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PDF - 4128 KB, Increased epithelial budding in mTORC1-inhibited PTEN-/- organoids is not due to increased net cell proliferation.

Background: Tumor mutational burden (TMB) is a biomarker approved to predict response to immune checkpoint blockade (ICB) in solid tumors irrespective of their tissue of origin. However, there are limited data in patients with breast cancer and high TMB to support the use of ICB. The goal of this analysis is to describe clinical, pathological and molecular associations with TMB within a cohort of patients with metastatic breast cancer. Methods: We included patients enrolled onto an ongoing prospective study titled Individualized Molecular Analyses Guide Efforts (IMAGE)-II. Patients eligible for IMAGE-II have metastatic breast cancer of any subtype that had progressed on at least one standard-of-care therapy. Genetic profiling of tumor tissue was performed at the discretion of the treating team using one of several commercially available next generation sequencing platforms. For purposes of this analysis, only patients who underwent tissue-based Foundation Medicine analysis are included as TMB assessments are different across different platforms. Data are summarized by descriptive statistics. Linear and logistic regression analyses are conducted to evaluate the association between TMB and other clinical, pathological and molecular factors. We will present data on associations with specific mutations (i.e. ESR1, ERBB2, DNA repair, Pi3K signaling, TP53) and ctDNA TMB at a later time. Results:Of 117 patients in the IMAGE-II database, median age was 57 (range 23-86), 65% were White, 29% Black, and 6% Other. TMB data were available on 62 patients. Of those with both TMB and subtype information, 35 (70%) had ER+HER2- tumors, and 15 (30%) had ER-HER2- tumors. Median TMB was 4 mutations/megabase and ranged from 0 to 27. We did not observe significant differences in TMB in patients with ER+HER2- and those with ER-HER2- tumors (median TMB of 4 [0-27] and 5 [1-25], respectively), nor between White versus Black patients (median TMB of 4 [0-27] and 5 [0-12], respectively). However, we did observe that age was positively associated with higher TMB (p-value = 0.02). Additionally, we observed that the time between metastatic diagnosis and TMB measurement was positively associated with TMB (p-value < 0.01); this significant association was also observed in ER+HER2- patients (p-value < 0.01) but not in ER-HER2- patients. Median time to obtaining TMB since metastatic diagnosis was 1.1 (range -0.8 - 12.8) years. More lines of chemotherapy prior to TMB assessment was not observed to be associated with higher TMB. Conclusions: We observed that TMB was higher in patients who have had a longer disease course. Further research is required to understand changes in TMB over time, and how TMB is correlated with. other genomic and tumor microenvironment characteristics. A deeper understanding of TMB may help refine it as a predictive biomarker for ICB. Citation Format: Mohamed A Mohamed, Chenghuang Wang, Morgan Buckley, Jennifer Lehman, Jenna Canzoniero, Christopher D Gocke, Raquel Nunes, Ben Ho Park, Karen L Smith, Jessica Tao, Hanna Tukachinsky, Mary Wilkinson, Antonio C Wolff, Vered Stearns, Cesar A Santa-Maria. Clinical, pathologic, and molecular associations of tumor mutational burden in metastatic breast cancer [abstract]. In: Proceedings of the 2021 San Antonio Breast Cancer Symposium; 2021 Dec 7-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2022;82(4 Suppl):Abstract nr P2-08-15.

SUMMARYA long-term goal in cancer research has been to inhibit the cell cycle in tumour cells without causing toxicity in proliferative healthy tissues. The best evidence that this is achievable is provided by CDK4/6 inhibitors, which arrest the cell cycle in G1, are well-tolerated in patients, and are effective in treating ER+/HER2-breast cancer. CDK4/6 inhibitors are effective because they arrest tumour cells more efficiently than some healthy cell types and, in addition, they affect the tumour microenvironment to enhance anti-tumour immunity. We demonstrate here another reason to explain their efficacy. Tumour cells are specifically vulnerable to CDK4/6 inhibition because during the G1 arrest, oncogenic signals drive toxic cell overgrowth. This overgrowth causes permanent cell cycle withdrawal by either preventing exit from G1 or by inducing replication stress and genotoxic damage during the subsequent S-phase and mitosis. Inhibiting or reverting oncogenic signals that converge onto mTOR can rescue this excessive growth, DNA damage and cell cycle exit in cancer cells. Conversely, inducing oncogenic signals in non-transformed cells can drive these toxic phenotypes and sensitize cells to CDK4/6 inhibition. Together, this demonstrates how oncogenic signals that have evolved to stimulate constitutive tumour growth and proliferation can be driven to cause toxic cell growth and irreversible cell cycle exit when proliferation is halted in G1.

Previous short-hairpin RNA knockdown studies have established that depletion of human uracil DNA glycosylase (hUNG) sensitizes some cell lines to 5-fluorodeoxyuridine (FdU). Here, we selectively inhibit the catalytic activity of hUNG by lentiviral transduction of uracil DNA glycosylase inhibitor protein into a large panel of cancer cell lines under control of a doxycycline-inducible promoter. This induced inhibition strategy better assesses the therapeutic potential of small-molecule targeting of hUNG. In total, 6 of 11 colorectal lines showed 6- to 70-fold increases in FdU potency upon hUNG inhibition ("responsive"). This hUNG-dependent response was not observed with fluorouracil (FU), indicating that FU does not operate through the same DNA repair mechanism as FdU in vitro. Potency of the thymidylate synthase inhibitor raltitrexed (RTX), which elevates deoxyuridine triphosphate levels, was only incrementally enhanced upon hUNG inhibition (

PURPOSE To update the ASCO Biomarkers to Guide Systemic Therapy for Metastatic Breast Cancer (MBC) guideline. METHODS An Expert Panel conducted a systematic review to identify randomized clinical trials and prospective-retrospective studies from January 2015 to January 2022. RESULTS The search identified 19 studies informing the evidence base. RECOMMENDATIONS Candidates for a regimen with a phosphatidylinositol 3-kinase inhibitor and hormonal therapy should undergo testing for PIK3CA mutations using next-generation sequencing of tumor tissue or circulating tumor DNA (ctDNA) in plasma to determine eligibility for alpelisib plus fulvestrant. If no mutation is found in ctDNA, testing in tumor tissue, if available, should be used. Patients who are candidates for poly (ADP-ribose) polymerase (PARP) inhibitor therapy should undergo testing for germline BRCA1 and BRCA2 pathogenic or likely pathogenic mutations to determine eligibility for a PARP inhibitor. There is insufficient evidence for or against testing for a germline PALB2 pathogenic variant to determine eligibility for PARP inhibitor therapy in the metastatic setting. Candidates for immune checkpoint inhibitor therapy should undergo testing for expression of programmed cell death ligand-1 in the tumor and immune cells to determine eligibility for treatment with pembrolizumab plus chemotherapy. Candidates for an immune checkpoint inhibitor should also undergo testing for deficient mismatch repair/microsatellite instability-high to determine eligibility for dostarlimab-gxly or pembrolizumab, as well as testing for tumor mutational burden. Clinicians may test for NTRK fusions to determine eligibility for TRK inhibitors. There are insufficient data to recommend routine testing of tumors for ESR1 mutations, for homologous recombination deficiency, or for TROP2 expression to guide MBC therapy selection. There are insufficient data to recommend routine use of ctDNA or circulating tumor cells to monitor response to therapy among patients with MBC. Additional information can be found at www.asco.org/breast-cancer-guidelines .

Background: Estrogen receptor alpha (ER/ESR1) mutations are found in 20-40% of endocrine resistant ER+ metastatic breast cancers, and they are associated with worse outcome. Preclinical studies have shown that they cause ligand-independent growth, resistance to endocrine therapy, and there is growing evidence for a role in metastasis. It is not known how ESR1 mutant cancer cells cause metastases and whether such a mechanism may indicate novel therapeutic options. Methods: ddPCR was used to detect hotspot ESR1 mutations. Transcriptome data were derived from cell line models and clinical samples. For in vitro phenotypic characterization, Y537S and D538G genome-edited MCF7 and T47D cell models from four different labs were used. Cell-cell adhesive properties were assessed using calcein-labelled adhesion, spontaneous cell aggregation and microfluidic aggregation assays. Altered expression of cell-cell adhesion genes detected in RNA seq data was validated via qRT-PCR, immunoblot and immune staining. Functional contributions of desmosome and gap junctions were tested by blocking peptide and carbenoxolone respectively. Mutant ER cistromes were profiled using ChIP-sequencing. Tail vein injection was performed on nude mice to evaluate metastasis in vivo. Mouse lung micro-metastatic foci were quantified using human-specific CK19 staining. Circulating tumor cells (CTCs) clustering propensity in vivo was assessed via intracardiac injection of ESR1 WT and mutant cells into nude mice following CTC microfilter capture. CTCs enumeration from breast cancer patients’ blood samples was performed using CellSearchTM system. Results: We identified a significant enrichment of ESR1 mutations in distant (12/48) vs local (0/27) recurrences, confirming the strong association of mutant ER with metastasis. Transcriptomic analysis revealed altered cell-to-cell interaction pathways in ESR1 mutant tumors compared to ESR1 WT tumors, suggesting a previously undescribed role of ESR1 mutations in reprogramming cell-cell adhesome. ESR1 mutant cells grown in suspension culture revealed more compact multicellular spheroids compared to WT cells. This observation was confirmed under both static and microfluidic conditions, indicative of increased cell-cell interactions. The effect was more pronounced in MCF7 compared to T47D cells, and it correlated with increased expression of multiple desmosome and gap junction pathway genes, which were also significantly enriched in ESR1 mutant tumors. Pharmacological blockade of desmosome and gap junctions significantly rescued enhanced cell-cell adhesion in ESR1 mutant cells. Mechanistically, our ER ChIP-seq did not identify any gained mutant ER binding sites in proximity to cell-cell adhesion gene loci, indicating indirect regulation by mutant ER. Consistent with this, expression of Connexin 43, one of the top upregulated gap junction components, was induced by cFOS found to be highly upregulated in ESR1 mutant cells. Tail vein injection of ESR1-mutant cells derived more distant macro- (MCF7) and micro- (T47D) metastases. Given increasing evidence for role of cell-cell attachment in CTC phenotypes, we tested CTC formation for ESR1 WT and mutant cells. In vivo studies showed MCF7 Y537S ESR1 mutant cells formed larger multi-cellular CTC clusters with increased compactness compared to WT CTCs. These preclinical data translated to clinical observation, where we observed an enrichment of CTC clusters in patients with ESR1 mutant-metastatic breast cancers. Conclusion: Hotspot ESR1 mutations induce expression of multiple desmosome and gap junction genes and confer increased cell-cell adhesion, which facilitate breast cancer metastasis via increased CTCs clustering propensity. These findings might guide approaches to test potential repurpose of drugs targeting gap junction in ER mutant tumors. Citation Format: Zheqi Li, Yang Wu, Amir Bahreini, Jian Chen, Ye Qin, Kevin M. Levine, Nilgun Tasdemir, Nolan Priedigkeit, Li Zhu, George C. Tseng, Yu Jiang, Benjamin Troness, Laki Buluwela, Simak Ali, Spencer Arnesen, Jason Gertz, Ben H. Park, Qiang Zhang, Lorenzo Gerratana, Andrew Davis, Jennifer M. Atkinson, Dorraya El-Ashry, Massimo Cristofanilli, Adrian V. Lee, Steffi Oesterreich. Hotspot ESR1 mutations rewire cell-cell adhesome to facilitate breast cancer metastasis [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 GS1-05.

