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19 pages, 809 KiB  
Review
Overcoming Cancer Resistance: Strategies and Modalities for Effective Treatment
by Mahesh Koirala and Mario DiPaola
Biomedicines 2024, 12(8), 1801; https://doi.org/10.3390/biomedicines12081801 - 8 Aug 2024
Viewed by 324
Abstract
Resistance to cancer drugs is a complex phenomenon that poses a significant challenge in the treatment of various malignancies. This review comprehensively explores cancer resistance mechanisms and discusses emerging strategies and modalities to overcome this obstacle. Many factors contribute to cancer resistance, including [...] Read more.
Resistance to cancer drugs is a complex phenomenon that poses a significant challenge in the treatment of various malignancies. This review comprehensively explores cancer resistance mechanisms and discusses emerging strategies and modalities to overcome this obstacle. Many factors contribute to cancer resistance, including genetic mutations, activation of alternative signaling pathways, and alterations in the tumor microenvironment. Innovative approaches, such as targeted protein degradation, immunotherapy combinations, precision medicine, and novel drug delivery systems, hold promise for improving treatment outcomes. Understanding the intricacies of cancer resistance and leveraging innovative modalities are essential for advancing cancer therapy. Full article
(This article belongs to the Special Issue Drug Resistance and Novel Targets for Cancer Therapy—Second Edition)
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<p>Different modes of drug resistance.</p>
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<p>Mechanism of PROTAC and protein degradation.</p>
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22 pages, 1950 KiB  
Review
Enzyme Is the Name—Adapter Is the Game
by Michael Huber and Tilman Brummer
Cells 2024, 13(15), 1249; https://doi.org/10.3390/cells13151249 - 25 Jul 2024
Viewed by 409
Abstract
Signaling proteins in eukaryotes usually comprise a catalytic domain coupled to one or several interaction domains, such as SH2 and SH3 domains. An additional class of proteins critically involved in cellular communication are adapter or scaffold proteins, which fulfill their purely non-enzymatic functions [...] Read more.
Signaling proteins in eukaryotes usually comprise a catalytic domain coupled to one or several interaction domains, such as SH2 and SH3 domains. An additional class of proteins critically involved in cellular communication are adapter or scaffold proteins, which fulfill their purely non-enzymatic functions by organizing protein–protein interactions. Intriguingly, certain signaling enzymes, e.g., kinases and phosphatases, have been demonstrated to promote particular cellular functions by means of their interaction domains only. In this review, we will refer to such a function as "the adapter function of an enzyme". Though many stories can be told, we will concentrate on several proteins executing critical adapter functions in cells of the immune system, such as Bruton´s tyrosine kinase (BTK), phosphatidylinositol 3-kinase (PI3K), and SH2-containing inositol phosphatase 1 (SHIP1), as well as in cancer cells, such as proteins of the rat sarcoma/extracellular signal-regulated kinase (RAS/ERK) mitogen-activated protein kinase (MAPK) pathway. We will also discuss how these adaptor functions of enzymes determine or even undermine the efficacy of targeted therapy compounds, such as ATP-competitive kinase inhibitors. Thereby, we are highlighting the need to develop pharmacological approaches, such as proteolysis-targeting chimeras (PROTACs), that eliminate the entire protein, and thus both enzymatic and adapter functions of the signaling protein. We also review how genetic knock-out and knock-in approaches can be leveraged to identify adaptor functions of signaling proteins. Full article
(This article belongs to the Section Cell Signaling)
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Figure 1

Figure 1
<p>Differentiating between enzymatic function and adapter function. (<b>A</b>) An enzyme (in this example, we show a kinase) consisting of interaction domains (ID) and a kinase domain (KD) interacts with protein X in a way that allows the kinase to phosphorylate protein X and modulate its function. We are using the term “enzymatic function” for such interactions. (<b>B</b>) The kinase via one of its IDs connects protein X and protein Y, thus allowing these proteins to functionally interact (bilateral arrow). In this example, the enzymatic activity (KD) of the kinase is not relevant for this functional interaction. In such a scenario, we use the term “adapter function”. (<b>C</b>) In the situation shown, the kinase interacts with the plasma membrane (PM) or an organelle. Using one of its IDs, the kinase promotes the functional interaction between protein Z and the membrane. In this scenario, the KD of the kinase is not relevant for the function of protein Z (arrow), and we use the term “adapter function” for such situations.</p>
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<p>BTK structure and catalytic as well as adapter functions. BTK comprises (from N- to C-terminus) a PH-domain, a TH-domain, an SH3-domain, an SH2-domain, as well as a tyrosine kinase (TK) domain (also known as SH1-domain). The following amino acids are accentuated: Y551 has to be phosphorylated for BTK activation; Y223 can be auto-phosphorylated by active BTK; C481 in the catalytic domain can form a covalent bond with the inhibitor Ibrutinib; and R28 within the PH-domain is crucial for PIP<sub>3</sub> interaction. The red question mark alludes to the fact that in certain cells upon differential stimulation, BTK activation does not appear to be dependent on PI3K activation (see text). One dominant catalytic function (highlighted by a red dashed rectangle) is the phosphorylation/activation of PLCγ1/2, which then hydrolyzes PI45P<sub>2</sub> to yield IP<sub>3</sub> and DAG to promote signaling towards Ca<sup>2+</sup> mobilization and PKC activation, respectively. The adapter functions known so far (highlighted by green dashed rectangles) comprise the SH2-mediated interaction with the adapter protein SLP65, which together execute a tumor suppressing function in the B-cell lineage, as well as the interaction of PIP5K with BTK’s PH-domain allowing PIP5K translocation to the plasma membrane to phosphorylate the phospholipid PI4P to yield PI45P<sub>2</sub>. BTK-promoted PI45P<sub>2</sub> production is thought to constitute two feed-forward loops to provide the substrate for both PLCγ1/2 and PI3K.</p>
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<p>SHIP1 structure and catalytic as well as adapter functions. SHIP1 comprises (from N- to C-terminus) an SH2-domain, a catalytic 5′-phosphatase (PPtase) domain containing a PI34P<sub>2</sub>-binding C2 domain allowing allosteric feed-forward enhancement, and a proline-rich (P) C-terminus additionally comprising two NPxY sequences (Y912 and Y1020). As an enzyme, SHIP1 hydrolyzes the phospholipid PIP3 to yield PI34P<sub>2</sub> (highlighted by a red dashed rectangle). The adapter functions reported so far (highlighted by green dashed rectangles) comprise the SH2-mediated displacement of the GRB2-SOS complex from the adapter protein SHC, thus repressing GDP-to-GTP exchange at RAS (resulting in enhanced RAS<sup>GDP</sup> to RAS<sup>GTP</sup> levels (RAS<sup>GDP</sup> &gt; RAS<sup>GTP</sup>)) as well as the recruitment of the DOK1-RASGAP1 complex to a C-terminal phosphorylated NPxY sequence via DOK1´s PTB-domain, hence causing enhanced GTP-to-GDP hydrolysis at RAS (RAS<sup>GDP</sup> &gt; RAS<sup>GTP</sup>). Moreover, the E3 ubiquitin ligase XIAP can interact with the proline-rich tail of SHIP1, thereby displacing XIAP from RIP2, and blocking NFκB activation. Furthermore, the SH2-domain of SHIP1 has been demonstrated to interact with phosphorylated Y1020, allowing dimerization (and most probably oligomerization) of SHIP1 to promote its potential scaffolding function.</p>
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<p>Simplified sketch of the RAS/ERK MAPK pathway. This pathway is activated by a plethora of receptor tyrosine kinases (RTK), such as the subsequently mentioned HER2/HER3 heterodimer, but also antigen and cytokine receptors [<a href="#B61-cells-13-01249" class="html-bibr">61</a>,<a href="#B62-cells-13-01249" class="html-bibr">62</a>,<a href="#B63-cells-13-01249" class="html-bibr">63</a>]. Phosphorylation of the receptor tails, either by intrinsic enzymatic activity as in the case of RTKs, or by associated protein tyrosine kinases of the SRC, SYK, or JAK families in case of antigen and cytokine receptors, results in the recruitment of SH2 domain containing adaptor proteins like GRB2. With its two SH3 domains, GRB2 can then recruit the guanine nucleotide exchange factor SOS and docking proteins of the GAB family, which, upon tyrosine phosphorylation, recruit and allosterically activate SHP2 by engaging with its tandem SH2 domain [<a href="#B64-cells-13-01249" class="html-bibr">64</a>,<a href="#B65-cells-13-01249" class="html-bibr">65</a>]. Both SOS and active SHP2 are required for optimal RAS signaling. Active RAS not only recruits RAF family members, such as BRAF and RAF1 to the plasma membrane, but also induces conformational changes resulting in the exposure of their kinase domains and homo- or heterodimerization, leading to the allosteric transactivation of RAF protomers indicated by the swung red arrow [<a href="#B66-cells-13-01249" class="html-bibr">66</a>,<a href="#B67-cells-13-01249" class="html-bibr">67</a>,<a href="#B68-cells-13-01249" class="html-bibr">68</a>]. Likewise, the pseudokinase KSR1 or RAF proteins rendered inactive either by mutations abolishing enzymatic activity or by ATP competitive kinase inhibitors can also trigger allosteric transactivation of catalytically competent RAFs [<a href="#B69-cells-13-01249" class="html-bibr">69</a>,<a href="#B70-cells-13-01249" class="html-bibr">70</a>]. Figure was created with <a href="http://BioRender.com" target="_blank">BioRender.com</a> (accessed on 27 April 2024).</p>
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18 pages, 8210 KiB  
Review
Primed for Interactions: Investigating the Primed Substrate Channel of the Proteasome for Improved Molecular Engagement
by Cody A. Loy and Darci J. Trader
Molecules 2024, 29(14), 3356; https://doi.org/10.3390/molecules29143356 - 17 Jul 2024
Viewed by 790
Abstract
Protein homeostasis is a tightly conserved process that is regulated through the ubiquitin proteasome system (UPS) in a ubiquitin-independent or ubiquitin-dependent manner. Over the past two decades, the proteasome has become an excellent therapeutic target through inhibition of the catalytic core particle, inhibition [...] Read more.
