Endocrine-therapy-resistant ESR1 variants revealed by genomic characterization of breast-cancer-derived xenografts

Omics Technologies Improving Breast Cancer Research and Diagnostics

Breast cancer (BC) has yielded approximately 2.26 million new cases and has caused nearly 685,000 deaths worldwide in the last two years, making it the most common diagnosed cancer type in the world. BC is an intricate ecosystem formed by both the tumor microenvironment and malignant cells, and its heterogeneity impacts the response to treatment. Biomedical research has entered the era of massive omics data thanks to the high-throughput sequencing revolution, quick progress and widespread adoption. These technologies-liquid biopsy, transcriptomics, epigenomics, proteomics, metabolomics, pharmaco-omics and artificial intelligence imaging-could help researchers and clinicians to better understand the formation and evolution of BC. This review focuses on the findings of recent multi-omics-based research that has been applied to BC research, with an introduction to every omics technique and their applications for the different BC phenotypes, biomarkers, target therapies, diagnosis, treatment and prognosis, to provide a comprehensive overview of the possibilities of BC research.

Combined kinome inhibition states are predictive of cancer cell line sensitivity to kinase inhibitor combination therapies

Protein kinases are a primary focus in targeted therapy development for cancer, owing to their role as regulators in nearly all areas of cell life. Kinase inhibitors are one of the fastest growing drug classes in oncology, but resistance acquisition to kinase-targeting monotherapies is inevitable due to the dynamic and interconnected nature of the kinome in response to perturbation. Recent strategies targeting the kinome with combination therapies have shown promise, such as the approval of Trametinib and Dabrafenib in advanced melanoma, but similar empirical combination design for less characterized pathways remains a challenge. Computational combination screening is an attractive alternative, allowing in-silico screening prior to in-vitro or in-vivo testing of drastically fewer leads, increasing efficiency and effectiveness of drug development pipelines. In this work, we generate combined kinome inhibition states of 40,000 kinase inhibitor combinations from kinobeads-based kinome profiling across 64 doses. We then integrated these with baseline transcriptomics from CCLE to build robust machine learning models to predict cell line sensitivity from NCI-ALMANAC across nine cancer types, with model accuracy R2 ~ 0.75-0.9 after feature selection using elastic-net regression. We further validated the model's ability to extend to real-world examples by using the best-performing breast cancer model to generate predictions for kinase inhibitor combination sensitivity and synergy in a PDX-derived TNBC cell line and saw reasonable global accuracy in our experimental validation (R2 ~ 0.7) as well as high accuracy in predicting synergy using four popular metrics (R2 ~ 0.9). Additionally, the model was able to predict a highly synergistic combination of Trametinib (MEK inhibitor) and Omipalisib (PI3K inhibitor) for TNBC treatment, which incidentally was recently in phase I clinical trials for TNBC. Our choice of tree-based models over networks for greater interpretability also allowed us to further interrogate which specific kinases were highly predictive of cell sensitivity in each cancer type, and we saw confirmatory strong predictive power in the inhibition of MAPK, CDK, and STK kinases. Overall, these results suggest that kinome inhibition states of kinase inhibitor combinations are strongly predictive of cell line responses and have great potential for integration into computational drug screening pipelines. This approach may facilitate the identification of effective kinase inhibitor combinations and accelerate the development of novel cancer therapies, ultimately improving patient outcomes.

The Efficacy of CB-103, a First-in-Class Transcriptional Notch Inhibitor, in Preclinical Models of Breast Cancer

BACKGROUND

The efficacy of CB-103 was evaluated in preclinical models of both ER+ and TNBC. Furthermore, the therapeutic efficacy of combining CB-103 with fulvestrant in ER+ BC and paclitaxel in TNBC was determined.

METHODS

CB-103 was screened in combination with a panel of anti-neoplastic drugs. We evaluated the anti-tumor activity of CB-103 with fulvestrant in ESR1-mutant (Y537S), endocrine-resistant BC xenografts. In the same model, we examined anti-CSC activity in mammosphere formation assays for CB-103 alone or in combination with fulvestrant or palbociclib. We also evaluated the effect of CB-103 plus paclitaxel on primary tumors and CSC in a GSI-resistant TNBC model HCC1187. Comparisons between groups were performed with a two-sided unpaired Students' t-test. A one-way or two-way ANOVA followed by Tukey's post-analysis was performed to analyze the in vivo efficacy study results.

THE RESULTS

CB-103 showed synergism with fulvestrant in ER+ cells and paclitaxel in TNBC cells. CB-103 combined with fulvestrant or paclitaxel potently inhibited mammosphere formation in both models. Combination of CB-103 and fulvestrant significantly reduced tumor volume in an ESR1-mutant, the endocrine-resistant BC model. In a GSI-resistant TNBC model, CB-103 plus paclitaxel significantly delayed tumor growth compared to paclitaxel alone.

CONCLUSION

our data indicate that CB-103 is an attractive candidate for clinical investigation in endocrine-resistant, recurrent breast cancers with biomarker-confirmed Notch activity in combination with SERDs and/or CDKis and in TNBCs with biomarker-confirmed Notch activity in combination with taxane-containing chemotherapy regimens.

Alternating 17β-Estradiol and Aromatase Inhibitor Therapies Is Efficacious in Postmenopausal Women with Advanced Endocrine-Resistant ER+ Breast Cancer

PURPOSE

Strategies to implement estrogen therapy for advanced estrogen receptor-positive (ER+) breast cancer are underdeveloped. Preclinical data suggest that cycling treatment with 17β-estradiol followed by estrogen deprivation can control tumor growth long-term.

PATIENTS AND METHODS

Postmenopausal women with advanced ER+/HER2- breast cancer with recurrence or progression on ≥ 1 antiestrogen or aromatase inhibitor (AI)-based therapy were eligible. Patients received 17β-estradiol (2 mg orally, three times a day) for 8 weeks followed by AI (physician's choice) for 16 weeks, alternating treatments on an 8-week/16-week schedule until disease progression. Patients then optionally received continuous single-agent treatment until a second instance of disease progression. Endpoints included 24-week clinical benefit and objective response per RECIST, and tumor genetic alterations.

RESULTS

Of 19 evaluable patients, clinical benefit rate was 42.1% [95% confidence interval (CI), 23.1%-63.9%] and objective response rate (ORR) was 15.8% (95% CI, 5.7%-37.9%). One patient experienced a grade 3 adverse event related to 17β-estradiol. Among patients who received continuous single-agent treatment until a second instance of disease progression, clinical benefit was observed in 5 of 12 (41.7%) cases. Tumor ER (ESR1) mutations were found by whole-exome profiling in 4 of 7 (57.1%) versus 2 of 9 (22.2%) patients who did versus did not experience clinical benefit from alternating 17β-estradiol/AI therapy. The only two patients to experience objective responses to initial 17β-estradiol had tumor ESR1 mutations.

CONCLUSIONS

Alternating 17β-estradiol/AI therapy may be a promising treatment for endocrine-refractory ER+ breast cancer, including following progression on CDK4/6 inhibitors or everolimus. Further study is warranted to determine whether the antitumor activity of 17β-estradiol differs according to ESR1 mutation status.

Evaluating steroid hormone receptor interactions using the live-cell NanoBRET proximity assay

Steroid hormone receptors play a crucial role in the development and characterization of the majority of breast cancers. These receptors canonically function through homodimerization, but physical interactions between different hormone receptors play a key role in cell functions as well. The estrogen receptor (ERα) and progesterone receptor (PR), for example, are involved in a complex set of interactions known as ERα/PR crosstalk. Here, we developed a valuable panel of nuclear receptor expression plasmids specifically for use in NanoBRET assays to assess nuclear receptor homo- and heterodimerization. We demonstrate the utility of this assay system by assessing ERα/PR physical interaction in the context of the endocrine therapy resistance-associated ERα Y537S mutation. We identify a role of the ERα Y537S mutation beyond that of constitutive activity of the receptor; it also increases ERα/PR crosstalk. In total, the NanoBRET assay provides a novel avenue for investigating hormone receptor crosstalk. Future research may use this system to assess the effects of other clinically significant hormone receptor mutations on hormone receptor crosstalk.

