1
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Altendorf T, Mohrlüder J, Willbold D. TSAT: Efficient evaluation software for NGS data of phage/mirror-image phage display selections. BIOPHYSICAL REPORTS 2024; 4:100166. [PMID: 38909902 PMCID: PMC11269273 DOI: 10.1016/j.bpr.2024.100166] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/30/2024] [Revised: 05/31/2024] [Accepted: 06/20/2024] [Indexed: 06/25/2024]
Abstract
Phage display and mirror-image phage display are commonly used techniques for the identification of binders that are specific to predefined targets. Recent studies demonstrated the effectiveness of next-generation sequencing (NGS) by increasing the amount of information extracted from selections. This allows for a better analysis and increases the possibility to select effective binders. A potential downside to NGS analysis of phage display selections is the increased workload that is needed to analyze the obtained information. Here, we report on the development of TSAT (target-specific analysis tool), software for user-friendly and efficient analysis of peptide sequence data from NGS of phage display selections.
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Affiliation(s)
- Tim Altendorf
- Institut für Biologische Informationsprozesse, IBI-7, Forschungszentrum Jülich, Jülich, Germany; Institut für Physikalische Biologie, Heinrich-Heine-Universität Düsseldorf, Düsseldorf, Germany
| | - Jeannine Mohrlüder
- Institut für Biologische Informationsprozesse, IBI-7, Forschungszentrum Jülich, Jülich, Germany.
| | - Dieter Willbold
- Institut für Biologische Informationsprozesse, IBI-7, Forschungszentrum Jülich, Jülich, Germany; Institut für Physikalische Biologie, Heinrich-Heine-Universität Düsseldorf, Düsseldorf, Germany.
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2
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Li Y, Li XM, Yang KD, Tong WH. Advancements in ovarian cancer immunodiagnostics and therapeutics via phage display technology. Front Immunol 2024; 15:1402862. [PMID: 38863706 PMCID: PMC11165035 DOI: 10.3389/fimmu.2024.1402862] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/18/2024] [Accepted: 05/13/2024] [Indexed: 06/13/2024] Open
Abstract
Ovarian cancer, ranking as the seventh most prevalent malignancy among women globally, faces significant challenges in diagnosis and therapeutic intervention. The difficulties in early detection are amplified by the limitations and inefficacies inherent in current screening methodologies, highlighting a pressing need for more efficacious diagnostic and treatment strategies. Phage display technology emerges as a pivotal innovation in this context, utilizing extensive phage-peptide libraries to identify ligands with specificity for cancer cell markers, thus enabling precision-targeted therapeutic strategies. This technology promises a paradigm shift in ovarian cancer management, concentrating on targeted drug delivery systems to improve treatment accuracy and efficacy while minimizing adverse effects. Through a meticulous review, this paper evaluates the revolutionary potential of phage display in enhancing ovarian cancer therapy, representing a significant advancement in combating this challenging disease. Phage display technology is heralded as an essential instrument for developing effective immunodiagnostic and therapeutic approaches in ovarian cancer, facilitating early detection, precision-targeted medication, and the implementation of customized treatment plans.
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Affiliation(s)
- Yang Li
- Obstetrics and Gynecology Center, First Hospital of Jilin University, Changchun, Jilin, China
- Department of Rehabilitation, School of Nursing, Jilin University, Changchun, China
| | - Xiao-meng Li
- Department of Rehabilitation, School of Nursing, Jilin University, Changchun, China
| | - Kai-di Yang
- Department of Rehabilitation, School of Nursing, Jilin University, Changchun, China
| | - Wei-hua Tong
- Obstetrics and Gynecology Center, First Hospital of Jilin University, Changchun, Jilin, China
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3
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Kim SM, Heo HR, Kim CS, Shin HH. Genetically engineered bacteriophages as novel nanomaterials: applications beyond antimicrobial agents. Front Bioeng Biotechnol 2024; 12:1319830. [PMID: 38725991 PMCID: PMC11079243 DOI: 10.3389/fbioe.2024.1319830] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/11/2023] [Accepted: 04/11/2024] [Indexed: 05/12/2024] Open
Abstract
Bacteriophages, also known as phages, are viruses that replicate in bacteria and archaea. Phages were initially discovered as antimicrobial agents, and they have been used as therapeutic agents for bacterial infection in a process known as "phage therapy." Recently, phages have been investigated as functional nanomaterials in a variety of areas, as they can function not only as therapeutic agents but also as biosensors and tissue regenerative materials. Phages are nontoxic to humans, and they possess self-assembled nanostructures and functional properties. Additionally, phages can be easily genetically modified to display specific peptides or to screen for functional peptides via phage display. Here, we demonstrated the application of phage nanomaterials in the context of tissue engineering, sensing, and probing.
