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Nuclei classification provides valuable information for histopathology image analysis. However, the large variations in the appearance of different nuclei types cause difficulties in identifying nuclei. Most neural network based methods are affected by the local receptive field of convolutions, and pay less attention to the spatial distribution of nuclei or the irregular contour shape of a nucleus. In this paper, we first propose a novel polygon-structure feature learning mechanism that transforms a nucleus contour into a sequence of points sampled in order, and employ a recurrent neural network that aggregates the sequential change in distance between key points to obtain learnable shape features. Next, we convert a histopathology image into a graph structure with nuclei as nodes, and build a graph neural network to embed the spatial distribution of nuclei into their representations. To capture the correlations between the categories of nuclei and their surrounding tissue patterns, we further introduce edge features that are defined as the background textures between adjacent nuclei. Lastly, we integrate both polygon and graph structure learning mechanisms into a whole framework that can extract intra and inter-nucleus structural characteristics for nuclei classification. Experimental results show that the proposed framework achieves significant improvements compared to the previous methods. Code and data are made available via https://github.com/lhaof/SENC. IEEE

Nuclei classification is a critical step in computer-aided diagnosis with histopathology images. In the past, various methods have employed graph neural networks (GNN) to analyze cell graphs that model inter-cell relationships by considering nuclei as vertices. However, they are limited by the GNN mechanism that only passes messages among local nodes via fixed edges. To address the issue, we develop a cell graph transformer (CGT) that treats nodes and edges as input tokens to enable learnable adjacency and information exchange among all nodes. Nevertheless, training the transformer with a cell graph presents another challenge. Poorly initialized features can lead to noisy self-attention scores and inferior convergence, particularly when processing the cell graphs with numerous connections. Thus, we further propose a novel topology-aware pretraining method that leverages a graph convolutional network (GCN) to learn a feature extractor. The pre-trained features may suppress unreasonable correlations and hence ease the finetuning of CGT. Experimental results suggest that the proposed cell graph transformer with topology-aware pretraining significantly improves the nuclei classification results, and achieves the state-of-the-art performance. Code and models are available at https://github.com/lhaof/CGT, Comment: AAAI 2024, Code and models are available at https://github.com/lhaof/CGT

Current common treatments for castration-resistant prostate cancer (CRPC) typically belong to one of three major categories: next-generation anti-androgen therapies (NGAT) including enzalutamide, abiraterone acetate, apalutamide, and darolutamide; taxane therapy represented by docetaxel; and PARP inhibitors (PARPi) like olaparib. Although these treatments have shown efficacy and have improved outcomes for many patients, some do not survive due to the emergence of therapeutic resistance. The clinical landscape is further complicated by limited knowledge about how the sequence of treatments impacts the development of therapeutic cross-resistance in CRPC. We have developed multiple CRPC models of acquired therapeutic resistance cell sublines from C4-2B cells. These include C4-2B MDVR, C4-2B AbiR, C4-2B ApaR, C4-2B DaroR, TaxR, and 2B-olapR, which are resistant to enzalutamide, abiraterone, apalutamide, darolutamide, docetaxel, and olaparib, respectively. These models are instrumental for analyzing gene expression and assessing responses to various treatments. Our findings reveal distinct cross-resistance characteristics among NGAT-resistant cell sublines. Specifically, resistance to enzalutamide induces resistance to abiraterone and vice versa, while maintaining sensitivity to taxanes and olaparib. Conversely, cells with acquired resistance to docetaxel exhibit cross-resistance to both cabazitaxel and olaparib but retain sensitivity to NGATs like enzalutamide and abiraterone. OlapR cells, significantly resistant to olaparib compared to parental cells, are still responsive to NGATs and docetaxel. Moreover, OlapR models display cross-resistance to other clinically relevant PARP inhibitors, including rucaparib, niraparib, and talazoparib. RNA-sequencing analyses have revealed a complex network of altered gene expressions that influence signaling pathways, energy metabolism, and apoptotic signaling, pivotal to cancers evolution and progression. The data indicate that resis

Rolling bearings are the most important components in the transmission system of coal mining machinery, and their operating condition significantly impacts the entire mechanical and electrical equipment. Therefore, the fault diagnosis of rolling bearing can effectively ensure the operation reliability of equipment. Given the strong noise, coal impact, and other interference, the vibration signal of the rolling bearing cannot be effectively decomposed, and the fault identification efficiency is low. According to the method based on vibration analysis, this article proposes a rolling bearing fault diagnosis method based on ensemble local mean decomposition (ELMD) hybrid feature extraction and wavelet neural network. ELMD is used to solve the problem of modal aliasing in local mean decomposition (LMD), which can improve the efficiency of LMD. Quantitatively extracting the mixed features of each component and introducing a wavelet neural network for fault type recognition. The experimental results demonstrate that the proposed method has a high accuracy in fault recognition and is an effective fault diagnosis method.

Nuclei classification provides valuable information for histopathology image analysis. However, the large variations in the appearance of different nuclei types cause difficulties in identifying nuclei. Most neural network based methods are affected by the local receptive field of convolutions, and pay less attention to the spatial distribution of nuclei or the irregular contour shape of a nucleus. In this paper, we first propose a novel polygon-structure feature learning mechanism that transforms a nucleus contour into a sequence of points sampled in order, and employ a recurrent neural network that aggregates the sequential change in distance between key points to obtain learnable shape features. Next, we convert a histopathology image into a graph structure with nuclei as nodes, and build a graph neural network to embed the spatial distribution of nuclei into their representations. To capture the correlations between the categories of nuclei and their surrounding tissue patterns, we further introduce edge features that are defined as the background textures between adjacent nuclei. Lastly, we integrate both polygon and graph structure learning mechanisms into a whole framework that can extract intra and inter-nucleus structural characteristics for nuclei classification. Experimental results show that the proposed framework achieves significant improvements compared to the state-of-the-art methods.

Qin Qian,* Yu-Zhen Wang,* Lian-Di Kan,* Jie Chen, Chen Wang, Gang Han, Liu-Cheng Li, Wei-Jian Lou Department of Pharmacy, Sir Run Run Shaw Hospital, School of Medicine, Zhejiang University, Hangzhou, 310016, People’s Republic of China*These authors contributed equally to this workCorrespondence: Liu-Cheng Li; Wei-Jian Lou, Department of Pharmacy, Sir Run Run Shaw Hospital, School of Medicine, Zhejiang University, Hangzhou, 310016, People’s Republic of China, Tel/Fax +86-571-8600-6803, Email 3415116@zju.edu.cn; 13588708537@163.comBackground: Pediatric hypertension become an early marker of cardiovascular diseases, but their antihypertensive drug use patterns are rarely known.Purpose: To investigate the epidemiological characteristics of pediatric hypertension and the use of antihypertensive drugs in the real world in China.Methods: In this study, the demographic, diagnosis, and medication prescription data including the antihypertensive drug types and comorbidities, were analyzed. The antihypertensive drugs use were evaluated according to the Chinese guidelines for hypertension.Results: 1301 prescriptions (number of visits) containing 1880 antihypertensive medical orders were collected. The average number of antihypertensive drugs per prescription was 1.45 (± 0.75). The patients aged 16 to 18 (70.18%) accounted for the highest proportion. Kidney diseases (33.28%) were the most common comorbidities. Calcium channel blocker (CCB), angiotensin II receptor blocker (ARB), and β receptor blocker (BB) were the most used antihypertensive drugs. The most frequent monotherapy was CCB, while that of two and three drugs combination were ARB+CCB and ARB+BB+CCB, respectively. Metoprolol (11.44%), nifedipine (10.64%), amlodipine (10.59%), valsartan (6.12%) were the most commonly used antihypertensive drugs. The utilization rate of fixed compound preparations was 7.34%. However, the percentage of recommended antihypertensive drugs was just 14.20

With the prosperity of Internet of Things, a large number of heterogeneous wireless devices share the same unlicensed spectrum, leading to severe cross-technology interference (CTI). Especially, the transmission power asymmetry of heterogeneous devices will further deteriorate this problem, as the high-power devices (like WiFi) always corrupt the ongoing transmissions of low-power devices (like ZigBee), because the energy of the ZigBee signal perceived by WiFi is too weak to achieve the CCA (Clear Channel Assessment) threshold and the channel is considered to be idle. This paper proposes an enhanced CCA (E-CCA) mechanism to mitigate CTI in WiFi and ZigBee coexistence networks. E-CCA contains ZShark which can identify signals within a tolerable time duration. It also contains a MAC layer design, with which a WiFi device can still determine the channel to be busy when the detected energy is below the CCA threshold while a ZigBee signal is identified, thus to avoid CTI to ZigBee transmissions. We set up a testbed based on USRP B200 and TelosB to collect data and evaluate the performance of ZShark. We further evaluate the performance of E-CCA through both theoretical analysis and simulations on NS-3. The results show significant performance improvement of ZigBee.

