PKMYT1 is a Marker of Treatment Response and a Therapeutic Target for CDK4/6 Inhibitor-Resistance in ER+ Breast Cancer

Endocrine therapies (ET) with CDK4/6 inhibition are the standard treatment for estrogen receptor-α-positive (ER+) breast cancer, however drug resistance is common. In this study, proteogenomic analyses of 22 ER+ breast cancer patient-derived xenografts (PDXs) demonstrated that PKMYT1, a WEE1 homolog, is estradiol (E2) regulated in E2-dependent PDXs and constitutively expressed when growth is E2-independent. In clinical samples, high PKMYT1 mRNA levels associated with resistance to both ET and CDK4/6 inhibition. The PKMYT1 inhibitor lunresertib (RP-6306) with gemcitabine selectively and synergistically reduced the viability of ET and palbociclib-resistant ER+ breast cancer cells without functional p53. In vitro the combination increased DNA damage and apoptosis. In palbociclib-resistant, TP53 mutant PDX organoids and xenografts, RP-6306 with low-dose gemcitabine induced greater tumor volume reduction compared to treatment with either single agent. Our study demonstrates the clinical potential of RP-6306 in combination with gemcitabine for ET and CDK4/6 inhibitor resistant TP53 mutant ER+ breast cancer.

Deep Learning Prediction Boosts Phosphoproteomics-Based Discoveries Through Improved Phosphopeptide Identification

Shotgun phosphoproteomics enables high-throughput analysis of phosphopeptides in biological samples. One of the primary challenges associated with this technology is the relatively low rate of phosphopeptide identification during data analysis. This limitation hampers the full realization of the potential offered by shotgun phosphoproteomics. Here we present DeepRescore2, a computational workflow that leverages deep learning-based retention time and fragment ion intensity predictions to improve phosphopeptide identification and phosphosite localization. Using a state-of-the-art computational workflow as a benchmark, DeepRescore2 increases the number of correctly identified peptide-spectrum matches by 17% in a synthetic dataset and identifies 19% to 46% more phosphopeptides in biological datasets. In a liver cancer dataset, 30% of the significantly altered phosphosites between tumor and normal tissues and 60% of the prognosis-associated phosphosites identified from DeepRescore2-processed data could not be identified based on the state-of-the-art workflow. Notably, DeepRescore2-processed data uniquely identifies EGFR hyperactivation as a new target in poor-prognosis liver cancer, which is validated experimentally. Integration of deep learning prediction in DeepRescore2 improves phosphopeptide identification and facilitates biological discoveries.

The Breast Cancer Proteome and Precision Oncology

The goal of precision oncology is to translate the molecular features of cancer into predictive and prognostic tests that can be used to individualize treatment leading to improved outcomes and decreased toxicity. Success for this strategy in breast cancer is exemplified by efficacy of trastuzumab in tumors overexpressing ERBB2 and endocrine therapy for tumors that are estrogen receptor positive. However, other effective treatments, including chemotherapy, immune checkpoint inhibitors, and CDK4/6 inhibitors are not associated with strong predictive biomarkers. Proteomics promises another tier of information that, when added to genomic and transcriptomic features (proteogenomics), may create new opportunities to improve both treatment precision and therapeutic hypotheses. Here, we review both mass spectrometry-based and antibody-dependent proteomics as complementary approaches. We highlight how these methods have contributed toward a more complete understanding of breast cancer and describe the potential to guide diagnosis and treatment more accurately.

Kinome Reprogramming Is a Targetable Vulnerability in ESR1 Fusion-Driven Breast Cancer

Transcriptionally active ESR1 fusions (ESR1-TAF) are a potent cause of breast cancer endocrine therapy (ET) resistance. ESR1-TAFs are not directly druggable because the C-terminal estrogen/anti-estrogen-binding domain is replaced with translocated in-frame partner gene sequences that confer constitutive transactivation. To discover alternative treatments, a mass spectrometry (MS)-based kinase inhibitor pulldown assay (KIPA) was deployed to identify druggable kinases that are upregulated by diverse ESR1-TAFs. Subsequent explorations of drug sensitivity validated RET kinase as a common therapeutic vulnerability despite remarkable ESR1-TAF C-terminal sequence and structural diversity. Organoids and xenografts from a pan-ET-resistant patient-derived xenograft model that harbors the ESR1-e6>YAP1 TAF were concordantly inhibited by the selective RET inhibitor pralsetinib to a similar extent as the CDK4/6 inhibitor palbociclib. Together, these findings provide preclinical rationale for clinical evaluation of RET inhibition for the treatment of ESR1-TAF-driven ET-resistant breast cancer.

SIGNIFICANCE

Kinome analysis of ESR1 translocated and mutated breast tumors using drug bead-based mass spectrometry followed by drug-sensitivity studies nominates RET as a therapeutic target. See related commentary by Wu and Subbiah, p. 3159.

A proteogenomics data-driven knowledge base of human cancer

By combining mass-spectrometry-based proteomics and phosphoproteomics with genomics, epi-genomics, and transcriptomics, proteogenomics provides comprehensive molecular characterization of cancer. Using this approach, the Clinical Proteomic Tumor Analysis Consortium (CPTAC) has characterized over 1,000 primary tumors spanning 10 cancer types, many with matched normal tissues. Here, we present LinkedOmicsKB, a proteogenomics data-driven knowledge base that makes consistently processed and systematically precomputed CPTAC pan-cancer proteogenomics data available to the public through ∼40,000 gene-, protein-, mutation-, and phenotype-centric web pages. Visualization techniques facilitate efficient exploration and reasoning of complex, interconnected data. Using three case studies, we illustrate the practical utility of LinkedOmicsKB in providing new insights into genes, phosphorylation sites, somatic mutations, and cancer phenotypes. With precomputed results of 19,701 coding genes, 125,969 phosphosites, and 256 genotypes and phenotypes, LinkedOmicsKB provides a comprehensive resource to accelerate proteogenomics data-driven discoveries to improve our understanding and treatment of human cancer. A record of this paper's transparent peer review process is included in the supplemental information.

Proteogenomic insights suggest druggable pathways in endometrial carcinoma

We characterized a prospective endometrial carcinoma (EC) cohort containing 138 tumors and 20 enriched normal tissues using 10 different omics platforms. Targeted quantitation of two peptides can predict antigen processing and presentation machinery activity, and may inform patient selection for immunotherapy. Association analysis between MYC activity and metformin treatment in both patients and cell lines suggests a potential role for metformin treatment in non-diabetic patients with elevated MYC activity. PIK3R1 in-frame indels are associated with elevated AKT phosphorylation and increased sensitivity to AKT inhibitors. CTNNB1 hotspot mutations are concentrated near phosphorylation sites mediating pS45-induced degradation of β-catenin, which may render Wnt-FZD antagonists ineffective. Deep learning accurately predicts EC subtypes and mutations from histopathology images, which may be useful for rapid diagnosis. Overall, this study identified molecular and imaging markers that can be further investigated to guide patient stratification for more precise treatment of EC.

Proteogenomic data and resources for pan-cancer analysis

The National Cancer Institute's Clinical Proteomic Tumor Analysis Consortium (CPTAC) investigates tumors from a proteogenomic perspective, creating rich multi-omics datasets connecting genomic aberrations to cancer phenotypes. To facilitate pan-cancer investigations, we have generated harmonized genomic, transcriptomic, proteomic, and clinical data for >1000 tumors in 10 cohorts to create a cohesive and powerful dataset for scientific discovery. We outline efforts by the CPTAC pan-cancer working group in data harmonization, data dissemination, and computational resources for aiding biological discoveries. We also discuss challenges for multi-omics data integration and analysis, specifically the unique challenges of working with both nucleotide sequencing and mass spectrometry proteomics data.

Kinase Inhibitor Pulldown Assay Identifies a Chemotherapy Response Signature in Triple-negative Breast Cancer Based on Purine-binding Proteins

Triple-negative breast cancer (TNBC) constitutes 10%-15% of all breast tumors. The current standard of care is multiagent chemotherapy, which is effective in only a subset of patients. The original objective of this study was to deploy a mass spectrometry (MS)-based kinase inhibitor pulldown assay (KIPA) to identify kinases elevated in non-pCR (pathologic complete response) cases for therapeutic targeting. Frozen optimal cutting temperature compound-embedded core needle biopsies were obtained from 43 patients with TNBC before docetaxel- and carboplatin-based neoadjuvant chemotherapy. KIPA was applied to the native tumor lysates that were extracted from samples with high tumor content. Seven percent of all identified proteins were kinases, and none were significantly associated with lack of pCR. However, among a large population of "off-target" purine-binding proteins (PBP) identified, seven were enriched in pCR-associated samples (P < 0.01). In orthogonal mRNA-based TNBC datasets, this seven-gene "PBP signature" was associated with chemotherapy sensitivity and favorable clinical outcomes. Functional annotation demonstrated IFN gamma response, nuclear import of DNA repair proteins, and cell death associations. Comparisons with standard tandem mass tagged-based discovery proteomics performed on the same samples demonstrated that KIPA-nominated pCR biomarkers were unique to the platform. KIPA is a novel biomarker discovery tool with unexpected utility for the identification of PBPs related to cytotoxic drug response. The PBP signature has the potential to contribute to clinical trials designed to either escalate or de-escalate therapy based on pCR probability.

Significance

The identification of pretreatment predictive biomarkers for pCR in response to neoadjuvant chemotherapy would advance precision treatment for TNBC. To complement standard proteogenomic discovery profiling, a KIPA was deployed and unexpectedly identified a seven-member non-kinase PBP pCR-associated signature. Individual members served diverse pathways including IFN gamma response, nuclear import of DNA repair proteins, and cell death.

Proteogenomic Approaches for the Identification of NF1/Neurofibromin-depleted Estrogen Receptor-positive Breast Cancers for Targeted Treatment

NF1 is a key tumor suppressor that represses both RAS and estrogen receptor-α (ER) signaling in breast cancer. Blocking both pathways by fulvestrant (F), a selective ER degrader, together with binimetinib (B), a MEK inhibitor, promotes tumor regression in NF1-depleted ER⁺ models. We aimed to establish approaches to determine how NF1 protein levels impact B+F treatment response to improve our ability to identify B+F sensitive tumors. We examined a panel of ER⁺ patient-derived xenograft (PDX) models by DNA and mRNA sequencing and found that more than half of these models carried an NF1 shallow deletion and generally have low mRNA levels. Consistent with RAS and ER activation, RET and MEK levels in NF1-depleted tumors were elevated when profiled by mass spectrometry (MS) after kinase inhibitor bead pulldown. MS showed that NF1 can also directly and selectively bind to palbociclib-conjugated beads, aiding quantification. An IHC assay was also established to measure NF1, but the MS-based approach was more quantitative. Combined IHC and MS analysis defined a threshold of NF1 protein loss in ER⁺ breast PDX, below which tumors regressed upon treatment with B+F. These results suggest that we now have a MS-verified NF1 IHC assay that can be used for patient selection as a complement to somatic genomic analysis.

Significance

A major challenge for targeting the consequence of tumor suppressor disruption is the accurate assessment of protein functional inactivation. NF1 can repress both RAS and ER signaling, and a ComboMATCH trial is underway to treat the patients with binimetinib and fulvestrant. Herein we report a MS-verified NF1 IHC assay that can determine a threshold for NF1 loss to predict treatment response. These approaches may be used to identify and expand the eligible patient population.

Molecular portraits of cell cycle checkpoint kinases in cancer evolution, progression, and treatment responsiveness

Cell cycle dysregulation is prerequisite for cancer formation. However, it is unknown whether the mode of dysregulation affects disease characteristics. Here, we conduct comprehensive analyses of cell cycle checkpoint dysregulation using patient data and experimental investigations. We find that ATM mutation predisposes the diagnosis of primary estrogen receptor (ER)+/human epidermal growth factor (HER)2- cancer in older women. Conversely, CHK2 dysregulation induces formation of metastatic, premenopausal ER+/HER2- breast cancer (P = 0.001) that is treatment-resistant (HR = 6.15, P = 0.01). Lastly, while mutations in ATR alone are rare, ATR/TP53 co-mutation is 12-fold enriched over expected in ER+/HER2- disease (P = 0.002) and associates with metastatic progression (HR = 2.01, P = 0.006). Concordantly, ATR dysregulation induces metastatic phenotypes in TP53 mutant, not wild-type, cells. Overall, we identify mode of cell cycle dysregulation as a distinct event that determines subtype, metastatic potential, and treatment responsiveness, providing rationale for reconsidering diagnostic classification through the lens of the mode of cell cycle dysregulation..

Abstract 5011: Targeting kinome reprogramming in ESR1 fusion-driven breast cancer

Background: Transcriptionally active ESR1 gene fusions (ESR1-TAF) are a potent cause of estrogen receptor alpha-positive (ERα+) breast cancer endocrine therapy (ET) resistance. These ESR1-TAF are gain-of-function mutations, exhibiting estrogen-independent cell growth, motility and ET resistance. They are not directly druggable because the ERα C-terminal ligand binding domain (LBD) encoding sequence is replaced with a translocated in-frame partner gene sequence. Herein we utilized proteomic approaches to develop novel targeted therapies against ESR1-TAF driven tumorigenesis.

