resistance. The experimental results show that not only an improved prediction performance can be achieved by the BMRF approach when tested on independent data sets, but biologically meaningful subnetworks can also be revealed that are relevant to breast cancer and tamoxifen resistance.

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.

Robust identification of transcriptional regulatory networks using a Gibbs sampler on outlier sum statistic.

MOTIVATION: Identification of transcriptional regulatory networks (TRNs) is of significant importance in computational biology for cancer research, providing a critical building block to unravel disease pathways. However, existing methods for TRN identification suffer from the inclusion of excessive 'noise' in microarray data and false-positives in binding data, especially when applied to human tumor-derived cell line studies. More robust methods that can counteract the imperfection of data sources are therefore needed for reliable identification of TRNs in this context. RESULTS: In this article, we propose to establish a link between the quality of one target gene to represent its regulator and the uncertainty of its expression to represent other target genes. Specifically, an outlier sum statistic was used to measure the aggregated evidence for regulation events between target genes and their corresponding transcription factors. A Gibbs sampling method was then developed to estimate the marginal distribution of the outlier sum statistic, hence, to uncover underlying regulatory relationships. To evaluate the effectiveness of our proposed method, we compared its performance with that of an existing sampling-based method using both simulation data and yeast cell cycle data. The experimental results show that our method consistently outperforms the competing method in different settings of signal-to-noise ratio and network topology, indicating its robustness for biological applications. Finally, we applied our method to breast cancer cell line data and demonstrated its ability to extract biologically meaningful regulatory modules related to estrogen signaling and action in breast cancer. AVAILABILITY AND IMPLEMENTATION: The Gibbs sampler MATLAB package is freely available at http://www.cbil.ece.vt.edu/software.htm. CONTACT: xuan@vt.edu SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Acquired temozolomide resistance instructs patterns of glioblastoma behavior in gelatin hydrogels.

Acquired drug resistance in glioblastoma (GBM) presents a major clinical challenge and is a key factor contributing to abysmal prognosis, with less than 15 months median overall survival. Aggressive chemotherapy with the frontline therapeutic, temozolomide (TMZ), ultimately fails to kill residual highly invasive tumor cells after surgical resection and radiotherapy. Here, we report a three-dimensional (3D) engineered model of acquired TMZ resistance using two isogenically-matched sets of GBM cell lines encapsulated in gelatin methacrylol hydrogels. We benchmark response of TMZ-resistant vs. TMZ-sensitive GBM cell lines within the gelatin-based extracellular matrix platform and further validate drug response at physiologically relevant TMZ concentrations. We show changes in drug sensitivity, cell invasion, and matrix-remodeling cytokine production as the result of acquired TMZ resistance. This platform lays the foundation for future investigations targeting key elements of the GBM tumor microenvironment to combat GBM's devastating impact by advancing our understanding of GBM progression and treatment response to guide the development of novel treatment strategies. Teaser: A hydrogel model to investigate the impact of acquired drug resistance on functional response in glioblastoma.

ROS is a master regulator of in vitro matriptase activation.

Matriptase is a type II transmembrane serine protease that is widely expressed in normal epithelial cells and epithelial cancers. Studies have shown that regulation of matriptase expression and activation becomes deranged in several cancers and is associated with poor disease-free survival. Although the central mechanism of its activation has remained unknown, our lab has previously demonstrated that inflammatory conditions such as intracellular pH decrease strongly induces matriptase activation. In this investigation, we first demonstrate clear matriptase activation following Fulvestrant (ICI) and Tykerb (Lapatinib) treatment in HER2-amplified, estrogen receptor (ER)-positive BT474, MDA-MB-361 and ZR-75-30 or single ER-positive MCF7 cells, respectively. This activation modestly involved Phosphoinositide 3-kinase (PI3K) activation and occurred as quickly as six hours post treatment. We also demonstrate that matriptase activation is not a universal hallmark of stress, with Etoposide treated cells showing a larger degree of matriptase activation than Lapatinib and ICI-treated cells. While etoposide toxicity has been shown to be mediated through reactive oxygen species (ROS) and MAPK/ERK kinase (MEK) activity, MEK activity showed no correlation with matriptase activation. Novelly, we demonstrate that endogenous and exogenous matriptase activation are ROS-mediated in vitro and inhibited by N-acetylcysteine (NAC). Lastly, we demonstrate matriptase-directed NAC treatment results in apoptosis of several breast cancer cell lines either alone or in combination with clinically used therapeutics. These data demonstrate the contribution of ROS-mediated survival, its independence of kinase-mediated survival, and the plausibility of using matriptase activation to indicate the potential success of antioxidant therapy.

