Biochemical and structural basis for differential inhibitor sensitivity of EGFR with distinct exon 19 mutations

Rosenburgh, Iris van Alderwerelt van K.; Lu, David; Grant, Michael J.; Stayrook, Steven E.; Phadke, Manali; Walther, Zenta; Goldberg, Sarah B.; Politi, Katerina; Lemmon, Mark A.; Ashtekar, Kumar Dilip; Tsutsui, Yuko

doi:10.1038/s41467-022-34398-z

Cited by 16 publications

(11 citation statements)

References 83 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Agilent site-directed mutagenesis was used to introduce the V924R mutation into JM-TKD and the I682Q mutation into TKD (using numbering for mature protein). Protein expression employed the Bac-to-Bac system (Invitrogen) exactly as previously described 75 , using a Ni-NTA column followed by anion exchange chromatography and gel filtration. Extinction coefficients for both JM-V924R-TKD and I682Q-TKD were determined to be 52,370 M -1 cm -1 using the ExPASy ProtParam Tool 76 .…”

Section: Fret-flim Imagingmentioning

confidence: 99%

Distinct interactions stabilize EGFR dimers and higher-order oligomers in cell membranes

Mudumbi

Burns

Schodt

et al. 2023

Preprint

Self Cite

View full text Add to dashboard Cite

The epidermal growth factor receptor (EGFR) is a receptor tyrosine kinase (RTK) with important roles in many cellular processes as well as cancer and other diseases. EGF binding promotes EGFR dimerization and autophosphorylation through interactions that are well understood structurally. However, it is not clear how these dimers relate to higher-order EGFR oligomers detected at the cell surface. We used single-particle tracking (SPT) and Forster resonance energy transfer (FRET) imaging to examine how each domain within EGFR contributes to receptor dimerization and the rate of its diffusion in the cell membrane. We show that the EGFR extracellular region is sufficient to drive receptor dimerization, but that the EGF-induced EGFR slow-down seen by SPT requires formation of higher order oligomers, mediated in part by the intracellular tyrosine kinase domain - but only when in its active conformation. Our data thus provide important insight into higher-order EGFR interactions required for EGF signaling.

show abstract

Section: Fret-flim Imagingmentioning

confidence: 99%

Distinct interactions stabilize EGFR dimers and higher-order oligomers in cell membranes

Mudumbi

Burns

Schodt

et al. 2023

Preprint

Self Cite

View full text Add to dashboard Cite

show abstract

“…The ι1uptake of all peptides was normalized to the highest ι1uptake value, which is defined as the stability index = 1. The stability index of different regions is mapped as described previously 43 . Briefly, the stability index of a region is assigned using the index of the shortest peptide in a given region.…”

Section: Methodsmentioning

confidence: 99%

Physical basis for the interaction betweenDrosophilaROS1 and the GPCR BOSS

Zhang,

Tsutsui,

et al. 2024

Preprint

Self Cite

View full text Add to dashboard Cite

Drosophila ROS1 (dROS1, Sevenless) is a receptor tyrosine kinase (RTK) essential for the differentiation of Drosophila R7 photoreceptor cells. Activation of dROS1 is mediated by binding to the extracellular region (ECR) of the GPCR (G protein coupled receptor) BOSS (Bride Of Sevenless) on adjacent cells. Genetic evidence together with in vitro activity assays confirmed the activation of dROS1 by BOSS and identified subsequent downstream signaling pathways including SOS (Son of Sevenless). However, the physical basis for how dROS1 interacts with the GPCR BOSS has long remained unknown. Here we provide the first structure, using Cryo-Electron Microscopy (CryoEM), of dROS1's extracellular region, which mediates ligand binding. We show that the N-terminal region of dROS1 adopts a folded-over conformation harboring a novel structural domain. We further narrowed down the interacting binding epitopes on both dROS1 and BOSS. This includes a beta-strand in dROS1's third Fibronectin type III (FNIII) domain and the C-terminal portion of BOSS' ECR. Our mutagenesis studies, coupled with AlphaFold complex predictions, support a binding interaction mediated by a hydrophobic interaction and beta-strand augmentation between these regions. Our findings provide a fundamental understanding of the regulatory function of dROS1 and further provide mechanistic insight into the human ortholog and oncogene ROS1.

show abstract

“…Similarly, in thyroid carcinoma, we observed an interaction between ERBB3, a member of the epidermal growth factor receptor (EGFR) family of receptor tyrosine kinases, and four inhibitors (sapitinib, poziotinib, gefitinib, and dacomitinib). These inhibitors, all classified as tyrosine kinase inhibitors [72][73][74][75][76][77][78][79], align with ERBB3's predicted role as an OCG. Another example is the interaction between EpCAM and solitomab in lung adenocarcinoma.…”

Section: Predicted Driver Genes Have Therapeutic Potential As Drug Ta...mentioning

confidence: 99%

Revealing cancer driver genes through integrative transcriptomic and epigenomic analyses with Moonlight

Nourbakhsh,

Zheng,

Noor

et al. 2024

Preprint

View full text Add to dashboard Cite

Cancer involves dynamic changes caused by (epi)genetic alterations such as mutations or abnormal DNA methylation patterns which occur in cancer driver genes. These driver genes are divided into oncogenes and tumor suppressors depending on their function and mechanism of action. Discovering driver genes in different cancer (sub)types is important not only for increasing current understanding of carcinogenesis but also from prognostic and therapeutic perspectives. We have previously developed a framework called Moonlight which uses a systems biology multi-omics approach for prediction of driver genes. Here, we present further updates to Moonlight by incorporating a DNA methylation layer which provides epigenetic evidence for deregulated expression profiles of driver genes. To this end, we present a novel functionality called Gene Methylation Analysis (GMA) which investigates abnormal DNA methylation patterns to predict driver genes. This is achieved by integrating the tool EpiMix which is designed to detect such aberrant DNA methylation patterns in a cohort of patients and further couples these patterns with changes in gene expression. To showcase GMA, we applied it to three cancer (sub)types (basal-like breast cancer, lung adenocarcinoma, and thyroid carcinoma) where we discovered 33, 190, and 263 epigenetically driven genes, respectively. A subset of these driver genes had prognostic effects with expression levels significantly affecting survival of the patients. Moreover, a subset of the driver genes demonstrated therapeutic potential as drug targets. This study provides a framework for exploring the driving forces behind cancer and provides novel insights into the landscape of three cancer sub(types) by integrating gene expression and methylation data. Moonlight2R is available on GitHub (https://github.com/ELELAB/Moonlight2R) and BioCondcutor (https://bioconductor.org/packages/release/bioc/html/Moonlight2R.html) and the associated case studies presented in this study are available on GitHub (https://github.com/ELELAB/Moonlight2_GMA_case_studies) and OSF (https://osf.io/j4n8q/).

show abstract

Biochemical and structural basis for differential inhibitor sensitivity of EGFR with distinct exon 19 mutations

Cited by 16 publications

References 83 publications

Distinct interactions stabilize EGFR dimers and higher-order oligomers in cell membranes

Distinct interactions stabilize EGFR dimers and higher-order oligomers in cell membranes

Physical basis for the interaction betweenDrosophilaROS1 and the GPCR BOSS

Revealing cancer driver genes through integrative transcriptomic and epigenomic analyses with Moonlight

Contact Info

Product

Resources

About