Type I IFNs promote cancer cell stemness by triggering the epigenetic regulator KDM1B.

Cancer stem cells (CSCs) are a subpopulation of cancer cells endowed with high tumorigenic, chemoresistant and metastatic potential. Nongenetic mechanisms of acquired resistance are increasingly being discovered, but molecular insights into the evolutionary process of CSCs are limited. Here, we show that type I interferons (IFNs-I) function as molecular hubs of resistance during immunogenic chemotherapy, triggering the epigenetic regulator demethylase 1B (KDM1B) to promote an adaptive, yet reversible, transcriptional rewiring of cancer cells towards stemness and immune escape. Accordingly, KDM1B inhibition prevents the appearance of IFN-I-induced CSCs, both in vitro and in vivo. Notably, IFN-I-induced CSCs are heterogeneous in terms of multidrug resistance, plasticity, invasiveness and immunogenicity. Moreover, in breast cancer (BC) patients receiving anthracycline-based chemotherapy, KDM1B positively correlated with CSC signatures. Our study identifies an IFN-I → KDM1B axis as a potent engine of cancer cell reprogramming, supporting KDM1B targeting as an attractive adjunctive to immunogenic drugs to prevent CSC expansion and increase the long-term benefit of therapy.

Herceptin: A First Assault on Oncogenes that Launched a Revolution.

This year's Lasker Clinical Research Award honors H. Michael Shepard, Dennis J. Slamon, and Axel Ullrich for their invention of Herceptin, the first monoclonal antibody that blocks a cancer-causing protein, and for its development as a life-saving therapy for women with breast cancer.

Dynamic Risk Profiling Using Serial Tumor Biomarkers for Personalized Outcome Prediction.

Accurate prediction of long-term outcomes remains a challenge in the care of cancer patients. Due to the difficulty of serial tumor sampling, previous prediction tools have focused on pretreatment factors. However, emerging non-invasive diagnostics have increased opportunities for serial tumor assessments. We describe the Continuous Individualized Risk Index (CIRI), a method to dynamically determine outcome probabilities for individual patients utilizing risk predictors acquired over time. Similar to "win probability" models in other fields, CIRI provides a real-time probability by integrating risk assessments throughout a patient's course. Applying CIRI to patients with diffuse large B cell lymphoma, we demonstrate improved outcome prediction compared to conventional risk models. We demonstrate CIRI's broader utility in analogous models of chronic lymphocytic leukemia and breast adenocarcinoma and perform a proof-of-concept analysis demonstrating how CIRI could be used to develop predictive biomarkers for therapy selection. We envision that dynamic risk assessment will facilitate personalized medicine and enable innovative therapeutic paradigms.

Therapeutic Ligands Antagonize Estrogen Receptor Function by Impairing Its Mobility.

Estrogen receptor-positive (ER+) breast cancers frequently remain dependent on ER signaling even after acquiring resistance to endocrine agents, prompting the development of optimized ER antagonists. Fulvestrant is unique among approved ER therapeutics due to its capacity for full ER antagonism, thought to be achieved through ER degradation. The clinical potential of fulvestrant is limited by poor physicochemical features, spurring attempts to generate ER degraders with improved drug-like properties. We show that optimization of ER degradation does not guarantee full ER antagonism in breast cancer cells; ER "degraders" exhibit a spectrum of transcriptional activities and anti-proliferative potential. Mechanistically, we find that fulvestrant-like antagonists suppress ER transcriptional activity not by ER elimination, but by markedly slowing the intra-nuclear mobility of ER. Increased ER turnover occurs as a consequence of ER immobilization. These findings provide proof-of-concept that small molecule perturbation of transcription factor mobility may enable therapeutic targeting of this challenging target class.

Functional Genomic Landscape of Human Breast Cancer Drivers, Vulnerabilities, and Resistance.

Large-scale genomic studies have identified multiple somatic aberrations in breast cancer, including copy number alterations and point mutations. Still, identifying causal variants and emergent vulnerabilities that arise as a consequence of genetic alterations remain major challenges. We performed whole-genome small hairpin RNA (shRNA) "dropout screens" on 77 breast cancer cell lines. Using a hierarchical linear regression algorithm to score our screen results and integrate them with accompanying detailed genetic and proteomic information, we identify vulnerabilities in breast cancer, including candidate "drivers," and reveal general functional genomic properties of cancer cells. Comparisons of gene essentiality with drug sensitivity data suggest potential resistance mechanisms, effects of existing anti-cancer drugs, and opportunities for combination therapy. Finally, we demonstrate the utility of this large dataset by identifying BRD4 as a potential target in luminal breast cancer and PIK3CA mutations as a resistance determinant for BET-inhibitors.