Purpose: Cyclin-dependent kinase 4 (CDK4) and CDK6 inhibitors (CDK4/6i) are highly effective against estrogen receptor–positive (ER+)/HER2− breast cancer; however, intrinsic and acquired resistance is common. Elucidating the molecular features of sensitivity and resistance to CDK4/6i may lead to identification of predictive biomarkers and novel therapeutic targets, paving the way toward improving patient outcomes. Experimental Design: Parental breast cancer cells and their endocrine-resistant derivatives (EndoR) were used. Derivatives with acquired resistance to palbociclib (PalboR) were generated from parental and estrogen deprivation–resistant MCF7 and T47D cells. Transcriptomic and proteomic analyses were performed in palbociclib-sensitive and PalboR lines. Gene expression data from CDK4/6i neoadjuvant trials and publicly available datasets were interrogated for correlations of gene signatures and patient outcomes. Results: Parental and EndoR breast cancer lines showed varying degrees of sensitivity to palbociclib. Transcriptomic analysis of these cell lines identified an association between high IFN signaling and reduced CDK4/6i sensitivity; thus an “IFN-related palbociclib-resistance Signature” (IRPS) was derived. In two neoadjuvant trials of CDK4/6i plus endocrine therapy, IRPS and other IFN-related signatures were highly enriched in patients with tumors exhibiting intrinsic resistance to CDK4/6i. PalboR derivatives displayed dramatic activation of IFN/STAT1 signaling compared with their short-term treated or untreated counterparts. In primary ER+/HER2− tumors, the IRPS score was significantly higher in lumB than lumA subtype and correlated with increased gene expression of immune checkpoints, endocrine resistance, and poor prognosis. Conclusions: Aberrant IFN signaling is associated with intrinsic resistance to CDK4/6i. Experimentally, acquired resistance to palbociclib is associated with activation of the IFN pathway, warranting additional studies to clarify its involvement in resistance to CDK4/6i.

PURPOSE The American Association for Cancer Research Project Genomics Evidence Neoplasia Information Exchange Biopharma Collaborative is a multi-institution effort to build a pan-cancer repository of genomic and clinical data curated from the electronic health record. For the research community to be confident that data extracted from electronic health record text are reliable, transparency of the approach used to ensure data quality is essential. MATERIALS AND METHODS Four institutions participating in AACR's Project GENIE created an observational cohort of patients with cancer for whom tumor molecular profiling data, therapeutic exposures, and treatment outcomes are available and will be shared publicly with the research community. A comprehensive approach to quality assurance included assessments of (1) feasibility of the curation model through pressure test cases; (2) accuracy through programmatic queries and comparison with source data; and (3) reproducibility via double curation and code review. RESULTS Assessments of feasibility resulted in critical modifications to the curation directives. Queries and comparison with source data identified errors that were rectified via data correction and curator retraining. Assessment of intercurator reliability indicated a reliable curation model. CONCLUSION The transparent quality assurance processes for the GENIE BPC data ensure that the data can be used for analyses that support clinical decision making and advances in precision oncology.

Importance Real-world data sets that combine clinical and genomic data may be subject to left truncation (when potential study participants are not included because they have already passed the milestone of interest at the time of study recruitment). The lapse between diagnosis and molecular testing can present analytic challenges and threaten the validity and interpretation of survival analyses. Observations Effects of ignoring left truncation when estimating overall survival are illustrated using data from the American Association for Cancer Research (AACR) Project Genomics Evidence Neoplasia Information Exchange Biopharma Collaborative (GENIE BPC), and a straightforward risk-set adjustment approach is described. Ignoring left truncation results in overestimation of overall survival: unadjusted median survival estimates from diagnosis among patients with stage IV non-small cell lung cancer or stage IV colorectal cancer were overestimated by more than 1 year. Conclusions and relevance Clinicogenomic data are a valuable resource for evaluation of real-world cancer outcomes and should be analyzed using appropriate methods to maximize their potential. Analysts must become adept at application of appropriate statistical methods to ensure valid, meaningful, and generalizable research findings.

AKT inhibitors have promising activity in AKT1E17K-mutant estrogen receptor (ER)–positive metastatic breast cancer, but the natural history of this rare genomic subtype remains unknown. Utilizing AACR Project GENIE, an international clinicogenomic data-sharing consortium, we conducted a comparative analysis of clinical outcomes of patients with matched AKT1E17K-mutant (n = 153) and AKT1–wild-type (n = 302) metastatic breast cancer. AKT1-mutant cases had similar adjusted overall survival (OS) compared with AKT1–wild-type controls (median OS, 24.1 vs. 29.9, respectively; P = 0.98). AKT1-mutant cases enjoyed longer durations on mTOR inhibitor therapy, an observation previously unrecognized in pivotal clinical trials due to the rarity of this alteration. Other baseline clinicopathologic features, as well as durations on other classes of therapy, were broadly similar. In summary, we demonstrate the feasibility of using a novel and publicly accessible clincogenomic registry to define outcomes in a rare genomically defined cancer subtype, an approach with broad applicability to precision oncology. Significance: We delineate the natural history of a rare genomically distinct cancer, AKT1E17K-mutant ER-positive breast cancer, using a publicly accessible registry of real-world patient data, thereby illustrating the potential to inform drug registration through synthetic control data. See related commentary by Castellanos and Baxi, p. 490.

The ability to serially monitor tumor-derived cell-free DNA (cfDNA) brings with it the potential to measure response to anticancer therapies and detect minimal residual disease (MRD). This report describes a patient with HER2-positive metastatic breast cancer with an exceptional response to trastuzumab and nab-paclitaxel who remains in complete remission several years after cessation of therapy. Next-generation sequencing of the patient’s primary tumor tissue showed several mutations, including an oncogenic hotspot PIK3CA mutation. A sample of cfDNA was collected 6 years after her last therapy and then analyzed for mutant PIK3CA using digital PCR. No detectable mutations associated with the primary tumor were found despite assaying >10,000 genome equivalents, suggesting that the patient had achieved a molecular remission. Results of this case study suggest that serial monitoring of MRD using liquid biopsies could provide a useful method for individualizing treatment plans for patients with metastatic disease with extreme responses to therapy. However, large-scale clinical studies are needed to validate and implement these techniques for patient care.