Methods: ESR1 fusion cDNA constructs were expressed in ERα+ breast cancer cell lines (T47D and MCF7). Cell growth was assayed by an Alamar blue assay. A mass spectrometry (MS)-based Kinase Inhibitor Pulldown Assay (KIPA) was employed to identify druggable kinases that are commonly upregulated by diverse ESR1-TAFs. A panel of 22 ERα+ patient-derived xenograft (PDX) models were profiled using proteomics and phosphoproteomics to identify models with sensitivity to RET kinase inhibition.

Results: KIPA detected an increased abundance of a receptor tyrosine kinase, RET, in T47D cells expressing ESR1-TAFs in an estrogen-independent manner, compared to stable cell lines expressing transcriptionally inactive fusions as well as wild-type ERα protein. Interestingly, RET was also increased when constitutive activating ERα LBD point mutants, Y537S and D538G, were expressed in breast cancer cells. Inhibition of the RET kinase in vitro by repurposing pralsetinib, an FDA-approved RET inhibitor for advanced thyroid and non-small-cell lung cancers, demonstrated a significant reduction in the growth of cells expressing ESR1-TAFs and ERα LBD mutants. These data nominate RET kinase as a common therapeutic vulnerability for ESR1-TAF expressing breast cancers. Proteomic profiling of 22 biologically heterogenous ERα+ PDX tumors defined targetable pathways and predicted tumor subsets that were responsive to RET inhibition therapy. Organoids and xenografts from the pan-ET resistant WHIM18 PDX (that expresses the ESR1-YAP1 TAF) were inhibited by pralsetinib to a similar extent as the CDK4/6 inhibitor palbociclib. These data provide key preclinical rationale for the consideration of RET inhibition for the treatment of ESR1-TAF-driven ET-resistant breast cancer. Interestingly, the growth of WHIM37 PDX (that expresses ERα D538G) that had low level of RET and high level of GFRα-1, the co-receptor of RET, was also suppressed by pralsetinib. This data suggests that either RET or GFRα-1 is a predictive biomarker for RET inhibitor efficacy.

Conclusions: Kinome analysis of ESR1 translocated breast tumors using KIPA followed by drug sensitivity studies nominated RET as a new therapeutic target for ET-resistant ERα+ breast cancer.

Citation Format: Xuxu Gou, Beom-Jun Kim, Meenakshi Anurag, Jonathan T. Lei, Meggie N. Young, Matthew V. Holt, Diana Fandino, Craig T. Vollert, Purba Singh, Mohammad A. Alzubi, Anna Malovannaya, Lacey E. Dobrolecki, Michael T. Lewis, Shunqiang Li, Matthew J. Ellis, Charles E. Foulds. Targeting kinome reprogramming in ESR1 fusion-driven breast cancer. [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 5011.

Abstract 6575: LinkedOmicsKB: A web portal to explore pan-cancer molecular and phenotype associations

Pan-cancer multi-omics data produced from integrated genomic, epigenomic, transcriptomic, proteomic, and post-translational modification (PTM) profiling of a wide variety of cancer types holds great potential for understanding cancer biology and generating therapeutic hypotheses. To realize this potential and make analysis and visualization of these complex and interconnected data easily accessible to cancer biologists and clinicians, we have developed a web portal, LinkedOmicsKB. The web portal provides access to a harmonized proteogenomic dataset of over 1000 patient samples covering 10 cancer cohorts from the Clinical Proteomic Tumor Analysis Consortium (CPTAC). We calculated associations between methylation, copy number variation (CNV), RNA, protein, and phosphosite data for each gene and further correlated the proteogenomics data with clinical and computed molecular phenotypes. All results are stored in a MongoDB database and visualizations are provided for exploring pan-cancer multi-omics relationships as well as individual statistics. We demonstrate the utility of LinkedOmicsKB to provide insights into clinical phenotypes, somatic mutations, and understudied genes. In the pan-cancer CPTAC data, overall survival was correlated with proteins involved in protein hydroxylation, including PLOD1 and PLOD2. Additionally, two phosphorylation sites on the tumor suppressor MIG-6 were associated with worse survival. These sites were also associated with hypoxia, MAPK, and EGFR pathway activity scores, suggesting a relationship between the signaling in these pathways and cancer prognosis. STK17B is an understudied kinase that regulates apoptosis. We found STK17B was upregulated in 6 cancer types at the protein level but only two at the RNA level. The protein abundance of STK17B was highly associated with immune scores and JAK/STAT signaling, supporting a role for STK17B in the immune response. We identified 3 phosphorylation sites on STK17B, which were associated with EGF pathway activity scores and immune-related scores. LinkedOmicsKB is a valuable tool that can be used to generate biological and clinical insights into any gene, phosphosite, mutation, or phenotype.

Citation Format: Sara R. Savage, Yuxing Liao, Yongchao Dou, Zhiao Shi, Xinpei Yi, Wen Jiang, Jonathan T. Lei, Bing Zhang. LinkedOmicsKB: A web portal to explore pan-cancer molecular and phenotype associations [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 6575.

Abstract 5726: Pan-cancer proteogenomics expands the landscape of therapeutic targets

Background: Molecularly targeted therapies are critical for improving cancer treatment. Since proteins are the targets of these therapies and functional effectors of genomic aberrations, proteogenomics data from the Clinical Proteomics Tumor Analysis Consortium (CPTAC) provides an unprecedented opportunity to characterize existing and future therapeutic targets for cancer treatment.

Approach: CPTAC proteogenomics data from &gt;1000 cancer patients spanning 10 cancer types was used to evaluate current and potential therapeutic targets curated from four databases. Cell line data from DepMap was further integrated to distinguish causations from associations. Computational pipelines were deployed to identify synthetic lethality for targeting tumor suppressor loss and to prioritize tumor associated antigens as immunotherapy targets.

Results: We systematically collected 3050 druggable proteins and classified them into 5 tiers to facilitate different applications such as companion diagnostics, drug repurposing, and new therapy development. Many druggable proteins showed poor mRNA-protein correlation, including secreted proteins and proteins whose abundance was correlated with their interaction partners instead of cognate mRNA, highlighting the necessity of direct proteomic quantification of drug targets. 618 druggable proteins showed both overexpression in tumors compared to normal and significant dependency in CRISPR-Cas9 screens of cell lines of the same lineage. Notably, PAK1, a kinase targeted by investigational drugs, demonstrated both overexpression and dependency in all cancer types. A similar analysis of phosphoproteomics data focusing on known activating sites of druggable proteins further revealed targetable dependencies driven by protein hyperactivation. The phosphosite pS50 on PTPN1, a phosphatase targeted by experimental drugs, was increased in 7 cancer types and PTPN1 demonstrated dependency in related cancer cell lines. Based on tumor proteogenomic data and cell line CRISPR-Cas9 screen data, we identified synthetic lethality for difficult to target tumor suppressor losses, revealing TP53 mutations as a candidate biomarker to select breast cancer patients for CHEK1 inhibition, and endometrial cancer patients for treatment with doxorubicin. We identified 140 proteins whose expression was restricted in normal tissues but abnormal in tumors. Experimental analysis of peptides predicted to have high binding affinity to the most common allotype HLA-A02 for 7 prioritized proteins identified 21 peptides from 5 proteins with both strong binding affinity and immunogenicity which could be further investigated as immunotherapy targets.

Conclusion: We generate a comprehensive resource of protein and peptide targets that covers multiple therapeutic modalities. This unique resource will pave the way for repurposing of currently available drugs and developing new drugs for cancer treatment.

Citation Format: Jonathan T. Lei, Sara R. Savage, Xinpei Yi, Bo Wen, Hongwei Zhao, Lauren K. Somes, Paul W. Shafer, Yongchao Dou, Qiang Gao, Valentina Hoyos, Bing Zhang. Pan-cancer proteogenomics expands the landscape of therapeutic targets. [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 5726.

Abstract P2-23-01: Patient-derived xenografts allow deconvolution of single agent and combination chemotherapy responses in triple-negative breast cancer

Background: Triple-negative breast cancer (TNBC) patients frequently receive combination chemotherapy treatment, but a direct comparison of response to carboplatin, docetaxel, and their combination in 50 TNBC patient-derived xenografts (PDXs) showed that combination treatment was largely ineffective at generating enhanced responses over the best single agent. This suggests de-escalation of chemotherapy may be possible if molecular mechanisms and biomarkers underlying response to individual treatments can be identified. To this end, we performed multi-omics profiling for the 50 TNBC PDXs. Methods: Orthotopic TNBC PDXs were treated with four weekly cycles of docetaxel, carboplatin, or the combination. Changes in tumor volume after 4 weeks of treatment were assessed quantitatively and by modified RECIST criteria. Genomic, transcriptomic, and mass-spectrometry-based proteomic profiling were performed on baseline tumors prior to treatments to identify associations with chemotherapy response at the gene and pathway level. ProMS was used to integrate both RNA and protein data to select a 5 RNA feature combination for optimized prediction of carboplatin response in a logistic regression model. Publicly available neoadjuvant chemotherapy clinical datasets with transcriptomic data and response information used for validation/testing included TNBC samples from: GSE18864, I-SPY2 (GSE194040), and BrighTNess (GSE164458). Results: Proteogenomic profiles revealed distinct genes associated with response to each agent and their combination, respectively, suggesting distinct molecular mechanisms underlying response to each treatment. A substantial number of genes associated with single agent and combination treatment were validated in multiple independent patient cohorts receiving platinum and taxane containing neoadjuvant therapy, confirming clinical relevance of our PDX panel. For the same treatment, different types of molecular data identified distinct sets of associated genes, providing highly complementary information. At the pathway level, RNA and protein data converged to metabolic and E2F/G2M related pathways which were upregulated in PDXs resistant or responsive to all treatment types, respectively, while variable levels of MYC-related proliferation pathways were observed across all treatments suggesting pathways that are common across and unique to different treatments. Several individual genes found to be higher in PDXs with better response to either single-agent had discriminatory power in external clinical TNBC datasets treated with similar neoadjuvant chemotherapy regimens. In addition, a logistic regression-based carboplatin response prediction model trained to select a group of 5 RNA markers (TKT, MAGI2, ATF6B, MCM7, LRP6) using both RNA and protein data performed the best in predicting response to cisplatin in a clinical TNBC dataset vs predicting response to other datasets with taxane and platinum + taxane combination containing chemotherapy regimens, demonstrating specificity of the prediction model. These results suggest potential individual biomarkers or biomarker combinations to select TNBC tumors that may respond to either single agent carboplatin, docetaxel, or their combination. PDXs refractory to all treatment arms had higher levels of proteostasis-related pathways including proteasome degradation and the unfolded protein response (UPR) related to endoplasmic reticulum stress and altered levels of chromatin regulation. Subsequent pharmacological targeting of the UPR pathway and targeting HDACs enhanced chemotherapy response. Conclusion: Proteogenomic characterization identifies molecular mechanisms and putative biomarkers for stratifying TNBC tumors for single or combination chemotherapy treatments, suggests targeted therapies to augment chemotherapy response, and provides a valuable resource for researchers and clinicians.

Citation Format: Jonathan T. Lei, Chen Huang, Ramakrishnan R. Srinivasan, Suhas Vasaikar, Lacey E. Dobrolecki, Alaina N. Lewis, Na Zhao, Jin Cao, Susan G. Hilsenbeck, C. Kent Osborne, Mothaffar Rimawi, Matthew J. Ellis, Varduhi Petrosyan, Alexander B. Saltzman, Anna Malovannaya, John D. Landua, Bo Wen, Antrix Jain, Gerburg M. Wulf, Shunqiang Li, Daniel C. Kraushaar, Tao Wang, Xi Chen, Gloria V. Echeverria, Meenakshi Anurag, Bing Zhang, Michael T. Lewis. Patient-derived xenografts allow deconvolution of single agent and combination chemotherapy responses in triple-negative breast cancer [abstract]. In: Proceedings of the 2022 San Antonio Breast Cancer Symposium; 2022 Dec 6-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2023;83(5 Suppl):Abstract nr P2-23-01.

Deep learning prediction boosts phosphoproteomics-based discoveries through improved phosphopeptide identification

Shotgun phosphoproteomics enables high-throughput analysis of phosphopeptides in biological samples, but low phosphopeptide identification rate in data analysis limits the potential of this technology. Here we present DeepRescore2, a computational workflow that leverages deep learning-based retention time and fragment ion intensity predictions to improve phosphopeptide identification and phosphosite localization. Using a state-of-the-art computational workflow as a benchmark, DeepRescore2 increases the number of correctly identified peptide-spectrum matches by 17% in a synthetic dataset and identifies 19%-46% more phosphopeptides in biological datasets. In a liver cancer dataset, 30% of the significantly altered phosphosites between tumor and normal tissues and 60% of the prognosis-associated phosphosites identified from DeepRescore2-processed data could not be identified based on the state-of-the-art workflow. Notably, DeepRescore2-processed data uniquely identifies EGFR hyperactivation as a new target in poor-prognosis liver cancer, which is validated experimentally. Integration of deep learning prediction in DeepRescore2 improves phosphopeptide identification and facilitates biological discoveries.

