Predicting Drug Resistance Using Deep Mutational Scanning

Pines, Gur; Fankhauser, Reilly; Eckert, Carrie A.

doi:10.3390/molecules25092265

“…An extensive functional interpretation of variants will enable us to clarify the targeted inhibitors applicable for the corresponding mutations. Moreover, high throughput sequencing of circulating tumor DNA allows us to forecast the potential drug-resistance events [43][44][45][46]. This will dramatically promote the development of precision medicine.…”

Section: Discussionmentioning

confidence: 99%

Defining the Sensitivity Landscape of 74,389 <i>EGFR</i> Variants to Tyrosine Kinase Inhibitors

An

¹

,

Xu

²

,

Chen³

et al. 2022

SSRN Journal

0

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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, ge tinib, 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, ge tinib, 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 ve 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 ve commonly used TKIs. The approach used here should be applicable to other genes and targeted drugs. Signi cance StatementMutation-directed cancer precision medicine requires pre-interpretation of variants response on targeted drugs. For Asian lung adenocarcinoma patients, epidermal growth factor receptor (EGFR) is a commonly mutated gene with many rare mutations that lack drug response interpretations. We conducted a systematic cytotoxicity screening of EGFR mutations on ve tyrosine kinase inhibitors. We found that patients with rare EGFR mutations are most likely to bene t from osimertinib therapy compared to afatinib, erlotinib, ge tinib, or icotinib therapy. This study provides the rst case of deep mutational scanning that simultaneously assayed substitution, deletion, and insertion variants. This approach is applicable for other oncogenes and targeted drugs.

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“…An extensive functional interpretation of variants will enable us to clarify the targeted inhibitors applicable for the corresponding mutations. Moreover, high throughput sequencing of circulating tumor DNA allows us to forecast the potential drug-resistance events [43][44][45][46]. This will dramatically promote the development of precision medicine.…”

Section: Discussionmentioning

confidence: 99%

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

An

¹

,

Chen²,

Wu

³

et al. 2021

Preprint

0

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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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“…Predictions of the echinocandin susceptibility profile from sequence alone could help prescribe the most relevant echinocandin, increasing the chances of treatment success while helping to slow down the development of resistance. This approach has successfully been applied to the etiologic agents of malaria or tuberculosis (23,24), but has yet to be implemented in fungi. Our data and recent work on other antifungal drug targets (25,26) contribute to this collective effort.…”

Section: Disruption Of Bonds With Shared Features Of Echinocandins Le...mentioning

confidence: 99%

Mutational landscape and molecular bases of echinocandin resistance

Durand,

Torbey,

Giguere

et al. 2024

Preprint

1

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One of the front-line drug classes used to treat invasive fungal infections is echinocandins, which target the fungal-specific beta-glucan synthase (Fks). Treatment failure due to resistance often coincides with mutations in two protein regions known as hotspots. The biophysical bases by which such mutations confer resistance and cross-resistance among echinocandins are largely unknown. Here, we use deep-mutational scanning to quantify the resistance level of 660 mutations in the hotspots of two homologous Fks. We detail the constraints acting on drug binding and explain the resistance specificity for some mutations using the drug-protein interactions from our molecular models. Our findings will enable DNA sequence-based predictions of resistance to this important drug family and the improvement of future molecules that could overcome current resistance mutations.

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Predicting Drug Resistance Using Deep Mutational Scanning

Cited by 10 publications

References 99 publications

Defining the Sensitivity Landscape of 74,389 <i>EGFR</i> Variants to Tyrosine Kinase Inhibitors

Defining the Sensitivity Landscape of 74,389 <i>EGFR</i> Variants to Tyrosine Kinase Inhibitors

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

Mutational landscape and molecular bases of echinocandin resistance

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