Revisiting Estrogen for the Treatment of Endocrine-Resistant Breast Cancer: Novel Therapeutic Approaches

Estrogen receptor (ER)-positive breast cancer is the most common subtype, representing 70-75% of all breast cancers. Several ER-targeted drugs commonly used include the selective estrogen receptor modulator (SERM), tamoxifen (TAM), aromatase inhibitors (AIs) and selective estrogen receptor degraders (SERDs). Through different mechanisms of action, all three drug classes reduce estrogen receptor signaling. Inevitably, resistance occurs, resulting in disease progression. The counterintuitive action of estrogen to inhibit ER-positive breast cancer was first observed over 80 years ago. High-dose estrogen and diethylstilbestrol (DES) were used to treat metastatic breast cancer accompanied by harsh side effects until the approval of TAM in the 1970s. After the development of TAM, randomized trials comparing TAM to estrogen found similar or slightly inferior efficacy but much better tolerability. After decades of research, it was learned that estrogen induces tumor regression only after a period of long-term estrogen deprivation, and the mechanisms of tumor regression were described. Despite the long history of breast cancer treatment with estrogen, this therapeutic modality is now revitalized due to the development of novel estrogenic compounds with improved side effect profiles, newly discovered predictive biomarkers, the development of non-estrogen small molecules and new combination therapeutic approaches.

Epigenetic reprogramming of cell cycle genes by ACK1 promotes breast cancer resistance to CDK4/6 inhibitor

Hormone receptor-positive, HER2-negative advanced breast cancers exhibit high sensitivity to CDK4/6 inhibitors such as palbociclib. However, most patients inevitably develop resistance, thus identification of new actionable therapeutic targets to overcome the recurrent disease is an urgent need. Immunohistochemical studies of tissue microarray revealed increased activation of non-receptor tyrosine kinase, ACK1 (also known as TNK2) in most of the breast cancer subtypes, independent of their hormone receptor status. Chromatin immunoprecipitation studies demonstrated that the nuclear target of activated ACK1, pY88-H4 epigenetic marks, were deposited at cell cycle genes, CCNB1, CCNB2 and CDC20, which in turn initiated their efficient transcription. Pharmacological inhibition of ACK1 using its inhibitor, (R)-9b dampened CCNB1, CCNB2 and CDC20 expression, caused G2/M arrest, culminating in regression of palbociclib-resistant breast tumor growth. Further, (R)-9b suppressed expression of CXCR4 receptor, which resulted in significant impairment of metastasis of breast cancer cells to lung. Overall, our pre-clinical data identifies activated ACK1 as an oncogene that epigenetically controls the cell cycle genes governing the G2/M transition in breast cancer cells. ACK1 inhibitor, (R)-9b could be a novel therapeutic option for the breast cancer patients that have developed resistance to CDK4/6 inhibitors.

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

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

Significance

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

Breast cancer brain metastasis: from etiology to state-of-the-art modeling

Currently, breast carcinoma is the most common form of malignancy and the main cause of cancer mortality in women worldwide. The metastasis of cancer cells from the primary tumor site to other organs in the body, notably the lungs, bones, brain, and liver, is what causes breast cancer to ultimately be fatal. Brain metastases occur in as many as 30% of patients with advanced breast cancer, and the 1-year survival rate of these patients is around 20%. Many researchers have focused on brain metastasis, but due to its complexities, many aspects of this process are still relatively unclear. To develop and test novel therapies for this fatal condition, pre-clinical models are required that can mimic the biological processes involved in breast cancer brain metastasis (BCBM). The application of many breakthroughs in the area of tissue engineering has resulted in the development of scaffold or matrix-based culture methods that more accurately imitate the original extracellular matrix (ECM) of metastatic tumors. Furthermore, specific cell lines are now being used to create three-dimensional (3D) cultures that can be used to model metastasis. These 3D cultures satisfy the requirement for in vitro methodologies that allow for a more accurate investigation of the molecular pathways as well as a more in-depth examination of the effects of the medication being tested. In this review, we talk about the latest advances in modeling BCBM using cell lines, animals, and tissue engineering methods.

Liver organoids: a promising three-dimensional model for insights and innovations in tumor progression and precision medicine of liver cancer

Primary liver cancer (PLC) is one type of cancer with high incidence rate and high mortality rate in the worldwide. Systemic therapy is the major treatment for PLC, including surgical resection, immunotherapy and targeted therapy. However, mainly due to the heterogeneity of tumors, responses to the above drug therapy differ from person to person, indicating the urgent needs for personalized treatment for PLC. Organoids are 3D models derived from adult liver tissues or pluripotent stem cells. Based on the ability to recapitulate the genetic and functional features of in vivo tissues, organoids have assisted biomedical research to make tremendous progress in understanding disease origin, progression and treatment strategies since their invention and application. In liver cancer research, liver organoids contribute greatly to reflecting the heterogeneity of liver cancer and restoring tumor microenvironment (TME) by co-organizing tumor vasculature and stromal components in vitro. Therefore, they provide a promising platform for further investigation into the biology of liver cancer, drug screening and precision medicine for PLC. In this review, we discuss the recent advances of liver organoids in liver cancer, in terms of generation methods, application in precision medicine and TME modeling.

Oral selective estrogen receptor degraders (SERDs): The new emperors in breast cancer clinical practice?

Endocrine therapy (ET) targeting estrogen receptor (ER) signaling is still the mainstay treatment option for early or advanced ER-positive breast cancer (BC) and may involve suppressing estrogen production by means of aromatase inhibitors or directly blocking the ER pathway through selective estrogen receptor modulators such as tamoxifen or selective estrogen receptor degraders such as fulvestrant. However, despite the availability of this armamentarium in clinical practice, de novo or acquired resistance to ET is the main cause of endocrine-based treatment failure leading to the progression of the BC. Recent advances in targeting, modulating, and degrading ERs have led to the development of new drugs capable of overcoming intrinsic or acquired ET resistance related to alterations in the ESR1 gene. The new oral selective estrogen receptor degraders, which are capable of reducing ER protein expression and blocking estrogen-dependent and -independent ER signaling, have a broader spectrum of activity against ESR1 mutations and seem to be a promising means of overcoming the failure of standard ET. The aim of this review is to summarize the development of oral selective estrogen receptor degraders, their current status, and their future perspectives.

Alteration in molecular properties during establishment and passaging of endometrial carcinoma patient-derived xenografts

Patient-derived xenograft (PDX) tumor models are known to maintain the genomic and phenotypic profiles, including the histopathological structures, of the parental tumors. On the other hand, unique enrichment of single-nucleotide variants or copy number aberrations has been reported in several types of tumors. However, an understanding of endometrial carcinoma PDXs is limited. The purpose of the present study was to clarify the presence or absence of the molecular properties of endometrial carcinomas in PDXs passaged up to eight times. Established PDXs of endometrioid carcinomas maintained their histopathological characteristics, but those of carcinosarcomas predominantly consisted of sarcomatous components when compared to the parental tumors. Alterations in the proportion of cells with positive/negative immunohistochemical staining for estrogen receptor, PTEN, PAX8, and PAX2 were observed, whereas the proportions of cells with AE1/AE3, TP53, ARID1A, PMS2, and MSH6 staining were unchanged. Variants of cancer-associated genes were compared between PDXs and parental tumors. Mutations in POLE and a frameshift deletion in BRCA1 were observed in the parental tumor tissue in each of the six cases, and additional genomic alterations, which were not apparently related to histopathological and immunohistochemical alterations, were found in the PDXs of these cases. The genomic and phenotypic alterations observed between endometrial carcinoma PDXs and parental tumors were partly associated with endometrial cancer-specific characteristics related to cellular differentiation and gene mutations.

The role of tumor microenvironment in drug resistance: emerging technologies to unravel breast cancer heterogeneity

Breast cancer is a highly heterogeneous disease, at both inter- and intra-tumor levels, and this heterogeneity is a crucial determinant of malignant progression and response to treatments. In addition to genetic diversity and plasticity of cancer cells, the tumor microenvironment contributes to tumor heterogeneity shaping the physical and biological surroundings of the tumor. The activity of certain types of immune, endothelial or mesenchymal cells in the microenvironment can change the effectiveness of cancer therapies via a plethora of different mechanisms. Therefore, deciphering the interactions between the distinct cell types, their spatial organization and their specific contribution to tumor growth and drug sensitivity is still a major challenge. Dissecting intra-tumor heterogeneity is currently an urgent need to better define breast cancer biology and to develop therapeutic strategies targeting the microenvironment as helpful tools for combined and personalized treatment. In this review, we analyze the mechanisms by which the tumor microenvironment affects the characteristics of tumor heterogeneity that ultimately result in drug resistance, and we outline state of the art preclinical models and emerging technologies that will be instrumental in unraveling the impact of the tumor microenvironment on resistance to therapies.

