An unbiased in vitro screen for activating epidermal growth factor receptor mutations

Chakroborty, Deepankar; Kurppa, Kari J.; Paatero, Ilkka; Ojala, Veera K.; Koivu, Marika K.A.; Tamirat, Mahlet Z.; Koivunen, Jussi; Johnson, Mark S.; Elo, Laura L.; Elenius, Klaus

doi:10.1074/jbc.ra118.006336

Cited by 23 publications

(32 citation statements)

References 48 publications

(50 reference statements)

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“…The method exploiting error-prone PCR to generate random mutations for an expression library, and a model of ERBB4 activity-dependent cellular growth was based on the iSCREAM (in vitro screen for activating mutations) approach ( 29). The iSCREAM method was previously successfully used to analyze somatic evolution of random EGFR mutants during clonal expansion of the IL3-dependent Ba/F3 cells (29). ERBB4 provided a clinically relevant candidate for the effort, as it is a member of the well-characterized ERBB oncogene family but with an ambiguous role as a drug target by its own right (73)(74)(75)(76), and as several recently approved pan-ERBB TKI drugs [afatinib, neratinib, dacomitinib (www.fda.gov), and poziotinib (77)] as well as other wide-spectrum RTK TKIs [such as ibrutinib (78,79)] also target ERBB4.…”

Section: Discussionmentioning

confidence: 99%

“…To screen for activating ERBB4 mutants in an unbiased manner, expression libraries of randomly mutated ERBB cDNAs were created. Random mutations were generated by error-prone PCR using full-length cDNAs encoding the wild-type human ERBB4 isoforms JM-a CYT-1 or JM-a CYT-2 as templates, as described in our previous work with EGFR (29). These two ERBB4 isoforms were selected for the experimentation as they represent the isoforms present in epithelial-derived cancer tissues (51)(52)(53).…”

Section: Generation Of Cdna Libraries For Expression Of Randomly Mutated Single-nucleotide Erbb4 Variantsmentioning

confidence: 99%

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An Unbiased Functional Genetics Screen Identifies Rare Activating ERBB4 Mutations

Chakroborty

Ojala

Knittle

et al. 2022

Cancer Research Communications

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Despite the relatively high frequency of somatic ERBB4 mutations in various cancer types, only a few activating ERBB4 mutations have been characterized, primarily due to lack of mutational hotspots in the ERBB4 gene. Here, we utilized our previously published pipeline, an in vitro screen for activating mutations, to perform an unbiased functional screen to identify potential activating ERBB4 mutations from a randomly mutated ERBB4 expression library. Ten potentially activating ERBB4 mutations were identified and subjected to validation by functional and structural analyses. Two of the 10 ERBB4 mutants, E715K and R687K, demonstrated hyperactivity in all tested cell models and promoted cellular growth under two-dimensional and three-dimensional culture conditions. ERBB4 E715K also promoted tumor growth in in vivo Ba/F3 cell mouse allografts. Importantly, all tested ERBB4 mutants were sensitive to the pan-ERBB tyrosine kinase inhibitors afatinib, neratinib, and dacomitinib. Our data indicate that rare ERBB4 mutations are potential candidates for ERBB4-targeted therapy with pan-ERBB inhibitors. Statement of Significance: ERBB4 is a member of the ERBB family of oncogenes that is frequently mutated in different cancer types but the functional impact of its somatic mutations remains unknown. Here, we have analyzed the function of over 8,000 randomly mutated ERBB4 variants in an unbiased functional genetics screen. The data indicate the presence of rare activating ERBB4 mutations in cancer, with potential to be targeted with clinically approved pan-ERBB inhibitors.

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Section: Discussionmentioning

confidence: 99%

Section: Generation Of Cdna Libraries For Expression Of Randomly Mutated Single-nucleotide Erbb4 Variantsmentioning

confidence: 99%

An Unbiased Functional Genetics Screen Identifies Rare Activating ERBB4 Mutations

Chakroborty

Ojala

Knittle

et al. 2022

Cancer Research Communications

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“…Indeed, therapeutic targeting of ALK in other tumors such as non-small cell lung cancer (NSCLC), in which it is activated in an oncogenic fusion protein ( 7 ), has been successful. However, as shown for EGFR in NSCLC ( 8 – 10 ) and for ALK in earlier studies in NB, TKD mutations vary in the degree to which they activate the kinase—leading to oncogenesis—and in their effects on sensitivity to inhibition with small molecule inhibitors ( 5 , 11 , 12 ).…”

mentioning

confidence: 88%

“…We previously identified ALK mutations or amplifications in 14% of 1,600 patients with NB ( 11 ). Three hot spots in the ALK TKD (positions 1174, 1245, and 1275) account for 85% of kinase mutations, although mutations at numerous other sites have also been reported ( 10 , 11 , 13 ). These include clearly activating mutations, silent mutations (i.e., those shown not to be activating), and mutations that confer resistance to known ALK kinase inhibitors.…”

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confidence: 99%

Computational studies of anaplastic lymphoma kinase mutations reveal common mechanisms of oncogenic activation

Patil

Jordan

Park

et al. 2021

Proc. Natl. Acad. Sci. U.S.A.

