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Metastatic breast cancer is an intractable disease that responds poorly to immunotherapy. We show that p38MAPKα inhibition (p38i) limits tumor growth by reprogramming the metastatic tumor microenvironment in a CD4+ T cell-, IFNγ-, and macrophage-dependent manner. To identify targets that further increased p38i efficacy, we utilized a stromal labeling approach and single-cell RNA sequencing. Thus, we combined p38i and an OX40 agonist that synergistically reduced metastatic growth and increased overall survival. Intriguingly, patients with a p38i metastatic stromal signature had better overall survival that was further improved by the presence of an increased mutational load, leading us to ask if our approach would be effective in antigenic breast cancer. The combination of p38i, anti-OX40, and cytotoxic T-cell engagement cured mice of metastatic disease and produced long-term immunologic memory. Our findings demonstrate that a detailed understanding of the stromal compartment can be used to design effective antimetastatic therapies. Significance: Immunotherapy is rarely effective in breast cancer. We dissected the metastatic tumor stroma, which revealed a novel therapeutic approach that targets the stromal p38MAPK pathway and creates an opportunity to unleash an immunologic response. Our work underscores the importance of understanding the tumor stromal compartment in therapeutic design.

Estrogen receptor alpha (ER/ESR1) mutations occur in 30% to 40% of endocrine resistant ER-positive (ER+) breast cancer. Forkhead box A1 (FOXA1) is a key pioneer factor mediating ER–chromatin interactions and endocrine response in ER+ breast cancer, but its role in ESR1-mutant breast cancer remains unclear. Our previous FOXA1 chromatin immunoprecipitation sequencing (ChIP-seq) identified a large portion of redistributed binding sites in T47D genome-edited Y537S and D538G ESR1–mutant cells. Here, we further integrated FOXA1 genomic binding profile with the isogenic ER cistrome, accessible genome, and transcriptome data of T47D cell model. FOXA1 redistribution was significantly associated with transcriptomic alterations caused by ESR1 mutations. Furthermore, in ESR1-mutant cells, FOXA1-binding sites less frequently overlapped with ER, and differential gene expression was less associated with the canonical FOXA1–ER axis. Motif analysis revealed a unique enrichment of retinoid X receptor (RXR) motifs in FOXA1-binding sites of ESR1-mutant cells. Consistently, ESR1-mutant cells were more sensitive to growth stimulation with the RXR agonist LG268. The mutant-specific response was dependent on two RXR isoforms, RXR-α and RXR-β, with a stronger dependency on the latter. In addition, T3, the agonist of thyroid receptor (TR) also showed a similar growth-promoting effect in ESR1-mutant cells. Importantly, RXR antagonist HX531 blocked growth of ESR1-mutant cells and a patient-derived xenograft (PDX)-derived organoid with an ESR1 D538G mutation. Collectively, our data support the evidence for a stronger RXR response associated with FOXA1 reprograming in ESR1-mutant cells, suggesting development of therapeutic strategies targeting RXR pathways in breast tumors with ESR1 mutation. Implications: It provides comprehensive characterization of the role of FOXA1 in ESR1-mutant breast cancer and potential therapeutic strategy through blocking RXR activation.

Background The status of CDH1, ERBB2, and ESR1 is important for the diagnostic and treatment workup for patients with breast cancer. Most alterations in these genes occur in the form of short variants (eg missense and indel alterations) or copy number alterations (eg amplifications of ERBB2 or deletions in CDH1). The prevalence and characteristics of rearrangement events have been understudied. Materials and Methods: Comprehensive genomic profiling using a hybrid-capture based approach was performed on 44,842 breast carcinomas during the course of routine clinical care (FoundationOne® or FoundationOne®CDx) examining all classes of alterations in up to 395 genes, including CDH1, ESR1, and ERBB2. All rearrangements were included in the analysis (known/likely pathogenic and variants of uncertain significance). Estrogen receptor status was extracted from pathology reports for a subset of samples. Results: Rearrangements in CDH1, ESR1, and ERBB2 were observed in 0.26% (115/44842), 0.34% (153/44842), and 1.33% (598/44842) of breast cancer samples, respectively. As expected, CDH1 rearrangements were most common in invasive lobular carcinoma (ILC) (0.64%; 16/2516) though events were observed in samples originally submitted as invastive ductal carcinoma (IDC) (0.16%; 26/15,836), suggesting possible misdiagnosis. CDH1 rearrangements were predominantly loss of function consisting of large deletions, inversions, and truncation events. ESR1 rearrangements were observed at the highest frequency in ER+/HER2- tumors (0.58%) and were never seen in ER-/HER2- and ER-/HER2+ tumors. ESR1 rearrangements were observed with a variety of partners, with recurrent events with CCDC170, SYNE1, RMND1, PLEKHG1, ARMT1, MTHFD1L, and ZBTB2. Consistent with a possible role in therapy resistance, ESR1 rearrangements were enriched in metastatic samples relative to those biopsied from the breast (OR = 2.25; p = 8E-05). ERBB2 rearrangement events were commonly observed in HER2 amplified tumors (13.4%) and rarely in other subtypes (0.12% in ER+/HER2- and 0.28% in ER-/HER2-). Most of the events were intra-chromosomal and typically represented non-fusion duplication fragments that may have generated the ERBB2 amplification. Fusions were much rarer. Out of the 598 rearrangement events, only 18 were predicted to create in-frame and in-strand fusion products retaining the HER2 kinase domain following manual review of the events. Most fusion events were unique, though a fusion with IKZF3 was seen recurrently (n=2). Conclusions Rearrangement events in diagnostically important breast cancer genes (CDH1, ESR1, and ERBB2) were commonly observed in breast cancer with subtype-specific enrichment. Since these alterations have implications in disease diagnosis and therapy response (eg endocrine therapy resistance), comprehensive genomic profiling can provide value in breast cancer care. Citation Format: Ethan Sokol, Dexter Jin, Jeffrey S. Ross, ADRIAN V. LEE, Steffi Oesterreich. Rearrangements in CDH1, ESR1, and ERBB2 are commonly observed in breast cancer and may influence diagnosis and treatment [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 P5-14-11.

