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  1. Article ; Online: Adaptive phase I-II clinical trial designs identifying optimal biological doses for targeted agents and immunotherapies.

    Zang, Yong / Guo, Beibei / Qiu, Yingjie / Liu, Hao / Opyrchal, Mateusz / Lu, Xiongbin

    Clinical trials (London, England)

    2024  , Page(s) 17407745231220661

    Abstract: Targeted agents and immunotherapies have revolutionized cancer treatment, offering promising options for various cancer types. Unlike traditional therapies the principle of "more is better" is not always applicable to these new therapies due to their ... ...

    Abstract Targeted agents and immunotherapies have revolutionized cancer treatment, offering promising options for various cancer types. Unlike traditional therapies the principle of "more is better" is not always applicable to these new therapies due to their unique biomedical mechanisms. As a result, various phase I-II clinical trial designs have been proposed to identify the optimal biological dose that maximizes the therapeutic effect of targeted therapies and immunotherapies by jointly monitoring both efficacy and toxicity outcomes. This review article examines several innovative phase I-II clinical trial designs that utilize accumulated efficacy and toxicity outcomes to adaptively determine doses for subsequent patients and identify the optimal biological dose, maximizing the overall therapeutic effect. Specifically, we highlight three categories of phase I-II designs: efficacy-driven, utility-based, and designs incorporating multiple efficacy endpoints. For each design, we review the dose-outcome model, the definition of the optimal biological dose, the dose-finding algorithm, and the software for trial implementation. To illustrate the concepts, we also present two real phase I-II trial examples utilizing the EffTox and ISO designs. Finally, we provide a classification tree to summarize the designs discussed in this article.
    Language English
    Publishing date 2024-01-11
    Publishing country England
    Document type Journal Article
    ZDB-ID 2138796-5
    ISSN 1740-7753 ; 1740-7745
    ISSN (online) 1740-7753
    ISSN 1740-7745
    DOI 10.1177/17407745231220661
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  2. Article ; Online: Harnessing tumorous flaws for immune supremacy

    Samantha Sharma / Mateusz Opyrchal / Xiongbin Lu

    The Journal of Clinical Investigation, Vol 132, Iss

    is miRNA-155 the weak link in breast cancer progression?

    2022  Volume 19

    Abstract: With the advent of immune checkpoint blockade (ICB) therapy, treatment strategies for late-stage cancers have seen a radical advancement. In this issue of the JCI, Wang et al. characterize the functional role of miR-155 in breast cancer and its potential ...

    Abstract With the advent of immune checkpoint blockade (ICB) therapy, treatment strategies for late-stage cancers have seen a radical advancement. In this issue of the JCI, Wang et al. characterize the functional role of miR-155 in breast cancer and its potential in harnessing the efficacy of immunotherapy. The study reports that high expression levels of miR-155 in breast cancer cells downregulated suppressor of cytokine signaling 1 (SOCS1), increased the phosphorylated STAT1 (pSTAT1)/pSTAT3 ratio, and thereby stimulated chemoattractants for tumor infiltration of effector T cells. Moreover, miR-155 overexpression set the stage for ICB therapy via increased programmed death ligand 1 (PD-L1) expression on cancer cells and enhanced immunological memory response via the release of miR-155–containing extracellular vesicles. Collectively, these data suggest that miR-155 is a strong candidate as a prognostic biomarker for ICB therapy.
    Keywords Medicine ; R
    Subject code 616
    Language English
    Publishing date 2022-10-01T00:00:00Z
    Publisher American Society for Clinical Investigation
    Document type Article ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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  3. Article: Retraction of "Overcoming Ovarian Cancer Drug Resistance with a Cold Responsive Nanomaterial".

    Wang, Hai / Agarwal, Pranay / Zhao, Gang / Ji, Guang / Jewell, Christopher M / Fisher, John P / Lu, Xiongbin / He, Xiaoming

    ACS central science

    2023  Volume 9, Issue 4, Page(s) 844

    Abstract: This retracts the article DOI: 10.1021/acscentsci.8b00050.]. ...

    Abstract [This retracts the article DOI: 10.1021/acscentsci.8b00050.].
    Language English
    Publishing date 2023-04-11
    Publishing country United States
    Document type Retraction of Publication
    ISSN 2374-7943
    ISSN 2374-7943
    DOI 10.1021/acscentsci.3c00335
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  4. Article ; Online: Harnessing tumorous flaws for immune supremacy: is miRNA-155 the weak link in breast cancer progression?