Nuclei segmentation is a fundamental but challenging task in the quantitative analysis of histopathology images. Although fully-supervised deep learning-based methods have made significant progress, a large number of labeled images are required to achieve great segmentation performance. Considering that manually labeling all nuclei instances for a dataset is inefficient, obtaining a large-scale human-annotated dataset is time-consuming and labor-intensive. Therefore, augmenting a dataset with only a few labeled images to improve the segmentation performance is of significant research and application value. In this paper, we introduce the first diffusion-based augmentation method for nuclei segmentation. The idea is to synthesize a large number of labeled images to facilitate training the segmentation model. To achieve this, we propose a two-step strategy. In the first step, we train an unconditional diffusion model to synthesize the Nuclei Structure that is defined as the representation of pixel-level semantic and distance transform. Each synthetic nuclei structure will serve as a constraint on histopathology image synthesis and is further post-processed to be an instance map. In the second step, we train a conditioned diffusion model to synthesize histopathology images based on nuclei structures. The synthetic histopathology images paired with synthetic instance maps will be added to the real dataset for training the segmentation model. The experimental results show that by augmenting 10% labeled real dataset with synthetic samples, one can achieve comparable segmentation results with the fully-supervised baseline. The code is released in: https://github.com/lhaof/Nudiff, Comment: MICCAI 2023, released code: https://github.com/lhaof/Nudiff

Cell segmentation for multi-modal microscopy images remains a challenge due to the complex textures, patterns, and cell shapes in these images. To tackle the problem, we first develop an automatic cell classification pipeline to label the microscopy images based on their low-level image characteristics, and then train a classification model based on the category labels. Afterward, we train a separate segmentation model for each category using the images in the corresponding category. Besides, we further deploy two types of segmentation models to segment cells with roundish and irregular shapes respectively. Moreover, an efficient and powerful backbone model is utilized to enhance the efficiency of our segmentation model. Evaluated on the Tuning Set of NeurIPS 2022 Cell Segmentation Challenge, our method achieves an F1-score of 0.8795 and the running time for all cases is within the time tolerance., Comment: The second place in NeurIPS 2022 cell segmentation challenge (https://neurips22-cellseg.grand-challenge.org/), released code: https://github.com/lhaof/CellSeg

Cell segmentation is a critical step for quantitative single-cell analysis in microscopy images. Existing cell segmentation methods are often tailored to specific modalities or require manual interventions to specify hyper-parameters in different experimental settings. Here, we present a multi-modality cell segmentation benchmark, comprising over 1500 labeled images derived from more than 50 diverse biological experiments. The top participants developed a Transformer-based deep-learning algorithm that not only exceeds existing methods but can also be applied to diverse microscopy images across imaging platforms and tissue types without manual parameter adjustments. This benchmark and the improved algorithm offer promising avenues for more accurate and versatile cell analysis in microscopy imaging., Comment: NeurIPS22 Cell Segmentation Challenge: https://neurips22-cellseg.grand-challenge.org/ . Nature Methods (2024)

BackgroundTreatment-emergent neuroendocrine prostate cancer (NEPC) after androgen receptor (AR) targeted therapies is an aggressive variant of prostate cancer with an unfavorable prognosis. The underlying mechanisms for early neuroendocrine differentiation are poorly defined and diagnostic and prognostic biomarkers are needed.MethodsWe performed transcriptomic analysis on the enzalutamide-resistant prostate cancer cell line C4-2B MDVR and NEPC patient databases to identify neural lineage signature (NLS) genes. Correlation of NLS genes with clinicopathologic features was determined. Cell viability was determined in C4-2B MDVR and H660 cells after knocking down ARHGEF2 using siRNA. Organoid viability of patient-derived xenografts was measured after knocking down ARHGEF2.ResultsWe identify a 95-gene NLS representing the molecular landscape of neural precursor cell proliferation, embryonic stem cell pluripotency, and neural stem cell differentiation, which may indicate an early or intermediate stage of neuroendocrine differentiation. These NLS genes positively correlate with conventional neuroendocrine markers such as chromogranin and synaptophysin, and negatively correlate with AR and AR target genes in advanced prostate cancer. Differentially expressed NLS genes stratify small-cell NEPC from prostate adenocarcinoma, which are closely associated with clinicopathologic features such as Gleason Score and metastasis status. Higher ARGHEF2, LHX2, and EPHB2 levels among the 95 NLS genes correlate with a shortened survival time in NEPC patients. Furthermore, downregulation of ARHGEF2 gene expression suppresses cell viability and markers of neuroendocrine differentiation in enzalutamide-resistant and neuroendocrine cells.ConclusionsThe 95 neural lineage gene signatures capture an early molecular shift toward neuroendocrine differentiation, which could stratify advanced prostate cancer patients to optimize clinical treatment and serve as a source of potential therapeutic targe

PARP inhibition represents the dawn of precision medicine for treating prostate cancer. Despite this advance, questions remain regarding the use of PARP inhibitors (PARPi) for the treatment of this disease, including (i) how specifically do PARPi-sensitive tumor cells respond to treatment, and (ii) how does PARPi resistance develop? To address these questions, we characterized response to olaparib in sensitive LNCaP and C4-2B cells and developed two olaparib-resistant derivative cell line models from each, termed LN-OlapR and 2B-OlapR, respectively. OlapR cells possess distinct morphology from parental cells and display robust resistance to olaparib and other clinically relevant PARPis, including rucaparib, niraparib, and talazoparib. In LNCaP and C4-2B cells, we found that olaparib induces massive DNA damage, leading to activation of the G2-M checkpoint, activation of p53, and cell-cycle arrest. Furthermore, our data suggest that G2-M checkpoint activation leads to both cell death and senescence associated with p21 activity. In contrast, both LN-OlapR and 2B-OlapR cells do not arrest at G2-M and display a markedly blunted response to olaparib treatment. Interestingly, both OlapR cell lines harbor increased DNA damage relative to parental cells, suggesting that OlapR cells accumulate and manage persistent DNA damage during acquisition of resistance, likely through augmenting DNA repair capacity. Further impairing DNA repair through CDK1 inhibition enhances DNA damage, induces cell death, and sensitizes OlapR cells to olaparib treatment. Our data together further our understanding of PARPi treatment and provide a cellular platform system for the study of response and resistance to PARP inhibition.

Resistance to androgen receptor (AR) targeted therapies remains as the main reason for most prostate cancer related deaths. Lineage plasticity resulting in altered, treatment insensitive prostate tumor cell phenotypes such neuroendocrine differentiated prostate cancer is a common manifestation within resistant tumors upon AR-targeted therapies. The mechanisms responsible for lineage plasticity in prostate cancer remain incompletely understood. Here we demonstrate that the enzalutamide resistant MDVR cell line possesses lineage plastic characteristics associated with overexpression of the Wnt transporter Wntless (WLS). Furthermore, we present evidence that overexpression of WLS is common in varying cell line models of lineage plastic prostate cancer, is higher in neuroendocrine patient samples, and positively correlates with the neuroendocrine marker SYP in clinical data. Targeting WLS in lineage plastic cellular models reduces viability and represses lineage plasticity associated gene expression. Our study provides insight into the importance of WLS to the development of lethal resistant prostate cancer and provides a potential target for the treatment of advanced disease.

