Functional delineation of the luminal epithelial microenvironment in breast using cell-based screening in combinatorial microenvironments

Microenvironment signals are potent determinants of cell fate and arbiters of tissue homeostasis, however understanding how different microenvironment factors coordinately regulate cellular phenotype has been experimentally challenging. Here we used a high-throughput microenvironment microarray comprised of 2640 unique pairwise signals to identify factors that support proliferation and maintenance of primary human mammary luminal epithelial cells. Multiple microenvironment factors that modulated luminal cell number were identified, including: HGF, NRG1, BMP2, CXCL1, TGFB1, FGF2, PDGFB, RANKL, WNT3A, SPP1, HA, VTN, and OMD. All of these factors were previously shown to modulate luminal cell numbers in painstaking mouse genetics experiments, or were shown to have a role in breast cancer, demonstrating the relevance and power of our high-dimensional approach to dissect key microenvironmental signals. RNA-sequencing of primary epithelial and stromal cell lineages identified the cell types that express these signals and the cognate receptors in vivo. Cell-based functional studies confirmed which effects from microenvironment factors were reproducible and robust to individual variation. Hepatocyte growth factor (HGF) was the factor most robust to individual variation and drove expansion of luminal cells via cKit+ progenitor cells, which expressed abundant MET receptor. Luminal cells from women who are genetically high risk for breast cancer had significantly more MET receptor and may explain the characteristic expansion of the luminal lineage in those women. In ensemble, our approach provides proof of principle that microenvironment signals that control specific cellular states can be dissected with high-dimensional cell-based approaches.

Computational drug repositioning for the identification of new agents to sensitize drug-resistant breast tumors across treatments and receptor subtypes

Introduction

Drug resistance is a major obstacle in cancer treatment and can involve a variety of different factors. Identifying effective therapies for drug resistant tumors is integral for improving patient outcomes.

Methods

In this study, we applied a computational drug repositioning approach to identify potential agents to sensitize primary drug resistant breast cancers. We extracted drug resistance profiles from the I-SPY 2 TRIAL, a neoadjuvant trial for early stage breast cancer, by comparing gene expression profiles of responder and non-responder patients stratified into treatments within HR/HER2 receptor subtypes, yielding 17 treatment-subtype pairs. We then used a rank-based pattern-matching strategy to identify compounds in the Connectivity Map, a database of cell line derived drug perturbation profiles, that can reverse these signatures in a breast cancer cell line. We hypothesize that reversing these drug resistance signatures will sensitize tumors to treatment and prolong survival.

Results

We found that few individual genes are shared among the drug resistance profiles of different agents. At the pathway level, however, we found enrichment of immune pathways in the responders in 8 treatments within the HR+HER2+, HR+HER2-, and HR-HER2- receptor subtypes. We also found enrichment of estrogen response pathways in the non-responders in 10 treatments primarily within the hormone receptor positive subtypes. Although most of our drug predictions are unique to treatment arms and receptor subtypes, our drug repositioning pipeline identified the estrogen receptor antagonist fulvestrant as a compound that can potentially reverse resistance across 13/17 of the treatments and receptor subtypes including HR+ and triple negative. While fulvestrant showed limited efficacy when tested in a panel of 5 paclitaxel resistant breast cancer cell lines, it did increase drug response in combination with paclitaxel in HCC-1937, a triple negative breast cancer cell line.

Conclusion

We applied a computational drug repurposing approach to identify potential agents to sensitize drug resistant breast cancers in the I-SPY 2 TRIAL. We identified fulvestrant as a potential drug hit and showed that it increased response in a paclitaxel-resistant triple negative breast cancer cell line, HCC-1937, when treated in combination with paclitaxel.

An altered extracellular matrix-integrin interface contributes to Huntington’s disease-associated CNS dysfunction in glial and vascular cells

Astrocytes and brain endothelial cells are components of the neurovascular unit that comprises the blood brain barrier (BBB) and their dysfunction contributes to pathogenesis in Huntington’s disease (HD). Defining the contribution of these cells to disease can inform cell-type specific effects and uncover new disease-modifying therapeutic targets. These cells express integrin (ITG) adhesion receptors that anchor the cells to the extracellular matrix (ECM) to maintain the integrity of the BBB. We used HD patient-derived induced pluripotent stem cell (iPSC) modeling to study the ECM-ITG interface in astrocytes and brain microvascular endothelial cells (BMECs) and found ECM-ITG dysregulation in human iPSC-derived cells that may contribute to dysfunction of the BBB in HD. This disruption has functional consequences since reducing ITG expression in glia in an HD Drosophila model suppressed disease-associated CNS dysfunction. Since ITGs can be targeted therapeutically and manipulating ITG signaling prevents neurodegeneration in other diseases, defining the role of ITGs in HD may provide a novel strategy of intervention to slow CNS pathophysiology to treat HD.

A multiplex implantable microdevice assay identifies synergistic combinations of cancer immunotherapies and conventional drugs

Systematically identifying synergistic combinations of targeted agents and immunotherapies for cancer treatments remains difficult. In this study, we integrated high-throughput and high-content techniques-an implantable microdevice to administer multiple drugs into different sites in tumors at nanodoses and multiplexed imaging of tumor microenvironmental states-to investigate the tumor cell and immunological response signatures to different treatment regimens. Using a mouse model of breast cancer, we identified effective combinations from among numerous agents within days. In vivo studies in three immunocompetent mammary carcinoma models demonstrated that the predicted combinations synergistically increased therapeutic efficacy. We identified at least five promising treatment strategies, of which the panobinostat, venetoclax and anti-CD40 triple therapy was the most effective in inducing complete tumor remission across models. Successful drug combinations increased spatial association of cancer stem cells with dendritic cells during immunogenic cell death, suggesting this as an important mechanism of action in long-term breast cancer control.

Systematic replication enables normalization of high-throughput imaging assays

MOTIVATION

High-throughput fluorescent microscopy is a popular class of techniques for studying tissues and cells through automated imaging and feature extraction of hundreds to thousands of samples. Like other high-throughput assays, these approaches can suffer from unwanted noise and technical artifacts that obscure the biological signal. In this work, we consider how an experimental design incorporating multiple levels of replication enables the removal of technical artifacts from such image-based platforms.

RESULTS

We develop a general approach to remove technical artifacts from high-throughput image data that leverages an experimental design with multiple levels of replication. To illustrate the methods, we consider microenvironment microarrays (MEMAs), a high-throughput platform designed to study cellular responses to microenvironmental perturbations. In application to MEMAs, our approach removes unwanted spatial artifacts and thereby enhances the biological signal. This approach has broad applicability to diverse biological assays.

AVAILABILITY AND IMPLEMENTATION

Raw data are on synapse (syn2862345), analysis code is on github: gjhunt/mema_norm, a reproducible Docker image is available on dockerhub: gjhunt/mema_norm.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

A multi-omic analysis of MCF10A cells provides a resource for integrative assessment of ligand-mediated molecular and phenotypic responses

The phenotype of a cell and its underlying molecular state is strongly influenced by extracellular signals, including growth factors, hormones, and extracellular matrix proteins. While these signals are normally tightly controlled, their dysregulation leads to phenotypic and molecular states associated with diverse diseases. To develop a detailed understanding of the linkage between molecular and phenotypic changes, we generated a comprehensive dataset that catalogs the transcriptional, proteomic, epigenomic and phenotypic responses of MCF10A mammary epithelial cells after exposure to the ligands EGF, HGF, OSM, IFNG, TGFB and BMP2. Systematic assessment of the molecular and cellular phenotypes induced by these ligands comprise the LINCS Microenvironment (ME) perturbation dataset, which has been curated and made publicly available for community-wide analysis and development of novel computational methods ( synapse.org/LINCS_MCF10A ). In illustrative analyses, we demonstrate how this dataset can be used to discover functionally related molecular features linked to specific cellular phenotypes. Beyond these analyses, this dataset will serve as a resource for the broader scientific community to mine for biological insights, to compare signals carried across distinct molecular modalities, and to develop new computational methods for integrative data analysis.

Ferrous iron–activatable drug conjugate achieves potent MAPK blockade in KRAS-driven tumors

KRAS mutations drive a quarter of cancer mortality, and most are undruggable. Several inhibitors of the MAPK pathway are FDA approved but poorly tolerated at the doses needed to adequately extinguish RAS/RAF/MAPK signaling in the tumor cell. We found that oncogenic KRAS signaling induced ferrous iron (Fe²⁺) accumulation early in and throughout mutant KRAS-mediated transformation. We converted an FDA-approved MEK inhibitor into a ferrous iron–activatable drug conjugate (FeADC) and achieved potent MAPK blockade in tumor cells while sparing normal tissues. This innovation allowed sustainable, effective treatment of tumor-bearing animals, with tumor-selective drug activation, producing superior systemic tolerability. Ferrous iron accumulation is an exploitable feature of KRAS transformation, and FeADCs hold promise for improving the treatment of KRAS-driven solid tumors.