Toward Practical Integration of Omic and Imaging Data in Co-Clinical Trials

Co-clinical trials are the concurrent or sequential evaluation of therapeutics in both patients clinically and patient-derived xenografts (PDX) pre-clinically, in a manner designed to match the pharmacokinetics and pharmacodynamics of the agent(s) used. The primary goal is to determine the degree to which PDX cohort responses recapitulate patient cohort responses at the phenotypic and molecular levels, such that pre-clinical and clinical trials can inform one another. A major issue is how to manage, integrate, and analyze the abundance of data generated across both spatial and temporal scales, as well as across species. To address this issue, we are developing MIRACCL (molecular and imaging response analysis of co-clinical trials), a web-based analytical tool. For prototyping, we simulated data for a co-clinical trial in "triple-negative" breast cancer (TNBC) by pairing pre- (T0) and on-treatment (T1) magnetic resonance imaging (MRI) from the I-SPY2 trial, as well as PDX-based T0 and T1 MRI. Baseline (T0) and on-treatment (T1) RNA expression data were also simulated for TNBC and PDX. Image features derived from both datasets were cross-referenced to omic data to evaluate MIRACCL functionality for correlating and displaying MRI-based changes in tumor size, vascularity, and cellularity with changes in mRNA expression as a function of treatment.

Workflow enabling deepscale immunopeptidome, proteome, ubiquitylome, phosphoproteome, and acetylome analyses of sample-limited tissues

Serial multi-omic analysis of proteome, phosphoproteome, and acetylome provides insights into changes in protein expression, cell signaling, cross-talk and epigenetic pathways involved in disease pathology and treatment. However, ubiquitylome and HLA peptidome data collection used to understand protein degradation and antigen presentation have not together been serialized, and instead require separate samples for parallel processing using distinct protocols. Here we present MONTE, a highly sensitive multi-omic native tissue enrichment workflow, that enables serial, deep-scale analysis of HLA-I and HLA-II immunopeptidome, ubiquitylome, proteome, phosphoproteome, and acetylome from the same tissue sample. We demonstrate that the depth of coverage and quantitative precision of each 'ome is not compromised by serialization, and the addition of HLA immunopeptidomics enables the identification of peptides derived from cancer/testis antigens and patient specific neoantigens. We evaluate the technical feasibility of the MONTE workflow using a small cohort of patient lung adenocarcinoma tumors.

Estrogen therapy induces receptor-dependent DNA damage enhanced by PARP inhibition in ER+ breast cancer

Purpose

Clinical evidence indicates that treatment with estrogens elicits anti-cancer effects in ∼30% of patients with advanced endocrine-resistant estrogen receptor alpha (ER)-positive breast cancer. Despite the proven efficacy of estrogen therapy, its mechanism of action is unclear and this treatment remains under-utilized. Mechanistic understanding may offer strategies to enhance therapeutic efficacy.

Experimental Design

We performed genome-wide CRISPR/Cas9 screening and transcriptomic profiling in long-term estrogen-deprived (LTED) ER+ breast cancer cells to identify pathways required for therapeutic response to the estrogen 17β-estradiol (E2). We validated findings in cell lines, patient-derived xenografts (PDXs), and patient samples, and developed a novel combination treatment through testing in cell lines and PDX models.

Results

Cells treated with E2 exhibited replication-dependent markers of DNA damage and the DNA damage response prior to apoptosis. Such DNA damage was partially driven by the formation of DNA:RNA hybrids (R-loops). Pharmacological suppression of the DNA damage response via poly(ADP-ribose) polymerase (PARP) inhibition with olaparib enhanced E2-induced DNA damage. PARP inhibition synergized with E2 to suppress growth and prevent tumor recurrence in BRCA1/2 -mutant and BRCA1 /2-wild-type cell line and PDX models.

Conclusions

E2-induced ER activity drives DNA damage and growth inhibition in endocrine-resistant breast cancer cells. Inhibition of the DNA damage response using drugs such as PARP inhibitors can enhance therapeutic response to E2. These findings warrant clinical exploration of the combination of E2 with DNA damage response inhibitors in advanced ER+ breast cancer, and suggest that PARP inhibitors may synergize with therapeutics that exacerbate transcriptional stress.

TopPICR: A Companion R Package for Top-Down Proteomics Data Analysis

Top-down proteomics is the analysis of proteins in their intact form without proteolysis, thus preserving valuable information about post-translational modifications, isoforms, and proteolytic processing. However, it is still a developing field due to limitations in the instrumentation, difficulties with the interpretation of complex mass spectra, and a lack of well-established quantification approaches. TopPIC is one of the popular tools for proteoform identification. We extended its capabilities into label-free proteoform quantification by developing a companion R package (TopPICR). Key steps in the TopPICR pipeline include filtering identifications, inferring a minimal set of protein accessions explaining the observed sequences, aligning retention times, recalibrating measured masses, clustering features across data sets, and finally compiling feature intensities using the match-between-runs approach. The output of the pipeline is an MSnSet object which makes downstream data analysis seamlessly compatible with packages from the Bioconductor project. It also provides the capability for visualizing proteoforms within the context of the parent protein sequence. The functionality of TopPICR is demonstrated on top-down LC-MS/MS data sets of 10 human-in-mouse xenografts of luminal and basal breast tumor samples.

Modulating Glycolysis to Improve Cancer Therapy

Cancer cells undergo metabolic reprogramming and switch to a 'glycolysis-dominant' metabolic profile to promote their survival and meet their requirements for energy and macromolecules. This phenomenon, also known as the 'Warburg effect,' provides a survival advantage to the cancer cells and make the tumor environment more pro-cancerous. Additionally, the increased glycolytic dependence also promotes chemo/radio resistance. A similar switch to a glycolytic metabolic profile is also shown by the immune cells in the tumor microenvironment, inducing a competition between the cancer cells and the tumor-infiltrating cells over nutrients. Several recent studies have shown that targeting the enhanced glycolysis in cancer cells is a promising strategy to make them more susceptible to treatment with other conventional treatment modalities, including chemotherapy, radiotherapy, hormonal therapy, immunotherapy, and photodynamic therapy. Although several targeting strategies have been developed and several of them are in different stages of pre-clinical and clinical evaluation, there is still a lack of effective strategies to specifically target cancer cell glycolysis to improve treatment efficacy. Herein, we have reviewed our current understanding of the role of metabolic reprogramming in cancer cells and how targeting this phenomenon could be a potential strategy to improve the efficacy of conventional cancer therapy.

Predictors of success in establishing orthotopic patient-derived xenograft models of triple negative breast cancer

Patient-derived xenograft (PDX) models of breast cancer are an effective discovery platform and tool for preclinical pharmacologic testing and biomarker identification. We established orthotopic PDX models of triple negative breast cancer (TNBC) from the primary breast tumors of patients prior to and following neoadjuvant chemotherapy (NACT) while they were enrolled in the ARTEMIS trial (NCT02276443). Serial biopsies were obtained from patients prior to treatment (pre-NACT), from poorly responsive disease after four cycles of Adriamycin and cyclophosphamide (AC, mid-NACT), and in cases of AC-resistance, after a 3-month course of different experimental therapies and/or additional chemotherapy (post-NACT). Our study cohort includes a total of 269 fine needle aspirates (FNAs) from 217 women, generating a total of 62 PDX models (overall success-rate = 23%). Success of PDX engraftment was generally higher from those cancers that proved to be treatment-resistant, whether poorly responsive to AC as determined by ultrasound measurements mid-NACT (p = 0.063), RCB II/III status after NACT (p = 0.046), or metastatic relapse within 2 years of surgery (p = 0.008). TNBC molecular subtype determined from gene expression microarrays of pre-NACT tumors revealed no significant association with PDX engraftment rate (p = 0.877). Finally, we developed a statistical model predictive of PDX engraftment using percent Ki67 positive cells in the patient's diagnostic biopsy, positive lymph node status at diagnosis, and low volumetric reduction of the patient's tumor following AC treatment. This novel bank of 62 PDX models of TNBC provides a valuable resource for biomarker discovery and preclinical therapeutic trials aimed at improving neoadjuvant response rates for patients with TNBC.