A Biobank of Breast Cancer Explants with Preserved Intra-tumor Heterogeneity to Screen Anticancer Compounds.

The inter- and intra-tumor heterogeneity of breast cancer needs to be adequately captured in pre-clinical models. We have created a large collection of breast cancer patient-derived tumor xenografts (PDTXs), in which the morphological and molecular characteristics of the originating tumor are preserved through passaging in the mouse. An integrated platform combining in vivo maintenance of these PDTXs along with short-term cultures of PDTX-derived tumor cells (PDTCs) was optimized. Remarkably, the intra-tumor genomic clonal architecture present in the originating breast cancers was mostly preserved upon serial passaging in xenografts and in short-term cultured PDTCs. We assessed drug responses in PDTCs on a high-throughput platform and validated several ex vivo responses in vivo. The biobank represents a powerful resource for pre-clinical breast cancer pharmacogenomic studies (http://caldaslab.cruk.cam.ac.uk/bcape), including identification of biomarkers of response or resistance.

Systemic therapy for hormone receptor-positive/human epidermal growth factor receptor 2-negative early stage and metastatic breast cancer.

Hormone receptor (HR)-positive and human epidermal growth factor receptor 2 (HER2)-negative breast cancer is defined by the presence of the estrogen receptor and/or the progesterone receptor and the absence of HER2 gene amplification. HR-positive/HER2-negative breast cancer accounts for 65%-70% of all breast cancers, and incidence increases with increasing age. Treatment varies by stage, and endocrine therapy is the mainstay of treatment in both early stage and late-stage disease. Combinations with cyclin-dependent kinase 4/6 inhibitors have reduced distant recurrence in the early stage setting and improved overall survival in the metastatic setting. Chemotherapy is used based on stage and tumor biology in the early stage setting and after endocrine resistance for advanced disease. New therapies, including novel endocrine agents and antibody-drug conjugates, are now changing the treatment landscape. With the availability of new treatment options, it is important to define the optimal sequence of treatment to maximize clinical benefit while minimizing toxicity. In this review, the authors first discuss the pathologic and molecular features of HR-positive/HER2-negative breast cancer and mechanisms of endocrine resistance. Then, they discuss current and emerging therapies for both early stage and metastatic HR-positive/HER2-negative breast cancer, including treatment algorithms based on current data.

Multimodal regulatory elements within a hormone-specific super enhancer control a heterogeneous transcriptional response.

The hormone-stimulated glucocorticoid receptor (GR) modulates transcription by interacting with thousands of enhancers and GR binding sites (GBSs) throughout the genome. Here, we examined the effects of GR binding on enhancer dynamics and investigated the contributions of individual GBSs to the hormone response. Hormone treatment resulted in genome-wide reorganization of the enhancer landscape in breast cancer cells. Upstream of the DDIT4 oncogene, GR bound to four sites constituting a hormone-dependent super enhancer. Three GBSs were required as hormone-dependent enhancers that differentially promoted histone acetylation, transcription frequency, and burst size. Conversely, the fourth site suppressed transcription and hormone treatment alleviated this suppression. GR binding within the super enhancer promoted a loop-switching mechanism that allowed interaction of the DDIT4 TSS with the active GBSs. The unique functions of each GR binding site contribute to hormone-induced transcriptional heterogeneity and demonstrate the potential for targeted modulation of oncogene expression.

Predicting cancer-specific vulnerability via data-driven detection of synthetic lethality.

Synthetic lethality occurs when the inhibition of two genes is lethal while the inhibition of each single gene is not. It can be harnessed to selectively treat cancer by identifying inactive genes in a given cancer and targeting their synthetic lethal (SL) partners. We present a data-driven computational pipeline for the genome-wide identification of SL interactions in cancer by analyzing large volumes of cancer genomic data. First, we show that the approach successfully captures known SL partners of tumor suppressors and oncogenes. We then validate SL predictions obtained for the tumor suppressor VHL. Next, we construct a genome-wide network of SL interactions in cancer and demonstrate its value in predicting gene essentiality and clinical prognosis. Finally, we identify synthetic lethality arising from gene overactivation and use it to predict drug efficacy. These results form a computational basis for exploiting synthetic lethality to uncover cancer-specific susceptibilities.

Exosome transfer from stromal to breast cancer cells regulates therapy resistance pathways.