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Affiliation(s)
- Seong-Min Kim
- Medical Device Development Center, Daegu-Gyeongbuk Medical Innovation Foundation, Daegu, Republic of Korea
| | - Hye Ryoung Heo
- Department of Chemical and Biochemical Engineering, Dongguk University, Seoul, Republic of Korea
| | - Chang Sup Kim
- Department of Chemical and Biochemical Engineering, Dongguk University, Seoul, Republic of Korea
| | - Hwa Hui Shin
- Medical Device Development Center, Daegu-Gyeongbuk Medical Innovation Foundation, Daegu, Republic of Korea
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4
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Asar M, Newton-Northup J, Soendergaard M. Improving Pharmacokinetics of Peptides Using Phage Display. Viruses 2024; 16:570. [PMID: 38675913 PMCID: PMC11055145 DOI: 10.3390/v16040570] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/19/2024] [Revised: 04/03/2024] [Accepted: 04/05/2024] [Indexed: 04/28/2024] Open
Abstract
Phage display is a versatile method often used in the discovery of peptides that targets disease-related biomarkers. A major advantage of this technology is the ease and cost efficiency of affinity selection, also known as biopanning, to identify novel peptides. While it is relatively straightforward to identify peptides with optimal binding affinity, the pharmacokinetics of the selected peptides often prove to be suboptimal. Therefore, careful consideration of the experimental conditions, including the choice of using in vitro, in situ, or in vivo affinity selections, is essential in generating peptides with high affinity and specificity that also demonstrate desirable pharmacokinetics. Specifically, in vivo biopanning, or the combination of in vitro, in situ, and in vivo affinity selections, has been proven to influence the biodistribution and clearance of peptides and peptide-conjugated nanoparticles. Additionally, the marked difference in properties between peptides and nanoparticles must be considered. While peptide biodistribution depends primarily on physiochemical properties and can be modified by amino acid modifications, the size and shape of nanoparticles also affect both absorption and distribution. Thus, optimization of the desired pharmacokinetic properties should be an important consideration in biopanning strategies to enable the selection of peptides and peptide-conjugated nanoparticles that effectively target biomarkers in vivo.
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Affiliation(s)
- Mallika Asar
- College of Osteopathic Medicine, Kansas City University, Kansas City, MO 64106, USA;
| | | | - Mette Soendergaard
- Cell Origins LLC, 1601 South Providence Road Columbia, Columbia, MO 65203, USA;
- Department of Chemistry, Western Illinois University, Macomb, IL 61455, USA
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5
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de Castilhos J, Tillmanns K, Blessing J, Laraño A, Borisov V, Stein-Thoeringer CK. Microbiome and pancreatic cancer: time to think about chemotherapy. Gut Microbes 2024; 16:2374596. [PMID: 39024520 PMCID: PMC11259062 DOI: 10.1080/19490976.2024.2374596] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/24/2024] [Accepted: 06/26/2024] [Indexed: 07/20/2024] Open
Abstract
Pancreatic ductal adenocarcinoma (PDAC) is a highly aggressive cancer characterized by late diagnosis, rapid progression, and a high mortality rate. Its complex biology, characterized by a dense, stromal tumor environment with an immunosuppressive milieu, contributes to resistance against standard treatments like chemotherapy and radiation. This comprehensive review explores the dynamic role of the microbiome in modulating chemotherapy efficacy and outcomes in PDAC. It delves into the microbiome's impact on drug metabolism and resistance, and the interaction between microbial elements, drugs, and human biology. We also highlight the significance of specific bacterial species and microbial enzymes in influencing drug action and the immune response in the tumor microenvironment. Cutting-edge methodologies, including artificial intelligence, low-biomass microbiome analysis and patient-derived organoid models, are discussed, offering insights into the nuanced interactions between microbes and cancer cells. The potential of microbiome-based interventions as adjuncts to conventional PDAC treatments are discussed, paving the way for personalized therapy approaches. This review synthesizes recent research to provide an in-depth understanding of how the microbiome affects chemotherapy efficacy. It focuses on elucidating key mechanisms and identifying existing knowledge gaps. Addressing these gaps is crucial for enhancing personalized medicine and refining cancer treatment strategies, ultimately improving patient outcomes.
