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.

Dynamics of breast-cancer relapse reveal late-recurring ER-positive genomic subgroups.

The rates and routes of lethal systemic spread in breast cancer are poorly understood owing to a lack of molecularly characterized patient cohorts with long-term, detailed follow-up data. Long-term follow-up is especially important for those with oestrogen-receptor (ER)-positive breast cancers, which can recur up to two decades after initial diagnosis1-6. It is therefore essential to identify patients who have a high risk of late relapse7-9. Here we present a statistical framework that models distinct disease stages (locoregional recurrence, distant recurrence, breast-cancer-related death and death from other causes) and competing risks of mortality from breast cancer, while yielding individual risk-of-recurrence predictions. We apply this model to 3,240 patients with breast cancer, including 1,980 for whom molecular data are available, and delineate spatiotemporal patterns of relapse across different categories of molecular information (namely immunohistochemical subtypes; PAM50 subtypes, which are based on gene-expression patterns10,11; and integrative or IntClust subtypes, which are based on patterns of genomic copy-number alterations and gene expression12,13). We identify four late-recurring integrative subtypes, comprising about one quarter (26%) of tumours that are both positive for ER and negative for human epidermal growth factor receptor 2, each with characteristic tumour-driving alterations in genomic copy number and a high risk of recurrence (mean 47-62%) up to 20 years after diagnosis. We also define a subgroup of triple-negative breast cancers in which cancer rarely recurs after five years, and a separate subgroup in which patients remain at risk. Use of the integrative subtypes improves the prediction of late, distant relapse beyond what is possible with clinical covariates (nodal status, tumour size, tumour grade and immunohistochemical subtype). These findings highlight opportunities for improved patient stratification and biomarker-driven clinical trials.

PI3K activation promotes resistance to eribulin in HER2-negative breast cancer.

BACKGROUND: Eribulin is a microtubule-targeting agent approved for the treatment of advanced or metastatic breast cancer (BC) previously treated with anthracycline- and taxane-based regimens. PIK3CA mutation is associated with worse response to chemotherapy in oestrogen receptor-positive (ER+)/human epidermal growth factor receptor 2-negative (HER2-) metastatic BC. We aimed to evaluate the role of phosphoinositide 3-kinase (PI3K)/AKT pathway mutations in eribulin resistance. METHODS: Resistance to eribulin was evaluated in HER2- BC cell lines and patient-derived tumour xenografts, and correlated with a mutation in the PI3K/AKT pathway. RESULTS: Eleven out of 23 HER2- BC xenografts treated with eribulin exhibited disease progression. No correlation with ER status was detected. Among the resistant models, 64% carried mutations in PIK3CA, PIK3R1 or AKT1, but only 17% among the sensitive xenografts (P = 0.036). We observed that eribulin treatment induced AKT phosphorylation in vitro and in patient tumours. In agreement, the addition of PI3K inhibitors reversed primary and acquired resistance to eribulin in xenograft models, regardless of the genetic alterations in PI3K/AKT pathway or ER status. Mechanistically, PI3K blockade reduced p21 levels likely enabling apoptosis, thus sensitising to eribulin treatment. CONCLUSIONS: PI3K pathway activation induces primary resistance or early adaptation to eribulin, supporting the combination of PI3K inhibitors and eribulin for the treatment of HER2- BC patients.

Progesterone receptor modulates ERα action in breast cancer.

Progesterone receptor (PR) expression is used as a biomarker of oestrogen receptor-α (ERα) function and breast cancer prognosis. Here we show that PR is not merely an ERα-induced gene target, but is also an ERα-associated protein that modulates its behaviour. In the presence of agonist ligands, PR associates with ERα to direct ERα chromatin binding events within breast cancer cells, resulting in a unique gene expression programme that is associated with good clinical outcome. Progesterone inhibited oestrogen-mediated growth of ERα(+) cell line xenografts and primary ERα(+) breast tumour explants, and had increased anti-proliferative effects when coupled with an ERα antagonist. Copy number loss of PGR, the gene coding for PR, is a common feature in ERα(+) breast cancers, explaining lower PR levels in a subset of cases. Our findings indicate that PR functions as a molecular rheostat to control ERα chromatin binding and transcriptional activity, which has important implications for prognosis and therapeutic interventions.

Dynamics of genomic clones in breast cancer patient xenografts at single-cell resolution.