Background: Activating HER2 missense mutations can develop in HER2-negative metastatic breast cancer, particularly in ER-positive disease. These mutations may be targeted with anti-HER2-directed therapy, providing a novel therapeutic option for women with HER2-negative metastatic breast cancer. The clinical behavior and significance of these mutations in the era of cyclin-dependent kinase 4 and 6 inhibitors (CDK4/6i) for ER-positive breast cancer are unknown. Methods: We examined patients enrolled onto an ongoing single institution prospective study entitled Individualized Molecular Analyses Guide Efforts (IMAGE) II. The purpose of IMAGE II was to identify potentially targetable tumor genetic alterations, and the purpose of this analysis was to identify HER2 missense mutations. Patients eligible for IMAGE II had metastatic breast cancer of any subtype that had progressed on at least one standard-of-care therapy. Genetic profiling of blood was performed using the FoundationOne Liquid platform; metastatic tumor tissue profiling was performed using one of several commercially available next-generation sequencing platforms. All assays were capable of detecting common point mutations in the ERBB2 gene. Results: As of June 1, 2019, 54 patients were enrolled onto IMAGE II and had available genetic profiling results. Approximately half had ER+HER2- disease (n=29, 54%), one-third had triple negative breast cancer-TNBC (n=18, 33%), and the rest had HER2-positive disease (n=7, 13%). Six patients had activating HER2 missense mutations, with the same mutation(s) found in both tissue and blood in all patients. Five of these patients had ER+HER2- disease and the prevalence of HER2 mutations among patients with ER+HER2- disease was 17% (5/29) in our cohort. All five patients had received CDK4/6i with endocrine therapy in the metastatic setting prior to enrollment on IMAGE II. Four patients had markedly rapid tumor progression with this therapy. The median time to progression on CDK4/6i and endocrine therapy was 3.7 months (range 2.4-14.7) among patients with ER+HER2- disease and a HER2 missense mutation, compared to 9.4 months (range 2.3-40.9) among patients with ER+HER2- disease without a missense mutation. A summary of the patients with a HER2 missense mutation is shown in Table 1. Three patients with a HER2 missense mutation received HER2-directed therapy with trastuzumab and pertuzumab. One patient has an ongoing clinical response at 9.4 months, one patient has a clinical response after 1.8 months of therapy, and one patient recently began treatment with no follow-up data available yet. Conclusions: The frequency of HER2 missense mutations in patients with ER+HER2- metastatic breast cancer in our small cohort was higher than previously reported, and patients with this mutation had early tumor progression on CDK4/6i therapy regardless of endocrine therapy pairing. We hypothesize that activating HER2 missense mutations may be important drivers of resistance to CDK4/6i therapy. Testing patients who progress rapidly on CDK4/6i therapy for activating HER2 missense mutations may provide a novel therapeutic option. PatientSubtypeHER2 Mutation(s)Found whereReceived CDK4/6iLineWith which endocrine therapyTime to progression (in months)1ER+HER2-L755STissue/bloodYes2ndfulvestrant14.82ER+HER2-V777LTissue/bloodYes1sttamoxifen3.73ER+HER2-L755PTissue/bloodYes1stfulvestrant3.34ER+HER2-L755S, V697LTissue/bloodYes2ndfulvestrant4.15ER+HER2-L869RTissue/bloodYes1stletrozole2.46TNBCD769YTissue/bloodNoNANANA Citation Format: Mirat Shah, Jennifer Ensminger, Chenguang Wang, Siraj Ali, Jon Chung, Josh Lauring, Ben Ho Park, Vered Stearns. Activating HER2 missense mutations in HER2-negative metastatic 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 P6-10-07.

Introduction: The PREDICT DNA trial is the first prospective, multi-center study aimed at validating cell-free plasma derived circulating tumor DNA (ctDNA) as a biomarker for treatment response and recurrence in early stage, triple-negative or HER2-positive (any hormone receptor status) breast cancer. Its primary aim is to determine the negative predictive value (NPV) of the absence of ctDNA after neoadjuvant therapy (NAT) for the achievement of pathologic complete response (pCR). This study has met its accrual goals and results of the overall trial are anticipated within the next year. The initial PREDICT DNA study design stipulated that tumor specific mutations (TSMs) to be tracked in blood would be identified by next gen sequencing (NGS) of tumor biopsy tissue. A disadvantage of this design is the dependence on adequate biopsy tissue. Recently, the advent of Safe-SeqS technology has enabled robust detection of rare variants using NGS with a sensitivity of approximately 0.05% mutant allele fraction. We employed these new NGS methods to pilot a novel tissue-independent approach to ctDNA detection and monitoring. Objective: The primary objective of this pilot study was to determine whether ultrasensitive NGS using a targeted cancer mutation panel can identify TSMs in ctDNA of early-stage breast cancer patients without the use of biopsy tissue. Methods: The PREDICT DNA trial enrolled 228 women from 22 sites with stage II/III breast cancer for whom standard neoadjuvant therapy was planned. Of these, 58 patients had matched pre-and post-NAT samples available for analysis at the time of this pilot. All pre-NAT samples were analyzed for the presence of TSMs using Sysmex Inostics’ SafeSEQ. Patients with detectable ctDNA before NAT were also evaluated for residual ctDNA after completion of NAT but prior to surgery. Five samples were also tested by digital PCR (BEAMing) for cross-platform comparison. Results: TSMs in ctDNA were identified in 29 of 58 patients (50%) prior to NAT. Of pre-NAT ctDNA(+) patients, TSMs were detected in TP53 (90%) and PIK3CA (10%); three patients (10%) were found to have 2 TSMs. Concordance between SafeSEQ and BEAMing was 100% in five samples tested [3 ctDNA(+), 2 ctDNA(-)]. Of 29 ctDNA(+) patients, 24 (83%) demonstrated reduction or elimination of detectable ctDNA following neoadjuvant therapy, with 16 (55%) converting to ctDNA(-). Conclusion: Identification of TSMs in the plasma of early-stage breast cancer patients without the need for biopsy tissue is feasible using a SafeSEQ cancer mutation panel. Further measures to improve the sensitivity of pre-treatment TSM analysis, such as increased plasma volume input and comprehensive TP53 mutational analysis are currently under investigation. Correlations between clinicopathologic factors with ctDNA detection and burden, as well as the NPV of post-NAT ctDNA for pCR and residual cancer burden, will be reported at the time of abstract presentation. NH and HP contributed equally to this work. Citation Format: Natasha Hunter, Heather Parsons, Alexander Sherry, Daniel Shinn, Dong Ho Shin, Alex Cole, Giovanni Cragnotti, Taylor Groginski, Margaret Leathers, Andrea L Richardson, Pedram Argani, Antonio Wolff, Leslie Cope, Dan Edelstein, Frank Holtrup, Hilary Sloane, Bapsi Chakravarthy, Vered Stearns, Ben H Park. TBCRC 040: Pathologic response evaluation and detection in circulating tumor DNA (PREDICT DNA): Initial results piloting a tissue-biopsy independent method of identifying and monitoring tumor-specific mutations in early stage 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 P6-10-05.

Background: It has become increasingly clear that effective treatment of metastatic breast cancer (MBC) requires an in-depth understanding of the molecular differences between primary tumors and metastases. The AURORA US Network was established to collect primary breast cancer-metastasis pairs for multi-platform genomic profiling in order to identify the molecular drivers of metastatic disease. AURORA US has both a retrospective and prospective phase. This is the first report of the retrospective phase. Methods: Archived tissue samples from the primary tumor and at least one distant metastasis were retrospectively collected from 83 MBC patients. Following internal quality assessment, samples from 55 pts, including 105 distinct metastatic lesions, were subject to DNA low pass whole genome and exome sequencing, DNA methylation arrays, and RNA sequencing. Early analyses of these multi-platform data include: DNA methylation, tumor gene expression and microenvironmental signatures, somatic and germline variants, DNA copy number changes, and structural variants between breast primaries and matched metastases. Results: Median age at diagnosis was 49 years (25-76); 32 (58%) were Stage I or II at presentation, 27 (49%) had a family history of breast cancer, and 20 (36%) had a second breast primary. Median disease-free interval before developing MBC was 2 years (range 0-36, 5 patients presented with Stage IV). Median overall survival from initial presentation was 4 years (range 0-37). Median survival after developing MBC was 1 year (range 0-13), with a median of three treatments. Primary tissue samples were banked from 1977-2017 and metastases were banked from 1999-2017. Clinical phenotypes of the primaries included 27 HR+ (49%), 15 triple negative (TNBC, 27%), and 11 HER2+ (20%, 12 missing HER2 status). Intrinsic subtype distribution of the primaries included 17 Basal-like (31%), 17 Luminal A (31%), 7 Normal-like (13%), 5 HER2-enriched (9%), and 1 Luminal B, with 8 pending. All metastases from the Basal-like cases remained Basal-like, while metastases from luminal primaries tended to gain HER2-Enriched subtype features (5/18, p = 0.01). Overall, we identified significant metastasis-enriched alterations in metabolism pathways, an increase in proliferation, and the loss of differentiation signatures and immune infiltrates with progression; the latter being the most pronounced in brain metastases. The most frequent somatic mutations in this cohort were in TP53, NCOR1, and RUNX1. Interestingly, ERBB2, EGFR, and ATM were also mutated in ≥10% of the tumors sequenced. In almost all cases, CpG island hypermethylation was clonally present in the primary tumor and persisted stably in the majority of metastatic lesions. Promoter CpG island hypermethylation was also identified in some metastatic lesions at JAM3, an important cellular adhesion molecule,and this was accompanied by reduced mRNA expression. CONCLUSIONS: Collection of banked primary and metastatic tissue pairs identified a young MBC cohort with a high frequency of breast cancer family history and second breast primaries. Molecular characterization of luminal tumor pairs highlighted acquisition of aggressive traits including increased proliferation and loss of differentiation in the metastases. In contrast, basal-like pairs remained relatively unchanged, except for the loss of immune activation. Ongoing analyses to be presented include clonal heterogeneity and phylogeny, novel metastasis signature discovery, gene fusion, and endogenous retrovirus detection. Citation Format: Tari A King, Minetta C Liu, Marni B McClure, Toshinori Hinoue, Benjamin J Kelly, Chad J Creighton, Jay Bowen, Kristen Leraas, Robyn T Burns, Sara Coppens, Salma Rezk, Amy L Garrett, Justin M Balko, Joel S Parker, Ben H Park, Ian Krop, Carey Anders, Katherine A Hoadley, Julie Gastier-Foster, Mothaffar F Rimawi, Rita Nanda, Nancy U Lin, Claudine Isaacs, P. Kelly Marcom, Anna Maria Storniolo, Fergus J Couch, Elaine R Mardis, Adrian V Lee, Uma Chandran, Peter W Laird, Susan G Hilsenbeck, Larry Norton, Andrea L Richardson, W. Fraser Symmans, Lisa A Carey, Antonio C Wolff, Nancy E Davidson, Charles M Perou, the AURORA US Network. Multiplatform analysis of matched primary and metastatic breast tumors from the AURORA US Network [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 GS3-08.