Unraveling Vulnerabilities in Endocrine Therapy-Resistant HER2+/ER+ Breast Cancer.

Breast tumors overexpressing human epidermal growth factor receptor (HER2) confer intrinsic resistance to endocrine therapy (ET), and patients with HER2/estrogen receptor-positive (HER2+/ER+) breast cancer (BCa) are less responsive to ET than HER2-/ER+. However, real-world evidence reveals that a large subset of patients with HER2+/ER+ receive ET as monotherapy, positioning this treatment pattern as a clinical challenge. In the present study, we developed and characterized 2 in vitro models of ET-resistant (ETR) HER2+/ER+ BCa to identify possible therapeutic vulnerabilities. To mimic ETR to aromatase inhibitors (AIs), we developed 2 long-term estrogen deprivation (LTED) cell lines from BT-474 (BT474) and MDA-MB-361 (MM361). Growth assays, PAM50 subtyping, and genomic and transcriptomic analyses, followed by validation and functional studies, were used to identify targetable differences between ET-responsive parental and ETR-LTED HER2+/ER+ cells. Compared to their parental cells, MM361 LTEDs grew faster, lost ER, and increased HER2 expression, whereas BT474 LTEDs grew slower and maintained ER and HER2 expression. Both LTED variants had reduced responsiveness to fulvestrant. Whole-genome sequencing of aggressive MM361 LTEDs identified mutations in genes encoding transcription factors and chromatin modifiers. Single-cell RNA sequencing demonstrated a shift towards non-luminal phenotypes, and revealed metabolic remodeling of MM361 LTEDs, with upregulated lipid metabolism and ferroptosis-associated antioxidant genes, including GPX4. Combining a GPX4 inhibitor with anti-HER2 agents induced significant cell death in both MM361 and BT474 LTEDs. The BT474 and MM361 AI-resistant models capture distinct phenotypes of HER2+/ER+ BCa and identify altered lipid metabolism and ferroptosis remodeling as vulnerabilities of this type of ETR BCa.

Unraveling Vulnerabilities in Endocrine Therapy-Resistant HER2+/ER+ Breast Cancer.

Background: Breast tumors overexpressing human epidermal growth factor receptor (HER2) confer intrinsic resistance to endocrine therapy (ET), and patients with HER2/ estrogen receptor-positive (HER2+/HR+) breast cancer (BCa) are less responsive to ET than HER2-/ER+. However, real-world evidence reveals that a large subset of HER2+/ER+ patients receive ET as monotherapy, positioning this treatment pattern as a clinical challenge. In the present study, we developed and characterized two distinct in vitro models of ET-resistant (ETR) HER2+/ER+ BCa to identify possible therapeutic vulnerabilities. Methods: To mimic ETR to aromatase inhibitors (AI), we developed two long-term estrogen-deprived (LTED) cell lines from BT-474 (BT474) and MDA-MB-361 (MM361). Growth assays, PAM50 molecular subtyping, genomic and transcriptomic analyses, followed by validation and functional studies, were used to identify targetable differences between ET-responsive parental and ETR-LTED HER2+/ER+ cells. Results: Compared to their parental cells, MM361 LTEDs grew faster, lost ER, and increased HER2 expression, whereas BT474 LTEDs grew slower and maintained ER and HER2 expression. Both LTED variants had reduced responsiveness to fulvestrant. Whole-genome sequencing of the more aggressive MM361 LTED model system identified exonic mutations in genes encoding transcription factors and chromatin modifiers. Single-cell RNA sequencing demonstrated a shift towards non-luminal phenotypes, and revealed metabolic remodeling of MM361 LTEDs, with upregulated lipid metabolism and antioxidant genes associated with ferroptosis, including GPX4. Combining the GPX4 inhibitor RSL3 with anti-HER2 agents induced significant cell death in both the MM361 and BT474 LTEDs. Conclusions: The BT474 and MM361 AI-resistant models capture distinct phenotypes of HER2+/ER+ BCa and identify altered lipid metabolism and ferroptosis remodeling as vulnerabilities of this type of ETR BCa.