INHBA is a mediator of aggressive tumor behavior in HER2+ basal breast cancer

Background

Resistance to HER2-targeted therapeutics remains a significant clinical problem in HER2+ breast cancer patients with advanced disease. This may be particularly true for HER2+ patients with basal subtype disease, as recent evidence suggests they receive limited benefit from standard of care HER2-targeted therapies. Identification of drivers of resistance and aggressive disease that can be targeted clinically has the potential to impact patient outcomes.

Methods

We performed siRNA knockdown screens of genes differentially expressed between lapatinib-responsive and -resistant HER2+ breast cancer cells, which corresponded largely to luminal versus basal subtypes. We then validated hits in 2-d and 3-d cell culture systems.

Results

Knockdown of one of the genes, INHBA, significantly slowed growth and increased sensitivity to lapatinib in multiple basal HER2+ cell lines in both 2-d and 3-d cultures, but had no effect in luminal HER2+ cells. Loss of INHBA altered metabolism, eliciting a shift from glycolytic to oxidative phosphorylative metabolism, which was also associated with a decrease in tumor invasiveness. Analysis of breast cancer datasets showed that patients with HER2+ breast cancer and high levels of INHBA expression had worse outcomes than patients with low levels of INHBA expression.

Conclusions

Our data suggest that INHBA is associated with aggressiveness of the basal subtype of HER2+ tumors, resulting in poor response to HER2-targeted therapy and an invasive phenotype. We hypothesize that targeting this pathway could be an effective therapeutic strategy to reduce invasiveness of tumor cells and to improve therapeutic response.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13058-022-01512-4.

Cellular senescence in cancer: from mechanisms to detection

Senescence refers to a cellular state featuring a stable cell-cycle arrest triggered in response to stress. This response also involves other distinct morphological and intracellular changes including alterations in gene expression and epigenetic modifications, elevated macromolecular damage, metabolism deregulation and a complex pro-inflammatory secretory phenotype. The initial demonstration of oncogene-induced senescence in vitro established senescence as an important tumour-suppressive mechanism, in addition to apoptosis. Senescence not only halts the proliferation of premalignant cells but also facilitates the clearance of affected cells through immunosurveillance. Failure to clear senescent cells owing to deficient immunosurveillance may, however, lead to a state of chronic inflammation that nurtures a pro-tumorigenic microenvironment favouring cancer initiation, migration and metastasis. In addition, senescence is a response to post-therapy genotoxic stress. Therefore, tracking the emergence of senescent cells becomes pivotal to detect potential pro-tumorigenic events. Current protocols for the in vivo detection of senescence require the analysis of fixed or deep-frozen tissues, despite a significant clinical need for real-time bioimaging methods. Accuracy and efficiency of senescence detection are further hampered by a lack of universal and more specific senescence biomarkers. Recently, in an attempt to overcome these hurdles, an assortment of detection tools has been developed. These strategies all have significant potential for clinical utilisation and include flow cytometry combined with histo- or cytochemical approaches, nanoparticle-based targeted delivery of imaging contrast agents, OFF-ON fluorescent senoprobes, positron emission tomography senoprobes and analysis of circulating SASP factors, extracellular vesicles and cell-free nucleic acids isolated from plasma. Here, we highlight the occurrence of senescence in neoplasia and advanced tumours, assess the impact of senescence on tumorigenesis and discuss how the ongoing development of senescence detection tools might improve early detection of multiple cancers and response to therapy in the near future.

Sensitivity to targeted therapy differs between HER2-amplified breast cancer cells harboring kinase and helical domain mutations in PIK3CA

BACKGROUND

HER2-amplified breast cancer is a clinically defined subtype of breast cancer for which there are multiple viable targeted therapies. Resistance to these targeted therapies is a common problem, but the mechanisms by which resistance occurs remain incompletely defined. One mechanism that has been proposed is through mutation of genes in the PI3-kinase pathway. Intracellular signaling from the HER2 pathway can occur through PI3-kinase, and mutations of the encoding gene PIK3CA are known to be oncogenic. Mutations in PIK3CA co-occur with HER2-amplification in ~ 20% of cases within the HER2-amplified subtype.

METHODS

We generated isogenic knockin mutants of each PIK3CA hotspot mutation in HER2-amplified breast cancer cells using adeno-associated virus-mediated gene targeting. Isogenic clones were analyzed using a combinatorial drug screen to determine differential responses to HER2-targeted therapy. Western blot analysis and immunofluorescence uncovered unique intracellular signaling dynamics in cells resistant to HER2-targeted therapy. Subsequent combinatorial drug screens were used to explore neuregulin-1-mediated resistance to HER2-targeted therapy. Finally, results from in vitro experiments were extrapolated to publicly available datasets.

RESULTS

Treatment with HER2-targeted therapy reveals that mutations in the kinase domain (H1047R) but not the helical domain (E545K) increase resistance to lapatinib. Mechanistically, sustained AKT signaling drives lapatinib resistance in cells with the kinase domain mutation, as demonstrated by staining for the intracellular product of PI3-kinase, PIP3. This resistance can be overcome by co-treatment with an inhibitor to the downstream kinase AKT. Additionally, knockout of the PIP3 phosphatase, PTEN, phenocopies this result. We also show that neuregulin-1, a ligand for HER-family receptors, confers resistance to cells harboring either hotspot mutation and modulates response to combinatorial therapy. Finally, we show clinical evidence that the hotspot mutations have distinct expression profiles related to therapeutic resistance through analysis of TCGA and METABRIC data cohorts.

CONCLUSION

Our results demonstrate unique intracellular signaling differences depending on which mutation in PIK3CA the cell harbors. Only mutations in the kinase domain fully activate the PI3-kinase signaling pathway and maintain downstream signaling in the presence of HER2 inhibition. Moreover, we show there is potentially clinical importance in understanding both the PIK3CA mutational status and levels of neuregulin-1 expression in patients with HER2-amplified breast cancer treated with targeted therapy and that these problems warrant further pre-clinical and clinical testing.

Abstract 1870: The impact of the microenvironment on heterogeneity and trametinib response in HCC1143 triple negative breast cancer cells

Triple negative breast cancer (TNBC) lacks expression of hormone receptors (ER and PR) and HER2 and is characterized by aggressive disease with poor outcomes. Recent work suggests that TNBC also has a high degree of intratumoral heterogeneity, as measured by lineage differentiation status. This heterogeneity may impact therapeutic response, as it has been shown that treatment with PI3K/mTOR (BEZ235) or MEK (trametinib) inhibitors can drive TNBC cells into more homogeneous states, but that the surviving cells are resistant to the targeted therapy. In this study, we sought to understand how the microenvironment impacts differentiation state heterogeneity and response to targeted therapeutics in HCC1143 cells using our microenvironment microarray (MEMA) platform. Under low serum growth conditions, we found that several ligands could drive the growth of HCC1143, particularly EGF family ligands like AREG and EGF. With respect to differentiation state and heterogeneity, EGF and TGFB1 drove HCC1143 cells into a more mesenchymal like state, with increased expression of VIM and decreased expression of KRT14. In contrast, BMP2 led to higher levels of KRT14 and lower levels of VIM, leading to a more basal-like state. We also grew HCC1143 on MEMA with trametinib treatment. Here we found that combinations of collagen-based substrates and NRG1, HGF, and EGF ligands all led to higher cell counts and EdU incorporation rates compared to PBS-control treated cells. However, the levels of resistance conferred by the microenvironment was less than we had previously seen in HER2 positive MEMA, as the GR50 values (dose required to inhibit growth by 50%) only increased modestly (18 nM for untreated cells, 40 nM for NRG1, 45 nM for HGF). Interestingly, in that HER2 positive MEMA study, we identified HGF and NRG1 as potent resistance factors to lapatinib, but that they functioned in a subtype specific manner. HGF was effective in basal subtype cells and NRG1 in luminal, but not vice versa. We postulated that the modest resistance we observed was due to ligands acting on subsets of cells. We thus treated cells with a combination of NRG1 plus HGF, and found that this resulted in increased resistance (GR50= 91 nM). Imaging showed that trametinib drove HCC1143 cells to a homogenous KRT14 positive state, but surprisingly, addition of ligands reverted the cells to a more heterogeneous state that was resistant to trametinib. These data demonstrate that the microenvironment can impact the differentiation state of TNBC cells and is also capable of conferring resistance within subsets of the heterogeneous cell populations.

Citation Format: Rebecca Smith, Kaylyn Devlin, Moqing Liu, Tiera Liby, David Kilburn, Elmar Bucher, Damir Sudar, Guillaume Thibault, Mark Dane, Joe Gray, Laura Heiser, James E. Korkola. The impact of the microenvironment on heterogeneity and trametinib response in HCC1143 triple negative breast cancer cells [abstract]. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr 1870.

Transcriptional signatures in histologic structures within glioblastoma tumors may predict personalized drug sensitivity and survival

Background

Glioblastoma is a rapidly fatal brain cancer that exhibits extensive intra- and intertumoral heterogeneity. Improving survival will require the development of personalized treatment strategies that can stratify tumors into subtypes that differ in therapeutic vulnerability and outcomes. Glioblastoma stratification has been hampered by intratumoral heterogeneity, limiting our ability to compare tumors in a consistent manner. Here, we develop methods that mitigate the impact of intratumoral heterogeneity on transcriptomic-based patient stratification.