Purpose: Prognostic value of Oncotype DX Breast Recurrence Score (RS) in male patients with breast cancer is understudied. We evaluated associations of RS with overall mortality in male patients with breast cancer and compared it with female counterparts. Experimental Design: With a cohort of 848 male and 110,898 female patients with breast cancer identified from the National Cancer Database (2010–2014), we estimated HRs and 95% confidence intervals (CI) for overall mortality associated with RS using Cox regression models. RS was evaluated continuously, as well as by categorization following respective traditional (≤17, 18–30, and ≥31) and TAILORx (≤10, 11–25, and ≥26) cutoffs. Results: RS was positively associated with mortality in male patients (HR = 1.13; 95% CI, 1.02–1.26 per unit RS increment) up to RS > 21, after which the risk plateaued. Among female patients, mortality began to increase with RS only when RS > 23 (HR = 1.02; 95% CI, 1.01–1.02 per unit of RS increment). The intermediate- (HR = 5.37; 95% CI, 1.79–16.11) and high-risk diseases (HR = 4.28; 95% CI, 1.22–14.97) defined by TAILORx, but not traditional cutoffs established for female patients, were associated with elevated mortality risk in men even after adjustment for demographic, clinical characteristics, and treatments, except chemotherapy. Conclusions: RS is associated with mortality in male patients with breast cancer at a much lower threshold than that for female patients. Studies are needed to establish specific guidelines for RS thresholds for male patients with breast cancer.

Estrogen receptor-positive (ER+) metastatic tumors contribute to nearly 70% of breast cancer-related deaths. Most patients with ER+ metastatic breast cancer (MBC) undergo treatment with the estrogen receptor antagonist fulvestrant (Fulv) as standard-of-care. Yet, among such patients, metastasis in liver is associated with reduced overall survival compared to other metastasis sites. The factors underlying the reduced responsiveness of liver metastases to ER-targeting agents remain unknown, impeding the development of more effective treatment approaches to improve outcomes for patients with ER+ liver metastases. We therefore evaluated site-specific changes in MBC cells and determined the mechanisms through which the liver metastatic niche specifically influences ER+ tumor metabolism and drug resistance. We characterized ER activity of MBC cells both in vitro, using a novel system of tissue-specific extracellular matrix hydrogels representing the stroma of ER+ tumor metastatic sites (liver, lung and bone), and in vivo, in liver and lung metastasis mouse models. ER+ metastatic liver tumors and MBC cells grown in liver hydrogels displayed upregulated expression of glucose metabolism enzymes in response to Fulv. Furthermore, differential ERα activity, but not expression, was detected in liver hydrogels. In vivo, increased glucose metabolism led to increased glycogen deposition in liver metastatic tumors, while a fasting-mimicking diet increased efficacy of Fulv treatment to reduce the metastatic burden.ImplicationsOur findings identify a novel mechanism of endocrine resistance driven by the liver tumor microenvironment. These results may guide the development of dietary strategies to circumvent drug resistance in liver metastasis, with potential applicability in other metastatic diseases.

Metastatic estrogen receptor α (ERα)-positive breast cancer is presently incurable. Seeking to target these drug-resistant cancers, we report the discovery of a compound, called ErSO, that activates the anticipatory unfolded protein response (a-UPR) and induces rapid and selective necrosis of ERα-positive breast cancer cell lines in vitro. We then tested ErSO in vivo in several preclinical orthotopic and metastasis mouse models carrying different xenografts of human breast cancer lines or patient-derived breast tumors. In multiple orthotopic models, ErSO treatment given either orally or intraperitoneally for 14 to 21 days induced tumor regression without recurrence. In a cell line tail vein metastasis model, ErSO was also effective at inducing regression of most lung, bone, and liver metastases. ErSO treatment induced almost complete regression of brain metastases in mice carrying intracranial human breast cancer cell line xenografts. Tumors that did not undergo complete regression and regrew remained sensitive to retreatment with ErSO. ErSO was well tolerated in mice, rats, and dogs at doses above those needed for therapeutic responses and had little or no effect on normal ERα-expressing murine tissues. ErSO mediated its anticancer effects through activation of the a-UPR, suggesting that activation of a tumor protective pathway could induce tumor regression.

Both epidemiologic and cellular studies in the context of autoimmune diseases have established that protein tyrosine phosphatase nonreceptor type 22 (PTPN22) is a key regulator of T cell receptor (TCR) signaling. However, its mechanism of action in tumors and its translatability as a target for cancer immunotherapy have not been established. Here, we show that a germline variant of PTPN22, rs2476601, portended a lower likelihood of cancer in patients. PTPN22 expression was also associated with markers of immune regulation in multiple cancer types. In mice, lack of PTPN22 augmented antitumor activity with greater infiltration and activation of macrophages, natural killer (NK) cells, and T cells. Notably, we generated a small molecule inhibitor of PTPN22, named L-1, that phenocopied the antitumor effects seen in genotypic PTPN22 knockout. PTPN22 inhibition promoted activation of CD8(+) T cells and macrophage subpopulations toward MHC-II–expressing M1-like phenotypes, both of which were necessary for successful antitumor efficacy. Increased PD-1/PD-L1 axis expression in the setting of PTPN22 inhibition could be further leveraged with PD-1 inhibition to augment antitumor effects. Similarly, cancer patients with the rs2476601 variant responded significantly better to checkpoint inhibitor immunotherapy. Our findings suggest that PTPN22 is a druggable systemic target for cancer immunotherapy.

PURPOSE Tissue-based next-generation sequencing (NGS) in metastatic breast cancer (mBC) is limited by the inability to noninvasively track tumor evolution. Cell-free DNA (cfDNA) NGS has made sequential testing feasible; however, the relationship between cfDNA and tissue-based testing in mBC is not well understood. Here, we evaluate concordance between tissue and cfDNA NGS relative to cfDNA sampling frequency in a large, clinically annotated mBC data set. METHODS Tempus LENS was used to analyze deidentified records of mBC cases with Tempus xT (tissue) and xF (cfDNA) sequencing results. Then, various metrics of concordance were assessed within overlapping probe regions of the tissue and cfDNA assays (104 genes), focusing on pathogenic variants. Variant allele frequencies of discordant and concordant pathogenic variants were also compared. Analyses were stratified by mBC subtype and time between tests. RESULTS Records from 300 paired tissue and liquid biopsies were analyzed. Median time between tissue and blood collection was 78.5 days (standard deviation = 642.99). The median number of pathogenic variants/patient was one for cfDNA and two for tissue. Across the cohort, 77.8% of pathogenic tissue variants were found in cfDNA and 75.7% of pathogenic cfDNA variants were found in tissue when tests were ≤ 7 days apart, which decreased to 50.3% and 51.8%, respectively, for > 365 days. Furthermore, the median patient-level variant concordance was 67% when tests were ≤7 days apart and 30%-37% when > 30 days. The median variant allele frequencies of discordant variants were generally lower than those of concordant variants within the same time frame. CONCLUSION We observed high concordances between tissue and cfDNA results that generally decreased with longer durations between tests. Thus, cfDNA NGS reliably measures tissue genomics and is likely beneficial for longitudinal monitoring of molecular changes in mBC.

PURPOSE Patients with triple-negative breast cancer (TNBC) and residual invasive disease (RD) after completion of neoadjuvant chemotherapy (NAC) have a high-risk for recurrence, which is reduced by adjuvant capecitabine. Preclinical models support the use of platinum agents in the TNBC basal subtype. The EA1131 trial hypothesized that invasive disease-free survival (iDFS) would not be inferior but improved in patients with basal subtype TNBC treated with adjuvant platinum compared with capecitabine. PATIENTS AND METHODS Patients with clinical stage II or III TNBC with ≥ 1 cm RD in the breast post-NAC were randomly assigned to receive platinum (carboplatin or cisplatin) once every 3 weeks for four cycles or capecitabine 14 out of 21 days every 3 weeks for six cycles. TNBC subtype (basal v nonbasal) was determined by PAM50 in the residual disease. A noninferiority design with superiority alternative was chosen, assuming a 4-year iDFS of 67% with capecitabine. RESULTS Four hundred ten of planned 775 participants were randomly assigned to platinum or capecitabine between 2015 and 2021. After median follow-up of 20 months and 120 iDFS events (61% of full information) in the 308 (78%) patients with basal subtype TNBC, the 3-year iDFS for platinum was 42% (95% CI, 30 to 53) versus 49% (95% CI, 39 to 59) for capecitabine. Grade 3 and 4 toxicities were more common with platinum agents. The Data and Safety Monitoring Committee recommended stopping the trial as it was unlikely that further follow-up would show noninferiority or superiority of platinum. CONCLUSION Platinum agents do not improve outcomes in patients with basal subtype TNBC RD post-NAC and are associated with more severe toxicity when compared with capecitabine. Participants had a lower than expected 3-year iDFS regardless of study treatment, highlighting the need for better therapies in this high-risk population.

Acquired mutations in the ligand-binding domain (LBD) of the gene encoding estrogen receptor α (ESR1) are common mechanisms of endocrine therapy resistance in patients with metastatic ER+ breast cancer. The ESR1 Y537S mutation, in particular, is associated with development of resistance to most endocrine therapies used to treat breast cancer. Employing a high-throughput screen of nearly 1,200 Federal Drug Administration-approved (FDA-approved) drugs, we show that OTX015, a bromodomain and extraterminal domain (BET) inhibitor, is one of the top suppressors of ESR1 mutant cell growth. OTX015 was more efficacious than fulvestrant, a selective ER degrader, in inhibiting ESR1 mutant xenograft growth. When combined with abemaciclib, a CDK4/6 inhibitor, OTX015 induced more potent tumor regression than current standard-of-care treatment of abemaciclib + fulvestrant. OTX015 has preferential activity against Y537S mutant breast cancer cells and blocks their clonal selection in competition studies with WT cells. Thus, BET inhibition has the potential to both prevent and overcome ESR1 mutant-induced endocrine therapy resistance in breast cancer.