Riluzole Suppresses Growth and Enhances Response to Endocrine Therapy in ER+ Breast Cancer.

Background: Resistance to endocrine therapy in estrogen receptor-positive (ER+) breast cancer remains a significant clinical problem. Riluzole is FDA-approved for the treatment of amyotrophic lateral sclerosis. A benzothiazole-based glutamate release inhibitor with several context-dependent mechanism(s) of action, riluzole has shown antitumor activity in multiple malignancies, including melanoma, glioblastoma, and breast cancer. We previously reported that the acquisition of tamoxifen resistance in a cellular model of invasive lobular breast cancer is accompanied by the upregulation of GRM mRNA expression and growth inhibition by riluzole. Methods: We tested the ability of riluzole to reduce cell growth, alone and in combination with endocrine therapy, in a diverse set of ER+ invasive ductal and lobular breast cancer-derived cell lines, primary breast tumor explant cultures, and the estrogen-independent, ESR1-mutated invasive lobular breast cancer patient-derived xenograft model HCI-013EI. Results: Single-agent riluzole suppressed the growth of ER+ invasive ductal and lobular breast cancer cell lines in vitro, inducing a histologic subtype-associated cell cycle arrest (G0-G1 for ductal, G2-M for lobular). Riluzole induced apoptosis and ferroptosis and reduced phosphorylation of multiple prosurvival signaling molecules, including Akt/mTOR, CREB, and Fak/Src family kinases. Riluzole, in combination with either fulvestrant or 4-hydroxytamoxifen, additively suppressed ER+ breast cancer cell growth in vitro. Single-agent riluzole significantly inhibited HCI-013EI patient-derived xenograft growth in vivo, and the combination of riluzole plus fulvestrant significantly reduced proliferation in ex vivo primary breast tumor explant cultures. Conclusion: Riluzole may offer therapeutic benefits in diverse ER+ breast cancers, including lobular breast cancer.

SGC-CLK-1: A chemical probe for the Cdc2-like kinases CLK1, CLK2, and CLK4.

Small molecule modulators are important tools to study both basic biology and the complex signaling of protein kinases. The cdc2-like kinases (CLK) are a family of four kinases that have garnered recent interest for their involvement in a diverse set of diseases such as neurodegeneration, autoimmunity, and many cancers. Targeted medicinal chemistry around a CLK inhibitor hit identified through screening of a kinase inhibitor set against a large panel of kinases allowed us to identify a potent and selective inhibitor of CLK1, 2, and 4. Here, we present the synthesis, selectivity, and preliminary biological characterization of this compound - SGC-CLK-1 (CAF-170). We further show CLK2 has the highest binding affinity, and high CLK2 expression correlates with a lower IC50 in a screen of multiple cancer cell lines. Finally, we show that SGC-CLK-1 not only reduces serine arginine-rich (SR) protein phosphorylation but also alters SR protein and CLK2 subcellular localization in a reversible way. Therefore, we anticipate that this compound will be a valuable tool for increasing our understanding of CLKs and their targets, SR proteins, at the level of phosphorylation and subcellular localization.