The next-generation antiandrogen drugs such as enzalutamide and abiraterone extend survival times and improve quality of life in patients with advanced prostate cancer. However, resistance to both drugs occurs frequently through mechanisms that are incompletely understood. Wnt signaling, particularly through Wnt5a, plays vital roles in promoting prostate cancer progression and induction of resistance to enzalutamide and abiraterone. Development of novel strategies targeting Wnt5a to overcome resistance is an urgent need. In this study, we demonstrated that Wnt5a/FZD2-mediated noncanonical Wnt pathway is overexpressed in enzalutamide-resistant prostate cancer. In patient databases, both the levels of Wnt5a and FZD2 expression are upregulated upon the development of enzalutamide resistance and correlate with higher Gleason score, biochemical recurrence, and metastatic status, and with shortened disease-free survival duration. Blocking Wnt5a/FZD2 signal transduction not only diminished the activation of noncanonical Wnt signaling pathway, but also suppressed the constitutively activated androgen receptor (AR) and AR variants. Furthermore, we developed a novel bioengineered BERA-Wnt5a siRNA construct and demonstrated that inhibition of Wnt5a expression by the BERA-Wnt5a siRNA significantly suppressed tumor growth and enhanced enzalutamide treatment in vivo. These results indicate that Wnt5a/FZD2 signal pathway plays a critical role in promoting enzalutamide resistance, and targeting this pathway by BERA-Wnt5a siRNA can be developed as a potential therapy to treat advanced prostate cancer.

Recently deep neural networks, which require a large amount of annotated samples, have been widely applied in nuclei instance segmentation of H\&E stained pathology images. However, it is inefficient and unnecessary to label all pixels for a dataset of nuclei images which usually contain similar and redundant patterns. Although unsupervised and semi-supervised learning methods have been studied for nuclei segmentation, very few works have delved into the selective labeling of samples to reduce the workload of annotation. Thus, in this paper, we propose a novel full nuclei segmentation framework that chooses only a few image patches to be annotated, augments the training set from the selected samples, and achieves nuclei segmentation in a semi-supervised manner. In the proposed framework, we first develop a novel consistency-based patch selection method to determine which image patches are the most beneficial to the training. Then we introduce a conditional single-image GAN with a component-wise discriminator, to synthesize more training samples. Lastly, our proposed framework trains an existing segmentation model with the above augmented samples. The experimental results show that our proposed method could obtain the same-level performance as a fully-supervised baseline by annotating less than 5% pixels on some benchmarks., Comment: IEEE TMI 2022, Released code: https://github.com/lhaof/NuSeg

Client selection schemes are widely adopted to handle the communication-efficient problems in recent studies of Federated Learning (FL). However, the large variance of the model updates aggregated from the randomly-selected unrepresentative subsets directly slows the FL convergence. We present a novel clustering-based client selection scheme to accelerate the FL convergence by variance reduction. Simple yet effective schemes are designed to improve the clustering effect and control the effect fluctuation, therefore, generating the client subset with certain representativeness of sampling. Theoretically, we demonstrate the improvement of the proposed scheme in variance reduction. We also present the tighter convergence guarantee of the proposed method thanks to the variance reduction. Experimental results confirm the exceed efficiency of our scheme compared to alternatives., Comment: arXiv admin note: text overlap with arXiv:2201.05762

Client selection strategies are widely adopted to handle the communication-efficient problem in recent studies of Federated Learning (FL). However, due to the large variance of the selected subset's update, prior selection approaches with a limited sampling ratio cannot perform well on convergence and accuracy in heterogeneous FL. To address this problem, in this paper, we propose a novel stratified client selection scheme to reduce the variance for the pursuit of better convergence and higher accuracy. Specifically, to mitigate the impact of heterogeneity, we develop stratification based on clients' local data distribution to derive approximate homogeneous strata for better selection in each stratum. Concentrating on a limited sampling ratio scenario, we next present an optimized sample size allocation scheme by considering the diversity of stratum's variability, with the promise of further variance reduction. Theoretically, we elaborate the explicit relation among different selection schemes with regard to variance, under heterogeneous settings, we demonstrate the effectiveness of our selection scheme. Experimental results confirm that our approach not only allows for better performance relative to state-of-the-art methods but also is compatible with prevalent FL algorithms., Comment: there is something wrong in the experiment

Targeting androgen signaling with the second-generation anti-androgen drugs, such as enzalutamide (Enza), abiraterone (Abi), apalutamide (Apal), and darolutamide (Daro), is the mainstay for the treatment of castration-resistant prostate cancer (CRPC). While these treatments are effective initially, resistance occurs frequently. Continued expression of androgen receptor (AR) and its variants such as AR-V7 despite AR-targeted therapy contributes to treatment resistance and cancer progression in advanced CRPC patients. This highlights the need for new strategies blocking continued AR signaling. Here, we identify a novel AR/AR-V7 degrader (ARVib) and found that ARVib effectively degrades AR/AR-V7 protein and attenuates AR/AR-V7 downstream target gene expression in prostate cancer cells. Mechanistically, ARVib degrades AR/AR-V7 protein through the ubiquitin-proteasome pathway mediated by HSP70/STUB1 machinery modulation. ARVib suppresses HSP70 expression and promotes STUB1 nuclear translocation, where STUB1 binds to AR/AR-V7 and promotes its ubiquitination and degradation. ARVib significantly inhibits resistant prostate tumor growth and improves enzalutamide treatment in vitro and in vivo. These data suggest that ARVib has potential for development as an AR/AR-V7 degrader to treat resistant CRPC.

Targeting androgen signaling with the second-generation anti-androgen drugs, such as enzalutamide (Enza), abiraterone (Abi), apalutamide (Apal), and darolutamide (Daro), is the mainstay for the treatment of castration-resistant prostate cancer (CRPC). While these treatments are effective initially, resistance occurs frequently. Continued expression of androgen receptor (AR) and its variants such as AR-V7 despite AR-targeted therapy contributes to treatment resistance and cancer progression in advanced CRPC patients. This highlights the need for new strategies blocking continued AR signaling. Here, we identify a novel AR/AR-V7 degrader (ARVib) and found that ARVib effectively degrades AR/AR-V7 protein and attenuates AR/AR-V7 downstream target gene expression in prostate cancer cells. Mechanistically, ARVib degrades AR/AR-V7 protein through the ubiquitin-proteasome pathway mediated by HSP70/STUB1 machinery modulation. ARVib suppresses HSP70 expression and promotes STUB1 nuclear translocation, where STUB1 binds to AR/AR-V7 and promotes its ubiquitination and degradation. ARVib significantly inhibits resistant prostate tumor growth and improves enzalutamide treatment in vitro and in vivo. These data suggest that ARVib has potential for development as an AR/AR-V7 degrader to treat resistant CRPC.

Docetaxel and cabazitaxel-based taxane chemotherapy are critical components in the management of advanced prostate cancer. However, their efficacy is hindered due to de novo presentation with or the development of resistance. Characterizing models of taxane-resistant prostate cancer will lead to creation of strategies to overcome insensitivity. We have previously characterized docetaxel-resistant C4-2B and DU145 cell line derivatives, TaxR and DU145-DTXR, respectively. In the present study, we characterize cabazitaxel-resistant derivative cell lines created from chronic cabazitaxel exposure of TaxR and DU145-DTXR cells, CabR and CTXR, respectively. We show that CabR and CTXR cells are robustly resistant to both taxanes but retain sensitivity to antiandrogens. Both CabR and CTXR cells possess increased expression of ABCB1, which is shown to mediate resistance to treatment. Interestingly, we also present evidence for coordinated overexpression of additional genes present within the 7q21.12 gene locus where ABCB1 resides. This locus, known as the ABCB1 amplicon, has been demonstrated to be amplified in multidrug-resistant tumor cells, but little is known regarding its role in prostate cancer. We show that two ABCB1-amplicon genes other than ABCB1, RUNDC3B and DBF4, promote cellular viability and treatment resistance in taxane-resistant prostate cancer models. We present evidence that coordinated amplification of ABCB1-amplicon genes is common in a subset of prostate cancer patients. These data together suggest that ABCB1-amplicon activation plays a critical role in taxane resistance.

