Suppression of Bcl3 disrupts viability of breast cancer cells through both p53-dependent and p53-independent mechanisms via loss of NF-κB signalling

The NF-κB co-factor Bcl3 is a proto-oncogene that promotes breast cancer proliferation, metastasis and therapeutic resistance, yet its role in breast cancer cell survival is unclear. Here, we sought to determine the effect of Bcl3 suppression alone on breast cancer cell viability, with a view to informing future studies that aim to target Bcl3 therapeutically. Bcl3 was suppressed by siRNA in breast cancer cell lines before changes in viability, proliferation, apoptosis and senescence were examined. Bcl3 suppression significantly reduced viability and was shown to induce apoptosis in all cell lines tested, while an additional p53-dependent senescence and senescence-associated secretory phenotype was also observed in those cells with functional p53. The role of the Bcl3/NF-κB axis in this senescence response was confirmed via siRNA of the non-canonical NF-κB subunit NFKB2/p52, which resulted in increased cellular senescence and the canonical subunit NFKB1/p50, which induced the senescence-associated secretory phenotype. An analysis of clinical data showed a correlation between reduced relapse-free survival in patients that expressed high levels of Bcl3 and carried a p53 mutation. Together, these data demonstrate a dual role for Bcl3/NF-κB in the maintenance of breast cancer cell viability and suggests that targeting Bcl3 may be more beneficial to patients with tumours that lack functional p53

Bcl-3 promotes multi-modal tumour cell migration via NF-κB1 mediated regulation of Cdc42

A key challenge in the implementation of anti-metastatics as cancer therapies is the multi-modal nature of cell migration, which allows tumour cells to evade the targeted inhibition of specific cell motility pathways. The nuclear factor-kappaB (NF-κB) co-factor B-cell lymphoma 3 (Bcl-3) has been implicated in breast cancer cell migration and metastasis, yet it remains to be determined exactly which cell motility pathways are controlled by Bcl-3 and whether migrating tumour cells are able to evade Bcl-3 intervention. Addressing these questions and the mechanism underpinning Bcl-3’s role in this process would help determine its potential as a therapeutic target. Here we identify Bcl-3 as an upstream regulator of the two principal forms of breast cancer cell motility, involving collective and single-cell migration. This was found to be mediated by the master regulator Cdc42 through binding of the NF-κB transcription factor p50 to the Cdc42 promoter. Notably, Bcl-3 depletion inhibited both stable and transitory motility phenotypes in breast cancer cells with no evidence of migratory adaptation. Overexpression of Bcl-3 enhanced migration and increased metastatic tumour burden of breast cancer cells in vivo, whereas overexpression of a mutant Bcl-3 protein, which is unable to bind p50, suppressed cell migration and metastatic tumour burden suggesting that disruption of Bcl-3/NF-κB complexes is sufficient to inhibit metastasis. These findings identify a novel role for Bcl-3 in intrinsic and adaptive multi-modal cell migration mediated by its direct regulation of the Rho GTPase Cdc42 and identify the upstream Bcl-3:p50 transcription complex as a potential therapeutic target for metastatic disease

The PTEN conundrum: how to target PTEN-deficient prostate cancer

Loss of the tumor suppressor phosphatase and tensin homologue deleted on chromosome 10 (PTEN), which negatively regulates the PI3K–AKT–mTOR pathway, is strongly linked to advanced prostate cancer progression and poor clinical outcome. Accordingly, several therapeutic approaches are currently being explored to combat PTEN-deficient tumors. These include classical inhibition of the PI3K–AKT–mTOR signaling network, as well as new approaches that restore PTEN function, or target PTEN regulation of chromosome stability, DNA damage repair and the tumor microenvironment. While targeting PTEN-deficient prostate cancer remains a clinical challenge, new advances in the field of precision medicine indicate that PTEN loss provides a valuable biomarker to stratify prostate cancer patients for treatments, which may improve overall outcome. Here, we discuss the clinical implications of PTEN loss in the management of prostate cancer and review recent therapeutic advances in targeting PTEN-deficient prostate cancer. Deepening our understanding of how PTEN loss contributes to prostate cancer growth and therapeutic resistance will inform the design of future clinical studies and precision-medicine strategies that will ultimately improve patient care. View Full-Text Keywords: PTEN; PI3K; targeted therapy; prostate cance

Biodistribution PET/CT study of hemoglobin-DFO-89Zr complex in healthy and lung tumor-bearing mice

Proteins, as a major component of organisms, are considered the preferred biomaterials for drug delivery vehicles. Hemoglobin (Hb) has been recently rediscovered as a potential drug carrier, but its use for biomedical applications still lacks extensive investigation. To further explore the possibility of utilizing Hb as a potential tumor targeting drug carrier, we examined and compared the biodistribution of Hb in healthy and lung tumor-bearing mice, using for the first time 89Zr labelled Hb in a positron emission tomography (PET) measurement. Hb displays a very high conjugation yield in its fast and selective reaction with the maleimide-deferoxamine (DFO) bifunctional chelator. The high-resolution X-ray structure of the Hb-DFO complex demonstrated that cysteine β93 is the sole attachment moiety to the αβ-protomer of Hb. The Hb-DFO complex shows quantitative uptake of 89Zr in solution as determined by radiochromatography. Injection of 0.03 mg of Hb-DFO-89Zr complex in healthy mice indicates very high radioactivity in liver, followed by spleen and lungs, whereas a threefold increased dosage results in intensification of PET signal in kidneys and decreased signal in liver and spleen. No difference in biodistribution pattern is observed between naïve and tumor-bearing mice. Interestingly, the liver Hb uptake did not decrease upon clodronate-mediated macrophage depletion, indicating that other immune cells contribute to Hb clearance. This finding is of particular interest for rapidly developing clinical immunology and projects aiming to target, label or specifically deliver agents to immune cells