Protein homeostasis is a tightly conserved process that is regulated through the ubiquitin proteasome system (UPS) in a ubiquitin-independent or ubiquitin-dependent manner. Over the past two decades, the proteasome has become an excellent therapeutic target through inhibition of the catalytic core particle, inhibition of subunits responsible for recognizing and binding ubiquitinated proteins, and more recently, through targeted protein degradation using proteolysis targeting chimeras (PROTACs). The majority of the developed inhibitors of the proteasome’s core particle rely on gaining selectivity through binding interactions within the unprimed substrate channel. Although this has allowed for selective inhibitors and chemical probes to be generated for the different proteasome isoforms, much remains unknown about the interactions that could be harnessed within the primed substrate channel to increase potency or selectivity. Herein, we discuss small molecules that interact with the primed substrate pocket and how their differences may give rise to altered activity. Taking advantage of additional interactions with the primed substrate pocket of the proteasome could allow for the generation of improved chemical tools for perturbing or monitoring proteasome activity. Full article
(This article belongs to the Section Chemical Biology)
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Figure 1
<p>(<b>A</b>) Structure of the 20S Standard Core Particle (sCP), containing 14 distinct subunits repeated twice (28 total proteins), forming heptoheteromic rings that assemble into the active barrel-like structure. Catalytically active subunits are highlighted (yellow). (<b>B</b>) Structure of the 20S immunoproteasome (iCP) containing the same barrel-like assembly of subunits but with altered catalytic subunits (red). These isoforms are capable of degrading proteins that have been oxidatively damaged or unstructured, but their cleavage products will differ due to their altered substate specificities. PDB ID: 4R3O and 5LE5.</p>
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<p>(<b>A</b>) Structure of the 30S isoform of the proteasome, containing a 20S catalytic core particle and two 19S regulatory particles. (<b>B</b>) Structure of the 26S isoform of the proteasome, containing a 20S catalytic core particle and one 19S regulatory particle. (<b>C</b>) Structure of the PA28—iCP complex. PDB IDs: 5GJR, 7DR6.</p>
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<p>(<b>A</b>) Structure of the 20S sCP. The symmetry of the proteasome allows one set of α and β subunits to be clockwise, while the other two are counterclockwise in orientation. (<b>B</b>) A sliced view of the proteasome to show the two antechambers and the catalytic chamber.</p>
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<p>(<b>A</b>) Substrate entry into the 20S proteasome through the α-subunit portal into the inner catalytic chamber. (<b>B</b>) Active site hydrolysis of an unwound substrate by the β5 subunit. All subunits utilize an active site Thr (red) for hydrolysis of substrates but have altered substrate specificities due to differences in S1 and S2 substrate binding pockets.</p>
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<p>Substrate channel for the β5i (purple) and β5 (orange) subunits of the iCP and sCP, respectively. The unprimed channel has been thoroughly explored for differences in the substrate binding pockets S1–S4. The differences in substrate binding pockets S1′–S4′ have remained relatively understudied; however, several inhibitors and chemical probes have been found to take advantage of interactions in this channel to gain selectivity and potency. These indications hint that the primed substrate channel has interactions that can be harnessed when developing proteasome inhibitors or probes, and work is needed to further identify the crucial interactors.</p>
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<p>Structures of Belactosin A and its derivatives that engage with the primed substrate channel to inhibit proteasome activity. (<b>A</b>) Belactosin A contains a lactone ring to react with the 20S CP catalytic Thr. (<b>B</b>) Belactosin B does not have a lactone ring (orange circle) and is no longer effective at inhibiting 20S CP. (<b>C</b>) Belactosin C no longer has the <span class="html-italic">trans</span>-cycloproane ring but can still engage and inhibit 20S CP because of the lactone. (<b>D</b>) Optimization of Belactosin A led to improved inhibition with the introduction of the phenyl ring at the carboxylic acid. This demonstrates that there are moieties that can be explored to better engage with the primed substrate channel that lead to improved selectivity or potency.</p>
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<p>(<b>A</b>) SAR of Belactosin A from its <span class="html-italic">trans</span>-isomer to <span class="html-italic">cis</span>- was found to increase its IC<sub>50</sub> value. Further optimization of the scaffold led to the development of compound <b>3e</b>, which has toxicity similar to that of Bortezomib, all through interactions, highlighted in orange, in the primed substrate channel. (<b>B</b>) Structure of Marizomib that interacts with all catalytic subunits of the 20S CP and is orally available.</p>
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<p>(<b>A</b>) α-ketoamide was developed to engage the primed substrate channel to increase selectivity. SAR derivative 27 was the most potent and selective of the inhibitors developed, with IC<sub>50</sub> values in low nM concentrations as well as over 4-fold selectivity for the sCP over iCP. (<b>B</b>) UK-101 was developed to gain selectivity for the LMP2 subunit of the iCP by engaging with the primed substrate pocket. (<b>C</b>) Derivatives of the FDA-approved proteasome inhibitor Carfilzomib have been developed to overcome resistance seen with current proteasome inhibitors. By adding interactions to the primed substrate channel, this derivative increased its potency and was able to be effective against proteasome inhibitor resistance cells.</p>
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<p>Fluorescent activity-based AMC probes for 20S CP. Intact probes are non-fluorescent until liberated by cleavage from the proteasome. Specificity has generally been achieved through unprimed substrate interactions (purple). As substrate (green) is cleaved (dashed red line), AMC is released, and fluorescence increases are monitored over time. (<b>A</b>) Structure of Suc-LLVY-AMC, which is selective for the chymotrypsin-like activity of the β5 subunit. (<b>B</b>) Structure of Ac-ANW-AMC, which is selective for the chymotrypsin-like activity of the β5i subunit.</p>
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<p>(<b>A</b>) TED FRET reporter to monitor sCP cleavage activity. When intact, FRET reporter signal for EDANS is quenched by the acceptor, DABCYL. Upon interaction with the 20S sCP, the bond between phenylalanine and alanine is cleaved (dashed red line), leading to an increase in fluorescent signal from liberated EDANS. (<b>B</b>) Rhodamine-based probes to monitor iCP activity biochemically or in cells (TBZ-1). iCP recognition sequence ATMW conjugates a rhodamine-peptoid that is non-fluorescent until interaction with the β5i subunit to cleave the bond between Trp and rhodamine (red-dashed line) that allows for increase in fluorescent signal to be monitored over time. (<b>C</b>) Rhodamine-based probes to monitor sCP activity biochemically or in cells (TAS-1). The sCP recognition sequence LLVY conjugates a rhodamine-peptoid that is non-fluorescent until interaction with the β5 subunit to cleave the bond between Tyr and rhodamine (red-dashed line), which allows for increase in fluorescent signal to be monitored over time. (<b>D</b>) FRET probe generated through combinatorial library for primed substrate interactors. Primed interactions led to probes being selective for iCP, demonstrating that engagements in this channel can lead to more selective probes/inhibitors.</p>
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13 pages, 4033 KiB  
Article
Use of Poly(vinyl alcohol) in Spray-Dried Dispersions: Enhancing Solubility and Stability of Proteolysis Targeting Chimeras
by Lena Mareczek, Lena K. Mueller, Laura Halstenberg, Thomas M. Geiger, Michael Walz, Min Zheng and Felix Hausch
Pharmaceutics 2024, 16(7), 924; https://doi.org/10.3390/pharmaceutics16070924 - 11 Jul 2024
Viewed by 626
Abstract
PROTACs, proteolysis targeting chimeras, are bifunctional molecules inducing protein degradation through a unique proximity-based mode of action. While offering several advantages unachievable by classical drugs, PROTACs have unfavorable physicochemical properties that pose challenges in application and formulation. In this study, we show the [...] Read more.
PROTACs, proteolysis targeting chimeras, are bifunctional molecules inducing protein degradation through a unique proximity-based mode of action. While offering several advantages unachievable by classical drugs, PROTACs have unfavorable physicochemical properties that pose challenges in application and formulation. In this study, we show the solubility enhancement of two PROTACs, ARV-110 and SelDeg51, using Poly(vinyl alcohol). Hereby, we apply a three-fluid nozzle spray drying set-up to generate an amorphous solid dispersion with a 30% w/w drug loading with the respective PROTACs and the hydrophilic polymer. Dissolution enhancement was achieved and demonstrated for t = 0 and t = 4 weeks at 5 °C using a phosphate buffer with a pH of 6.8. A pH shift study on ARV-110-PVA is shown, covering transfer from simulated gastric fluid (SGF) at pH 2.0 to fasted-state simulated intestinal fluid (FaSSIF) at pH 6.5. Additionally, activity studies and binding assays of the pure SelDeg51 versus the spray-dried SelDeg51-PVA indicate no difference between both samples. Our results show how modern enabling formulation technologies can partially alleviate challenging physicochemical properties, such as the poor solubility of increasingly large ‘small’ molecules. Full article
(This article belongs to the Special Issue Spray Drying in the Pharmaceutical and Nutraceutical Field)
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<p>Molecular structure of ARV-110.</p>
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<p>X-ray powder diffractograms of the PROTAC ARV-110 and the physical mixture (PM) of ARV-110 with PVA containing 30% drug load as well as the spray-dried dispersion (SDD) of ARV-110 with PVA containing 30% drug load at t = 0 and after storage for 4 weeks at 5 °C (t = 4 W 5 °C).</p>
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<p>Differential scanning calorimetry of the PROTAC ARV-100, the physical mixture (PM) and the spray-dried dispersion (SDD) containing a 30% drug loading of ARV-110 in the PVA matrix.</p>
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<p>Scanning electron microscopy images of the PROTAC ARV-110 and the physical mixture (PM) of ARV-110 with PVA containing 30% drug load as well as the spray-dried dispersion (SDD) of ARV-110 with PVA containing 30% drug load at 5000× magnification.</p>
Full article ">Figure 5
<p>Dissolution profiles of the PROTAC ARV-110, the physical mixture (PM) of ARV-110 with PVA containing 30% drug, and the spray-dried dispersion (SDD) of ARV-110 with PVA containing 30% drug, as well as the respective materials, stored at 5 °C for 4 weeks in phosphate buffer with a pH of 6.8. Arithmetic means of n = 3 ± SD.</p>
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<p>Dissolution profiles of the PROTAC ARV-110 and the physical mixture (PM) of ARV-110 with PVA containing 30% drug as well as the spray-dried dispersion (SDD) of ARV-110 with PVA containing 30% drug in fasted-state simulated intestinal fluid with a pH of 6.5 after transfer from simulated gastric fluid with a pH of 2.0. Arithmetic means of n = 2 ± SD.</p>
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<p>Molecular structure of SelDeg51.</p>
Full article ">Figure 8
<p>(<b>a</b>) X-ray powder diffractograms of the PROTAC SelDeg51 and the spray-dried dispersion (SDD) of SelDeg51 with PVA containing 30% drug load as well as the respective materials stored at 5 °C for 4 weeks and (<b>b</b>) scanning electron microscopy images of SelDeg51 and the spray-dried dispersion (SDD) of SelDeg51 with PVA containing 30% drug load at 5000× magnification.</p>
Full article ">Figure 8 Cont.
<p>(<b>a</b>) X-ray powder diffractograms of the PROTAC SelDeg51 and the spray-dried dispersion (SDD) of SelDeg51 with PVA containing 30% drug load as well as the respective materials stored at 5 °C for 4 weeks and (<b>b</b>) scanning electron microscopy images of SelDeg51 and the spray-dried dispersion (SDD) of SelDeg51 with PVA containing 30% drug load at 5000× magnification.</p>
Full article ">Figure 9
<p>Dissolution profiles of the PROTAC SelDeg51 and the spray-dried dispersion (SDD) of SelDeg51 with PVA containing 30% drug as well as the respective materials stored at 5 °C for 4 weeks in phosphate buffer with a pH of 6.8. Arithmetic means of n = 3 ± SD.</p>
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<p>Performance characterization of SelDeg51 after spray drying. (<b>b</b>) Western blot analysis of SelDeg51-mediated FKBP51 degradation by neat SelDeg51 as well as the SDD with 30% drug load after 24 h of treatment in HEK293T cells. GAPDGH was determined as loading control. (<b>a</b>) Binding to the E3 ligase VHL as determined by fluorescence polarization of neat SelDeg51, the SDD, a physical mixture with 30% drug load and neat PVA in presence of a saturating excess of FKBP51<sup>FK1</sup>HP: high protein control representing fully bound VHL tracer; DMSO with no additional substance treatment; No VCB: Assay mix without VHL/EloB/EloC, representing fully unbound tracer.</p>
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15 pages, 1157 KiB  
Review
The Evolving Role of Bruton’s Tyrosine Kinase Inhibitors in B Cell Lymphomas
by Shefali Mehra, Miah Nicholls and Justin Taylor
Int. J. Mol. Sci. 2024, 25(14), 7516; https://doi.org/10.3390/ijms25147516 (registering DOI) - 9 Jul 2024
Viewed by 704
Abstract
Bruton’s tyrosine kinase (BTK), a non-receptor tyrosine kinase crucial for B cell development and function, acts downstream of the B cell receptor (BCR) in the BCR pathway. Other kinases involved downstream of the BCR besides BTK such as Syk, Lyn, PI3K, and Mitogen-activated [...] Read more.