Methods

We accessed open-source transcriptional profiles of histological structures from 34 human glioblastomas from the Ivy Glioblastoma Atlas Project. Principal component and correlation network analyses were performed to assess sample inter-relationships. Gene set enrichment analysis was used to identify enriched biological processes and classify glioblastoma subtype. For survival models, Cox proportional hazards regression was utilized. Transcriptional profiles from 156 human glioblastomas were accessed from The Cancer Genome Atlas to externally validate the survival model.

Results

We showed that intratumoral histologic architecture influences tumor classification when assessing established subtyping and prognostic gene signatures, and that indiscriminate sampling can produce misleading results. We identified the cellular tumor as a glioblastoma structure that can be targeted for transcriptional analysis to more accurately stratify patients by subtype and prognosis. Based on expression from cellular tumor, we created an improved risk stratification gene signature.

Conclusions

Our results highlight that biomarker performance for diagnostics, prognostics, and prediction of therapeutic response can be improved by analyzing transcriptional profiles in pure cellular tumor, which is a critical step toward developing personalized treatment for glioblastoma.

Automatic Transformation and Integration to Improve Visualization and Discovery of Latent Effects in Imaging Data

Proper data transformation is an essential part of analysis. Choosing appropriate transformations for variables can enhance visualization, improve efficacy of analytical methods, and increase data interpretability. However determining appropriate transformations of variables from high-content imaging data poses new challenges. Imaging data produces hundreds of covariates from each of thousands of images in a corpus. Each of these covariates will have a different distribution and need a potentially different transformation. As such imaging data produces hundreds of covariates, determining an appropriate transformation for each of them is infeasible by hand. In this paper we explore simple, robust, and automatic transformations of high-content image data. A central application of our work is to microenvironment microarray bio-imaging data from the NIH LINCS program. We show that our robust transformations enhance visualization and improve the discovery of substantively relevant latent effects. These transformations enhance analysis of image features individually and also improve data integration approaches when combining together multiple features. We anticipate that the advantages of this work will likely also be realized in the analysis of data from other high-content and highly-multiplexed technologies like Cell Painting or Cyclic Immunofluorescence. Software and further analysis can be found at gjhunt.github.io/rr.

Annot: a Django-based sample, reagent, and experiment metadata tracking system

Background

In biological experiments, comprehensive experimental metadata tracking – which comprises experiment, reagent, and protocol annotation with controlled vocabulary from established ontologies – remains a challenge, especially when the experiment involves multiple laboratory scientists who execute different steps of the protocol. Here we describe Annot, a novel web application designed to provide a flexible solution for this task.

Results

Annot enforces the use of controlled vocabulary for sample and reagent annotation while enabling robust investigation, study, and protocol tracking. The cornerstone of Annot’s implementation is a json syntax-compatible file format, which can capture detailed metadata for all aspects of complex biological experiments. Data stored in this json file format can easily be ported into spreadsheet or data frame files that can be loaded into R (https://www.r-project.org/) or Pandas, Python’s data analysis library (https://pandas.pydata.org/). Annot is implemented in Python3 and utilizes the Django web framework, Postgresql, Nginx, and Debian. It is deployed via Docker and supports all major browsers.

Conclusions

Annot offers a robust solution to annotate samples, reagents, and experimental protocols for established assays where multiple laboratory scientists are involved. Further, it provides a framework to store and retrieve metadata for data analysis and integration, and therefore ensures that data generated in different experiments can be integrated and jointly analyzed. This type of solution to metadata tracking can enhance the utility of large-scale datasets, which we demonstrate here with a large-scale microenvironment microarray study.

A Multi-center Study on the Reproducibility of Drug-Response Assays in Mammalian Cell Lines

Evidence that some high-impact biomedical results cannot be repeated has stimulated interest in practices that generate findable, accessible, interoperable, and reusable (FAIR) data. Multiple papers have identified specific examples of irreproducibility, but practical ways to make data more reproducible have not been widely studied. Here, five research centers in the NIH LINCS Program Consortium investigate the reproducibility of a prototypical perturbational assay: quantifying the responsiveness of cultured cells to anti-cancer drugs. Such assays are important for drug development, studying cellular networks, and patient stratification. While many experimental and computational factors impact intra- and inter-center reproducibility, the factors most difficult to identify and control are those with a strong dependency on biological context. These factors often vary in magnitude with the drug being analyzed and with growth conditions. We provide ways to identify such context-sensitive factors, thereby improving both the theory and practice of reproducible cell-based assays.

Factors that impact the reproducibility of experimental data are poorly understood. Five NIH-LINCS centers performed the same set of drug-response measurements and compared results. Technical and biological variables that impact precision and reproducibility and are also sensitive to biological context were the most problematic.

Using Microarrays to Interrogate Microenvironmental Impact on Cellular Phenotypes in Cancer

Understanding the impact of the microenvironment on the phenotype of cells is a difficult problem due to the complex mixture of both soluble growth factors and matrix-associated proteins in the microenvironment in vivo. Furthermore, readily available reagents for the modeling of microenvironments in vitro typically utilize complex mixtures of proteins that are incompletely defined and suffer from batch to batch variability. The microenvironment microarray (MEMA) platform allows for the assessment of thousands of simple combinations of microenvironment proteins for their impact on cellular phenotypes in a single assay. The MEMAs are prepared in well plates, which allows the addition of individual ligands to separate wells containing arrayed extracellular matrix (ECM) proteins. The combination of the soluble ligand with each printed ECM forms a unique combination. A typical MEMA assay contains greater than 2,500 unique combinatorial microenvironments that cells are exposed to in a single assay. As a test case, the breast cancer cell line MCF7 was plated on the MEMA platform. Analysis of this assay identified factors that both enhance and inhibit the growth and proliferation of these cells. The MEMA platform is highly flexible and can be extended for use with other biological questions beyond cancer research.

Modeling Tumor Phenotypes In Vitro with Three-Dimensional Bioprinting

The tumor microenvironment plays a critical role in tumor growth, progression, and therapeutic resistance, but interrogating the role of specific tumor-stromal interactions on tumorigenic phenotypes is challenging within in vivo tissues. Here, we tested whether three-dimensional (3D) bioprinting could improve in vitro models by incorporating multiple cell types into scaffold-free tumor tissues with defined architecture. We generated tumor tissues from distinct subtypes of breast or pancreatic cancer in relevant microenvironments and demonstrate that this technique can model patient-specific tumors by using primary patient tissue. We assess intrinsic, extrinsic, and spatial tumorigenic phenotypes in bioprinted tissues and find that cellular proliferation, extracellular matrix deposition, and cellular migration are altered in response to extrinsic signals or therapies. Together, this work demonstrates that multi-cell-type bioprinted tissues can recapitulate aspects of in vivo neoplastic tissues and provide a manipulable system for the interrogation of multiple tumorigenic endpoints in the context of distinct tumor microenvironments.

Microenvironment-Mediated Mechanisms of Resistance to HER2 Inhibitors Differ between HER2+ Breast Cancer Subtypes

Extrinsic signals are implicated in breast cancer resistance to HER2-targeted tyrosine kinase inhibitors (TKIs). To examine how microenvironmental signals influence resistance, we monitored TKI-treated breast cancer cell lines grown on microenvironment microarrays composed of printed extracellular matrix proteins supplemented with soluble proteins. We tested ~2,500 combinations of 56 soluble and 46 matrix microenvironmental proteins on basal-like HER2+ (HER2E) or luminal-like HER2+ (L-HER2+) cells treated with the TKIs lapatinib or neratinib. In HER2E cells, hepatocyte growth factor, a ligand for MET, induced resistance that could be reversed with crizotinib, an inhibitor of MET. In L-HER2+ cells, neuregulin1-β1 (NRG1β), a ligand for HER3, induced resistance that could be reversed with pertuzumab, an inhibitor of HER2-HER3 heterodimerization. The subtype-specific responses were also observed in 3D cultures and murine xenografts. These results, along with bioinformatic pathway analysis and siRNA knockdown experiments, suggest different mechanisms of resistance specific to each HER2+ subtype: MET signaling for HER2E and HER2-HER3 heterodimerization for L-HER2+ cells.

The Library of Integrated Network-Based Cellular Signatures NIH Program: System-Level Cataloging of Human Cells Response to Perturbations

The Library of Integrated Network-Based Cellular Signatures (LINCS) is an NIH Common Fund program that catalogs how human cells globally respond to chemical, genetic, and disease perturbations. Resources generated by LINCS include experimental and computational methods, visualization tools, molecular and imaging data, and signatures. By assembling an integrated picture of the range of responses of human cells exposed to many perturbations, the LINCS program aims to better understand human disease and to advance the development of new therapies. Perturbations under study include drugs, genetic perturbations, tissue micro-environments, antibodies, and disease-causing mutations. Responses to perturbations are measured by transcript profiling, mass spectrometry, cell imaging, and biochemical methods, among other assays. The LINCS program focuses on cellular physiology shared among tissues and cell types relevant to an array of diseases, including cancer, heart disease, and neurodegenerative disorders. This Perspective describes LINCS technologies, datasets, tools, and approaches to data accessibility and reusability.