    Sharma, Samantha / Opyrchal, Mateusz / Lu, Xiongbin

    The Journal of clinical investigation

    2022  Volume 132, Issue 19

    Abstract: With the advent of immune checkpoint blockade (ICB) therapy, treatment strategies for late-stage cancers have seen a radical advancement. In this issue of the JCI, Wang et al. characterize the functional role of miR-155 in breast cancer and its potential ...

    Abstract With the advent of immune checkpoint blockade (ICB) therapy, treatment strategies for late-stage cancers have seen a radical advancement. In this issue of the JCI, Wang et al. characterize the functional role of miR-155 in breast cancer and its potential in harnessing the efficacy of immunotherapy. The study reports that high expression levels of miR-155 in breast cancer cells downregulated suppressor of cytokine signaling 1 (SOCS1), increased the phosphorylated STAT1 (pSTAT1)/pSTAT3 ratio, and thereby stimulated chemoattractants for tumor infiltration of effector T cells. Moreover, miR-155 overexpression set the stage for ICB therapy via increased programmed death ligand 1 (PD-L1) expression on cancer cells and enhanced immunological memory response via the release of miR-155-containing extracellular vesicles. Collectively, these data suggest that miR-155 is a strong candidate as a prognostic biomarker for ICB therapy.
    MeSH term(s) B7-H1 Antigen/metabolism ; Biomarkers ; Breast Neoplasms/drug therapy ; Breast Neoplasms/therapy ; Chemotactic Factors/therapeutic use ; Cytokines ; Female ; Humans ; Immune Checkpoint Inhibitors ; Immunotherapy ; MicroRNAs/genetics ; MicroRNAs/metabolism
    Chemical Substances B7-H1 Antigen ; Biomarkers ; Chemotactic Factors ; Cytokines ; Immune Checkpoint Inhibitors ; MIRN155 microRNA, human ; MicroRNAs
    Language English
    Publishing date 2022-10-03
    Publishing country United States
    Document type Journal Article ; Research Support, N.I.H., Extramural ; Research Support, Non-U.S. Gov't ; Comment
    ZDB-ID 3067-3
    ISSN 1558-8238 ; 0021-9738
    ISSN (online) 1558-8238
    ISSN 0021-9738
    DOI 10.1172/JCI163010
    Database MEDical Literature Analysis and Retrieval System OnLINE

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    Ua VI Zs.184: Show issues Location:
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  5. Article ; Online: Rg1 alleviates oxidative stress and spermatogonium apoptosis in D-gal-induced testicular toxicity by activating Akt.

    Wang, Ziling / Du, Kunhang / Hou, Jiying / Xiao, Hanxianzhi / Hu, Ling / Chen, Xiongbin / Wang, Lu / Wang, Yaping

    Redox report : communications in free radical research

    2023  Volume 28, Issue 1, Page(s) 2206197

    Abstract: ... ...

    Abstract ABSTRACT
    MeSH term(s) Animals ; Male ; Mice ; Antioxidants/pharmacology ; Antioxidants/metabolism ; Apoptosis ; Glycogen Synthase Kinase 3 beta/metabolism ; Glycogen Synthase Kinase 3 beta/pharmacology ; Mice, Inbred C57BL ; Oxidative Stress ; Proto-Oncogene Proteins c-akt/metabolism ; Spermatogonia/metabolism ; Testis/metabolism
    Chemical Substances Antioxidants ; Glycogen Synthase Kinase 3 beta (EC 2.7.11.1) ; Proto-Oncogene Proteins c-akt (EC 2.7.11.1) ; PPP1R3A protein, mouse (EC 3.1.3.-)
    Language English
    Publishing date 2023-04-27
    Publishing country England
    Document type Journal Article
    ZDB-ID 1305290-1
    ISSN 1743-2928 ; 1351-0002
    ISSN (online) 1743-2928
    ISSN 1351-0002
    DOI 10.1080/13510002.2023.2206197
    Database MEDical Literature Analysis and Retrieval System OnLINE

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    In stock of ZB MED Cologne/Königswinter

    Zs.A 4584: Show issues Location:
    Je nach Verfügbarkeit (siehe Angabe bei Bestand)
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    Jg. 1995 - 2021: Lesesall (2.OG)
    ab Jg. 2022: Lesesaal (EG)

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  6. Article ; Online: Bioinspired One Cell Culture Isolates Highly Tumorigenic and Metastatic Cancer Stem Cells Capable of Multilineage Differentiation.