Advances in genomic strategies and the development of targeted therapies have enabled precision medicine to revolutionise the field of oncology. Precision medicine uses patient-specific genetic and molecular information, traditionally obtained from tumour biopsy samples, to classify tumours and treat them accordingly. However, biopsy samples often fail to provide complete tumour profiling, and the technique is expensive and, of course, relatively invasive. Advances in genomic techniques have led to improvements in the isolation and detection of circulating tumour DNA (ctDNA), a component of a peripheral blood draw/liquid biopsy. Liquid biopsy offers a minimally invasive method to gather genetic information that is representative of a global snapshot of both primary and metastatic sites and can thereby provide invaluable information for potential targeted therapies and methods for tumour surveillance. However, a lack of prospective clinical trials showing direct patient benefit has limited the implementation of liquid biopsies in standard clinical applications. Here, we review the potential of ctDNA obtained by liquid biopsy to revolutionise personalised medicine and discuss current applications of ctDNA both at the benchtop and bedside.

Cancer-associated mutations in the spliceosome gene SF3B1 create a neomorphic protein that produces aberrant mRNA splicing in hundreds of genes, but the ensuing biologic and therapeutic consequences of this missplicing are not well understood. Here we have provided evidence that aberrant splicing by mutant SF3B1 altered the transcriptome, proteome, and metabolome of human cells, leading to missplicing-associated downregulation of metabolic genes, decreased mitochondrial respiration, and suppression of the serine synthesis pathway. We also found that mutant SF3B1 induces vulnerability to deprivation of the nonessential amino acid serine, which was mediated by missplicing-associated downregulation of the serine synthesis pathway enzyme PHGDH. This vulnerability was manifest both in vitro and in vivo, as dietary restriction of serine and glycine in mice was able to inhibit the growth of SF3B1(MUT) xenografts. These findings describe a role for SF3B1 mutations in altered energy metabolism, and they offer a new therapeutic strategy against SF3B1(MUT) cancers.

Tumor progression to metastasis is not cancer cell autonomous, but rather involves the interplay of multiple cell types within the tumor microenvironment. Here we identify asporin (ASPN) as a novel, secreted mesenchymal stromal cell (MSC) factor in the tumor microenvironment that regulates metastatic development. MSCs expressed high levels of ASPN, which decreased following lineage differentiation. ASPN loss impaired MSC self-renewal and promoted terminal cell differentiation. Mechanistically, secreted ASPN bound to BMP-4 and restricted BMP-4–induced MSC differentiation prior to lineage commitment. ASPN expression was distinctly conserved between MSC and cancer-associated fibroblasts (CAF). ASPN expression in the tumor microenvironment broadly impacted multiple cell types. Prostate tumor allografts in ASPN-null mice had a reduced number of tumor-associated MSCs, fewer cancer stem cells, decreased tumor vasculature, and an increased percentage of infiltrating CD8+ T cells. ASPN-null mice also demonstrated a significant reduction in lung metastases compared with wild-type mice. These data establish a role for ASPN as a critical MSC factor that extensively affects the tumor microenvironment and induces metastatic progression.Significance:These findings show that asporin regulates key properties of mesenchymal stromal cells, including self-renewal and multipotency, and asporin expression by reactive stromal cells alters the tumor microenvironment and promotes metastatic progression.

PURPOSE Predictive biomarkers to identify patients with human epidermal growth factor receptor 2 (HER2)–positive breast cancer who may benefit from targeted therapy alone are required. We hypothesized that early measurements of tumor maximum standardized uptake values corrected for lean body mass (SULmax) on [18F]fluorodeoxyglucose positron emission tomography/computed tomography would predict pathologic complete response (pCR) to neoadjuvant pertuzumab and trastuzumab (PT). PATIENTS AND METHODS Patients with stage II/III, estrogen receptor–negative, HER2-positive breast cancer received four cycles of neoadjuvant PT. [18F]Fluorodeoxyglucose positron emission tomography/computed tomography was performed at baseline and 15 days after PT initiation (C1D15). Eighty evaluable patients were required to test the null hypothesis that the area under the curve of percentage of change in SULmax by C1D15 predicting pCR is less than or equal to 0.65, with a one-sided type I error rate of 10%. RESULTS Eighty-eight women were enrolled (83 evaluable), and 85% (75 of 88) completed all four cycles of PT. pCR after PT alone was 34%. Receiver operating characteristic analysis yielded an area under the curve of 0.76 (90% CI, 0.67 to 0.85), which rejected the null hypothesis. Between patients who obtained pCR versus not, a significant difference in median percent reduction in SULmax by C1D15 was observed (63.8% v 33.5%; P < .001), an SULmax reduction greater than or equal to 40% was more prevalent (86% v 46%; P < .001; negative predictive value, 88%; positive predictive value, 49%), and a significant difference in median C1D15 SULmax (1.6 v 3.9; P < .001) and higher proportion of C1D15 SULmax less than or equal to 3 (93% v 38%; P < .001; negative predictive value, 94%; positive predictive value, 55%) were observed. CONCLUSION Early changes in SULmax predict response to four cycles of PT in estrogen receptor–negative, HER2-positive breast cancer. Once optimized, this quantitative imaging strategy may facilitate a more tailored approach to therapy in this setting.

Despite the well-documented benefits of circulating tumor DNA (ctDNA) based liquid biopsy, including screening, prognostication, and treatment monitoring, there remain several concerns with its application. Chief among these concerns are imperfect sensitivity and specificity, particularly pre-diagnosis and after tumor resection, when ctDNA burden is low. Cell death, either through apoptosis or necrosis, has been the most widely accepted mechanism of DNA release. Recent studies have also suggested active release through extracellular vesicles as a paradigm for DNA release. However, this pathway remains highly debated in terms of its contribution, mechanism, and even credibility. To address the deficiencies in ctDNA detection in the clinic and the lack of basic mechanistic knowledge of cf/ctDNA release, we performed an in vitro CRISPR screen on MCF10A cells to identify regulators of DNA release. This normal breast epithelial cell line was chosen because MCF10A cells release DNA into cell culture media with a similar fragmentation pattern to that observed in human blood. After lentiviral infection with the genome-wide Brunello CRISPR-Cas9 knockout library, the population of knockouts identified in the genomic DNA of cells attached to the plates was compared to the population of knockouts found in the DNA released into the cell-depleted culture media. Genes with skewed representation were considered potential regulators of DNA release. Our analysis identified several genes in the TRAIL apoptotic pathway including FADD, as well as several genes encoding RNA-binding proteins including Sam68. Knockout of Sam68 and FADD in MCF10As, MDA-MB-468 breast cancer cells, and NCI-H841 lung cancer cells lead to decreases in DNA release. Previous studies have hypothesized that the fragment size of released DNA is dependent on release mechanism. However, the decreases observed in our knockout cell lines were not limited to a specific fragment size of DNA. Application of the small molecule apoptosis inhibitor Z-VAD-FMK also recapitulated the DNA release phenotype seen in our knockout cell lines. From these results, we conclude that apoptosis is the major source of DNA release from cancer cells, and that fragment size is not the indicator of release mechanism it has been presumed to be. Mechanistic studies of DNA release such as this could lead to the ability to modify the amount of ctDNA in circulation, which would significantly improve accurate detection in the clinic. Citation Format: Brad A. Davidson, Adam X. Miranda, Sarah Croessmann, Ben Ho Park. Novel CRISPR screening approach identifies regulators of cell-free DNA release in vitro [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 13.

PIK3CA is the most commonly mutated gene in breast cancer, and in breast cancer there are two hotspot mutations that represent an outsized proportion of PIK3CA mutations. Previous research suggests that there are distinct prognostic and cell signaling differences induced by these mutational isoforms, however there is currently only one targeted treatment approved for PIK3CA mutant breast cancer. The goal of our research is to leverage a comprehensive multi-lineage isogenic breast cell line model to further interrogate the unique effects of these PIK3CA mutations on breast cells using assays to assess gene expression and chromatin state. Insights gained from these assays shed light on disrupted pathways that may prove to be new targets for PIK3CA mutation-specific treatment of breast cancer. Citation Format: Adam X. Miranda, Emily Hodges, Ben Ho Park. Functional genomic dissection of PIK3CA hotspot mutations using a multi-lineage isogenic breast cell model [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 3726.