Background: Previous studies have shown that rapid autopsies (RA) provide a unique opportunity for tissue collection from patients who succumb to the disease. Because cancer patients are unable to donate their organs to other people, this program provides the patient an opportunity to leave a legacy by donating their body to research. These donations are vital for advancing breast cancer research. The UPMC/Pitt RA group revamped an existing program in 2018 through the formation of a larger multidisciplinary team that includes breast cancer laboratory and clinical researchers, pathologists, nurses, bioinformaticians, and tissue bankers. Because recruitment to the RA program was a challenge, we recently added patient advocates to the team to provide their essential perspective, and a dedicated research coordinator who serves as an ambassador for the program. Methods: Autopsy is performed by the Autopsy and Forensic Pathology Center of Excellence/Decedent Affairs Service of UPMC. Samples are banked in the Pitt Biospecimen Core (PBC), in addition to immediate processing including preparing of samples for sequencing and growing of organoids in the laboratory. Immunohistochemical (IHC) analysis is performed by UPMC/Magee Pathology. Results: The research coordinator quickly became an integral part of the program and closely interacts with care providers, patients and their families, pathologists on call, and manages interactions with transport services. Five breast cancer advocates have been instrumental in advising on additional changes to the program. The advocates attend regular team meetings and have formulated patient considerations for the the RA program, including appropriate and sensitive recruitment of patients, the role of physicians in decision making by the patient, registration for more than one RA program, potential issues with transporting a body across state lines and more. The advocates also developed the name for the program - “Hope for OTHERS” with Others standing for “Our Tissue Helping Enhance Research & Science”. As of June 2022, the team has completed 26 autopsies, and an additional 20 patients have consented to the program. The completed autopsies include patients with breast tumors representing different molecular and histological classes, ethnicities, and genders. The average disease-free survival and overall survival of patients that underwent autopsy was 81.6 and 127.8 months, respectively. Most patients passed outside the hospital (86%), with 62% in home hospice and 24% in inpatient hospice. Average time between death and start and end of autopsy was 4.56 hrs and 7.09 hours, respectively. The most common metastatic sites from which specimens are collected are liver, lung and lymph nodes. Per patient we collect on average specimens from 4 different organs. In addition to the metastatic lesions, we have access to primary tumor tissue and liquid biopsies obtained during the breast cancer disease progression for 44% and 73% of the patients, respectively. For a subset of the patients, tissue has been grown as patient-derived organoids or xenograft models. Preliminary IHC and sequencing analysis has provided insight into inter- and intra-patient and intra-tumor heterogeneity. Further molecular studies are ongoing. Conclusion In summary, over the last 5+ years, we have established a successful post-mortem tissue collection program, by addressing a series of barriers through the formation and work of a multi-disciplinary well-coordinated team. We are currently expanding our omics studies using state-of-the-art technologies to improve understanding how intra- and inter-tumor heterogeneity play a role in the clinical course of advanced breast cancer, to increase diversity of the patients enrolled in the RA program, and to support the successful implementation of other RA programs nationwide and worldwide. Citation Format: Steffi Oesterreich, Lori Miller, Margaret Q. Rosenzweig, Tanner L. Bartholow, Megan Yates, Ashuvinee Elangovan, Laura Savariau, Allison N. Casey, Nolan Priedigkeit, Kai Ding, Abdalla Wedn, Jie Bin Liu, Daniel D. Brown, Tara Hyder, Geoffrey Pecar, Neil Carleton, Humberto Trejo Bittar, Daniel Geisler, Oscar Lopez-Nunez, Amanda M. Clark, Alan Wells, Partha Roy, Shannon Puhalla, Naomi Howard, Christine Needles, Susan Trent, Stephanie Walker, Christine Hodgdon, Rohit Bhargava, Jennifer M. Atkinson, Adrian V. Lee. Hope for OTHERS – An organ donation program for metastatic breast cancer research [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 P6-14-02.