Proteogenomic Markers of Chemotherapy Resistance and Response in Triple-Negative Breast Cancer

Microscaled proteogenomics was deployed to probe the molecular basis for differential response to neoadjuvant carboplatin and docetaxel combination chemotherapy for triple-negative breast cancer (TNBC). Proteomic analyses of pretreatment patient biopsies uniquely revealed metabolic pathways, including oxidative phosphorylation, adipogenesis, and fatty acid metabolism, that were associated with resistance. Both proteomics and transcriptomics revealed that sensitivity was marked by elevation of DNA repair, E2F targets, G2-M checkpoint, interferon-gamma signaling, and immune-checkpoint components. Proteogenomic analyses of somatic copy-number aberrations identified a resistance-associated 19q13.31-33 deletion where LIG1, POLD1, and XRCC1 are located. In orthogonal datasets, LIG1 (DNA ligase I) gene deletion and/or low mRNA expression levels were associated with lack of pathologic complete response, higher chromosomal instability index (CIN), and poor prognosis in TNBC, as well as carboplatin-selective resistance in TNBC preclinical models. Hemizygous loss of LIG1 was also associated with higher CIN and poor prognosis in other cancer types, demonstrating broader clinical implications.

SIGNIFICANCE

Proteogenomic analysis of triple-negative breast tumors revealed a complex landscape of chemotherapy response associations, including a 19q13.31-33 somatic deletion encoding genes serving lagging-strand DNA synthesis (LIG1, POLD1, and XRCC1), that correlate with lack of pathologic response, carboplatin-selective resistance, and, in pan-cancer studies, poor prognosis and CIN. This article is highlighted in the In This Issue feature, p. 2483.

Elevated NRAS expression during DCIS is a potential driver for progression to basal-like properties and local invasiveness

BACKGROUND

Ductal carcinoma in situ (DCIS) is the most common type of in situ premalignant breast cancers. What drives DCIS to invasive breast cancer is unclear. Basal-like invasive breast cancers are aggressive. We have previously shown that NRAS is highly expressed selectively in basal-like subtypes of invasive breast cancers and can promote their growth and progression. In this study, we investigated whether NRAS expression at the DCIS stage can control transition from luminal DCIS to basal-like invasive breast cancers.

METHODS

Wilcoxon rank-sum test was performed to assess expression of NRAS in DCIS compared to invasive breast tumors in patients. NRAS mRNA levels were also determined by fluorescence in situ hybridization in patient tumor microarrays (TMAs) with concurrent normal, DCIS, and invasive breast cancer, and association of NRAS mRNA levels with DCIS and invasive breast cancer was assessed by paired Wilcoxon signed-rank test. Pearson's correlation was calculated between NRAS mRNA levels and basal biomarkers in the TMAs, as well as in patient datasets. RNA-seq data were generated in cell lines, and unsupervised hierarchical clustering was performed after combining with RNA-seq data from a previously published patient cohort.

RESULTS

Invasive breast cancers showed higher NRAS mRNA levels compared to DCIS samples. These NRAShigh lesions were also enriched with basal-like features, such as basal gene expression signatures, lower ER, and higher p53 protein and Ki67 levels. We have shown previously that NRAS drives aggressive features in DCIS-like and basal-like SUM102PT cells. Here, we found that NRAS-silencing induced a shift to a luminal gene expression pattern. Conversely, NRAS overexpression in the luminal DCIS SUM225 cells induced a basal-like gene expression pattern, as well as an epithelial-to-mesenchymal transition signature. Furthermore, these cells formed disorganized mammospheres containing cell masses with an apparent reduction in adhesion.

CONCLUSIONS

These data suggest that elevated NRAS levels in DCIS are not only a marker but can also control the emergence of basal-like features leading to more aggressive tumor activity, thus supporting the therapeutic hypothesis that targeting NRAS and/or downstream pathways may block disease progression for a subset of DCIS patients with high NRAS.

Epithelial immunomodulation by aerosolized Toll-like receptor agonists prevents allergic inflammation in airway mucosa in mice

Allergic asthma is a chronic inflammatory respiratory disease associated with eosinophilic infiltration, increased mucus production, airway hyperresponsiveness, and airway remodeling. Epidemiologic data reveal that the prevalence of allergic sensitization and associated diseases has increased in the twentieth century. This has been hypothesized to be partly due to reduced contact with microbial organisms (the hygiene hypothesis) in industrialized society. Airway epithelial cells, once considered a static physical barrier between the body and the external world, are now widely recognized as immunologically active cells that can initiate, maintain, and restrain inflammatory responses, such as those that mediate allergic disease. Airway epithelial cells can sense allergens via expression of myriad Toll-like receptors (TLRs) and other pattern-recognition receptors. We sought to determine whether the innate immune response stimulated by a combination of Pam2CSK4 ("Pam2", TLR2/6 ligand) and a class C oligodeoxynucleotide ODN362 ("ODN", TLR9 ligand), when delivered together by aerosol ("Pam2ODN"), can modulate the allergic immune response to allergens. Treatment with Pam2ODN 7 days before sensitization to House Dust Mite (HDM) extract resulted in a strong reduction in eosinophilic and lymphocytic inflammation. This Pam2ODN immunomodulatory effect was also seen using Ovalbumin (OVA) and A. oryzae (Ao) mouse models. The immunomodulatory effect was observed as much as 30 days before sensitization to HDM, but ineffective just 2 days after sensitization, suggesting that Pam2ODN immunomodulation lowers the allergic responsiveness of the lung, and reduces the likelihood of inappropriate sensitization to aeroallergens. Furthermore, Pam2 and ODN cooperated synergistically suggesting that this treatment is superior to any single agonist in the setting of allergen immunotherapy.

Abstract 2979: ElevatedNRASexpression as a potential driver of DCIS progression to basal-like invasive breast cancer

Background: Ductal carcinoma in situ (DCIS) is the most common type of in situ premalignant breast cancers. What drives a subset of luminal DCIS to transition to basal invasive breast cancers is unclear. Basal-like invasive breast cancers are aggressive and associated with the shortest overall survival and time to distant metastasis. We have previously shown that N-Ras is highly expressed selectively in the basal-like subtypes of invasive breast cancers and can promote their growth and progression. In this study, we investigated whether NRAS expression at the DCIS stage can control transition from luminal DCIS to basal-like invasive breast cancers.

Methods: Wilcoxon rank-sum test was conducted to assess the relative expression of NRAS in DCIS compared to invasive breast cancers in a patient cohort (GSE59248). NRAS levels were also determined by fluorescence in situ hybridization (FISH) in a collection of 21 patient tumor microarrays (TMAs) with concurrent normal, DCIS, and invasive breast cancer, and NRAS’s association with DCIS and invasive breast cancer was assessed by Wilcoxon signed rank test. How NRAS levels correlated with basal biomarkers in the TMAs, as well as in patient datasets GSE59248 and GSE3369 was determined by Pearson correlation. Gene expression changes in cell line were assessed by RNA-seq.

Results: Invasive breast cancers showed higher NRAS mRNA levels, as compared to DCIS samples. These NRAShigh lesions were also enriched with basal-like features, such as basal gene expression signature, lower ER, higher p53 protein levels, and higher Ki67 levels. We have shown previously that N-Ras is a driver for tumor growth in SUM102 cells, which is a DCIS-like cell line model displaying basal-like features. Here we found that NRAS-silencing in these cells induced a shift to a luminal gene expression pattern as determined by PAM50.

Conclusions: These data suggest that the rise of N-RAS levels in DCIS can not only mark but also control the emergence of basal-like features leading to more aggressive tumor activities. Targeting N-Ras and/or its downstream pathway may prevent the emergence of basal invasive breast cancers.

Citation Format: Ze-yi Zheng, Hanan Elsarraj, Yang Hong, Jonathan T. Lei, Meenakshi Anurag, Yichao Shen, Flora Lo, Long Feng, Zifan Zhao, Xiang H. Zhang, Fariba Behbod, Eric C. Chang. ElevatedNRASexpression as a potential driver of DCIS progression to basal-like invasive breast cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 2979.

LINC00355 regulates p27KIP expression by binding to MENIN to induce proliferation in late-stage relapse breast cancer

Late-stage relapse (LSR) in patients with breast cancer (BC) occurs more than five years and up to 10 years after initial treatment and has less than 30% 5-year relative survival rate. Long non-coding RNAs (lncRNAs) play important roles in BC yet have not been studied in LSR BC. Here, we identify 1127 lncRNAs differentially expressed in LSR BC via transcriptome sequencing and analysis of 72 early-stage and 24 LSR BC patient tumors. Decreasing expression of the most up-regulated lncRNA, LINC00355, in BC and MCF7 long-term estrogen deprived cell lines decreases cellular invasion and proliferation. Subsequent mechanistic studies show that LINC00355 binds to MENIN and changes occupancy at the CDKN1B promoter to decrease p27Kip. In summary, this is a key study discovering lncRNAs in LSR BC and LINC00355 association with epigenetic regulation and proliferation in BC.

Transcriptional reprogramming differentiates active from inactive ESR1 fusions in endocrine therapy-refractory metastatic breast cancer

Genomic analysis has recently identified multiple ESR1 gene translocations in estrogen receptor-alpha positive (ERα+) metastatic breast cancer (MBC) that encode chimeric proteins whereby the ESR1 ligand binding domain (LBD) is replaced by C-terminal sequences from many different gene partners. Here we functionally screened 15 ESR1 fusions and identified 10 that promoted estradiol-independent cell growth, motility, invasion, EMT and resistance to fulvestrant. RNA sequencing identified a gene expression pattern specific to functionally active ESR1 gene fusions that was subsequently reduced to a diagnostic 24-gene signature. This signature was further examined in 20 ERα+ patient-derived xenografts (PDXs) and in 55 ERα+ MBC samples. The 24-gene signature successfully identified cases harboring ESR1 gene fusions and also accurately diagnosed the presence of activating ESR1 LBD point mutations. Therefore, the 24-gene signature represents an efficient approach to screening samples for the presence of diverse somatic ESR1 mutations and translocations that drive endocrine treatment failure in MBC.

A proteogenomic portrait of lung squamous cell carcinoma

Lung squamous cell carcinoma (LSCC) remains a leading cause of cancer death with few therapeutic options. We characterized the proteogenomic landscape of LSCC, providing a deeper exposition of LSCC biology with potential therapeutic implications. We identify NSD3 as an alternative driver in FGFR1-amplified tumors and low-p63 tumors overexpressing the therapeutic target survivin. SOX2 is considered undruggable, but our analyses provide rationale for exploring chromatin modifiers such as LSD1 and EZH2 to target SOX2-overexpressing tumors. Our data support complex regulation of metabolic pathways by crosstalk between post-translational modifications including ubiquitylation. Numerous immune-related proteogenomic observations suggest directions for further investigation. Proteogenomic dissection of CDKN2A mutations argue for more nuanced assessment of RB1 protein expression and phosphorylation before declaring CDK4/6 inhibition unsuccessful. Finally, triangulation between LSCC, LUAD, and HNSCC identified both unique and common therapeutic vulnerabilities. These observations and proteogenomics data resources may guide research into the biology and treatment of LSCC.

Abstract 742: The integration of a structure-function rule and a transcriptional signature to assign ESR1 fusion activity in metastatic breast cancer

Background: In-frame chimeric ESR1 fusion proteins can cause endocrine therapy (ET) resistance in estrogen receptor-positive (ER+) metastatic breast cancer (MBC) (PMC6171747). Here, we further investigated multiple new examples of ESR1 fusions in order to differentiate between transcriptionally active “driver” ESR1 fusions from inactive, likely “passenger” events.

Methods: ESR1 fusions were identified by RNA-sequencing (RNA-seq) or whole genome sequencing in MBC (PMC5913625, PMC6872491 and unpublished). ESR1 fusion cDNA constructs were expressed in ER+ breast cancer cell lines. Cell proliferation and cell motility were assessed. RNA-seq followed by qPCR validation was conducted to examine individual transcriptional profiles.

Results: All ESR1 fusions studied contained the first six exons of ESR1 (e6) fused in-frame to diverse partner gene sequences that replaced the ESR1 drug/ligand binding domain. Fusions with a transcription factor (TF) or coactivator (CoA) gene partner, for example ESR1-YAP1, ESR1-ARNT2-e18 and ESR1-SOX9 activated fulvestrant-resistant cell growth and hormone-independent cell motility. Other ESR1-e6 fusions, including ESR1-DAB2, ESR1-GYG1, ESR1-PCMT1 and ESR1-ARID1B did not show these phenotypes. We thus conclude that in-frame ESR1-e6 fusions arising from inter-chromosomal translocations with 3' TF/CoA partners are likely to be active. However, the active ESR1-PCDH11X fusion involves a proto-cadherin and is therefore an exception to this rule. This outlier emphasizes the need to establish additional approaches to determine ESR1 fusion activity. RNA-seq of T47D cells expressing active and inactive ESR1 fusions defined a gene signature associated with active ESR1 fusions, with activation of estrogen response and epithelial-to-mesenchymal transition (EMT) genes. This transcriptional signature was present in a patient-derived xenograft bearing the ESR1-YAP1 fusion, and thus potentially identifies the presence of an active ESR1 fusion protein. We subsequently identified two new ESR1 fusions involving recurrent TF/CoA partners, ESR1-ARNT2-e2 and ESR1-LPP. Both demonstrated tumor cell growth and motility activation, as predicted by the functional rule. The gene activation patterns were similar to the three other active fusions suggesting that despite marked diversity in the 3' partners, the transcriptional activities were similar and potentially diagnostic.

Conclusion: The integration of the structure-function rule and the stereotypic transcriptional signature distinguishes pathogenic ESR1 fusions from non-active passenger events, thus prioritizing patients bearing ESR1 translocation-driven tumors for targeted therapeutic approaches.