Cytotoxic chemotherapy has been the backbone of medical oncology for nearly a century for multiple cancer types. However, when treating advanced or metastatic disease toxicity, side effects, and acquired resistance often limit the duration of therapy. While randomized control trials have traditionally served as the proving ground for first and subsequent line therapies, rare tumor subtypes including soft tumor sarcoma (STS) provide unique challenges for developing robust treatment data. By developing human based in vitro models, we can investigate potential therapeutic mechanisms for STS. Fibrosarcoma is one distinct histologic STS subtype that relies heavily on anthracycline treatment in the first line setting, however, there are limited options once resistance develops. Anthracyclines, including doxorubicin, exert their effect through a variety of mechanisms including reactive oxygen species, DNA-adduct formation, and inhibiting topoisomerase II, histone eviction, calcium and iron homeostasis, and ceramide overproduction. However, there have also been multiple mechanisms of doxorubicin resistance including disruption of cell membrane, alteration of cell surface molecules, inactivation of drugs, gene amplification, activating alternative signaling pathways, and affecting cellular repair mechanisms. In order to investigate the role of anthracycline resistance in fibrosarcoma lines we acquired two human derived fibrosarcoma lines SW684 and HT-1080 from American Type Culture Collection (ATCC). Characterization of HT-1080 using publicly available datasets demonstrated that TP53, CDK2NA and NF1 serve as major driver mutations while SW684 relies on NRAS and IDH1 mutations. We further characterized these cell lines in vitro and noted that HT-1080 has a quick doubling time of 16 hours while SW684 has a doubling time of 91 hours. Additionally, after doxorubicin treatment, we found that HT-1080 is sensitive with an IC50 of 5.594 nanomolar while SW684 is relatively doxorubicin resistant with an IC50 of 28.915 micromolar. While proliferative rate may play a role in the sensitivities of these cell lines further characterization of the mechanism leading to doxorubicin resistance is needed. To that end, we are using a CRISPR-Cas9 approach for further genome wide screening of these fibrosarcoma lines in the presence of doxorubicin. Exploring the genetic mechanisms that result in development of doxorubicin resistance may reveal novel, targetable mechanisms expanding treatment durability in this rare STS. Citation Format: Rodney Dixon Dorand, Donna Dang, Elizabeth J. Davis, Ben Ho Park. Investigating doxorubicin resistance in fibrosarcoma [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 3974.

e13564 Background: Immune checkpoint inhibitor (ICI) therapies have shown impressive results in treating oncology patients. However, some patients exhibit immune-related adverse events (irAE-s), one significant irAE is autoimmune hepatitis. Oncologists routinely screen for hepatic toxicity with a complete metabolic panel prior to each ICI administration. Predictive modeling of irAE-s based on patient factors has the potential to help guide treatment selection and monitoring protocols. We have developed a widely usable model based on patient history and routinely collected standard blood panels that can predict whether a patient will experience hepatitis with ICI administration. Methods: We defined irAE hepatitis as any single value of AST, ALT, or alkaline phosphatase three-times the upper limit of normal (ULN) as following ICI treatment. The goal was to determine whether the level of the biomarkers exceed this threshold within certain, pre-defined time-windows, as determined by medical experts. We used feature engineering to compress the time-series of lab panels into single meaningful statistical descriptors, such as mean or maximum of these vectors. The dataset was highly unbalanced with many more negative cases (out of the 3231 patients, depending on the window length used for feature generation, 100-400 positives were found), which warranted the application of synthetic resampling methods. Finally, we trained various ensemble models ( e.g., random forest, gradient boosting), on both the resampled and original dataset, to obtain the final, predictive model for the likelihood of irAE hepatitis. Models were tuned to favor high recall and lower precision (identification of patients for increased monitoring) or moderate recall and moderate precision (maximizing F1-score). Results: We explored several modelling methods, such as KNN, Logistic Regression, Random Forests (RF), Gradient Boosting (GB), and stacking. GB without resampling produced the best model with the moderate recall and precision. To achieve high recall with low precision, we needed to resample the dataset with random majority class under sampling and then use RF (see table below for exact results). Conclusions: In this study, we show contemporary machine learning methods can be used as a screening tool for patients at risk for irAE hepatitis. This method could be used to identify patients who would benefit from additional laboratory monitoring between ICI administrations or guide clinical decisions about therapy cessation in advance of toxicity. Additionally, these methods may be further developed and adapted to improve clinical trial exclusion criteria for patients most likely to develop irAE hepatitis.[Table: see text]

e13566 Background: Immune checkpoint inhibitors (ICI) have improved outcomes in tumor types allowing subgroups of patients to have longer, higher quality lives. However, potential life-threatening immunotoxicities can arise in susceptible patients, including pneumonitis. Identifying patients at high risk of immunotoxicity can help patients understand potential adverse events, improve clinical trial cohort selection, and inform therapy selection in clinical settings. Here, we use electronic health record (EHR) data to build a binary classification model that predicts the probability of developing pneumonitis after the first ICI administration. Methods: We utilized real-world EHR-derived structured and unstructured data from > 2,700 patients from Vanderbilt University Medical Center obtained prior to December 31, 2018. Unstructured data were transformed into structured variables by expert curators, including labels for pneumonitis episodes following ICI initiation. Feature engineering involved aggregating lab measurements over a 60-day time window before the first ICI; other features (conditions, smoking status, etc.) used a 1-year window. To build a small, easily deployable model and assess its performance robustly, we utilized a sequential process. In each step, we decided between two versions of a random forest model, one with the original feature set (M1) and one extended with a candidate feature (M2). We identified candidate features using 90% of the data. We performed nested cross-validation on this partition and compared the inner loop results. If M2 was significantly better, we tested whether it performed better on the 10% partition. If it did, we chose M2 and assessed its performance on the outer loop. This procedure was created as our dataset was rather small and noisy, which is typical for EHR-derived data. Results: All-cause pneumonitis incidence following ICI initiation was 8.4%. Our final model includes only six features: frequency of lung-related ICD-10 codes, frequency of C34 code, frequency of C78 code, smoking status, interaction between smoking and C34/C78 indicators, and median of blood oxygen saturation. This model achieved a mean AUC of 0.66 (SD: 0.07). Our analysis on the outer loop predictions showed that selecting 50% of patients with the lowest predicted probabilities reduced the occurrence of pneumonitis in the cohort to 5%, compared to 8.4%, when we select patients randomly. The model achieved a mean positive predictive value of 0.3 and negative predictive value of 0.96. Conclusions: We utilized a real-world EHR dataset to identify patterns in patient medical history that could predict the development of pneumonitis. We demonstrated that a small number of easily obtainable clinical covariates can result in meaningful predictions. This model illustrates potential future use for identifying the patients with the highest and lowest risks for pneumonitis during treatment.

3077 Background: While targeted DNA-seq can detect clinically actionable fusions in tumor tissue samples, technical and analytical challenges may give rise to false negatives. RNA-based, whole-exome sequencing provides a complementary method for fusion detection, and may improve the identification of actionable variants. In this study, we quantify this benefit using a large, real-world clinical dataset to assess actionable fusions detected from RNA in conjunction with DNA profiling. Methods: Using the Tempus Research Database, we retrospectively analyzed a de-identified dataset of ̃80K samples (77.4K patients) profiled with the Tempus xT assay (both DNA-seq with fusion detection in 21 genes and whole exome capture RNA-seq). Only patients that had successful RNA- and DNA-seq were included. Fusions were detected using the Tempus bioinformatic and clinical workflow. Candidate fusions were filtered based on read support thresholds, fusion annotation ( i.e., breakpoints, reading frame, conserved domains), and manual review. OncoKB was used to select fusion alterations in levels 1 and 2 and to identify those indication-matched to targeted therapies. Results: We identified 2118 level 1 and 2 fusion events across 1945 patients across 20 different cancer types. Most fusions were observed in non-small cell lung cancer (NSCLC) (25%) and biliary cancer (9%) samples. Of the 2118 fusion events, 29.1% (616) were detected only through RNA-seq while 4.8% (101) of the events were identifiable only through DNA-seq. Notably, 69.4% of fusions in low-grade glioma and 58.2% in sarcomas were detected only by RNA-seq. When evaluating specific gene fusion events, RNA-seq consistently improved the detection of fusions compared to DNA-seq alone (Table) across all cancer types. A total of 1106 fusions were classified as targetable by OncoKB indication-matched therapies with 19% (214) of these identifiable through RNA-seq alone, 5% (54) by DNA-seq alone, and 76% (838) identifiable through RNA- and DNA-seq. Overall, fusions identified through RNA-seq alone led to a 24% increase in the number of patients who were eligible to receive matched therapies (214 / 892). This included imatinib for patients with CML/BLCL (69.8%), crizotinib for NSCLC (40.3%) and entrectinib for NTRK and ROS1 fusions (32.5%). Conclusions: The addition of RNA-seq to DNA-seq significantly increased the detection of fusion events and ability to match patients to targeted therapies. Results support consideration of combined RNA-DNA-seq for standard-of-care fusion calling. [Table: see text]

e13565 Background: Hepatitis toxicity is one of the most important adverse effects of immune checkpoint inhibitor (ICI) therapy, occurring in approximately 10% of patients. However, when identified early, it can be managed clinically, potentially allowing continuation of ICI treatment. The goal of the study was to evaluate the feasibility and clinical usefulness of an artificial intelligence (AI) model to predict the risk of developing hepatitis toxicity during the course of ICI treatment from routine bloodwork values. Methods: Our model uses a clinical dataset of 2438 patients who received ICI treatment at the Vanderbilt University Medical Center prior to the end of 2020. Hepatitis toxicity was defined as one or more of ALT, AST, ALKPHOS, BILIRUBIN values exceeding 2.5-times the upper limit of normal value. The available feature set was limited to the routinely available blood test values. All features were normalized to the upper limit of normal and transformed to a discretized symbolic representation, a modified version of Symbolic Aggregate ApproXimation. Motifs were extracted as n-grams from the symbol series, and the counts were used as input features for the predictive model. The study uses standard data science model training and evaluation concepts: train, validation, and test splits were created randomly on the patient level; the reported evaluation metrics are median AUC, TPR, TNR, PPV, NPV over 10 sampling runs. The final, best-performing model architecture is a boosted decision tree model (XGBoost) trained on the last four blood tests to predict hepatitis at the next blood sampling timepoint (i.e., at the time of the next ICI treatment appointment). Results: The best model uses the following eight blood values as features: ALT, AST, ALKPHOS, BILIRUBIN, ALBUMIN, CO2, CALCIUM, and BUN, and achieves an AUC of 0.82 (std. 0.01), with TPR = 0.32 (0.03), TNR = 0.97 (0.005), PPV = 0.18 (0.03), and NPV = 0.99 (0.002). It finds 32% of the timepoints where the patient is going to develop hepatitis toxicity prior to their next treatment, and about 1 in 5 positive predictions are correct. It is important to note that only about 1% of all ‘sequences’ of four consecutive blood tests are followed by hepatitis at the next test. That is, while a relatively large proportion of patients are going to develop hepatitis toxicity during their ICI treatment, the timepoint at which this happens is very uncertain. Conclusions: We demonstrate that an AI model built using only already available patient laboratory data could provide clinically useful input for clinicians to support their ICI treatment decisions to reduce the occurrence of hepatitis toxicity. The dynamic nature and below-patient-level granularity of the model would allow a clinician / clinical trial investigator to make adjustments to the therapy based on individual patient reaction over time.

