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1. Transaction Fee Estimation in the Bitcoin System

Author

Zhang, Limeng, Zhou, Rui, Liu, Qing, Liu, Chengfei, and Babar, M. Ali

Subjects
Computer Science - Cryptography and Security
Abstract

In the Bitcoin system, transaction fees serve as an incentive for blockchain confirmations. In general, a transaction with a higher fee is likely to be included in the next block mined, whereas a transaction with a smaller fee or no fee may be delayed or never processed at all. However, the transaction fee needs to be specified when submitting a transaction and almost cannot be altered thereafter. Hence it is indispensable to help a client set a reasonable fee, as a higher fee incurs over-spending and a lower fee could delay the confirmation. In this work, we focus on estimating the transaction fee for a new transaction to help with its confirmation within a given expected time. We identify two major drawbacks in the existing works. First, the current industry products are built on explicit analytical models, ignoring the complex interactions of different factors which could be better captured by machine learning based methods; Second, all of the existing works utilize limited knowledge for the estimation which hinders the potential of further improving the estimation quality. As a result, we propose a framework FENN, which aims to integrate the knowledge from a wide range of sources, including the transaction itself, unconfirmed transactions in the mempool and the blockchain confirmation environment, into a neural network model in order to estimate a proper transaction fee. Finally, we conduct experiments on real blockchain datasets to demonstrate the effectiveness and efficiency of our proposed framework over the state-of-the-art works evaluated by MAPE and RMSE. Each variation model in our framework can finish training within one block interval, which shows the potential of our framework to process the realtime transaction updates in the Bitcoin blockchain.

Published
2024

2. IGFBP3 promotes resistance to Olaparib via modulating EGFR signaling in advanced prostate cancer

Author

Leslie, Amy R, Ning, Shu, Armstrong, Cameron M, D’Abronzo, Leandro S, Sharifi, Masuda, Schaaf, Zachary A, Lou, Wei, Liu, Chengfei, Evans, Christopher P, Lombard, Alan P, and Gao, Allen C

Subjects
Biomedical and Clinical Sciences, Clinical Sciences, Oncology and Carcinogenesis, Prostate Cancer, Cancer, Urologic Diseases, 5.1 Pharmaceuticals, Development of treatments and therapeutic interventions, Cell biology, Transcriptomics
Abstract

Olaparib is a pioneering PARP inhibitor (PARPi) approved for treating castration-resistant prostate cancer (CRPC) tumors harboring DNA repair defects, but clinical resistance has been documented. To study acquired resistance, we developed Olaparib-resistant (OlapR) cell lines through chronic Olaparib treatment of LNCaP and C4-2B cell lines. Here, we found that IGFBP3 is highly expressed in acquired (OlapR) and intrinsic (Rv1) models of Olaparib resistance. We show that IGFBP3 expression promotes Olaparib resistance by enhancing DNA repair capacity through activation of EGFR and DNA-PKcs. IGFBP3 depletion enhances efficacy of Olaparib by promoting DNA damage accumulation and subsequently, cell death in resistant models. Mechanistically, we show that silencing IGFBP3 or EGFR expression reduces cell viability and resensitizes OlapR cells to Olaparib treatment. Inhibition of EGFR by Gefitinib suppressed growth of OlapR cells and improved Olaparib sensitivity, thereby phenocopying IGFBP3 inhibition. Collectively, our results highlight IGFBP3 and EGFR as critical mediators of Olaparib resistance.

Published
2024

5. Multi-stage feature decorrelation constraints for improving CNN classification performance

Author

Zhu, Qiuyu, Wang, Hao, Zu, Xuewen, and Liu, Chengfei

Subjects
Computer Science - Computer Vision and Pattern Recognition
Abstract

For the convolutional neural network (CNN) used for pattern classification, the training loss function is usually applied to the final output of the network, except for some regularization constraints on the network parameters. However, with the increasing of the number of network layers, the influence of the loss function on the network front layers gradually decreases, and the network parameters tend to fall into local optimization. At the same time, it is found that the trained network has significant information redundancy at all stages of features, which reduces the effectiveness of feature mapping at all stages and is not conducive to the change of the subsequent parameters of the network in the direction of optimality. Therefore, it is possible to obtain a more optimized solution of the network and further improve the classification accuracy of the network by designing a loss function for restraining the front stage features and eliminating the information redundancy of the front stage features .For CNN, this article proposes a multi-stage feature decorrelation loss (MFD Loss), which refines effective features and eliminates information redundancy by constraining the correlation of features at all stages. Considering that there are many layers in CNN, through experimental comparison and analysis, MFD Loss acts on multiple front layers of CNN, constrains the output features of each layer and each channel, and performs supervision training jointly with classification loss function during network training. Compared with the single Softmax Loss supervised learning, the experiments on several commonly used datasets on several typical CNNs prove that the classification performance of Softmax Loss+MFD Loss is significantly better. Meanwhile, the comparison experiments before and after the combination of MFD Loss and some other typical loss functions verify its good universality.