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.

Temozolomide-induced guanine mutations create exploitable vulnerabilities of guanine-rich DNA and RNA regions in drug-resistant gliomas.

Temozolomide (TMZ) is a chemotherapeutic agent that has been the first-line standard of care for the aggressive brain cancer glioblastoma (GBM) since 2005. Although initially beneficial, TMZ resistance is universal and second-line interventions are an unmet clinical need. Here, we took advantage of the known mechanism of action of TMZ to target guanines (G) and investigated G-rich G-quadruplex (G4) and splice site changes that occur upon TMZ resistance. We report that TMZ-resistant GBM has guanine mutations that disrupt the G-rich DNA G4s and splice sites that lead to deregulated alternative splicing. These alterations create vulnerabilities, which are selectively targeted by either the G4-stabilizing drug TMPyP4 or a novel splicing kinase inhibitor of cdc2-like kinase. Last, we show that the G4 and RNA binding protein EWSR1 aggregates in the cytoplasm in TMZ-resistant GBM cells and patient samples. Together, our findings provide insight into targetable vulnerabilities of TMZ-resistant GBM and present cytoplasmic EWSR1 as a putative biomarker.

Motif-guided sparse decomposition of gene expression data for regulatory module identification.

BACKGROUND: Genes work coordinately as gene modules or gene networks. Various computational approaches have been proposed to find gene modules based on gene expression data; for example, gene clustering is a popular method for grouping genes with similar gene expression patterns. However, traditional gene clustering often yields unsatisfactory results for regulatory module identification because the resulting gene clusters are co-expressed but not necessarily co-regulated. RESULTS: We propose a novel approach, motif-guided sparse decomposition (mSD), to identify gene regulatory modules by integrating gene expression data and DNA sequence motif information. The mSD approach is implemented as a two-step algorithm comprising estimates of (1) transcription factor activity and (2) the strength of the predicted gene regulation event(s). Specifically, a motif-guided clustering method is first developed to estimate the transcription factor activity of a gene module; sparse component analysis is then applied to estimate the regulation strength, and so predict the target genes of the transcription factors. The mSD approach was first tested for its improved performance in finding regulatory modules using simulated and real yeast data, revealing functionally distinct gene modules enriched with biologically validated transcription factors. We then demonstrated the efficacy of the mSD approach on breast cancer cell line data and uncovered several important gene regulatory modules related to endocrine therapy of breast cancer. CONCLUSION: We have developed a new integrated strategy, namely motif-guided sparse decomposition (mSD) of gene expression data, for regulatory module identification. The mSD method features a novel motif-guided clustering method for transcription factor activity estimation by finding a balance between co-regulation and co-expression. The mSD method further utilizes a sparse decomposition method for regulation strength estimation. The experimental results show that such a motif-guided strategy can provide context-specific regulatory modules in both yeast and breast cancer studies.

Multilevel support vector regression analysis to identify condition-specific regulatory networks.

MOTIVATION: The identification of gene regulatory modules is an important yet challenging problem in computational biology. While many computational methods have been proposed to identify regulatory modules, their initial success is largely compromised by a high rate of false positives, especially when applied to human cancer studies. New strategies are needed for reliable regulatory module identification. RESULTS: We present a new approach, namely multilevel support vector regression (ml-SVR), to systematically identify condition-specific regulatory modules. The approach is built upon a multilevel analysis strategy designed for suppressing false positive predictions. With this strategy, a regulatory module becomes ever more significant as more relevant gene sets are formed at finer levels. At each level, a two-stage support vector regression (SVR) method is utilized to help reduce false positive predictions by integrating binding motif information and gene expression data; a significant analysis procedure is followed to assess the significance of each regulatory module. To evaluate the effectiveness of the proposed strategy, we first compared the ml-SVR approach with other existing methods on simulation data and yeast cell cycle data. The resulting performance shows that the ml-SVR approach outperforms other methods in the identification of both regulators and their target genes. We then applied our method to breast cancer cell line data to identify condition-specific regulatory modules associated with estrogen treatment. Experimental results show that our method can identify biologically meaningful regulatory modules related to estrogen signaling and action in breast cancer. AVAILABILITY AND IMPLEMENTATION: The ml-SVR MATLAB package can be downloaded at http://www.cbil.ece.vt.edu/software.htm.