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Affiliation(s)
- Juliana de Castilhos
- Translational Microbiome Research, Internal Medicine I and M3 Research Center, University Hospital Tuebingen, Tübingen, Germany
- Cluster of Excellence “Controlling Microbes to Fight Infections” (CMFI), University of Tuebingen, Tübingen, Germany
| | - Katharina Tillmanns
- Translational Microbiome Research, Internal Medicine I and M3 Research Center, University Hospital Tuebingen, Tübingen, Germany
- Cluster of Excellence “Controlling Microbes to Fight Infections” (CMFI), University of Tuebingen, Tübingen, Germany
| | - Jana Blessing
- Translational Microbiome Research, Internal Medicine I and M3 Research Center, University Hospital Tuebingen, Tübingen, Germany
- Cluster of Excellence “Controlling Microbes to Fight Infections” (CMFI), University of Tuebingen, Tübingen, Germany
| | - Arnelyn Laraño
- Translational Microbiome Research, Internal Medicine I and M3 Research Center, University Hospital Tuebingen, Tübingen, Germany
- Cluster of Excellence “Controlling Microbes to Fight Infections” (CMFI), University of Tuebingen, Tübingen, Germany
| | - Vadim Borisov
- Translational Microbiome Research, Internal Medicine I and M3 Research Center, University Hospital Tuebingen, Tübingen, Germany
- Cluster of Excellence “Controlling Microbes to Fight Infections” (CMFI), University of Tuebingen, Tübingen, Germany
| | - Christoph K. Stein-Thoeringer
- Translational Microbiome Research, Internal Medicine I and M3 Research Center, University Hospital Tuebingen, Tübingen, Germany
- Cluster of Excellence “Controlling Microbes to Fight Infections” (CMFI), University of Tuebingen, Tübingen, Germany
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6
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Li B, Chen H, Huang J, He B. CD47Binder: Identify CD47 Binding Peptides by Combining Next-Generation Phage Display Data and Multiple Peptide Descriptors. Interdiscip Sci 2023; 15:578-589. [PMID: 37389722 DOI: 10.1007/s12539-023-00575-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/09/2023] [Revised: 06/08/2023] [Accepted: 06/09/2023] [Indexed: 07/01/2023]
Abstract
CD47/SIRPα pathway is a new breakthrough in the field of tumor immunity after PD-1/PD-L1. While current monoclonal antibody therapies targeting CD47/SIRPα have demonstrated some anti-tumor effectiveness, there are several inherent limitations associated with these formulations. In the paper, we developed a predictive model that combines next-generation phage display (NGPD) and traditional machine learning methods to distinguish CD47 binding peptides. First, we utilized NGPD biopanning technology to screen CD47 binding peptides. Second, ten traditional machine learning methods based on multiple peptide descriptors and three deep learning methods were used to build computational models for identifying CD47 binding peptides. Finally, we proposed an integrated model based on support vector machine. During the five-fold cross-validation, the integrated predictor demonstrated specificity, accuracy, and sensitivity of 0.755, 0.764, and 0.772, respectively. Furthermore, an online bioinformatics tool called CD47Binder has been developed for the integrated predictor. This tool is readily accessible on http://i.uestc.edu.cn/CD47Binder/cgi-bin/CD47Binder.pl .