CCR5 Governs DNA Damage Repair and Breast Cancer Stem Cell Expansion

The functional significance of the chemokine receptor CCR5 in human breast cancer epithelial cells is poorly understood. Here, we report that CCR5 expression in human breast cancer correlates with poor outcome. CCR5⁺ breast cancer epithelial cells formed mammospheres and initiated tumors with >60-fold greater efficiency in mice. Reintroduction of CCR5 expression into CCR5-negative breast cancer cells promoted tumor metastases and induced DNA repair gene expression and activity. CCR5 antagonists Maraviroc and Vicriviroc dramatically enhanced cell killing mediated by DNA-damaging chemotherapeutic agents. Single-cell analysis revealed CCR5 governs PI3K/Akt, ribosomal biogenesis, and cell survival signaling. As CCR5 augments DNA repair and is reexpressed selectively on cancerous, but not normal breast epithelial cells, CCR5 inhibitors may enhance the tumor-specific activities of DNA damage response-based treatments, allowing a dose reduction of standard chemotherapy and radiation.Significance: This study offers a preclinical rationale to reposition CCR5 inhibitors to improve the treatment of breast cancer, based on their ability to enhance the tumor-specific activities of DNA-damaging chemotherapies administered in that disease. Cancer Res; 78(7); 1657-71. ©2018 AACR.

Cellular androgen content influences enzalutamide agonism of F877L mutant androgen receptor

Prostate cancer is the most commonly diagnosed and second-most lethal cancer among men in the United States. The vast majority of prostate cancer deaths are due to castration-resistant prostate cancer (CRPC) – the lethal form of the disease that has progressed despite therapies that interfere with activation of androgen receptor (AR) signaling. One emergent resistance mechanism to medical castration is synthesis of intratumoral androgens that activate the AR. This insight led to the development of the AR antagonist enzalutamide. However, resistance to enzalutamide invariably develops, and disease progression is nearly universal. One mechanism of resistance to enzalutamide is an F877L mutation in the AR ligand-binding domain that can convert enzalutamide to an agonist of AR activity. However, mechanisms that contribute to the agonist switch had not been fully clarified, and there were no therapies to block AR F877L. Using cell line models of castration-resistant prostate cancer (CRPC), we determined that cellular androgen content influences enzalutamide agonism of mutant F877L AR. Further, enzalutamide treatment of AR F877L-expressing cell lines recapitulated the effects of androgen activation of F877L AR or wild-type AR. Because the BET bromodomain inhibitor JQ-1 was previously shown to block androgen activation of wild-type AR, we tested JQ-1 in AR F877L-expressing CRPC models. We determined that JQ-1 suppressed androgen or enzalutamide activation of mutant F877L AR and suppressed growth of mutant F877L AR CRPC tumors in vivo, demonstrating a new strategy to treat tumors harboring this mutation.

Abstract P3-03-04: Sensitivity to lapatinib differs between HER2-amplified breast cancer cells harboring kinase and helical domain mutations in PIK3CA and relies on production of PIP3

Introduction: HER2 is amplified in nearly 25% of all primary breast cancers. Lapatinib is a targeted therapy that inhibits overactive HER2 signaling but invariably resistance to this targeted therapy occurs in a substantial number of patients. The PI3K-AKT axis is the major pathway downstream of HER2 signaling. Activated PI3-kinase phosphorylates the membrane lipid PIP2 resulting in PIP3. PIP3 is as a docking site for pleckstrin homology (PH) domain proteins, such as the AKT. AKT influences a variety of pathways inside the cell involving cell growth, regulation of apoptosis, glucose metabolism, and others. Mutations in the gene PIK3CA deregulate this signaling axis. In HER2 amplified cancers, co-occurrence of PIK3CA mutations have been reported in approximately 20% of cases. Hotspot mutations of PIK3CA translate to changes in either the helical domain (E545K) or kinase domain (H1047R) of the protein and these two hotspots comprise over 80% of all reported oncogenic mutations across all tumor types. Crystallographic studies have shown conformational differences between the two hotspot mutations in PIK3CA, yet it is unclear if functional differences exist between the two mutations.

Methods: We generated isogenic knockin mutants of the helical domain (E545K) and kinase domain (H1047R) of PIK3CA in the HER2-amplified breast cancer cell line SK-BR-3. Mutant and parental cell lines were subjected to drug sensitivity assays measured by cell growth during prolonged exposure to drug. We investigated changes of relevant intracellular signaling pathways via western blot analysis. Additionally, we used immunofluorescence of PIP3 and confocal microscopy to visualize cellular differences in the production of this signaling molecule.

Results: Our results demonstrate a distinction between the helical domain (E545K) and kinase domain (H1047R) mutations of PIK3CA. Mutations in the helical domain do not confer resistance to lapatinib while mutations in the kinase domain do. This is a result of sustained AKT signaling even in the presence of high dose lapatinib in cells with the kinase domain mutation. We also show the PTEN loss phenocopies this phenomenon. Finally, we show that kinase domain mutations allow the protein to generate significantly higher levels of PIP3 which is the necessary molecule for downstream signaling through AKT but helical domain mutations do not.

Conclusion: This phenotypic disparity between helical and kinase domain mutations of PIK3CA has important clinical implications. It is possible to imagine that in a heterogeneous tumor in which some cells are wildtype and some cells carry this mutation for PIK3CA treatment with lapatinib will select for cells with the mutation conferring a growth advantage. Our results show that only H1047R mutant cells demonstrate lapatinib resistance and this is achieved via sustained AKT signaling through continual production of PIP3. Altogether, we demonstrate a mechanism of de novo resistance to HER2-targeted therapy in breast cancer.

Citation Format: Garay JP, Korkola JE, Gray JW. Sensitivity to lapatinib differs between HER2-amplified breast cancer cells harboring kinase and helical domain mutations in PIK3CA and relies on production of PIP3 [abstract]. In: Proceedings of the 2016 San Antonio Breast Cancer Symposium; 2016 Dec 6-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2017;77(4 Suppl):Abstract nr P3-03-04.

Abstract PD5-01: Microenvironment microarrays show that microenvironment mediated resistance mechanisms to lapatinib differ between basal and luminal HER2+ cells

Cell lines represent a valuable model system for the study of breast cancer, as they capture the cellular diversity, mutational spectrum, expression subtypes, and genomic alterations that are observed in clinical specimens. However, like any model system, cell lines are imperfect, particularly when it comes to capturing the effects of the myriad of signals and interactions they encounter in their microenvironment (ME). We are utilizing a technology known as microenvironment microarrays (MEMA) to begin to unravel the consequences of interactions of breast cancer cells with the ME. MEMA consist of thousands of unique combinations of insoluble matrix proteins that are printed to form growth pads with ligands added to the media. Cells are grown on the MEMA spots and the effects of the specific ME that they are exposed to can be read out using immunofluorescent stains of interest. When combined with automated imaging and sophisticated image processing and analysis, the MEMA platform enables the identification of specific ME conditions that alter the phenotypes of cells. We have applied MEMA to understand both baseline responses to the ME as well as how the ME might mediate response to therapeutics. We performed a pilot experiment to investigate the effects of the ME on the response to the HER2-targeted inhibitor lapatinib. We found that HCC1954 cells continued to proliferate robustly in the presence of HGF when treated with 500 nM lapatinib. In contrast, AU565 cells were proliferative in the presence of NRG1 and lapatinib, but not HGF. Focused follow up studies showed that HGF is effective in rescuing only basal HER2+ cells, while NRG1 is effective in rescuing only luminal subtype HER2+cells. Rescue with the relevant growth factor was also observed in 3-d matrigel studies, showing this was not an artifact of the 2-d culture system. We investigated the effects of drug combinations using lapatinib plus drugs that target either MET (Crizotinib) or HER3-HER2 dimers (pertuzumab). These drug combinations were able to overcome the resistance mediated by HGF and NRG1 in basal and luminal cells respectively. We found the effectiveness of pertuzumab particularly interesting, given that lapatinib should still be inhibiting HER2 kinase activity. Parallel studies found that inhibitors targeting other kinase receptors such as IGF1R partially restored sensitivity to HER2 in the presence of NRG1, suggesting a role for such receptors in the resistance. Immunoprecipitation studies showed that IGF1R co-immunoprecipitated with HER2/HER3 when pertuzumab was absent, but that additional of pertuzumab abrogated the binding of IGF1R to HER3, suggesting the formation of HER2-dependent higher order structures that can signal even when HER2 is inhibited. These studies highlight the importance of understanding the effects of the ME on cancer cells, and demonstrate the differences between ME factors that can confer resistance to HER2 targeted inhibitors in basal and luminal HER2+ cells. These findings suggest that both subtype and ME composition may be important in determining response to combinatorial treatments and may be useful to inform clinical decision making.

