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Kurppa, K. J.

Publications and source records attributed to Kurppa, K. J..

2 recordsLinked to original sources

Recurrent cancer-associated ERBB4 mutations are transforming and confer resistance to targeted therapies

Receptor tyrosine kinase ERBB4 (HER4) is frequently mutated in human cancer, and ERBB4 mutations have been identified in patients relapsing on targeted therapy. Here, we addressed the functional consequences of recurrent cancer-associated ERBB4 mutations that are located at regions important for dimer interactions and/or are paralogous to known oncogenic hotspot mutations in other ERBB genes. Eleven out of 18 analyzed mutations were transforming in cell models, thus suggesting oncogenic potential for more than half of the recurrent ERBB4 mutations. More detailed analyses of the most potent mutations, S303F, E452K and L798R, showed that they are activating, can co-operate with other ERBB receptors and are targetable with clinically available second-generation pan-ERBB inhibitors neratinib, afatinib and dacomitinib. Furthermore, the S303F mutation, together with a previously identified activating ERBB4 mutation, E715K, promoted resistance to third-generation EGFR inhibitor osimertinib in EGFR-mutant lung cancer model in vitro and in vivo. Together, these results are expected to facilitate clinical interpretation of the most recurrent cancer-associated ERBB4 mutations. The findings provide rationale for testing the efficacy of clinically used pan-ERBB inhibitors in patients harboring driver ERBB4 mutations both in the treatment-naive setting, and upon development of resistance to targeted agents.

cancer biology↗

Database of recurrent mutations (DORM), a web tool to browse recurrent mutations in cancers

Advances in sequencing technologies have facilitated the genetic characterization of large numbers of clinical cancer samples, leading to accumulation of extensive amounts of data. While potentially very useful for directing research and for clinical decision making, the increasing quantity of data generates challenges in its optimal management, and translation to informing clinical and research questions. Here, we present Database Of Recurrent Mutations (DORM), a database listing recurrent mutations (tissue-agnostic population frequency > 1) identified from cancer samples analyzed with whole genome or whole exome sequencing. The DORM database is a fast and feature-rich database supporting searching for several proteins, amino acid substitutions as well as queries using regular expressions.

bioinformatics↗