Human cancers, including breast cancers, comprise clones differing in mutation content. Clones evolve dynamically in space and time following principles of Darwinian evolution, underpinning important emergent features such as drug resistance and metastasis. Human breast cancer xenoengraftment is used as a means of capturing and studying tumour biology, and breast tumour xenografts are generally assumed to be reasonable models of the originating tumours. However, the consequences and reproducibility of engraftment and propagation on the genomic clonal architecture of tumours have not been systematically examined at single-cell resolution. Here we show, using deep-genome and single-cell sequencing methods, the clonal dynamics of initial engraftment and subsequent serial propagation of primary and metastatic human breast cancers in immunodeficient mice. In all 15 cases examined, clonal selection on engraftment was observed in both primary and metastatic breast tumours, varying in degree from extreme selective engraftment of minor (<5% of starting population) clones to moderate, polyclonal engraftment. Furthermore, ongoing clonal dynamics during serial passaging is a feature of tumours experiencing modest initial selection. Through single-cell sequencing, we show that major mutation clusters estimated from tumour population sequencing relate predictably to the most abundant clonal genotypes, even in clonally complex and rapidly evolving cases. Finally, we show that similar clonal expansion patterns can emerge in independent grafts of the same starting tumour population, indicating that genomic aberrations can be reproducible determinants of evolutionary trajectories. Our results show that measurement of genomically defined clonal population dynamics will be highly informative for functional studies using patient-derived breast cancer xenoengraftment.

SOX4 can redirect TGF-ß-mediated SMAD3-transcriptional output in a context-dependent manner to promote tumorigenesis.

Expression of the transcription factor SOX4 is often elevated in human cancers, where it generally correlates with tumor-progression and poor-disease outcome. Reduction of SOX4 expression results in both diminished tumor-incidence and metastasis. In breast cancer, TGF-ß-mediated induction of SOX4 has been shown to contribute to epithelial-to-mesenchymal transition (EMT), which controls pro-metastatic events. Here, we identify SMAD3 as a novel, functionally relevant SOX4 interaction partner. Genome-wide analysis showed that SOX4 and SMAD3 co-occupy a large number of genomic loci in a cell-type specific manner. Moreover, SOX4 expression was required for TGF-ß-mediated induction of a subset of SMAD3/SOX4-co-bound genes regulating migration and extracellular matrix-associated processes, and correlating with poor-prognosis. These findings identify SOX4 as an important SMAD3 co-factor controlling transcription of pro-metastatic genes and context-dependent shaping of the cellular response to TGF-ß. Targeted disruption of the interaction between these factors may have the potential to disrupt pro-oncogenic TGF-ß signaling, thereby impairing tumorigenesis.

Computational approach to discriminate human and mouse sequences in patient-derived tumour xenografts.

BACKGROUND: Patient-Derived Tumour Xenografts (PDTXs) have emerged as the pre-clinical models that best represent clinical tumour diversity and intra-tumour heterogeneity. The molecular characterization of PDTXs using High-Throughput Sequencing (HTS) is essential; however, the presence of mouse stroma is challenging for HTS data analysis. Indeed, the high homology between the two genomes results in a proportion of mouse reads being mapped as human. RESULTS: In this study we generated Whole Exome Sequencing (WES), Reduced Representation Bisulfite Sequencing (RRBS) and RNA sequencing (RNA-seq) data from samples with known mixtures of mouse and human DNA or RNA and from a cohort of human breast cancers and their derived PDTXs. We show that using an In silico Combined human-mouse Reference Genome (ICRG) for alignment discriminates between human and mouse reads with up to 99.9% accuracy and decreases the number of false positive somatic mutations caused by misalignment by >99.9%. We also derived a model to estimate the human DNA content in independent PDTX samples. For RNA-seq and RRBS data analysis, the use of the ICRG allows dissecting computationally the transcriptome and methylome of human tumour cells and mouse stroma. In a direct comparison with previously reported approaches, our method showed similar or higher accuracy while requiring significantly less computing time. CONCLUSIONS: The computational pipeline we describe here is a valuable tool for the molecular analysis of PDTXs as well as any other mixture of DNA or RNA species.

High TGFbeta-Smad activity confers poor prognosis in glioma patients and promotes cell proliferation depending on the methylation of the PDGF-B gene.

TGFbeta acts as a tumor suppressor in normal epithelial cells and early-stage tumors and becomes an oncogenic factor in advanced tumors. The molecular mechanisms involved in the malignant function of TGFbeta are not fully elucidated. We demonstrate that high TGFbeta-Smad activity is present in aggressive, highly proliferative gliomas and confers poor prognosis in patients with glioma. We discern the mechanisms and molecular determinants of the TGFbeta oncogenic response with a transcriptomic approach and by analyzing primary cultured patient-derived gliomas and human glioma biopsies. The TGFbeta-Smad pathway promotes proliferation through the induction of PDGF-B in gliomas with an unmethylated PDGF-B gene. The epigenetic regulation of the PDGF-B gene dictates whether TGFbeta acts as an oncogenic factor inducing PDGF-B and proliferation in human glioma.