    Wang, Hai / Agarwal, Pranay / Jiang, Bin / Stewart, Samantha / Liu, Xuanyou / Liang, Yutong / Hancioglu, Baris / Webb, Amy / Fisher, John P / Liu, Zhenguo / Lu, Xiongbin / Tkaczuk, Katherine H R / He, Xiaoming

    Advanced science (Weinheim, Baden-Wurttemberg, Germany)

    2023  Volume 10, Issue 12, Page(s) e2301726

    Language English
    Publishing date 2023-04-26
    Publishing country Germany
    Document type Published Erratum
    ZDB-ID 2808093-2
    ISSN 2198-3844 ; 2198-3844
    ISSN (online) 2198-3844
    ISSN 2198-3844
    DOI 10.1002/advs.202301726
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  7. Article ; Online: PLUS

    Junyi Zhou / Xiaoyu Lu / Wennan Chang / Changlin Wan / Xiongbin Lu / Chi Zhang / Sha Cao

    PLoS Computational Biology, Vol 18, Iss 3, p e

    Predicting cancer metastasis potential based on positive and unlabeled learning.

    2022  Volume 1009956

    Abstract: Metastatic cancer accounts for over 90% of all cancer deaths, and evaluations of metastasis potential are vital for minimizing the metastasis-associated mortality and achieving optimal clinical decision-making. Computational assessment of metastasis ... ...

    Abstract Metastatic cancer accounts for over 90% of all cancer deaths, and evaluations of metastasis potential are vital for minimizing the metastasis-associated mortality and achieving optimal clinical decision-making. Computational assessment of metastasis potential based on large-scale transcriptomic cancer data is challenging because metastasis events are not always clinically detectable. The under-diagnosis of metastasis events results in biased classification labels, and classification tools using biased labels may lead to inaccurate estimations of metastasis potential. This issue is further complicated by the unknown metastasis prevalence at the population level, the small number of confirmed metastasis cases, and the high dimensionality of the candidate molecular features. Our proposed algorithm, called Positive and unlabeled Learning from Unbalanced cases and Sparse structures (PLUS), is the first to use a positive and unlabeled learning framework to account for the under-detection of metastasis events in building a classifier. PLUS is specifically tailored for studying metastasis that deals with the unbalanced instance allocation as well as unknown metastasis prevalence, which are not considered by other methods. PLUS achieves superior performance on synthetic datasets compared with other state-of-the-art methods. Application of PLUS to The Cancer Genome Atlas Pan-Cancer gene expression data generated metastasis potential predictions that show good agreement with the clinical follow-up data, in addition to predictive genes that have been validated by independent single-cell RNA-sequencing datasets.
    Keywords Biology (General) ; QH301-705.5
    Subject code 006
    Language English
    Publishing date 2022-03-01T00:00:00Z
    Publisher Public Library of Science (PLoS)
    Document type Article ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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  8. Article ; Online: PLUS: Predicting cancer metastasis potential based on positive and unlabeled learning.

    Zhou, Junyi / Lu, Xiaoyu / Chang, Wennan / Wan, Changlin / Lu, Xiongbin / Zhang, Chi / Cao, Sha

    PLoS computational biology

    2022  Volume 18, Issue 3, Page(s) e1009956

    Abstract: Metastatic cancer accounts for over 90% of all cancer deaths, and evaluations of metastasis potential are vital for minimizing the metastasis-associated mortality and achieving optimal clinical decision-making. Computational assessment of metastasis ... ...