Published
2023

6. Androgen receptor blockade resistance with enzalutamide in prostate cancer results in immunosuppressive alterations in the tumor immune microenvironment

Author

Xu, Pengfei, Yang, Joy C, Chen, Bo, Nip, Christopher, Van Dyke, Jonathan E, Zhang, Xiong, Chen, Hong-Wu, Evans, Christopher P, Murphy, William J, and Liu, Chengfei

Subjects
Biomedical and Clinical Sciences, Clinical Sciences, Oncology and Carcinogenesis, Immunology, Cancer, Aging, Urologic Diseases, Clinical Research, Rare Diseases, Prostate Cancer, 5.1 Pharmaceuticals, 2.1 Biological and endogenous factors, Aetiology, Development of treatments and therapeutic interventions, Good Health and Well Being, Animals, Humans, Male, Mice, Drug Resistance, Neoplasm, Immunosuppressive Agents, Phenylthiohydantoin, Prostatic Neoplasms, Castration-Resistant, Receptors, Androgen, Tumor Microenvironment, Prostatic Neoplasms, Programmed Cell Death 1 Receptor, Immune Evation, Drug Therapy, Combination, Drug Therapy, Combination, Oncology and carcinogenesis
Abstract

BackgroundEmerging data suggest that patients with enzalutamide-treated prostate cancer with increased programmed death-ligand 1 (PD-L1) expression may benefit from anti-PD-L1 treatment. Unfortunately, the Phase III IMbassador250 clinical trial revealed that the combination of atezolizumab (a PD-L1 inhibitor) and enzalutamide failed to extend overall survival in patients with castration-resistant prostate cancer (CRPC). However, the mechanisms underlying treatment failure remain unknown.MethodsHuman CRPC C4-2B cells and murine Myc-CaP cells were chronically exposed to increasing concentrations of enzalutamide and the cells resistant to enzalutamide were referred to as C4-2B MDVR and Myc-CaP MDVR, respectively. The mechanisms of action in drug-resistant prostate cancer cells were determined using RNA sequencing analyses, RNA interference, real-time PCR, western blotting, and co-culturing technologies. Myc-CaP and Myc-CaP MDVR tumors were established in syngeneic FVB mice, and tumor-infiltrating leukocytes were isolated after enzalutamide treatment. The stained immune cells were determined by flow cytometry, and the data were analyzed using FlowJo.ResultsImmune-related signaling pathways (interferon alpha/gamma response, inflammatory response, and cell chemotaxis) were suppressed in human enzalutamide-resistant prostate cancer cells. PD-L1 was overexpressed and negatively regulated by androgen receptor signaling in resistant cells and patient with CRPC cohorts. Enzalutamide treatment decreased CD8+ T-cell numbers but increased monocytic myeloid-derived suppressor cell (M-MDSC) populations and PD-L1 expression within murine Myc-CaP tumors. Similarly, chemotaxis and immune response-regulating signaling pathways were suppressed, and PD-L1 expression was also increased using enzalutamide-resistant Myc-CaP MDVR cells. Notably, MDSC populations were significantly increased in Myc-CaP MDVR orthotopic tumors compared with those in Myc-CaP parental tumors. Co-culturing bone marrow cells with Myc-CaP MDVR cells significantly promoted MDSC differentiation and shifted towards M2 macrophage skewing.ConclusionsOur study suggests that immunosuppressive signaling can be promoted directly by enzalutamide-resistant prostate cancer cells and may be a potential means by which the efficacy of immune checkpoint inhibitors in enzalutamide-resistant prostate cancer is diminished.

Published
2023

8. Allosteric inhibition of HSP70 in collaboration with STUB1 augments enzalutamide efficacy in antiandrogen resistant prostate tumor and patient-derived models

Author

Xu, Pengfei, Yang, Joy C, Ning, Shu, Chen, Bo, Nip, Christopher, Wei, Qiang, Liu, Liangren, Johnson, Oleta T, Gao, Allen C, Gestwicki, Jason E, Evans, Christopher P, and Liu, Chengfei

Subjects
Biomedical and Clinical Sciences, Clinical Sciences, Oncology and Carcinogenesis, Prostate Cancer, Cancer, Urologic Diseases, 2.1 Biological and endogenous factors, 5.1 Pharmaceuticals, Aetiology, Development of treatments and therapeutic interventions, Good Health and Well Being, Male, Humans, Receptors, Androgen, Androgen Antagonists, Prostatic Neoplasms, Castration-Resistant, Cell Line, Tumor, Nitriles, Androgen Receptor Antagonists, Androgens, HSP70 Heat-Shock Proteins, Drug Resistance, Neoplasm, Ubiquitin-Protein Ligases, Prostate cancer, Enzalutamide resistance, HSP70, STUB1, Androgen receptor variant, Patient-derived model, JG98, MG132, apalutamide, cycloheximide, darolutamide, enzalutamide, Pharmacology and Pharmaceutical Sciences, Pharmacology & Pharmacy, Pharmacology and pharmaceutical sciences
Abstract

Ubiquitin proteasome activity is suppressed in enzalutamide resistant prostate cancer cells, and the heat shock protein 70/STIP1 homology and U-box-containing protein 1 (HSP70/STUB1) machinery are involved in androgen receptor (AR) and AR variant protein stabilization. Targeting HSP70 could be a viable strategy to overcome resistance to androgen receptor signaling inhibitor (ARSI) in advanced prostate cancer. Here, we showed that a novel HSP70 allosteric inhibitor, JG98, significantly suppressed drug-resistant C4-2B MDVR and CWR22Rv1 cell growth, and enhanced enzalutamide treatment. JG98 also suppressed cell growth in conditional reprogramed cell cultures (CRCs) and organoids derived from advanced prostate cancer patient samples. Mechanistically, JG98 degraded AR/AR-V7 expression in resistant cells and promoted STUB1 nuclear translocation to bind AR-V7. Knockdown of the E3 ligase STUB1 significantly diminished the anticancer effects and partially restored AR-V7 inhibitory effects of JG98. JG231, a more potent analog developed from JG98, effectively suppressed the growth of the drug-resistant prostate cancer cells, CRCs, and organoids. Notably, the combination of JG231 and enzalutamide synergistically inhibited AR/AR-V7 expression and suppressed CWR22Rv1 xenograft tumor growth. Inhibition of HSP70 using novel small-molecule inhibitors coordinates with STUB1 to regulate AR/AR-V7 protein stabilization and ARSI resistance.

