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KMS-11R cells harbour a Val555Met gatekeeper mutation in FGFR3. (a, b) Genomic DNA from KMS-11 or KMS-11R cells was extracted, and PCR was performed using M13-tagged forward and reverse primers to amplify (a) exon 9 including codon 373 or (b) exon 13 including codon 555 from FGFR3. PCR products were sequenced in both directions by dye-terminator sequencing using the ABI3730 capillary sequencer. Both KMS-11 and KMS-11R cells harbour the driving FGFR3Y373C mutation, whereas only KMS-11R harbour the FGFR3V555M gatekeeper mutation. (c) Cartoon and surface-rendered representation of the ATP-binding pocket of human FGFR1 in complex with PD173074 (sticks) (2fgi.pdb). Gatekeeper residue Val561, equivalent to FGFR3 Val555, is shown in yellow in upper panels. A model of the Val561-to-Met mutation, highlighted in yellow, is shown in the lower panels. Pocket surface contributed by Val561 or Met561 is shown in panels on right.

KMS-11R cells harbour a Val555Met gatekeeper mutation in FGFR3. (a, b) Genomic DNA from KMS-11 or KMS-11R cells was extracted, and PCR was performed using M13-tagged forward and reverse primers to amplify (a) exon 9 including codon 373 or (b) exon 13 including codon 555 from FGFR3. PCR products were sequenced in both directions by dye-terminator sequencing using the ABI3730 capillary sequencer. Both KMS-11 and KMS-11R cells harbour the driving FGFR3Y373C mutation, whereas only KMS-11R harbour the FGFR3V555M gatekeeper mutation. (c) Cartoon and surface-rendered representation of the ATP-binding pocket of human FGFR1 in complex with PD173074 (sticks) (2fgi.pdb). Gatekeeper residue Val561, equivalent to FGFR3 Val555, is shown in yellow in upper panels. A model of the Val561-to-Met mutation, highlighted in yellow, is shown in the lower panels. Pocket surface contributed by Val561 or Met561 is shown in panels on right.

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Fibroblast growth factor receptors (FGFRs) can act as driving oncoproteins in certain cancers, making them attractive drug targets. Here we have characterized tumour cell responses to two new inhibitors of FGFR1-3, AZ12908010 and the clinical candidate AZD4547, making comparisons with the well-characterized FGFR inhibitor PD173074. In a panel of 16...

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... mutations in several tyrosine kinases confer increased activity as well as being drug refractory. 38 Sequencing confirmed that both KMS-11 and KMS-11R contained the FGFR Y373C mutation (Figure 7a), but we also found a heterozygous mutation encoding FGFR V555M in KMS-11R cells that was not detected in parental KMS-11 cells (Figure 7b). Val555 of FGFR3 has the same role as Val561 of FGFR1 and Val564 of FGFR2 as the gatekeeper residue in the ATP-binding site (shown in yellow in Figure 7c, upper panels); mutations at this site frequently impart resistance to TKIs. ...
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... mutations in several tyrosine kinases confer increased activity as well as being drug refractory. 38 Sequencing confirmed that both KMS-11 and KMS-11R contained the FGFR Y373C mutation (Figure 7a), but we also found a heterozygous mutation encoding FGFR V555M in KMS-11R cells that was not detected in parental KMS-11 cells (Figure 7b). Val555 of FGFR3 has the same role as Val561 of FGFR1 and Val564 of FGFR2 as the gatekeeper residue in the ATP-binding site (shown in yellow in Figure 7c, upper panels); mutations at this site frequently impart resistance to TKIs. ...
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... Sequencing confirmed that both KMS-11 and KMS-11R contained the FGFR Y373C mutation (Figure 7a), but we also found a heterozygous mutation encoding FGFR V555M in KMS-11R cells that was not detected in parental KMS-11 cells (Figure 7b). Val555 of FGFR3 has the same role as Val561 of FGFR1 and Val564 of FGFR2 as the gatekeeper residue in the ATP-binding site (shown in yellow in Figure 7c, upper panels); mutations at this site frequently impart resistance to TKIs. [38][39][40] As residues comprising the ATP-binding pocket are completely conserved among FGFR1-3, with the exception of Ala559 in FGFR3 (see Methods), we used the structure of PD173074 in complex with FGFR1 to model this mutation. ...