Citation Format: Xuxu Gou, Meenakshi Anurag, Jonathan T. Lei, Sinem Seker, Adrian V. Lee, Dan R. Robinson, Matthew J. Ellis. The integration of a structure-function rule and a transcriptional signature to assign ESR1 fusion activity in metastatic breast cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2021; 2021 Apr 10-15 and May 17-21. Philadelphia (PA): AACR; Cancer Res 2021;81(13_Suppl):Abstract nr 742.

Abstract 2490: Optimizing treatment strategy for NF1-depleted estrogen receptor positive breast cancer

Background: Germline mutations in the NF1 gene are responsible for neurofibromatosis type 1, which is the world's most common genetic disorder. NF1 is also a key tumor suppressor gene that is frequently somatically mutated in a wide range of cancers. Approximately 80% of breast cancer is driven by the estrogen receptor α (ER), encoded by the ESR1 gene, and ER-positive (ER+) breast cancer can be treated by endocrine therapy targeting the ER transcriptional pathway. NF1 encodes neurofibromin, which is best known as a GTPase Activating Protein (GAP) for repressing Ras signaling. However, in a recent study we presented evidence supporting the model that NF1 has a GAP-independent activity by also acting as a transcriptional co-repressor for ER. NF1 loss enhanced ER transcription causing resistance to tamoxifen and aromatase inhibition.

Approach and Results: In this study, we examined patient data from TCGA cohort and found that low NF1 mRNA levels associated with recurrence in luminal breast cancer, particularly in the luminal B subtype. Using purified components, we showed that full-length NF1 can directly bind ER. The ESR1-pE380Q mutation is a recurrent event in metastatic ER+ breast cancer. Our two-hybrid data showed that NF1 interacted less with the ER-E380Q than wild type ER, which agrees with structural analysis predicting co-repressors binding to be mediated by the ER-E380 residue. To assess how NF1-loss impacts ER-dependent gene expression in ER+ breast cancer cells, our ER ChIP-seq data showed that in the presence of estradiol, NF1-depletion promoted global ER recruitment to estrogen response elements (EREs) on chromatin. Expression of ERE-bound genes showed concordant expression changes by RNA-seq, confirming genome-wide transcriptional dysregulation of ER targeted genes by NF1 loss. ER+ NF1-depleted breast cancer cells responded initially to a selective ER degrader (SERD), such as fulvestrant and an oral SERD AZD9496, but acquired resistance with prolonged treatment. Resistance may be dependent on CDK4/6, a common growth pathway controlled by both Ras and ER. We showed that fulvestrant together with a CDK4/6 inhibitor Palbociclib can efficiently inhibit the growth of ER+ NF1-depleted breast cancer leading to tumor regression in a patient derived xenograft model.

Conclusion: The loss of the full length NF1 can stimulate both ER and Ras signaling, and it is possible to efficiently treat ER+ NF1-depleted breast cancer by a SERD, in combination with CDK4/6 inhibitor.

Citation Format: Zeyi Zheng, Jonathan T. Lei, Meenakshi Anurag, Long Feng, Purba Singh, Hilda Kennedy, Jin Cao, Xi Chen, Matthew J. Ellis, Eric C. Chang. Optimizing treatment strategy for NF1-depleted estrogen receptor positive breast cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2021; 2021 Apr 10-15 and May 17-21. Philadelphia (PA): AACR; Cancer Res 2021;81(13_Suppl):Abstract nr 2490.

Abstract 2992: Proteogenomic characterization of triple-negative breast cancer patient-derived xenografts reveals molecular correlates of differential chemotherapy response and potential therapeutic targets to overcome resistance

Background: Chemotherapy is essential for the management of patients with triple-negative breast cancer (TNBC). Identification of biomarkers that may indicate treatment efficacy will be critical to improve patient stratification prior to treatment. To elucidate molecular determinants underlying chemotherapy response, we conducted a proteogenomic study using TNBC patient-derived xenografts (PDXs) treated with chemotherapy.

Approach: 50 TNBC PDXs were treated with either docetaxel or carboplatin. Changes in tumor volume after 4 weeks from baseline were evaluated. Genomic, transcriptomic, and mass-spectrometry-based proteomic profiling were performed on baseline tumors prior to treatment to identify associations with chemotherapy response. Fisher's exact tests were used to test for significant enrichment of mutation and copy number events (p&lt;0.05). Gene Set Enrichment Analysis was performed for pathway analyses.

Results: At the DNA level, genomic aberrations in BRCA2 and BCL2 were enriched in carboplatin-responsive PDXs, while ARID1B aberrations were enriched in docetaxel-responsive PDXs. Gene-drug response correlations supported by both mRNA and protein-based measurements, but not mRNA or protein alone, for both carboplatin and docetaxel treatment in PDXs were associated with prognosis from basal and claudin-low human breast tumors in receipt of any chemotherapy from the METABRIC dataset. These data suggest that the combination of mRNA and protein data increased power to identify genes related to clinical outcome in TNBC. Some of the top genes overexpressed at both mRNA and protein levels in chemoresistant PDXs are targets of approved drugs, many of which have not been evaluated for their ability to augment response to taxane- or platinum-based chemotherapies. These genes are being investigated as therapeutic targets as well as markers of chemotherapy response. At the pathway level, both RNA and protein data associated models resistant to both agents with enhanced oxidative phosphorylation and translation regulation. Protein data further associated resistant models with elevated cytoplasmic ribosomal proteins. In contrast, both RNA and protein data associated tumors sensitive to both agents with genes involved in the E2F-Rb axis and cell cycle progression. Moreover, DNA mismatch repair and mRNA processing pathways were uniquely associated with carboplatin and docetaxel sensitivity, respectively, while amino acid metabolism and MAPK signaling pathways were uniquely associated with carboplatin and docetaxel resistance, respectively.

Conclusion: Taken together, proteogenomic analysis of PDX tumors identifies diverse genes and pathways associated with chemotherapy response and further suggests potential therapeutic opportunities in TNBC.

Citation Format: Jonathan T. Lei, Chen Huang, Ramakrishnan R. Srinivasan, Suhas Vasaikar, Lacey E. Dobrolecki, Alaina N. Lewis, Christina Sallas, Susan G. Hilsenbeck, C Kent Osborne, Mothaffar F. Rimawi, Matthew J. Ellis, Varduhi Petrosyan, Alexander B. Saltzman, Anna Malovannaya, Gerburg Wulf, Daniel C. Kraushaar, Tao Wang, Gloria V. Echeverria, Bing Zhang, Michael T. Lewis. Proteogenomic characterization of triple-negative breast cancer patient-derived xenografts reveals molecular correlates of differential chemotherapy response and potential therapeutic targets to overcome resistance [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2021; 2021 Apr 10-15 and May 17-21. Philadelphia (PA): AACR; Cancer Res 2021;81(13_Suppl):Abstract nr 2992.

Proteogenomics drives therapeutic hypothesis generation for precision oncology

Precision oncology has largely been driven by genomic profiling, but success so far has been limited. By combining genomic and proteomic analyses of tumours, proteogenomics holds promise in providing deeper mechanistic insights and generating therapeutic hypotheses to better match patients to targeted treatments than analysing each 'ome in isolation.

Proteogenomic insights into the biology and treatment of HPV-negative head and neck squamous cell carcinoma

We present a proteogenomic study of 108 human papilloma virus (HPV)-negative head and neck squamous cell carcinomas (HNSCCs). Proteomic analysis systematically catalogs HNSCC-associated proteins and phosphosites, prioritizes copy number drivers, and highlights an oncogenic role for RNA processing genes. Proteomic investigation of mutual exclusivity between FAT1 truncating mutations and 11q13.3 amplifications reveals dysregulated actin dynamics as a common functional consequence. Phosphoproteomics characterizes two modes of EGFR activation, suggesting a new strategy to stratify HNSCCs based on EGFR ligand abundance for effective treatment with inhibitory EGFR monoclonal antibodies. Widespread deletion of immune modulatory genes accounts for low immune infiltration in immune-cold tumors, whereas concordant upregulation of multiple immune checkpoint proteins may underlie resistance to anti-programmed cell death protein 1 monotherapy in immune-hot tumors. Multi-omic analysis identifies three molecular subtypes with high potential for treatment with CDK inhibitors, anti-EGFR antibody therapy, and immunotherapy, respectively. Altogether, proteogenomics provides a systematic framework to inform HNSCC biology and treatment.

Abstract PD8-02: Kinome profiling of ER+ breast cancer PDXs identifies PKMYT1 as a marker of hormone independent growth and poor outcome

Background: Endocrine therapy resistance is common and is a leading cause of breast cancer-related death. Thus, the search for therapeutic targets based on mechanistic insights into endocrine therapy resistance continues. Kinases are important drug targets and regulators in cells, many of which are involved in tumorigenesis and the development of treatment resistance. Mass spectrometry-based kinome analysis has been impeded by the low abundance of individual kinases. Here we utilized kinase inhibitor-conjugated beads to enrich and thereby sensitively profile the kinome of estrogen receptor-positive (ER+) breast cancer patient-derived xenograft (PDX) tumors under estradiol-deprivation treatment.

Experimental design and methods: We harvested tumor samples from 20 breast PDX lines with various degrees of estradiol (E2) dependence in ovariectomized SCID-beige mice with and without E2 supplementation (n=3 per PDX line per arm). The kinases in the tumor lysates were enriched using kinase inhibitor pulldown (KIP) beads and the tightly bound kinases were quantified by mass spectrometry. To identify candidates, we selected for kinases that were highly E2-regulated in the E2-dependent PDX lines but constitutively expressed in E2-independent PDX lines. Survival analysis of candidate kinases in patients with ER+ breast cancer was performed using the METABRIC dataset.

Results: Each PDX line had a unique yet reproducible kinome. To seek kinases with consistent relationships with estrogen dependence, we sought kinases that were statistically differentially expressed in tumors between E2 supplied and deprived conditions. Noticeably, membrane-associated tyrosine-and threonine-specific cdc2-inhibitory kinase (PKMYT1), a WEE family kinase known to have estrogen response elements (EREs) in its regulatory region, was significantly decreased after E2 deprivation in E2-dependent PDXs (log2 fold change = -7.86, p&lt;0.001) but was constitutive in E2-independent PDXs. High PKMYT1 mRNA expression was associated with poor prognosis in the ER+ samples in METABRIC (hazard ratio=2.2, p&lt;0.001). In contrast, the more studied member of the WEE family, WEE1, lacks an estrogen response element (ERE) and is not E2-regulated from the kinome profiling result. WEE1 mRNA expression level is not associated with the outcome of patients with ER+ breast cancer, suggesting that PKMYT1 has evolved a specific role in the cell cycle of ER+ tumors.

Conclusion: Here, we analyzed the kinomes of 20 ER+ breast cancer PDX tumors with or without E2 by mass spectrometry. We discovered that PKMYT1 is a marker of hormone independent growth and poor outcome. Ongoing experiments that study the effects of PKMYT1 inhibition in both ER-dependent and independent circumstances will be presented.

Citation Format: Anran Chen, Beom-Jun Kim, Doug W Chan, Purba Singh, Lacey E Dobrolecki, Jonathan T Lei, Shunqiang Li, Alana L Welm, Michael T Lewis, Matthew J Ellis. Kinome profiling of ER+ breast cancer PDXs identifies PKMYT1 as a marker of hormone independent growth and poor outcome [abstract]. In: Proceedings of the 2020 San Antonio Breast Cancer Virtual Symposium; 2020 Dec 8-11; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2021;81(4 Suppl):Abstract nr PD8-02.

Abstract PS17-03: Recurrent active ESR1 fusions render a diagnostic transcriptional signature in metastatic breast cancer

Background: We recently reported two ESR1 fusions (ESR1-YAP1 and ESR1-PCDH11X) that drive endocrine therapy (ET) resistance and metastasis in estrogen receptor positive (ER+) metastatic breast cancer (MBC) (PMC6171747). Here, we report the functional properties of additional ESR1 fusions in ET-resistant MBC with an emphasis on the identification of a transcriptional signature designed to diagnose the presence of an active ESR1 fusion for targeted therapies directed against ESR1 fusion-driven biology. Methods: ESR1 fusions were detected by RNA-seq in ER+ MBC samples. ESR1 fusions were reproduced as cDNA constructs and expressed in ER+ breast cancer cell lines. Hormone-independent cell growth was detected by an Alamar blue assay and activated cell motility by a scratch wound assay. The transcriptional properties of ESR1 fusions was studied by RNA-seq followed by qPCR-based validation. Signature performance was evaluated using a ROC analysis on ER+ patient derived xenografts (PDX) harboring a variety of ESR1 somatic events. Results: All ESR1 fusions studied encoded the first six exons of ESR1 fused in-frame to diverse partner genes, thus replacing the ESR1 drug/ligand binding domain (LBD). Fusions involving a known transcription factor (TF) or coactivator (CoA) gene, including ESR1-YAP1, ESR1-SOX9 and ESR1-ARNT2 drove fulvestrant-resistant cell growth and hormone-independent cell motility. Other ESR1-e6 fusions, including ESR1-DAB2, ESR1-GYG1, ESR1-PCMT1 and ESR1-ARID1B did not induce these properties. From these examples, a functional rule is emerging whereby inter-chromosomal ESR1 translocations fused in-frame to 3’ partner genes with a positive role in transcription are active. Intra-chromosomal fusions with genes with no transcriptional roles are likely inactive. The ESR1-PCDH11X fusion is an exception, suggesting the need for continued functional study of non-TF/CoA partner ESR1-e6 fusions. RNA-seq of T47D cells expressing the full panel of gene fusions demonstrated an overlapping pattern of transcriptional activation focused on estrogen response and epithelial-to-mesenchymal transition (EMT) genes driven by active fusions. This gene signature was well-preserved in a PDX naturally expressing the ESR1-YAP1 fusion. Interestingly, further study showed that a series of ET-resistant PDXs bearing a variety of ESR1 LBD point mutations induced a similar pattern to the active ESR1 fusion signature suggesting overlapping transcriptional regulatory events between ESR1 fusions and ESR1 LBD mutations. The ESR1-D538G mutation conferred the most comparable gene dysregulation to ESR1 fusions. The Y537S/N and E380Q mutations also reproduced the signature driving hormone-independent growth but with exceptions. Two PDX lines bearing either a fully heterozygous Y537S or L536P mutations were surprisingly completely estrogen-dependent. Neither of these examples exhibited the ESR1 fusion gene signature, suggesting an unknown secondary event needed to fully express the phenotype of some ESR1 mutants. The gene signature distinguished ESR1 mutations (constitutively active fusions and point mutations) from wild-type ESR1, with a 92.0% Area Under Curve. Conclusion: Here, we show that ESR1 fusions are recurrent somatic mutations that lead to drug resistance and metastasis by transcriptional reprogramming. We describe a fusion gene signature that may be useful to determine whether an ESR1 fusion or mutation is transcriptionally active and is capable of driving hormone-independent growth and endocrine therapy resistance.