Mechanisms of Endocrine Resistance in Hormone Receptor-Positive Breast Cancer

Hormone receptor-positive (HR+) breast cancer (BC) accounts for approximately 70% of all breast invasive tumors. Endocrine therapy (ET) represents the standard treatment for HR + BC. Most patients, however, eventually develop resistance to ET, which limits their effectiveness and poses a major challenge for the management of HR + BC. Several mechanisms that contribute to ET resistance have been described. One of the most common mechanisms is the upregulation of alternative signaling pathways that can bypass estrogen dependency, such as activation of the PI3K/Akt/mTOR as well as mitogen-activated protein kinase (MAPK) and the insulin-like growth factor 1 receptor (IGF-1R) pathways. Another common mechanism of endocrine resistance is the acquisition of activating mutations of ESR1, which encodes for the estrogen receptor, that lead to structural changes of the receptor, prevent the binding to anti-estrogen drugs and result in constitutive activation of the receptor, even in the absence of estrogens. Epigenetic changes, such as DNA methylation and histone modifications, can also contribute to ET resistance by altering the expression of genes that are involved in estrogen signaling. Understanding the mechanisms of resistance to ET is crucial for the development of new therapies that can overcome resistance and improve outcomes for patients with HR + BC.

Clinical Implications and Treatment Strategies for ESR1 Fusions in Hormone Receptor-Positive Metastatic Breast Cancer: A Case Series

In hormone receptor-positive metastatic breast cancer (HR+ MBC), endocrine resistance is commonly due to genetic alterations of ESR1, the gene encoding estrogen receptor alpha (ERα). While ESR1 point mutations (ESR1-MUT) cause acquired resistance to aromatase inhibition (AI) through constitutive activation, far less is known about the molecular functions and clinical consequences of ESR1 fusions (ESR1-FUS). This case series discusses 4 patients with HR+ MBC with ESR1-FUS in the context of the existing ESR1-FUS literature. We consider therapeutic strategies and raise the hypothesis that CDK4/6 inhibition (CDK4/6i) may be effective against ESR1-FUS with functional ligand-binding domain swaps. These cases highlight the importance of screening for ESR1-FUS in patients with HR+ MBC while continuing investigation of precision treatments for these genomic rearrangements.

Diptoindonesin G is a middle domain HSP90 modulator for cancer treatment

HSP90 inhibitors can target many oncoproteins simultaneously, but none have made it through clinical trials due to dose-limiting toxicity and induction of heat shock response, leading to clinical resistance. We identified diptoindonesin G (dip G) as an HSP90 modulator that can promote degradation of HSP90 clients by binding to the middle domain of HSP90 (K_d = 0.13 ± 0.02 μM) without inducing heat shock response. This is likely because dip G does not interfere with the HSP90-HSF1 interaction like N-terminal inhibitors, maintaining HSF1 in a transcriptionally silent state. We found that binding of dip G to HSP90 promotes degradation of HSP90 client protein estrogen receptor α (ER), a major oncogenic driver protein in most breast cancers. Mutations in the ER ligand-binding domain (LBD) are an established mechanism of endocrine resistance and decrease the binding affinity of mainstay endocrine therapies targeting ER, reducing their ability to promote ER degradation or transcriptionally silence ER. Because dip G binds to HSP90 and does not bind to the LBD of ER, unlike endocrine therapies, it is insensitive to ER LBD mutations that drive endocrine resistance. Additionally, we determined that dip G promoted degradation of WT and mutant ER with similar efficacy, downregulated ER- and mutant ER-regulated gene expression, and inhibited WT and mutant cell proliferation. Our data suggest that dip G is not only a molecular probe to study HSP90 biology and the HSP90 conformation cycle, but also a new therapeutic avenue for various cancers, particularly endocrine-resistant breast cancer harboring ER LBD mutations.

Molecular Mechanisms of Anti-Estrogen Therapy Resistance and Novel Targeted Therapies

Breast cancer (BC) is the most commonly diagnosed cancer in women, constituting one-third of all cancers in women, and it is the second leading cause of cancer-related deaths in the United States. Anti-estrogen therapies, such as selective estrogen receptor modulators, significantly improve survival in estrogen receptor-positive (ER+) BC patients, which represents about 70% of cases. However, about 60% of patients inevitably experience intrinsic or acquired resistance to anti-estrogen therapies, representing a major clinical problem that leads to relapse, metastasis, and patient deaths. The resistance mechanisms involve mutations of the direct targets of anti-estrogen therapies, compensatory survival pathways, as well as alterations in the expression of non-coding RNAs (e.g., microRNA) that regulate the activity of survival and signaling pathways. Although cyclin-dependent kinase 4/6 and phosphatidylinositol 3-kinase (PI3K)/AKT/mammalian target of rapamycin (mTOR) inhibitors have significantly improved survival, the efficacy of these therapies alone and in combination with anti-estrogen therapy for advanced ER+ BC, are not curative in advanced and metastatic disease. Therefore, understanding the molecular mechanisms causing treatment resistance is critical for developing highly effective therapies and improving patient survival. This review focuses on the key mechanisms that contribute to anti-estrogen therapy resistance and potential new treatment strategies alone and in combination with anti-estrogen drugs to improve the survival of BC patients.

Genome engineering for estrogen receptor mutations reveals differential responses to anti-estrogens and new prognostic gene signatures for breast cancer

Mutations in the estrogen receptor (ESR1) gene are common in ER-positive breast cancer patients who progress on endocrine therapies. Most mutations localise to just three residues at, or near, the C-terminal helix 12 of the hormone binding domain, at leucine-536, tyrosine-537 and aspartate-538. To investigate these mutations, we have used CRISPR-Cas9 mediated genome engineering to generate a comprehensive set of isogenic mutant breast cancer cell lines. Our results confirm that L536R, Y537C, Y537N, Y537S and D538G mutations confer estrogen-independent growth in breast cancer cells. Growth assays show mutation-specific reductions in sensitivities to drugs representing three classes of clinical anti-estrogens. These differential mutation- and drug-selectivity profiles have implications for treatment choices following clinical emergence of ER mutations. Our results further suggest that mutant expression levels may be determinants of the degree of resistance to some anti-estrogens. Differential gene expression analysis demonstrates up-regulation of estrogen-responsive genes, as expected, but also reveals that enrichment for interferon-regulated gene expression is a common feature of all mutations. Finally, a new gene signature developed from the gene expression profiles in ER mutant cells predicts clinical response in breast cancer patients with ER mutations.

Giredestrant reverses progesterone hypersensitivity driven by estrogen receptor mutations in breast cancer

ESR1 (estrogen receptor 1) hotspot mutations are major contributors to therapeutic resistance in estrogen receptor-positive (ER⁺) breast cancer. Such mutations confer estrogen independence to ERα, providing a selective advantage in the presence of estrogen-depleting aromatase inhibitors. In addition, ESR1 mutations reduce the potency of tamoxifen and fulvestrant, therapies that bind ERα directly. These limitations, together with additional liabilities, inspired the development of the next generation of ERα-targeted therapeutics, of which giredestrant is a high-potential candidate. Here, we generated Esr1 mutant-expressing mammary gland models and leveraged patient-derived xenografts (PDXs) to investigate the biological properties of the ESR1 mutations and their sensitivity to giredestrant in vivo. In the mouse mammary gland, Esr1 mutations promote hypersensitivity to progesterone, triggering pregnancy-like tissue remodeling and profoundly elevated proliferation. These effects were driven by an altered progesterone transcriptional response and underpinned by gained sites of ERα-PR (progesterone receptor) cobinding at the promoter regions of pro-proliferation genes. PDX experiments showed that the mutant ERα-PR proliferative program is also relevant in human cancer cells. Giredestrant suppressed the mutant ERα-PR proliferation in the mammary gland more so than the standard-of-care agents, tamoxifen and fulvestrant. Giredestrant was also efficacious against the progesterone-stimulated growth of ESR1 mutant PDX models. In addition, giredestrant demonstrated activity against a molecularly characterized ESR1 mutant tumor from a patient enrolled in a phase 1 clinical trial. Together, these data suggest that mutant ERα can collaborate with PR to drive protumorigenic proliferation but remain sensitive to inhibition by giredestrant.