Bruton’s tyrosine kinase (BTK), a non-receptor tyrosine kinase crucial for B cell development and function, acts downstream of the B cell receptor (BCR) in the BCR pathway. Other kinases involved downstream of the BCR besides BTK such as Syk, Lyn, PI3K, and Mitogen-activated protein (MAP) kinases also play roles in relaying signals from the BCR to provide pro-survival, activation, and proliferation cues. BTK signaling is implicated in various B-cell lymphomas such as mantle cell lymphoma, Waldenström Macroglobulinemia, follicular lymphoma, and diffuse large B cell lymphoma, leading to the development of transformative treatments like ibrutinib, the first-in-class covalent BTK inhibitor, and pirtobrutinib, the first-in-class noncovalent BTK inhibitor. However, kinase-deficient mutations C481F, C481Y, C481R, and L528W in the BTK gene confer resistance to both covalent and non-covalent BTK inhibitors, facilitating B cell survival and lymphomagenesis despite kinase inactivation. Further studies have revealed BTK’s non-catalytic scaffolding function, mediating the assembly and activation of proteins including Toll-like receptor 9 (TLR9), vascular cell adhesion protein 1 (VCAM-1), hematopoietic cell kinase (HCK), and integrin-linked kinase (ILK). This non-enzymatic role promotes cell survival and proliferation independently of kinase activity. Understanding BTK’s dual roles unveils opportunities for therapeutics targeting its scaffolding function, promising advancements in disrupting lymphomagenesis and refining B cell lymphoma treatments. Full article
(This article belongs to the Special Issue New Advances in B-cell Lymphoma Biology)
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Figure 1
<p>This schematic diagram depicts the signaling cascade downstream of Bruton’s tyrosine kinase (BTK) in the B-cell receptor (BCR) pathway, highlighting critical substrates that drive B cell proliferation, activation, survival, and differentiation. Upon BCR engagement, BTK phosphorylates phospholipase Cγ2 (PLCγ2), leading to the generation of inositol 1,4,5-trisphosphate (IP3) and DAG (diacylglycerol). IP3 mobilizes intracellular calcium, while DAG activates PKC (protein kinase c). This activation further stimulates the rat sarcoma (RAS) pathway, leading to the activation of extracellular signal-regulated kinase (ERK) and transcription factors (myelocytomatosis) MYC and ETS-like kinase (ELK). Concurrently, PKC activates the inhibitor of the nuclear factor-κB kinase (IKK) complex, resulting in the translocation of nuclear factor kappa-light-chain-enhancer of activated B cells (NF-κB) to the nucleus, promoting gene expression essential for B cell survival and proliferation.</p>
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<p>This schematic diagram illustrates the mechanisms of action and resistance to Bruton’s tyrosine kinase (BTK) inhibitors in B cell receptor (BCR) signaling. The left panel shows BTK inhibitors blocking BTK activity, resulting in the inhibition of downstream signaling pathways, including PKC, DAG, PLCγ2, IP3, ERK, and NF-κB, thereby inhibiting B cell proliferation and survival. The middle panel represents kinase-proficient BTK mutation resistance, where mutations allow BTK to remain active despite inhibitor presence, maintaining BCR signaling and B cell proliferation. The right panel depicts kinase-impaired BTK mutation resistance, where alternative kinases like HCK compensate for impaired BTK activity, sustaining downstream signaling and B cell proliferation. Green stars indicate active BTK and red stars indicate kinase impaired BTK.</p>
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14 pages, 2375 KiB  
Communication
The Degradation of Botulinum Neurotoxin Light Chains Using PROTACs
by Yien Che Tsai, Loren Kozar, Zo P. Mawi, Konstantin Ichtchenko, Charles B. Shoemaker, Patrick M. McNutt and Allan M. Weissman
Int. J. Mol. Sci. 2024, 25(13), 7472; https://doi.org/10.3390/ijms25137472 - 8 Jul 2024
Viewed by 685
Abstract
Botulinum neurotoxins are some of the most potent natural toxins known; they cause flaccid paralysis by inhibiting synaptic vesicle release. Some serotypes, notably serotype A and B, can cause persistent paralysis lasting for several months. Because of their potency and persistence, botulinum neurotoxins [...] Read more.
Botulinum neurotoxins are some of the most potent natural toxins known; they cause flaccid paralysis by inhibiting synaptic vesicle release. Some serotypes, notably serotype A and B, can cause persistent paralysis lasting for several months. Because of their potency and persistence, botulinum neurotoxins are now used to manage several clinical conditions, and there is interest in expanding their clinical applications using engineered toxins with novel substrate specificities. It will also be beneficial to engineer toxins with tunable persistence. We have investigated the potential use of small-molecule proteolysis-targeting chimeras (PROTACs) to vary the persistence of modified recombinant botulinum neurotoxins. We also describe a complementary approach that has potential relevance for botulism treatment. This second approach uses a camelid heavy chain antibody directed against botulinum neurotoxin that is modified to bind the PROTAC. These strategies provide proof of principle for the use of two different approaches to fine tune the persistence of botulinum neurotoxins by selectively targeting their catalytic light chains for proteasomal degradation. Full article
(This article belongs to the Special Issue Advances in Clostridial and Related Neurotoxins 2.0)
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Figure 1
<p>(<b>A</b>) Cells were transfected with plasmids encoding GFP-tagged LC/A1 (Lanes 1–3), LC/A2 (Lanes 4–6), or LC/A3 (Lanes 7–9). After 36 h, cells were treated with 50 μg/mL cycloheximide (CHX) for the indicated times and levels of GFP-LC/As were assessed by immunoblotting (IB) with GFP antibody. (<b>B</b>) Cells transfected with GFP-LC/A1 were treated with CHX and DMSO (Lanes 1–3), 2 μM WP1130 (Lanes 4–6), or 10 μM P22077 (Lanes 7–9). Levels of GFP-LC/A1 were assessed by IB. RFP serves as a transfection efficiency control in (<b>A</b>,<b>B</b>).</p>
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<p>(<b>A</b>) Schematic representation of how a cellular E3 can be redirected to target LC/A using a PROTAC designed to bind a specific targeting domain (TD). The PROTAC binds the TD on one end and recruits the E3 ligase complex that binds to a ubiquitin-conjugating enzyme (E2) charged with ubiquitin (Ub) on the other. (<b>B</b>) Cells were treated with increasing doses of HaloPROTAC3 for 24 h and cell viability was assessed with ethidium homodimer-2. Data shown are mean ± SD (n = 3). (<b>C</b>) Cells transfected with plasmids encoding GFP-Halo-LC/A1 were treated with vehicle (Lane 1) or increasing concentrations of HaloPROTAC3, ranging from ~390 nM (Lane 2) to 50 μM (Lane 9), for 24 h. Levels of GFP-Halo-LC/A1 (arrow) were assessed by IB. (<b>D</b>) Cells transfected with plasmids encoding GFP-LC/A1 lacking the HaloTag were treated with vehicle (Lane 1) or increasing concentrations of HaloPROTAC3, ranging from ~390 nM (Lane 2) to 50 μM (Lane 9), for 24 h. Levels of GFP-LC/A1 were assessed by IB; RFP served as a transfection control in (<b>C</b>,<b>D</b>). (<b>E</b>) Dose responses for GFP-Halo-LC/A1 and GFP-LC/A1 are from data in (<b>C</b>,<b>D</b>). (<b>F</b>) Cells were transfected with plasmids encoding GFP-Halo-LC/A1 and treated for 20 h with 20 μM HaloPROTAC3, followed by 4 h with 30 μM MG132. Cells were lysed in denaturing buffer and processed for immunoprecipitation of GFP-Halo-LC/A1. Ubiquitin and LC/A1 were detected by IB. The arrow indicates the expected apparent molecular weight of unmodified GFP-Halo-LC/A1.</p>
Full article ">Figure 2 Cont.