Citation Format: Xuxu Gou, Meenakshi Anurag, Jonathan T Lei, Purba Singh, Sinem Seker, Adrian V Lee, Dan R Robinson, Matthew J Ellis. Recurrent active ESR1 fusions render a diagnostic transcriptional signature in metastatic breast cancer [abstract]. In: Proceedings of the 2020 San Antonio Breast Cancer Virtual Symposium; 2020 Dec 8-11; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2021;81(4 Suppl):Abstract nr PS17-03.

Proteogenomic Landscape of Breast Cancer Tumorigenesis and Targeted Therapy

The integration of mass spectrometry-based proteomics with next-generation DNA and RNA sequencing profiles tumors more comprehensively. Here this "proteogenomics" approach was applied to 122 treatment-naive primary breast cancers accrued to preserve post-translational modifications, including protein phosphorylation and acetylation. Proteogenomics challenged standard breast cancer diagnoses, provided detailed analysis of the ERBB2 amplicon, defined tumor subsets that could benefit from immune checkpoint therapy, and allowed more accurate assessment of Rb status for prediction of CDK4/6 inhibitor responsiveness. Phosphoproteomics profiles uncovered novel associations between tumor suppressor loss and targetable kinases. Acetylproteome analysis highlighted acetylation on key nuclear proteins involved in the DNA damage response and revealed cross-talk between cytoplasmic and mitochondrial acetylation and metabolism. Our results underscore the potential of proteogenomics for clinical investigation of breast cancer through more accurate annotation of targetable pathways and biological features of this remarkably heterogeneous malignancy.

Abstract 5118: Proteogenomics characterization of HPV-negative head and neck squamous cell carcinomas

Patients with head and neck squamous cell carcinomas (HNSCCs) are treated with surgery, radiation, chemotherapy, and limited targeted therapies. Compared to human papillomavirus (HPV)-positive HNSCCs, HPV-negative cases have worse treatment response and prognosis and represent an unmet clinical need. We performed comprehensive proteogenomic characterization of tumor specimens, matched normal adjacent tissues (NATs), and blood samples from 109 HPV-negative HNSCC patients. This cohort is dominated by tumors from oral cavity (45, 41%) and larynx (49, 45%). Somatic mutation and somatic copy number analyses validated previously reported genomic aberrations in HPV-negative HNSCC. Proteomics analysis linked p53 loss of heterozygosity to increased expression of EPCAM, a stemness marker. Additionally, FAT1 truncation mutations were associated with increased expression of proteins involved in keratinization, a key feature of SCC differentiation. Deletions of 3p and 9p led to the loss of genes encoding p16, chemokine receptors, and interferon/JAK/STAT signaling pathway proteins, whereas amplifications of 3q and 11q led to overexpression of proteins involved in cell proliferation and anti-apoptosis pathways. Comparative analysis of tumor and NAT proteomes and phosphoproteomes identified putative diagnostic biomarkers and druggable targets, and proteogenomic integration further identified putative neoantigens. Tumor site-specific characterization associated epigenetic silencing of neurofilaments with laryngeal but not oral cavity SCC. Protein targets of FDA approved or investigational drugs for HNSCC treatment showed high inter-tumor heterogeneity in their protein abundances. DNA copy number and RNA expression level were good surrogates of protein abundance for some targets, such as EGFR and PD-L1, but they failed to reflect protein levels or kinase activities for other targets, such as MMP9 and MTOR. Thus, there is a critical need for protein biomarker-driven treatment stratification. Deconvolution of bulk tumor gene expression data revealed an immune-hot subgroup and an immune-cold subgroup. Immune-hot tumors broadly overexpressed multiple immune checkpoints including PD-L1, IDO1, and CTLA4, underscoring the necessity of combination immune checkpoint inhibition to improve treatment efficacy. Immune-cold tumors were characterized by smoking, chromosomal instability, and activation of the CDK4/6-pRb axis, suggesting they could be targeted by CDK4/6 inhibitors. We also noted that EGFR-amplified tumors frequently harbor copy number aberrations of downstream signaling components of the EGFR pathway. This may explain the low response rate of EGFR-amplified tumors to EGFR inhibitors, and targeting multiple pathway components, including EGFR, PIK3CA and STAT3, may be required for these tumors. In summary, our integrative proteogenomic characterization revealed multiple novel insights into the pathogenesis and treatment of HPV-negative HNSCCs.

Citation Format: Chen Huang, Lijun Chen, Yize Li, Sara Savage, Michael Schnaubelt, Felipe V. Leprevost, Marcin Cieslik, Yongchao Dou, Bo Wen, Jonathan T. Lei, Kai Li, Eric Jaehnig, Zhiao Shi, Meenakshi Anurag, Jianbo Pan, Yingwei Hu, Rodrigo V. Eguez, David J. Clark, Matthew Wyczalkowski, Saravana M. Dhanasekaran, Chandan Kumar, Antonio Colaprico, Karsten Krug, Michael Gillette, D. R. Mani, Seungyeul Yoo, Jiayi Ji, Xiaoyu Song, Weiping Ma, Xi Steven Chen, Alex Pico, Nathan J. Edwards, Scott D. Jewell, Mathangi Thiagarajan, Emily S. Boja, Henry Rodriguez, Andrew Sikora, Pei Wang, Matthew Ellis, Gilbert S. Omenn, Li Ding, Alexey I. Nesvizhskii, Adel K. EI-Naggar, Daniel W. Chan, Hui Zhang, Bing Zhang, Clinical Proteomic Tumor Analysis Consortium. Proteogenomics characterization of HPV-negative head and neck squamous cell carcinomas [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 5118.

Abstract 4385: Proteogenomics-driven synthetic lethality discovery to predict targetable protein dependencies induced by somatic deletions

Computational prediction of synthetic lethality has been shown as a promising approach to identify therapeutic vulnerabilities in many cancer types but has been limited to using genomics and transcriptomics data for discovery. Recent advancements on integrating mass spectrometry (MS)-based proteomics with genomics and transcriptomics in cancer research have produced proteogenomics datasets on large tumor cohorts, enabling the integration of proteomics data into synthetic lethality discovery. This is particularly attractive for tumors driven by loss-of-function alterations such as somatic deletions. Although deletions are challenging to target themselves, they may induce targetable protein dependencies, and this relationship can be identified through computational prediction of synthetic lethality. Here, we performed an unbiased discovery of such synthetic lethal interactions by identifying protein targets of drugs for which under-expression is observed significantly less than expected by chance with gene deletions using proteogenomics data from a breast cancer cohort with 105 tumors. We found many significant pairs uniquely driven by either protein under-expression (18,897 pairs) or mRNA under-expression (42,754 pairs) while only 5% (3,042 pairs) were supported by both protein and mRNA measurements. To systematically evaluate candidate synthetic lethal pairs, an AUROC analysis was performed using publicly available drug response data from breast cancer cells. Results showed synthetic lethal relationships supported by both protein and mRNA-based analyses were substantially more predictive of drug response (AUC = 81%) than protein alone (AUC = 65%) or mRNA alone (AUC = 61%). Despite having comparable AUCs, protein-based analysis showed much higher sensitivity than mRNA-based analysis when limiting false positive rate to less than 10%. An example of a synthetic lethal pair supported by both protein and mRNA-based analyses include tumors with low AURKA protein/mRNA and PARP2 deletions, which were significantly under-represented in the proteogenomics dataset (p = 0.003). Interestingly, these tumors were enriched for triple-negative breast tumors (p = 0.001), a type of breast cancer that lacks biomarkers to guide clinical treatment. This finding suggests AURKA as a putative dependency in triple-negative tumors with PARP2 deletion as a biomarker. Taken together, these results demonstrate that a multi-omics approach using proteomics to complement transcriptomics along with genomic changes may better predict therapeutic vulnerabilities in breast cancer with driver gene deletions than using proteomics or transcriptomics alone. As genomic testing has become more widely implemented as part of precision oncology programs, our approach to identifying protein dependencies induced by loss-of-function genomic alterations may provide new treatment opportunities for many patients with breast cancer or other tumor types.

Citation Format: Jonathan T. Lei, Eric Jaehnig, Bing Zhang. Proteogenomics-driven synthetic lethality discovery to predict targetable protein dependencies induced by somatic deletions [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 4385.

Abstract 5467: Outlier analysis to identify determinants of therapeutic resistance in breast cancer

Tumors are typically characterized by variable responses to targeted therapy driven by the heterogeneity of drivers among tumors. Inter-tumor heterogeneity also results in different resistance determinants to the same therapeutic agent. Outlier analysis has been applied extensively to identify drivers of cancer when comparing a heterogenous population of tumor samples to a relatively homogenous population of normal samples. However, the application of outlier analysis has rarely been applied to identify intrinsic determinants of resistance to targeted cancer therapies. We recently applied outlier analysis to baseline proteomics data collected from HER2/ERBB2 positive breast cancer patients treated with anti-HER2 therapy, comparing protein levels in each patient that did not show pathological complete response (pCR) to the population of patients that did. Three of the five non-pCR patients were outliers for low expression of the ERBB2 protein relative to the pCR patients, suggesting that lack of protein expression of the direct therapeutic target drives resistance in some cases whereas other mechanisms contribute to resistance in other cases. Here, we systematically evaluate the ability of multiple outlier analysis methods, including the method we implemented for the HER2 study (outlieR), to identify molecular genes associated with poor prognosis in estrogen receptor (ESR1) positive patients receiving hormone therapy (targeting ESR1) using a large-scale publicly available dataset which contains baseline gene expression and survival data for ~2000 breast cancer patients (METABRIC). Specifically, we compared expression data from tumors of 72 patients that showed poor prognosis (died of disease within 5 years) to data from 226 tumors from patients with good prognosis (did not die of disease, with at least five years of follow-up time). For this evaluation, we focused on the direct target of hormone therapy, ESR1, and growth factor receptors associated with endocrine therapy resistance. Scores from outlier analysis methods consistently ranked ESR1, EGFR, and genes associated with the ERBB2 locus (amplification of the locus drives ERBB2 gene expression in HER2 positive breast cancer) more highly than the the T-test metric did, with the outlieR method outperforming another established method, Outlier Sums (OS), in most cases. Furthermore, four targets of FDA-approved drugs, including two genes in the MAPK pathway, were amongst the top 200 genes identified by the outlieR method, whereas TOP2A was the only approved target in the top 200 genes identified by the T-test, a target of cytotoxic chemotherapy treatments. Finally, the outlieR method generates outlier scores for each gene in each non-responder relative to the set of non-responders, allowing for the evaluation of genes associated with resistance on a patient-by-patient basis. These observations suggest that outlier analysis can be used to prioritize molecular features as potential mechanisms of resistance and alternative drug targets by accounting for heterogeneity between resistant tumors.

Citation Format: Eric James Jaehnig, Meenakshi Anurag, Jonathan T. Lei, Bing Zhang. Outlier analysis to identify determinants of therapeutic resistance in breast cancer [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 5467.

Neurofibromin Is an Estrogen Receptor-α Transcriptional Co-repressor in Breast Cancer

We report that neurofibromin, a tumor suppressor and Ras-GAP (GTPase-activating protein), is also an estrogen receptor-α (ER) transcriptional co-repressor through leucine/isoleucine-rich motifs that are functionally independent of GAP activity. GAP activity, in turn, does not affect ER binding. Consequently, neurofibromin depletion causes estradiol hypersensitivity and tamoxifen agonism, explaining the poor prognosis associated with neurofibromin loss in endocrine therapy-treated ER⁺ breast cancer. Neurofibromin-deficient ER⁺ breast cancer cells initially retain sensitivity to selective ER degraders (SERDs). However, Ras activation does play a role in acquired SERD resistance, which can be reversed upon MEK inhibitor addition, and SERD/MEK inhibitor combinations induce tumor regression. Thus, neurofibromin is a dual repressor for both Ras and ER signaling, and co-targeting may treat neurofibromin-deficient ER⁺ breast tumors.

