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Robitaille MC, Kim C, Christodoulides JA, Calhoun PJ, Kang W, Liu J, Byers JM, Raphael MP. Topographical depth reveals contact guidance mechanism distinct from focal adhesion confinement. Cytoskeleton (Hoboken) 2024; 81:238-248. [PMID: 38226738 DOI: 10.1002/cm.21810] [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: 01/12/2023] [Revised: 09/27/2023] [Accepted: 11/06/2023] [Indexed: 01/17/2024]
Abstract
Cellular response to the topography of their environment, known as contact guidance, is a crucial aspect to many biological processes yet remains poorly understood. A prevailing model to describe cellular contact guidance involves the lateral confinement of focal adhesions (FA) by topography as an underlying mechanism governing how cells can respond to topographical cues. However, it is not clear how this model is consistent with the well-documented depth-dependent contact guidance responses in the literature. To investigate this model, we fabricated a set of contact guidance chips with lateral dimensions capable of confining focal adhesions and relaxing that confinement at various depths. We find at the shallowest depth of 330 nm, the model of focal adhesion confinement is consistent with our observations. However, the cellular response at depths of 725 and 1000 nm is inadequately explained by this model. Instead, we observe a distinct reorganization of F-actin at greater depths in which topographically induced cell membrane deformation alters the structure of the cytoskeleton. These results are consistent with an alternative curvature-hypothesis to explain cellular response to topographical cues. Together, these results indicate a confluence of two molecular mechanisms operating at increased induced membrane curvature that govern how cells sense and respond to topography.
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Affiliation(s)
| | - Chunghwan Kim
- School for Engineering of Matter, Transport and Energy, Arizona State University, Tempe, Arizona, USA
| | | | | | - Wonmo Kang
- School for Engineering of Matter, Transport and Energy, Arizona State University, Tempe, Arizona, USA
| | - Jinny Liu
- U.S. Naval Research Laboratory, Washington, DC, USA
| | - Jeff M Byers
- U.S. Naval Research Laboratory, Washington, DC, USA
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Zhou L, Lu Y, Liu W, Wang S, Wang L, Zheng P, Zi G, Liu H, Liu W, Wei S. Drug conjugates for the treatment of lung cancer: from drug discovery to clinical practice. Exp Hematol Oncol 2024; 13:26. [PMID: 38429828 PMCID: PMC10908151 DOI: 10.1186/s40164-024-00493-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/06/2024] [Accepted: 02/21/2024] [Indexed: 03/03/2024] Open
Abstract
A drug conjugate consists of a cytotoxic drug bound via a linker to a targeted ligand, allowing the targeted delivery of the drug to one or more tumor sites. This approach simultaneously reduces drug toxicity and increases efficacy, with a powerful combination of efficient killing and precise targeting. Antibody‒drug conjugates (ADCs) are the best-known type of drug conjugate, combining the specificity of antibodies with the cytotoxicity of chemotherapeutic drugs to reduce adverse reactions by preferentially targeting the payload to the tumor. The structure of ADCs has also provided inspiration for the development of additional drug conjugates. In recent years, drug conjugates such as ADCs, peptide‒drug conjugates (PDCs) and radionuclide drug conjugates (RDCs) have been approved by the Food and Drug Administration (FDA). The scope and application of drug conjugates have been expanding, including combination therapy and precise drug delivery, and a variety of new conjugation technology concepts have emerged. Additionally, new conjugation technology-based drugs have been developed in industry. In addition to chemotherapy, targeted therapy and immunotherapy, drug conjugate therapy has undergone continuous development and made significant progress in treating lung cancer in recent years, offering a promising strategy for the treatment of this disease. In this review, we discuss recent advances in the use of drug conjugates for lung cancer treatment, including structure-based drug design, mechanisms of action, clinical trials, and side effects. Furthermore, challenges, potential approaches and future prospects are presented.