Citation Format: Korkola JE, Watson S, Smith R, Thompson W, Dame M, Liby T, Bucher E, Sudar D, Nederlof M, Heiser L, Gray JW. Microenvironment microarrays show that microenvironment mediated resistance mechanisms to lapatinib differ between basal and luminal HER2+ cells [abstract]. In: Proceedings of the 2016 San Antonio Breast Cancer Symposium; 2016 Dec 6-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2017;77(4 Suppl):Abstract nr PD5-01.

Context Specificity in Causal Signaling Networks Revealed by Phosphoprotein Profiling

Signaling networks downstream of receptor tyrosine kinases are among the most extensively studied biological networks, but new approaches are needed to elucidate causal relationships between network components and understand how such relationships are influenced by biological context and disease. Here, we investigate the context specificity of signaling networks within a causal conceptual framework using reverse-phase protein array time-course assays and network analysis approaches. We focus on a well-defined set of signaling proteins profiled under inhibition with five kinase inhibitors in 32 contexts: four breast cancer cell lines (MCF7, UACC812, BT20, and BT549) under eight stimulus conditions. The data, spanning multiple pathways and comprising ∼70,000 phosphoprotein and ∼260,000 protein measurements, provide a wealth of testable, context-specific hypotheses, several of which we experimentally validate. Furthermore, the data provide a unique resource for computational methods development, permitting empirical assessment of causal network learning in a complex, mammalian setting.

Time-course assays of signaling proteins in cancer cell lines under kinase inhibition

Causal conceptual framework for network analysis

Data shed light on causal protein networks that are specific to biological context

Resource for signaling biology and for benchmarking computational methods

Abstract 1347: NTRK1/TRKA as a therapeutic target in castration resistant prostate cancer

Treatment options remain limited for men with castration resistant prostate cancer, with current chemotherapy offering mainly palliative benefits. Thus, there is an urgent need to identify new targets for therapeutic intervention in men who have progressed on anti-androgen therapy. We have compiled a panel of 20 prostate cancer cell lines that has been extensively characterized at the molecular level that enables us to perform high throughput drug and siRNA screens to identify novel therapeutic targets. We performed an siRNA screen targeting kinases using eight representative lines, both in the presence and absence of the anti-androgen MDV3100. Knockdown of NTRK1 (TRKA) significantly inhibited growth in 4/8 of the cell lines tested. To confirm this, we screened the entire panel of cell lines with the inhibitor CEP-701, which targets FLT3, JAK2, and TRK-A/B/C. CEP-701 showed GI50 values (dose required to inhibit growth by 50%) less than 400 nM in 8/20 cell lines. Since this drug had already been tested in clinical trials for prostate cancer and the trials were discontinued due to lack of PSA decline, we looked for other drugs that also inhibit TRKA. Both BIBF-1120 and GSK-1363089 are also known to inhibit TRKA, but neither have been tested in prostate cancer expressing TRKA. We tested GSK-136089 in a subset of 9 prostate cell lines, and found that 4/9 lines reached GI50 at 1 uM or less, including AR mutant or null lines such as 22rv1 and PC3 that are non-responsive to MDV3100. Additional tests with BIBF-1120 and GSK-1363089 are underway. These data suggest that NTRK1 may be a potential target for patients with castration resistant prostate cancer.

Citation Format: James E. Korkola, Moqing Liu, Rebecca Smith, Tiera Liby, Joe W. Gray. NTRK1/TRKA as a therapeutic target in castration resistant prostate cancer. [abstract]. In: Proceedings of the 107th Annual Meeting of the American Association for Cancer Research; 2016 Apr 16-20; New Orleans, LA. Philadelphia (PA): AACR; Cancer Res 2016;76(14 Suppl):Abstract nr 1347.

Genome co-amplification upregulates a mitotic gene network activity that predicts outcome and response to mitotic protein inhibitors in breast cancer

BACKGROUND

High mitotic activity is associated with the genesis and progression of many cancers. Small molecule inhibitors of mitotic apparatus proteins are now being developed and evaluated clinically as anticancer agents. With clinical trials of several of these experimental compounds underway, it is important to understand the molecular mechanisms that determine high mitotic activity, identify tumor subtypes that carry molecular aberrations that confer high mitotic activity, and to develop molecular markers that distinguish which tumors will be most responsive to mitotic apparatus inhibitors.

METHODS

We identified a coordinately regulated mitotic apparatus network by analyzing gene expression profiles for 53 malignant and non-malignant human breast cancer cell lines and two separate primary breast tumor datasets. We defined the mitotic network activity index (MNAI) as the sum of the transcriptional levels of the 54 coordinately regulated mitotic apparatus genes. The effect of those genes on cell growth was evaluated by small interfering RNA (siRNA).

RESULTS

High MNAI was enriched in basal-like breast tumors and was associated with reduced survival duration and preferential sensitivity to inhibitors of the mitotic apparatus proteins, polo-like kinase, centromere associated protein E and aurora kinase designated GSK462364, GSK923295 and GSK1070916, respectively. Co-amplification of regions of chromosomes 8q24, 10p15-p12, 12p13, and 17q24-q25 was associated with the transcriptional upregulation of this network of 54 mitotic apparatus genes, and we identify transcription factors that localize to these regions and putatively regulate mitotic activity. Knockdown of the mitotic network by siRNA identified 22 genes that might be considered as additional therapeutic targets for this clinically relevant patient subgroup.

CONCLUSIONS

We define a molecular signature which may guide therapeutic approaches for tumors with high mitotic network activity.

Mechanism and Role of SOX2 Repression in Seminoma: Relevance to Human Germline Specification

Human male germ cell tumors (GCTs) are derived from primordial germ cells (PGCs). The master pluripotency regulator and neuroectodermal lineage effector transcription factor SOX2 is repressed in PGCs and the seminoma (SEM) subset of GCTs. The mechanism of SOX2 repression and its significance to GC and GCT development currently are not understood. Here, we show that SOX2 repression in SEM-derived TCam-2 cells is mediated by the Polycomb repressive complex (PcG) and the repressive H3K27me3 chromatin mark that are enriched at its promoter. Furthermore, SOX2 repression in TCam-2 cells can be abrogated by recruitment of the constitutively expressed H3K27 demethylase UTX to the SOX2 promoter through retinoid signaling, leading to expression of neuronal and other lineage genes. SOX17 has been shown to initiate human PGC specification, with its target PRDM1 suppressing mesendodermal genes. Our results are consistent with a role for SOX2 repression in normal germline development by suppressing neuroectodermal genes.

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SOX2 is repressed in hPGC, germ cell neoplasia in situ, and seminoma

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SOX2 repression is mediated by PcG and H3K27me3 enrichment at its promoter

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Retinoid signaling recruits UTX to SOX2 promoter leading to reactivation of SOX2

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These studies shed light on the role of SOX2 in germline development

Development and Validation of a Gene-Based Model for Outcome Prediction in Germ Cell Tumors Using a Combined Genomic and Expression Profiling Approach

Germ Cell Tumors (GCT) have a high cure rate, but we currently lack the ability to accurately identify the small subset of patients who will die from their disease. We used a combined genomic and expression profiling approach to identify genomic regions and underlying genes that are predictive of outcome in GCT patients. We performed array-based comparative genomic hybridization (CGH) on 53 non-seminomatous GCTs (NSGCTs) treated with cisplatin based chemotherapy and defined altered genomic regions using Circular Binary Segmentation. We identified 14 regions associated with two year disease-free survival (2yDFS) and 16 regions associated with five year disease-specific survival (5yDSS). From corresponding expression data, we identified 101 probe sets that showed significant changes in expression. We built several models based on these differentially expressed genes, then tested them in an independent validation set of 54 NSGCTs. These predictive models correctly classified outcome in 64–79.6% of patients in the validation set, depending on the endpoint utilized. Survival analysis demonstrated a significant separation of patients with good versus poor predicted outcome when using a combined gene set model. Multivariate analysis using clinical risk classification with the combined gene model indicated that they were independent prognostic markers. This novel set of predictive genes from altered genomic regions is almost entirely independent of our previously identified set of predictive genes for patients with NSGCTs. These genes may aid in the identification of the small subset of patients who are at high risk of poor outcome.

Interrogation of a context-specific transcription factor network identifies novel regulators of pluripotency

The predominant view of pluripotency regulation proposes a stable ground state with coordinated expression of key transcription factors (TFs) that prohibit differentiation. Another perspective suggests a more complexly regulated state involving competition between multiple lineage-specifying TFs that define pluripotency. These contrasting views were developed from extensive analyses of TFs in pluripotent cells in vitro. An experimentally validated, genome-wide repertoire of the regulatory interactions that control pluripotency within the in vivo cellular contexts is yet to be developed. To address this limitation, we assembled a TF interactome of adult human male germ cell tumors (GCTs) using the Algorithm for the Accurate Reconstruction of Cellular Pathways (ARACNe) to analyze gene expression profiles of 141 tumors comprising pluripotent and differentiated subsets. The network (GCT(Net)) comprised 1,305 TFs, and its ingenuity pathway analysis identified pluripotency and embryonal development as the top functional pathways. We experimentally validated GCT(Net) by functional (silencing) and biochemical (ChIP-seq) analysis of the core pluripotency regulatory TFs POU5F1, NANOG, and SOX2 in relation to their targets predicted by ARACNe. To define the extent of the in vivo pluripotency network in this system, we ranked all TFs in the GCT(Net) according to sharing of ARACNe-predicted targets with those of POU5F1 and NANOG using an odds-ratio analysis method. To validate this network, we silenced the top 10 TFs in the network in H9 embryonic stem cells. Silencing of each led to downregulation of pluripotency and induction of lineage; 7 of the 10 TFs were identified as pluripotency regulators for the first time.