Published
2023

9. Novel inhibition of AKR1C3 and androgen receptor axis by PTUPB synergizes enzalutamide treatment in advanced prostate cancer

Author

Yang, Joy C, Xu, Pengfei, Ning, Shu, Wasielewski, Logan J, Adomat, Hans, Hwang, Sung Hee, Morisseau, Christophe, Gleave, Martin, Corey, Eva, Gao, Allen C, Lara Jr, Primo N, Evans, Christopher P, Hammock, Bruce D, and Liu, Chengfei

Subjects
Biomedical and Clinical Sciences, Clinical Sciences, Oncology and Carcinogenesis, Cancer, Urologic Diseases, Prostate Cancer, Development of treatments and therapeutic interventions, 5.1 Pharmaceuticals, Good Health and Well Being, Male, Humans, Receptors, Androgen, Prostatic Neoplasms, Castration-Resistant, Drug Resistance, Neoplasm, Cell Line, Tumor, Nitriles, Androgen Receptor Antagonists, Aldo-Keto Reductase Family 1 Member C3, Oncology & Carcinogenesis, Biochemistry and cell biology, Oncology and carcinogenesis
Abstract

Castration-resistant prostate cancer (CRPC) is the main driving force of mortality in prostate cancer patients. Among the parameters contributing to the progression of CRPC and treatment failure, elevation of the steroidogenic enzyme AKR1C3 and androgen receptor variant 7 (AR-V7) are frequently reported. The AKR1C3/AR-V7 complex has been recognized as a major driver for drug resistance in advanced prostate cancer. Herein we report that the level of AKR1C3 is reciprocally regulated by the full-length androgen receptor (AR-FL) through binding to the distal enhancer region of the AKR1C3 gene. A novel function of PTUPB in AKR1C3 inhibition was discovered and PTUPB showed more effectiveness than indomethacin and celecoxib in suppressing AKR1C3 activity and CRPC cell growth. PTUPB synergizes with enzalutamide treatment in tumor suppression and gene signature regulation. Combination treatments with PTUPB and enzalutamide provide benefits by blocking AR/AR-V7 signaling, which inhibits the growth of castration relapsed VCaP xenograft tumors and patient-derived xenograft organoids. Targeting of the ARK1C3/AR/AR-V7 axis with PTUPB and enzalutamide may overcome drug resistance to AR signaling inhibitors in advanced prostate cancer.

Published
2023

10. CD200/CD200R: Bidirectional Role in Cancer Progression and Immunotherapy

Author

Nip, Christopher, Wang, Leyi, and Liu, Chengfei

Subjects
Biomedical and Clinical Sciences, Oncology and Carcinogenesis, Immunology, Immunization, Cancer, Vaccine Related, 2.1 Biological and endogenous factors, Aetiology, cancer, CD200, CD200R, immunosuppressive signaling, tumor immune microenvironment, checkpoint, therapy, Biochemistry and cell biology, Pharmacology and pharmaceutical sciences, Medicinal and biomolecular chemistry
Abstract

As an immune checkpoint molecule, CD200 serves a foundational role in regulating immune homeostasis and promoting self-tolerance. While CD200 expression occurs in various immune cell subsets and normal tissues, its aberrant expression patterns in hematologic malignancies and solid tumors have been linked to immune evasion and cancer progression under pathological conditions, particularly through interactions with its cognate receptor, CD200R. Through this CD200/CD200R signaling pathway, CD200 exerts its immunosuppressive effects by inhibiting natural killer (NK) cell activation, cytotoxic T cell functions, and M1-polarized macrophage activity, while also facilitating expansion of myeloid-derived suppressor cells (MDSCs) and Tregs. Moreover, CD200/CD200R expression has been linked to epithelial-to-mesenchymal transition and distant metastasis, further illustrating its role in cancer progression. Conversely, CD200 has also been shown to exert anti-tumor effects in certain cancer types, such as breast carcinoma and melanoma, indicating that CD200 may exert bidirectional effects on cancer progression depending on the specific tumor microenvironment (TME). Regardless, modulating the CD200/CD200R axis has garnered clinical interest as a potential immunotherapeutic strategy for cancer therapy, as demonstrated by early-phase clinical trials. However, further research is necessary to fully understand the complex interactions of CD200 in the tumor microenvironment and to optimize its therapeutic potential in cancer immunotherapy.

Published
2023

11. Therapeutic Resistance Models and Treatment Sequencing in Advanced Prostate Cancer

Author

Schaaf, Zachary A, Ning, Shu, Leslie, Amy R, Sharifi, Masuda, Han, Xianrui, Armstrong, Cameron, Lou, Wei, Lombard, Alan P, Liu, Chengfei, and Gao, Allen C

Subjects
Biomedical and Clinical Sciences, Clinical Sciences, Oncology and Carcinogenesis, Cancer, Prostate Cancer, Genetics, Urologic Diseases, 5.1 Pharmaceuticals, Development of treatments and therapeutic interventions, Good Health and Well Being, prostate, cancer, resistance, enzalutamide, abiraterone, darolutamide, apalutamide, docetaxel, olaparib, Oncology and carcinogenesis
Abstract

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 cancer's evolution and progression. The data indicate that resistance mechanisms are distinct among different drug classes. Notably, NGAT-resistant sublines exhibited a significant downregulation of androgen-regulated genes, contrasting to the stable expression noted in olaparib and docetaxel-resistant sublines. These results may have clinical implications by showing that treatments of one class can be sequenced with those from another class, but caution should be taken when sequencing drugs of the same class.