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Affiliation(s)
- Ling Zhou
- Department of Respiratory and Critical Care Medicine, National Health Commission (NHC) Key Laboratory of Respiratory Disease, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Yunlong Lu
- Jiangsu Collaborative Innovation Center of Chinese Medicinal Resources Industrialization, School of Medicine, Nanjing University of Chinese Medicine, Nanjing, 210023, China
| | - Wei Liu
- Department of Geriatrics, Key Laboratory of Vascular Aging, Ministry of Education, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430030, China
| | - Shanglong Wang
- Jiangsu Collaborative Innovation Center of Chinese Medicinal Resources Industrialization, School of Medicine, Nanjing University of Chinese Medicine, Nanjing, 210023, China
| | - Lingling Wang
- Department of Respiratory and Critical Care Medicine, National Health Commission (NHC) Key Laboratory of Respiratory Disease, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Pengdou Zheng
- Department of Respiratory and Critical Care Medicine, National Health Commission (NHC) Key Laboratory of Respiratory Disease, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Guisha Zi
- Department of Respiratory and Critical Care Medicine, National Health Commission (NHC) Key Laboratory of Respiratory Disease, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Huiguo Liu
- Department of Respiratory and Critical Care Medicine, National Health Commission (NHC) Key Laboratory of Respiratory Disease, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Wukun Liu
- Jiangsu Collaborative Innovation Center of Chinese Medicinal Resources Industrialization, School of Medicine, Nanjing University of Chinese Medicine, Nanjing, 210023, China.
- Department of Respiratory and Critical Care Medicine, Shanxi Bethune Hospital, Shanxi Academy of Medical Sciences, Tongji Shanxi Hospital, Third Hospital of Shanxi Medical University, Taiyuan, 030000, China.
| | - Shuang Wei
- Department of Respiratory and Critical Care Medicine, National Health Commission (NHC) Key Laboratory of Respiratory Disease, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
- Department of Respiratory and Critical Care Medicine, Shanxi Bethune Hospital, Shanxi Academy of Medical Sciences, Tongji Shanxi Hospital, Third Hospital of Shanxi Medical University, Taiyuan, 030000, China.
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Robitaille MC, Byers JM, Christodoulides JA, Raphael MP. Self-supervised machine learning for live cell imagery segmentation. Commun Biol 2022; 5:1162. [PMID: 36323790 PMCID: PMC9630527 DOI: 10.1038/s42003-022-04117-x] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/26/2022] [Accepted: 10/14/2022] [Indexed: 11/05/2022] Open
Abstract
Segmenting single cells is a necessary process for extracting quantitative data from biological microscopy imagery. The past decade has seen the advent of machine learning (ML) methods to aid in this process, the overwhelming majority of which fall under supervised learning (SL) which requires vast libraries of pre-processed, human-annotated labels to train the ML algorithms. Such SL pre-processing is labor intensive, can introduce bias, varies between end-users, and has yet to be shown capable of robust models to be effectively utilized throughout the greater cell biology community. Here, to address this pre-processing problem, we offer a self-supervised learning (SSL) approach that utilizes cellular motion between consecutive images to self-train a ML classifier, enabling cell and background segmentation without the need for adjustable parameters or curated imagery. By leveraging motion, we achieve accurate segmentation that trains itself directly on end-user data, is independent of optical modality, outperforms contemporary SL methods, and does so in a completely automated fashion-thus eliminating end-user variability and bias. To the best of our knowledge, this SSL algorithm represents a first of its kind effort and has appealing features that make it an ideal segmentation tool candidate for the broader cell biology research community.
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Affiliation(s)
- Michael C Robitaille
- Materials Science and Technology Division, U.S. Naval Research Laboratory, Washington, DC, USA
| | - Jeff M Byers
- Materials Science and Technology Division, U.S. Naval Research Laboratory, Washington, DC, USA
| | | | - Marc P Raphael
- Materials Science and Technology Division, U.S. Naval Research Laboratory, Washington, DC, USA.