Mobile and embedded platforms are increasingly required to efficiently execute computationally demanding DNNs across heterogeneous processing elements. At runtime, the available hardware resources to DNNs can vary considerably due to other concurrently running applications. The performance requirements of the applications could also change under different scenarios. To achieve the desired performance, dynamic DNNs have been proposed in which the number of channels/layers can be scaled in real time to meet different requirements under varying resource constraints. However, the training process of such dynamic DNNs can be costly, since platform-aware models of different deployment scenarios must be retrained to become dynamic. This paper proposes Dynamic-OFA, a novel dynamic DNN approach for state-of-the-art platform-aware NAS models (i.e. Once-for-all network (OFA)). Dynamic-OFA pre-samples a family of sub-networks from a static OFA backbone model, and contains a runtime manager to choose different sub-networks under different runtime environments. As such, Dynamic-OFA does not need the traditional dynamic DNN training pipeline. Compared to the state-of-the-art, our experimental results using ImageNet on a Jetson Xavier NX show that the approach is up to 3.5x (CPU), 2.4x (GPU) faster for similar ImageNet Top-1 accuracy, or 3.8% (CPU), 5.1% (GPU) higher accuracy at similar latency., Comment: Accepted at CVPR ECV Workshop 2021

The next-generation antiandrogen drugs, XTANDI (enzalutamide), ZYTIGA (abiraterone acetate), ERLEADA (apalutamide) and NUBEQA (darolutamide) extend survival times and improve quality of life in patients with advanced prostate cancer. Despite these advances, resistance occurs frequently and there is currently no definitive cure for castration-resistant prostate cancer. Our previous studies identified that similar mechanisms of resistance to enzalutamide or abiraterone occur following treatment and cross-resistance exists between these therapies in advanced prostate cancer. Here, we show that enzalutamide- and abiraterone-resistant prostate cancer cells are further cross-resistant to apalutamide and darolutamide. Mechanistically, we have determined that the AKR1C3/AR-V7 axis confers this cross-resistance. Knockdown of AR-V7 in enzalutamide-resistant cells resensitize cells to apalutamide and darolutamide treatment. Furthermore, targeting AKR1C3 resensitizes resistant cells to apalutamide and darolutamide treatment through AR-V7 inhibition. Chronic apalutamide treatment in C4-2B cells activates the steroid hormone biosynthesis pathway and increases AKR1C3 expression, which confers resistance to enzalutamide, abiraterone, and darolutamide. In conclusion, our results suggest that apalutamide and darolutamide share similar resistant mechanisms with enzalutamide and abiraterone. The AKR1C3/AR-V7 complex confers cross-resistance to second-generation androgen receptor-targeted therapies in advanced prostate cancer.

PurposeMost patients with prostate cancer receiving enzalutamide or abiraterone develop resistance. Clinical evidence indicates that serum levels of dehydroepiandrosterone sulfate (DHEAS) and biologically active DHEA remain in the high range despite antiandrogen treatment. The conversion of DHEAS into DHEA by steroid sulfatase (STS) may contribute to sustained intracrine androgen synthesis. Here, we determine the contribution of STS to treatment resistance and explore the potential of targeting STS to overcome resistance in prostate cancer.Experimental designSTS expression was examined in patients and cell lines. In vitro, STS activity and expression were modulated using STS-specific siRNA or novel STS inhibitors (STSi). Cell growth, colony formation, androgen production, and gene expression were examined. RNA-sequencing analysis was conducted on VCaP cells treated with STSi. Mice were treated with STSis with or without enzalutamide to determine their effects in vivo.ResultsSTS is overexpressed in patients with castration-resistant prostate cancer (CRPC) and resistant cells. STS overexpression increases intracrine androgen synthesis, cell proliferation, and confers resistance to enzalutamide and abiraterone. Inhibition of STS using siRNA suppresses prostate cancer cell growth. Targeting STS activity using STSi inhibits STS activity, suppresses androgen receptor transcriptional activity, and reduces the growth of resistant C4-2B and VCaP prostate cancer cells. STSis significantly suppress resistant VCaP tumor growth, decrease serum PSA levels, and enhance enzalutamide treatment in vitro and in vivo.ConclusionsThese studies suggest that STS drives intracrine androgen synthesis and prostate cancer proliferation. Targeting STS represents a therapeutic strategy to treat CRPC and improve second-generation antiandrogen therapy.

Castration-resistant prostate cancer remains as an incurable disease. Exploiting DNA damage repair defects via inhibition of poly (ADP-ribose) polymerase (PARP) is becoming an attractive therapeutic option. The TOPARP-A clinical trial demonstrated that the PARP inhibitor olaparib may be an effective strategy for treating prostate cancer. However, several unanswered questions regarding the use of olaparib remain: 1) How do we best stratify patients for olaparib treatment? 2) Where do we place olaparib in the treatment sequence paradigm? 3) Is there cross-resistance between olaparib and currently used therapies? Here, we tested putative cross-resistance between current therapies and olaparib in treatment-resistant castration-resistant prostate cancer models. Docetaxel-resistant cells exhibited robust resistance to olaparib which could be attributed to blunted PARP trapping in response to olaparib treatment. Upregulated ABCB1 mediates cross-resistance between taxanes and olaparib, which can be overcome through decreasing ABCB1 expression or inhibiting ABCB1 using elacridar or enzalutamide. We also show that combining olaparib with enzalutamide is more effective in olaparib-sensitive cells than either single agent. Our results demonstrate that cross-resistance between olaparib and other therapies could blunt response to treatment and highlight the need to develop strategies to maximize olaparib efficacy.

Castration-resistant prostate cancer remains as an incurable disease. Exploiting DNA damage repair defects via inhibition of poly (ADP-ribose) polymerase (PARP) is becoming an attractive therapeutic option. The TOPARP-A clinical trial demonstrated that the PARP inhibitor olaparib may be an effective strategy for treating prostate cancer. However, several unanswered questions regarding the use of olaparib remain: 1) How do we best stratify patients for olaparib treatment? 2) Where do we place olaparib in the treatment sequence paradigm? 3) Is there cross-resistance between olaparib and currently used therapies? Here, we tested putative cross-resistance between current therapies and olaparib in treatment-resistant castration-resistant prostate cancer models. Docetaxel-resistant cells exhibited robust resistance to olaparib which could be attributed to blunted PARP trapping in response to olaparib treatment. Upregulated ABCB1 mediates cross-resistance between taxanes and olaparib, which can be overcome through decreasing ABCB1 expression or inhibiting ABCB1 using elacridar or enzalutamide. We also show that combining olaparib with enzalutamide is more effective in olaparib-sensitive cells than either single agent. Our results demonstrate that cross-resistance between olaparib and other therapies could blunt response to treatment and highlight the need to develop strategies to maximize olaparib efficacy.

The mechanisms resulting in resistance to next-generation antiandrogens in castration-resistant prostate cancer are incompletely understood. Numerous studies have determined that constitutively active androgen receptor (AR) signaling or full-length AR bypass mechanisms may contribute to the resistance. Previous studies established that AKR1C3 and AR-V7 play important roles in enzalutamide and abiraterone resistance. In the present study, we found that AKR1C3 increases AR-V7 expression in resistant prostate cancer cells through enhancing protein stability via activation of the ubiquitin-mediated proteasome pathway. AKR1C3 reprograms AR signaling in enzalutamide-resistant prostate cancer cells. In addition, bioinformatical analysis of indomethacin-treated resistant cells revealed that indomethacin significantly activates the unfolded protein response, p53, and apoptosis pathways, and suppresses cell-cycle, Myc, and AR/ARV7 pathways. Targeting AKR1C3 with indomethacin significantly decreases AR/AR-V7 protein expression in vitro and in vivo through activation of the ubiquitin-mediated proteasome pathway. Our results suggest that the AKR1C3/AR-V7 complex collaboratively confers resistance to AR-targeted therapies in advanced prostate cancer.