Published
2023

15. CHIEF: Clustering with Higher-order Motifs in Big Networks

Author

Xia, Feng, Yu, Shuo, Liu, Chengfei, and Lee, Ivan

Subjects
Computer Science - Social and Information Networks, Computer Science - Machine Learning
Abstract

Clustering a group of vertices in networks facilitates applications across different domains, such as social computing and Internet of Things. However, challenges arises for clustering networks with increased scale. This paper proposes a solution which consists of two motif clustering techniques: standard acceleration CHIEF-ST and approximate acceleration CHIEF-AP. Both algorithms first find the maximal k-edge-connected subgraphs within the target networks to lower the network scale, then employ higher-order motifs in clustering. In the first procedure, we propose to lower the network scale by optimizing the network structure with maximal k-edge-connected subgraphs. For CHIEF-ST, we illustrate that all target motifs will be kept after this procedure when the minimum node degree of the target motif is equal or greater than k. For CHIEF-AP, we prove that the eigenvalues of the adjacency matrix and the Laplacian matrix are relatively stable after this step. That is, CHIEF-ST has no influence on motif clustering, whereas CHIEF-AP introduces limited yet acceptable impact. In the second procedure, we employ higher-order motifs, i.e., heterogeneous four-node motifs clustering in higher-order dense networks. The contributions of CHIEF are two-fold: (1) improved efficiency of motif clustering for big networks; (2) verification of higher-order motif significance. The proposed solutions are found to outperform baseline approaches according to experiments on real and synthetic networks, which demonstrates CHIEF's strength in large network analysis. Meanwhile, higher-order motifs are proved to perform better than traditional triangle motifs in clustering.

Published
2022

16. Reliable Community Search in Dynamic Networks

Author

Tang, Yifu, Li, Jianxin, Haldar, Nur Al Hasan, Guan, Ziyu, Xu, Jiajie, and Liu, Chengfei

Subjects
Computer Science - Social and Information Networks, Computer Science - Databases
Abstract

Searching for local communities is an important research problem that supports advanced data analysis in various complex networks, such as social networks, collaboration networks, cellular networks, etc. The evolution of such networks over time has motivated several recent studies to identify local communities in dynamic networks. However, these studies only utilize the aggregation of disjoint structural information to measure the quality and ignore the reliability of the communities in a continuous time interval. To fill this research gap, we propose a novel $(\theta,k)$-$core$ reliable community (CRC) model in the weighted dynamic networks, and define the problem of \textit{most reliable community search} that couples the desirable properties of connection strength, cohesive structure continuity, and the maximal member engagement. To solve this problem, we first develop a novel edge filtering based online CRC search algorithm that can effectively filter out the trivial edge information from the networks while searching for a \textit{reliable} community. Further, we propose an index structure, Weighted Core Forest-Index (WCF-index), and devise an index-based dynamic programming CRC search algorithm, that can prune a large number of insignificant intermediate results and support efficient query processing. Finally, we conduct extensive experiments systematically to demonstrate the efficiency and effectiveness of our proposed algorithms on eight real datasets under various experimental settings.

Published
2022
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17. Bioengineered BERA-Wnt5a siRNA Targeting Wnt5a/FZD2 Signaling Suppresses Advanced Prostate Cancer Tumor Growth and Enhances Enzalutamide Treatment.

Author

Ning, Shu, Liu, Chengfei, Lou, Wei, Yang, Joy C, Lombard, Alan P, D'Abronzo, Leandro S, Batra, Neelu, Yu, Ai-Ming, Leslie, Amy R, Sharifi, Masuda, Evans, Christopher P, and Gao, Allen C

Subjects
Biomedical and Clinical Sciences, Clinical Sciences, Oncology and Carcinogenesis, Cancer, Clinical Research, Aging, Prostate Cancer, Urologic Diseases, Development of treatments and therapeutic interventions, 5.1 Pharmaceuticals, Androgen Antagonists, Benzamides, Cell Line, Tumor, Drug Resistance, Neoplasm, Frizzled Receptors, Humans, Male, Nitriles, Phenylthiohydantoin, Prostatic Neoplasms, Prostatic Neoplasms, Castration-Resistant, RNA, Small Interfering, Receptors, Androgen, Wnt Signaling Pathway, Wnt-5a Protein, Pharmacology and Pharmaceutical Sciences, Oncology & Carcinogenesis, Biochemistry and cell biology, Oncology and carcinogenesis
Abstract

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.

Published
2022

20. Activation of neural lineage networks and ARHGEF2 in enzalutamide-resistant and neuroendocrine prostate cancer and association with patient outcomes

Author

Ning, Shu, Zhao, Jinge, Lombard, Alan P, D’Abronzo, Leandro S, Leslie, Amy R, Sharifi, Masuda, Lou, Wei, Liu, Chengfei, Yang, Joy C, Evans, Christopher P, Corey, Eva, Chen, Hong-Wu, Yu, Aiming, Ghosh, Paramita M, and Gao, Allen C

Subjects
Biomedical and Clinical Sciences, Clinical Sciences, Oncology and Carcinogenesis, Prostate Cancer, Urologic Diseases, Stem Cell Research, Clinical Research, Stem Cell Research - Nonembryonic - Human, Cancer, Genetics, Detection, screening and diagnosis, Aetiology, 4.1 Discovery and preclinical testing of markers and technologies, 2.1 Biological and endogenous factors, Prostate, Prostate cancer
Abstract

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 targets in advanced prostate cancer.