Therapeutic Potential for Targeting Autophagy in ER+ Breast Cancer

Simple Summary

While ER+ breast cancer is generally considered to have a better prognosis than other breast cancer subtypes, relapse may nevertheless occur years after diagnosis and treatment. Despite initially responding to treatment, 30–40% of tumors acquire resistance to treatment that contributes to disease recurrence, metastasis, and ultimately, death. In the case of the individual estrogen antagonists or aromatase inhibitors, the autophagy induced by these agents is largely cytoprotective. However, whether autophagy inhibition will prove to be a useful strategy for improving outcomes for current combination therapeutic strategies awaits further studies.

Abstract

While endocrine therapy remains the mainstay of treatment for ER-positive, HER2-negative breast cancer, tumor progression and disease recurrence limit the utility of current standards of care. While existing therapies may allow for a prolonged progression-free survival, however, the growth-arrested (essentially dormant) state of residual tumor cells is not permanent and is frequently a precursor to disease relapse. Tumor cells that escape dormancy and regain proliferative capacity also tend to acquire resistance to further therapies. The cellular process of autophagy has been implicated in the adaptation, survival, and reactivation of dormant cells. Autophagy is a cellular stress mechanism induced to maintain cellular homeostasis. Tumor cells often undergo therapy-induced autophagy which, in most contexts, is cytoprotective in function; however, depending on how the autophagy is regulated, it can also be non-protective, cytostatic, or cytotoxic. In this review, we explore the literature on the relationship(s) between endocrine therapies and autophagy. Moreover, we address the different functional roles of autophagy in response to these treatments, exploring the possibility of targeting autophagy as an adjuvant therapeutic modality together with endocrine therapies.

Accelerating drug development in breast cancer: New frontiers for ER inhibition

The estrogen receptor (ER) is an important driver in the proliferation, tumorigenesis, and progression of breast cancers, and targeting ER signaling at different levels is a successful strategy in the control of hormone receptor positive (HR+) breast cancer. Endocrine therapy has been the treatment of choice for HR+ breast cancer in the early and advanced stages with multiple agents, including selective estrogen receptor modulators (SERMS), selective estrogen receptor degraders (SERDs), and aromatase inhibitors (AIs), which vary in their mechanisms of action and pharmacokinetics. Combination strategies also employ cyclin dependent kinase 4 and 6 and phosphatidylinositol 3-kinase to maximize the benefits of endocrine therapy. This paper reviews the clinical development of SERDs and other novel ER inhibitors, as well as combination strategies to overcome mechanisms of ER pathway escape. It also assesses the advantages of newer oral ER inhibitors with increased bioavailability, improved therapeutic index, better administration, and increased efficacy, as well as discussing future directions in the field.

Integrated DNA and RNA Sequencing Reveals Drivers of Endocrine Resistance in Estrogen Receptor-Positive Breast Cancer

PURPOSE

Endocrine therapy resistance (ETR) remains the greatest challenge in treating patients with hormone receptor-positive breast cancer. We set out to identify molecular mechanisms underlying ETR through in-depth genomic analysis of breast tumors.

EXPERIMENTAL DESIGN

We collected pre-treatment and sequential on-treatment tumor samples from 35 patients with estrogen receptor-positive breast cancer treated with neoadjuvant then adjuvant endocrine therapy; 3 had intrinsic resistance, 19 acquired resistance, and 13 remained sensitive. Response was determined by changes in tumor volume neoadjuvantly and by monitoring for adjuvant recurrence. Twelve patients received two or more lines of endocrine therapy, with subsequent treatment lines being initiated at the time of development of resistance to the previous endocrine therapy. DNA whole-exome sequencing and RNA sequencing were performed on all samples, totalling 169 unique specimens. DNA mutations, copy-number alterations, and gene expression data were analyzed through unsupervised and supervised analyses to identify molecular features related to ETR.

RESULTS

Mutations enriched in ETR included ESR1 and GATA3. The known ESR1 D538G variant conferring ETR was identified, as was a rarer E380Q variant that confers endocrine hypersensitivity. Resistant tumors which acquired resistance had distinct gene expression profiles compared with paired sensitive tumors, showing elevated pathways including ER, HER2, GATA3, AKT, RAS, and p63 signaling. Integrated analysis in individual patients highlighted the diversity of ETR mechanisms.

CONCLUSIONS

The mechanisms underlying ETR are multiple and characterized by diverse changes in both somatic genetic and transcriptomic profiles; to overcome resistance will require an individualized approach utilizing genomic and genetic biomarkers and drugs tailored to each patient.

Targeting ESR1 mutation-Induced transcriptional addiction in breast cancer with BET inhibition

Acquired mutations in the ligand-binding domain (LBD) of the gene encoding Estrogen Receptor alpha (ESR1) are a common mechanism of endocrine therapy resistance in metastatic ER-positive breast cancer patients. 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 1200 Federal Drug Administration (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 wild-type cells. Thus, BET inhibition has the potential to both prevent and overcome ESR1 mutant-induced endocrine therapy resistance in breast cancer.

ESR1 hotspot mutations in endometrial stromal sarcoma with high-grade transformation and endocrine treatment

High-grade endometrial stromal sarcomas (HGESSs) are more aggressive and have higher rates of resistance to endocrine therapy than low-grade endometrial stromal sarcomas (LGESSs). The pathogenesis of hormonal resistance in these lesions has yet to be defined. Here we sought to histologically and genetically characterize 3 LGESSs and their recurrences that underwent histologic high-grade transformation following endocrine therapy. For this, DNA from primary tumors and select subsequent recurrences were subject to massively parallel sequencing targeting 468 cancer-related genes. Somatic mutation analyses were performed using validated bioinformatics methods. In addition, RNA from each case was evaluated for the presence of gene fusions using targeted RNA-sequencing. All patients initially presented with LGESS, developed HGESS recurrences, and received at least 2 lines of hormonal suppressive therapy. Gene fusions classically described as associated with LGESS were identified in all 3 cases, including JAZF1-PHF1, EPC1-PHF1 and JAZF1-SUZ12 fusions for Cases 1, 2 and 3, respectively. Targeted sequencing analysis revealed that none of the primary LGESS, however the HGESS recurrences of Cases 1 and 3, and the LGESS and HGESS recurrences of Case 2 post endocrine treatment harbored ESR1 p.Y537S hotspot mutations. These ESR1 ligand-binding domain mutations have been found as a mechanism of acquired endocrine resistance in breast cancer. Also, a reduction in estrogen receptor (ER) expression was observed in recurrences. Our findings suggest that the ESR1 p.Y537S hotspot mutation in LGESS with histologic high-grade transformation may be associated with endocrine resistance in these lesions. Furthermore, our data suggest that genetic analyses may be performed in recurrent LGESS following hormonal therapy, development of high-grade morphology, and/or altered/diminished ER expression.

Zebrafish Patient-Derived Xenograft Model to Predict Treatment Outcomes of Colorectal Cancer Patients

The use of zebrafish embryos for personalized medicine has become increasingly popular. We present a co-clinical trial aiming to evaluate the use of zPDX (zebrafish Patient-Derived Xenografts) in predicting the response to chemotherapy regimens used for colorectal cancer patients. zPDXs are generated by xenografting tumor tissues in two days post-fertilization zebrafish embryos. zPDXs were exposed to chemotherapy regimens (5-FU, FOLFIRI, FOLFOX, FOLFOXIRI) for 48 h. We used a linear mixed effect model to evaluate the zPDX-specific response to treatments showing for 4/36 zPDXs (11%), a statistically significant reduction of tumor size compared to controls. We used the RECIST criteria to compare the outcome of each patient after chemotherapy with the objective response of its own zPDX model. Of the 36 patients enrolled, 8 metastatic colorectal cancer (mCRC), response rate after first-line therapy, and the zPDX chemosensitivity profile were available. Of eight mCRC patients, five achieved a partial response and three had a stable disease. In 6/8 (75%) we registered a concordance between the response of the patient and the outcomes reported in the corresponding zPDX. Our results provide evidence that the zPDX model can reflect the outcome in mCRC patients, opening a new frontier to personalized medicine.