BackgroundDe-regulation of Wnt signaling pathways has been shown to be associated with progression of castration-resistant prostate cancer and more recently, studies indicate that both canonical and non-canonical Wnt pathways may mediate resistance to anti-androgen therapies such as enzalutamide. However, the mechanisms by which Wnt signaling is altered in prostate cancer remain poorly understood. Wnt pathway function begins with Wnt biogenesis and secretion from Wnt signal sending cells. While previous studies have investigated downstream mechanisms of Wnt pathway alterations in prostate cancer, little is known on the role of Wnt secretion mediating proteins. Wntless (WLS) is thought to be essential for the secretion of all Wnts. In this study, we sought to understand the role of WLS in prostate cancer.MethodsRNA-seq and gene set enrichment analysis were used to understand expression profile changes in enzalutamide-resistant C4-2B-MDVR (MDVR) cells versus parental C4-2B cells. Quantitative-PCR and western blot were used to confirm RNA-seq data and to assess expression changes of gene targets of interest. Rv1 cells were used as a separate model of enzalutamide-resistant prostate cancer. RNAi was used to inhibit WLS expression. Cell viability, colony formation, and PSA ELISA assays were used to assess cell growth and survival.ResultsTranscriptomic profiling revealed enriched Wnt pathway signatures in MDVR versus parental C4-2B cells. We further show that MDVR cells upregulate Wnt signaling and overexpress WLS. Inhibition of WLS decreases Wnt signaling, markedly attenuates prostate cancer cell viability, induces apoptosis, and re-sensitizes enzalutamide-resistant cells to enzalutamide treatment. Lastly, we show that inhibition of WLS reduces AR and AR-variants expression and downstream signaling.ConclusionsOur findings support a role for WLS in the progression of prostate cancer to a treatment-resistant state. Further efforts to understand Wnt signaling pathway altera

Excessive alcohol consumption is a worldwide social problem that has greatly contributed to the global burden of disease, disability and death. Overall volume of alcohol consumption and prevalence of alcohol-related problems in China have remained relatively low in comparison to many western countries until recent years. Since the liberal economic reforms of the early 1980s, China has witnessed an alarmingly increasing rate of alcohol consumption, and as a result, increasing incidence of alcohol-related injuries and morbidity. However, comprehensive alcohol policy and public health infrastructure to address the problems associated with these changes have not yet been established. Using data from the China Health and Nutrition Survey, this dissertation - comprised of three papers - utilizes quantitative methods to examine alcohol consumption behaviors in China, in order to identify alcohol policies and interventions that are both applicable to and appropriate for the Chinese context and to recommend next steps for alcohol control policy and intervention areas in China. The first paper explores the socio-demographic and other factors that are associated with alcohol consumption behaviors in order to identify populations that are at risk for problem alcohol use and that may be targeted for prevention/public health education programs. The second paper establishes evidence regarding alcohol consumption behaviors and its association with community-level alcohol access characteristics, such as proximity of alcohol outlets and price of different types of alcohol. The third examines the association between alcohol consumption and healthcare utilization, in order to identify health policy needs for persons at risk for the development of costly chronic diseases. The three principal conclusions from the three papers are: (1) there is strong evidence of a closing gender gap in problematic alcohol consumption behaviors between men and women - although men are still more likely to

Excessive alcohol consumption is a worldwide social problem that has greatly contributed to the global burden of disease, disability and death. Overall volume of alcohol consumption and prevalence of alcohol-related problems in China have remained relatively low in comparison to many western countries until recent years. Since the liberal economic reforms of the early 1980s, China has witnessed an alarmingly increasing rate of alcohol consumption, and as a result, increasing incidence of alcohol-related injuries and morbidity. However, comprehensive alcohol policy and public health infrastructure to address the problems associated with these changes have not yet been established. Using data from the China Health and Nutrition Survey, this dissertation - comprised of three papers - utilizes quantitative methods to examine alcohol consumption behaviors in China, in order to identify alcohol policies and interventions that are both applicable to and appropriate for the Chinese context and to recommend next steps for alcohol control policy and intervention areas in China. The first paper explores the socio-demographic and other factors that are associated with alcohol consumption behaviors in order to identify populations that are at risk for problem alcohol use and that may be targeted for prevention/public health education programs. The second paper establishes evidence regarding alcohol consumption behaviors and its association with community-level alcohol access characteristics, such as proximity of alcohol outlets and price of different types of alcohol. The third examines the association between alcohol consumption and healthcare utilization, in order to identify health policy needs for persons at risk for the development of costly chronic diseases. The three principal conclusions from the three papers are: (1) there is strong evidence of a closing gender gap in problematic alcohol consumption behaviors between men and women - although men are still more likely to

Protein homeostasis (proteostasis) is a potential mechanism that contributes to cancer cell survival and drug resistance. Constitutively active androgen receptor (AR) variants confer anti-androgen resistance in advanced prostate cancer. However, the role of proteostasis involved in next generation anti-androgen resistance and the mechanisms of AR variant regulation are poorly defined. Here we show that the ubiquitin-proteasome-system (UPS) is suppressed in enzalutamide/abiraterone resistant prostate cancer. AR/AR-V7 proteostasis requires the interaction of E3 ubiquitin ligase STUB1 and HSP70 complex. STUB1 disassociates AR/AR-V7 from HSP70, leading to AR/AR-V7 ubiquitination and degradation. Inhibition of HSP70 significantly inhibits prostate tumor growth and improves enzalutamide/abiraterone treatments through AR/AR-V7 suppression. Clinically, HSP70 expression is upregulated and correlated with AR/AR-V7 levels in high Gleason score prostate tumors. Our results reveal a novel mechanism of anti-androgen resistance via UPS alteration which could be targeted through inhibition of HSP70 to reduce AR-V7 expression and overcome resistance to AR-targeted therapies.

Current treatments for castration resistant prostate cancer (CRPC) largely fall into two classes: androgen receptor (AR)-targeted therapies such as the next-generation antiandrogen therapies (NGAT), enzalutamide and abiraterone, and taxanes such as docetaxel and cabazitaxel. Despite improvements in outcomes, patients still succumb to the disease due to the development of resistance. Further complicating the situation is lack of a well-defined treatment sequence and potential for cross-resistance between therapies. We have developed several models representing CRPC with acquired therapeutic resistance. Here, we utilized these models to assess putative cross-resistance between treatments. We find that resistance to enzalutamide induces resistance to abiraterone and vice versa, but resistance to neither alters sensitivity to taxanes. Acquired resistance to docetaxel induces cross-resistance to cabazitaxel but not to enzalutamide or abiraterone. Correlating responses with known mechanisms of resistance indicates that AR variants are associated with resistance to NGATs, whereas the membrane efflux protein ABCB1 is associated with taxane resistance. Mechanistic studies show that AR variant-7 (AR-v7) is involved in NGAT resistance but not resistance to taxanes. Our findings suggest the existence of intra cross-resistance within a drug class (i.e., within NGATs or within taxanes), whereas inter cross-resistance between drug classes does not develop. Furthermore, our data suggest that resistance mechanisms differ between drug classes. These results may have clinical implications by showing that treatments of one class can be sequenced with those of another, but caution should be taken when sequencing similar classed drugs. In addition, the development and use of biomarkers indicating resistance will improve patient stratification for treatment. Mol Cancer Ther; 17(10); 2197-205. ©2018 AACR.

The mmWave frequency band has been widely accepted as an ideal carrier for the next-generation ultra-dense small cell communications to achieve the ambitious objective of 1000-fold increase in network capacity, but such a novel architecture also invokes tremendous anxiety for operators regarding the planning, configuration, maintenance, optimization, and troubleshooting. SON, introduced about 10 years ago, aiming to affiliate network management through addressing complexity and decreasing cost in an automatic way, nowadays has been extensively considered the only viable way to enable small cell deployments; however, as a technology traditionally designed and standardized for LTE-based systems, the conventional paradigm will no longer be suitable for mmWavebased cellular networks, which contain some peculiar characteristics, such as directivity of signal transmission and sensitivity to blockage and mobility, differing from their low-frequency counterparts and thereby bringing numerous unprecedented challenges. To smoothly migrate toward the 5G era, the legacy SON campaign eagerly demands a thorough revolution to think over the new features and cope with the new problems by defining new functionalities and proposing new algorithms. It is important, but not easy. In this article, we share some preliminary insights about the mmWave-oriented proactive SON paradigm, hopefully spurring further research in this area and accelerating its practical application in 5G.