Stromal communication with cancer cells can influence treatment response. We show that stromal and breast cancer (BrCa) cells utilize paracrine and juxtacrine signaling to drive chemotherapy and radiation resistance. Upon heterotypic interaction, exosomes are transferred from stromal to BrCa cells. RNA within exosomes, which are largely noncoding transcripts and transposable elements, stimulates the pattern recognition receptor RIG-I to activate STAT1-dependent antiviral signaling. In parallel, stromal cells also activate NOTCH3 on BrCa cells. The paracrine antiviral and juxtacrine NOTCH3 pathways converge as STAT1 facilitates transcriptional responses to NOTCH3 and expands therapy-resistant tumor-initiating cells. Primary human and/or mouse BrCa analysis support the role of antiviral/NOTCH3 pathways in NOTCH signaling and stroma-mediated resistance, which is abrogated by combination therapy with gamma secretase inhibitors. Thus, stromal cells orchestrate an intricate crosstalk with BrCa cells by utilizing exosomes to instigate antiviral signaling. This expands BrCa subpopulations adept at resisting therapy and reinitiating tumor growth.

NR4A1 regulates expression of immediate early genes, suppressing replication stress in cancer.

Deregulation of oncogenic signals in cancer triggers replication stress. Immediate early genes (IEGs) are rapidly and transiently expressed following stressful signals, contributing to an integrated response. Here, we find that the orphan nuclear receptor NR4A1 localizes across the gene body and 3' UTR of IEGs, where it inhibits transcriptional elongation by RNA Pol II, generating R-loops and accessible chromatin domains. Acute replication stress causes immediate dissociation of NR4A1 and a burst of transcriptionally poised IEG expression. Ectopic expression of NR4A1 enhances tumorigenesis by breast cancer cells, while its deletion leads to massive chromosomal instability and proliferative failure, driven by deregulated expression of its IEG target, FOS. Approximately half of breast and other primary cancers exhibit accessible chromatin domains at IEG gene bodies, consistent with this stress-regulatory pathway. Cancers that have retained this mechanism in adapting to oncogenic replication stress may be dependent on NR4A1 for their proliferation.

In Vivo Evidence for Serine Biosynthesis-Defined Sensitivity of Lung Metastasis, but Not of Primary Breast Tumors, to mTORC1 Inhibition.

In tumors, nutrient availability and metabolism are known to be important modulators of growth signaling. However, it remains elusive whether cancer cells that are growing out in the metastatic niche rely on the same nutrients and metabolic pathways to activate growth signaling as cancer cells within the primary tumor. We discovered that breast-cancer-derived lung metastases, but not the corresponding primary breast tumors, use the serine biosynthesis pathway to support mTORC1 growth signaling. Mechanistically, pyruvate uptake through Mct2 supported mTORC1 signaling by fueling serine biosynthesis-derived α-ketoglutarate production in breast-cancer-derived lung metastases. Consequently, expression of the serine biosynthesis enzyme PHGDH was required for sensitivity to the mTORC1 inhibitor rapamycin in breast-cancer-derived lung tumors, but not in primary breast tumors. In summary, we provide in vivo evidence that the metabolic and nutrient requirements to activate growth signaling differ between the lung metastatic niche and the primary breast cancer site.

Depletion of a putatively druggable class of phosphatidylinositol kinases inhibits growth of p53-null tumors.

Here, we show that a subset of breast cancers express high levels of the type 2 phosphatidylinositol-5-phosphate 4-kinases α and/or ß (PI5P4Kα and ß) and provide evidence that these kinases are essential for growth in the absence of p53. Knocking down PI5P4Kα and ß in a breast cancer cell line bearing an amplification of the gene encoding PI5P4K ß and deficient for p53 impaired growth on plastic and in xenografts. This growth phenotype was accompanied by enhanced levels of reactive oxygen species (ROS) leading to senescence. Mice with homozygous deletion of both TP53 and PIP4K2B were not viable, indicating a synthetic lethality for loss of these two genes. Importantly however, PIP4K2A(-/-), PIP4K2B(+/-), and TP53(-/-) mice were viable and had a dramatic reduction in tumor formation compared to TP53(-/-) littermates. These results indicate that inhibitors of PI5P4Ks could be effective in preventing or treating cancers with mutations in TP53.

Multi-omic machine learning predictor of breast cancer therapy response.