<p>(<b>A</b>) Schematic representation of how a cellular E3 can be redirected to target LC/A using a PROTAC designed to bind a specific targeting domain (TD). The PROTAC binds the TD on one end and recruits the E3 ligase complex that binds to a ubiquitin-conjugating enzyme (E2) charged with ubiquitin (Ub) on the other. (<b>B</b>) Cells were treated with increasing doses of HaloPROTAC3 for 24 h and cell viability was assessed with ethidium homodimer-2. Data shown are mean ± SD (n = 3). (<b>C</b>) Cells transfected with plasmids encoding GFP-Halo-LC/A1 were treated with vehicle (Lane 1) or increasing concentrations of HaloPROTAC3, ranging from ~390 nM (Lane 2) to 50 μM (Lane 9), for 24 h. Levels of GFP-Halo-LC/A1 (arrow) were assessed by IB. (<b>D</b>) Cells transfected with plasmids encoding GFP-LC/A1 lacking the HaloTag were treated with vehicle (Lane 1) or increasing concentrations of HaloPROTAC3, ranging from ~390 nM (Lane 2) to 50 μM (Lane 9), for 24 h. Levels of GFP-LC/A1 were assessed by IB; RFP served as a transfection control in (<b>C</b>,<b>D</b>). (<b>E</b>) Dose responses for GFP-Halo-LC/A1 and GFP-LC/A1 are from data in (<b>C</b>,<b>D</b>). (<b>F</b>) Cells were transfected with plasmids encoding GFP-Halo-LC/A1 and treated for 20 h with 20 μM HaloPROTAC3, followed by 4 h with 30 μM MG132. Cells were lysed in denaturing buffer and processed for immunoprecipitation of GFP-Halo-LC/A1. Ubiquitin and LC/A1 were detected by IB. The arrow indicates the expected apparent molecular weight of unmodified GFP-Halo-LC/A1.</p>
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<p>(<b>A</b>) Cells transfected with <span class="html-italic">m</span>FKBP-LC/A1 were treated with increasing concentrations of dTAG<sup>V</sup>-1, ranging from ~0.1 nM (Lane 1) to 10 μM (Lane 9), for 24 h. Levels of <span class="html-italic">m</span>FKBP-LC/A1 were monitored by IB. RFP serves as a transfection efficiency control. (<b>B</b>) Dose response for <span class="html-italic">m</span>FKBP-LC/A1 is derived from data in (<b>A</b>). (<b>C</b>) M17 neuroblastoma cells transfected with <span class="html-italic">m</span>FKBP-LC/A1 were treated with 10 μg/mL CHX for 16 h in the presence of 200 nM dTAG<sup>V</sup>-1 or dTAG<sup>V</sup>-1-NEG (inert PROTAC, negative control). Levels of <span class="html-italic">m</span>FKBP-LC/A1 were assessed by IB. RFP serves as a transfection efficiency control. Levels of <span class="html-italic">m</span>FKBP-LC/A1 were monitored by IB. RFP serves as a transfection efficiency control.</p>
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<p>(<b>A</b>) Schematic representation of targeting LC/A with PROTAC using an intermediary protein. Here, an LC/A-specific VHH is fused to the targeting domain (TD) and serves to couple the PROTAC to the LC/A and E3 complex. (<b>B</b>) Cells transfected with plasmids encoding GFP-Halo-VHH and GFP-LC/A1 were treated with increasing concentrations of HaloPROTAC3, ranging from ~156 nM (Lane 1) to 40 μM (Lane 9), for 24 h. Levels of GFP-LC/A1 and GFP-Halo-VHH were assessed by IB. RFP serves as a transfection efficiency control. (<b>C</b>) Dose response for GFP-LC/A1 is derived from data in (<b>B</b>).</p>
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<p>(<b>A</b>) Cells transfected with plasmids encoding <span class="html-italic">m</span>FKBP-tagged VHH and GFP-LC/A1 were treated with increasing concentrations of dTAG<sup>V</sup>-1, ranging from ~0.1 nM (Lane 1) to 10 μM (Lane 9), for 24 h. Levels of GFP-LC/A1 and <span class="html-italic">m</span>FKBP-tagged VHH were assessed by IB. (<b>B</b>) Cells transfected with plasmids encoding VHH B8 and GFP-LC/A1 were treated with increasing concentrations of dTAG<sup>V</sup>-1, ranging from ~0.1 nM (Lane 1) to 10 μM (Lane 9), for 24 h. Levels of GFP-LC/A1 and VHH B8 were assessed by IB. RFP serves as a transfection efficiency control in (<b>A</b>,<b>B</b>). (<b>C</b>) Dose response for GFP-LC/A1 in the presence of B8 vs. <span class="html-italic">m</span>FKBP-B8 from (<b>A</b>,<b>B</b>).</p>
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<p>(<b>A</b>) Cells were transfected with plasmids encoding GFP-LC/A1 and either VHH (Lanes 5–8) or <span class="html-italic">m</span>FKBP-tagged VHH (Lanes 1–4). After 40 h, cells were treated with 10 μg/mL CHX for 16 h in the presence of 200 nM dTAG<sup>V</sup>-1 or dTAG<sup>V</sup>-1-NEG (inert PROTAC, negative control). Levels of GFP-LC/A1 and VHH were assessed by IB. (<b>B</b>) M17 neuroblastoma cells were transfected with plasmids encoding GFP-LC/A1 and <span class="html-italic">m</span>FKBP-tagged VHH. After 40 h, cells were treated with 10 μg/mL CHX for 16 h in the presence of 200 nM dTAG<sup>V</sup>-1 or dTAG<sup>V</sup>-1-NEG (inert PROTAC, negative control). Levels of GFP-LC/A1 and VHH were assessed by IB. RFP serves as a transfection efficiency control in (<b>A</b>,<b>B</b>).</p>
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18 pages, 3583 KiB  
Article
Blood Lines: Intraspecific and Interspecific Variations in Anticoagulant Actions of Agkistrodon Viperid Venoms
by Francisco C. P. Coimbra, Elda E. Sanchez, Bruno Lomonte, José María Gutiérrez, Juan J. Calvete and Bryan G. Fry
Toxins 2024, 16(7), 291; https://doi.org/10.3390/toxins16070291 - 26 Jun 2024
Viewed by 1015
Abstract
This study investigated the intraspecific and interspecific variability in the venom effects of Agkistrodon viperid snake species and subspecies (eleven venoms total) on plasma clotting times, fibrinogen levels, and fibrin clot strength. Significant delays in plasma clotting time were observed for A. conanti [...] Read more.
This study investigated the intraspecific and interspecific variability in the venom effects of Agkistrodon viperid snake species and subspecies (eleven venoms total) on plasma clotting times, fibrinogen levels, and fibrin clot strength. Significant delays in plasma clotting time were observed for A. conanti, A. contortrix mokasen, A. contortrix phaeogaster, A. howardgloydi, A. piscivorus leucostoma, and A. piscivorus piscivorus. Notably, the phylogenetically disjunct lineages A. conanti, A. contortrix mokasen, and A. howardgloydi exhibited the most potent anticoagulant effects, indicating the independent amplification of a basal trait. Inhibition assays with the activated clotting enzymes Factors XIa, IXa, Xa, and IIa (thrombin) revealed that FXa inhibition is another basal trait amplified independently on multiple occasions within the genus, but with A. howardgloydi, notably more potent than all others. Phospholipid degradation and zymogen destruction were identified as mechanisms underlying the variability in venom effects observed experimentally and in previous clinical reports. Thromboelastography demonstrated that the venoms did not clot fibrinogen directly but affected fibrin clot strength by damaging fibrinogen and that thrombin was subsequently only able to cleave into weak, unstable clots. The ability to activate Protein C, an endogenous anticoagulant enzyme, varied across species, with some venoms exceeding that of A. contortrix contortrix, which previously yielded the protein diagnostic agent Protac®. Phylogenetic analysis suggested that both fibrinogen degradation and Protein C activation were each amplified multiple times within the genus, albeit with negative correlation between these two modes of action. This study highlights the evolutionary, clinical, and biodiscovery implications of venom variability in the Agkistrodon species, underscoring their dynamic evolution, emphasising the need for tailored clinical approaches, and highlighting the potential for novel diagnostic and therapeutic developments inspired by the unique properties of snake venoms. Full article
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<p>Venom impacts upon clotting of human plasma. (<b>A</b>) Raw time numbers (machine maximum: 999 s). <span class="html-italic">p</span>-values for each venom relative to control are from Brown–Forsythe and Welch ANOVA tests with post hoc Dunnett T3 multiple comparisons. (<b>B</b>) Proportional increases in clotting time relative to the control (no venom effect = 0%). (<b>C</b>) Ancestral reconstruction of the relative effects upon clotting time; phylogeny based upon Burbrink [<a href="#B2-toxins-16-00291" class="html-bibr">2</a>]. Data are n = 4 mean ± standard deviation.</p>
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<p>Copperhead clade proportional increase in clotting time relative to the control for each test (no venom effect = 0%). Note: to allow for comparison across venoms, all graphs are scaled relative to the point of greatest impact, which is (plasma + venom) + FIXa for <span class="html-italic">A. conanti</span> in <a href="#toxins-16-00291-f003" class="html-fig">Figure 3</a>. Data are n = 4 mean ± standard deviation.</p>
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<p>Moccasin clade proportional increase in clotting time relative to the control for each test (no venom effect = 0%). Note: to allow for comparison across venoms, all graphs are scaled relative to the point of greatest impact, which is (plasma + venom) + FIXa for <span class="html-italic">A. conanti</span> in this figure. Data are n = 4 mean ± standard deviation.</p>
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<p>Ancestral reconstruction of elative inhibition of Factor Xa, showing the proportional increase in clotting time relative to the control (no venom effect = 0%). Phylogeny based upon Burbrink [<a href="#B2-toxins-16-00291" class="html-bibr">2</a>]. Data are n = 4 mean ± standard deviation.</p>
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<p>Thromboelastography tests where venom was incubated with fibrinogen without forming a clot, with thrombin subsequently added to form. (<b>A</b>) Thromboelastography R values (reaction time) representing the time taken from the start of the test until initial fibrin formation began. This measurement reflects the speed at which clotting starts. As the fibrinogen test was run under Claussian conditions, in which an excess of thrombin was added, any delay in R is reflective of depletion of fibrinogen levels. (<b>B</b>) R values as proportional increases in clotting time relative to the control (no venom effect = 0%). (<b>C</b>) Thromboelastography G values, which each represent the shear elastic modulus strength of a clot, which quantifies the clot’s firmness. The G value is expressed in dynes per square centimetre (d/sc) and provides a direct measure of the strength and stability of the blood clot formed during the test. Lower values indicate weaker clots. (<b>D</b>) G values as proportional increases in clotting time relative to the control (no venom effect = 0%; negative values indicate decreases in clot strength). <span class="html-italic">p</span>-values in (<b>A</b>,<b>C</b>) for each venom relative to control are from Brown–Forsythe and Welch ANOVA tests with post hoc Dunnett T3 multiple comparisons. Data are n = 4 mean ± standard deviation.</p>
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<p>Relative activations of Protein C. <span class="html-italic">p</span>-values are from Brown–Forsythe and Welch ANOVA tests with post hoc Dunnett T3 multiple comparisons. Data are n = 4 mean ± standard deviation.</p>
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<p>Ancestral reconstruction of the inverse relationships between the relative thromboelastographic determination of effects upon clot strength and the relative ability to activate Protein C. Phylogeny based upon Burbrink [<a href="#B2-toxins-16-00291" class="html-bibr">2</a>]. Data are n = 4 mean ± standard deviation.</p>
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22 pages, 5360 KiB  
Article
Conquering the beyond Rule of Five Space with an Optimized High-Throughput Caco-2 Assay to Close Gaps in Absorption Prediction
by Patricia Muschong, Khader Awwad, Edward Price, Mario Mezler and Manuel Weinheimer
Pharmaceutics 2024, 16(7), 846; https://doi.org/10.3390/pharmaceutics16070846 - 22 Jun 2024
Viewed by 1161
Abstract
Current drug development tends towards complex chemical molecules, referred to as “beyond rule of five” (bRo5) compounds, which often exhibit challenging physicochemical properties. Measuring Caco-2 permeability of those compounds is difficult due to technical limitations, including poor recovery and detection sensitivity. We implemented [...] Read more.