YAP inhibits ERα and ER+ breast cancer growth by disrupting a TEAD-ERα signaling axis

Hippo signaling restricts tissue growth by inhibiting the transcriptional effector YAP. Here we uncover a role of Hippo signaling and a tumor suppressor function of YAP in estrogen receptor positive (ER⁺) breast cancer. We find that inhibition of Hippo/MST1/2 or activation of YAP blocks the ERα transcriptional program and ER⁺ breast cancer growth. Mechanistically, the Hippo pathway transcription factor TEAD physically interacts with ERα to increase its promoter/enhancer occupancy whereas YAP inhibits ERα/TEAD interaction, decreases ERα occupancy on its target promoters/enhancers, and promotes ERα degradation by the proteasome. Furthermore, YAP inhibits hormone-independent transcription of ERα gene (ESR1). Consistently, high levels of YAP correlate with good prognosis of ER⁺ breast cancer patients. Finally, we find that pharmacological inhibition of Hippo/MST1/2 impeded tumor growth driven by hormone therapy resistant ERα mutants, suggesting that targeting the Hippo-YAP-TEAD signaling axis could be a potential therapeutical strategy to overcome endocrine therapy resistance conferred by ERα mutants.

In Vivo Modeling of Human Breast Cancer Using Cell Line and Patient-Derived Xenografts

Historically, human breast cancer has been modeled largely in vitro using long-established cell lines primarily in two-dimensional culture, but also in three-dimensional cultures of varying cellular and molecular complexities. A subset of cell line models has also been used in vivo as cell line-derived xenografts (CDX). While outstanding for conducting detailed molecular analysis of regulatory mechanisms that may function in vivo, results of drug response studies using long-established cell lines have largely failed to translate clinically. In an attempt to address this shortcoming, many laboratories have succeeded in developing clinically annotated patient-derived xenograft (PDX) models of human cancers, including breast, in a variety of host systems. While immunocompromised mice are the predominant host, the immunocompromised rat and pig, zebrafish, as well as the chicken egg chorioallantoic membrane (CAM) have also emerged as potential host platforms to help address perceived shortcomings of immunocompromised mice. With any modeling platform, the two main issues to be resolved are criteria for "credentialing" the models as valid models to represent human cancer, and utility with respect to the ability to generate clinically relevant translational research data. Such data are beginning to emerge, particularly with the activities of PDX consortia such as the NCI PDXNet Program, EuroPDX, and the International Breast Cancer Consortium, as well as a host of pharmaceutical companies and contract research organizations (CRO). This review focuses primarily on these important aspects of PDX-related research, with a focus on breast cancer.

In vitro breast cancer models for studying mechanisms of resistance to endocrine therapy

The development of endocrine resistance is a common reason for the failure of endocrine therapies in hormone receptor-positive breast cancer. This review provides an overview of the different types of in vitro models that have been developed as tools for studying endocrine resistance. In vitro models include cell lines that have been rendered endocrine-resistant by ex vivo treatment; cell lines with de novo resistance mechanisms, including genetic alterations; three-dimensional (3D) spheroid, co-culture, and mammosphere techniques; and patient-derived organoid models. In each case, the key discoveries, different analysis strategies that are suitable, and strengths and weaknesses are discussed. Certain recently developed methodologies that can be used to further characterize the biological changes involved in endocrine resistance are then emphasized, along with a commentary on the types of research outcomes that using these techniques can support. Finally, a discussion anticipates how these recent developments will shape future trends in the field. We hope this overview will serve as a useful resource for investigators that are interested in understanding and testing hypotheses related to mechanisms of endocrine therapy resistance.

Covalent ERα Antagonist H3B-6545 Demonstrates Encouraging Preclinical Activity in Therapy-Resistant Breast Cancer

Nearly 30% of patients with relapsed breast cancer present activating mutations in estrogen receptor alpha (ERα) that confer partial resistance to existing endocrine-based therapies. We previously reported the development of H3B-5942, a covalent ERα antagonist that engages cysteine-530 (C530) to achieve potency against both wild-type (ERαWT) and mutant ERα (ERαMUT). Anticipating that the emergence of C530 mutations could promote resistance to H3B-5942, we applied structure-based drug design to improve the potency of the core scaffold to further enhance the antagonistic activity in addition to covalent engagement. This effort led to the development of the clinical candidate H3B-6545, a covalent antagonist that is potent against both  ERαWT/MUT, and maintains potency even in the context of ERα C530 mutations. H3B-6545 demonstrates significant activity and superiority over standard-of-care fulvestrant across a panel of ERαWT and ERαMUT palbociclib sensitive and resistant models. In summary, the compelling preclinical activity of H3B-6545 supports its further development for the potential treatment of endocrine therapy-resistant ERα+ breast cancer harboring wild-type or mutant ESR1, as demonstrated by the ongoing clinical trials (NCT03250676, NCT04568902, NCT04288089).

SUMMARY

H3B-6545 is an ERα covalent antagonist that exhibits encouraging preclinical activity against CDK4/6i naïve and resistant ERαWT and ERαMUT tumors.

Patient-derived models of brain metastases recapitulate human disseminated disease

Dissemination of cancer cells from primary tumors to the brain occurs in many cancer patients, increasing morbidity and death. There is an unmet medical need to develop translational platforms to evaluate therapeutic responses. Toward this goal, we established a library of 23 patient-derived xenografts (PDXs) of brain metastases (BMs) from eight distinct primary tumors. In vivo tumor formation correlates with patients’ poor survival. Mouse subcutaneous xenografts develop spontaneous metastases and intracardiac PDXs increase dissemination to the CNS, both models mimicking the dissemination pattern of the donor patient. We test the FDA-approved drugs buparlisib (pan-PI3K inhibitor) and everolimus (mTOR inhibitor) and show their efficacy in treating our models. Finally, we show by RNA sequencing that human BMs and their matched PDXs have similar transcriptional profiles. Overall, these models of BMs recapitulate the biology of human metastatic disease and can be valuable translational platforms for precision medicine.

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Established PDXs of brain metastasis from multiple cancers

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PDXs recapitulate the dissemination pattern of patient tumors

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Patient-derived models of brain metastases are valuable to test anticancer drugs

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Human brain metastases and their PDXs retain similar transcriptional profiles

Tumor organoids: applications in cancer modeling and potentials in precision medicine

Cancer is a top-ranked life-threatening disease with intratumor heterogeneity. Tumor heterogeneity is associated with metastasis, relapse, and therapy resistance. These factors contribute to treatment failure and an unfavorable prognosis. Personalized tumor models faithfully capturing the tumor heterogeneity of individual patients are urgently needed for precision medicine. Advances in stem cell culture have given rise to powerful organoid technology for the generation of in vitro three-dimensional tissues that have been shown to more accurately recapitulate the structures, specific functions, molecular characteristics, genomic alterations, expression profiles, and tumor microenvironment of primary tumors. Tumoroids in vitro serve as an important component of the pipeline for the discovery of potential therapeutic targets and the identification of novel compounds. In this review, we will summarize recent advances in tumoroid cultures as an excellent tool for accurate cancer modeling. Additionally, vascularization and immune microenvironment modeling based on organoid technology will also be described. Furthermore, we will summarize the great potential of tumor organoids in predicting the therapeutic response, investigating resistance-related mechanisms, optimizing treatment strategies, and exploring potential therapies. In addition, the bottlenecks and challenges of current tumoroids will also be discussed in this review.