Breast cancers are complex ecosystems of malignant cells and the tumour microenvironment1. The composition of these tumour ecosystems and interactions within them contribute to responses to cytotoxic therapy2. Efforts to build response predictors have not incorporated this knowledge. We collected clinical, digital pathology, genomic and transcriptomic profiles of pre-treatment biopsies of breast tumours from 168 patients treated with chemotherapy with or without HER2 (encoded by ERBB2)-targeted therapy before surgery. Pathology end points (complete response or residual disease) at surgery3 were then correlated with multi-omic features in these diagnostic biopsies. Here we show that response to treatment is modulated by the pre-treated tumour ecosystem, and its multi-omics landscape can be integrated in predictive models using machine learning. The degree of residual disease following therapy is monotonically associated with pre-therapy features, including tumour mutational and copy number landscapes, tumour proliferation, immune infiltration and T cell dysfunction and exclusion. Combining these features into a multi-omic machine learning model predicted a pathological complete response in an external validation cohort (75 patients) with an area under the curve of 0.87. In conclusion, response to therapy is determined by the baseline characteristics of the totality of the tumour ecosystem captured through data integration and machine learning. This approach could be used to develop predictors for other cancers.

A trispecific antibody targeting HER2 and T cells inhibits breast cancer growth via CD4 cells.

Effective antitumour immunity depends on the orchestration of potent T cell responses against malignancies1. Regression of human cancers has been induced by immune checkpoint inhibitors, T cell engagers or chimeric antigen receptor T cell therapies2-4. Although CD8 T cells function as key effectors of these responses, the role of CD4 T cells beyond their helper function has not been defined. Here we demonstrate that a trispecific antibody to HER2, CD3 and CD28 stimulates regression of breast cancers in a humanized mouse model through a mechanism involving CD4-dependent inhibition of tumour cell cycle progression. Although CD8 T cells directly mediated tumour lysis in vitro, CD4 T cells exerted antiproliferative effects by blocking cancer cell cycle progression at G1/S. Furthermore, when T cell subsets were adoptively transferred into a humanized breast cancer tumour mouse model, CD4 T cells alone inhibited HER2+ breast cancer growth in vivo. RNA microarray analysis revealed that CD4 T cells markedly decreased tumour cell cycle progression and proliferation, and also increased pro-inflammatory signalling pathways. Collectively, the trispecific antibody to HER2 induced T cell-dependent tumour regression through direct antitumour and indirect pro-inflammatory/immune effects driven by CD4 T cells.

Genomics to select treatment for patients with metastatic breast cancer.

Cancer progression is driven in part by genomic alterations1. The genomic characterization of cancers has shown interpatient heterogeneity regarding driver alterations2, leading to the concept that generation of genomic profiling in patients with cancer could allow the selection of effective therapies3,4. Although DNA sequencing has been implemented in practice, it remains unclear how to use its results. A total of 1,462 patients with HER2-non-overexpressing metastatic breast cancer were enroled to receive genomic profiling in the SAFIR02-BREAST trial. Two hundred and thirty-eight of these patients were randomized in two trials (nos. NCT02299999 and NCT03386162) comparing the efficacy of maintenance treatment5 with a targeted therapy matched to genomic alteration. Targeted therapies matched to genomics improves progression-free survival when genomic alterations are classified as level I/II according to the ESMO Scale for Clinical Actionability of Molecular Targets (ESCAT)6 (adjusted hazards ratio (HR): 0.41, 90% confidence interval (CI): 0.27-0.61, P < 0.001), but not when alterations are unselected using ESCAT (adjusted HR: 0.77, 95% CI: 0.56-1.06, P = 0.109). No improvement in progression-free survival was observed in the targeted therapies arm (unadjusted HR: 1.15, 95% CI: 0.76-1.75) for patients presenting with ESCAT alteration beyond level I/II. Patients with germline BRCA1/2 mutations (n = 49) derived high benefit from olaparib (gBRCA1: HR = 0.36, 90% CI: 0.14-0.89; gBRCA2: HR = 0.37, 90% CI: 0.17-0.78). This trial provides evidence that the treatment decision led by genomics should be driven by a framework of target actionability in patients with metastatic breast cancer.

Estrogen-related receptors are targetable ROS sensors.