Current drug development tends towards complex chemical molecules, referred to as “beyond rule of five” (bRo5) compounds, which often exhibit challenging physicochemical properties. Measuring Caco-2 permeability of those compounds is difficult due to technical limitations, including poor recovery and detection sensitivity. We implemented a novel assay, with optimized incubation and analytics, to measure permeability close to equilibrium. In this setup an appropriate characterization of permeability for bRo5 compounds is achievable. This equilibrated Caco-2 assay was verified with respect to data validity, compound recovery, and in vitro to in vivo correlation for human absorption. Compared to a standard assay, it demonstrated comparable performance in predicting the human fraction absorbed (fa) for reference compounds. The equilibrated assay also successfully characterized the permeability of more than 90% of the compounds analyzed, the majority of which were bRo5 (68%). These compounds could not be measured using the standard assay. Permeability and efflux ratio (ER) were highly predictive for in vivo absorption for a large set of internal bRo5 compounds. Reference cut-offs enabled the correct classification of high, moderate, and low absorption. This optimized equilibrated Caco-2 assay closes the gap for a high-throughput cellular permeability method in the bRo5 chemical space. Full article
(This article belongs to the Special Issue Recent Advances in Oral Biopharmaceutics)
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<p>Detailed assay workflow of the equilibrated Caco-2 permeability assay in its final setup. The assay workflow starts with an initial bioanalytical method check (LC-MS/MS) of the test articles on a Waters Acquity coupled to a Sciex 6500 (1). Caco-2 cells in transwell plates are pre-incubated apically or basolaterally with compound at 3 µM in HBSS for 60 min (2). After rinsing of the cells with assay buffer (3), the 60 min main incubation with 3 µM compound in HBSS + 1% BSA follows (4). After the main incubation, samples are taken and measured via LC-MS/MS (5). Image created with <a href="http://BioRender.com" target="_blank">BioRender.com</a>.</p>
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<p>Investigations of different pre-incubation regimes. Pre-incubation for 1 h with and without BSA was compared to 24 h pre-incubation as described by Cui et al. [<a href="#B11-pharmaceutics-16-00846" class="html-bibr">11</a>] for a set of reference and internal compounds covering Ro5 and bRo5 (<a href="#pharmaceutics-16-00846-t002" class="html-table">Table 2</a>, Methods 2.6). The main incubation was performed with BSA for 1 h in all conditions. Lines indicate line of unity ±3 fold.</p>
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<p>Reasons for invalid (NV) or qualified results in a compound set of 52 entities with broad physicochemical properties in the standard method. Poor detection sensitivity is indicated when the analyte concentration in the receiver is below the limit of detection (LOD) of the analytical method, resulting in the expression of the result as qualified P<sub>app</sub>, employing the LOD as a basis value for calculation. Poor recovery is indicated when the mass balance is less than 65% in a single direction, or less than 40% in bidirectional studies, where the recoveries are similar in both directions (with a recovery difference of less than 25%). High data variability is indicated when the difference between duplicates exceeds 50%, which is often observed in combination with recovery issues.</p>
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<p>Distribution of compound types evaluated in all three methods based on the number of zero-to-three failed Lipinski rules (<b>A</b>) and the molecular weight (<b>B</b>).</p>
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<p>Qualifier distribution for the shared compound set in the Caco-2 standard method based on the molecular weight (<b>A</b>) and number of failed Lipinski rules (<b>B</b>). The labels represent the respective percentages of each bar.</p>
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<p>Distribution of valid, qualified, and invalid (NV) results based on a shared compound set for the standard method (<b>A</b>), the BSA-modified standard method (<b>B</b>), and the equilibrated method (<b>C</b>).</p>
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<p>Distribution of valid, qualified, and invalid (NV) results obtained with the equilibrated method for those compounds with qualified and NV results with the standard method (<b>A</b>), as well as the respective numbers (0 to 3) of Lipinski violations (<b>B</b>) of the same compounds.</p>
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<p>Violin plot analyses of compound recovery values generated with the standard method (<b>A</b>), the BSA-modified standard method (<b>B</b>), and the equilibrated method (<b>C</b>). Upper and lower rows display recovery values of A-to-B transport and B-to-A transport, respectively. The compound set comprised 27 compounds with 67% being bRo5. Recovery is marked in blue and red for Ro5 and bRo5 compounds, respectively. The solid line equals the median and the dashed lines the quartiles. The dotted line marks 80% recovery.</p>
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<p>Comparison of P<sub>app,AB</sub> (<b>A</b>) and ER (<b>B</b>) values obtained using the standard and the equilibrated method. The lines represent the line of unity ±3 fold. Compounds are classified based on their number of Lipinski rule violations. R<sup>2</sup> of P<sub>app,AB</sub> is 0.63 and R<sup>2</sup> of ER is 0.84.</p>
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<p>Composition of the comparative compound set with human f<sub>a</sub> according to the number of failed Lipinski rules (<b>A</b>) and according to the binned molecular weight (<b>B</b>).</p>
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<p>Sigmoidal fit and box plot analyses of binned P<sub>app,AB</sub> values obtained from the standard (<b>A</b>,<b>C</b>) and the equilibrated method (<b>B</b>,<b>D</b>) for reference compounds with known human f<sub>a</sub> (<a href="#pharmaceutics-16-00846-t003" class="html-table">Table 3</a>). R<sup>2</sup> of P<sub>app,AB</sub> of the standard method to human f<sub>a</sub> is 0.31; R<sup>2</sup> of the equilibrated method is 0.27. No significant difference was observed between the standard and the equilibrated method in all respective binning categories (low, medium, and high permeability). Diamonds represent single data points in the sigmoidal fit and triangles mark outliers of the respective binning category in the box plot analyses. Significance was calculated with Welch’s <span class="html-italic">t</span>-test, with significance defined at <span class="html-italic">p</span> &lt; 0.05 (*), <span class="html-italic">p</span> &lt; 0.01 (**), and <span class="html-italic">p</span> &lt; 0.005 (***), ns refers to not significant.</p>
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<p>Composition of the internal compound set with rodent fafg according to the number of failed Lipinski rules (<b>A</b>) and according to binned molecular weight (<b>B</b>).</p>
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<p>Boxplot analyses of binned P<sub>app,AB</sub> (<b>A</b>,<b>C</b>) and binned ER (<b>B</b>,<b>D</b>) values obtained from the equilibrated method for compounds with internally determined rodent fafg. (<b>A</b>,<b>B</b>) consider Ro5 and bRo5 compounds (<span class="html-italic">N</span> = 741), whereas (<b>C</b>,<b>D</b>) only cover bRo5 compounds (<span class="html-italic">N</span> = 383). Triangles mark outliers of the respective binning categories. Significance was calculated with Welch’s <span class="html-italic">t</span>-test, with significance defined at <span class="html-italic">p</span> &lt; 0.01 (**), <span class="html-italic">p</span> &lt; 0.005 (***), and <span class="html-italic">p</span> &lt; 0.001 (****), ns refers to not significant.</p>
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<p>Binned solubility [µM] in phosphate buffer at pH 7.4 for a subset of compounds with corresponding internal solubility data available (<span class="html-italic">N</span> = 314 in total (<b>A</b>) and <span class="html-italic">N</span> = 174 bRo5 only (<b>B</b>)).</p>
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<p>Compound ranking based on fafg and P<sub>app,AB</sub> (<b>A</b>) or ER (<b>B</b>) cut-offs. Compounds are classified based on their number of Lipinski rule violations. <span class="html-italic">N</span> = 727 (total) and 369 (bRo5). If fafg was &lt;0.01, values were set to 0.01. (<b>A</b>): P<sub>app,AB</sub>; true positive (upper-right-hand quadrant); true negative (lower-left-hand quadrant); false positive (lower-right-hand quadrant); and false negative (upper-left-hand quadrant). (<b>B</b>): Efflux ratios: true positive (upper-left-hand quadrant); true negative (lower-right-hand quadrant); false positive (lower-left-hand quadrant); and false negative (upper-right-hand quadrant).</p>
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17 pages, 5510 KiB  
Article
Down-Regulation of AKT Proteins Slows the Growth of Mutant-KRAS Pancreatic Tumors
by Chuankai Chen, Ya-Ping Jiang, Inchul You, Nathanael S. Gray and Richard Z. Lin
Cells 2024, 13(12), 1061; https://doi.org/10.3390/cells13121061 - 19 Jun 2024
Viewed by 996
Abstract
Serine/threonine kinase AKT isoforms play a well-established role in cell metabolism and growth. Most pancreatic adenocarcinomas (PDACs) harbor activation mutations of KRAS, which activates the PI3K/AKT signaling pathway. However, AKT inhibitors are not effective in the treatment of pancreatic cancer. To better understand [...] Read more.
Serine/threonine kinase AKT isoforms play a well-established role in cell metabolism and growth. Most pancreatic adenocarcinomas (PDACs) harbor activation mutations of KRAS, which activates the PI3K/AKT signaling pathway. However, AKT inhibitors are not effective in the treatment of pancreatic cancer. To better understand the role of AKT signaling in mutant-KRAS pancreatic tumors, this study utilized proteolysis-targeting chimeras (PROTACs) and CRISPR-Cas9-genome editing to investigate AKT proteins. The PROTAC down-regulation of AKT proteins markedly slowed the growth of three pancreatic tumor cell lines harboring mutant KRAS. In contrast, the inhibition of AKT kinase activity alone had very little effect on the growth of these cell lines. The concurrent genetic deletion of all AKT isoforms (AKT1, AKT2, and AKT3) in the KPC (KrasG12D; Trp53R172H; Pdx1-Cre) pancreatic cancer cell line also dramatically slowed its growth in vitro and when orthotopically implanted in syngeneic mice. Surprisingly, insulin-like growth factor-1 (IGF-1), but not epidermal growth factor (EGF), restored KPC cell growth in serum-deprived conditions, and the IGF-1 growth stimulation effect was AKT-dependent. The RNA-seq analysis of AKT1/2/3-deficient KPC cells suggested that reduced cholesterol synthesis may be responsible for the decreased response to IGF-1 stimulation. These results indicate that the presence of all three AKT isoforms supports pancreatic tumor cell growth, and the pharmacological degradation of AKT proteins may be more effective than AKT catalytic inhibitors for treating pancreatic cancer. Full article
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<p>The AKT degrader outcompeted AKT inhibitors in impeding cell growth. (<b>A</b>) The colony formation assay compared the effect on colony formation of the AKT degrader INY-05-040 and inhibitor GDC0068 in the human pancreatic cancer cell line PANC-1, low-passage patient-derived PDAC cell UM5, and mouse PDAC cell line KPC. A total of 50 cells were seeded into each well of 6-well plates and grew in indicated conditions for 9 days, 16 days, or 20 days, respectively, before crystal violet staining. Media were replaced every 4 days once drug treatment started. Left, pictures of the colonies. Middle and right, the quantifications of colony sizes and numbers of the colony formation assay. Data were analyzed with a one-way ANOVA, followed by multiple comparisons with the Tukey’s method. ns not significant, * <span class="html-italic">p</span> &lt; 0.05, ** <span class="html-italic">p</span> &lt; 0.01, **** <span class="html-italic">p</span> &lt; 0.0001. (<b>B</b>–<b>D</b>) Immunoblot comparing the AKT degrader and inhibitor treatment in the human pancreatic cancer cell line PANC-1, low-passage patient-derived PDAC cell UM5, and mouse KPC cell line FC1245, respectively. Cells were cultured as in (<b>A</b>).</p>
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<p>Generation of KPC cell lines deficient in <span class="html-italic">Akt</span> isoforms by CRISPR-Cas9 genome editing. (<b>A</b>) Schematic of the strategy to genetically delete all three <span class="html-italic">Akt</span> paralogous genes. (<b>B</b>) Immunoblot of AKT proteins in knockout cell lines. <b>(C</b>) Immunoblot comparing AKT signaling between KPC vs. <span class="html-italic">Akt</span>-deficient cell lines. (<b>D</b>) Immunoblot using indicated phospho-antibodies comparing MEK/ERK signaling between KPC vs. <span class="html-italic">Akt</span>-deficient cell lines. Both blots were probed with anti-HSP90 antibodies as an additional loading control.</p>