Abstract P6-04-04: Functional characterization of ESR1 fusions in breast cancer

Background: We recently reported two in-frame estrogen receptor alpha gene (ESR1) fusion transcripts, ESR1-YAP1 and ESR1-PCDH11X, in endocrine therapy (ET)-refractory, metastatic estrogen receptor positive (ER+) breast cancer patients. Both fusions were causal in driving ET resistance and metastasis in experimental models. CDK4/6 inhibition suppressed tumor growth driven by ESR1 fusions, but did not induce tumor regression (Lei et al., Cell Rep., 2018). Additional ESR1 fusions with diverse partner genes have been recently reported (ESR1-DAB2, ESR1-GYG1, and ESR1-SOX9) (Hartmaier et al., Ann Oncol., 2018), or communicated to us (ESR1-ARNT2, ESR1-PCMT1 and ESR1-ARID1B) (Dr. Dan R. Robinson, University of Michigan). All were identified in ET-refractory tumors. We therefore undertook detailed functional characterization of these new ESR1 fusions to examine their role as disease drivers. We also used mass spectrometry-based kinomics to identify therapeutic targets induced by individual ESR1 fusions.

Methods: Unreported ESR1 fusions were identified by RNA sequencing followed by informatics designed to identify fusion gene reads. Stable ER+ breast cancer cell lines (T47D and MCF7) expressing in-frame ESR1 fusion proteins were generated by lentiviral transduction. ET-resistant cell proliferation was assessed in low estradiol medium and/or in the presence of anti-estrogen. Expression of estrogen responsive and epithelial-to-mesenchymal transition (EMT) genes were measured by mRNA-qPCR. Cell motility driven by these fusions was examined using scratch wound assay. Kinase expression patterns were examined using a Kinase Inhibitor Pulldown (KIP) mass spectrometry-based assay.

Results: All the fusions we studied contain the first 6 exons (ESR1-e6) of ESR1 that provides the first 4 coding exons. In-frame C-terminal sequences were provided by different partner genes. In addition to previously described ESR1-YAP1 and ESR1-PCDH11X fusions, ESR1-SOX9 and ESR1-ARNT2 conferred estrogen-independent and fulvestrant-resistant growth in stable ER+ breast cancer cells (T47D and MCF7). In T47D cells, these ESR1 fusions upregulated not only classical ER targets, including GREB1, PGR, and TFF1, but also EMT-associated genes, SNAI1 (Snail) and VCAN in an estradiol-independent, fulvestrant-resistant manner. In addition, transcriptionally active ESR1 fusions promoted cell motility. KIP profiling of T47D cells expressing transcriptionally active ESR1 fusions and a patient-derived xenograft naturally harboring the ESR1-YAP1 fusion revealed an increase in abundance of multiple receptor tyrosine kinases including RET and insulin like growth factor 1 receptor (IGF1R). Responses to targeting these kinases have been observed in vitro. Other ESR1-e6 fusions produced stable proteins (ESR1-DAB2, ESR1-GYG1, ESR1-PCMT1, ESR1-ARID1B) but had much less clear transcriptional phenotypes and fewer upregulated kinases identified by KIP.

Conclusion: A classification of ESR1 fusions in ET-refractory breast cancer is emerging from this study. About half of ESR1-e6 fusions studied are transcriptionally active, presumably because the 3’ partner in these examples is encoded by transcription factor gene (TF) (SOX9 or ARNT2) or co-activator gene (CoA) (YAP1). These can be classified as ESR1-e6 TF/CoA fusions. The phenotype of the remaining fusions remains under investigation because of the functionally diverse nature of the 3’ partners and the low activity in functional assays. While some of these may be passengers, the example of PCDH11X suggests a non-TF/CoA partner ESR1-e6 fusion can still be active and further studies on additional fusions will be necessary. Downstream targeting of fusion-dependent kinases may be effective.

Citation Format: Xuxu Gou, Jonathan T Lei, Sinem Seker, Beom-Jun Kim, Saif Rehman, Adrian V Lee, Dan R Robinson, Matthew J Ellis. Functional characterization of ESR1 fusions in breast cancer [abstract]. In: Proceedings of the 2019 San Antonio Breast Cancer Symposium; 2019 Dec 10-14; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2020;80(4 Suppl):Abstract nr P6-04-04.

Functional Annotation of ESR1 Gene Fusions in Estrogen Receptor-Positive Breast Cancer

RNA sequencing (RNA-seq) detects estrogen receptor alpha gene (ESR1) fusion transcripts in estrogen receptor-positive (ER⁺) breast cancer, but their role in disease pathogenesis remains unclear. We examined multiple ESR1 fusions and found that two, both identified in advanced endocrine treatment-resistant disease, encoded stable and functional fusion proteins. In both examples, ESR1-e6>YAP1 and ESR1-e6>PCDH11X, ESR1 exons 1-6 were fused in frame to C-terminal sequences from the partner gene. Functional properties include estrogen-independent growth, constitutive expression of ER target genes, and anti-estrogen resistance. Both fusions activate a metastasis-associated transcriptional program, induce cellular motility, and promote the development of lung metastasis. ESR1-e6>YAP1- and ESR1-e6>PCDH11X-induced growth remained sensitive to a CDK4/6 inhibitor, and a patient-derived xenograft (PDX) naturally expressing the ESR1-e6>YAP1 fusion was also responsive. Transcriptionally active ESR1 fusions therefore trigger both endocrine therapy resistance and metastatic progression, explaining the association with fatal disease progression, although CDK4/6 inhibitor treatment is predicted to be effective.

Abstract 850: Evaluating preclinical efficacy of anti-HER2 drug combinations using ER+/HER2 mutant models

Targeting HER2 is one of the greatest successes in oncology, and has resulted in the generation of a wide array of HER2-targeting agents. Our genomic approaches are revealing other mechanisms of HER2 activation, such as our discovery of activating HER2 mutations in different cancer types. From initial breast cancer and SUMMIT trial data, the pan-HER drug neratinib as monotherapy showed initial clinical response in ER+ breast cancer, but with frequent early relapse. This study investigates the preclinical efficacy of anti HER2 agents alone or in combination with endocrine therapy agents or in combination with CDK4/6 inhibitors using ER+/HER2 mutant cell lines and ex vivo HER2 mutant patient derived xenograft (PDX) model. ER+ breast cancer cell lines (T47D and MCF7) stably expressing HER2V777L, and ER+/HER2 mutant PDX model (HER2G778_P780 dup) were used to examine HER2 signaling. We found that MCF7/T47D cells expressing HER2V777L and HER2G778_P780 dup PDX tumors showed strongly activated autophosphorylation of HER2 and increased expression of CDK4, CDK6, phospho-Rb, and cyclin D1 as compared to MCF7/T47D cells expressing HER2WT or ER+/non-HER2mut PDX model, suggesting that HER2 mutations preferentially depend on CDK4/6 signaling for cell growth. Additionally, we showed that activating MCF7 HER2V777L cause resistance to endocrine therapy treatment (fulvestrant IC50 &gt;5μM). Further, we show that neratinib alone is effective at higher concentrations (IC50 &lt; 2μM) in MCF7/HER2V777L cells. Next we showed that abemaciclib alone exhibited moderate activity against MCF7 HER2V777L cells (IC50 &lt; 0.4μM) and additional activity in combination with neratinib (IC50 &lt; 0.06μM) was seen. Moreover, ex vivo HER2G778_P780 dup cells are relatively resistant to fulvestrant alone (IC50 &lt; 0.2μM), neratinib alone (IC50 &lt; 0.006μM), abemaciclib alone (IC50 &lt; 0.04μM), and neratinib in combination with abemaciclib (IC50 &lt; 0.005μM), suggesting that patients harboring ER+/HER2-mutant tumors may benefit from neratinib in combination with abemaciclib. Therefore, we propose that simultaneous targeting of both HER2 and the CDK4/6 axis is required for maximal inhibition of ER+ breast cancers harboring HER2 activating mutations.

Citation Format: Vaishnavi Devarakonda, LaTerrica Williams, Sinem Seker, Jonathan T. Lei, Purba Singh, Airi Han, Meenakshi Anurag, Kimberly R. Holloway, Alana L. Welm, Matthew J. Ellis, Shyam M. Kavuri. Evaluating preclinical efficacy of anti-HER2 drug combinations using ER+/HER2 mutant models [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2019; 2019 Mar 29-Apr 3; Atlanta, GA. Philadelphia (PA): AACR; Cancer Res 2019;79(13 Suppl):Abstract nr 850.

Abstract 3479: Functional significance of ESR1 fusions with diverse gene partners in endocrine therapy resistant breast cancer

Emerging evidence suggests that ESR1 fusion transcripts that produce functional fusion proteins in estrogen receptor positive (ER+) breast cancer play a role in acquired endocrine therapy resistance. We recently reported two in-frame ESR1 fusion transcripts, ESR1-YAP1 and ESR1-PCDH11X, identified in patients with endocrine therapy resistant breast cancer. Both ESR1 fusions generated stable in-frame, fusion proteins that were transcriptionally active, driving endocrine therapy resistant proliferation and also promoting an epithelial-to-mesenchymal transition (EMT) transcriptional program leading to metastasis in experimental models. Here, we extend our studies by examining properties of additional ESR1 fusions with diverse partner genes, ESR1-DAB2, ESR1-GYG1, ESR1-SOX9, ESR1-ARNT2, ESR1-PCMT1, and ESR1-ARID1B, all identified in endocrine-refractory breast tumors, to better understand the role of ESR1fusion gene formation in endocrine therapy resistance. Structurally, ESR1-ARNT2, ESR1-PCMT1, and ESR1-ARID1B fusions retain the first 6 exons of ESR1, therefore lacking ESR1 exons encoding the ligand-binding domain (LBD) that endocrine therapies recognize, but are instead fused in-frame to C-terminal sequences from partner genes, which follows the same fusion pattern of previously identified ESR1-YAP1, ESR1-PCDH11X, ESR1-DAB2, ESR1-GYG1, and ESR1-SOX9 fusions. ESR1-ARNT2, ESR1-PCMT1, and ESR1-ARID1B constructs, along with ESR1-DAB2, ESR1-GYG1, and ESR1-SOX9 constructs were stably expressed in an ER+ breast cancer cell line, T47D, and all produced stable fusion proteins. ESR1-ARNT2 and ESR1-SOX9 promoted hormone-independent and fulvestrant-resistant cell proliferation that was sensitive to cyclin-dependent kinase (CDK) 4/6 inhibitors, palbociclib and abemaciclib. In addition, ESR1-ARNT2 induced hormone-independent activation of estrogen responsive genes (TFF1, GREB1, and PGR), and EMT genes (SNAI1 and VCAN) along with upregulation of Snail protein. These results indicate that ESR1-ARNT2 and ESR1-SOX9 have similar functional and pharmacological properties to our previously described ESR1-YAP1 and ESR1-PCDH11X fusions. These data further support a role for ESR1 fusions in driving not only endocrine therapy resistance but also activating the metastatic process. Ongoing studies are examining the ability of ESR1 fusions to induce EMT phenotypes and to determine structure function relationships of ESR1 fusions. Although the formation of ESR1 fusions likely confers resistance to all endocrine therapies that target the LBD, ESR1 fusion driven growth remained sensitive to CDK4/6 inhibitor treatment therefore providing rationale for testing ESR1 fusion detection in guiding treatment with CDK4/6 monotherapy.

Citation Format: Jonathan T. Lei, Xuxu Gou, Sinem Seker, Vaishnaivi Devorakonda, Kimberly R. Holloway, Adrian V. Lee, Dan R. Robinson, Matthew J. Ellis. Functional significance of ESR1 fusions with diverse gene partners in endocrine therapy resistant breast cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2019; 2019 Mar 29-Apr 3; Atlanta, GA. Philadelphia (PA): AACR; Cancer Res 2019;79(13 Suppl):Abstract nr 3479.

Copy number alterations associated with clinical features in an underrepresented population with breast cancer

Background

As the most incident tumor among women worldwide, breast cancer is a heterogeneous disease. Tremendous efforts have been made to understand how tumor characteristics as histological type, molecular subtype, and tumor microenvironment collectively influence disease diagnosis to treatment, which impact outcomes. Differences between populations and environmental and cultural factors have impacts on the origin and evolution of the disease, as well as the therapeutic challenges that arise due to these factors. We, then, compared copy number variations (CNVs) in mucinous and nonmucinous luminal breast tumors from a Brazilian cohort to investigate major CNV imbalances in mucinous tumors versus non‐mucinous luminal tumors, taking into account their clinical and pathological features.

Methods

48 breast tumor samples and 48 matched control blood samples from Brazilian women were assessed for CNVs by chromosome microarray. Logistic regression and random forest models were used in order to assess CNVs in chromosomal regions from tumors.

Results

CNVs that were identified in chromosomes 1, 5, 8, 17, 19, and 21 classify tumors according to their histological type, ethnicity, disease stage, and familial history.

Conclusion

Copy number alterations described in this study provide a better understanding of the landscape of genomic aberrations in mucinous breast cancers that are associated with clinical features.

ESR1 alterations and metastasis in estrogen receptor positive breast cancer

Endocrine therapy is essential for the treatment of patients with estrogen receptor positive (ER+) breast cancer, however, resistance and the development of metastatic disease is common. Understanding how ER+ breast cancer metastasizes is critical since the major cause of death in breast cancer is metastasis to distant organs. Results from many studies suggest dysregulation of the estrogen receptor alpha gene (ESR1 ) contributes to therapeutic resistance and metastatic biology. This review covers both pre-clinical and clinical evidence on the spectrum of ESR1 alterations including amplification, point mutations, and genomic rearrangement events driving treatment resistance and metastatic potential of ER+ breast cancer. Importantly, we describe how these ESR1 alterations may provide therapeutic opportunities to improve outcomes in patients with lethal, metastatic breast cancer.