BCL2 and CASP8 regulation by NF-kappaB differentially affect mitochondrial function and cell fate in antiestrogen-sensitive and -resistant breast cancer cells.

Resistance to endocrine therapies remains a major problem in the management of estrogen receptor-alpha (ER)-positive breast cancer. We show that inhibition of NF-kappaB (p65/RELA), either by overexpression of a mutant IkappaB (IkappaBSR) or a small-molecule inhibitor of NF-kappaB (parthenolide; IC(50)=500 nM in tamoxifen-resistant cells), synergistically restores sensitivity to 4-hydroxytamoxifen (4HT) in resistant MCF7/RR and MCF7/LCC9 cells and further sensitizes MCF-7 and MCF7/LCC1 control cells to 4HT. These effects are independent of changes in either cell cycle distribution or in the level of autophagy measured by inhibition of p62/SQSTM1 expression and cleavage of LC3. NF-kappaB inhibition restores the ability of 4HT to decrease BCL2 expression, increase mitochondrial membrane permeability, and induce a caspase-dependent apoptotic cell death in resistant cells. Each of these effects is reversed by a caspase 8 (CASP8)-specific inhibitor that blocks enzyme-substrate binding. Thus, increased activation of NF-kappaB can alter sensitivity to tamoxifen by modulating CASP8 activity, with consequent effects on BCL2 expression, mitochondrial function, and apoptosis. These data provide significant new insights into how molecular signaling affects antiestrogen responsiveness and strongly suggest that a combination of parthenolide and tamoxifen may offer a novel therapeutic approach to the management of some ER-positive breast cancers.

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.

Steroid Hormone Receptor and Infiltrating Immune Cell Status Reveals Therapeutic Vulnerabilities of ESR1-Mutant Breast Cancer.

Mutations in ESR1 that confer constitutive estrogen receptor alpha (ER) activity in the absence of ligand are acquired by ≥40% of metastatic breast cancers (MBC) resistant to adjuvant aromatase inhibitor (AI) therapy. To identify targetable vulnerabilities in MBC, we examined steroid hormone receptors and tumor-infiltrating immune cells in metastatic lesions with or without ER mutations. ER and progesterone receptor (PR) were significantly lower in metastases with wild-type (WT) ER compared with those with mutant ER, suggesting that metastases that evade AI therapy by mechanism(s) other than acquiring ER mutations lose dependency on ER and PR. Metastases with mutant ER had significantly higher T regulatory and Th cells, total macrophages, and programmed death ligand-1 (PD-L1)-positive immune-suppressive macrophages than those with WT ER. Breast cancer cells with CRISPR-Cas9-edited ER (D538G, Y537S, or WT) and patient-derived xenografts harboring mutant or WT ER revealed genes and proteins elevated in mutant ER cells, including androgen receptor (AR), chitinase-3-like protein 1 (CHI3L1), and IFN-stimulated genes (ISG). Targeting these proteins blunted the selective advantage of ER-mutant tumor cells to survive estrogen deprivation, anchorage independence, and invasion. Thus, patients with mutant ER MBC might respond to standard-of-care fulvestrant or other selective ER degraders when combined with AR or CHI3L1 inhibition, perhaps with the addition of immunotherapy. SIGNIFICANCE: Targetable alterations in MBC, including AR, CHI3L1, and ISG, arise following estrogen-deprivation, and ER-mutant metastases may respond to immunotherapies due to elevated PD-L1+ macrophages.See related article by Arnesen et al., p. 539.