Published
2022

21. The Immunotherapy and Immunosuppressive Signaling in Therapy-Resistant Prostate Cancer

Author

Xu, Pengfei, Wasielewski, Logan J, Yang, Joy C, Cai, Demin, Evans, Christopher P, Murphy, William J, and Liu, Chengfei

Subjects
Cancer, Immunization, Urologic Diseases, Aging, Vaccine Related, Prostate Cancer, 5.1 Pharmaceuticals, Aetiology, Development of treatments and therapeutic interventions, 2.1 Biological and endogenous factors, prostate cancer, immunotherapy, immunosuppressive signaling, tumor immune microenvironment, checkpoint inhibitor, therapy resistance
Abstract

Prostate cancer is one of the most common malignant tumors in men. Initially, it is androgen-dependent, but it eventually develops into castration-resistant prostate cancer (CRPC), which is incurable with current androgen receptor signaling target therapy and chemotherapy. Immunotherapy, specifically with immune checkpoint inhibitors, has brought hope for the treatment of this type of prostate cancer. Approaches such as vaccines, adoptive chimeric antigen receptor-T (CAR-T) cells, and immune checkpoint inhibitors have been employed to activate innate and adaptive immune responses to treat prostate cancer, but with limited success. Only Sipuleucel-T and the immune checkpoint inhibitor pembrolizumab are approved by the US FDA for the treatment of limited prostate cancer patients. Prostate cancer has a complex tumor microenvironment (TME) in which various immunosuppressive molecules and mechanisms coexist and interact. Additionally, prostate cancer is considered a "cold" tumor with low levels of tumor mutational burden, low amounts of antigen-presenting and cytotoxic T-cell activation, and high levels of immunosuppressive molecules including cytokines/chemokines. Thus, understanding the mechanisms of immunosuppressive signaling activation and immune evasion will help develop more effective treatments for prostate cancer. The purpose of this review is to summarize emerging advances in prostate cancer immunotherapy, with a particular focus on the molecular mechanisms that lead to immune evasion in prostate cancer. At the same time, we also highlight some potential therapeutic targets to provide a theoretical basis for the treatment of prostate cancer.

Published
2022

24. Searching Personalized $k$-wing in Large and Dynamic Bipartite Graphs

Author

Abidi, Aman, Chen, Lu, Zhou, Rui, and Liu, Chengfei

Subjects
Computer Science - Databases, Computer Science - Information Retrieval, H.2, H.3
Abstract

There are extensive studies focusing on the application scenario that all the bipartite cohesive subgraphs need to be discovered in a bipartite graph. However, we observe that, for some applications, one is interested in finding bipartite cohesive subgraphs containing a specific vertex. In this paper, we study a new query dependent bipartite cohesive subgraph search problem based on $k$-wing model, named as the personalized $k$-wing search problem. We introduce a $k$-wing equivalence relationship to summarize the edges of a bipartite graph $G$ into groups. Therefore, all the edges of $G$ are segregated into different groups, i.e. $k$-wing equivalence class, forming an efficient and wing number conserving index called EquiWing. Further, we propose a more compact version of EquiWing, EquiWing-Comp, which is achieved by integrating our proposed $k$-butterfly loose approach and discovered hierarchy properties. These indices are used to expedite the personalized $k$-wing search with a non-repetitive access to $G$, which leads to linear algorithms for searching the personalized $k$-wing. Moreover, we conduct a thorough study on the maintenance of the proposed indices for evolving bipartite graphs. We discover novel properties that help us localize the scope of the maintenance at a low cost. By exploiting the discoveries, we propose novel algorithms for maintaining the two indices, which substantially reduces the cost of maintenance. We perform extensive experimental studies in real, large-scale graphs to validate the efficiency and effectiveness of EquiWing and EquiWing-Comp compared to the baseline., Comment: 13 pages, 10 figures and 4 tables

Published
2021
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25. ARVib suppresses growth of advanced prostate cancer via inhibition of androgen receptor signaling

Author

Liu, Chengfei, Armstrong, Cameron M, Ning, Shu, Yang, Joy C, Lou, Wei, Lombard, Alan P, Zhao, Jinge, Wu, Chun-Yi, Yu, Aiming, Evans, Christopher P, Tepper, Clifford G, Li, Pui-kai, and Gao, Allen C

Subjects
Biomedical and Clinical Sciences, Clinical Sciences, Oncology and Carcinogenesis, Aging, Prostate Cancer, Urologic Diseases, Cancer, Development of treatments and therapeutic interventions, 5.1 Pharmaceuticals, Aetiology, 2.1 Biological and endogenous factors, Humans, Male, Prostatic Neoplasms, Receptors, Androgen, Signal Transduction, Oncology & Carcinogenesis, Biochemistry and cell biology, Oncology and carcinogenesis
Abstract

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.