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Affiliation(s)
- Bowen Li
- Medical College, Guizhou University, Huaxi District, Guiyang, 550025, Guizhou, China
| | - Heng Chen
- Medical College, Guizhou University, Huaxi District, Guiyang, 550025, Guizhou, China.
| | - Jian Huang
- School of Life Science and Technology, University of Electronic Science and Technology of China, No.2006, Xiyuan Ave, West Hi-Tech Zone, Chengdu, 6173001, Sichuan, China.
| | - Bifang He
- Medical College, Guizhou University, Huaxi District, Guiyang, 550025, Guizhou, China.
- State Key Laboratory of Public Big Data, Guizhou University, Huaxi District, Guiyang, 550025, Guizhou, China.
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7
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Li Y, Yang KD, Duan HY, Du YN, Ye JF. Phage-based peptides for pancreatic cancer diagnosis and treatment: alternative approach. Front Microbiol 2023; 14:1231503. [PMID: 37601380 PMCID: PMC10433397 DOI: 10.3389/fmicb.2023.1231503] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/30/2023] [Accepted: 07/06/2023] [Indexed: 08/22/2023] Open
Abstract
Pancreatic cancer is a devastating disease with a high mortality rate and a lack of effective therapies. The challenges associated with early detection and the highly aggressive nature of pancreatic cancer have limited treatment options, underscoring the urgent need for better disease-modifying therapies. Peptide-based biotherapeutics have become an attractive area of research due to their favorable properties such as high selectivity and affinity, chemical modifiability, good tissue permeability, and easy metabolism and excretion. Phage display, a powerful technique for identifying peptides with high affinity and specificity for their target molecules, has emerged as a key tool in the discovery of peptide-based drugs. Phage display technology involves the use of bacteriophages to express peptide libraries, which are then screened against a target of interest to identify peptides with desired properties. This approach has shown great promise in cancer diagnosis and treatment, with potential applications in targeting cancer cells and developing new therapies. In this comprehensive review, we provide an overview of the basic biology of phage vectors, the principles of phage library construction, and various methods for binding affinity assessment. We then describe the applications of phage display in pancreatic cancer therapy, targeted drug delivery, and early detection. Despite its promising potential, there are still challenges to be addressed, such as optimizing the selection process and improving the pharmacokinetic properties of phage-based drugs. Nevertheless, phage display represents a promising approach for the development of novel targeted therapies in pancreatic cancer and other tumors.
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Affiliation(s)
- Yang Li
- General Surgery Center, First Hospital of Jilin University, Changchun, China
- School of Nursing, Jilin University, Changchun, China
| | - Kai-di Yang
- General Surgery Center, First Hospital of Jilin University, Changchun, China
- School of Nursing, Jilin University, Changchun, China
| | - Hao-yu Duan
- General Surgery Center, First Hospital of Jilin University, Changchun, China
- School of Nursing, Jilin University, Changchun, China
| | - Ya-nan Du
- General Surgery Center, First Hospital of Jilin University, Changchun, China
- School of Nursing, Jilin University, Changchun, China
| | - Jun-feng Ye
- General Surgery Center, First Hospital of Jilin University, Changchun, China
- School of Nursing, Jilin University, Changchun, China
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8
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Todaro B, Ottalagana E, Luin S, Santi M. Targeting Peptides: The New Generation of Targeted Drug Delivery Systems. Pharmaceutics 2023; 15:1648. [PMID: 37376097 DOI: 10.3390/pharmaceutics15061648] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/29/2023] [Revised: 05/22/2023] [Accepted: 05/29/2023] [Indexed: 06/29/2023] Open
Abstract
Peptides can act as targeting molecules, analogously to oligonucleotide aptamers and antibodies. They are particularly efficient in terms of production and stability in physiological environments; in recent years, they have been increasingly studied as targeting agents for several diseases, from tumors to central nervous system disorders, also thanks to the ability of some of them to cross the blood-brain barrier. In this review, we will describe the techniques employed for their experimental and in silico design, as well as their possible applications. We will also discuss advancements in their formulation and chemical modifications that make them even more stable and effective. Finally, we will discuss how their use could effectively help to overcome various physiological problems and improve existing treatments.
