Abstract 153: An unbiased in vitro screen for activating ERBB4 mutations
Abstract Introduction: Cancer tissues harbor thousands of mutations, and a given oncogene may be mutated at hundreds of sites across different samples. The discovery of most of the currently known driver mutations has been facilitated by their accumulation in mutation hotspots within their respectiv...
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Published in | Cancer research (Chicago, Ill.) Vol. 82; no. 12_Supplement; p. 153 |
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Main Authors | , , , , |
Format | Journal Article |
Language | English |
Published |
15.06.2022
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Online Access | Get full text |
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Abstract | Abstract
Introduction: Cancer tissues harbor thousands of mutations, and a given oncogene may be mutated at hundreds of sites across different samples. The discovery of most of the currently known driver mutations has been facilitated by their accumulation in mutation hotspots within their respective genes. However, a vast majority of mutations in cancer tissues are rare and their functional significance remains unknown. Several lines of in vitro and clinical evidence also indicate that there is a significant number of, as yet unidentified, activating driver mutations which could serve as predictive markers in oncology. Here, we performed an unbiased functional screen to identify potential activating mutations of ERBB4, a frequently mutated member of the epidermal growth factor receptor family.
Method: To identify functional driver mutations of ERBB4, the previously published pipeline, in vitro screen for activating mutations (iSCREAM) [1], was utilized. iSCREAM is a functional genetics screen based on the expression of random cDNA variants and the ability of driver mutations to promote cellular growth in vitro. The expression library encoding randomly mutated ERBB4 variants was retrovirally introduced into murine lymphoid Ba/F3 cells, that normally require interleukin-3 (IL-3) for survival but can exploit ectopic expression of activated variants of oncogenic kinases to compensate for the deficiency of exogenous IL-3. When expressed under an appropriate promoter, the wild-type ERBB4 receptor failed to promote IL-3-independent survival in the presence of the neuregulin-1 ligand, while the cells expressing activating mutations readily proliferated. The identity and frequency of the activating ERBB4 mutations were subsequently determined from the proliferating cell pool using targeted next-generation sequencing.
Results: Ten candidate activating mutations were identified out of the over 7000 random ERBB4 missense or nonsense mutations present in the original library. The candidate activating mutations were individually characterized using functional assays both in vitro and in vivo, as well as by structural analyses. The activating mutation were sensitive to clinically used pan-ERBB tyrosine kinase inhibitors afatinib, dacomitinib and neratinib.
Conclusions: A subset of ERBB4 missense mutations are activating and sensitive to tyrosine kinase inhibitor drugs.
Citation Format: Deepankar Chakroborty, Veera K. Ojala, Anna M. Knittle, Kari J. Kurppa, Klaus Elenius. An unbiased in vitro screen for activating ERBB4 mutations [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 153. |
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AbstractList | Abstract
Introduction: Cancer tissues harbor thousands of mutations, and a given oncogene may be mutated at hundreds of sites across different samples. The discovery of most of the currently known driver mutations has been facilitated by their accumulation in mutation hotspots within their respective genes. However, a vast majority of mutations in cancer tissues are rare and their functional significance remains unknown. Several lines of in vitro and clinical evidence also indicate that there is a significant number of, as yet unidentified, activating driver mutations which could serve as predictive markers in oncology. Here, we performed an unbiased functional screen to identify potential activating mutations of ERBB4, a frequently mutated member of the epidermal growth factor receptor family.
Method: To identify functional driver mutations of ERBB4, the previously published pipeline, in vitro screen for activating mutations (iSCREAM) [1], was utilized. iSCREAM is a functional genetics screen based on the expression of random cDNA variants and the ability of driver mutations to promote cellular growth in vitro. The expression library encoding randomly mutated ERBB4 variants was retrovirally introduced into murine lymphoid Ba/F3 cells, that normally require interleukin-3 (IL-3) for survival but can exploit ectopic expression of activated variants of oncogenic kinases to compensate for the deficiency of exogenous IL-3. When expressed under an appropriate promoter, the wild-type ERBB4 receptor failed to promote IL-3-independent survival in the presence of the neuregulin-1 ligand, while the cells expressing activating mutations readily proliferated. The identity and frequency of the activating ERBB4 mutations were subsequently determined from the proliferating cell pool using targeted next-generation sequencing.
Results: Ten candidate activating mutations were identified out of the over 7000 random ERBB4 missense or nonsense mutations present in the original library. The candidate activating mutations were individually characterized using functional assays both in vitro and in vivo, as well as by structural analyses. The activating mutation were sensitive to clinically used pan-ERBB tyrosine kinase inhibitors afatinib, dacomitinib and neratinib.
Conclusions: A subset of ERBB4 missense mutations are activating and sensitive to tyrosine kinase inhibitor drugs.
Citation Format: Deepankar Chakroborty, Veera K. Ojala, Anna M. Knittle, Kari J. Kurppa, Klaus Elenius. An unbiased in vitro screen for activating ERBB4 mutations [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 153. |
Author | Ojala, Veera K. Elenius, Klaus Knittle, Anna M. Kurppa, Kari J. Chakroborty, Deepankar |
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