Published
2021

26. Efficiently Finding a Maximal Clique Summary via Effective Sampling

Author

Li, Xiaofan, Zhou, Rui, Chen, Lu, Liu, Chengfei, He, Qiang, and Yang, Yun

Subjects
Computer Science - Databases, H.2
Abstract

Maximal clique enumeration (MCE) is a fundamental problem in graph theory and is used in many applications, such as social network analysis, bioinformatics, intelligent agent systems, cyber security, etc. Most existing MCE algorithms focus on improving the efficiency rather than reducing the output size. The output unfortunately could consist of a large number of maximal cliques. In this paper, we study how to report a summary of less overlapping maximal cliques. The problem was studied before, however, after examining the pioneer approach, we consider it still not satisfactory. To advance the research along this line, our paper attempts to make four contributions: (a) we propose a more effective sampling strategy, which produces a much smaller summary but still ensures that the summary can somehow witness all the maximal cliques and the expectation of each maximal clique witnessed by the summary is above a predefined threshold; (b) we prove that the sampling strategy is optimal under certain optimality conditions; (c) we apply clique-size bounding and design new enumeration order to approach the optimality conditions; and (d) to verify experimentally, we test eight real benchmark datasets that have a variety of graph characteristics. The results show that our new sampling strategy consistently outperforms the state-of-the-art approach by producing smaller summaries and running faster on all the datasets., Comment: 20 pages, 80 figures

Published
2020

28. Efficient Exact Algorithms for Maximum Balanced Biclique Search in Bipartite Graphs

Author

Chen, Lu, Liu, Chengfei, Zhou, Rui, Xu, Jiajie, and Li, Jianxin

Subjects
Computer Science - Data Structures and Algorithms
Abstract

Given a bipartite graph, the maximum balanced biclique (\textsf{MBB}) problem, discovering a mutually connected while equal-sized disjoint sets with the maximum cardinality, plays a significant role for mining the bipartite graph and has numerous applications. Despite the NP-hardness of the \textsf{MBB} problem, in this paper, we show that an exact \textsf{MBB} can be discovered extremely fast in bipartite graphs for real applications. We propose two exact algorithms dedicated for dense and sparse bipartite graphs respectively. For dense bipartite graphs, an $\mathcal{O}^{*}( 1.3803^{n})$ algorithm is proposed. This algorithm in fact can find an \textsf{MBB} in near polynomial time for dense bipartite graphs that are common for applications such as VLSI design. This is because, using our proposed novel techniques, the search can fast converge to sufficiently dense bipartite graphs which we prove to be polynomially solvable. For large sparse bipartite graphs typical for applications such as biological data analysis, an $\mathcal{O}^{*}( 1.3803^{\ddot{\delta}})$ algorithm is proposed, where $\ddot{\delta}$ is only a few hundreds for large sparse bipartite graphs with millions of vertices. The indispensible optimizations that lead to this time complexity are: we transform a large sparse bipartite graph into a limited number of dense subgraphs with size up to $\ddot{\delta}$ and then apply our proposed algorithm for dense bipartite graphs on each of the subgraphs. To further speed up this algorithm, tighter upper bounds, faster heuristics and effective reductions are proposed, allowing an \textsf{MBB} to be discovered within a few seconds for bipartite graphs with millions of vertices. Extensive experiments are conducted on synthetic and real large bipartite graphs to demonstrate the efficiency and effectiveness of our proposed algorithms and techniques.

Published
2020

29. Index-based Solutions for Efficient Density Peak Clustering

Author

Rasool, Zafaryab, Zhou, Rui, Chen, Lu, Liu, Chengfei, and Xu, Jiajie

Subjects
Computer Science - Databases, Computer Science - Information Retrieval
Abstract

Density Peak Clustering (DPC), a popular density-based clustering approach, has received considerable attention from the research community primarily due to its simplicity and fewer-parameter requirement. However, the resultant clusters obtained using DPC are influenced by the sensitive parameter $d_c$, which depends on data distribution and requirements of different users. Besides, the original DPC algorithm requires visiting a large number of objects, making it slow. To this end, this paper investigates index-based solutions for DPC. Specifically, we propose two list-based index methods viz. (i) a simple List Index, and (ii) an advanced Cumulative Histogram Index. Efficient query algorithms are proposed for these indices which significantly avoids irrelevant comparisons at the cost of space. For memory-constrained systems, we further introduce an approximate solution to the above indices which allows substantial reduction in the space cost, provided that slight inaccuracies are admissible. Furthermore, owing to considerably lower memory requirements of existing tree-based index structures, we also present effective pruning techniques and efficient query algorithms to support DPC using the popular Quadtree Index and R-tree Index. Finally, we practically evaluate all the above indices and present the findings and results, obtained from a set of extensive experiments on six synthetic and real datasets. The experimental insights obtained can help to guide in selecting a befitting index.

Published
2020

30. Phase Ib trial of reformulated niclosamide with abiraterone/prednisone in men with castration-resistant prostate cancer.

Author

Parikh, Mamta, Liu, Chengfei, Wu, Chun-Yi, Evans, Christopher P, Dall'Era, Marc, Robles, Daniel, Lara, Primo N, Agarwal, Neeraj, Gao, Allen C, and Pan, Chong-Xian

Subjects
Clinical Trials and Supportive Activities, Urologic Diseases, Cancer, Prostate Cancer, Clinical Research, Aging, 6.1 Pharmaceuticals
Abstract