e13581 Background: In the past decade, immunotherapies have revolutionized oncology practice by prolonging patient survival in previously rapidly fatal cancers. However, severe immune toxicities present a challenge, affecting ̃20% and up to 50% of patients on immune monotherapies and combination immunotherapies, respectively. Oncologists must balance toxicity risk with potential efficacy, and pharmaceutical companies have a vested interest in selecting patients with the highest benefit–risk ratio during trial enrollment. Predictive toxicity–efficacy modeling has the potential to guide trial subject selection and clinical care, yet there remains a need for predictive models that can be practically implemented in these settings. Methods: A common academic–industry contract data–transfer framework—wherein academic medical institutions and industry counterparts act in isolation—creates barriers to development of high-quality algorithms with practical applications. In this framework, 1) academic medical institutions provide patient data as a “data dump;” these data are static and cannot be refined—reducing opportunities for quality control; 2) predictive model outcomes may include artifacts that are not identified; 3) manual curation of patient data is required to accurately replicate the model in real-world settings; and 4) lack of clinician participation reduces the potential clinical applications of models and reciprocal benefit to the academic institution. We outline a more contemporary, engaged approach to unite strengths of both partners to achieve a common goal. Results: In 2019, Vanderbilt University Medical Center and GE Healthcare partnered with the goal of enabling safer and more precise immunotherapy use. As part of this work, we formulated a recipe for academic–industry partnerships that offers unique advantages over a static contract framework. In our iterative, interactive approach, 1) clinical and curation experts meet with industry modelers to dynamically refine deidentified data sets by resolving discrepancies in data from different sources (e.g., manually curated vs. structured data); 2) clinical experts iteratively review outputs of predictive models to identify potential artifacts and refine final models; 3) expert curators iterate with in-house machine-learning experts to create algorithms to automate curation of natural language elements from the identified EHR data; and 4) clinical and industry stakeholders participate in regular meetings with modelers to ensure clinical and trial utility of the modeling approach. Conclusions: Compared to data transfer-only relationships, this partnership framework offers an opportunity to develop more informed, higher quality immunotherapy models with clinical and industry applications.

PURPOSE: Estrogen receptor-alpha (ER) is a therapeutic target of ER positive (ER+) breast cancers. Although ER signaling is complex, many mediators of this pathway have been identified. Specifically, phosphorylation of ER at serine 118 affects responses to estrogen and therapeutic ligands and has been correlated with clinical outcomes in ER+ breast cancer patients. We hypothesized that a newly described germline variant (S118P) at this residue would drive cellular changes consistent with breast cancer development and/or hormone resistance. METHODS: Isogenic human breast epithelial cell line models harboring ER S118P were developed via genome editing and characterized to determine the functional effects of this variant. We also examined the frequency of ER S118P in a case control study (N=536) of women with and without breast cancer with a familial risk. RESULTS: In heterozygous knock-in models, the S118P variant demonstrated no significant change in proliferation, migration, MAP Kinase pathway signaling, or response to the endocrine therapies tamoxifen and fulvestrant. Further, there was no difference in the prevalence of S118P between women with and without cancer relative to population registry databases. CONCLUSIONS: This study suggests that the ER S118P variant does not affect risk for breast cancer or hormone therapy resistance. Germline screening and modification of treatments for patients harboring this variant are likely not warranted.

The use of circulating tumor DNA (ctDNA) in liquid biopsy as a biomarker is becoming the new paradigm for the screening and surveillance of breast and many other cancers. Liquid biopsies provide prognostic and predictive information without the limitations of tissue biopsies. Most early studies of the use of ctDNA focused on metastatic disease. However, recent advancements in ctDNA technologies have improved sensitivity and selectivity, allowing ctDNA to be detected in early-stage disease, including early-stage breast cancer. Despite a clear potential for utility, the implementation of ctDNA liquid biopsy in standard of care is significantly lacking. Researchers and clinicians are currently working to validate the clinical utility of ctDNA in diagnostics, prognostics, the surveillance of minimal residual disease, and the monitoring of therapeutic response. This review summarizes the current applications of ctDNA in early-stage breast cancer and discusses its potential uses in clinical practice.

Intratumor heterogeneity is an important mediator of poor outcomes in many cancers, including breast cancer. Genetic subclones frequently contribute to this heterogeneity; however, their growth dynamics and interactions remain poorly understood. PIK3CA and HER2 alterations are known to coexist in breast and other cancers. Herein, we present data that describe the ability of oncogenic PIK3CA mutant cells to induce the proliferation of quiescent HER2 mutant cells through a cell contact–mediated mechanism. Interestingly, the HER2 cells proliferated to become the major subclone over PIK3CA counterparts both in vitro and in vivo. Furthermore, this phenotype was observed in both hormone receptor–positive and –negative cell lines, and was dependent on the expression of fibronectin from mutant PIK3CA cells. Analysis of human tumors demonstrated similar HER2:PIK3CA clonal dynamics and fibronectin expression. Our study provides insight into nonrandom subclonal architecture of heterogenous tumors, which may aid the understanding of tumor evolution and inform future strategies for personalized medicine.

Constitutively active estrogen receptor-α (ER/ESR1) mutations have been identified in approximately one third of ER+ metastatic breast cancer. Although these mutations are known mediators of endocrine resistance, their potential role in promoting metastatic disease has not yet been mechanistically addressed. In this study, we show the presence of ESR1 mutations exclusively in distant, but not local recurrences. In concordance with transcriptomic profiling of ESR1 mutant tumors, genome-edited Y537S and D538G cell models have a reprogrammed cell adhesive gene network via alterations in desmosome/gap junction genes and the TIMP3/MMP axis, which functionally confers enhanced cell-cell contacts while decreased cell-ECM adhesion. Context-dependent migratory phenotypes revealed co-targeting of Wnt and ER as vulnerability. Mutant ESR1 exhibits non-canonical regulation of several metastatic pathways including secondary transactivation and de novo FOXA1-driven chromatin remodeling. Collectively, our data supports evidence for ESR1 mutation-driven metastases and provides insight for future preclinical therapeutic strategies.SignificanceContext and allele-dependent transcriptome and cistrome reprogramming in genome-edited ESR1 mutation cell models elicit diverse metastatic phenotypes, including but not limited to alterations in cell adhesion and migration. The gain-of-function mutations can be pharmacologically targeted, and thus may be key components of novel therapeutic treatment strategies for ER-mutant metastatic breast cancer.

PURPOSE Predictive biomarkers to identify patients with human epidermal growth factor receptor 2 (HER2)–positive breast cancer who may benefit from targeted therapy alone are required. We hypothesized that early measurements of tumor maximum standardized uptake value corrected for lean body mass (SULmax) on 18F-labeled fluorodeoxyglucose positron emission tomography-computed tomography (PET-CT) would predict pathologic complete response (pCR) to pertuzumab and trastuzumab (PT). PATIENTS AND METHODS Patients with stage II or III, estrogen receptor–negative, HER2-positive breast cancer received four cycles of neoadjuvant PT. 18F-labeled fluorodeoxyglucose positron emission tomography-computed tomography was performed at baseline and 15 days after PT initiation (C1D15). Eighty evaluable patients were required to test the null hypothesis that the area under the curve of percent change in SULmax by C1D15 predicting pCR is ≤ 0.65, with a one-sided type I error rate of 10%. RESULTS Eighty-eight women were enrolled (83 evaluable), and 85% (75 of 88) completed all four cycles of PT. pCR after PT alone was 22%. Receiver operator characteristic analysis of percent change in SULmax by C1D15 yielded an area under the curve of 0.72 (80% CI, 0.64 to 0.80; one-sided P = .12), which did not reject the null hypothesis. However, between patients who obtained pCR and who did not, a significant difference in median percent reduction in SULmax by C1D15 was observed (63.8% v 41.8%; P = .004) and SULmax reduction ≥ 40% was more prevalent (83% v 52%; P = .03; positive predictive value, 31%). Participants not obtaining a 40% reduction in SULmax by C1D15 were unlikely to obtain pCR (negative predictive value, 91%). CONCLUSION Although the primary objective was not met, early changes in SULmax predict response to PT in estrogen receptor–negative and HER2-positive breast cancer. Once optimized, this quantitative imaging strategy may facilitate tailoring of therapy in this setting.