Fusion-associated carcinomas of the breast: Diagnostic, prognostic, and therapeutic significance

Recurrent gene fusions comprise a class of viable genetic targets in solid tumors that have culminated several recent breakthrough cancer therapies. Their role in breast cancer, however, remains largely underappreciated due to the complexity of genomic rearrangements in breast malignancy. Just recently, we and others have identified several recurrent gene fusions in breast cancer with important clinical and biological implications. Examples of the most significant recurrent gene fusions to date include (1) ESR1::CCDC170 gene fusions in luminal B and endocrine-resistant breast cancer that exert oncogenic function via modulating the HER2/HER3/SRC Proto-Oncogene (SRC) complex, (2) ESR1 exon 6 fusions in metastatic disease that drive estrogen-independent estrogen-receptor transcriptional activity, (3) BCL2L14::ETV6 fusions in a more aggressive form of the triple-negative subtype that prime epithelial-mesenchymal transition and endow paclitaxel resistance, (4) the ETV6::NTRK3 fusion in secretory breast carcinoma that constitutively activates NTRK3 kinase, (5) the oncogenic MYB-NFIB fusion as a genetic driver underpinning adenoid cystic carcinomas of the breast that activates MYB Proto-Oncogene (MYB) pathway, and (6) the NOTCH/microtubule-associated serine-threonine (MAST) kinase gene fusions that activate NOTCH and MAST signaling. Importantly, these fusions are enriched in more aggressive and lethal breast cancer presentations and appear to confer therapeutic resistance. Thus, these gene fusions could be utilized as genetic biomarkers to identify patients who require more intensive treatment and surveillance. In addition, kinase fusions are currently being evaluated in breast cancer clinical trials and ongoing mechanistic investigation is exposing therapeutic vulnerabilities in patients with fusion-positive disease.

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

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

Real-Time Detection of ESR1 Mutation in Blood by Droplet Digital PCR in the PADA-1 Trial: Feasibility and Cross-Validation with NGS

The clinical actionability of circulating tumor DNA requires sensitive detection methods with a short turnaround time. In the PADA-1 phase 3 trial (NCT03079011), metastatic breast cancer patients treated with an aromatase inhibitor and palbociclib were screened every 2 months for activating ESR1 mutations in blood (bESR1_mut). We report the feasibility of the droplet digital polymerase chain reaction (ddPCR) and cross-validation with next-generation sequencing (NGS). bESR1_mut testing was centralized in two platforms using the same ddPCR assay. Results were reported as copies/mL of plasma and mutant allele frequency (MAF). We analyzed 200 positive ddPCR samples with an NGS assay (0.5-1% sensitivity). Overall, 12,552 blood samples were collected from 1017 patients from 83 centers. Among the 12,525 available samples with ddPCR results, 11,533 (92%) were bESR1_mut-negative. A total of 267 patients newly displayed bESR1_mut (26% patients/2% samples) with a median copy number of 14/mL (range: 4-1225) and a median MAF of 0.83% (0.11-35), 648 samples (20% patients/5% samples) displayed persistent bESR1_mut, and 77 (<1%) samples encountered a technical failure. The median turnaround time from blood drawing to result notification was 13 days (Q1:9; Q3:21 days). Among 200 ddPCR-positive samples tested, NGS detected bESR1_mut in 168 (84%); 25 of the 32 cases missed by NGS had low MAF and/or low coverage. In these 200 samples, bESR1_mut MAF by both techniques had an excellent intraclass correlation coefficient (ICC = 0.93; 95% CI [0.85; 0.97]). These results from a large-scale trial support the feasibility and accuracy of real-time bESR1_mut tracking by ddPCR, opening new opportunities for therapeutic interventions.

Preclinical Models of Brain Metastases in Breast Cancer

Breast cancer remains a leading cause of mortality among women worldwide. Brain metastases confer extremely poor prognosis due to a lack of understanding of their specific biology, unique physiologic and anatomic features of the brain, and limited treatment strategies. A major roadblock in advancing the treatment of breast cancer brain metastases (BCBM) is the scarcity of representative experimental preclinical models. Current models are predominantly based on the use of animal xenograft models with immortalized breast cancer cell lines that poorly capture the disease’s heterogeneity. Recent years have witnessed the development of patient-derived in vitro and in vivo breast cancer culturing systems that more closely recapitulate the biology from individual patients. These advances led to the development of modern patient-tissue-based experimental models for BCBM. The success of preclinical models is also based on the imaging technologies used to detect metastases. Advances in animal brain imaging, including cellular MRI and multimodality imaging, allow sensitive and specific detection of brain metastases and monitoring treatment responses. These imaging technologies, together with novel translational breast cancer models based on patient-derived cancer tissues, represent a unique opportunity to advance our understanding of brain metastases biology and develop novel treatment approaches. This review discusses the state-of-the-art knowledge in preclinical models of this disease.

Integrated Metabolic Profiling and Transcriptional Analysis Reveals Therapeutic Modalities for Targeting Rapidly Proliferating Breast Cancers

Metabolic dysregulation is a prominent feature in breast cancer, but it remains poorly characterized in patient tumors. In this study, untargeted metabolomics analysis of triple-negative breast cancer (TNBC) and patient with estrogen receptor (ER)-positive breast cancer samples, as well as TNBC patient-derived xenografts (PDX), revealed two major metabolic groups independent of breast cancer histologic subtypes: a "Nucleotide/Carbohydrate-Enriched" group and a "Lipid/Fatty Acid-Enriched" group. Cell lines grown in vivo more faithfully recapitulated the metabolic profiles of patient tumors compared with those grown in vitro. Integrated metabolic and gene expression analyses identified genes that strongly correlate with metabolic dysregulation and predict patient prognosis. As a proof of principle, targeting Nucleotide/Carbohydrate-Enriched TNBC cell lines or PDX xenografts with a pyrimidine biosynthesis inhibitor or a glutaminase inhibitor led to therapeutic efficacy. In multiple in vivo models of TNBC, treatment with the pyrimidine biosynthesis inhibitor conferred better therapeutic outcomes than chemotherapeutic agents. This study provides a metabolic stratification of breast tumor samples that can guide the selection of effective therapeutic strategies targeting breast cancer subsets. In addition, we have developed a public, interactive data visualization portal (http://brcametab.org) based on the data generated from this study to facilitate future research.

SIGNIFICANCE

A multiomics strategy that integrates metabolic and gene expression profiling in patient tumor samples and animal models identifies effective pharmacologic approaches to target rapidly proliferating breast tumor subtypes.

The prognostic and predictive value of ESR1 fusion gene transcripts in primary breast cancer

Background

In breast cancer (BC), recurrent fusion genes of estrogen receptor alpha (ESR1) and AKAP12, ARMT1 and CCDC170 have been reported. In these gene fusions the ligand binding domain of ESR1 has been replaced by the transactivation domain of the fusion partner constitutively activating the receptor. As a result, these gene fusions can drive tumor growth hormone independently as been shown in preclinical models, but the clinical value of these fusions have not been reported. Here, we studied the prognostic and predictive value of different frequently reported ESR1 fusion transcripts in primary BC.

Methods

We evaluated 732 patients with primary BC (131 ESR1-negative and 601 ESR1-positive cases), including two ER-positive BC patient cohorts: one cohort of 322 patients with advanced disease who received first-line endocrine therapy (ET) (predictive cohort), and a second cohort of 279 patients with lymph node negative disease (LNN) who received no adjuvant systemic treatment (prognostic cohort). Fusion gene transcript levels were measured by reverse transcriptase quantitative PCR. The presence of the different fusion transcripts was associated, in uni- and multivariable Cox regression analysis taking along current clinico-pathological characteristics, to progression free survival (PFS) during first-line endocrine therapy in the predictive cohort, and disease- free survival (DFS) and overall survival (OS) in the prognostic cohort.

Results

The ESR1-CCDC170 fusion transcript was present in 27.6% of the ESR1-positive BC subjects and in 2.3% of the ESR1-negative cases. In the predictive cohort, none of the fusion transcripts were associated with response to first-line ET. In the prognostic cohort, the median DFS and OS were respectively 37 and 93 months for patients with an ESR1-CCDC170 exon 8 gene fusion transcript and respectively 91 and 212 months for patients without this fusion transcript. In a multivariable analysis, this ESR1-CCDC170 fusion transcript was an independent prognostic factor for DFS (HR) (95% confidence interval (CI): 1.8 (1.2–2.8), P = 0.005) and OS (HR (95% CI: 1.7 (1.1–2.7), P = 0.023).