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... As residues comprising the ATP-binding pocket are completely conserved among FGFR1-3, with the exception of Ala559 in FGFR3 (see Methods), we used the structure of PD173074 in complex with FGFR1 to model this mutation. 41 Our model suggests that Met, with a B25% bulkier side-chain, will restrict access to the cavity adjacent to the adenine ring-binding region (shown in yellow in Figure 7c, lower panel). In particular, the equivalent residue of FGFR1, Val561, makes van der Waals contact with the PD173074, 41 whereas the bulkier side chain of Met561 would disrupt binding of PD173074 (Figure 7c, lower panel). ...
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... Our model suggests that Met, with a B25% bulkier side-chain, will restrict access to the cavity adjacent to the adenine ring-binding region (shown in yellow in Figure 7c, lower panel). In particular, the equivalent residue of FGFR1, Val561, makes van der Waals contact with the PD173074, 41 whereas the bulkier side chain of Met561 would disrupt binding of PD173074 (Figure 7c, lower panel). Taken together, our results suggest that a secondary gatekeeper mutation accounts for acquired resistance to AZ8010, AZD4547 and PD173074 in KMS-11R cells. ...

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... Due to the fact that patients respond differently to SMIs, such as Erdafitinib, and therapy resistances will inevitably occur in the clinical setting, we focused on this adaptive response. Published reports on how to effectively overcome resistance to FGFR inhibition are scarce [16][17][18][19]. Studies in urothelial, hepatic cholangio and breast carcinomas examined various targeting strategies for mutated FGFR variants and adaptive feedback loops activated after FGFR deactivation. ...
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... AZD4547, BGJ398, LY2874455, monoclonal antibodies such as MGFR1877S, and finally FGF traps such as HGS1036/ FP-1039 are selective TKIs. [77][78][79][80][81][82][83][84][85][86][87][88] Selective Anti-FGFR TKIs 1 [85,89] 2. BGJ398 is the next selective inhibitor of FGFR1-3. [86] Successful results of using this type of inhibitor to reduce tumor-induced lesions in amplified lung cancer have been reported in some studies. ...
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Artificial intelligence talks about modeling intelligent behavior through a computer with the least human involvement. Drug repositioning techniques based on artificial intelligence accelerate the research process and decrease the cost of experimental studies. Dysregulation of fibroblast growth factor (FGF) receptors as the tyrosine kinase family of receptors plays a vital role in a wide range of malignancies. Because of their functional significance, they were considered promising drug targets for the therapy of various cancers. This review has summarized small molecules capable of inhibiting FGF receptors that progressed using artificial intelligence and repositioning drugs examined in clinical trials associated with cancer therapy. This review is based on a literature search in PubMed, Web of Science, Scopus EMBASE, and Google Scholar databases to gather the necessary information in each chapter by employing keywords like artificial intelligence, computational drug design, drug repositioning, and FGF receptor inhibitors. To achieve this goal, a spacious literature review of human studies in these fields—published over the last 20 decades—was performed. According to published reports, nonselective FGF receptor inhibitors can be used for cancer management, and multitarget kinase inhibitors are the first drug class approved due to more advanced clinical studies. For example, AZD4547 and BGJ398 are gradually entering the consumption cycle and are good options as combined treatments. Artificial intelligence and drug repositioning methods can help preselect suitable drug targets more successfully for future inhibition of carcinogenicity.
... 1,3 Selective small-molecule FGFR inhibitors have shown clinical efficacy in patients with tumors harboring FGFR pathway aberrations; however, most are reversible adenosine triphosphate (ATP)competitive inhibitors, for which the emergence of acquired resistance mutations in the FGFR kinase domain is a major challenge. [4][5][6][7] Futibatinib (TAS-120) is a novel and highly selective inhibitor of all four FGFR subtypes that, via covalent binding, results in the irreversible inhibition of downstream FGF/FGFR signaling. Futibatinib has shown broad antiproliferative activity in FGFR-deregulated cell lines and xenograft models. ...