Excessive reactive oxygen species (ROS) can cause oxidative stress and consequently cell injury contributing to a wide range of diseases. Addressing the critical gaps in our understanding of the adaptive molecular events downstream ROS provocation holds promise for the identification of druggable metabolic vulnerabilities. Here, we unveil a direct molecular link between the activity of two estrogen-related receptor (ERR) isoforms and the control of glutamine utilization and glutathione antioxidant production. ERRα down-regulation restricts glutamine entry into the TCA cycle, while ERRγ up-regulation promotes glutamine-driven glutathione production. Notably, we identify increased ERRγ expression/activation as a hallmark of oxidative stress triggered by mitochondrial disruption or chemotherapy. Enhanced tumor antioxidant capacity is an underlying feature of human breast cancer (BCa) patients that respond poorly to treatment. We demonstrate that pharmacological inhibition of ERRγ with the selective inverse agonist GSK5182 increases antitumor efficacy of the chemotherapeutic paclitaxel on poor outcome BCa tumor organoids. Our findings thus underscore the ERRs as novel redox sensors and effectors of a ROS defense program and highlight the potential therapeutic advantage of exploiting ERRγ inhibitors for the treatment of BCa and other diseases where oxidative stress plays a central role.

CircPVT1 promotes ER-positive breast tumorigenesis and drug resistance by targeting ESR1 and MAVS.

The molecular mechanisms underlying estrogen receptor (ER)-positive breast carcinogenesis and endocrine therapy resistance remain incompletely understood. Here, we report that circPVT1, a circular RNA generated from the lncRNA PVT1, is highly expressed in ERα-positive breast cancer cell lines and tumor samples and is functionally important in promoting ERα-positive breast tumorigenesis and endocrine therapy resistance. CircPVT1 acts as a competing endogenous RNA (ceRNA) to sponge miR-181a-2-3p, promoting the expression of ESR1 and downstream ERα-target genes and breast cancer cell growth. Furthermore, circPVT1 directly interacts with MAVS protein to disrupt the RIGI-MAVS complex formation, inhibiting type I interferon (IFN) signaling pathway and anti-tumor immunity. Anti-sense oligonucleotide (ASO)-targeting circPVT1 inhibits ERα-positive breast cancer cell and tumor growth, re-sensitizing tamoxifen-resistant ERα-positive breast cancer cells to tamoxifen treatment. Taken together, our data demonstrated that circPVT1 can work through both ceRNA and protein scaffolding mechanisms to promote cancer. Thus, circPVT1 may serve as a diagnostic biomarker and therapeutic target for ERα-positive breast cancer in the clinic.

Ribociclib plus Endocrine Therapy in Early Breast Cancer.

BACKGROUND: Ribociclib has been shown to have a significant overall survival benefit in patients with hormone receptor (HR)-positive, human epidermal growth factor receptor 2 (HER2)-negative advanced breast cancer. Whether this benefit in advanced breast cancer extends to early breast cancer is unclear. METHODS: In this international, open-label, randomized, phase 3 trial, we randomly assigned patients with HR-positive, HER2-negative early breast cancer in a 1:1 ratio to receive ribociclib (at a dose of 400 mg per day for 3 weeks, followed by 1 week off, for 3 years) plus a nonsteroidal aromatase inhibitor (NSAI; letrozole at a dose of 2.5 mg per day or anastrozole at a dose of 1 mg per day for ≥5 years) or an NSAI alone. Premenopausal women and men also received goserelin every 28 days. Eligible patients had anatomical stage II or III breast cancer. Here we report the results of a prespecified interim analysis of invasive disease-free survival, the primary end point; other efficacy and safety results are also reported. Invasive disease-free survival was evaluated with the use of the Kaplan-Meier method. The statistical comparison was made with the use of a stratified log-rank test, with a protocol-specified stopping boundary of a one-sided P-value threshold of 0.0128 for superior efficacy. RESULTS: As of the data-cutoff date for this prespecified interim analysis (January 11, 2023), a total of 426 patients had had invasive disease, recurrence, or death. A significant invasive disease-free survival benefit was seen with ribociclib plus an NSAI as compared with an NSAI alone. At 3 years, invasive disease-free survival was 90.4% with ribociclib plus an NSAI and 87.1% with an NSAI alone (hazard ratio for invasive disease, recurrence, or death, 0.75; 95% confidence interval, 0.62 to 0.91; P = 0.003). Secondary end points - distant disease-free survival and recurrence-free survival - also favored ribociclib plus an NSAI. The 3-year regimen of ribociclib at a 400-mg starting dose plus an NSAI was not associated with any new safety signals. CONCLUSIONS: Ribociclib plus an NSAI significantly improved invasive disease-free survival among patients with HR-positive, HER2-negative stage II or III early breast cancer. (Funded by Novartis; NATALEE ClinicalTrials.gov number, NCT03701334.).