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<p>Loss of <span class="html-italic">Akt1/2/3</span> slowed KPC cell growth in vitro. (<b>A</b>) The growth curve of <span class="html-italic">Akt</span>-deficient KPC cell lines indicated <span class="html-italic">Akt1/2/3</span> KO cells grew the slowest. A total of 50,000 cells were seeded in each well of 6-well plates for a four-day growth assay (<span class="html-italic">n</span> = 3). The experiments were repeated three times with different passage numbers of the cell lines. The cell numbers were plotted as mean ± SD; the cell numbers on day 4 were analyzed by a one-way ANOVA (<span class="html-italic">p</span> &lt; 0.0001). Šídák’s multiple comparisons test was conducted between every possible pair, but only comparisons with <span class="html-italic">p</span> &lt; 0.05 are shown. * <span class="html-italic">p</span> &lt; 0.05, ** <span class="html-italic">p</span> &lt; 0.01, *** <span class="html-italic">p</span> &lt; 0.001, **** <span class="html-italic">p</span> &lt; 0.0001. (<b>B</b>) The colony formation assay of <span class="html-italic">Akt</span>-deficient cell lines. A total of 50 cells were seeded into each well of 6-well plates and grew for 7 days before evaluation. On the left are the images of the colonies of the indicated cell lines in technical replicates (<span class="html-italic">n</span> = 3). On the right is the quantification of the colony numbers and sizes. The colony numbers of parental KPC and <span class="html-italic">Akt1/2/3</span>KO cells were compared with the <span class="html-italic">t</span>-test. The colony sizes of all the lines were compared by a nested one-way ANOVA (<span class="html-italic">p</span> &lt; 0.0001). Multiple comparisons were performed with Tukey’s method between KPC and every other cell line, but only comparisons with <span class="html-italic">p</span> &lt; 0.05 are shown. * <span class="html-italic">p</span> &lt; 0.05, ** <span class="html-italic">p</span> &lt; 0.01, *** <span class="html-italic">p</span> &lt; 0.001, **** <span class="html-italic">p</span> &lt; 0.0001. See also <a href="#app1-cells-13-01061" class="html-app">Supplementary Figures S1 and S3</a>.</p>
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<p>Genetic ablation of <span class="html-italic">Akt1/2/3</span> slowed the progression of KPC tumors in a syngeneic orthotopic implantation mouse model. (<b>A</b>) Representative IVIS images for indicated time points of surviving mice with orthotopic cancer cell implantation. B6 mice were implanted with pancreatic cancer cells of the indicated genotypes. Mice were imaged using IVIS one day post-implantation and every week thereafter. The sample sizes are labeled in (<b>B</b>). (<b>B</b>) Quantification of the total flux from IVIS data of all the mice. As there were missing values, a mixed-effects analysis was conducted between KPC and <span class="html-italic">Akt1/2/3</span> KO with repeated measures, followed by Tukey’s multiple comparisons test. The statistical insignificance between KPC and <span class="html-italic">Akt1/2/3</span> KO of the 2-week time point was in part caused by the reduced sample size due to the deaths of the mice. (<b>C</b>) The Kaplan–Meier survival curve of mice implanted with the indicated cell line. Log-rank test of the survival of animals was performed (<span class="html-italic">p</span> &lt; 0.0001). The multiple comparisons between mice implanted with KPC and each of the single-, double-<span class="html-italic">Akt-</span>deficient cell lines, and <span class="html-italic">Akt1/2/3</span>KO and between <span class="html-italic">Akt1/2/3</span>KO and each of the double-<span class="html-italic">Akt</span>-deficient groups were made with Bonferroni correction, and only comparisons beyond the threshold (α<sub>bonferroni</sub> = 0.05/10 = 0.005) are shown. ns not significant, * <span class="html-italic">p</span> &lt; 0.005 ** <span class="html-italic">p</span> &lt; 0.001, *** <span class="html-italic">p</span> &lt; 0.0001.</p>
Full article ">Figure 5
<p><span class="html-italic">Akt1/2/3</span> was required for growth-promoting IGF-1 signaling in KPC cells. (<b>A</b>) Colony formation assay of parental KPC and <span class="html-italic">Akt1/2/3</span>KO cells cultured in the indicated conditions. A total of 10,000 cells were seeded in a 96-well plate and treatment started on day 2 by replacing the media with either DMEM with PBS, DMEM containing 100 ng/mL EGF or 100 ng/mL IGF-1 or 100 ng/mL EGF plus 100 ng/mL IGF-1, or 10% FBS. The media were replaced every day and cells were stained with crystal violet on day 5. The quantification of the crystal-violet-positive area with Image J is shown on the right; a two-way ANOVA was performed followed by Šídák’s multiple comparisons test. *** <span class="html-italic">p</span> &lt; 0.001, **** <span class="html-italic">p</span> &lt; 0.001. (<b>B</b>) Heatmap of all genes by RNA-seq of KPC and <span class="html-italic">Akt1/2/3</span>KO (<span class="html-italic">n</span> = 3). The experiment was conducted with triplicates of three different passages. The color scale for the z-score is shown on the right. (<b>C</b>) GSEA pathway enrichment analysis of the differentially expressed genes between KPC and <span class="html-italic">Akt1/2/3</span>KO cell lines, and subsequent visualization by EnrichmentMap in Cytoscape showed a cluster of interconnected pathways related to cholesterol metabolism. (<b>D</b>) The transcript levels of key genes involved in the cholesterol synthesis pathway. <span class="html-italic">t</span>-tests were performed. ** <span class="html-italic">p</span> &lt; 0.01, *** <span class="html-italic">p</span> &lt; 0.001, **** <span class="html-italic">p</span> &lt; 0.0001. <span class="html-italic">Srebp2</span> is a master regulator of cholesterol metabolism. <span class="html-italic">Hmgcs1</span> and <span class="html-italic">Hmgcr</span> encode the rate-limiting enzymes in the mevalonate pathway. <span class="html-italic">Ldlr</span> encodes the low-density lipoprotein receptor, responsible for cholesterol uptake. (<b>E</b>) Protein-mass-normalized whole-cell cholesterol levels were measured by the Amplex Red assay of KPC and <span class="html-italic">Akt1/2/3</span>KO cells in the indicated conditions. Two-way ANOVA with uncorrected Fisher’s LSD test. ns not significant, ** <span class="html-italic">p</span> &lt; 0.01.</p>
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16 pages, 1476 KiB  
Article
Cyclosporin A-Based PROTACs Can Deplete Abundant Cellular Cyclophilin A without Suppressing T Cell Activation
by Katharina Hilbig, Russell Towers, Marc Schmitz, Martin Bornhäuser, Petra Lennig and Yixin Zhang
Molecules 2024, 29(12), 2779; https://doi.org/10.3390/molecules29122779 - 11 Jun 2024
Viewed by 779
Abstract
Cyclophilin A (CypA), the cellular receptor of the immunosuppressant cyclosporin A (CsA), is an abundant cytosolic protein and is involved in a variety of diseases. For example, CypA supports cancer proliferation and mediates viral infections, such as the human immunodeficiency virus 1 (HIV-1). [...] Read more.
Cyclophilin A (CypA), the cellular receptor of the immunosuppressant cyclosporin A (CsA), is an abundant cytosolic protein and is involved in a variety of diseases. For example, CypA supports cancer proliferation and mediates viral infections, such as the human immunodeficiency virus 1 (HIV-1). Here, we present the design of PROTAC (proteolysis targeting chimera) compounds against CypA to induce its intracellular proteolysis and to investigate their effect on immune cells. Interestingly, upon connecting to E3 ligase ligands, both peptide-based low-affinity binders and CsA-based high-affinity binders can degrade CypA at nM concentration in HeLa cells and fibroblast cells. As the immunosuppressive effect of CsA is not directly associated with the binding of CsA to CypA but the inhibition of phosphatase calcineurin by the CypA:CsA complex, we investigated whether a CsA-based PROTAC compound could induce CypA degradation without affecting the activation of immune cells. P3, the most efficient PROTAC compound discovered from this study, could deplete CypA in lymphocytes without affecting cell proliferation and cytokine production. This work demonstrates the feasibility of the PROTAC approach in depleting the abundant cellular protein CypA at low drug dosage without affecting immune cells, allowing us to investigate the potential therapeutic effects associated with the endogenous protein in the future. Full article
(This article belongs to the Section Chemical Biology)
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<p><b>Design and synthesis of PROTACs against CypA</b>. (<b>A</b>) <span class="html-italic">Catalytic cycle of the PROTAC technique.</span> A PROTAC molecule is a bifunctional molecule and consists of a POI ligand, a linker, and an E3 ligase ligand. PROTAC brings the E3 ligase and the POI into proximity, leading to the subsequent degradation of POI by proteasome. In principle, the approach can be realized by using either a high-affinity binder (e.g., <b>P3</b>) or a low-affinity binder (e.g., <b>P5</b>). (<b>B</b>) <span class="html-italic">Chemical synthesis of CsA-derivative containing a terminal carboxylic group in the side chain of residue 1 and PROTAC compounds</span> <b>P1</b> <span class="html-italic">to</span> <b>P4</b>. (a) DCM, 0.2 eq. Grubbs Hoveyda II catalyst, 9.0 eq. pent-4-enoic acid, rt, and o.n. 9:1 MeOH/H<sub>2</sub>O, 10% Pd/C, H<sub>2</sub>, rt for 2 h. (b) DMF, 1.1 eq. PEG-linker:E3 ligase ligand compound, 1.2 eq. HATU, 6.0 eq. DIPEA, rt, and o.n. R corresponds to the VHL ligand or pomalidomide. (c) DMF, 1.1 eq. propargylamine, 1.2 eq. HATU, 6.0 eq. DIPEA, rt, and o.n.. R corresponds to the VHL ligand or pomalidomide. (d) Azide-conjugated VHL ligand or pomalidomide, 1:1 DMF/DMSO, 2.0 eq sodium ascorbate, 1.0 eq. CuSO<sub>4</sub> · 5 H<sub>2</sub>O, 0 °C → 60 °C and o.n.. (<b>C</b>) <span class="html-italic">Chemical synthesis of peptide-PROTACs containing a CypA binding site</span> <b>P5</b> <span class="html-italic">to</span> <b>P8</b>. (a) Azide-conjugated VHL ligand or pomalidomide, DMSO, 4.0 eq sodium ascorbate, 2.0 eq. CuSO<sub>4</sub> · 5 H<sub>2</sub>O.</p>
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<p><b>PROTAC compounds induce CypA degradation in HeLa cells analyzed by western blot.</b> (<b>A</b>) Eight-hour treatment, (<b>B</b>) 24 h treatment. (<b>C</b>) Treatment for eight hours with a mixture of <b>P1</b> and <b>P3</b>. (<b>D</b>) HDFn were pre-treated for one hour with 1 μM epoxomicin, 3 μM MG-132, 1 μM CsA, and 10 μM VHL ligand 1 and afterward incubated for seven hours with 1 μM <b>P3</b>. (<b>E</b>) HeLa cells treated for eight hours with peptide-based PROTACs <b>P5</b> to <b>P8</b>.</p>
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<p><b>P3 induces CypA degradation in PBMCs.</b> (<b>A</b>) Western blot of PBMCs from donor one treated with <b>P3</b> or CsA after four days or a daily treatment with DMSO or 1 μM <b>P3</b> for four days (marked with *). (<b>B</b>) Overview of the same experiments as in A) with five different PBMC donors. (<b>C</b>) PPIase activity assay of the cell lysate of PBMCs treated with <b>P3</b> or CsA for four days, or daily treatment with DMSO or 1 3M <b>P3</b> for four days (marked with *). Dashed line marks the mean of the five donors, and the solid line is the median.</p>
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<p><b>P3 does not induce cell death or cytokine secretion of PBMCs.</b> (<b>A</b>) FACS experiments to investigate the effect of the PROTAC on PBMC proliferation regarding the necrosis (<span class="html-italic">y</span>-axis) and apoptosis (<span class="html-italic">x</span>-axis). The markers used to determine the two types of cell death are 7-AAD (necrosis) and Annexin V (apoptosis). A representative dataset of one donor represents two biological replicates/donors. (<b>A</b>) PBMCs without treatment and treated with <b>P3</b> or DMSO control. (<b>B</b>) Proliferation assay with <sup>3</sup>H-Thymidine. * Daily treatment with DMSO/1 μM <b>P3</b> for 4 days. (<b>C</b>) ELISA assay with primary antibody against IL-2. Experiments were performed with five different donors. The control defines the IL-2 response of CD3/CD28-stimulated PBMCs. Treatment with DMSO, CsA, and <b>P3</b>. * Daily treatment with DMSO or 1 µM <b>P3</b> for 4 days. (<b>D</b>) ELISA assay with primary antibody against INF-γ. Experiments were performed with five different donors. The control defines the IFN-γ response of CD3/CD28-stimulated PBMCs. Treatment with DMSO, CsA, and <b>P3</b>. * Daily treatment with DMSO or 1 μM <b>P3</b>. The dashed line marks the mean of the five donors, and the solid line is the median.</p>
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23 pages, 3219 KiB  
Review
Extracellular Interactors of the IGF System: Impact on Cancer Hallmarks and Therapeutic Approaches
by Caterina Mancarella, Andrea Morrione and Katia Scotlandi
Int. J. Mol. Sci. 2024, 25(11), 5915; https://doi.org/10.3390/ijms25115915 - 29 May 2024
Viewed by 1494
Abstract
Dysregulation of the insulin-like growth factor (IGF) system determines the onset of various pathological conditions, including cancer. Accordingly, therapeutic strategies have been developed to block this system in tumor cells, but the results of clinical trials have been disappointing. After decades of research [...] Read more.