FOXC2 promotes vasculogenic mimicry and resistance to anti-angiogenic therapy.

Vasculogenic mimicry (VM) describes the formation of pseudo blood vessels constructed of tumor cells that have acquired endothelial-like properties. VM channels endow the tumor with a tumor-derived vascular system that directly connects to host blood vessels, and their presence is generally associated with poor patient prognosis. Here we show that the transcription factor, Foxc2, promotes VM in diverse solid tumor types by driving ectopic expression of endothelial genes in tumor cells, a process that is stimulated by hypoxia. VM-proficient tumors are resistant to anti-angiogenic therapy, and suppression of Foxc2 augments response. This work establishes co-option of an embryonic endothelial transcription factor by tumor cells as a key mechanism driving VM proclivity and motivates the search for VM-inhibitory agents that could form the basis of combination therapies with anti-angiogenics.

MiR-182-3p targets TRF2 and impairs tumor growth of triple-negative breast cancer.

The telomeric repeat-binding factor 2 (TRF2) is a telomere-capping protein that plays a key role in the maintenance of telomere structure and function. It is highly expressed in different cancer types, and it contributes to cancer progression. To date, anti-cancer strategies to target TRF2 remain a challenge. Here, we developed a miRNA-based approach to reduce TRF2 expression. By performing a high-throughput luciferase screening of 54 candidate miRNAs, we identified miR-182-3p as a specific and efficient post-transcriptional regulator of TRF2. Ectopic expression of miR-182-3p drastically reduced TRF2 protein levels in a panel of telomerase- or alternative lengthening of telomeres (ALT)-positive cancer cell lines. Moreover, miR-182-3p induced DNA damage at telomeric and pericentromeric sites, eventually leading to strong apoptosis activation. We also observed that treatment with lipid nanoparticles (LNPs) containing miR-182-3p impaired tumor growth in triple-negative breast cancer (TNBC) models, including patient-derived tumor xenografts (PDTXs), without affecting mouse survival or tissue function. Finally, LNPs-miR-182-3p were able to cross the blood-brain barrier and reduce intracranial tumors representing a possible therapeutic option for metastatic brain lesions.

RANK is a poor prognosis marker and a therapeutic target in ER-negative postmenopausal breast cancer.

Despite strong preclinical data, the therapeutic benefit of the RANKL inhibitor, denosumab, in breast cancer patients, beyond the bone, is unclear. Aiming to select patients who may benefit from denosumab, we hereby analyzed RANK and RANKL protein expression in more than 2,000 breast tumors (777 estrogen receptor-negative, ER- ) from four independent cohorts. RANK protein expression was more frequent in ER- tumors, where it associated with poor outcome and poor response to chemotherapy. In ER- breast cancer patient-derived orthoxenografts (PDXs), RANKL inhibition reduced tumor cell proliferation and stemness, regulated tumor immunity and metabolism, and improved response to chemotherapy. Intriguingly, tumor RANK protein expression associated with poor prognosis in postmenopausal breast cancer patients, activation of NFKB signaling, and modulation of immune and metabolic pathways, suggesting that RANK signaling increases after menopause. Our results demonstrate that RANK protein expression is an independent biomarker of poor prognosis in postmenopausal and ER- breast cancer patients and support the therapeutic benefit of RANK pathway inhibitors, such as denosumab, in breast cancer patients with RANK+ ER- tumors after menopause.

Vitamin B5 supports MYC oncogenic metabolism and tumor progression in breast cancer.

Tumors are intrinsically heterogeneous and it is well established that this directs their evolution, hinders their classification and frustrates therapy1-3. Consequently, spatially resolved omics-level analyses are gaining traction4-9. Despite considerable therapeutic interest, tumor metabolism has been lagging behind this development and there is a paucity of data regarding its spatial organization. To address this shortcoming, we set out to study the local metabolic effects of the oncogene c-MYC, a pleiotropic transcription factor that accumulates with tumor progression and influences metabolism10,11. Through correlative mass spectrometry imaging, we show that pantothenic acid (vitamin B5) associates with MYC-high areas within both human and murine mammary tumors, where its conversion to coenzyme A fuels Krebs cycle activity. Mechanistically, we show that this is accomplished by MYC-mediated upregulation of its multivitamin transporter SLC5A6. Notably, we show that SLC5A6 over-expression alone can induce increased cell growth and a shift toward biosynthesis, whereas conversely, dietary restriction of pantothenic acid leads to a reversal of many MYC-mediated metabolic changes and results in hampered tumor growth. Our work thus establishes the availability of vitamins and cofactors as a potential bottleneck in tumor progression, which can be exploited therapeutically. Overall, we show that a spatial understanding of local metabolism facilitates the identification of clinically relevant, tractable metabolic targets.