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Kinases play important roles in diverse cellular processes, including signaling, differentiation, proliferation, and metabolism. They are frequently mutated in cancer and are the targets of a large number of specific inhibitors. Surveys of cancer genome atlases reveal that kinase domains, which consist of 300 amino acids, can harbor numerous (150 to 200) single-point mutations across different patients in the same disease. This preponderance of mutations—some activating, some silent—in a known target protein make clinical decisions for enrolling patients in drug trials challenging since the relevance of the target and its drug sensitivity often depend on the mutational status in a given patient. We show through computational studies using molecular dynamics (MD) as well as enhanced sampling simulations that the experimentally determined activation status of a mutated kinase can be predicted effectively by identifying a hydrogen bonding fingerprint in the activation loop and the αC-helix regions, despite the fact that mutations in cancer patients occur throughout the kinase domain. In our study, we find that the predictive power of MD is superior to a purely data-driven machine learning model involving biochemical features that we implemented, even though MD utilized far fewer features (in fact, just one) in an unsupervised setting. Moreover, the MD results provide key insights into convergent mechanisms of activation, primarily involving differential stabilization of a hydrogen bond network that engages residues of the activation loop and αC-helix in the active-like conformation (in >70% of the mutations studied, regardless of the location of the mutation).

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“…The process of the MANO method is labor intensive, which makes it challenging to evaluate the functions of variants on a large scale, for example, for several thousands of variants. Another group reported screening for activating EGFR mutations using a library of 7,216 randomly mutated single-nucleotide variants [8]. This variant library was generated by the error-prone PCR method, which can barely cover all the interested variants.…”

Section: Introductionmentioning

confidence: 99%

Defining the Sensitivity Landscape of 74,389 EGFR Variants to Tyrosine Kinase Inhibitors

Chen²,

et al. 2021

Preprint

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Background: Tyrosine kinase inhibitors (TKIs) therapy is a standard treatment for patients with advanced non-small-cell lung carcinoma (NSCLC) when activating epidermal growth factor receptor (EGFR) mutations are detected. However, except for the well-studied EGFR mutations, most EGFR mutations lack treatment regimens. Methods: We constructed two EGFR variant libraries containing substitutions, deletions, or insertions using the saturation mutagenesis method. All the variants were located in the EGFR mutation hotspot (exons 18-21). The sensitivity of these variants to afatinib, erlotinib, gefitinib, icotinib, and osimertinib was systematically studied by determining their enrichment in massively parallel cytotoxicity assays using an endogenous EGFR-depleted cell line, PC9. Results: A total of 3,914 and 70,475 variants were detected in the constructed EGFR Substitution-Deletion (Sub-Del) and exon 20 Insertion (Ins) libraries, accounting for 99.3% and 55.8% of the designed variants, respectively. Of the 3,914 Sub-Del variants, 813 were highly enriched in the reversible TKI (erlotinib, gefitinib, icotinib) cytotoxicity assays and 51 were enriched in the irreversible TKI (afatinib, osimertinib) cytotoxicity assays. For the 70,475 Ins variants, insertions at amino acid positions 770-774 were highly enriched in all the five TKI cytotoxicity assays. Moreover, the top 5% of the enriched insertion variants included a glycine or serine insertion at high frequency. Conclusions: We present a comprehensive reference for the sensitivity of EGFR variants to five commonly used TKIs. The approach used here should be applicable to other genes and targeted drugs.

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An unbiased in vitro screen for activating epidermal growth factor receptor mutations

Cited by 23 publications

References 48 publications

An Unbiased Functional Genetics Screen Identifies Rare Activating ERBB4 Mutations

An Unbiased Functional Genetics Screen Identifies Rare Activating ERBB4 Mutations

Computational studies of anaplastic lymphoma kinase mutations reveal common mechanisms of oncogenic activation

Defining the Sensitivity Landscape of 74,389 EGFR Variants to Tyrosine Kinase Inhibitors

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