Background Mixed invasive ductal and lobular carcinoma (mDLC) is a rare special subtype (3-6%, ~10,000 cases/annually in US) of invasive breast cancer with elusive pathophysiology. This entity exhibits a mix of ductal-like and lobular-like tumor sub-components within the same tumor. With few seminal studies, mDLC remains poorly understood with little molecular understanding of its sub-components including their origin and implications on disease evolution, prognosis, and treatment response. With increasing recognition of no special type (NST) and invasive lobular carcinoma (ILC) as distinct diseases with unique biology, it is important to understand whether this mixed entity, and its sub-components are like NST and ILC subtypes or a distinct disease. Methods We identified mDLC cases from the UPMC cancer registry. These underwent comprehensive evaluation by a panel of expert pathologists. Three cases (each with a ductal and lobular sub-component on the same FFPE block) were shortlisted. These cases underwent digital spatial profiling (DSP) using Nanostring GeoMX Human Whole Transcriptome Atlas. Briefly, 5um slides were stained using RNAscope morphology marker probes (E-cadherin and PanCK) and GeoMX DSP oligo-conjugated RNA detection probes. Between 3-6 ductal and lobular regions of interest (ROI) per tumor were selected by pathologists. DSP barcodes were cleaved off using UV light and collected into 96-well plate. These underwent library preparation and sequencing. Raw reads were aligned to reference probes to quantify RNA counts. Q3 normalized counts were used in downstream analyses using R version 4.1. Linear modeling was used to assess differentially expressed genes (DEGs). Hypergeometric enrichment tests were used for geneset enrichment. T-tests was used to compare gene expression between two groups. Results In total 26 ROIs (14 ductal and 15 lobular) were profiled across the three mDLC FFPE slides. Overall data quality was excellent with > 90% sequencing saturation across profiled ROIs. Principle component analysis and consensus clustering showed that lobular and ductal ROIs clustered separately indicating distinct molecular profiles. Similarly, PAM50 analysis showed that ductal and lobular ROIs within each patient tumor had distinct PAM50 subtypes. To further investigate the molecular differences between ductal vs lobular ROIs, we performed differential gene expression analysis. We identified 38 up-regulated and 78 down-regulated genes in lobular compared to ductal ROIs. To assess whether mDLC sub-components share any molecular similarities to pure counterparts i.e., ILC and NST, we compared mDLC lobular vs ductal DEGs with those from TCGA ILC vs NST comparison. SHROOM1, KLK10 and KLK11 were up-regulated while CDH1, DCD, and CPB1 were down-regulated in both mDLC lobular ROIs and ILC vs mDLC ductal ROIs and NST, respectively. Pathway analysis revealed estrogen response, adhesion, and metabolism related differences between mDLC lobular vs ductal ROIs. Furthermore, key transcription factor signatures enriched in the up-regulated genes in lobular vs ductal ROIs included ESR1, FOXA2, GATA1/2 and AR signatures while those enriched in the down-regulated genes in lobular vs ductal ROIs included RCOR1, MYC, ZBTB7A, NELFE, and SPI1 signatures. Conclusion and Future Work Using DSP, we uncovered the molecular heterogeneity of mDLC. We revealed that lobular and ductal sub-components have distinct biology with differences in transcriptional signatures and hormone signaling, adhesion and metabolism related pathways. Our pilot study is the first to shed light on this elusive mixed entity using spatial profiling. Our future work will focus on DNA sequencing of mDLC sub-components to identify sub-component specific driver mutations. Our findings will need further investigation in larger mDLC cohorts to better understand their clinical implications in terms of evolution of this disease and its prognosis. Citation Format: Osama Shiraz Shah, Azadeh Nasrazadani, Jennifer M. Atkinson, Celina Kleer, Priscilla F. McAuliffe, Rohit Bhargava, Jorge Reis-Filho, Peter C. Lucas, ADRIAN V. LEE, Steffi Oesterreich. PD4-07 Uncovering molecular heterogeneity of mixed ductal and lobular carcinoma using digital spatial profiling [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 PD4-07.