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Robitaille MC, Christodoulides JA, Calhoun PJ, Byers JM, Raphael MP. Interfacing Live Cells with Surfaces: A Concurrent Control Technique for Quantifying Surface Ligand Activity. ACS APPLIED BIO MATERIALS 2021; 4:7856-7864. [PMID: 35006767 DOI: 10.1021/acsabm.1c00797] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
Abstract
Surface ligand activity is a key design parameter for successfully interfacing surfaces with cells─whether in the context of in vitro investigations for understanding cellular signaling pathways or more applied applications in drug delivery and medical implants. Unlike other crucial surface parameters, such as stiffness and roughness, surface ligand activity is typically based on a set of assumptions rather than directly measured, giving rise to interpretations of cell adhesion that can vary with the assumptions made. To fill this void, we have developed a concurrent control technique for directly characterizing in vitro ligand surface activity. Pairs of gold-coated glass chips were biofunctionalized with RGD ligand in a parallel workflow: one chip for in vitro applications and the other for surface plasmon resonance (SPR)-based RGD activity characterization. Recombinant αVβ3 integrins were injected over the SPR chip surface as mimics of the cellular-membrane-bound receptors and the resulting binding kinetics parameterized to quantify surface ligand activity. These activity measurements were correlated with cell morphological features, measured by interfacing MDA-MB-231 cells with the in vitro chip surfaces on the live cell microscope. We demonstrate how the interpretation of a cell phenotype based on direct activity measurements can vary markedly from interpretations based on assumed activity. The SPR concurrent control approach has multiple advantages due to the fact that SPR is a standardized technique and has the sensitivity to measure ligand activity across the most relevant range of extracellular surface densities, while the in vitro chip design can be used with all commonly used light microscopy modalities (e.g., phase contrast, DIC, and fluorescence) so that a wide range of phenotypic and molecular markers can be correlated to the ligand surface activity.
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Affiliation(s)
- Michael C Robitaille
- Naval Research Laboratory, 4555 Overlook Avenue SW, Washington, DC 20375-5320, United States
| | | | | | - Jeff M Byers
- Naval Research Laboratory, 4555 Overlook Avenue SW, Washington, DC 20375-5320, United States
| | - Marc P Raphael
- Naval Research Laboratory, 4555 Overlook Avenue SW, Washington, DC 20375-5320, United States
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Zhu YS, Tang K, Lv J. Peptide-drug conjugate-based novel molecular drug delivery system in cancer. Trends Pharmacol Sci 2021; 42:857-869. [PMID: 34334251 DOI: 10.1016/j.tips.2021.07.001] [Citation(s) in RCA: 58] [Impact Index Per Article: 19.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/20/2021] [Revised: 06/25/2021] [Accepted: 07/06/2021] [Indexed: 01/18/2023]
Abstract
Drug delivery systems are generally believed to comprise drugs and excipients. A peptide-drug conjugate is a single molecule that can simultaneously play multiple roles in a drug delivery system, such as in vivo drug distribution, targeted release, and bioactivity functions. This molecule can be regarded as an integrated drug delivery system, so it is called a molecular drug delivery system. In the context of cancer therapy, a peptide-drug conjugate comprises a tumor-targeting peptide, a payload, and a linker. Tumor-targeting peptides specifically identify membrane receptors on tumor cells, improve drug-targeted therapeutic effects, and reduce toxic and side effects. Payloads with bioactive functions connect to tumor-targeting peptides through linkers. In this review, we explored ongoing clinical work on peptide-drug conjugates targeting various receptors. We discuss the binding mechanisms of tumor-targeting peptides and related receptors, as well as the limiting factors for peptide-drug conjugate-based molecular drug delivery systems.
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Affiliation(s)
- Yi-Shen Zhu
- College of Biotechnology and Pharmaceutical Engineering, Nanjing Tech University, Nanjing, Jiangsu Province, China.