The mmWave frequency band has been widely accepted as an ideal carrier for the next-generation ultra-dense small cell communications to achieve the ambitious objective of 1000-fold increase in network capacity, but such a novel architecture also invokes tremendous anxiety for operators regarding the planning, configuration, maintenance, optimization, and troubleshooting. SON, introduced about 10 years ago, aiming to affiliate network management through addressing complexity and decreasing cost in an automatic way, nowadays has been extensively considered the only viable way to enable small cell deployments; however, as a technology traditionally designed and standardized for LTE-based systems, the conventional paradigm will no longer be suitable for mmWavebased cellular networks, which contain some peculiar characteristics, such as directivity of signal transmission and sensitivity to blockage and mobility, differing from their low-frequency counterparts and thereby bringing numerous unprecedented challenges. To smoothly migrate toward the 5G era, the legacy SON campaign eagerly demands a thorough revolution to think over the new features and cope with the new problems by defining new functionalities and proposing new algorithms. It is important, but not easy. In this article, we share some preliminary insights about the mmWave-oriented proactive SON paradigm, hopefully spurring further research in this area and accelerating its practical application in 5G.

Protein homeostasis (proteostasis) is a potential mechanism that contributes to cancer cell survival and drug resistance. Constitutively active androgen receptor (AR) variants confer anti-androgen resistance in advanced prostate cancer. However, the role of proteostasis involved in next generation anti-androgen resistance and the mechanisms of AR variant regulation are poorly defined. Here we show that the ubiquitin-proteasome-system (UPS) is suppressed in enzalutamide/abiraterone resistant prostate cancer. AR/AR-V7 proteostasis requires the interaction of E3 ubiquitin ligase STUB1 and HSP70 complex. STUB1 disassociates AR/AR-V7 from HSP70, leading to AR/AR-V7 ubiquitination and degradation. Inhibition of HSP70 significantly inhibits prostate tumor growth and improves enzalutamide/abiraterone treatments through AR/AR-V7 suppression. Clinically, HSP70 expression is upregulated and correlated with AR/AR-V7 levels in high Gleason score prostate tumors. Our results reveal a novel mechanism of anti-androgen resistance via UPS alteration which could be targeted through inhibition of HSP70 to reduce AR-V7 expression and overcome resistance to AR-targeted therapies.

Current treatments for castration resistant prostate cancer (CRPC) largely fall into two classes: androgen receptor (AR)-targeted therapies such as the next-generation antiandrogen therapies (NGAT), enzalutamide and abiraterone, and taxanes such as docetaxel and cabazitaxel. Despite improvements in outcomes, patients still succumb to the disease due to the development of resistance. Further complicating the situation is lack of a well-defined treatment sequence and potential for cross-resistance between therapies. We have developed several models representing CRPC with acquired therapeutic resistance. Here, we utilized these models to assess putative cross-resistance between treatments. We find that resistance to enzalutamide induces resistance to abiraterone and vice versa, but resistance to neither alters sensitivity to taxanes. Acquired resistance to docetaxel induces cross-resistance to cabazitaxel but not to enzalutamide or abiraterone. Correlating responses with known mechanisms of resistance indicates that AR variants are associated with resistance to NGATs, whereas the membrane efflux protein ABCB1 is associated with taxane resistance. Mechanistic studies show that AR variant-7 (AR-v7) is involved in NGAT resistance but not resistance to taxanes. Our findings suggest the existence of intra cross-resistance within a drug class (i.e., within NGATs or within taxanes), whereas inter cross-resistance between drug classes does not develop. Furthermore, our data suggest that resistance mechanisms differ between drug classes. These results may have clinical implications by showing that treatments of one class can be sequenced with those of another, but caution should be taken when sequencing similar classed drugs. In addition, the development and use of biomarkers indicating resistance will improve patient stratification for treatment. Mol Cancer Ther; 17(10); 2197-205. ©2018 AACR.

The mmWave frequency band has been widely accepted as an ideal carrier for the next-generation ultra-dense small cell communications to achieve the ambitious objective of 1000-fold increase in network capacity, but such a novel architecture also invokes tremendous anxiety for operators regarding the planning, configuration, maintenance, optimization, and troubleshooting. SON, introduced about 10 years ago, aiming to affiliate network management through addressing complexity and decreasing cost in an automatic way, nowadays has been extensively considered the only viable way to enable small cell deployments; however, as a technology traditionally designed and standardized for LTE-based systems, the conventional paradigm will no longer be suitable for mmWavebased cellular networks, which contain some peculiar characteristics, such as directivity of signal transmission and sensitivity to blockage and mobility, differing from their low-frequency counterparts and thereby bringing numerous unprecedented challenges. To smoothly migrate toward the 5G era, the legacy SON campaign eagerly demands a thorough revolution to think over the new features and cope with the new problems by defining new functionalities and proposing new algorithms. It is important, but not easy. In this article, we share some preliminary insights about the mmWave-oriented proactive SON paradigm, hopefully spurring further research in this area and accelerating its practical application in 5G.

Abiraterone suppresses intracrine androgen synthesis via inhibition of CYP17A1. However, clinical evidence suggests that androgen synthesis is not fully inhibited by abiraterone and the sustained androgen production may lead to disease relapse. In the present study, we identified AKR1C3, an important enzyme in the steroidogenesis pathway, as a critical mechanism driving resistance to abiraterone through increasing intracrine androgen synthesis and enhancing androgen signaling. We found that overexpression of AKR1C3 confers resistance to abiraterone while downregulation of AKR1C3 resensitizes resistant cells to abiraterone treatment. In abiraterone-resistant prostate cancer cells, AKR1C3 is overexpressed and the levels of intracrine androgens are elevated. In addition, AKR1C3 activation increases intracrine androgen synthesis and enhances androgen receptor (AR) signaling via activating AR transcriptional activity. Treatment of abiraterone-resistant cells with indomethacin, an AKR1C3 inhibitor, overcomes resistance and enhances abiraterone therapy both in vitro and in vivo by reducing the levels of intracrine androgens and diminishing AR transcriptional activity. These results demonstrate that AKR1C3 activation is a critical mechanism of resistance to abiraterone through increasing intracrine androgen synthesis and enhancing androgen signaling. Furthermore, this study provides a preclinical proof-of-principle for clinical trials investigating the combination of targeting AKR1C3 using indomethacin with abiraterone for advanced prostate cancer. Mol Cancer Ther; 16(1); 35-44. ©2016 AACR.

BackgroundDocetaxel is one of the primary drugs used for treating castration resistant prostate cancer (CRPC). Unfortunately, over time patients invariably develop resistance to docetaxel therapy and their disease will continue to progress. The mechanisms by which resistance develops are still incompletely understood. This study seeks to determine the involvement of miRNAs, specifically miR-181a, in docetaxel resistance in CRPC.MethodsReal-time PCR was used to measure miR-181a expression in parental and docetaxel resistant C4-2B and DU145 cells (TaxR and DU145-DTXR). miR-181a expression was modulated in parental or docetaxel resistant cells by transfecting them with miR-181a mimics or antisense, respectively. Following transfection, cell number was determined after 48 h with or without docetaxel. Cross resistance to cabazitaxel induced by miR-181a was also determined. Western blots were used to determine ABCB1 protein expression and rhodamine assays used to assess activity. Phospho-p53 expression was assessed by Western blot and apoptosis was measured by ELISA in C4-2B TaxR and PC3 cells with inhibited or overexpressed miR-181a expression with or without docetaxel.ResultsmiR-181a is significantly overexpressed in TaxR and DU145-DTXR cells compared to parental cells. Overexpression of miR-181a in parental cells confers docetaxel and cabazitaxel resistance and knockdown of miR-181a in TaxR cells re-sensitizes them to treatment with both docetaxel and cabazitaxel. miR-181a was not observed to impact ABCB1 expression or activity, a protein which was previously demonstrated to be highly involved in docetaxel resistance. Knockdown of miR-181a in TaxR cells induced phospho-p53 expression. Furthermore, miR-181a knockdown alone induced apoptosis in TaxR cells which could be further enhanced by the addition of DTX.ConclusionsOverexpression of mir-181a in prostate cancer cells contributes to their resistance to docetaxel and cabazitaxel and inhibition of mir-181a expression ca