Background Most breast cancers (~85%) are of no special histologic subtype (NST), and the most common special subtype is invasive lobular cancer (ILC). ILC accounts for 10-15% of all breast cancers, and there will be ~40,000 new cases in 2022 in the US alone. If considered an “independent” cancer type, ILC is the 6th most common cancer in women. The pathognomonic feature of ILC is loss of E-cadherin (CDH1). The resulting lack of adherens junctions causes the unique single-file growth pattern of discohesive ILC cells, which decreases the ability for detection by mammography, in turn resulting in late detection and hence larger tumors. Although ILCs show better prognostic factors than NST, patients with ILC have worse long-term outcome, which is not well understood. Additionally, ILC has historically been understudied, which is in part due to lack of appropriate research models. For example, the Cancer Cell Line Encyclopedia (CCLE) contains 54 NST cell lines but only 2 ILC cell lines, and only a limited number of patient-derived xenograft (PDX) models are evident in the published literature. There is a critical need for additional in vitro and in vivo models to study ILC biology, as well as to test targeted therapies. ILC PDX and patient derived xenograft organoids (PDXO) are particularly valuable tools to enable target validation and assess drug treatment response. Methods To identify and validate new ILC PDX models, we used Champions Oncology’s Lumin Bioinformatics to screen Champions’ collection of breast cancer models (n=126) for PDX harboring CDH1 mutation and/or low E-cadherin expression. We performed histological analysis on selected PDX models including H&E staining, and immunohistochemical assessment of E-cadherin, P120, estrogen receptor, progesterone receptor, HER2 and Ki67. Models with 2+ HER2 staining were assessed by FISH. All staining was interpreted by a certified breast pathologist. PDX tumor tissue was further used to develop PDXO models. Results Using Champions Oncology’s Lumin tool, we identified 10 putative ILC PDX models based upon CDH1 mutation, low E-cadherin mRNA expression, or clinical annotation of ILC (Table 1). Of the 10 PDX models analyzed, two cases were clinically annotated as ILC, while the remainder were classified as ‘carcinoma’ (n=5) or as NST (n=3). Histologic analysis revealed loss of E-cadherin and cytoplasmic P120 (lobular pattern) in 8/10 models assessed, and pathologic assessment confirmed these as having a lobular histology. IHC analysis classified these PDXs as 5 TNBC and 5 ER+ tumors, with none showing amplification of HER2 by FISH. All tumors demonstrated high (35%, n=1) or very high (>55%, n=9) Ki67 proliferation marker levels. We further developed PDXOs from one PDX model as proof of concept, and the resulting organoid demonstrated classic ‘grape-like’ ILC morphology. Conclusion Our study demonstrates how existing PDX banks with in-depth multi-omic and pathology analyses can be interrogated to identify models of unique histological and molecular subtypes of breast cancer. Of the PDX models selected from Champions Oncology’s breast cancer cohort, 7 models were classified as ILC either through re-classification from NST/carcinoma to ILC or confirmation of ILC histology. In addition, 1 PDX was re-classified as mixed type. Some of these models are ER+/HER- and thus have the classic molecular features of ILC. Our collaborative omics guided approach allows for reclassification of PDX models to increase available research models for unique breast cancer subtypes such as ILC which in turn will enhance translational research in unique histological subtypes of breast cancer. Citation Format: Jennifer M. Atkinson, Megan Yates, Daniel D. Brown, Jagmohan Hooda, Rohit Bhargava, Paolo Schiavini, Marianna Zipeto, Steffi Oesterreich, ADRIAN V. LEE. Combining multiomics and histological assessment to identify patient derived xenograft models of invasive lobular carcinoma [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 P3-08-10.

Background: The Surgical Society of Oncology Choosing Wisely Campaign for breast cancer advocates against the routine use of sentinel lymph node biopsy (SLNB) for women ≥ 70 years with early stage estrogen positive (ER+), clinically node negative (cN0) disease, given the low likelihood of axillary involvement and axillary recurrence risk, absence of survival benefit and greater reliance on genomic testing for therapeutic decisions. We hypothesize that this practice may be extended to a younger cohort of patients. In this proof-of-concept feasibility study, we first sought to determine the incidence of node positive (N+) disease in our health system using natural language understanding (NLU) technology to extract relevant data from the electronic medical record (EMR). NLU of the clinical narrative has been proven to aid clinical decision support by extracting relevant information and can populate clinical databases to facilitate optimal population management strategies. The advantage of NLU over a cancer registry is the speed and efficiency of data extraction for a large number of patients in real time, plus the capture of data points not conventionally included in a registry. Methods: All patients with early stage ER+, cN0 breast cancer who had SLNB from January 2015-December 2017 were identified in an integrated academic health network comprised of 15 hospitals in Western Pennsylvania. Patitent clinical data were abstracted from the EMR using Realyze Intelligence™ NLU technology. The Realyze NLU pipeline uses a combination of machine learning algorithms and standard terminologies to create a breast cancer patient model that includes genomic, phenotypic, and clinical data. The pipeline gathers information from all data sources – structured and unstructured – and normalizes the information to create a complete model of patient clinical criteria. Realyze Information Models use clinical data formatting flexible enough to represent clinical disorders on a concept level as well as the encounter, patient, and population levels. A breast cancer model with focus on the lymph node identification, pathological as well as clinical tumor and node classification were developed and mapped to standard terminology. A Semantic Reasoning layer is provided by different mechanisms including a rule-based layer to render answers to the questions posed in this hypothesis. NLU performance was validated by manually verifying key clinical variables (i.e., clinical stage, pathologic stage, and nodal positivity) on a subset of patients. Statistical analysis to determine any difference in N+ rates by age was performed using Chi-square testing with significance set at p < 0.05. Results: We identified 602 pts with early stage ER+, cN0 breast cancer over this period who underwent SLNB. Average age was 59.6 years old. As a whole group, there was an increase in N+ rates as the stage increased (Table 1). When comparing incidence of N+ disease stratified by age (< 70 or >70), there was no difference in N+ rates across all stages. In addition, equally low rates of SLN positivity were seen for patients specifically with stage T1a and T1b disease. Conclusions: These data suggest that the Choosing Wisely recommendation to omit SLNB may be extended to a younger cohort of pts with ER+, cN0 disease, specifically those with stage T1a or T1b tumors. With low rates of N+ disease, and less reliance on axillary stage for treatment decision making, the harms of surgical axillary staging may outweigh the benefits. Future validation is needed with a larger sample size. Table 1 Citation Format: Neil Carleton, Gilan Saadawi, Steffi Oesterreich, ADRIAN V. LEE, Emilia Diego. Omission of Sentinel Lymph Node Biopsy in Patients with Early Stage Breast Cancer: Looking Beyond the Choosing Wisely Guidelines for Age < 70 [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 P2-14-07.

