Kinase Inhibitors for Cancer

Mortlock, Andrew A.; Barker, Andy

doi:10.1016/b0-08-045044-x/00209-1

Cited by 2 publications

(2 citation statements)

References 402 publications

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“…Three hundred cells were seeded in 10% FBS medium, placed into 10-cm dishes, and allowed to attach overnight. The EGFR drugs (58), readily translatable therapeutic option in tumors overexpressing PRL-3. This is especially pertinent, given that no anti-PRL-3 agents have reached clinical trials, despite promising preclinical results (59,60).…”

Section: Discussionmentioning

confidence: 99%

Metastasis-associated PRL-3 induces EGFR activation and addiction in cancer cells

et al. 2013

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Metastasis-associated phosphatase of regenerating liver-3 (PRL-3) has pleiotropic effects in driving cancer progression, yet the signaling mechanisms of PRL-3 are still not fully understood. Here, we provide evidence for PRL-3-induced hyperactivation of EGFR and its downstream signaling cascades in multiple human cancer cell lines. Mechanistically, PRL-3-induced activation of EGFR was attributed primarily to transcriptional downregulation of protein tyrosine phosphatase 1B (PTP1B), an inhibitory phosphatase for EGFR. Functionally, PRL-3-induced hyperactivation of EGFR correlated with increased cell growth, promigratory characteristics, and tumorigenicity. Moreover, PRL-3 induced cellular addiction to EGFR signaling, as evidenced by the pronounced reversion of these oncogenic attributes upon EGFR-specific inhibition. Of clinical significance, we verified elevated PRL-3 expression as a predictive marker for favorable therapeutic response in a heterogeneous colorectal cancer (CRC) patient cohort treated with the clinically approved anti-EGFR antibody cetuximab. The identification of PRL-3-driven EGFR hyperactivation and consequential addiction to EGFR signaling opens new avenues for inhibiting PRL-3-driven cancer progression. We propose that elevated PRL-3 expression is an important clinical predictive biomarker for favorable anti-EGFR cancer therapy.

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Section: Discussionmentioning

confidence: 99%

Metastasis-associated PRL-3 induces EGFR activation and addiction in cancer cells

et al. 2013

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“…They also destabilize the inactive conformation of the enzyme, leading to a constitutively active state. Constitutive activity of these mutants is attributed to the enhanced van der Waals interactions between the phenylalanine of the DFG motif and the mutant gatekeeper residue. − The hydrogen bond network between the ATP-binding pocket and the adenine ring does not involve the gatekeeper residue side chain. Therefore, the gatekeeper residue mutations do not hinder the binding of ATP. − Instead, the adenine ring engages in a conserved hydrogen bonding network, involving the hinge region (backbone) of the enzyme (Figure ).…”

Section: Introductionmentioning

confidence: 99%

How Far Are We from the Rapid Prediction of Drug Resistance Arising Due to Kinase Mutations?

et al. 2021

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In all living organisms, protein kinases regulate various cell signaling events through phosphorylation. The phosphorylation occurs upon transferring an ATP’s terminal phosphate to a target residue. Because of the central role of protein kinases in several proliferative pathways, point mutations occurring within the kinase’s ATP-binding site can lead to a constitutively active enzyme, and ultimately, to cancer. A select set of these point mutations can also make the enzyme drug resistant toward the available kinase inhibitors. Because of technical and economical limitations, rapid experimental exploration of the impact of these mutations remains to be a challenge. This underscores the importance of kinase–ligand binding affinity prediction tools that are poised to measure the efficacy of inhibitors in the presence of kinase mutations. To this end, here, we compare the performances of six web-based scoring tools (DSX-ONLINE, KDEEP, HADDOCK2.2, PDBePISA, Pose&Rank, and PRODIGY-LIG) in assessing the impact of kinase mutations on their interactions with their inhibitors. This assessment is carried out on a new structure-based BINDKIN benchmark we compiled. BINDKIN contains wild-type and mutant structure pairs of kinase–inhibitor complexes, together with their corresponding experimental binding affinities (in the form of IC50, K d, and K i). The performance of various web servers over BINDKIN shows that they cannot predict the binding affinities (ΔGs) of wild-type and mutant cases directly. Still, they could catch whether a mutation improves or worsens the ligand binding (ΔΔGs) where the highest Pearson’s R correlation coefficient is reached by DSX-ONLINE over the K i dataset. When homology models are used instead of K i-associated crystal structures, DSX-ONLINE loses its predictive capacity. These results highlight that there is room to improve the available scoring functions to estimate the impact of protein kinase point mutations on inhibitor binding. The BINDKIN benchmark with all related results is freely accessible online ().

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Kinase Inhibitors for Cancer

Cited by 2 publications

References 402 publications

Metastasis-associated PRL-3 induces EGFR activation and addiction in cancer cells

Metastasis-associated PRL-3 induces EGFR activation and addiction in cancer cells

How Far Are We from the Rapid Prediction of Drug Resistance Arising Due to Kinase Mutations?

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