Activation of the androgen receptor (AR) and its splice variants is linked to advanced prostate cancer and drives resistance to antiandrogens. The roles of AR and AR variants in the development of resistance to androgen deprivation therapy (ADT) and bicalutamide treatment, however, are still incompletely understood. To determine whether AR variants play a role in bicalutamide resistance, we developed bicalutamide-resistant LNCaP cells (LNCaP-BicR) and found that these resistant cells express significantly increased levels of AR variants, particularly AR-V7, both at the mRNA and protein levels. Exogenous expression of AR-V7 in bicalutamide-sensitive LNCaP cells confers resistance to bicalutamide treatment. Knockdown of AR-V7 in bicalutamide- and enzalutamide-resistant CWR22Rv1, enzalutamide-resistant C4-2B (C4-2B MDVR), and LNCaP-BicR cells reversed bicalutamide resistance. Niclosamide, a potent inhibitor of AR variants, significantly enhanced bicalutamide treatment. Niclosamide and bicalutamide combination treatment not only suppressed AR and AR variants expression and inhibited their recruitment to the PSA promoter, but also significantly induced apoptosis in bicalutamide- and enzalutamide-resistant CWR22Rv1 and C4-2B MDVR cells. In addition, combination of niclosamide with bicalutamide inhibited the growth of enzalutamide-resistant tumors. In summary, our results demonstrate that AR variants, particularly AR-V7, drive bicalutamide resistance and that targeting AR-V7 with niclosamide can resensitize bicalutamide-resistant cells to bicalutamide treatment. Furthermore, combination of niclosamide with bicalutamide inhibits enzalutamide resistant tumor growth, suggesting that the combination of niclosamide and bicalutamide could be a potential cost-effective strategy to treat advanced prostate cancer in patients, including those who fail to respond to enzalutamide therapy. Mol Cancer Ther; 16(8); 1521-30. ©2017 AACR.

Advancements in research have added several new therapies for castration-resistant prostate cancer (CRPC), greatly augmenting our ability to treat patients. However, CRPC remains an incurable disease due to the development of therapeutic resistance and the existence of cross-resistance between available therapies. Understanding the interplay between different treatments will lead to improved sequencing and the creation of combinations that overcome resistance and prolong survival. Whether there exists cross-resistance between docetaxel and the next-generation taxane cabazitaxel is poorly understood. In this study, we use C4-2B and DU145 derived docetaxel-resistant cell lines to test response to cabazitaxel. Our results demonstrate that docetaxel resistance confers cross-resistance to cabazitaxel. We show that increased ABCB1 expression is responsible for cross-resistance to cabazitaxel and that inhibition of ABCB1 function through the small-molecule inhibitor elacridar resensitizes taxane-resistant cells to treatment. In addition, the antiandrogens bicalutamide and enzalutamide, previously demonstrated to be able to resensitize taxane-resistant cells to docetaxel through inhibition of ABCB1 ATPase activity, are also able to resensitize resistant cells to cabazitaxel treatment. Finally, we show that resensitization using an antiandrogen is far more effective in combination with cabazitaxel than docetaxel. Collectively, these results address key concerns in the field, including that of cross-resistance between taxanes and highlighting a mechanism of cabazitaxel resistance involving ABCB1. Furthermore, these preclinical studies suggest the potential in using combinations of antiandrogens with cabazitaxel for increased effect in treating advanced CRPC. Mol Cancer Ther; 16(10); 2257-66. ©2017 AACR.

Prostate cancer remains dependent on androgen receptor signaling even after castration. Aberrant androgen receptor signaling in castration-resistant prostate cancer is mediated by mechanisms such as alterations in the androgen receptor and activation of interacting signaling pathways. Clinical evidence confirms that resistance to the next-generation antiandrogen, enzalutamide, may be mediated to a large extent by alternative splicing of the androgen receptor to generate constitutively active splice variants such as AR-V7. The splice variants AR-V7 and ARv567es have been implicated in the resistance to not only enzalutamide, but also to abiraterone and other conventional therapeutics such as taxanes. Numerous studies, including ours, suggest that splicing factors such as hnRNPA1 promote the generation of AR-V7, thus contributing to enzalutamide resistance in prostate cancer cells. In the present study, we discovered that quercetin, a naturally occurring polyphenolic compound, reduces the expression of hnRNPA1, and consequently, that of AR-V7. The suppression of AR-V7 by quercetin resensitizes enzalutamide-resistant prostate cancer cells to treatment with enzalutamide. Our results indicate that quercetin downregulates hnRNPA1 expression, downregulates the expression of AR-V7, antagonizes androgen receptor signaling, and resensitizes enzalutamide-resistant prostate cancer cells to enzalutamide treatment in vivo in mouse xenografts. These findings demonstrate that suppressing the alternative splicing of the androgen receptor may have important implications in overcoming the resistance to next-generation antiandrogen therapy. Mol Cancer Ther; 16(12); 2770-9. ©2017 AACR.

Considerable evidence from both clinical and experimental studies suggests that androgen receptor variants, particularly androgen receptor variant 7 (AR-V7), are critical in the induction of resistance to enzalutamide and abiraterone. In this study, we investigated the role of AR-V7 in the cross-resistance of enzalutamide and abiraterone and examined if inhibition of AR-V7 can improve abiraterone treatment response. We found that enzalutamide-resistant cells are cross-resistant to abiraterone, and that AR-V7 confers resistance to abiraterone. Knock down of AR-V7 by siRNA in abiraterone resistant CWR22Rv1 and C4-2B MDVR cells restored their sensitivity to abiraterone, indicating that AR-V7 is involved in abiraterone resistance. Abiraterone resistant prostate cancer cells generated by chronic treatment with abiraterone showed enhanced AR-V7 protein expression. Niclosamide, an FDA-approved antihelminthic drug that has been previously identified as a potent inhibitor of AR-V7, re-sensitizes resistant cells to abiraterone treatment in vitro and in vivo. In summary, this preclinical study suggests that overexpression of AR-V7 contributes to resistance to abiraterone, and supports the development of combination of abiraterone with niclosamide as a potential treatment for advanced castration resistant prostate cancer.

Considerable evidence from both clinical and experimental studies suggests that androgen receptor variants, particularly androgen receptor variant 7 (AR-V7), are critical in the induction of resistance to enzalutamide and abiraterone. In this study, we investigated the role of AR-V7 in the cross-resistance of enzalutamide and abiraterone and examined if inhibition of AR-V7 can improve abiraterone treatment response. We found that enzalutamide-resistant cells are cross-resistant to abiraterone, and that AR-V7 confers resistance to abiraterone. Knock down of AR-V7 by siRNA in abiraterone resistant CWR22Rv1 and C4-2B MDVR cells restored their sensitivity to abiraterone, indicating that AR-V7 is involved in abiraterone resistance. Abiraterone resistant prostate cancer cells generated by chronic treatment with abiraterone showed enhanced AR-V7 protein expression. Niclosamide, an FDA-approved antihelminthic drug that has been previously identified as a potent inhibitor of AR-V7, re-sensitizes resistant cells to abiraterone treatment in vitro and in vivo. In summary, this preclinical study suggests that overexpression of AR-V7 contributes to resistance to abiraterone, and supports the development of combination of abiraterone with niclosamide as a potential treatment for advanced castration resistant prostate cancer.

BackgroundProstate cancer (PCa) is androgen-dependent initially and progresses to a castration-resistant state after androgen deprivation therapy. Treatment options for castration-resistant PCa include the potent second-generation anti-androgen enzalutamide or CYP17A1 inhibitor abiraterone. Recent clinical observations point to the development of resistance to these therapies which may be mediated by constitutively active alternative splice variants of the androgen receptor (AR).MethodsSensitivity of LNCaP cells overexpressing Lin28 (LN-Lin28) to enzalutamide, abiraterone, or bicalutamide was compared to that of control LN-neo cells using cell growth assays, proliferation assays using MTT, anchorage-dependent clonogenic ability assays and soft agar assays. Ability of LN-Lin28 cells to maintain AR activation after treatment with enzalutamide, abiraterone, or bicalutamide was tested using immunofluorescence, Western blotting, ChIP assays, and qRT-PCR. Importance of Lin28 in enzalutamide resistance was assessed by the downregulation of Lin28 expression in C4-2B and 22Rv1 cells chronically treated with enzalutamide. Requirement for sustained AR signaling in LN-Lin28 cells was examined by the downregulation of either full length AR or AR-V7 using siRNA.ResultsWe show that Lin28 promotes the development of resistance to currently used targeted therapeutics by enhancing the expression of AR splice variants such as AR-V7. PCa cells overexpressing Lin28 exhibit resistance to treatment with enzalutamide, abiraterone, or bicalutamide. Downregulation of Lin28 resensitizes enzalutamide-resistant PCa cells to enzalutamide treatment. We also show that the upregulation of splicing factors such as hnRNPA1 by Lin28 may mediate the enhanced generation of AR splice variants in Lin28-expressing cells.ConclusionsOur findings suggest that Lin28 plays a key role in the acquisition of resistance to AR-targeted therapies by PCa cells and establish the importance of Lin28 in PCa progression.