Breast cancer is a leading cause of female mortality and despite advancements in diagnostics and personalized therapeutics, metastatic disease largely remains incurable due to drug resistance. The druggable estrogen receptor (ER, ESR1), overexpressed in two-thirds of all breast cancer, evolves in 30% of tumors exposed to endocrine therapy consequently resulting in treatment resistance. A more recently discovered mechanism of ER mediated endocrine resistance is ER fusion proteins. ER fusions, found predominately in metastatic endocrine resistant disease, harbor ESR1 exons 1-6 fused to an in-frame gene partner due to an ESR1 intron 6 translocation break. Our lab has demonstrated that ER fusion proteins, which lack the C-terminal ligand-binding domain (LBD), recapitulate phenotypes of ER proteins harboring endocrine-resistant point mutations occurring in the LBD. Our research goals aim to 1) determine fusion prevalence and emergence, 2) understand fusion mechanisms of resistance and 3) explore alternative treatment options for our patients. The promiscuous nature of fusion partners hinders fusion detection by traditional sequencing and thus our research team has developed a novel ER fusion detection method, EnRich. The EnRich probe set (4,324 probes in total) is composed of two separate probe pools targeting at 2x tiling intronic and exonic ESR1, the upstream promoter region and select oncogenic genes. To optimize the EnRich pipeline, DNA was extracted from a frozen tumor sample and a PDX model harboring ESR1-DAB2 and ESR1-LPP fusions, respectively. ESR1-DAB2 and ESR1-LPP were accurately detected by quantifying discordant paired-end or split reads mapped to chromosome 6. In addition, liquid biopsies from 15 patients with ER positive advanced breast cancer were also assessed through EnRich to uncover unidentified ESR1 structural variants. Two patient samples were detected to harbor ESR1 fusions (ESR1-CCDC170, ESR1-AKAP12 and ESR1-YAP1) and were further validated in corresponding mRNA. These recurrent and novel fusions were supported with more than 10 reads each, indicating that the EnRich pipeline is an effective and accurate sequencing approach to understanding ER fusion prevalence. Our lab, furthermore, has studied ER fusion proteins mechanistically. We have stably overexpressed ER fusions in transgenic breast cancer cell lines engineered with shRNA targeting the endogenous wildtype ER (ESR1-WT). In this ESR1-WT depleted cellular context, we found that ER fusions (notably ESR1-SOX9 and ESR1-YAP1) demonstrate ER hyperactivation through an estrogen response element (ERE) assay compared to ESR1-WT and a truncated exon 1-6 ESR1 (ESR1∆CTD). Importantly, fusion ERE activity was robust in the absence of the ER ligand, estradiol, as well as in the presence of endocrine therapies, implying ER fusion proteins function in a ligand independent, endocrine resistant mechanism. ER fusion positive cell lines were also enriched in oncogenic phenotypes such as enhanced 3D growth, cell survival via colony formation, and migration in a wound scratch assay. These enhanced metastatic potentials of the ER fusions were observed in both invasive ductal and lobular carcinoma cell lines, albeit at varying magnitudes depending on the 3’ fusion partner and phenotype being assessed. Although the ER fusions harbored unique characteristics due to the C-terminal partner, transcriptomic profiling revealed that enhanced EMT and KRAS signaling signatures were shared among all fusions when compared to the ESR1-WT and ESR1∆CTD cell lines, which may serve as future exploitable drug targets. Comprehensive detection and functional evaluation of ER fusion proteins will provide clinicians and patients with better understanding of tumor endocrine-resistant prevalence and discovery of more effective treatment options. Citation Format: Megan E. Yates, Tiantong Liu, Jagmohan Hooda, Sichun Yang, Riyue Bao, Jennifer M. Atkinson, ADRIAN V. LEE, Steffi Oesterreich. PD10-02 Novel ER fusion detection method to gain insight in fusion prevalence and endocrine resistant mechanisms [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 PD10-02.