Dysregulation of the insulin-like growth factor (IGF) system determines the onset of various pathological conditions, including cancer. Accordingly, therapeutic strategies have been developed to block this system in tumor cells, but the results of clinical trials have been disappointing. After decades of research in the field, it is safe to say that one of the major reasons underlying the poor efficacy of anti-IGF-targeting agents is derived from an underestimation of the molecular complexity of this axis. Genetic, transcriptional, post-transcriptional and functional interactors interfere with the activity of canonical components of this axis, supporting the need for combinatorial approaches to effectively block this system. In addition, cancer cells interface with a multiplicity of factors from the extracellular compartment, which strongly affect cell destiny. In this review, we will cover novel extracellular mechanisms contributing to IGF system dysregulation and the implications of such dangerous liaisons for cancer hallmarks and responses to known and new anti-IGF drugs. A deeper understanding of both the intracellular and extracellular microenvironments might provide new impetus to better decipher the complexity of the IGF axis in cancer and provide new clues for designing novel therapeutic approaches. Full article
(This article belongs to the Special Issue The Role of the IGF Axis in Disease, 3nd Edition)
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<p>Schematic representation of the functional connections between the IGF system and major components of the tumor microenvironment (TME): cancer-associated fibroblasts (CAFs), tumor-associated macrophages (TAMs), and T lymphocytes. In cancer cells, IGF1 and IGF2 ligands bind with different affinities to IGF1R and IR-A, leading to the activation of the downstream PI3K/AKT and MAPK pathways. CAFs secrete IGF1, IGF2, and IGFBPs, eliciting the activation or inhibition of the IGF1R/IR-A axis, respectively, depending on their relative abundance. CAFs’ exposure to chemoradiotherapy enhances ligand secretion. TAMs secrete IGF1 and IGF2, leading to IGF1R/IR-A activation in cancer cells. Tumor-derived IGF1/IGF2 activate the IGF1R in TAMs (see the arrow), causing TAM polarization toward an M2-like pro-tumorigenic phenotype. The active IGF system in cancer cells favors the expression of the immune checkpoint inhibitor programmed death ligand 1 (PD-L1), which in turn binds to and inhibits the programmed death protein 1 (PD-1) on T-cells, causing T-cell suppression. Biological responses critical for cancer development and progression and functionally associated with the depicted interactions are reported on the right.</p>
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<p>Schematic representation of the functional connections between the IGF system and extracellular vesicles in the tumor microenvironment (TME). In cancer cells, IGF1, IGF2, and insulin ligands bind with different affinities to IGF1R and IR-A, leading to the activation of the downstream PI3K/AKT and MAPK pathways and biological responses. IGF1R activates SRC to induce downstream signaling. At the post-transcriptional level, different regulators modulate IGF1R expression in the cytoplasm. The RNA-binding protein IGF2BP3 sustains IGF1R mRNA translation and expression. The depicted microRNAs (miRs) 99b-5p, 603, and 100-5p inhibit IGF1R expression. The long non-coding RNA (lncRNA) MLETA sponges miR-497-5p, thereby favoring IGF1R expression. Cancer cells as well as cells from the TME, including mesenchymal stem cells and cancer-associated fibroblasts (CAFs), secrete extracellular vesicles containing major interactors/regulators of the IGF system (up arrow indicates elevated content of reported microRNA while down arrow indicates low content of reported microRNA). Biological responses critical for cancer development and progression and functionally associated with the depicted interactions are reported on the right.</p>
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<p>Schematic representation of the functional crosstalk between the IGF system and the Receptor for Advanced Glycation End Products (RAGE). In cancer cells, IGF1R and IR-A display high or low affinity for the ligands. Hyperglycemia favors the generation of AGE products, which activate RAGE. RAGE interacts with IGF1R and IR-A, modulating the activation of the PI3K/AKT/MAPK pathways and sustaining the transcription of IGF1 and the RAGE ligand S100A7. S100A7 additionally interacts with RAGE in vascular endothelial cells, sustaining angiogenesis. Biological responses critical for cancer development and progression and functionally associated with the depicted interactions are reported.</p>
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<p>Schematic representation of emerging therapeutic strategies targeting the IGF system. In the extracellular compartment, IGF1, IGF2, and insulin bind their cognate receptors IGF1R, IR-A, and IR-B with different affinities. Receptor activation causes the activation of the downstream PI3K/AKT and RAS/MAPK pathways. Biological responses elicited by an active IGF system and critical for cancer development and progression are reported. The IGF-Trap binds to IGF1 and IGF2 but not insulin and blocks IGF1/IGF2 binding to the receptors. In the cytoplasm, different proteolysis-targeting chimeras (PROTACs) induce the degradation of various proteins of interest: 1. IGF1R and its interactor SRC; 2. PI3Kα and PI3Kβ isoforms of PI3K; 3. AKT. Transduction of retroviral particles containing IGF1R or IGF1 antisense oligos blocks IGF1R and IGF1 expression. The major advantages of the depicted therapeutic approaches are reported in boxes.</p>
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14 pages, 4002 KiB  
Article
Sustainable and Safe N-alkylation of N-heterocycles by Propylene Carbonate under Neat Reaction Conditions
by Andrea Czompa, Dóra Bogdán, Balázs Balogh, Eszter Erdei, Patrik Selymes, Attila Csomos and István M. Mándity
Int. J. Mol. Sci. 2024, 25(10), 5523; https://doi.org/10.3390/ijms25105523 - 18 May 2024
Viewed by 670
Abstract
A new, eco-friendly process utilising the green solvent propylene carbonate (PC) has been developed to perform N-alkylation of N-, O- and/or S-containing heterocyclic compounds. PC in these reactions served as both the reagent and solvent. Importantly, no genotoxic alkyl [...] Read more.
A new, eco-friendly process utilising the green solvent propylene carbonate (PC) has been developed to perform N-alkylation of N-, O- and/or S-containing heterocyclic compounds. PC in these reactions served as both the reagent and solvent. Importantly, no genotoxic alkyl halides were required. No auxiliary was necessary when using anhydrous PC. Product formation includes nucleophilic substitution with the concomitant loss of water and carbon dioxide. Substrates prepared, including the newly invented PROTAC drugs, are widely used. Full article
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<p>The structures of substrates studied.</p>
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<p>General outline of the performed reactions.</p>
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<p>Tautomer of phthalimide.</p>
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<p><span class="html-italic">N</span>-Hydroxyalkylation of phthalimide (<b>1</b>).</p>
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<p><span class="html-italic">N</span>-Alkylation of isatine (<b>2</b>).</p>
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<p>Tautomers of phthalazin-1(2<span class="html-italic">H</span>)-one.</p>
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<p><span class="html-italic">N</span>-Alkylation of phthalazin-1(2<span class="html-italic">H</span>)-one (<b>3</b>).</p>
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<p>The structure of pyrimidin-4(3<span class="html-italic">H</span>)-one anions.</p>
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<p><span class="html-italic">N</span>-Alkylation of pyrimidin-4(3<span class="html-italic">H</span>)-one (<b>4</b>).</p>
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<p><span class="html-italic">N</span>-Alkylation of 6-methylpyrimidine-2,4(1<span class="html-italic">H</span>,3<span class="html-italic">H</span>)-dione (<b>5</b>).</p>
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<p>Possible transformation routes in the alkylation of 6-methylpyrimidine-2,4(1<span class="html-italic">H</span>,3<span class="html-italic">H</span>)-dione.</p>
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<p>Isomeric 1<span class="html-italic">H</span>- and 2<span class="html-italic">H</span>-benzotriazoles.</p>
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<p>Results with benzotriazole (<b>6</b>).</p>
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<p>Hydrolysis of 2-thiouracil and its tautomer.</p>
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<p><span class="html-italic">N</span>-Alkylation of 2-thiouracil (<b>7</b>) with 99% PC and CaCl<sub>2</sub>.</p>
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<p><span class="html-italic">N</span>-Alkylation of 2-thiouracil (<b>7</b>) with 99.7% PC without CaCl<sub>2</sub>.</p>
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<p>Cyclisation products of uracil and 2-thiouracil.</p>
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19 pages, 946 KiB  
Review
Clinical Developments and Challenges in Treating FGFR2-Driven Gastric Cancer
by David K. Lau, Jack P. Collin and John M. Mariadason
Biomedicines 2024, 12(5), 1117; https://doi.org/10.3390/biomedicines12051117 - 17 May 2024
Viewed by 1337
Abstract
Recent advances in the treatment of gastric cancer (GC) with chemotherapy, immunotherapy, anti-angiogenic therapy and targeted therapies have yielded some improvement in survival outcomes; however, metastatic GC remains a lethal malignancy and amongst the leading causes of cancer-related mortality worldwide. Importantly, the ongoing [...] Read more.