| | - Kexing Tang
- School of Pharmaceutical Sciences, Nanjing Tech University, Nanjing, Jiangsu Province, China
| | - Jiayi Lv
- College of Biotechnology and Pharmaceutical Engineering, Nanjing Tech University, Nanjing, Jiangsu Province, China
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Kanyo N, Kovacs KD, Saftics A, Szekacs I, Peter B, Santa-Maria AR, Walter FR, Dér A, Deli MA, Horvath R. Glycocalyx regulates the strength and kinetics of cancer cell adhesion revealed by biophysical models based on high resolution label-free optical data. Sci Rep 2020; 10:22422. [PMID: 33380731 PMCID: PMC7773743 DOI: 10.1038/s41598-020-80033-6] [Citation(s) in RCA: 40] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/21/2020] [Accepted: 12/16/2020] [Indexed: 02/06/2023] Open
Abstract
The glycocalyx is thought to perform a potent, but not yet defined function in cellular adhesion and signaling. Since 95% of cancer cells have altered glycocalyx structure, this role can be especially important in cancer development and metastasis. The glycocalyx layer of cancer cells directly influences cancer progression, involving the complicated kinetic process of cellular adhesion at various levels. In the present work, we investigated the effect of enzymatic digestion of specific glycocalyx components on cancer cell adhesion to RGD (arginine-glycine-aspartic acid) peptide motif displaying surfaces. High resolution kinetic data of cell adhesion was recorded by the surface sensitive label-free resonant waveguide grating (RWG) biosensor, supported by fluorescent staining of the cells and cell surface charge measurements. We found that intense removal of chondroitin sulfate (CS) and dermatan sulfate chains by chondroitinase ABC reduced the speed and decreased the strength of adhesion of HeLa cells. In contrast, mild digestion of glycocalyx resulted in faster and stronger adhesion. Control experiments on a healthy and another cancer cell line were also conducted, and the discrepancies were analysed. We developed a biophysical model which was fitted to the kinetic data of HeLa cells. Our analysis suggests that the rate of integrin receptor transport to the adhesion zone and integrin-RGD binding is strongly influenced by the presence of glycocalyx components, but the integrin-RGD dissociation is not. Moreover, based on the kinetic data we calculated the dependence of the dissociation constant of integrin-RGD binding on the enzyme concentration. We also determined the dissociation constant using a 2D receptor binding model based on saturation level static data recorded at surfaces with tuned RGD densities. We analyzed the discrepancies of the kinetic and static dissociation constants, further illuminating the role of cancer cell glycocalyx during the adhesion process. Altogether, our experimental results and modelling demonstrated that the chondroitin sulfate and dermatan sulfate chains of glycocalyx have an important regulatory function during the cellular adhesion process, mainly controlling the kinetics of integrin transport and integrin assembly into mature adhesion sites. Our results potentially open the way for novel type of cancer treatments affecting these regulatory mechanisms of cellular glycocalyx.
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Affiliation(s)
- Nicolett Kanyo
- Nanobiosensorics Laboratory, Institute of Technical Physics and Materials Science, Centre for Energy Research, Konkoly-Thege M. út 29-33, 1120, Budapest, Hungary
| | - Kinga Dora Kovacs
- Nanobiosensorics Laboratory, Institute of Technical Physics and Materials Science, Centre for Energy Research, Konkoly-Thege M. út 29-33, 1120, Budapest, Hungary
| | - Andras Saftics
- Nanobiosensorics Laboratory, Institute of Technical Physics and Materials Science, Centre for Energy Research, Konkoly-Thege M. út 29-33, 1120, Budapest, Hungary
| | - Inna Szekacs
- Nanobiosensorics Laboratory, Institute of Technical Physics and Materials Science, Centre for Energy Research, Konkoly-Thege M. út 29-33, 1120, Budapest, Hungary
| | - Beatrix Peter
- Nanobiosensorics Laboratory, Institute of Technical Physics and Materials Science, Centre for Energy Research, Konkoly-Thege M. út 29-33, 1120, Budapest, Hungary
| | - Ana R Santa-Maria
- Institute of Biophysics, Biological Research Centre, Temesvári krt. 62., 6726, Szeged, Hungary.,Doctoral School of Biology, University of Szeged, Közép fasor 52., 6726, Szeged, Hungary.,Department of Biotechnology, University of Szeged, Közép fasor 52., 6726, Szeged, Hungary
| | - Fruzsina R Walter
- Institute of Biophysics, Biological Research Centre, Temesvári krt. 62., 6726, Szeged, Hungary.,Department of Biotechnology, University of Szeged, Közép fasor 52., 6726, Szeged, Hungary
| | - András Dér
- Institute of Biophysics, Biological Research Centre, Temesvári krt. 62., 6726, Szeged, Hungary
| | - Mária A Deli
- Institute of Biophysics, Biological Research Centre, Temesvári krt. 62., 6726, Szeged, Hungary
| | - Robert Horvath
- Nanobiosensorics Laboratory, Institute of Technical Physics and Materials Science, Centre for Energy Research, Konkoly-Thege M. út 29-33, 1120, Budapest, Hungary.
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