Metastatic breast cancer is an intractable disease that responds poorly to immunotherapy. We show that p38MAPKα inhibition (p38i) limits tumor growth by reprogramming the metastatic tumor microenvironment in a CD4+ T cell-, IFNγ-, and macrophage-dependent manner. To identify targets that further increased p38i efficacy, we utilized a stromal labeling approach and single-cell RNA sequencing. Thus, we combined p38i and an OX40 agonist that synergistically reduced metastatic growth and increased overall survival. Intriguingly, patients with a p38i metastatic stromal signature had better overall survival that was further improved by the presence of an increased mutational load, leading us to ask if our approach would be effective in antigenic breast cancer. The combination of p38i, anti-OX40, and cytotoxic T-cell engagement cured mice of metastatic disease and produced long-term immunologic memory. Our findings demonstrate that a detailed understanding of the stromal compartment can be used to design effective antimetastatic therapies.Significance:Immunotherapy is rarely effective in breast cancer. We dissected the metastatic tumor stroma, which revealed a novel therapeutic approach that targets the stromal p38MAPK pathway and creates an opportunity to unleash an immunologic response. Our work underscores the importance of understanding the tumor stromal compartment in therapeutic design.

Contains supplemental figures and legends

Table containing all of our reagents

No special-type breast cancer [NST; commonly known as invasive ductal carcinoma (IDC)] and invasive lobular carcinoma (ILC) are the two major histological subtypes of breast cancer with significant differences in clinicopathological and molecular characteristics. The defining pathognomonic feature of ILC is loss of cellular adhesion protein, E-cadherin (CDH1). We have previously shown that E-cadherin functions as a negative regulator of the IGF1R and propose that E-cadherin loss in ILC sensitizes cells to growth factor signaling that thus alters their sensitivity to growth factor–signaling inhibitors and their downstream activators. To investigate this potential therapeutic vulnerability, we generated CRISPR-mediated CDH1 knockout (CDH1 KO) IDC cell lines (MCF7, T47D, and ZR75.1) to uncover the mechanism by which loss of E-cadherin results in IGF pathway activation. CDH1 KO cells demonstrated enhanced invasion and migration that was further elevated in response to IGF1, serum and collagen I. CDH1 KO cells exhibited increased sensitivity to IGF resulting in elevated downstream signaling. Despite minimal differences in membranous IGF1R levels between wild-type (WT) and CDH1 KO cells, significantly higher ligand–receptor interaction was observed in the CDH1 KO cells, potentially conferring enhanced downstream signaling activation. Critically, increased sensitivity to IGF1R, PI3K, Akt, and MEK inhibitors was observed in CDH1 KO cells and ILC patient-derived organoids. Implications: Overall, this suggests that these targets require further exploration in ILC treatment and that CDH1 loss may be exploited as a biomarker of response for patient stratification.

Estrogen receptor alpha (ER/ESR1) mutations occur in 30% to 40% of endocrine resistant ER-positive (ER+) breast cancer. Forkhead box A1 (FOXA1) is a key pioneer factor mediating ER–chromatin interactions and endocrine response in ER+ breast cancer, but its role in ESR1-mutant breast cancer remains unclear. Our previous FOXA1 chromatin immunoprecipitation sequencing (ChIP-seq) identified a large portion of redistributed binding sites in T47D genome-edited Y537S and D538G ESR1–mutant cells. Here, we further integrated FOXA1 genomic binding profile with the isogenic ER cistrome, accessible genome, and transcriptome data of T47D cell model. FOXA1 redistribution was significantly associated with transcriptomic alterations caused by ESR1 mutations. Furthermore, in ESR1-mutant cells, FOXA1-binding sites less frequently overlapped with ER, and differential gene expression was less associated with the canonical FOXA1–ER axis. Motif analysis revealed a unique enrichment of retinoid X receptor (RXR) motifs in FOXA1-binding sites of ESR1-mutant cells. Consistently, ESR1-mutant cells were more sensitive to growth stimulation with the RXR agonist LG268. The mutant-specific response was dependent on two RXR isoforms, RXR-α and RXR-β, with a stronger dependency on the latter. In addition, T3, the agonist of thyroid receptor (TR) also showed a similar growth-promoting effect in ESR1-mutant cells. Importantly, RXR antagonist HX531 blocked growth of ESR1-mutant cells and a patient-derived xenograft (PDX)-derived organoid with an ESR1 D538G mutation. Collectively, our data support the evidence for a stronger RXR response associated with FOXA1 reprograming in ESR1-mutant cells, suggesting development of therapeutic strategies targeting RXR pathways in breast tumors with ESR1 mutation.Implications:It provides comprehensive characterization of the role of FOXA1 in ESR1-mutant breast cancer and potential therapeutic strategy through blocking RXR activation.

S1. FOXA1 redistribution in ESR1 mutant cells causes distinct ER-FOXA1 interaction.S2. FOXA1 gained peaks annotated genes are significantly associated with novel target genes.S3. FOXA1 redistribution in ESR1 mutant cells confers potential RXR binding sites.S4. RXR agonist LG100268 can promote colonization and growth of ESR1 mutant cells.S5. Clonogenic survival assay and 2D growth assay to test RXR response in Park and Gertz MCF7 cell models.S6. FOXA1 knockdown drastically attenuated the base line growth of both ESR1 WT and mutant cells.S7. RXR antagonist HX531 can inhibit the response of ESR1 mutant cells to RXR agonist.S8. RXR antagonist HX531 can inhibit the basal and agonist promoted growth of IPM-PDXO-073 organoid.