Node localization becomes an important issue in the wireless sensor network as its wide applications in environment monitoring, emergency rescue and battlefield surveillance, etc. Basically, the DV-Hop localization scheme can work well with the assistance of beacon nodes that have the capability of self-positioning. However, if the network is invaded by a wormhole attack, the attacker can tunnel the packets via the wormhole link to severely disrupt the DV-Hop localization process. The distance-vector propagation phase during the DV-Hop localization can even aggravate the positioning error, compared to the localization schemes without wormhole attacks. In this paper, we analyze the impacts of wormhole attack on the DV-Hop localization scheme, based on which we propose a label-based DV-Hop secure localization scheme to defend against the wormhole attack. We further theoretically prove the correctness of the proposed scheme. Simulation results illustrate the effectiveness of the proposed label-based DV-Hop secure localization scheme. (C) 2014 Elsevier B.V. All rights reserved.

Node localization becomes an important issue in the wireless sensor network as its wide applications in environment monitoring, emergency rescue and battlefield surveillance, etc. Basically, the DV-Hop localization scheme can work well with the assistance of beacon nodes that have the capability of self-positioning. However, if the network is invaded by a wormhole attack, the attacker can tunnel the packets via the wormhole link to severely disrupt the DV-Hop localization process. The distance-vector propagation phase during the DV-Hop localization can even aggravate the positioning error, compared to the localization schemes without wormhole attacks. In this paper, we analyze the impacts of wormhole attack on the DV-Hop localization scheme, based on which we propose a label-based DV-Hop secure localization scheme to defend against the wormhole attack. We further theoretically prove the correctness of the proposed scheme. Simulation results illustrate the effectiveness of the proposed label-based DV-Hop secure localization scheme. (C) 2014 Elsevier B.V. All rights reserved.

The introduction of enzalutamide and abiraterone has led to improvement in the treatment of metastatic castration-resistant prostate cancer. However, acquired resistance to enzalutamide and abiraterone therapies frequently develops within a short period in many patients. In the present study, we developed enzalutamide-resistant prostate cancer cells in an effort to understand the mechanisms of resistance. Global gene-expression analysis showed that the steroid biosynthesis pathway is activated in enzalutamide-resistant prostate cancer cells. One of the crucial steroidogenic enzymes, AKR1C3, was significantly elevated in enzalutamide-resistant cells. In addition, AKR1C3 is highly expressed in metastatic and recurrent prostate cancer and in enzalutamide-resistant prostate xenograft tumors. LC/MS analysis of the steroid metabolites revealed that androgen precursors such as cholesterol, DHEA and progesterone, as well as androgens are highly upregulated in enzalutamide-resistant prostate cancer cells compared to the parental cells. Knockdown of AKR1C3 expression by shRNA or inhibition of AKR1C3 enzymatic activity by indomethacin resensitized enzalutamide-resistant prostate cancer cells to enzalutamide treatment both in vitro and in vivo. In contrast, overexpression of AKR1C3 confers resistance to enzalutamide. Furthermore, the combination of indomethacin and enzalutamide resulted in significant inhibition of enzalutamide-resistant tumor growth. These results suggest that AKR1C3 activation is a critical resistance mechanism associated with enzalutamide resistance; targeting intracrine androgens and AKR1C3 will overcome enzalutamide resistance and improve survival of advanced prostate cancer patients.

PurposePrevious studies show that inhibition of ABCB1 expression overcomes acquired docetaxel resistance in C4-2B-TaxR cells. In this study, we examined whether antiandrogens, such as bicalutamide and enzalutamide, could inhibit ABCB1 activity and overcome resistance to docetaxel.Experimental designABCB1 efflux activity was determined using a rhodamine efflux assay. ABCB1 ATPase activity was determined by Pgp-Glo assay systems. The effects of the antiandrogens bicalutamide and enzalutamide on docetaxel sensitivity were determined by cell growth assays and tumor growth in vivo.ResultsWe found that bicalutamide and enzalutamide inhibit ABCB1 ATP-binding cassette transporter activity through blocking ABCB1 efflux activity. Bicalutamide inhibited ABCB1 efflux activity by 40%, whereas enzalutamide inhibited ABCB1 efflux activity by approximately 60%. Both bicalutamide and enzalutamide inhibit ABCB1 ATPase activity. In addition, bicalutamide and enzalutamide inhibit ABCB1 efflux activity and desensitize docetaxel-resistant and androgen receptor (AR)-negative DU145 cells. Combination of bicalutamide with docetaxel had a significant antitumor effect in both AR-positive and AR-negative docetaxel-resistant xenograft models, suggesting that bicalutamide desensitizes docetaxel-resistant cells to docetaxel treatment independent of AR status.ConclusionsWe identified a novel mechanism of action for antiandrogens such as bicalutamide and enzalutamide as inhibitors of ABCB1 efflux and ATPase activity. Bicalutamide and enzalutamide desensitize docetaxel-resistant prostate cancer cells to docetaxel treatment independent of AR status. These studies may lead to the development of combinational therapies with bicalutamide/enzalutamide and docetaxel as effective regimens to treat advanced prostate cancer independent of AR status, and possibly other types of cancer.

PurposeIt is known that over expression of IL6 in prostate cancer cells confer enzalutamide resistance and that this may occur through constitutive Stat3 activation. Additionally, recent pre-clinical studies suggested enzalutamide might have the potential adverse effect of inducing metastasis of prostate cancer cells via Stat3 activation. This study is aimed to target Stat3 activation and improve enzalutamide therapy.Experimental designSensitivity of prostate cancer cells to enzalutamide was tested using cell growth assays and clonogenic assays. Wound healing and invasion assays were performed to determine cell migration and invasion in vitro. Quantitative reverse transcription-PCR, ELISA and Western blotting were performed to detect expression levels of PSA, c-Myc, survivin, Stat3, and AR. ChIP assay was performed to examine recruitment of AR to the PSA promoter.ResultsIn the present study, we found niclosamide, a previously identified novel inhibitor of androgen receptor variant (AR-V7), inhibited Stat3 phosphorylation, and expression of downstream target genes. Niclosamide synergistically reversed enzalutamide resistance in prostate cancer cells and combination treatment of niclosamide with enzalutamide significantly induced cell apoptosis and inhibited cell growth, colony formation, cell migration and invasion. Knock down of Stat3 abrogated enzalutamide resistance resulting in reduced recruitment of AR to the PSA promoter in prostate cancer cells expressing IL6. Moreover, niclosamide reversed enzalutamide resistance by down-regulating Stat3 target gene expression Stat3and abrogating recruitment of AR to PSA promoter resulting in PSA inhibition.ConclusionsThis study demonstrated the IL6-Stat3-AR axis in prostate cancer is one of the crucial mechanisms of enzalutamide resistance. Niclosamide has the potential to target the IL6-Stat3-AR pathway to overcome enzalutamide resistance and inhibit migration and invasion in advanced prostate cancer.

Node localization becomes an important issue in the wireless sensor network as its wide applications in environment monitoring, emergency rescue and battlefield surveillance, etc. Basically, the DV-Hop localization scheme can work well with the assistance of beacon nodes that have the capability of self-positioning. However, if the network is invaded by a wormhole attack, the attacker can tunnel the packets via the wormhole link to severely disrupt the DV-Hop localization process. The distance-vector propagation phase during the DV-Hop localization can even aggravate the positioning error, compared to the localization schemes without wormhole attacks. In this paper, we analyze the impacts of wormhole attack on the DV-Hop localization scheme, based on which we propose a label-based DV-Hop secure localization scheme to defend against the wormhole attack. We further theoretically prove the correctness of the proposed scheme. Simulation results illustrate the effectiveness of the proposed label-based DV-Hop secure localization scheme. (C) 2014 Elsevier B.V. All rights reserved.