Conclusions

Our study shows that in primary BC only ESR1-CCDC170 exon 8 gene fusion transcript carries prognostic value. None of the ESR1 fusion transcripts, which are considered to have constitutive ER activity, was predictive for outcome in BC with advanced disease treated with endocrine treatment.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12885-022-09265-1.

ESR1 mutations and therapeutic resistance in metastatic breast cancer: progress and remaining challenges

Breast cancer accounts for 25% of the cancers in women worldwide. The most common subtype of breast cancer diagnosed is hormone receptor positive, which expresses the oestrogen receptor (ER). Targeting of the ER with endocrine therapy (ET) is the current standard of care for ER-positive (ER+) breast cancer, reducing the mortality by up to 40%. Resistance to ET, however, remains a major issue for ER + breast cancer, leading to recurrence and metastasis. One major driver of ET resistance is mutations in the ER gene (ESR1) leading to constitutive transcriptional activity and reduced ET sensitivity. These mutations are particularly detrimental in metastatic breast cancer (MBC) as they are present in as high as 36% of the patients. This review summarises the pre-clinical characterisation of ESR1 mutations and their association with clinical outcomes in MBC and primary disease. The clinically approved and investigational therapeutic options for ESR1 mutant breast cancer and the current clinical trials evaluating ESR1 mutations and ET resistance are also discussed. Finally, this review addresses pre-clinical models and multi-'omics' approaches for developing the next generation of therapeutics for ESR1 mutant and ET-resistant breast cancer.

A human breast cancer-derived xenograft and organoid platform for drug discovery and precision oncology

Models that recapitulate the complexity of human tumors are urgently needed to develop more effective cancer therapies. We report a bank of human patient-derived xenografts (PDXs) and matched organoid cultures from tumors that represent the greatest unmet need: endocrine-resistant, treatment-refractory and metastatic breast cancers. We leverage matched PDXs and PDX-derived organoids (PDxO) for drug screening that is feasible and cost-effective with in vivo validation. Moreover, we demonstrate the feasibility of using these models for precision oncology in real time with clinical care in a case of triple-negative breast cancer (TNBC) with early metastatic recurrence. Our results uncovered a Food and Drug Administration (FDA)-approved drug with high efficacy against the models. Treatment with this therapy resulted in a complete response for the individual and a progression-free survival (PFS) period more than three times longer than their previous therapies. This work provides valuable methods and resources for functional precision medicine and drug development for human breast cancer.

Role of the Mediator Complex and MicroRNAs in Breast Cancer Etiology

Transcriptional coactivators play a key role in RNA polymerase II transcription and gene regulation. One of the most important transcriptional coactivators is the Mediator (MED) complex, which is an evolutionary conserved large multiprotein complex. MED transduces the signal between DNA-bound transcriptional activators (gene-specific transcription factors) to the RNA polymerase II transcription machinery to activate transcription. It is known that MED plays an essential role in ER-mediated gene expression mainly through the MED1 subunit, since estrogen receptor (ER) can interact with MED1 by specific protein–protein interactions; therefore, MED1 plays a fundamental role in ER-positive breast cancer (BC) etiology. Additionally, other MED subunits also play a role in BC etiology. On the other hand, microRNAs (miRNAs) are a family of small non-coding RNAs, which can regulate gene expression at the post-transcriptional level by binding in a sequence-specific fashion at the 3′ UTR of the messenger RNA. The miRNAs are also important factors that influence oncogenic signaling in BC by acting as both tumor suppressors and oncogenes. Moreover, miRNAs are involved in endocrine therapy resistance of BC, specifically to tamoxifen, a drug that is used to target ER signaling. In metazoans, very little is known about the transcriptional regulation of miRNA by the MED complex and less about the transcriptional regulation of miRNAs involved in BC initiation and progression. Recently, it has been shown that MED1 is able to regulate the transcription of the ER-dependent miR-191/425 cluster promoting BC cell proliferation and migration. In this review, we will discuss the role of MED1 transcriptional coactivator in the etiology of BC and in endocrine therapy-resistance of BC and also the contribution of other MED subunits to BC development, progression and metastasis. Lastly, we identified miRNAs that potentially can regulate the expression of MED subunits.

TIMP-2 regulates 5-Fu resistance via the ERK/MAPK signaling pathway in colorectal cancer

5-Fluorouracil (5-Fu) is the first-line chemotherapeutic option for colorectal cancer. However, its efficacy is inhibited by drug resistance. Cytokines play an important role in tumor drug resistance, even though their mechanisms are largely unknown. Using a cytokine array, we established that tissue inhibitor metalloproteinase 2 (TIMP-2) is highly expressed in 5-Fu resistant colorectal cancer patients. Analysis of samples from 84 patients showed that elevated TIMP-2 expression levels in colorectal patients were correlated with poor prognostic outcomes. In a 5-Fu-resistant patient-derived xenograft (PDX) model, TIMP-2 was also found to be highly expressed. We established an autocrine mechanism through which elevated TIMP-2 protein levels sustained colorectal cancer cell resistance to 5-Fu by constitutively activating the ERK/MAPK signaling pathway. Inhibition of TIMP-2 using an anti-TIMP-2 antibody or ERK/MAPK inhibition by U0126 suppressed TIMP-2 mediated 5-Fu-resistance in CRC patients. In conclusion, a novel TIMP-2-ERK/MAPK mediated 5-Fu resistance mechanism is involved in colorectal cancer. Therefore, targeting TIMP-2 or ERK/MAPK may provide a new strategy to overcome 5-Fu resistance in colorectal cancer chemotherapy.

Regulation of Bcl-2 Family Proteins in Estrogen Receptor-Positive Breast Cancer and Their Implications in Endocrine Therapy

Estrogen receptor (ER)-positive breast cancer accounts for around two-thirds of breast cancer occurrences, with endocrine therapy serving as first-line therapy in most cases. Targeting estrogen signaling pathways, which play a central role in regulating ER+ breast cell proliferation and survival, has proven to improve patient outcomes. However, despite the undeniable advantages of endocrine therapy, a subset of breast cancer patients develop acquired or intrinsic resistance to ER-targeting agents, limiting their efficacy. The activation of downstream ER signaling pathways upregulates pro-survival mechanisms that have been shown to influence the response of cells to endocrine therapy. The Bcl-2 family proteins play a central role in cell death regulation and have been shown to contribute to endocrine therapy resistance, supporting the survival of breast cancer cells and enhancing cell death evasion. Due to the overexpression of anti-apoptotic Bcl-2 proteins in ER-positive breast cancer, the role of these proteins as potential targets in hormone-responsive breast cancer is growing in interest. In particular, recent advances in the development of BH3 mimetics have enabled their evaluation in preclinical studies with ER+ breast cancer models, and BH3 mimetics have entered early ER+ breast cancer clinical trials. This review summarizes the molecular mechanisms underlying the regulation of Bcl-2 family proteins in ER+ breast cancer. Furthermore, an overview of recent advances in research regarding the efficacy of BH3 mimetics in ER+ breast cancer has been provided.

ESR1 fusions and therapeutic resistance in metastatic breast cancer

Breast cancer is the most frequent female malignant tumor, and the leading cause of cancer death in women worldwide. The most common subtype of breast cancer is hormone receptor positive that expresses the estrogen receptor (ER). Targeting ER with endocrine therapy (ET) is the current standard of care for ER positive (ER+) breast cancer, reducing mortality by up to 40% in early- stage disease. However, resistance to ET represents a major clinical challenge for ER+ breast cancer patients leading to disease recurrence or progression of metastatic disease. Salient drivers of ET resistance are missense mutations in the ER gene (ESR1) leading to constitutive transcriptional activity and reduced ET sensitivity. These mutations are particularly prominent and deleterious in metastatic breast cancer (MBC). In addition to activating ESR1 point mutations, emerging evidence imposes that chromosomal translocation involving the ESR1 gene can also drive ET resistance through the formation of chimeric transcription factors with constitutive transcriptional activity. Although these ESR1 gene fusions are relatively rare, they are enriched in ET resistant metastatic disease. This review discusses the characteristics of ER fusion proteins and their association with clinical outcomes in more aggressive and metastatic breast cancer. The structure and classification of ER fusion proteins based on function and clinical significance are also addressed. Finally, this review summarizes the metastatic phenotypes exhibited by the ER fusion proteins and their role in intrinsic ET resistance.