Table S1. Data Sets UsedTable S2. FOXA1 and ER Chip-seq peaksTable S3. DE genesTable S4. Enriched FOXA1 peak motifsTable S5. Enriched IPA pathways

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, epithelial-to-mesenchymal transition, 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 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.Significance:This study identifies a gene signature diagnostic for functional ESR1 fusions that drive poor outcome in advanced breast cancer, which could also help guide precision medicine approaches in patients harboring ESR1 mutations.

It includes Supplementary Methods, Supplementary Figures, Supplementary Tables, and Supplementary References

Supplemental Fig S5. Imprinted genes display approximately 50% DNA methylation. Gene regions known to be imprinted were chosen to confirm the validity of the Methyl-Seq assay. For each gene a β value was calculated for each window. The frequency of each particular β value is graphically represented for each gene.

Supplemental Figure S2. All samples from both time points were used in a hierarchal clustering analysis. 10 samples at the early time point and 11 samples at the late time point were included.(E=early, L=late, P=parous, NP=nulliparous)

Supplemental Fig S8. Hypermethylation of the Igf1r aligns with sites of histone methylation. (A) The UCSC Genome Browser was used to align the Igf1r with other epigenetic modifications. The red bar indicates the region of differential DNA methylation identified in the SureSelectXT Methyl-Seq Assay. Black bars represent sites of histone methylation, the intensity corresponds to the degree of methylation. (B) Igf1r bisulfite sequencing data are depicted. Each animal is numbered and each horizontal line represents DNA from a separate clone from that animal. The percent methylation of each animal is listed under each CpG site. Open circles = unmethylated, and closed circles = methylated. The lower panel represents a combined result from all clones in all animals.

Supplementary Data from Sustained c-Jun-NH2-Kinase Activity Promotes Epithelial-Mesenchymal Transition, Invasion, and Survival of Breast Cancer Cells by Regulating Extracellular Signal-Regulated Kinase Activation

Supplemental Fig S7. Igf1r is central to a top signaling network in Ingenuity pathway analysis. Ingenuity pathway analysis (IPA) identified this signaling network to be significantly altered by DNA methylation. The hyper and hypomethylated genes identified to be persistently differentially methylated by the meta-analysis were input into IPA (Supplemental Data 1). Red symbols represent hypermethylation, green symbols represent hypomethylation and intensity depicts methylation difference between nulliparous and parous.

Supplementary Data from Loss of E-cadherin Induces IGF1R Activation and Reveals a Targetable Pathway in Invasive Lobular Breast Carcinoma

Primers used for quantitative PCR and bisulfite sequencing.

Table S1. Clinicopathological characteristics and sample distribution by site Table S2. Primers/probes design for ddPCR (ESR1, EIF2C, AP3P1) Table S3. Raw nanoString counts Table S4. Normalized copy number calls (ER+ samples) Table S5. Normalized copy number calls (ER- samples) Table S6. DdPCR analysis of cell lines Table S7. NanoString raw counts (cell lines) Table S8. NanoString copy number calls (cell lines) Table S9. Nanostring log2 normalized counts (cell lines) Table S10. ESR1 CN amplifications by site in ER- samples Table S11. Multiple Fisher exact comparisons Table S12. ESR1 5`-3` copy number imbalance Table S13. Correlation matrix of ESR1 copy number calls by the different exons and mRNA expression Table S14. Normalized copy number calls for other genes (ER+ samples) Table S15. Normalized copy number calls other genes (ER- samples)

Supplemental Fig S9. Differentially methylated regions of IGF pathway genes align with histone methylation sites. The UCSC Genome Browser was used to align the Irs1, Igf1, and Igfbp4 with other epigenetic modifications. The red bars indicate the regions of differential DNA methylation identified in the SureSelectXT Methyl-Seq Assay. Black bars represent sites of histone methylation, the intensity corresponds to the degree of methylation.

Early full-term pregnancy is an effective natural protection against breast cancer in both humans and experimental rodents. The protective effect of an early pregnancy is, in part, linked to changes in circulating hormones that are involved in both normal breast development and breast cancer. For example, a reduction in circulating growth hormone (GH) has been shown to protect rats from carcinogen-induced mammary tumors. We examined the ability of a full-term pregnancy to alter the endocrine GH/insulin-like growth factor-I (IGF-I) axis and how this change affected normal mammary gland function in two commonly used rat models (Sprague-Dawley and Wistar Furth). Circulating GH and IGF-I were measured in blood drawn every 30 minutes from parous and age-matched virgin female rats. Mean serum GH levels were significantly decreased (P < 0.01) in parous compared with age-matched virgin rats for both strains. Changes in GH levels were independent of estrous cycle, indicated by a significant (P < 0.05) reduction in circulating levels of GH during estrus and diestrus in both parous strains. Despite the decrease in circulating GH, pituitary GH mRNA levels were unaltered in parous rats. Circulating IGF-I and hepatic IGF-I mRNA were also unaltered by parity in either rat strain. Immunoblot analysis of mammary glands showed decreases in phosphorylation of signal transducer and activator of transcription 5A and Janus-activated kinase 2, suggesting reduced action of GH in the mammary gland. Therefore, although the parity reduction in circulating GH does not affect circulating IGF-I levels, it is possible that reduced GH acts directly at the mammary gland and may play a role in pregnancy protection from breast cancer. Cancer Prev Res; 3(3); 312–21