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... FGFR3 mutations have been reported to implicate in malignant tumors, such as urothelial carcinoma [16,17], lung adenocarcinoma [18] and cervical cancer [19,20]. Just as kinase domain mutations in other tyrosine kinases lead to resistance to targeted inhibitors [21,22], point mutations in the molecular break residue (I538V, N540S/K), gatekeeper residue (V555M) of FGFR3 or TEL-FGFR3 are resistant to FGFR inhibitors, such as AZD4547 and erdafitinib [23][24][25]. However, the underlying mechanism of FGFR3 kinase domain mutations leading to drug resistance remains unclear. ...
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FGFR3 kinase mutations are associated with a variety of malignancies, but FGFR3 mutant inhibitors have rarely been studied. Furthermore, the mechanism of pan-FGFR inhibitors resistance caused by kinase domain mutations is still unclear. In this study, we try to explain the mechanism of drug resistance to FGFR3 mutation through global analysis and local analysis based on molecular dynamics simulation, binding free energy analysis, umbrella sampling and community network analysis. The results showed that FGFR3 mutations caused a decrease in the affinity between drugs and FGFR3 kinase, which was consistent with the reported experimental results. Possible mechanisms are that mutations affect drug-protein affinity by altering the environment of residues near the hinge region where the protein binds to the drug, or by affecting the A-loop and interfering with the allosteric communication networks. In conclusion, we systematically elucidated the underlying mechanism of pan-FGFR inhibitor resistance caused by FGFR3 mutation based on molecular dynamics simulation strategy, which provided theoretical guidance for the development of FGFR3 mutant kinase inhibitors.
... In contrast, drug resistance for anti-RTK TKIs occurs largely through secondary mutations in RTK kinase domain as well as moderately through bypass signaling activation of other RTKs or downstream molecules 267 . The secondary mutations consist of a large group of gatekeeper mutations such as T790M in EGFR, T798I in HER2, L1196M in ALK, T670I in c-Kit and those in FGFRs (V561M in FGFR1, V564M in FGFR2, V555M in FGFR3, and V550L/M in FGFR4) as well as some other mutations altering drug-binding pocket, which impair the loading of first-generation TKIs and hence abolish their efficacy 167,168,275,276,169,[268][269][270][271][272][273][274] . This problem has been resolved by the second-or third-generation TKIs that were designed to target the secondary mutations of RTKs. ...
... The KMS-11 myeloma cell line study revealed that the FGFR3 V555M mutant is resistant to AZD4547 and PD173074. Downstream signal transduction and FGFR3 phosphorylation could be correlated (Chell et al., 2013). Looking at the conformational explanation, it could be a steric clash with the PD173074 phenyl ring and structural changes in the P-the loop region (Yoza et al., 2016). ...
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... Although tyrosine kinase inhibitors (TKIs) are often used to treat these dysregulated FGFR driven cancers, this therapeutic method often leads to the emergence of a resistant population of cancer cells exhibiting gatekeeper mutations [9]. Such mutations prevent proper binding of TKIs, giving way to a subset of cancer cells that are resistant to TKI treatment, ultimately leading to relapse in patients despite initial responsiveness to treatment [10]. This developed resistance to TKI therapies highlights the need for new approaches to treating cancers with dysregulated FGFRs. ...
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... 2b and 3. PD166866 is considered as an FGFR1 inhibitor, while both BGJ398 and AZD4547 are potent inhibitors of FGFRs 1-3, although they might affect FGFR4 weakly. All the inhibitors affect tyrosine kinase activity, hence autophosphorylation and signaling [26][27][28], Treatment of microglial cells with FGFR inhibitors showed that they had efficacies at different doses. PD166866/FGFR1 inhibitor, in the presence of B. burgdorferi, did not have an appreciable effect at 500 nM concentration while at higher concentrations (≥ 1 µM) it significantly downregulated IL-6, CXCL8 and CCL2 (Fig. 2b). ...