Development and characterisation of a new patient-derived Xenograft model of AR-negative metastatic asctration-resistant prostate cancer

As the treatment landscape for prostate cancer gradually evolves, the frequency of treatment-induced neuroendocrine prostate cancer (NEPC) and double-negative prostate cancer (DNPC) that is deficient for androgen receptor (AR) and neuroendocrine (NE) markers has increased. These prostate cancer subtypes are typically refractory to AR-directed therapies and exhibit poor clinical outcomes. Only a small range of NEPC/DNPC models exist, limiting our molecular understanding of this disease and hindering our ability to perform preclinical trials exploring novel therapies to treat NEPC/DNPC that are urgently needed in the clinic. Here, we report the development of the CU-PC01 PDX model that represents AR-negative mCRPC with PTEN/RB/PSMA loss and CTNN1B/TP53/BRCA2 genetic variants. The CU-PC01 model lacks classic NE markers, with only focal and/or weak expression of chromogranin A, INSM1 and CD56. Collectively, these findings are most consistent with a DNPC phenotype. Ex vivo and in vivo preclinical studies revealed that CU-PC01 PDX tumours are resistant to mCRPC standard-of-care treatments enzalutamide and docetaxel, mirroring the donor patient’s treatment response. Furthermore, short-term CU-PC01 tumour explant cultures indicate this model is initially sensitive to PARP inhibition with olaparib. Thus, the CU-PC01 PDX model provides a valuable opportunity to study AR-negative mCRPC biology and to discover new treatment avenues for this hard-to-treat disease

Inferring Visuomotor Priors for Sensorimotor Learning

Sensorimotor learning has been shown to depend on both prior expectations and sensory evidence in a way that is consistent with Bayesian integration. Thus, prior beliefs play a key role during the learning process, especially when only ambiguous sensory information is available. Here we develop a novel technique to estimate the covariance structure of the prior over visuomotor transformations – the mapping between actual and visual location of the hand – during a learning task. Subjects performed reaching movements under multiple visuomotor transformations in which they received visual feedback of their hand position only at the end of the movement. After experiencing a particular transformation for one reach, subjects have insufficient information to determine the exact transformation, and so their second reach reflects a combination of their prior over visuomotor transformations and the sensory evidence from the first reach. We developed a Bayesian observer model in order to infer the covariance structure of the subjects' prior, which was found to give high probability to parameter settings consistent with visuomotor rotations. Therefore, although the set of visuomotor transformations experienced had little structure, the subjects had a strong tendency to interpret ambiguous sensory evidence as arising from rotation-like transformations. We then exposed the same subjects to a highly-structured set of visuomotor transformations, designed to be very different from the set of visuomotor rotations. During this exposure the prior was found to have changed significantly to have a covariance structure that no longer favored rotation-like transformations. In summary, we have developed a technique which can estimate the full covariance structure of a prior in a sensorimotor task and have shown that the prior over visuomotor transformations favor a rotation-like structure. Moreover, through experience of a novel task structure, participants can appropriately alter the covariance structure of their prior

PLEKHS1 drives PI3Ks and remodels pathway homeostasis in PTEN-null prostate

The PIP3/PI3K network is a central regulator of metabolism and is frequently activated in cancer, commonly by loss of the PIP3/PI(3,4)P2 phosphatase, PTEN. Despite huge research investment, the drivers of the PI3K network in normal tissues and how they adapt to overactivation are unclear. We find that in healthy mouse prostate PI3K activity is driven by RTK/IRS signaling and constrained by pathway feedback. In the absence of PTEN, the network is dramatically remodeled. A poorly understood YXXM- and PIP3/PI(3,4)P2-binding PH domain-containing adaptor, PLEKHS1, became the dominant activator and was required to sustain PIP3, AKT phosphorylation, and growth in PTEN-null prostate. This was because PLEKHS1 evaded pathway-feedback and experienced enhanced PI3K- and Src-family kinase-dependent phosphorylation of Y258XXM, eliciting PI3K activation. hPLEKHS1 mRNA and activating Y419 phosphorylation of hSrc correlated with PI3K pathway activity in human prostate cancers. We propose that in PTEN-null cells receptor-independent, Src-dependent tyrosine phosphorylation of PLEKHS1 creates positive feedback that escapes homeostasis, drives PIP3 signaling, and supports tumor progression

The experimental design.

<p>Each session alternated between veridical and transformed batches of trials. Each subject participated in three sessions, the first using an uncorrelated distribution of transformations, and the second and third using a correlated distribution. The joint distributions of and are plotted.</p

Schematic of the Bayesian observer model.

<p>The plots show six 2-dimensional views of the 4-dimensional probability space of the , , & parameters of the transformation matrix. The Gaussian prior is shown in blue (marginalised 1 s.d. isoprobability ellipses). On the first trial the evidence the subject receives (for simplicity shown here as noiseless) does not fully specify the transformation uniquely, and the transformations consistent with this evidence are shown in gray. This evidence (as a likelihood) is combined with the prior to give the posterior after the first trial (red ellipses: these are shown calculated from the noisy visual feedback) and the MAP of this posterior is taken as the estimate of the transformation. The cross shows the position of the actual transformation matrix used in generating the first-trial evidence.</p