Wnt Signaling in the Breast: From Development to Disease.

The Wnt cascade is a primordial developmental signaling pathway that plays a myriad of essential functions throughout development and adult homeostasis in virtually all animal species. Aberrant Wnt activity is implicated in embryonic and tissue morphogenesis defects, and several diseases, most notably cancer. The role of Wnt signaling in mammary gland development and breast cancer initiation, maintenance, and progression is far from being completely understood and is rather shrouded in controversy. In this review, we dissect the fundamental role of Wnt signaling in mammary gland development and adult homeostasis and explore how defects in its tightly regulated and intricated molecular network are interlinked with cancer, with a focus on the breast.

Anti-tumoural activity of the G-quadruplex ligand pyridostatin against BRCA1/2-deficient tumours.

The cells with compromised BRCA1 or BRCA2 (BRCA1/2) function accumulate stalled replication forks, which leads to replication-associated DNA damage and genomic instability, a signature of BRCA1/2-mutated tumours. Targeted therapies against BRCA1/2-mutated tumours exploit this vulnerability by introducing additional DNA lesions. Because homologous recombination (HR) repair is abrogated in the absence of BRCA1 or BRCA2, these lesions are specifically lethal to tumour cells, but not to the healthy tissue. Ligands that bind and stabilise G-quadruplexes (G4s) have recently emerged as a class of compounds that selectively eliminate the cells and tumours lacking BRCA1 or BRCA2. Pyridostatin is a small molecule that binds G4s and is specifically toxic to BRCA1/2-deficient cells in vitro. However, its in vivo potential has not yet been evaluated. Here, we demonstrate that pyridostatin exhibits a high specific activity against BRCA1/2-deficient tumours, including patient-derived xenograft tumours that have acquired PARP inhibitor (PARPi) resistance. Mechanistically, we demonstrate that pyridostatin disrupts replication leading to DNA double-stranded breaks (DSBs) that can be repaired in the absence of BRCA1/2 by canonical non-homologous end joining (C-NHEJ). Consistent with this, chemical inhibitors of DNA-PKcs, a core component of C-NHEJ kinase activity, act synergistically with pyridostatin in eliminating BRCA1/2-deficient cells and tumours. Furthermore, we demonstrate that pyridostatin triggers cGAS/STING-dependent innate immune responses when BRCA1 or BRCA2 is abrogated. Paclitaxel, a drug routinely used in cancer chemotherapy, potentiates the in vivo toxicity of pyridostatin. Overall, our results demonstrate that pyridostatin is a compound suitable for further therapeutic development, alone or in combination with paclitaxel and DNA-PKcs inhibitors, for the benefit of cancer patients carrying BRCA1/2 mutations.

High p16 expression and heterozygous RB1 loss are biomarkers for CDK4/6 inhibitor resistance in ER+ breast cancer.

CDK4/6 inhibitors combined with endocrine therapy have demonstrated higher antitumor activity than endocrine therapy alone for the treatment of advanced estrogen receptor-positive breast cancer. Some of these tumors are de novo resistant to CDK4/6 inhibitors and others develop acquired resistance. Here, we show that p16 overexpression is associated with reduced antitumor activity of CDK4/6 inhibitors in patient-derived xenografts (n = 37) and estrogen receptor-positive breast cancer cell lines, as well as reduced response of early and advanced breast cancer patients to CDK4/6 inhibitors (n = 89). We also identified heterozygous RB1 loss as biomarker of acquired resistance and poor clinical outcome. Combination of the CDK4/6 inhibitor ribociclib with the PI3K inhibitor alpelisib showed antitumor activity in estrogen receptor-positive non-basal-like breast cancer patient-derived xenografts, independently of PIK3CA, ESR1 or RB1 mutation, also in drug de-escalation experiments or omitting endocrine therapy. Our results offer insights into predicting primary/acquired resistance to CDK4/6 inhibitors and post-progression therapeutic strategies.

Identification of a Molecularly-Defined Subset of Breast and Ovarian Cancer Models that Respond to WEE1 or ATR Inhibition, Overcoming PARP Inhibitor Resistance.