Niclosamide has preclinical activity against a wide range of cancers. In prostate cancer, it inhibits androgen receptor variant 7 and synergizes with abiraterone. The approved niclosamide formulation has poor oral bioavailability. The primary objective of this phase Ib trial was to identify a maximum tolerated dose (MTD) and recommended phase 2 dose (RP2D) of a novel reformulated orally-bioavailable niclosamide/PDMX1001 in combination with abiraterone and prednisone in men with castration-resistant prostate cancer (CRPC). Eligible patients had progressing CRPC, adequate end-organ function, and no prior treatment with abiraterone or ketoconazole. Patients were treated with escalating doses of niclosamide/PDMX1001 and standard doses of abiraterone and prednisone. Peak and trough niclosamide plasma levels were measured. Common Terminology Criteria for Adverse Events (CTCAE) v4.0 and Prostate Cancer Working Group 2 criteria were used to evaluate toxicities and responses. Nine patients with metastatic CRPC were accrued, with no dose-limiting toxicities observed at all dose levels. The recommended Phase II dose of niclosamide/PDMX1001 was 1200 mg orally (PO) three times daily plus abiraterone 1000 mg PO once daily and prednisone 5 mg PO twice daily. Trough and peak niclosamide concentrations exceeded the therapeutic threshold of > 0.2 µM. The combination was well tolerated with most frequent adverse effects of diarrhea. Five out of eight evaluable patients achieved a PSA response; two achieved undetectable PSA and radiographic response. A novel niclosamide/PDMX1001 reformulation achieved targeted plasma levels when combined with abiraterone and prednisone, and was well tolerated. Further study of niclosamide/PDMX1001 with this combination is warranted.

Published
2021

31. Finding Effective Geo-Social Group for Impromptu Activity with Multiple Demands

Author

Chen, Lu, Liu, Chengfei, Zhou, Rui, Xu, Jiajie, and Li, Jianxin

Subjects
Computer Science - Databases, Computer Science - Data Structures and Algorithms
Abstract

Geo-social group search aims to find a group of people proximate to a location while socially related. One of the driven applications for geo-social group search is organizing an impromptu activity. This is because the social cohesiveness of a found geo-social group ensures a good communication atmosphere and the spatial closeness of the geo-social group reduces the preparation time for the activity. Most existing works treat geo-social group search as a problem that finds a group satisfying a single social constraint while optimizing the spatial proximity. However, when an impromptu activity has additional demands on attendees, e.g., the activity requires that the attendees have certain set of skills, the existing works cannot find an effective geo-social group efficiently. In this paper, we study how to find a group that is most proximate to a query location while satisfying multiple constraints. Specifically, the multiple constraints on which we focus include social constraint, size constraint and keyword constraint. We propose a novel search framework which first effectively narrows down the search space with theoretical guarantees and then efficiently finds the optimum result. Although our model considers multiple constraints, novel techniques devised in this paper ensure that search cost is equivalent to parameterized constant times of one time social constraint checking on a vastly restricted search space. We conduct extensive experiments on both real and semi-synthetic datasets for demonstrating the efficiency of the proposed search algorithm. To evaluate the effectiveness, we conduct two case studies on real datasets, demonstrating the superiority of our proposed model., Comment: 12 Pages with 1 Page References

Published
2019

33. Steroid Sulfatase Stimulates Intracrine Androgen Synthesis and is a Therapeutic Target for Advanced Prostate Cancer.

Author

Armstrong, Cameron M, Liu, Chengfei, Liu, Liangren, Yang, Joy C, Lou, Wei, Zhao, Ruining, Ning, Shu, Lombard, Alan P, Zhao, Jinge, D'Abronzo, Leandro S, Evans, Christopher P, Li, Pui-Kai, and Gao, Allen C

Subjects
Cell Line, Tumor, Humans, Prostatic Neoplasms, Benzamides, Nitriles, Phenylthiohydantoin, Androstenes, Dehydroepiandrosterone, Dehydroepiandrosterone Sulfate, Androgen Antagonists, Steryl-Sulfatase, Androgens, Neoplasm Staging, Cell Proliferation, Gene Expression Regulation, Neoplastic, Drug Resistance, Neoplasm, Male, Prostatic Neoplasms, Castration-Resistant, Carcinogenesis, RNA-Seq, Aging, Genetics, Clinical Research, Urologic Diseases, Cancer, Prostate Cancer, 5.1 Pharmaceuticals, Development of treatments and therapeutic interventions, Oncology and Carcinogenesis, Oncology & Carcinogenesis
Abstract

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.

Published
2020

36. Cross-Resistance Among Next-Generation Antiandrogen Drugs Through the AKR1C3/AR-V7 Axis in Advanced Prostate Cancer

Author

Zhao, Jinge, Ning, Shu, Lou, Wei, Yang, Joy C, Armstrong, Cameron M, Lombard, Alan P, D'Abronzo, Leandro S, Evans, Christopher P, Gao, Allen C, and Liu, Chengfei

Subjects
Cancer, Clinical Research, Urologic Diseases, Prostate Cancer, Aging, Development of treatments and therapeutic interventions, 5.1 Pharmaceuticals, Good Health and Well Being, Aldo-Keto Reductase Family 1 Member C3, Alternative Splicing, Androgen Receptor Antagonists, Apoptosis, Biomarkers, Tumor, Cell Proliferation, Drug Resistance, Neoplasm, Gene Expression Regulation, Neoplastic, Humans, Male, Prostatic Neoplasms, Castration-Resistant, Receptors, Androgen, Tumor Cells, Cultured, Oncology and Carcinogenesis, Pharmacology and Pharmaceutical Sciences, Oncology & Carcinogenesis
Abstract

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.