Exome Sequencing of Cell-Free DNA from Metastatic Cancer Patients Identifies Clinically Actionable Mutations Distinct from Primary Disease

The identification of the molecular drivers of cancer by sequencing is the backbone of precision medicine and the basis of personalized therapy; however, biopsies of primary tumors provide only a snapshot of the evolution of the disease and may miss potential therapeutic targets, especially in the metastatic setting. A liquid biopsy, in the form of cell-free DNA (cfDNA) sequencing, has the potential to capture the inter- and intra-tumoral heterogeneity present in metastatic disease, and, through serial blood draws, track the evolution of the tumor genome.

In order to determine the clinical utility of cfDNA sequencing we performed whole-exome sequencing on cfDNA and tumor DNA from two patients with metastatic disease; only minor modifications to our sequencing and analysis pipelines were required for sequencing and mutation calling of cfDNA. The first patient had metastatic sarcoma and 47 of 48 mutations present in the primary tumor were also found in the cell-free DNA. The second patient had metastatic breast cancer and sequencing identified an ESR1 mutation in the cfDNA and metastatic site, but not in the primary tumor. This likely explains tumor progression on Anastrozole. Significant heterogeneity between the primary and metastatic tumors, with cfDNA reflecting the metastases, suggested separation from the primary lesion early in tumor evolution. This is best illustrated by an activating PIK3CA mutation (H1047R) which was clonal in the primary tumor, but completely absent from either the metastasis or cfDNA. Here we show that cfDNA sequencing supplies clinically actionable information with minimal risks compared to metastatic biopsies. This study demonstrates the utility of whole-exome sequencing of cell-free DNA from patients with metastatic disease. cfDNA sequencing identified an ESR1 mutation, potentially explaining a patient’s resistance to aromatase inhibition, and gave insight into how metastatic lesions differ from the primary tumor.

Erratum to: Modeling precision treatment of breast cancer

During the type-setting of the final version of the article [1] some of the additional files were swapped. The correct files are republished in this Erratum.

Abstract S6-07: Detrimental effects of sequential compared to concurrent treatment of pertuzumab plus T-DM1 in HER2+ breast cancer cell lines

Background. Pertuzumab and T-DM1 are two recently approved monoclonal antibody based therapies targeting HER2+ breast cancer. Pertuzumab interferes with dimerization of HER family members, while T-DM1 binds to HER2 and interferes with its oncogenic function while also specifically delivering a cytotoxic agent (emtansine). One arm of the I-SPY 2 clinical trial is to investigate the efficacy of a combination Pertuzumab plus T-DM1 in HER2+ breast cancer patients. Methods. We performed pre-clinical screening of response to each agent alone and in combination in a set of 21 HER2+ breast cancer cell lines, with an end goal of identifying markers of response to the therapies. There were five treatment regimens employed in the initial screen: i) pertuzumab alone for 72 h; ii) T-DM1 alone for 72h; iii) pertuzumab plus T-DM1 concurrently for 72h; iv) pertuzumab for 24h followed by addition of T-DM1 for 48h more; and iv) T-DM1 for 24h followed by addition of pertuzumab for 48h more. Response was assessed using the Cell Titer Glo assay as a measure of cell viability. To assess the effects of drug combinations, we used a stringent measure of synergy and antagonism employing the median effect method of Chou and Talalay that included 95% confidence intervals to determine significance. Results. Initial screens showed that concurrent treatment of cells with pertuzumab plus T-DM1 gave significant synergistic interactions in 15/21 cell lines as measured by the median effect method, with combination indices (CI) less than 0.5 (and 95% upper confidence levels less than 1.0) for at least one drug concentration. However, 24h pretreatment with pertuzumab followed by T-DM1 significantly diminished the response of cells to T-DM1, resulting in significant antagonism in 17/21 cell lines test (CI>1.5, lower confidence level greater than 1). Since this could be due to a shorter exposure time to T-DM1, and since patients are scheduled to be treated with pertuzumab first followed by T-DM1 one hour later, we repeated the experiment with one hour between pertuzumab and T-DM1 rather than 24h. While the inhibitory effect was diminished, this treatment regimen still resulted in significant antagonism when T-DM1 was given 1 hour after pertuzumab in 5/5 cell lines tested, in contrast to concurrent pertuzumab plus T-DM1 treatment, which showed synergy. Conclusions. Pertuzumab plus T-DM1 appears to be beneficial when given concurrently, but pretreatment with pertuzumab appears to blunt the efficacy of T-DM1. This has important potential ramifications for patient treatment, and may further elucidate mechanisms of action for both compounds. Further testing will be necessary to determine whether these timing effects are operational in vivo and whether immune effects mitigate the antagonism.

Citation Format: James E Korkola, Moqing Liu, Tiera Liby, Laura Heiser, Heidi Feiler, Joe W Gray. Detrimental effects of sequential compared to concurrent treatment of pertuzumab plus T-DM1 in HER2+ breast cancer cell lines [abstract]. In: Proceedings of the Thirty-Seventh Annual CTRC-AACR San Antonio Breast Cancer Symposium: 2014 Dec 9-13; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2015;75(9 Suppl):Abstract nr S6-07.

Abstract 2387: Activation of Inhibin A signaling is associated with a basal-like HER2 subtype and resistance to lapatinib in breast cancer cell lines

HER2 amplification occurs in ∼20% of all breast cancers, and is associated with poor prognosis. Targeted therapeutics such as trastuzumab and lapatinib have been developed and have improved outcomes for patients with HER2+ disease. However, a significant proportion of patients have tumors that either develop resistance or simply fail to respond to these therapies at all. To better understand the mechanism of resistance, we screened a panel of 22 HER2+ breast cancer cell lines with lapatinib. Of these, 6 showed significant resistance, failing to reach 50% growth inhibition (GI50) even at 5uM, the highest dose tested. The resistant lines were all more basal-like in expression patterns, and were more responsive to MEK inhibitors than their luminal-like counterparts. These two patterns of expression are similar to the different HER2 subtypes recently identified by the TCGA project. Differential expression analysis utilizing t-tests with Benjamini-Hochberg correction for multiple comparisons identified approximately 150 transcripts that were more highly expressed in resistant cell lines. We performed high-throughput screening using siRNA knockdown of the target genes in combination with lapatinib treatment. Staining for markers of proliferation (Ki67), apoptosis (cleaved PARP), and activity of the PI3K-AKT pathway showed that silencing of inhibin A resulted in a decrease in the ratio of proliferative to apoptotic cells in the resistant cell lines 21-NT and 21-PT. Concurrent with this decrease was a down-regulation of both p-MAPK and p-AKT. GO analysis revealed a strong enrichment for Inhibin A signaling amongst the 150 resistance associated transcripts. Mining of tumor databases revealed that there was a trend between high levels of Inhibin A expression and poor outcome in HER2 positive tumors (p=0.08). These data suggest that activation of Inhibin A signaling is associated with a more basal like subclass of HER2+ tumors, resistance to HER2 targeted therapeutics such as lapatinib, and that corresponding over-expression of Inhibin A is associated with poor outcome in HER2+ patients.

Citation Format: James E. Korkola, Juha Rantala, Nora Bayani, Laura Heiser, Nicholas Wang, Obi Griffith, Joe Gray. Activation of Inhibin A signaling is associated with a basal-like HER2 subtype and resistance to lapatinib in breast cancer cell lines. [abstract]. In: Proceedings of the 104th Annual Meeting of the American Association for Cancer Research; 2013 Apr 6-10; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2013;73(8 Suppl):Abstract nr 2387. doi:10.1158/1538-7445.AM2013-2387

Cross-platform pathway-based analysis identifies markers of response to the PARP inhibitor olaparib

Poly(ADP-ribose) polymerase (PARP) is an enzyme involved in DNA repair. PARP inhibitors can act as chemosensitizers, or operate on the principle of synthetic lethality when used as single agent. Clinical trials have shown drugs in this class to be promising for BRCA mutation carriers. We postulated that inability to demonstrate response in non-BRCA carriers in which BRCA is inactivated by other mechanisms or with deficiency in homologous recombination for DNA repair is due to lack of molecular markers that define a responding subpopulation. We identified candidate markers for this purpose for olaparib (AstraZeneca) by measuring inhibitory effects of nine concentrations of olaparib in 22 breast cancer cell lines and identifying features in transcriptional and genome copy number profiles that were significantly correlated with response. We emphasized in this discovery process genes involved in DNA repair. We found that the cell lines that were sensitive to olaparib had a significant lower copy number of BRCA1 compared to the resistant cell lines (p value 0.012). In addition, we discovered seven genes from DNA repair pathways whose transcriptional levels were associated with response. These included five genes (BRCA1, MRE11A, NBS1, TDG, and XPA) whose transcript levels were associated with resistance and two genes (CHEK2 and MK2) whose transcript levels were associated with sensitivity. We developed an algorithm to predict response using the seven-gene transcription levels and applied it to 1,846 invasive breast cancer samples from 8 U133A/plus 2 (Affymetrix) data sets and found that 8–21 % of patients would be predicted to be responsive to olaparib. A similar response frequency was predicted in 536 samples analyzed on an Agilent platform. Importantly, tumors predicted to respond were enriched in basal subtype tumors. Our studies support clinical evaluation of the utility of our seven-gene signature as a predictor of response to olaparib.