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Affiliation(s)
- Biagio Todaro
- NEST Laboratory, Scuola Normale Superiore, Piazza San Silvestro 12, 56127 Pisa, Italy
| | - Elisa Ottalagana
- NEST Laboratory, Scuola Normale Superiore, Piazza San Silvestro 12, 56127 Pisa, Italy
- Fondazione Pisana per la Scienza, Via Ferruccio Giovannini 13, San Giuliano Terme, 56017 Pisa, Italy
| | - Stefano Luin
- NEST Laboratory, Scuola Normale Superiore, Piazza San Silvestro 12, 56127 Pisa, Italy
- NEST, Istituto Nanoscienze-CNR and Scuola Normale Superiore, Piazza San Silvestro 12, 56127 Pisa, Italy
| | - Melissa Santi
- NEST, Istituto Nanoscienze-CNR and Scuola Normale Superiore, Piazza San Silvestro 12, 56127 Pisa, Italy
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9
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Attebury H, Daley D. The Gut Microbiome and Pancreatic Cancer Development and Treatment. Cancer J 2023; 29:49-56. [PMID: 36957973 PMCID: PMC10042586 DOI: 10.1097/ppo.0000000000000647] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/25/2023]
Abstract
ABSTRACT Changes in the gut microbiome have been increasingly shown to accompany oncogenesis across various tumors. Similarly, microbial dysbiosis was found to be associated with pancreatic cancer progression and survival outcomes, expanding the field of tumor microenvironment research in pancreatic cancer. Mechanistic studies in pancreatic cancer models implicate components of the gut and pancreatic cancer microbiome in regulating tumorigenesis by altering cancer cell signaling, modulating immune function, and influencing the efficacy of current therapies in pancreatic cancer. This review discusses the outcomes of microbial modulation across various preclinical and clinical studies and highlights ongoing trials targeting the microbiome for pancreatic cancer therapy.
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10
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He B, Li B, Chen X, Zhang Q, Lu C, Yang S, Long J, Ning L, Chen H, Huang J. PDL1Binder: Identifying programmed cell death ligand 1 binding peptides by incorporating next-generation phage display data and different peptide descriptors. Front Microbiol 2022; 13:928774. [PMID: 35910615 PMCID: PMC9335124 DOI: 10.3389/fmicb.2022.928774] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/26/2022] [Accepted: 06/27/2022] [Indexed: 11/13/2022] Open
Abstract
Monoclonal antibody drugs targeting the PD-1/PD-L1 pathway have showed efficacy in the treatment of cancer patients, however, they have many intrinsic limitations and inevitable drawbacks. Peptide inhibitors as alternatives might compensate for the drawbacks of current PD-1/PD-L1 interaction blockers. Identifying PD-L1 binding peptides by random peptide library screening is a time-consuming and labor-intensive process. Machine learning-based computational models enable rapid discovery of peptide candidates targeting the PD-1/PD-L1 pathway. In this study, we first employed next-generation phage display (NGPD) biopanning to isolate PD-L1 binding peptides. Different peptide descriptors and feature selection methods as well as diverse machine learning methods were then incorporated to implement predictive models of PD-L1 binding. Finally, we proposed PDL1Binder, an ensemble computational model for efficiently obtaining PD-L1 binding peptides. Our results suggest that predictive models of PD-L1 binding can be learned from deep sequencing data and provide a new path to discover PD-L1 binding peptides. A web server was implemented for PDL1Binder, which is freely available at http://i.uestc.edu.cn/pdl1binder/cgi-bin/PDL1Binder.pl.