Published
2020

38. Bitcoin Transaction Confirmation Time Prediction: A Classification View

Author

Zhang, Limeng, Zhou, Rui, Liu, Qing, Xu, Jiajie, Liu, Chengfei, Goos, Gerhard, Founding Editor, Hartmanis, Juris, Founding Editor, Bertino, Elisa, Editorial Board Member, Gao, Wen, Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Yung, Moti, Editorial Board Member, Chbeir, Richard, editor, Huang, Helen, editor, Silvestri, Fabrizio, editor, Manolopoulos, Yannis, editor, and Zhang, Yanchun, editor

Published
2022
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39. Transportation-Mode Aware Travel Time Estimation via Meta-learning

Author

Fan, Yu, Xu, Jiajie, Zhou, Rui, Liu, Chengfei, Goos, Gerhard, Founding Editor, Hartmanis, Juris, Founding Editor, Bertino, Elisa, Editorial Board Member, Gao, Wen, Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Woeginger, Gerhard, Editorial Board Member, Yung, Moti, Editorial Board Member, Bhattacharya, Arnab, editor, Lee Mong Li, Janice, editor, Agrawal, Divyakant, editor, Reddy, P. Krishna, editor, Mohania, Mukesh, editor, Mondal, Anirban, editor, Goyal, Vikram, editor, and Uday Kiran, Rage, editor

Published
2022
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40. HRG: A Hybrid Retrieval and Generation Model in Multi-turn Dialogue

Author

Zhao, Deji, Liu, Xinyi, Ning, Bo, Liu, Chengfei, Goos, Gerhard, Founding Editor, Hartmanis, Juris, Founding Editor, Bertino, Elisa, Editorial Board Member, Gao, Wen, Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Woeginger, Gerhard, Editorial Board Member, Yung, Moti, Editorial Board Member, Bhattacharya, Arnab, editor, Lee Mong Li, Janice, editor, Agrawal, Divyakant, editor, Reddy, P. Krishna, editor, Mohania, Mukesh, editor, Mondal, Anirban, editor, Goyal, Vikram, editor, and Uday Kiran, Rage, editor

Published
2022
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41. AKR1C3 Promotes AR-V7 Protein Stabilization and Confers Resistance to AR-Targeted Therapies in Advanced Prostate Cancer

Author

Liu, Chengfei, Yang, Joy C, Armstrong, Cameron M, Lou, Wei, Liu, Liangren, Qiu, Xiaomin, Zou, Binhao, Lombard, Alan P, D'Abronzo, Leandro S, Evans, Christopher P, and Gao, Allen C

Subjects
Biochemistry and Cell Biology, Biomedical and Clinical Sciences, Biological Sciences, Clinical Sciences, Oncology and Carcinogenesis, Prostate Cancer, Urologic Diseases, Cancer, Aging, 5.1 Pharmaceuticals, Development of treatments and therapeutic interventions, 2.1 Biological and endogenous factors, Aetiology, Administration, Oral, Aldo-Keto Reductase Family 1 Member C3, Alternative Splicing, Animals, Benzamides, Cell Line, Tumor, Drug Resistance, Neoplasm, Humans, Indomethacin, Male, Mice, SCID, Molecular Targeted Therapy, Neoplasm Staging, Nitriles, Phenylthiohydantoin, Prostatic Neoplasms, Protein Binding, Protein Stability, Receptors, Androgen, Signal Transduction, Steroids, Pharmacology and Pharmaceutical Sciences, Oncology & Carcinogenesis, Biochemistry and cell biology, Oncology and carcinogenesis
Abstract

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.

Published
2019

46. Plexin D1 emerges as a novel target in the development of neural lineage plasticity in treatment-resistant prostate cancer

Author

Liu, Chengfei, primary, Chen, Bo, additional, Xu, Pengfei, additional, Yang, Joy, additional, Nip, Christopher, additional, Wang, Leyi, additional, Shen, Yuqiu, additional, Ning, Shu, additional, Shang, Yufeng, additional, Corey, Eva, additional, Gao, Allen C., additional, Gestwicki, Jason, additional, Wei, Qiang, additional, and Liu, Liangren, additional

Published
2024
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49. Overexpressed ABCB1 Induces Olaparib-Taxane Cross-Resistance in Advanced Prostate Cancer.

Author

Lombard, Alan P, Liu, Chengfei, Armstrong, Cameron M, D'Abronzo, Leandro S, Lou, Wei, Chen, Hongwu, Dall'Era, Marc, Ghosh, Paramita M, Evans, Christopher P, and Gao, Allen C

Subjects
Aging, Urologic Diseases, Genetics, Cancer, Prostate Cancer, Development of treatments and therapeutic interventions, 5.1 Pharmaceuticals, Evaluation of treatments and therapeutic interventions, 6.2 Cellular and gene therapies, Biochemistry and Cell Biology, Clinical Sciences, Oncology and Carcinogenesis, Oncology & Carcinogenesis
Abstract

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.

Published
2019

50. Wntless promotes cellular viability and resistance to enzalutamide in castration-resistant prostate cancer cells.

Author

Lombard, Alan P, Liu, Chengfei, Armstrong, Cameron M, D'Abronzo, Leandro S, Lou, Wei, Evans, Christopher P, and Gao, Allen C

Subjects
Biochemistry and Cell Biology, Biomedical and Clinical Sciences, Biological Sciences, Clinical Sciences, Oncology and Carcinogenesis, Biotechnology, Aging, Cancer, Genetics, Prostate Cancer, Urologic Diseases, 2.1 Biological and endogenous factors, Development of treatments and therapeutic interventions, 5.1 Pharmaceuticals, Aetiology, Wnt signaling, castration-resistant prostate cancer, enzalutamide resistance, wntless, wls, porcupine, porcn
Abstract

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 alterations in this disease may lead to the development of novel treatments.

Published
2019

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