A central role for RAF→MEK→ERK signaling in the genesis of pancreatic ductal adenocarcinoma

KRAS mutation is a hallmark of pancreatic ductal adenocarcinoma (PDA) but remains an intractable pharmacologic target. Consequently, defining RAS effector pathway(s) required for PDA initiation and maintenance is critical to improve treatment of this disease. Here, we show that expression of BRAF(V600E), but not PIK3CA(H1047R), in the mouse pancreas leads to pancreatic intraepithelial neoplasia (PanIN) lesions. Moreover, concomitant expression of BRAF(V600E) and TP53(R270H) result in lethal PDA. We tested pharmacologic inhibitors of RAS effectors against multiple human PDA cell lines. Mitogen-activated protein (MAP)/extracellular signal-regulated (ERK) kinase (MEK) inhibition was highly effective both in vivo and in vitro and was synergistic with AKT inhibition in most cell lines tested. We show that RAF→MEK→ERK signaling is central to the initiation and maintenance of PDA and to rational combination strategies in this disease. These results emphasize the value of leveraging multiple complementary experimental systems to prioritize pathways for effective intervention strategies in PDA.

SIGNIFICANCE

PDA is diffi cult to treat, in large part, due to recurrent mutations in the KRAS gene. Here, we defi ne rational treatment approaches for the disease achievable today with existing drug combinations by thorough genetic and pharmacologic dissection of the major KRAS effector pathways, RAF→MEK→ERK and phosphoinositide 3′-kinase (PI3'K)→AKT.

The transcription factor ZNF217 is a prognostic biomarker and therapeutic target during breast cancer progression

The transcription factor ZNF217 is a candidate oncogene in the amplicon on chromosome 20q13 that occurs in 20% to 30% of primary human breast cancers and that correlates with poor prognosis. We show that Znf217 overexpression drives aberrant differentiation and signaling events, promotes increased self-renewal capacity, mesenchymal marker expression, motility, and metastasis, and represses an adult tissue stem cell gene signature downregulated in cancers. By in silico screening, we identified candidate therapeutics that at low concentrations inhibit growth of cancer cells expressing high ZNF217. We show that the nucleoside analogue triciribine inhibits ZNF217-induced tumor growth and chemotherapy resistance and inhibits signaling events [e.g., phospho-AKT, phospho-mitogen-activated protein kinase (MAPK)] in vivo. Our data suggest that ZNF217 is a biomarker of poor prognosis and a therapeutic target in patients with breast cancer and that triciribine may be part of a personalized treatment strategy in patients overexpressing ZNF217. Because ZNF217 is amplified in numerous cancers, these results have implications for other cancers.

SIGNIFICANCE

This study finds that ZNF217 is a poor prognostic indicator and therapeutic target in patients with breast cancer and may be a strong biomarker of triciribine treatment efficacy in patients. Because previous clinical trials for triciribine did not include biomarkers of treatment efficacy, this study provides a rationale for revisiting triciribine in the clinical setting as a therapy for patients with breast cancer who overexpress ZNF217.

A genetic strategy for single and combinatorial analysis of miRNA function in mammalian hematopoietic stem cells

The regulatory role of micro-RNAs (miRNAs) in hematopoietic development is increasingly appreciated. Reverse genetics strategies based on the targeted disruption of miRNAs offer a powerful tool to study miRNA functions in mammalian hematopoiesis. The miR-144/451 cluster comprises two miRNAs coexpressed from a common precursor transcript in an erythroid-specific manner. To decipher the contribution of each miRNA of the cluster in mammalian erythropoiesis, we developed a strategy for stable in vivo individual and combinatorial miRNA inhibition. We developed decoy target sequences for each miRNA expressed by lentiviral vectors marked with distinct fluorescent proteins and used them to probe the functions of miR-144 and miR-451 in the murine hematopoietic system in a competitive repopulation setting. Murine hematopoietic chimeras expressing lentiviral-encoded inhibitory sequences specific for miR-144 or miR-451 exhibited markedly reduced Ter119(+) erythroblast counts, with the combined knockdown showing additive effect. These chimeras showed abnormal patterns of erythroid differentiation primarily affecting the proerythroblast to basophilic erythroblast transition, coinciding with the stage where expression of the miRNA cluster is dramatically induced and posttranscriptional gene regulation becomes prominent. These results reveal a role for the miR-144/451 locus in mammalian erythropoiesis and provide the first evidence of functional cooperativity between clustered miRNAs in the hematopoietic system. The strategy described herein will prove useful in functional miRNA studies in mammalian hematopoietic stem cells.

Abstract 4240: Transcription factor networks that regulate pluripotency and lineage differentiation in adult human male germ cell tumors

Recent interest and effort have been focused on identification of transcription factors (TFs) and TF networks that regulate pluripotency and lineage differentiation in human and murine cells. Yet, a complete repertoire of regulatory interactions supporting these processes remains elusive. Embryonic stem (ES) cells, induced pluripotent (iPS) cells, and embryonal carcinoma (EC) cells derived from germ cell tumors (GCTs) comprise the three classic pluripotent cell types. EC cells exhibit, in vivo and in vitro, many properties in common with ES cells, making them an excellent system to study pluripotency and lineage differentiation. We previously characterized the gene expression profile (GEP) of a panel of 135 GCT biopsies comprising all described in vivo differentiation lineages and 6 normal testes as controls, using the Affymetrix U133A+B arrays (Korkola et al. Cancer Res., 66: 820-7, 2006 and J. Clin. Oncol., 27: 5240-7, 2009). These GEP data were analyzed using the ARACNe reverse engineering algorithm (Basso et al., Nat. Genet., 37: 382-90, 2005) to reconstruct a global transcriptional interaction network regulating pluripotency and lineage differentiation in these tumors. The ensuing interactome, comprising 1312 TFs, displayed three strongly intra-connected modules: Module A, including 187 genes associated with regulation of development and differentiation, Module B, including 89 genes associated with regulation of immune response and B-cell development, and Module C, including 80 genes associated with regulation of transcription. Furthermore, the interactome recapitulated 830 regulatory targets of the core pluripotency TFs, POU5F1, NANOG, and SOX2 (369 of POU5F1, 375 of NANOG, and 306 of SOX2). Validation of these targets by ChIP-PCR and ChIP-seq in NT2/D1 (EC) and H9 (ES) cells revealed that all of the top 10 target genes of POU5F1 (NANOG, FAM46B, L1TD1, DND1, ZYG11, FRAT2, DPPA4, ARGEF1, KLRG2 and CBR3) and SOX2 (SEPHS1, PLCB2, ZNF518, ECE2, SLC26A3, GPM6B, PHLDA2, PATZ1, ADRB3 and MAP1A) could specifically bind the corresponding TF in their promoter regions, within both cell types. For NANOG, 9 of the top 10 targets (POU5F1, FAM46B, DPPA4, L1TD1, UTF1, FRAT2, RAB15, TEAD4 and ZYG11A) showed specific promoter binding of the TF in both cell types, while one target (DND1) showed specific binding only in H9 cells. ChIP-seq analysis was consistent with the results of ChIP-PCR. We sought functional validation of the targets by performing lentivirus-mediated shRNA silencing of POU5F1 in NT2/D1 cells. Results showed that the ARACNe-inferred targets were both positively and negatively regulated, consistently with regulation of pluripotency and/or differentiation. Taken together, these results define a novel and highly accurate regulatory model for the systems biology study of TFs involved in regulation of pluripotency and lineage differentiation in mammalian cells.

Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 101st Annual Meeting of the American Association for Cancer Research; 2010 Apr 17-21; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2010;70(8 Suppl):Abstract nr 4240.

Molecular events in germ cell tumours: linking chromosome-12 gain, acquisition of pluripotency and response to cisplatin

Germ cell tumours (GCTs) represent the leading cause of cancer-related morbidity and mortality in young men aged 18-35 years. Transformation of the cell of origin results in tumours with several unique properties. GCTs are characterized by gain of the short arm of chromosome 12 in almost all cases, a frequency of genomic alteration not seen in any other solid tumours. GCTs are truly pluripotent, giving rise to cells of somatic and extra-embryonic lineages, which results in tumours with a spectrum of differentiation that rivals that seen in normal embryogenesis and development. Despite the presence of genomic instability and many oncogenic changes, GCTs are highly curable, even in the metastatic setting, due to their extreme sensitivity to cisplatin-based chemotherapy. In this review we highlight some of the molecular events associated with the genesis, differentiation and chemotherapeutic response of these tumours, and discuss how these alterations are linked with biological features unique to germ cells.

