Trans-activating mutations of the pseudokinase ERBB3.

Genetic changes in the ERBB family of receptor tyrosine kinases serve as oncogenic driver events and predictive biomarkers for ERBB inhibitor drugs. ERBB3 is a pseudokinase member of the family that, although lacking a fully active kinase domain, is well known for its potent signaling activity as a heterodimeric complex with ERBB2. Previous studies have identified few transforming ERBB3 mutations while the great majority of the hundreds of different somatic ERBB3 variants observed in different cancer types remain of unknown significance. Here, we describe an unbiased functional genetics screen of the transforming potential of thousands of ERBB3 mutations in parallel. The screen based on a previously described iSCREAM (in vitro screen of activating mutations) platform, and addressing ERBB3 pseudokinase signaling in a context of ERBB3/ERBB2 heterodimers, identified 18 hit mutations. Validation experiments in Ba/F3, NIH 3T3, and MCF10A cell backgrounds demonstrated the presence of both previously known and unknown transforming ERBB3 missense mutations functioning either as single variants or in cis as a pairwise combination. Drug sensitivity assays with trastuzumab, pertuzumab and neratinib indicated actionability of the transforming ERBB3 variants.

Cytolytic Properties and Genome Analysis of Rigvir® Oncolytic Virotherapy Virus and Other Echovirus 7 Isolates.

Rigvir® is a cell-adapted, oncolytic virotherapy enterovirus, which derives from an echovirus 7 (E7) isolate. While it is claimed that Rigvir® causes cytolytic infection in several cancer cell lines, there is little molecular evidence for its oncolytic and oncotropic potential. Previously, we genome-sequenced Rigvir® and five echovirus 7 isolates, and those sequences are further analyzed in this paper. A phylogenetic analysis of the full-length data suggested that Rigvir® was most distant from the other E7 isolates used in this study, placing Rigvir® in its own clade at the root of the phylogeny. Rigvir® contained nine unique mutations in the viral capsid proteins VP1-VP4 across the whole data set, with a structural analysis showing six of the mutations concerning residues with surface exposure on the cytoplasmic side of the viral capsid. One of these mutations, E/Q/N162G, was located in the region that forms the contact interface between decay-accelerating factor (DAF) and E7. Rigvir® and five other isolates were also subjected to cell infectivity assays performed on eight different cell lines. The used cell lines contained both cancer and non-cancer cell lines for observing Rigvir®'s claimed properties of being both oncolytic and oncotropic. Infectivity assays showed that Rigvir® had no discernable difference in the viruses' oncolytic effect when compared to the Wallace prototype or the four other E7 isolates. Rigvir® was also seen infecting non-cancer cell lines, bringing its claimed effect of being oncotropic into question. Thus, we conclude that Rigvir®'s claim of being an effective treatment against multiple different cancers is not warranted under the evidence presented here. Bioinformatic analyses do not reveal a clear mechanism that could elucidate Rigvir®'s function at a molecular level, and cell infectivity tests do not show a discernable difference in either the oncolytic or oncotropic effect between Rigvir® and other clinical E7 isolates used in the study.

Identification of Predictive ERBB Mutations by Leveraging Publicly Available Cell Line Databases.

Although targeted therapies can be effective for a subgroup of patients, identification of individuals who benefit from the treatments is challenging. At the same time, the predictive significance of the majority of the thousands of mutations observed in the cancer tissues remains unknown. Here, we describe the identification of novel predictive biomarkers for ERBB-targeted tyrosine kinase inhibitors (TKIs) by leveraging the genetic and drug screening data available in the public cell line databases: Cancer Cell Line Encyclopedia, Genomics of Drug Sensitivity in Cancer, and Cancer Therapeutics Response Portal. We assessed the potential of 412 ERBB mutations in 296 cell lines to predict responses to 10 different ERBB-targeted TKIs. Seventy-six ERBB mutations were identified that were associated with ERBB TKI sensitivity comparable with non-small cell lung cancer cell lines harboring the well-established predictive EGFR L858R mutation or exon 19 deletions. Fourteen (18.4%) of these mutations were classified as oncogenic by the cBioPortal database, whereas 62 (81.6%) were regarded as novel potentially predictive mutations. Of the nine functionally validated novel mutations, EGFR Y1069C and ERBB2 E936K were transforming in Ba/F3 cells and demonstrated enhanced signaling activity. Mechanistically, the EGFR Y1069C mutation disrupted the binding of the ubiquitin ligase c-CBL to EGFR, whereas the ERBB2 E936K mutation selectively enhanced the activity of ERBB heterodimers. These findings indicate that integrating data from publicly available cell line databases can be used to identify novel, predictive nonhotspot mutations, potentially expanding the patient population benefiting from existing cancer therapies.