Recent advances in the treatment of gastric cancer (GC) with chemotherapy, immunotherapy, anti-angiogenic therapy and targeted therapies have yielded some improvement in survival outcomes; however, metastatic GC remains a lethal malignancy and amongst the leading causes of cancer-related mortality worldwide. Importantly, the ongoing molecular characterisation of GCs continues to uncover potentially actionable molecular targets. Among these, aberrant FGFR2-driven signalling, predominantly arising from FGFR2 amplification, occurs in approximately 3–11% of GCs. However, whilst several inhibitors of FGFR have been clinically tested to-date, there are currently no approved FGFR-directed therapies for GC. In this review, we summarise the significance of FGFR2 as an actionable therapeutic target in GC, examine the recent pre-clinical and clinical data supporting the use of small-molecule inhibitors, antibody-based therapies, as well as novel approaches such as proteolysis-targeting chimeras (PROTACs) for targeting FGFR2 in these tumours, and discuss the ongoing challenges and opportunities associated with their clinical development. Full article
(This article belongs to the Section Cancer Biology and Oncology)
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<p>Schematic diagram of the four major FGFR signalling pathways and location of binding sites for FGFR-targeting agents. FGFR 1–4 monomers are comprised of an extracellular region with three immunoglobulin-like domains, a transmembrane domain, and an intracellular region containing two tyrosine kinase domains. FGF binding to FGFR (which is stabilised by HSPG) triggers receptor dimerization and FRS2α phosphorylation. Phosphorylated FRS2α is then able to recruit SOS and GRB2, which initiates the RAS/MAPK and PI3K/AKT/mTOR signalling pathways. Additional signalling pathways initiated by FGFR activation include JAK/STAT and PLCγ/DAG/PKC. FGFR-targeting agents, including small-molecule FGFR inhibitors and FGFR-targeting monoclonal antibodies, bind to the tyrosine kinase domain and the immunoglobulin domain of FGFR, respectively, to inhibit downstream signalling output. Abbreviations: FGF—fibroblast growth factor, FGFR—fibroblast growth factor receptor, FGFRi: fibroblast growth factor receptor inhibitor.</p>
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15 pages, 1140 KiB  
Review
PROTACs in Ovarian Cancer: Current Advancements and Future Perspectives
by Makenzie Vorderbruggen, Carlos A. Velázquez-Martínez, Amarnath Natarajan and Adam R. Karpf
Int. J. Mol. Sci. 2024, 25(10), 5067; https://doi.org/10.3390/ijms25105067 - 7 May 2024
Viewed by 1717
Abstract
Ovarian cancer is the deadliest gynecologic malignancy. The majority of patients diagnosed with advanced ovarian cancer will relapse, at which point additional therapies can be administered but, for the most part, these are not curative. As such, a need exists for the development [...] Read more.
Ovarian cancer is the deadliest gynecologic malignancy. The majority of patients diagnosed with advanced ovarian cancer will relapse, at which point additional therapies can be administered but, for the most part, these are not curative. As such, a need exists for the development of novel therapeutic options for ovarian cancer patients. Research in the field of targeted protein degradation (TPD) through the use of proteolysis-targeting chimeras (PROTACs) has significantly increased in recent years. The ability of PROTACs to target proteins of interest (POI) for degradation, overcoming limitations such as the incomplete inhibition of POI function and the development of resistance seen with other inhibitors, is of particular interest in cancer research, including ovarian cancer research. This review provides a synopsis of PROTACs tested in ovarian cancer models and highlights PROTACs characterized in other types of cancers with potential high utility in ovarian cancer. Finally, we discuss methods that will help to enable the selective delivery of PROTACs to ovarian cancer and improve the pharmacodynamic properties of these agents. Full article
(This article belongs to the Special Issue Ovarian Cancer: Advances on Pathophysiology and Therapies)
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<p>PROTAC structure and mechanism of action (MOA): (<b>A</b>) the PROTAC structure includes a warhead that binds the POI, a linker, and an E3 ligase ligand; and (<b>B</b>) the PROTAC MOA includes the formation of a ternary complex comprised of the POI, the PROTAC, and the E3 ligase. The transfer of Ubiquitin to the POI leads to its proteolytic degradation by the proteosome, while the PROTAC is recycled and can engage another molecule of POI. Figure created with <a href="http://BioRender.com" target="_blank">BioRender.com</a>.</p>
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<p>Biological effects of PROTACs tested in EOC models. Figure created with <a href="http://BioRender.com" target="_blank">BioRender.com</a>.</p>
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<p>Methods to improve selective delivery of PROTACs in EOC: (<b>A</b>) conjugation of folate to PROTACs results in selectivity for cells expressing FRα; (<b>B</b>) inorganic, lipid-based, and polymeric nanoparticle-based PROTAC delivery; (<b>C</b>) conjugation of PROTACs to antibodies facilitates selective delivery; and (<b>D</b>) light irradiation removes the caging group on opto-PROTACs, activating the PROTAC. Created with BioRender.com.</p>
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23 pages, 14761 KiB  
Article
Self-Assembled Matrine-PROTAC Encapsulating Zinc(II) Phthalocyanine with GSH-Depletion-Enhanced ROS Generation for Cancer Therapy
by Sitong Lai, Bing Wang, Kunhui Sun, Fan Li, Qian Liu, Xie-An Yu, Lihe Jiang and Lisheng Wang
Molecules 2024, 29(8), 1845; https://doi.org/10.3390/molecules29081845 - 18 Apr 2024
Cited by 1 | Viewed by 1018
Abstract
The integration of a multidimensional treatment dominated by active ingredients of traditional Chinese medicine (TCM), including enhanced chemotherapy and synergistically amplification of oxidative damage, into a nanoplatform would be of great significance for furthering accurate and effective cancer treatment with the active ingredients [...] Read more.
The integration of a multidimensional treatment dominated by active ingredients of traditional Chinese medicine (TCM), including enhanced chemotherapy and synergistically amplification of oxidative damage, into a nanoplatform would be of great significance for furthering accurate and effective cancer treatment with the active ingredients of TCM. Herein, in this study, we designed and synthesized four matrine-proteolysis-targeting chimeras (PROTACs) (depending on different lengths of the chains named LST-1, LST-2, LST-3, and LST-4) based on PROTAC technology to overcome the limitations of matrine. LST-4, with better anti-tumor activity than matrine, still degrades p-Erk and p-Akt proteins. Moreover, LST-4 NPs formed via LST-4 self-assembly with stronger anti-tumor activity and glutathione (GSH) depletion ability could be enriched in lysosomes through their outstanding enhanced permeability and retention (EPR) effect. Then, we synthesized LST-4@ZnPc NPs with a low-pH-triggered drug release property that could release zinc(II) phthalocyanine (ZnPc) in tumor sites. LST-4@ZnPc NPs combine the application of chemotherapy and phototherapy, including both enhanced chemotherapy from LST-4 NPs and the synergistic amplification of oxidative damage, through increasing the reactive oxygen species (ROS) by photodynamic therapy (PDT), causing an GSH decrease via LST-4 mediation to effectively kill tumor cells. Therefore, multifunctional LST-4@ZnPc NPs are a promising method for killing cancer cells, which also provides a new paradigm for using natural products to kill tumors. Full article
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Figure 1
<p>Synthetic routes of LST-1, LST-2, LST-3, and LST-4.</p>
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<p>Viability of HepG2 cells treated with various concentrations of (<b>a</b>) LST-1, (<b>b</b>) LST-2, (<b>c</b>) LST-3, and (<b>d</b>) LST-4 (n = 4). (<b>e</b>) Comparison of IC<sub>50</sub> in HepG2 cells treated with target compounds (LST-1, LST-2, LST-3, and LST-4) (n = 3). (<b>f</b>) p-Akt and p-Erk expression in HepG2 cells after a series of concentration treatments (1. 0, 2. 1/2 × IC<sub>50</sub>, 3. IC<sub>50,</sub> 4. 2 × IC<sub>50</sub>).</p>
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<p>(<b>a</b>) UV–Vis absorption spectra of LST-4. (<b>b</b>) FL emission spectra of LST-4 with λ<sub>Ex</sub> = 416 nm. (<b>c</b>) Quantification of GSH levels in HepG2 cells with a series of concentrations treatments (1. 0, 2. 1/2 × IC<sub>50</sub> (LST-4), 3. IC<sub>50</sub> (LST-4), 4. 2 × IC<sub>50</sub> (LST-4)) (n = 3). (<b>d</b>) In vitro FL images of LST-4 at different concentrations of MeOH with λ<sub>Em</sub> = 503 nm.</p>
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<p>(<b>a</b>) Photograph of ZnPc, LST-4, LST-4 NPs, and LST-4@ZnPc NPs. (<b>b</b>) The UV–Vis absorption spectra of ZnPc, LST-4, LST-4 NPs, and LST-4@ZnPc NPs (ZnPc, LST-4, LST-4 NPs, and LST-4@ZnPc NPs at the same concentration is 20 μg/mL). (<b>c</b>) The fluorescence intensities of ZnPc, LST-4, LST-4 NPs, and LST-4@ZnPc NPs (ZnPc, LST-4, LST-4 NPs, and LST-4@ZnPc NPs at the same concentration of 20 μg/mL). (<b>d</b>) TEM images of LST-4 NPs. (<b>e</b>) TEM images of LST-4@ZnPc NPs. (<b>f</b>) Size distribution of LST-4@ZnPc NPs. (<b>g</b>) Zeta potentials of LST-4@ZnPc NPs. (<b>h</b>) UV–Vis absorption response recovery in LST-4 NPs solution at different pH values. (<b>i</b>) Fluorescence response recovery in LST-4 NPs solution at different pH values.</p>
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<p>(<b>a</b>) The UV–Vis spectra of DPBF containing LST-4 for different irradiation times. (<b>b</b>) The corresponding relative absorbance variations under 690 nm laser irradiation (0.2 W/cm<sup>2</sup>), including DPBF, ZnPc, and LST-4. (<b>c</b>) The UV–Vis spectra of DPBF containing LST-4 NPs for different irradiation times. (<b>d</b>) The UV–Vis spectra of DPBF containing LST-4@ZnPc NPs for different irradiation times. (<b>e</b>) The UV–Vis spectra of DPBF containing LST-4@ZnPc NPs (+Acid) for different irradiation times. (<b>f</b>) The corresponding relative absorbance variations under 690 nm laser irradiation (0.2 W/cm<sup>2</sup>) including LST-4 NPs, LST-4@ZnPc NPs, and LST-4@ZnPc NPs + Acid.</p>
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<p>Cell uptake of LST-4@ZnPc NPs by HepG2 cells with different incubation times (0, 0.5, 1, 2, 4 h). The green fluorescence represents LST-4 NPs, the purple fluorescence represents ZnPc, and the blue fluorescence represents the cell nuclei by H33342. (Scale bar represents 20 µm).</p>
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<p>Confocal fluorescence images of HepG2 cells stained with LysoTracker Red and Hoechst 33342 following incubation with LST-4@ZnPc NPs for 4 h. (Scale bar represents 20 µm.).</p>
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<p>(<b>a</b>) Intracellular generation of ROS in HepG2 cells after different treatments with cellrox<sup>TM</sup> orange as a probe. (Scale bar represents 20 µm.) (<b>b</b>) Quantification comparison of GSH levels in HepG2 cells with a series of concentrations treatments including LST-4 and LST-4 NPs. (1. 1/2 × IC<sub>50</sub> (LST-4 NPs), 2. IC<sub>50</sub> (LST-4 NPs), 3. 2 × IC<sub>50</sub> (LST-4 NPs)) (n = 3). (<b>c</b>) Viability of HepG2 cells treated with various concentrations of LST-4 NPs (n = 4). (<b>d</b>) Viability of HepG2 cells treated with various concentrations of LST-4@ZnPc NPs in dark or upon exposure to laser radiation (a 690 nm laser (0.2 W/cm<sup>2</sup>, 5 min)) (n = 4). (<b>e</b>) Comparison of IC<sub>50</sub> in HepG2 cells treated with various conditions (1. LST-4, 2. LST-4 NPs, 3. LST-4@ZnPc NPs + Dark, 4. LST-4@ZnPc NPs + Laser) (n = 4).</p>
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<p>Schematic illustrations of (<b>a</b>,<b>b</b>) structure and (<b>c</b>) function of the LST-4@ZnPc NPs for TME, responding to selectively and effectively kill cancer cells via combination therapy, including both chemotherapy and synergistic amplification of oxidative damage.</p>
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