Identification and validation of a gene expression signature that predicts outcome in adult men with germ cell tumors

PURPOSE

Germ cell tumor (GCT) is the most common malignancy in young adult men. Currently, patients are risk-stratified on the basis of clinical presentation and serum tumor markers. The introduction of molecular markers could improve outcome prediction.

PATIENTS AND METHODS

Expression profiling was performed on 74 nonseminomatous GCTs (NSGCTs) from cisplatin-treated patients (ie, training set) and on 34 similarly treated patients with NSGCTs (ie, validation set). A gene classifier was developed by using prediction analysis for microarrays (PAM) for the binary end point of 5-year overall survival (OS). A predictive score was developed for OS by using the univariate Cox model.

RESULTS

In the training set, PAM identified 140 genes that predicted 5-year OS (cross-validated classification rate, 60%). The PAM model correctly classified 90% of patients in the validation set. Patients predicted to have good outcome had significantly longer survival than those with poor predicted outcome (P < .001). For the OS end point, a 10-gene model had a predictive accuracy (ie, concordance index) of 0.66 in the training set and a concordance index of 0.83 in the validation set. Dichotomization of the samples on the basis of the median score resulted in significant differences in survival (P = .002). For both end points, the gene-based predictor was an independent prognostic factor in a multivariate model that included clinical risk stratification (P < .01 for both).

CONCLUSION

We have identified gene expression signatures that accurately predict outcome in patients with GCTs. These predictive genes should be useful for the prediction of patient outcome and could provide novel targets for therapeutic intervention.

Interferon-α Resistance Associated Genes in Renal Cell Carcinoma Identified by Expression Profiling

PURPOSE

We identified differentially expressed genes associated with response to pegylated interferon-alpha treatment in patients with renal cell carcinoma.

MATERIALS AND METHODS

We performed expression profiling on renal cell carcinoma specimens isolated from 23 patients with metastatic disease who were subsequently treated with interferon. Significance Analysis for Microarrays software was used to identify genes that were differentially expressed between patients with partial response compared to those with disease progression.

RESULTS

A candidate gene approach looking at VHL and known target genes did not identify any genes whose expression correlated with patient response. A global analysis of approximately 54,000 probe sets identified 4 genes that had expression correlated with response. Reverse transcriptase-polymerase chain reaction analysis of 2 of these genes confirmed that they were more highly expressed in tumors from patients who responded to interferon-alpha. Interestingly, both of these genes mapped to 4q31-32, a region that has been implicated as the site of a potential tumor suppressor gene in renal cell carcinoma.

CONCLUSIONS

We have identified 4 genes (3 uncharacterized and 1 known) that may prove useful in predicting response to interferon-alpha treatment in patients with renal cell carcinoma.

Biology and Genetics of Adult Male Germ Cell Tumors

Adult male germ cell tumors (GCTs) arise by transformation of totipotent germ cells. They have the unique potential to activate molecular pathways, in part mimicking those occurring during gametogenesis and normal human development, as evidenced by the array of histopathologies observed in vivo. Recent expression profiling studies of GCTs along with advances in embryonic stem-cell research have contributed to our understanding of the underlying biology of the disease. Gain of the short arm of chromosome 12 detected in almost all adult GCTs appears to be multifunctional in germ cell tumorigenesis on the basis of the observed overexpression of genes mapped to this region involved in maintenance of pluripotency and oncogenesis. Expression signatures associated with the different histopathologies have yielded clues as to the functional mechanisms involved in GCT invasion, loss of pluripotency, and lineage differentiation. Genomic and epigenomic abnormalities that contribute to or cause these events have been identified by traditional genome analyses and continue to be revealed as genome-scanning technologies develop. Given the high sensitivity of most GCTs to cisplatin-based treatment, these tumors serve as an excellent model system for the identification of factors associated with drug resistance, including differentiation status and acquisition of genomic alterations. Overall, adult male GCTs provide a unique opportunity for the examination of functional links between transformation and pluripotency, genomic and epigenomic abnormalities and lineage differentiation, and the identification of genetic features associated with chemotherapy resistance.

Constitutive gene expression predisposes morphogen-mediated cell fate responses of NT2/D1 and 27X-1 human embryonal carcinoma cells

Human embryonal carcinoma (EC) cell lines exhibit considerable heterogeneity in their levels of pluripotency. Thus, NT2/D1 cells differentiate into neural lineages upon exposure to all-trans retinoic acid (ATRA) and non-neural epithelial lineages upon exposure to bone morphogenetic protein-2 (BMP-2). In contrast, 27X-1 cells differentiate into extra-embryonic endodermal (ExE) cells upon treatment with either morphogen. To understand the molecular basis for the differential responses of the two cell lines, we performed gene expression profiling at the undifferentiated EC cell line state to identify constitutive differences in gene expression. NT2/D1 cells preferentially expressed transcripts associated with neurectodermal development, whereas 27X-1 cells expressed high levels of transcripts associated with mesendodermal characteristics. We then determined temporal expression profiles of 27X-1 cells during ExE differentiation upon treatment with ATRA and BMP-2 and compared the data with changes in gene expression observed during BMP-2- and ATRA-induced differentiation of NT2/D1 cells. ATRA and BMP-2 induced distinct sets of transcription factors and phenotypic markers in the two EC cell lines, underlying distinct lineage choices. Although 27X-1 differentiation yielded comprehensive gene expression profiles of parietal endodermal lineages, we were able to use the combined analysis of 27X-1 data with data derived from yolk sac tumors for the identification of transcripts associated with visceral endoderm formation. Our results demonstrate constitutive differences in the levels of pluripotency between NT2/D1 and 27X-1 cells that correlate with lineage potential. This study also demonstrates that EC cells can serve as robust models to investigate early lineage choices during both embryonic and extra-embryonic human development.

Transcriptional Program Associated with IFN-αResponse of Renal Cell Carcinoma

Metastatic renal cell carcinoma (RCC) is refractory to therapy; however, 10%-20% of patients respond favorably with interferon-alpha (IFN-alpha) treatment. To understand the molecular basis of response to IFN-alpha therapy, we performed global gene expression analysis of sensitive and resistant RCC cell lines in the absence and in the presence of IFN-alpha, using high-density oligonucleotide arrays to detect differentially expressed genes. In the absence of IFN-alpha, no significant differences in gene expression were observed between six sensitive and six resistant cell lines. Gene expression analysis following a time course of IFN-alpha2b treatment in one sensitive (SK-RC-17) and one resistant (SK-RC-12) cell line revealed that 484 and 354 transcripts, respectively, were modulated. A considerable number of these transcripts were similarly modulated between the two cell types that included several known targets of IFN signaling associated with antiviral and immunomodulatory activity. A further analysis of gene expression pattern in response to IFN revealed that several transcripts associated with proapoptotic function were upregulated in the sensitive cells. In the resistant cells, transcripts associated with cell survival and proliferation were induced, and key apoptotic molecules were suppressed. This study suggests that the IFN-alpha response of individual RCC tumors is determined by the expression pattern of genes in the apoptosis vs. survival and proliferation pathways rather than by alterations in expression of one or more individual genes.

Down-regulation of stem cell genes, including those in a 200-kb gene cluster at 12p13.31, is associated with in vivo differentiation of human male germ cell tumors

Adult male germ cell tumors (GCTs) comprise distinct groups: seminomas and nonseminomas, which include pluripotent embryonal carcinomas as well as other histologic subtypes exhibiting various stages of differentiation. Almost all GCTs show 12p gain, but the target genes have not been clearly defined. To identify 12p target genes, we examined Affymetrix (Santa Clara, CA) U133A+B microarray ( approximately 83% coverage of 12p genes) expression profiles of 17 seminomas, 84 nonseminoma GCTs, and 5 normal testis samples. Seventy-three genes on 12p were significantly overexpressed, including GLUT3 and REA (overexpressed in all GCTs) and CCND2 and FLJ22028 (overexpressed in all GCTs, except choriocarcinomas). We characterized a 200-kb gene cluster at 12p13.31 that exhibited coordinated overexpression in embryonal carcinomas and seminomas, which included the known stem cell genes NANOG, STELLA, and GDF3 and two previously uncharacterized genes. A search for other coordinately regulated genomic clusters of stem cell genes did not reveal any genomic regions similar to that at 12p13.31. Comparison of embryonal carcinoma with seminomas revealed relative overexpression of several stem cell-associated genes in embryonal carcinoma, including several core "stemness" genes (EBAF, TDGF1, and SOX2) and several downstream targets of WNT, NODAL, and FGF signaling (FGF4, NODAL, and ZFP42). Our results indicate that 12p gain is a functionally relevant change leading to activation of proliferation and reestablishment/maintenance of stem cell function through activation of key stem cell genes. Furthermore, the differential expression of core stem cell genes may explain the differences in pluripotency between embryonal carcinomas and seminomas.