Abstract P6-17-15: Evaluating preclinical efficacy of anti-HER2 drug combinations using ER+/HER2 mutant models

Background

Until recently, HER2 gene amplification was the only mechanism of HER2 activation recognized. However, activating HER2 mutations have been noted in different cancer types. A trials of HER2 mutant breast cancer and the subsequent SUMMIT trial data have shown that monotherapy with the pan-HER drug neratinib as showed clinical efficacy, but with poor response durability. This study therefore investigates the preclinical efficacy of anti HER2 agents alone or in combination with endocrine therapy agents or in combination with CDK4/6 inhibitors using ER+/HER2 mutant cell lines and ex vivo HER2 mutant patient derived xenograft (PDX) model to define a more effective treatment approach.

Methods

ER+ breast cancer cell lines (T47D and MCF7) stably expressing HER2V777L, and ER+/HER2 mutant PDX model (HER2G778_P780 dup) were used to examine HER2 signaling and drug responses. Signaling downstream mutant HER2 was examined by immunoblot analysis. Effects of neratinib alone, neratinib + fulvestrant, and neratinib + abemaciclib on cell growth were examined in ER+/HER2 mutant cell lines and in an ex vivo HER2G778_P780 dup.

Results

We found that MCF7/T47D cells expressing HER2V777L and HER2G778_P780 dup PDX tumors showed strongly activated autophosphorylation of HER2 and increased expression of CDK4, CDK6, phospho-Rb, and cyclin D1 as compared to MCF7/T47D cells expressing HER2WT or ER+/non-HER2mut PDX modes, suggesting that HER2 mutations preferentially depend on CDK4/6 signaling for cell growth. Additionally, we showed that activating MCF7 HER2 V777L cause resistance to endocrine therapy treatment (fulvestrant IC50 &gt;5μM). Further, we show that neratinib alone is effective at higher concentrations (IC50 &lt; 2μM) in MCF7/HER2 V777L cells. We also demonstrate that abemaciclib alone exhibited moderate activity against MCF7 HER2 V777L cells (IC50 &lt; 0.4μM) and additional activity in combination with neratinib (IC50 &lt; 0.06μM) was seen. Moreover, ex vivo HER2 G778_P780 dup cells are relatively resistant to fulvestrant alone (IC50 &lt; 0.2μM), neratinib alone (IC50 &lt; 0.006μM), abemaciclib alone (IC50 &lt; 0.04μM), and neratinib in combination with abemaciclib (IC50 &lt; 0.005μM), suggesting that patients harboring ER+/HER2-mutant tumors may benefit from neratinib in combination with abemaciclib.

Conclusion

These preclinical data suggest that neratinib monotherapy may not be effective to treat ER+/HER2 mutant patients and we propose that simultaneous targeting of both HER2 and the CDK4/6 axis will be required for effective treatment of ER+ breast cancers harboring HER2 activating mutations.

Citation Format: Kavuri SM, Devarakonda V, Williams LC, Seker S, Lei JT, Singh P, Han A, Anurag M, Holloway KR, Welm AL, Ellis MJ. Evaluating preclinical efficacy of anti-HER2 drug combinations using ER+/HER2 mutant models [abstract]. In: Proceedings of the 2018 San Antonio Breast Cancer Symposium; 2018 Dec 4-8; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2019;79(4 Suppl):Abstract nr P6-17-15.

Abstract P5-04-01: Functional and therapeutic significance of ESR1 fusions in metastatic ER+ breast cancer

Background. Next-generation sequencing methods have identified several ESR1 fusion genes in treatment refractory ER+ breast cancer, however detailed functional studies in experimental models are lacking and how they might be targeted remains poorly understood. We recently reported two transcriptionally active, in-frame ESR1 fusions, ESR1-YAP1 and ESR1-PCDH11X, identified in a small cohort of metastatic ER+ cases, that induce not only pan-endocrine therapy resistance but also metastatic disease progression (Lei et al., Cell Reports, in press). Limited characterization of ESR1-DAB2 and ESR1-GYG1, also identified in metastatic ER+ disease from a recent study, suggests these two ESR1 fusions also drive estrogen-independent gene activation (Hartmaier et al., Annals of Oncology, 2018). Here, we functionally characterize ESR1-DAB2 and ESR1-GYG1 along with additional ESR1 fusions discovered in metastatic ER+ breast tumors to further support a causal role for in-frame ESR1 fusions in driving endocrine therapy resistance and promoting metastasis-associated biology, and explore therapeutic vulnerabilities induced by ESR1 fusion gene formation.

Methods. RNA-seq identified ESR1 fusions from treatment refractory, ER+ metastatic breast tumors. In-frame ESR1 fusions constructs were generated and stably expressed in ER+ breast cancer cell lines: T47D, MCF7, and ZR75-1. Estrogen-independent and fulvestrant-resistant growth was monitored in hormone-deprived stable cell lines. mRNA-qPCR was performed to examine expression of estrogen responsive and epithelial-to-mesenchymal transition (EMT) genes. In vitro sensitivity to CDK4/6 inhibition was tested with palbociclib and abemaciclib.

Results. In addition to previously described ESR1-YAP1, ESR1-PCDH11X, ESR1-DAB2, and ESR1-GYG1, that follow a pattern retaining the first 6 exons of ESR1 (ESR1-e6) fused in-frame to C-terminal sequences provided by the partner gene, additional in-frame ESR1-e6 fusions, ESR1-PCMT1, ESR1-ARNT2, and ESR1-ARID1B, all identified in metastatic ER+ samples, were found to follow the same fusion pattern. ESR1-DAB2 and ESR1-GYG1 produced stable ESR1 fusion proteins in ER+ breast cancer cell lines. In T47D, these two fusions drove estrogen-independent and fulvestrant-resistant growth. In addition, T47D and ZR75-1 models revealed that ESR1-DAB2 drove estrogen-independent expression of estrogen responsive genes and also EMT genes, including SNAI1, suggesting this fusion, like ESR1-YAP1 and ESR1-PCDH11X, could also drive metastasis. Treatment with CDK4/6 inhibitors suppressed growth induced by ESR1-DAB2 and ESR1-GYG1.

Conclusion. The majority of in-frame ESR1 exon 6 fusions found in metastatic ER+ breast are transcriptionally active, drive endocrine therapy resistant proliferation, and induce an EMT-like transcriptional program. The ability to block ESR1 fusion induced growth with a CDK4/6 inhibitor is clinically significant as ESR1 fusion gene formation renders ER insensitive to all endocrine therapies that target the ligand binding domain. Furthermore, clinical diagnosis of an active ESR1 fusion could potentially stratify patients for CDK4/6 inhibitor treatment. This presentation is the most complete description of the role for ESR1 fusions in endocrine therapy resistance and metastasis described to date.

Citation Format: Lei JT, Gou X, Seker S, Haricharan S, Lee AV, Robinson DR, Ellis MJ. Functional and therapeutic significance of ESR1 fusions in metastatic ER+ breast cancer [abstract]. In: Proceedings of the 2018 San Antonio Breast Cancer Symposium; 2018 Dec 4-8; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2019;79(4 Suppl):Abstract nr P5-04-01.

Abstract P5-08-01: DPYSL3 modulates mitosis, migration and epithelial to mesenchymal transition in claudin-low breast cancer

Proteogenomics is the field of integrating data from mass spectrometry-based shotgun proteomics, and phosphoproteomics into next-generation RNA and DNA sequencing data analysis pipelines that promises new insights into cancer biology and therapeutic targeting. As well as analyses of clinical samples for disease phenotype association analysis, the application of proteogenomics to model systems also has considerable potential. A Clinical Proteomic Tumor Analysis Consortium (CPTAC) proteogenomic analysis prioritized dihydropyrimidinase-like-3 (DPYSL3) as a multi-level (RNA/Protein/Phosphoprotein) expression outlier specific to the Claudin-Low (CLOW) subset of triple negative breast cancers. A Pubmed informatics tool indicated a paucity of data in the context of breast cancer which further prioritized DPYSL3 for study.

DPYSL3 was identified as a protein that is regulated during neuronal differentiation in the cerebral cortex and in neuronal cell lines and plays a role in regulating neurite outgrowth somehow through an association with vesicles in the growth cone. In addition, DPYSL3 expression has been observed in several malignant tumors, including prostate cancer, pancreatic cancer, gastric cancer and neuroblastoma. DPYSL3 is reported to play a role in cell migration and metastasis suppression in prostate cancer. However, in pancreatic cancer, DPYSL3 is positively associated with liver metastasis and poor outcome.

DPYSL3 knock-down in DPYSL3 (+) CLOW cell lines demonstrated reduced proliferation, yet enhanced motility and increased expression of Epithelial to Mesenchymal Transition (EMT) markers suggesting that DPYSL3 is a multi-functional signaling modulator. Slower proliferation in DPYSL3 (-) CLOW cells was associated with accumulation of multi-nucleated cells indicating a mitotic defect that was associated with a collapse of the vimentin (VIM) microfilament networkinduced by VIM hyperphosphorylation. On the other hand, DPYSL3 suppressed the expression of EMT regulators TWIST and SNAIL and opposed p21 activated kinase 2 (PAK2) dependent migration, but these EMT regulators in turn induced DPYSL3 expression, suggesting DPYSL3 participates in negative feedback in EMT. Cell migration in DPYSL3 (-) cells correlated with increased phosphorylation of PAK2 on Ser20 and was sensitive to PAK2 siRNA and pharmacological PAK inhibition.Immunoprecipitation and mass spectrometry-based proteomics or western blotting strongly suggests that PAKs interact such that DPYSL3 may function as a direct negative regulator of PAK family kinases. Thus, a PAK inhibitor could potentially mitigate increase migration as an adverse effect of DPYSL3 suppression.

In conclusion, DPYSL3 is a remarkable multifunctional signaling scaffold that should be examined further to provide insights into the stem cell-like state of claudin-low breast cancers, particularly in terms of their cell cycle dependencies, migratory activity and capacity for EMT.

Citation Format: Matsunuma R, Chan DW, Kim B-J, Singh P, Han A, Saltzman A, Cheng C, Lei JT, Sahin E, Leng M, Fan C, Perou CM, Malovannaya A, Ellis MJ. DPYSL3 modulates mitosis, migration and epithelial to mesenchymal transition in claudin-low breast cancer [abstract]. In: Proceedings of the 2018 San Antonio Breast Cancer Symposium; 2018 Dec 4-8; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2019;79(4 Suppl):Abstract nr P5-08-01.

ESR1 fusions drive endocrine therapy resistance and metastasis in breast cancer

Estrogen receptor alpha gene (ESR1) fusion transcripts have been identified in breast cancer but their role in breast cancer is not completely understood. Here, we report a causal role for ESR1 fusions in driving both endocrine therapy resistance and metastasis, and describe a therapeutic strategy to target ESR1 fusion-induced growth.

Abstract 1814: NF1 as an estrogen receptor-α co-repressor in breast cancer

NF1 has been best known as a GAP (GTPase Activating Protein) that inactivates Ras. However, we are now finding evidence that it also functions as an ER co-repressor, whose loss leads to endocrine therapy resistance. Sequencing tumor DNA from &gt;600 ER+ breast cancers treated by tamoxifen adjuvant monotherapy, we found that frameshift (FS) and nonsense (NS) NF1 mutations, which can create an NF1-null state, strongly correlate with relapse risk (HR=2.6, submitted). Surprisingly, no recurrent missense NF1 mutations inactivating GAP activity were found in our cohort, and such mutations are rare in primary cancers in general. We thus posulated that complete loss of NF1 protein (e.g., caused by NS/FS mutations), but not GAP inactivation alone, is required to drive endocrine therapy resistance.

Here we demonstrate that NF1 loss (by gene silencing) in ER+ breast cancer cells greatly enhances ligand-dependent ER transcriptional activity in vitro and in vivo, causing estradiol (E2) hypersensitivity and tamoxifen agonism. Mechanistically we show that NF1 can bind directly to ER, an interaction enhanced by tamoxifen but not by E2. Binding is mediated by leucine/isoleucine-rich motifs in NF1, analogous to other ER co-repressors. Mutations in these motifs (some of which are targeted by somatic mutation in cancer) inhibit ER binding and transcriptional activity without impacting GAP activity; conversely, inactivating GAP activity does not impact ER binding and repression. To validate NF1 as an ER co-repressor, we examined proteomic data from &gt;100 breast cancer patients in the CPTAC data base and found that proteins whose levels are positively correlated with NF1 are highly enriched with factors known to bind nuclear receptors; by contrast, levels of another GAP, p120, which lacks ER binding sites, are negatively correlated with these molecules. Importantly, preclinical treatment studies indicate that while NF1-deficient ER+ breast cancer should not be treated by tamoxifen or aromatase inhibitors, fulvestrant, which degrades ER, remains effective. However, fulvestrant monotherapy can activate the Ras-MAP pathway, which may promote cell survival and acquired fulvestrant resistance unless combined with dabrafinib and trametinib to inhibit Raf and MEK —a clinical trial for this combination is in development.

Our data suggest that NF1 is a dual negative regulator at the intersection of two potent oncogenic signaling pathways, Ras and ER. Combination therapy targeting both the ER and the Ras-Raf pathways should be investigated for NF1-deficient cancers driven by ER.