PURPOSE: PARP inhibitors (PARPi) induce synthetic lethality in homologous recombination repair (HRR)-deficient tumors and are used to treat breast, ovarian, pancreatic, and prostate cancers. Multiple PARPi resistance mechanisms exist, most resulting in restoration of HRR and protection of stalled replication forks. ATR inhibition was highlighted as a unique approach to reverse both aspects of resistance. Recently, however, a PARPi/WEE1 inhibitor (WEE1i) combination demonstrated enhanced antitumor activity associated with the induction of replication stress, suggesting another approach to tackling PARPi resistance. EXPERIMENTAL DESIGN: We analyzed breast and ovarian patient-derived xenoimplant models resistant to PARPi to quantify WEE1i and ATR inhibitor (ATRi) responses as single agents and in combination with PARPi. Biomarker analysis was conducted at the genetic and protein level. Metabolite analysis by mass spectrometry and nucleoside rescue experiments ex vivo were also conducted in patient-derived models. RESULTS: Although WEE1i response was linked to markers of replication stress, including STK11/RB1 and phospho-RPA, ATRi response associated with ATM mutation. When combined with olaparib, WEE1i could be differentiated from the ATRi/olaparib combination, providing distinct therapeutic strategies to overcome PARPi resistance by targeting the replication stress response. Mechanistically, WEE1i sensitivity was associated with shortage of the dNTP pool and a concomitant increase in replication stress. CONCLUSIONS: Targeting the replication stress response is a valid therapeutic option to overcome PARPi resistance including tumors without an underlying HRR deficiency. These preclinical insights are now being tested in several clinical trials where the PARPi is administered with either the WEE1i or the ATRi.

The Promise of Patient-Derived Preclinical Models to Accelerate the Implementation of Personalised Medicine for Children with Neuroblastoma.

Patient-derived preclinical models are now a core component of cancer research and have the ability to drastically improve the predictive power of preclinical therapeutic studies. However, their development and maintenance can be challenging, time consuming, and expensive. For neuroblastoma, a developmental malignancy of the neural crest, it is possible to establish patient-derived models as xenografts in mice and zebrafish, and as spheroids and organoids in vitro. These varied approaches have contributed to comprehensive packages of preclinical evidence in support of new therapeutics for neuroblastoma. We discuss here the ethical and technical considerations for the creation of patient-derived models of neuroblastoma and how their use can be optimized for the study of tumour evolution and preclinical therapies. We also discuss how neuroblastoma patient-derived models might become avatars for personalised medicine for children with this devastating disease.

Metabolic imaging with hyperpolarized [1-13C] pyruvate in patient-derived preclinical mouse models of breast cancer.

13C nuclear spin hyperpolarization can increase the sensitivity of detection in an MRI experiment by more than 10,000-fold. 13C magnetic resonance spectroscopic imaging (MRSI) of hyperpolarized 13C label exchange between injected [1-13C]pyruvate and the endogenous tumor lactate pool can be used clinically to assess tumor grade and response to treatment. We describe here an experimental protocol for using this technique in patient-derived and established cell line xenograft models of breast cancer in the mouse. For complete details on the use and execution of this protocol, please refer to Ros et al. (2020).

Predicting Cancer Drug Response In Vivo by Learning an Optimal Feature Selection of Tumour Molecular Profiles.

(1) Background: Inter-tumour heterogeneity is one of cancer's most fundamental features. Patient stratification based on drug response prediction is hence needed for effective anti-cancer therapy. However, single-gene markers of response are rare and/or may fail to achieve a significant impact in the clinic. Machine Learning (ML) is emerging as a particularly promising complementary approach to precision oncology. (2) Methods: Here we leverage comprehensive Patient-Derived Xenograft (PDX) pharmacogenomic data sets with dimensionality-reducing ML algorithms with this purpose. (3) Results: Combining multiple gene alterations via ML leads to better discrimination between sensitive and resistant PDXs in 19 of the 26 analysed cases. Highly predictive ML models employing concise gene lists were found for three cases: paclitaxel (breast cancer), binimetinib (breast cancer) and cetuximab (colorectal cancer). Interestingly, each of these multi-gene ML models identifies some treatment-responsive PDXs not harbouring the best actionable mutation for that case. Thus, ML multi-gene predictors generally have much fewer false negatives than the corresponding single-gene marker. (4) Conclusions: As PDXs often recapitulate clinical outcomes, these results suggest that many more patients could benefit from precision oncology if ML algorithms were also applied to existing clinical pharmacogenomics data, especially those algorithms generating classifiers combining data-selected gene alterations.