    Abstract Metastatic cancer accounts for over 90% of all cancer deaths, and evaluations of metastasis potential are vital for minimizing the metastasis-associated mortality and achieving optimal clinical decision-making. Computational assessment of metastasis potential based on large-scale transcriptomic cancer data is challenging because metastasis events are not always clinically detectable. The under-diagnosis of metastasis events results in biased classification labels, and classification tools using biased labels may lead to inaccurate estimations of metastasis potential. This issue is further complicated by the unknown metastasis prevalence at the population level, the small number of confirmed metastasis cases, and the high dimensionality of the candidate molecular features. Our proposed algorithm, called Positive and unlabeled Learning from Unbalanced cases and Sparse structures (PLUS), is the first to use a positive and unlabeled learning framework to account for the under-detection of metastasis events in building a classifier. PLUS is specifically tailored for studying metastasis that deals with the unbalanced instance allocation as well as unknown metastasis prevalence, which are not considered by other methods. PLUS achieves superior performance on synthetic datasets compared with other state-of-the-art methods. Application of PLUS to The Cancer Genome Atlas Pan-Cancer gene expression data generated metastasis potential predictions that show good agreement with the clinical follow-up data, in addition to predictive genes that have been validated by independent single-cell RNA-sequencing datasets.
    MeSH term(s) Algorithms ; Humans ; Neoplasms
    Language English
    Publishing date 2022-03-29
    Publishing country United States
    Document type Journal Article ; Research Support, U.S. Gov't, Non-P.H.S. ; Research Support, Non-U.S. Gov't
    ZDB-ID 2193340-6
    ISSN 1553-7358 ; 1553-734X
    ISSN (online) 1553-7358
    ISSN 1553-734X
    DOI 10.1371/journal.pcbi.1009956
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  9. Article ; Online: Rg1 alleviates oxidative stress and spermatogonium apoptosis in D-gal-induced testicular toxicity by activating Akt

    Ziling Wang / Kunhang Du / Jiying Hou / Hanxianzhi Xiao / Ling Hu / Xiongbin Chen / Lu Wang / Yaping Wang

    Redox Report, Vol 28, Iss

    2023  Volume 1

    Abstract: ABSTRACTObjectives: High reactive oxygen species (ROS) levels lead to cell death, and the testes are among the most vulnerable organs to oxidative damage. Rg1, an active ingredient extracted from the natural medicine ginseng, has potential anti- ... ...

    Abstract ABSTRACTObjectives: High reactive oxygen species (ROS) levels lead to cell death, and the testes are among the most vulnerable organs to oxidative damage. Rg1, an active ingredient extracted from the natural medicine ginseng, has potential anti-inflammatory, antioxidant and antiapoptotic properties. Our previous studies showed that Rg1 can effectively improve spermatogenic function in mice, but the specific mechanism remains unclear. The purpose of this study was to investigate the effect of Rg1 on oxidative stress and spermatogonium apoptosis in D-gal-induced testicular toxicity and elucidate the associated mechanism.Methods: Male C57BL/6 mice at 6–8 weeks of age were intraperitoneally injected with D-gal (200 mg/kg) for 42 days to establish a testicular injury model, and on day 16, 40 mg/kg Rg1-rich saline was injected intraperitoneally. Concurrently, we established an in vitro model of D-gal-damaged spermatogonia, which was treated with Rg1.Results: We found that treatment with the ginsenoside Rg1 reduced D-gal-induced oxidative stress and spermatogonium apoptosis in vivo and in vitro. Mechanistically, we found that Rg1 activated Akt/bad signaling and reduced D-gal-induced spermatogonium apoptosis.Discussion: We provide evidence showing that the antioxidant effect of Rg1 is mediated by the Akt/GSK-3β/NRF2 axis. Based on these findings, we consider Rg1 a potential treatment for testicular oxidative damage.
    Keywords Ginsenoside Rg1 ; testis ; oxidative damage ; apoptosis ; Pathology ; RB1-214 ; Biology (General) ; QH301-705.5
    Subject code 500
    Language English
    Publishing date 2023-12-01T00:00:00Z
    Publisher Taylor & Francis Group
    Document type Article ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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  10. Article: N

    Niu, Yi / Wan, Arabella / Lin, Ziyou / Lu, Xiongbin / Wan, Guohui

    Acta pharmaceutica Sinica. B

    2018  Volume 8, Issue 6, Page(s) 833–843

    Abstract: ... ...

    Abstract N
    Language English
    Publishing date 2018-06-06
    Publishing country Netherlands
    Document type Journal Article ; Review
    ISSN 2211-3835
    ISSN 2211-3835
    DOI 10.1016/j.apsb.2018.06.001
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