Citation Format: Eric C. Chang, zeyi Zheng, Meenakshi Anurag, Jin Gao, Burcu Cakar, Xinhui Du, Jing Li, Philip Lavere, Jonathan T. Lei, Purba Singh, Sinem Seker, Wei Song, Jianheng Peng, Tiffany Nguyen, Doug Chan, Xi Chen, Kimberly C. Banks, Richarad B. Lanman, Maryam Shafaee, Susan Hilsenbeck, Charles Foulds, Matthew J. Ellis. NF1 as an estrogen receptor-α co-repressor in breast cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2018; 2018 Apr 14-18; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2018;78(13 Suppl):Abstract nr 1814.

Abstract 5240: Functional and therapeutic significance of ESR1 gene fusions in breast cancer

RNA sequencing detects estrogen receptor alpha gene (ESR1) fusion transcripts in estrogen receptor positive (ER+) breast cancer but their role in disease pathogenesis remains unclear. Herein we examined multiple in-frame and out-of-frame ESR1 fusions and found only two, both identified in advanced endocrine treatment resistant disease, encoded stable and functional in-frame fusion proteins. In both examples, ESR1-e6&gt;YAP1 and ESR1-e6&gt;PCDH11X, the N-terminal, DNA binding and dimerization motifs encoded by exons 2-6 were fused to C-terminal sequences from the partner gene. Functional properties included estrogen-independent growth, constitutive expression of ER target genes, anti-estrogen resistance, induction of cellular motility in vitro and the development of lung metastasis in vivo. Chromatin immunoprecipitation and RNA sequencing experiments showed both fusions uniquely activated a metastasis-associated transcriptional program. ESR1-e6&gt;YAP1 and ESR1-e6&gt;PCDH11X-induced growth remained sensitive to a CDK4/6 inhibitor, palbociclib, and a patient-derived xenograft (PDX) expressing the ESR1-e6&gt;YAP1 fusion was also responsive. Transcriptionally active ESR1 fusions therefore trigger both endocrine therapy resistance and metastatic progression explaining the association with fatal disease progression, although CDK4/6 inhibitor treatment is predicted to be effective.

Citation Format: Jonathan T. Lei, Jieya Shao, Jin Zhang, Michael Iglesia, Doug W. Chan, Jin Cao, Meenakshi Anurag, Purba Singh, Xiaping He, Yoshimasa Kosaka, Ryoichi Matsunuma, Robert Crowder, Jeremy Hoog, Chanpheng Phommaly, Rodrigo Goncalves, Susana Romalho, Raquel M. Peres, Nindo Punturi, Cheryl Schmidt, Alex Bartram, Eric Jou, W V. Lai, Oliver Hampton, Anna Rogers, Ethan Tobias, Poojan Parikh, Sherri R. Davies, Shunqiang Li, Cynthia X. Ma, Vera Suman, Kelly K. Hunt, Mark A. Watson, Katherine A. Hoadley, E A. Thompson, Xi Chen, Shyam M. Kavuri, Chad J. Creighton, Christopher A. Maher, Charles M. Perou, Svasti Haricharan, Matthew J. Ellis. Functional and therapeutic significance of ESR1 gene fusions in breast cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2018; 2018 Apr 14-18; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2018;78(13 Suppl):Abstract nr 5240.

Proteomic profiling identifies key coactivators utilized by mutant ERα proteins as potential new therapeutic targets

Approximately 75% of breast cancers are estrogen receptor alpha (ERα)-positive and are treatable with endocrine therapies, but often patients develop lethal resistant disease. Frequent mutations (10–40%) in the ligand-binding domain (LBD) codons in the gene encoding ERα (ESR1) have been identified, resulting in ligand-independent, constitutively active receptors. In addition, ESR1 chromosomal translocations can occur, resulting in fusion proteins that lack the LBD and are entirely unresponsive to all endocrine treatments. Thus, identifying coactivators that bind to these mutant ERα proteins may offer new therapeutic targets for endocrine-resistant cancer. To define coactivator candidate targets, a proteomics approach was performed profiling proteins recruited to the two most common ERα LBD mutants, Y537S and D538G, and an ESR1-YAP1 fusion protein. These mutants displayed enhanced coactivator interactions as compared to unliganded wild-type ERα. Inhibition of these coactivators decreased the ability of ESR1 mutants to activate transcription and promote breast cancer growth in vitro and in vivo. Thus, we have identified specific coactivators that may be useful as targets for endocrine-resistant breast cancers.

Abstract PD8-03: ESR1 gene fusions drive endocrine therapy resistance and metastasis in breast cancer

Background. Dysregulation of the estrogen receptor gene (ESR1) is an established mechanism of inducing endocrine therapy resistance. We previously discovered a chromosomal translocation event generating an estrogen receptor gene fused in-frame to C-terminal sequences of YAP1 (ESR1-YAP1) that contributed to endocrine therapy resistance in estrogen receptor positive (ER+) breast cancer models. This study compares functional, transcriptional, and pharmacological properties of additional ESR1 gene fusion events of both early stage (ESR1-NOP2) late stage (ESR1-YAP1 and ESR1-PCDH11x) breast cancers to gain a better understanding of therapeutic resistance and metastasis. Understanding the role of ESR1 fusions in inducing metastasis is critical, since the primary cause of death in breast cancer patients is through metastasis to distant sites.

Methods. RNA-seq screens identified ESR1 fusions from early and late stage, endocrine therapy resistant breast tumor samples. Functional experiments were conducted using ER+ breast cancer cell lines, xenograft, and PDX models to test the ability of ESR1 fusions to induce therapeutic resistance and metastasis. ChIP-seq and RNA-seq were performed to examine transcriptional properties and differential gene expression induced by the fusions which directed subsequent pharmacological experiments with a CDK4/6 inhibitor.

Results. ESR1-YAP1 and ESR1-PCDH11x promoted estrogen-independent and fulvestrant-resistant growth in vitro and induced greater tumor growth and increased metastatic capacity to the lungs of xenografted mice. In contrast, the ESR1-NOP2 fusion was sensitive to low estrogen conditions in vitro, and did not promote tumor growth. RNA-seq profiling revealed E2F targets pathway as the most highly enriched pathway induced by the ESR1 fusions. IHC revealed higher levels of pRb in ESR1-YAP1 and ESR1-PCDH11x xenograft tumors and subsequent CDK4/6 inhibition completely blocked tumor growth in an ESR1-YAP1 PDX model. Integrating RNA-seq with ChIP-seq data, we discovered a set of EMT and metastasis genes bound by all ESR1 fusions and WT-ER, but whose expression was strongly and uniquely up-regulated only by the ESR1-YAP1 and ESR1-PCDH11x fusions. These studies also revealed gained sites bound only by the ESR1-YAP1 and ESR1-PCDH11x fusions, not bound by WT-ER nor ESR1-NOP2. Genes mapping to these sites have a role in metastatic biology and were highly up-regulated by the YAP1 and PCDH11x fusions, potentially mediated by long range transcriptional activation.

Conclusion. ESR1-YAP1 and ESR1-PCDH11x are driver fusions that occur in drug-resistant, advanced stage breast cancer and are a new class of recurrent somatic mutation that can cause acquired endocrine therapy resistance, yet can be treated with CDK4/6 inhibition. These driver fusions also confer increased metastatic ability through their ability to drive expression of genes that contribute to EMT and metastasis. In contrast, ESR1-NOP2 did not produce functional protein and appears to be a passenger event. These studies may provide pre-clinical rationale for targeting ESR1 translocated breast tumors, since the presence of an ESR1 driver fusion places a patient in a therapeutic category where none of the currently available endocrine therapies are likely to be effective.

Citation Format: Lei JT, Shao J, Zhang J, Iglesia M, Chan DW, Cao J, Anurag M, Singh P, Haricharan S, Kavuri SM, Matsunuma R, Schmidt C, Kosaka Y, Crowder R, Hoog J, Phommaly C, Goncalves R, Ramalho S, Rodrigues-Peres RM, Lai W-C, Hampton O, Rogers A, Tobias E, Parikh P, Davies S, Ma C, Suman V, Hunt K, Watson M, Hoadley KA, Thompson A, Perou CM, Creighton CJ, Maher C, Ellis MJ. ESR1 gene fusions drive endocrine therapy resistance and metastasis in breast cancer [abstract]. In: Proceedings of the 2017 San Antonio Breast Cancer Symposium; 2017 Dec 5-9; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2018;78(4 Suppl):Abstract nr PD8-03.

Loss of MutL Disrupts CHK2-Dependent Cell-Cycle Control through CDK4/6 to Promote Intrinsic Endocrine Therapy Resistance in Primary Breast Cancer

Significant endocrine therapy-resistant tumor proliferation is present in ≥20% of estrogen receptor-positive (ER⁺) primary breast cancers and is associated with disease recurrence and death. Here, we uncover a link between intrinsic endocrine therapy resistance and dysregulation of the MutL mismatch repair (MMR) complex (MLH1/3, PMS1/2), and demonstrate a direct role for MutL complex loss in resistance to all classes of endocrine therapy. We find that MutL deficiency in ER⁺ breast cancer abrogates CHK2-mediated inhibition of CDK4, a prerequisite for endocrine therapy responsiveness. Consequently, CDK4/6 inhibitors (CDK4/6i) remain effective in MutL-defective ER⁺ breast cancer cells. These observations are supported by data from a clinical trial where a CDK4/6i was found to strongly inhibit aromatase inhibitor-resistant proliferation of MutL-defective tumors. These data suggest that diagnostic markers of MutL deficiency could be used to direct adjuvant CDK4/6i to a population of patients with breast cancer who exhibit marked resistance to the current standard of care.Significance: MutL deficiency in a subset of ER⁺ primary tumors explains why CDK4/6 inhibition is effective against some de novo endocrine therapy-resistant tumors. Therefore, markers of MutL dysregulation could guide CDK4/6 inhibitor use in the adjuvant setting, where the risk benefit ratio for untargeted therapeutic intervention is narrow. Cancer Discov; 7(10); 1168-83. ©2017 AACR.This article is highlighted in the In This Issue feature, p. 1047.

Abstract 1033: Estrogen receptor gene fusions drive endocrine therapy resistance in estrogen receptor positive breast cancer

Dysregulation of estrogen receptor gene (ESR1) is an established mechanism of inducing endocrine therapy resistance. We previously discovered a chromosomal translocation event generating an estrogen receptor gene fused in-frame to C-terminal sequences of YAP1 (ESR1-YAP1) that contributed to endocrine therapy resistance in estrogen receptor positive (ER+) breast cancer models. This current study compares functional and pharmacological properties of additional ESR1 gene fusion events of both early stage (ESR1-NOP2) and advanced endocrine therapy resistant (ESR1-YAP1 and ESR1-PCDH11x) breast cancers. The YAP1 and PCDH11x fusions conferred estrogen-independent and fulvestrant-resistant growth in T47D, an ER+ breast cancer cell line in vitro and in vivo, in contrast to the NOP2 fusion which was sensitive to hormone deprivation. Immunohistochemical (IHC) staining of mouse lungs revealed significantly higher numbers of micrometastatic ER+ cells from the T47D tumors expressing the YAP1 and PCDH11x fusions than YFP control and NOP2 fusion. Estrogen response element (ERE) reporter and pull down assays revealed that although all ESR1 fusions studied bound EREs, only the YAP1 and PCDH11x caused ERE activation. Cell lines containing these “canonical” ESR1 fusions upregulated expression of ER responsive genes such as TFF1 and GREB1 in hormone deprived conditions. In contrast, the NOP2 fusion neither induced ERE activity nor upregulated TFF1 and GREB1 gene expression. The proliferative ability of canonical fusion-containing T47D cells was inhibited by palbociclib, a CDK4/6 inhibitor, in a dose-dependent manner. In vivo growth of patient-derived xenograft tumors naturally harboring the ESR1-YAP1 fusion (WHIM18) was significantly reduced in mice fed palbociclib-containing chow. Mice transplanted with WHIM18 also formed lung micrometastases, with an ER IHC staining pattern similar to lungs from YAP1 and PCDH11x fusion expressing T47D xenografts. In conclusion, in-frame ERE activating canonical fusions occur in end-stage, drug resistant, advanced breast cancer and can be added to ESR1 point mutations as a class of somatic mutation that may cause acquired resistance. Endocrine therapy resistant growth induced by these fusions can be treated with CDK4/6 inhibition, using an FDA approved drug, palbociclib, which could potentially improve outcomes in patients with ESR1 translocated tumors.

Citation Format: Jonathan T. Lei, Jieya Shao, Jin Zhang, Michael Iglesia, Doug W. Chan, Ryoichi Matsunuma, Xiaping He, Purba Singh, Yoshimasa Kosaka, Robert Crowder, Svasti Haricharan, Shyam Kavuri, Jeremy Hoog, Chanpheng Phommaly, Rodrigo Goncalves, Susana Romalho, Wei-Chu Lai, Oliver Hampton, Anna Rogers, Ethan Tobias, Poojan Parikh, Sherri Davies, Cynthia Ma, Vera Suman, Kelly Hunt, Mark Watson, Katherine A. Hoadley, Aubrey Thompson, Charles Perou, Chad J. Creighton, Chris Maher, Matthew J. Ellis. Estrogen receptor gene fusions drive endocrine therapy resistance in estrogen receptor positive breast cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2017; 2017 Apr 1-5; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2017;77(13 Suppl):Abstract nr 1033. doi:10.1158/1538-7445.AM2017-1033