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Background Lyme neuroborreliosis, caused by the bacterium Borrelia burgdorferi affects both the central and peripheral nervous systems (CNS, PNS). The CNS manifestations, especially at later stages, can mimic/cause many other neurological conditions including psychiatric disorders, dementia, and others, with a likely neuroinflammatory basis. The pathogenic mechanisms associated with Lyme neuroborreliosis, however, are not fully understood. Methods In this study, using cultures of primary rhesus microglia, we explored the roles of several fibroblast growth factor receptors (FGFRs) and fibroblast growth factors (FGFs) in neuroinflammation associated with live B. burgdorferi exposure. FGFR specific siRNA and inhibitors, custom antibody arrays, ELISAs, immunofluorescence and microscopy were used to comprehensively analyze the roles of these molecules in microglial neuroinflammation due to B. burgdorferi. Results FGFR1-3 expressions were upregulated in microglia in response to B. burgdorferi. Inhibition of FGFR 1, 2 and 3 signaling using siRNA and three different inhibitors showed that FGFR signaling is proinflammatory in response to the Lyme disease bacterium. FGFR1 activation also contributed to non-viable B. burgdorferi mediated neuroinflammation. Analysis of the B. burgdorferi conditioned microglial medium by a custom antibody array showed that several FGFs are induced by the live bacterium including FGF6, FGF10 and FGF12, which in turn induce IL-6 and/or CXCL8, indicating a proinflammatory nature. To our knowledge, this is also the first-ever described role for FGF6 and FGF12 in CNS neuroinflammation. FGF23 upregulation, in addition, was observed in response to the Lyme disease bacterium. B. burgdorferi exposure also downregulated many FGFs including FGF 5, 7, 9, 11, 13, 16, 20 and 21. Some of the upregulated FGFs have been implicated in major depressive disorder (MDD) or dementia development, while the downregulated ones have been demonstrated to have protective roles in epilepsy, Parkinson’s disease, Alzheimer’s disease, spinal cord injury, blood–brain barrier stability, and others. Conclusions In this study we show that FGFRs and FGFs are novel inducers of inflammatory mediators in Lyme neuroborreliosis. It is likely that an unresolved, long-term (neuro)-Lyme infection can contribute to the development of other neurologic conditions in susceptible individuals either by augmenting pathogenic FGFs or by suppressing ameliorative FGFs or both.
... FRS2 interacts with FGFRs via its phosphotyrosine-binding (PTB) domain [20] and increased expression or activation of FRS2 is involved in tumorigenesis of several tumor entities [21][22][23][24][25]. Selective (AZD4547, NVP-BGJ398 and JNJ-42756493) and non-selective (dovitinib or ponatinib) FGFR inhibitors have been explored for cancer therapy [26,27]. However, resistance to FGFR inhibitors can evolve similarly to other receptor tyrosine kinase (RTK) inhibitors, either by the formation of gatekeeper mutations in the catalytic domain or the activation of bypass mechanisms [28,29]. Targeting the adaptor protein FRS2 instead would likely prevent the evolution of FGFR gatekeeper mutations and could possibly also be effective in gatekeeper mutant FGFR-driven tumors by blocking signaling downstream of the RTK [26]. ...
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... However, AZD4547 inhibits all members of FGFR and resistance has occurred in some lung cancer. [35][36] We decide to develop a library of FGFR degraders using AZD4547 as the binder and investigate the degradation activity and selectivity against members of FGFRs. The co-crystal structure (Fig. 1b) indicates that the piperazine group is exposed to the solvent and we hypothesize that we can attach a linker to the nitrogen atom of this group for the development of PROTACs. ...
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Proteolysis Targeting Chimera (PROTAC) has emerged as a novel therapeutic strategy. The major bottleneck for the development of PROTACs is the need to screen multiple parameters to create an effective degrader. It often involves the synthesis of dozens to hundreds of compounds one by one through a tedious process. We have developed a two-stage approach that allows for the rapid synthesis of PROTACs (Rapid-TAC) using preassembled building blocks to screen multiple parameters simultaneously. We herein report the application of this method to the development of PROTACs for FGFR, a challenging membrane protein target. In the first stage, we prepared 24 potential PROTACs quickly from a hydrazide-containing FGFR inhibitor and our previously reported VHL and CRBN ligand library bearing various linkers and an aldehyde functional group. These 24 PROTACs were then directly used for screening in cellular assay for protein degradation. Multiple hits were identified from the initial screening. We then prepared the corresponding stable analogues by replacing the hydrolytic labile acylhydrazone motif with an amide in the second stage. Among them, PROTAC LG1188 was identified as a potent and selective FGFR1 degrader.