Metastatic estrogen receptor α (ERα) positive breast cancer is presently incurable and most patients die within 7 years. From a medicinal chemistry program, we identified a novel small molecule that acts through ERα to kill breast cancer cells and often induces complete regression without recurrence of large, therapy-resistant primary breast tumors and of lung, bone, and liver metastases. We exploited our finding that estrogen-ERα activates an extranuclear tumor-protective, signaling pathway, the anticipatory unfolded protein response (UPR). We repurposed this tumor protective pathway by targeting it with the small molecule, ErSO. ErSO kills cancer cells by acting non-competitively through ERα to induce lethal hyperactivation of the anticipatory UPR (a-UPR), triggering rapid necrotic cell death. Using luciferase to image primary tumors and metastases containing lethal ERαD538G and ERαY537S mutations seen in metastatic breast cancer, oral and injected ErSO exhibited unprecedented antitumor activity. In mouse xenografts bearing large breast tumors, oral and injected ErSO induced complete regression (>115,000 fold mean regression) in about 45% of mice (18/39). Although durable response without treatment for 4-6 months was common, tumors that did recur remained fully sensitive to ErSO re-treatment. Consistent with the essential nature of the a-UPR pathway targeted by ErSO, in more than 100 tumor-bearing mice, we have never seen an ErSO-resistant tumor. In just 7 days, oral ErSO induced complete regression of most lung, bone, and liver metastases. ErSO is well-tolerated in mice and blood-brain-barrier penetrant. Injected ErSO induced profound regression of challenging brain tumors. On average, ErSO-treated tumors were >180-fold smaller than vehicle-treated tumors. Moreover, use of ErSO is not limited to breast cancer. With its unique mechanism of action through the a-UPR, ErSO eradicated orthotoptic ERα positive ovarian tumors that do not require estrogen for growth. These xenograft studies used human cancer cells in immune compromised mice and therefore did not exploit the known ability of inducers of necrotic cell death to activate immune cells and induce immunogenic cell death. Notably, medium from breast cancer cells killed by ErSO contained high levels of the established immune cell activators, HMGB1 and ATP, robustly activated mouse and human macrophages and increased macrophage migration. ErSO’s potent activity against advanced primary and metastatic ERα-positive breast cancers represents a paradigm shift in leveraging ERα for anticancer efficacy.

Breast carcinomas commonly carry mutations in the tumor suppressor p53, although therapeutic efforts to target mutant p53 have previously been unfruitful. Here we report a selective combination therapy strategy for treatment of p53 mutant cancers. Genomic data revealed that p53 mutant cancers exhibit high replication activity and express high levels of the Base-Excision Repair (BER) pathway, whereas experimental testing showed substantial dysregulation in BER. This defect rendered accumulation of DNA damage in p53 mutant cells upon treatment with deoxyuridine analogues. Notably, inhibition of poly (ADP-ribose) polymerase (PARP) greatly enhanced this response, whereas normal cells responded with activation of the p53-p21 axis and cell cycle arrest. Inactivation of either p53 or p21/CDKN1A conferred the p53 mutant phenotype. Preclinical animal studies demonstrated a greater anti-neoplastic efficacy of the drug combination (deoxyuridine analogue and PARP inhibitor) than either drug alone. This work illustrates a selective combination therapy strategy for p53 mutant cancers that will improve survival rates and outcomes for thousands of breast cancer patients., Zonneville et al. show that p53 mutant cancers express high levels of the Base Excision Repair (BER) pathway and that deoxyuridine analogues induce DNA damage in p53-mutant TNBC cells. They exploit this genetic liability for therapeutic purposes using a combination of fluorinated deoxyuridine analogues and PARP1 inhibitors to target the BER pathway, inducing cytotoxicity and suppressing tumor growth in mice.

The majority of breast cancer specific deaths in women with estrogen receptor positive (ER+) tumors occur due to metastases that are resistant to therapy. There is a critical need for novel therapeutic approaches to achieve tumor regression and/or maintain therapy responsiveness in metastatic ER+ tumors. The objective of this study was to elucidate the role of metabolic pathways that undermine therapy efficacy in ER+ breast cancers. Our previous studies identified Exportin 1 (XPO1), a nuclear export protein, as an important player in endocrine resistance progression and showed that combining selinexor (SEL), an FDA-approved XPO1 antagonist, synergized with endocrine agents and provided sustained tumor regression. In the current study, using a combination of transcriptomics, metabolomics and metabolic flux experiments, we identified certain mitochondrial pathways to be upregulated during endocrine resistance. When endocrine resistant cells were treated with single agents in media conditions that mimic a nutrient deprived tumor microenvironment, their glutamine dependence for continuation of mitochondrial respiration increased. The effect of glutamine was dependent on conversion of the glutamine to glutamate, and generation of NAD+. PGC1&alpha, a key regulator of metabolism, was the main driver of the rewired metabolic phenotype. Remodeling metabolic pathways to regenerate new vulnerabilities in endocrine resistant breast tumors is novel, and our findings reveal a critical role that ER&alpha, XPO1 crosstalk plays in reducing cancer recurrences. Combining SEL with current therapies used in clinical management of ER+ metastatic breast cancer shows promise for treating and keeping these cancers responsive to therapies in already metastasized patients.

PURPOSE The cancer research community is constantly evolving to better understand tumor biology, disease etiology, risk stratification, and pathways to novel treatments. Yet the clinical cancer genomics field has been hindered by redundant efforts to meaningfully collect and interpret disparate data types from multiple high-throughput modalities and integrate into clinical care processes. Bespoke data models, knowledgebases, and one-off customized resources for data analysis often lack adequate governance and quality control needed for these resources to be clinical grade. Many informatics efforts focused on genomic interpretation resources for neoplasms are underway to support data collection, deposition, curation, harmonization, integration, and analytics to support case review and treatment planning. METHODS In this review, we evaluate and summarize the landscape of available tools, resources, and evidence used in the evaluation of somatic and germline tumor variants within the context of molecular tumor boards. RESULTS Molecular tumor boards (MTBs) are collaborative efforts of multidisciplinary cancer experts equipped with genomic interpretation resources to aid in the delivery of accurate and timely clinical interpretations of complex genomic results for each patient, within an institution or hospital network. Virtual MTBs (VMTBs) provide an online forum for collaborative governance, provenance, and information sharing between experts outside a given hospital network with the potential to enhance MTB discussions. Knowledge sharing in VMTBs and communication with guideline-developing organizations can lead to progress evidenced by data harmonization across resources, crowd-sourced and expert-curated genomic assertions, and a more informed and explainable usage of artificial intelligence. CONCLUSION Advances in cancer genomics interpretation aid in better patient and disease classification, more streamlined identification of relevant literature, and a more thorough review of available treatments and predicted patient outcomes.

Metastatic estrogen receptor α (ERα) positive breast cancer is presently incurable and most patients die within 7 years. From a medicinal chemistry program, we identified a novel small molecule that acts through ERα to kill breast cancer cells and often induces complete regression without recurrence of large, therapy-resistant primary breast tumors and of lung, bone, and liver metastases. To target metastatic ERα positive breast cancer, we exploited our finding that estrogen-ERα activates an extranuclear tumor-protective, signaling pathway, the anticipatory unfolded protein response (UPR). We repurposed this tumor protective pathway by targeting it with the small molecule, ErSO. ErSO kills cancer cells by acting non-competitively through ERα to induce lethal hyperactivation of the anticipatory UPR, triggering rapid necrotic cell death. Using luciferase to image primary tumors and metastases containing lethal ERαD538G and ERαY537S mutations seen in metastatic breast cancer, oral and injected ErSO exhibited unprecedented antitumor activity. In mouse xenografts bearing large breast tumors, oral and injected ErSO induced complete regression (>115,000 fold mean regression) in about 45% of mice (18/39). Although durable response for 4-6 months without additional treatment was common, tumors that did recur remained fully sensitive to ErSO re-treatment. Consistent with the essential nature of the UPR pathway targeted by ErSO, in more than 100 tumor-bearing mice, we have never seen an ErSO-resistant tumor. In just 7 days, oral ErSO induced complete regression of most lung, bone, and liver metastases. ErSO is well-tolerated in mice and blood-brain-barrier penetrant. Injected ErSO induced profound regression of challenging brain tumors. On average, ErSO-treated tumors were >180-fold smaller than vehicle-treated tumors. These xenograft studies used human cancer cells in mice that lack a functional immune system and therefore did not exploit the known ability of inducers of necrotic cell death to activate immune cells and induce immunogenic cell death. Notably, medium from breast cancer cells killed by ErSO contained high levels of immune cell activators, robustly activated mouse and human macrophages and increased macrophage migration. Moreover, use of ErSO is not limited to breast cancer. ErSO rapidly kills ERα positive ovarian and endometrial cancer cells that do not require estrogen for growth. ErSO’s potent activity against advanced primary and metastatic ERα-positive breast cancers represents a paradigm shift in leveraging ERα for anticancer efficacy.

PURPOSE: Many human breast tumors become resistant to endocrine therapies and recur due to estrogen receptor (ERα) mutations that convey constitutive activity and a more aggressive phenotype. Here, we examined the effectiveness of a novel adamantyl antiestrogen, K-07, in suppressing the growth of breast cancer metastases containing the two most frequent ER-activating mutations, Y537S and D538G, and in extending survival in a preclinical metastatic cancer model. METHODS: MCF-7 breast cancer cells expressing luciferase and Y537S or D538G ER were injected into NOD-SCID-gamma female mice, and animals were treated orally with the antiestrogen K-07 or control vehicle. Comparisons were also made with the antiestrogen Fulvestrant. The development of metastases was monitored by in vivo bioluminescence imaging with phenotypic characterization of the metastases in liver and lung by immunohistochemical and biochemical analyses. RESULTS: These breast cancer cells established metastases in liver and lung, and K-07 treatment reduced the metastatic burden. Mice treated with K-07 also survived much longer. By day 70, only 28% of vehicle-treated mice with mutant ER metastases were alive, whereas all K-07-treated D538G and Y537S mice were still alive. K-07 also markedly reduced the level of metastatic cell ER and the expression of ER-regulated genes. CONCLUSION: The antiestrogen K-07 can reduce in vivo metastasis of breast cancers and extend host survival in this preclinical model driven by constitutively active mutant ERs, suggesting that this compound may be suitable for further translational examination of its efficacy in suppression of metastasis in breast cancers containing constitutively active mutant ERs.