The most effective natural prevention against breast cancer is an early first full-term pregnancy. Understanding how the protective effect is elicited will inform the development of new prevention strategies. To better understand the role of epigenetics in long-term protection, we investigated parity-induced DNA methylation in the mammary gland. FVB mice were bred or remained nulliparous and mammary glands harvested immediately after involution (early) or 6.5 months following involution (late), allowing identification of both transient and persistent changes. Targeted DNA methylation (109 Mb of Ensemble regulatory features) analysis was performed using the SureSelectXT Mouse Methyl-seq assay and massively parallel sequencing. Two hundred sixty-nine genes were hypermethylated and 128 hypomethylated persistently at both the early and late time points. Pathway analysis of the persistently differentially methylated genes revealed Igf1r to be central to one of the top identified signaling networks, and Igf1r itself was one of the most significantly hypermethylated genes. Hypermethylation of Igf1r in the parous mammary gland was associated with a reduction of Igf1r mRNA expression. These data suggest that the IGF pathway is regulated at multiple levels during pregnancy and that its modification might be critical in the protective role of pregnancy. This supports the approach of lowering IGF action for prevention of breast cancer, a concept that is currently being tested clinically. Cancer Prev Res; 8(10); 1000–9. ©2015 AACR.

Supplemental Figure S3. Mapping efficiency was above 50 for all samples in both time points. One sample was an outlier in the early time point (P12) and one at the late time point (NP4) and were removed from further analysis. Both Pearson Correlation plots and Principal Component Analysis are displayed.

All Supplementary Figure legends are included in this document.

Supplemental Figure S6. Supervised hierarchical clustering and cell type content analysis. (A) Heatmaps displaying supervised hierarchical clustering of hypermethylated and hypomethylated windows including dendrograms (Red=Methylated, Green=Unmethylated).

Supplementary Data from MALT1 Is a Targetable Driver of Epithelial-to-Mesenchymal Transition in Claudin-Low, Triple-Negative Breast Cancer

Supplemental Data 1. This spreadsheet contains the results of the differential methylation analysis, the meta-analysis and the pathway analysis. In the meta-analysis sheets, the first 3 columns represent the chromosomal locations, followed by the significance level (stat, p-value, and FDR). Weight.1 and weight.2 represent the weight of early and late data respectively. For the meta-analysis we weighted both as 1. The effect size represents the difference in DNA methylation between NP and P at the early and late time points (effect size.1=early, effect size.2=late), and the p-value for each is next depicted. We then filtered the data by trimmed means as in the Materials and Methods section and the new values are listed in columns N and O. We then annotated the gene name, which genomic feature the loci resides in, and the distance to the nearest promoter (distance to feature). We then annotated the mean coverage and the number of CpG sites in the differentially methylated region. The differential methylation sheets include similar data without the columns pertaining to the meta-analysis. The 3Ingenuity Pathway Analysis (IPA) spreadsheets contain the pathway analysis result. The pathway name, followed by the statistical significance, and molecules represented in our data for each pathway are detailed on each sheet. The analysis was first conducted on the hyper and hypomethylated genes separately, then the combined hyper and hypermethylated genes were analyzed together.

The c-Jun NH2-terminus kinase (JNK) mediates stress-induced apoptosis and the cytotoxic effect of anticancer therapies. Paradoxically, recent clinical studies indicate that elevated JNK activity in human breast cancer is associated with poor prognosis. Here, we show that overexpression of a constitutively active JNK in human breast cancer cells did not cause apoptosis, but actually induced cell migration and invasion, a morphologic change associated with epithelial-mesenchymal transition (EMT), expression of mesenchymal-specific markers vimentin and fibronectin, and activity of activator protein transcription factors. Supporting this observation, mouse mammary tumor cells that have undergone EMT showed upregulated JNK activity, and the EMT was reversed by JNK inhibition. Sustained JNK activity enhanced insulin receptor substrate-2–mediated ERK activation, which in turn increased c-Fos expression and activator protein activity. In addition, hyperactive JNK attenuated the apoptosis of breast cancer cells treated by the chemotherapy drug paclitaxel, which is in contrast to the requirement for inducible JNK activity in response to cytotoxic chemotherapy. Blockade of extracellular signal-regulated kinase activity diminished hyperactive JNK-induced cell invasion and survival. Our data suggest that the role of JNK changes when its activity is elevated persistently above the basal levels associated with cell apoptosis, and that JNK activation may serve as a marker of breast cancer progression and resistance to cytotoxic drugs. Mol Cancer Res; 8(2); 266–77