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Affiliation(s)
- Bifang He
- Medical College, Guizhou University, Guiyang, China
| | - Bowen Li
- Medical College, Guizhou University, Guiyang, China
| | - Xue Chen
- Medical College, Guizhou University, Guiyang, China
| | | | - Chunying Lu
- Medical College, Guizhou University, Guiyang, China
| | | | - Jinjin Long
- Medical College, Guizhou University, Guiyang, China
| | - Lin Ning
- School of Healthcare Technology, Chengdu Neusoft University, Chengdu, China
| | - Heng Chen
- Medical College, Guizhou University, Guiyang, China
- *Correspondence: Heng Chen,
| | - Jian Huang
- School of Life Sciences and Technology, University of Electronic Science and Technology of China, Chengdu, China
- Jian Huang,
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11
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Chandra V, McAllister F. Therapeutic potential of microbial modulation in pancreatic cancer. Gut 2021; 70:gutjnl-2019-319807. [PMID: 33906958 PMCID: PMC8292583 DOI: 10.1136/gutjnl-2019-319807] [Citation(s) in RCA: 17] [Impact Index Per Article: 5.7] [Reference Citation Analysis] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/13/2020] [Revised: 03/16/2021] [Accepted: 04/12/2021] [Indexed: 02/06/2023]
Affiliation(s)
- Vidhi Chandra
- Department of Clinical Cancer Prevention, Houston, Texas, USA
| | - Florencia McAllister
- Department of Clinical Cancer Prevention, Houston, Texas, USA
- Department of Gastrointestinal Medical Oncology, University of Texas MD Anderson Cancer Center, Houston, Texas, USA
- Department of Immunology, University of Texas MD Anderson Cancer Center, Houston, Texas, USA
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12
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Zhao S, Li C, Gao Y, Qian L, Dong J, Zhai L, Chen B, Zhang J. Screening and Identification of a Specific Binding Peptide to Ovarian Cancer Cells from a Phage-Displayed Peptide Library. Int J Pept Res Ther 2021; 27:1741-1749. [PMID: 33841057 PMCID: PMC8019349 DOI: 10.1007/s10989-021-10206-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 03/24/2021] [Indexed: 11/25/2022]
Abstract
To select specific binding peptides for imaging and detection of human ovarian cancer. The phage 12-mer peptide library was used to select specific phage clones to ovarian cancer cells. After four rounds of biopanning, the binding specificity of randomly selected phage clones to ovarian cancer cells was determined by enzyme-linked immunosorbent assay (ELISA). DNA sequencing and homology analysis were performed on specifically bound phages. The binding ability of the selected peptides to SKOV3 cells was confirmed by fluorescence microscopy and flow cytometry. After four rounds of optimized biological panning, phage recovery was 34-fold higher than that of the first round, and the specific phage clones bound to SKOV3 cells were significantly enriched. A total of 32 positive phage clones were preliminarily identified by ELISA from 54 randomly selected clones, and the positive rate was 59.3%. S36 was identified as the clone with best affinity to SKOV3 cells via fluorescence microscopy and flow cytometry. A representative clone of OSP2, S36 is expected to be an effective probe for diagnosis and treatment of ovarian cancer.
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Affiliation(s)
- Shuhui Zhao
- Department of Obstetrics and Gynecology, Xijing Hospital, The Fourth Military Medical University, Xi'an, 710032 Shaanxi China.,Department of Obstetrics and Gynecology, Baiyin Central Hospital, Baiyin, 730913 Gansu China
| | - Chunyan Li
- Department of Obstetrics and Gynecology, Xijing Hospital, The Fourth Military Medical University, Xi'an, 710032 Shaanxi China
| | - Yunge Gao
- Department of Obstetrics and Gynecology, Xijing Hospital, The Fourth Military Medical University, Xi'an, 710032 Shaanxi China
| | - Luomeng Qian
- Department of Obstetrics and Gynecology, Xijing Hospital, The Fourth Military Medical University, Xi'an, 710032 Shaanxi China
| | - Jian Dong
- Department of Obstetrics and Gynecology, Xijing Hospital, The Fourth Military Medical University, Xi'an, 710032 Shaanxi China
| | - Lianghao Zhai
- Department of Obstetrics and Gynecology, Xijing Hospital, The Fourth Military Medical University, Xi'an, 710032 Shaanxi China
| | - Biliang Chen
- Department of Obstetrics and Gynecology, Xijing Hospital, The Fourth Military Medical University, Xi'an, 710032 Shaanxi China
| | - Jianfang Zhang
- Department of Obstetrics and Gynecology, Xijing Hospital, The Fourth Military Medical University, Xi'an, 710032 Shaanxi China
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