Katie M. Campbell

DGIdb 2.0: mining clinically relevant drug–gene interactions

The Drug–Gene Interaction Database (DGIdb, www.dgidb.org) is a web resource that consolidates disparate data sources describing drug–gene interactions and gene druggability. It provides an intuitive graphical user interface and a documented application programming interface (API) for querying these data. DGIdb was assembled through an extensive manual curation effort, reflecting the combined information of twenty-seven sources. For DGIdb 2.0, substantial updates have been made to increase content and improve its usefulness as a resource for mining clinically actionable drug targets. Specifically, nine new sources of drug–gene interactions have been added, including seven resources specifically focused on interactions linked to clinical trials. These additions have more than doubled the overall count of drug–gene interactions. The total number of druggable gene claims has also increased by 30%. Importantly, a majority of the unrestricted, publicly-accessible sources used in DGIdb are now automatically updated on a weekly basis, providing the most current information for these sources. Finally, a new web view and API have been developed to allow searching for interactions by drug identifiers to complement existing gene-based search functionality. With these updates, DGIdb represents a comprehensive and user friendly tool for mining the druggable genome for precision medicine hypothesis generation.

CIViC is a community knowledgebase for expert crowdsourcing the clinical interpretation of variants in cancer

CIViC is an expert-crowdsourced knowledgebase for Clinical Interpretation of Variants in Cancer describing the therapeutic, prognostic, diagnostic and predisposing relevance of inherited and somatic variants of all types. CIViC is committed to open-source code, open-access content, public application programming interfaces (APIs) and provenance of supporting evidence to allow for the transparent creation of current and accurate variant interpretations for use in cancer precision medicine.

GenVisR: Genomic Visualizations in R

Summary: Visualizing and summarizing data from genomic studies continues to be a challenge. Here, we introduce the GenVisR package to addresses this challenge by providing highly customizable, publication-quality graphics focused on cohort level genome analyses. GenVisR provides a rapid and easy-to-use suite of genomic visualization tools, while maintaining a high degree of flexibility by leveraging the abilities of ggplot2 and Bioconductor. Availability and Implementation: GenVisR is an R package available via Bioconductor (https://bioconductor.org/packages/GenVisR) under GPLv3. Support is available via GitHub (https://github.com/griffithlab/GenVisR/issues) and the Bioconductor support website. Contacts: obigriffith@wustl.edu or mgriffit@wustl.edu Supplementary information: Supplementary data are available at Bioinformatics online.

Melorheostosis: Exome sequencing of an associated dermatosis implicates postzygotic mosaicism of mutated KRAS☆☆☆

Melorheostosis (MEL) is the rare sporadic dysostosis characterized by monostotic or polyostotic osteosclerosis and hyperostosis often distributed in a sclerotomal pattern. The prevailing hypothesis for MEL invokes postzygotic mosaicism. Sometimes scleroderma-like skin changes, considered a representation of the pathogenetic process of MEL, overlie the bony changes, and sometimes MEL becomes malignant. Osteopoikilosis (OPK) is the autosomal dominant skeletal dysplasia that features symmetrically distributed punctate osteosclerosis due to heterozygous loss-of-function mutation within LEMD3. Rarely, radiographic findings of MEL occur in OPK. However, germline mutation of LEMD3 does not explain sporadic MEL. To explore if mosaicism underlies MEL, we studied a boy with polyostotic MEL and characteristic overlying scleroderma-like skin, a few bony lesions consistent with OPK, and a large epidermal nevus known to usually harbor a HRAS, FGFR3, or PIK3CA gene mutation. Exome sequencing was performed to ~100× average read depth for his two dermatoses, two areas of normal skin, and peripheral blood leukocytes. As expected for non-malignant tissues, the patients mutation burden in his normal skin and leukocytes was low. He, his mother, and his maternal grandfather carried a heterozygous, germline, in-frame, 24-base-pair deletion in LEMD3. Radiographs of the patient and his mother revealed bony foci consistent with OPK, but she showed no MEL. For the patient, somatic variant analysis, using four algorithms to compare all 20 possible pairwise combinations of his five DNA samples, identified only one high-confidence mutation, heterozygous KRAS Q61H (NM_033360.3:c.183A>C, NP_203524.1:p.Gln61His), in both his dermatoses but absent in his normal skin and blood. Thus, sparing our patient biopsy of his MEL bone, we identified a heterozygous somatic KRAS mutation in his scleroderma-like dermatosis considered a surrogate for MEL. This implicates postzygotic mosaicism of mutated KRAS, perhaps facilitated by germline LEMD3 haploinsufficiency, causing his MEL.

CIViC: A knowledgebase for expert-crowdsourcing the clinical interpretation of variants in cancer.

CIViC is an expert crowdsourced knowledgebase for Clinical Interpretation of Variants in Cancer (www.civicdb.org) describing the therapeutic, prognostic, and diagnostic relevance of inherited and somatic variants of all types. CIViC is committed to open source code, open access content, public application programming interfaces (APIs), and provenance of supporting evidence to allow for the transparent creation of current and accurate variant interpretations for use in cancer precision medicine.

Standard operating procedure for somatic variant refinement of tumor sequencing data

Purpose: Manual review of aligned sequencing reads is required to develop a high-quality list of somatic variants from massively parallel sequencing data (MPS). Despite widespread use in analyzing MPS data, there has been little attempt to describe methods for manual review, resulting in high inter- and intra-lab variability in somatic variant detection and characterization of tumors. Methods: Open source software was used to develop an optimal method for manual review setup. We also developed a systemic approach to visually inspect each variant during manual review. Results: We present a standard operating procedures for somatic variant refinement for use by manual reviewers. The approach is enhanced through representative examples of 4 different manual review categories that indicate a reviewer’s confidence in the somatic variant call and 19 annotation tags that contextualize commonly observed sequencing patterns during manual review. Representative examples provide detailed instructions on how to classify variants during manual review to rectify lack of confidence in automated somatic variant detection. Conclusion: Standardization of somatic variant refinement through systematization of manual review will improve the consistency and reproducibility of identifying true somatic variants after automated variant calling.

The prognostic effects of somatic mutations in ER-positive breast cancer

Here we report targeted sequencing of 83 genes using DNA from primary breast cancer samples from 625 postmenopausal (UBC-TAM series) and 328 premenopausal (MA12 trial) hormone receptor-positive (HR+) patients to determine interactions between somatic mutation and prognosis. Independent validation of prognostic interactions was achieved using data from the METABRIC study. Previously established associations between MAP3K1 and PIK3CA mutations with luminal A status/favorable prognosis and TP53 mutations with Luminal B/non-luminal tumors/poor prognosis were observed, validating the methodological approach. In UBC-TAM, NF1 frame-shift nonsense (FS/NS) mutations were also a poor outcome driver that was validated in METABRIC. For MA12, poor outcome associated with PIK3R1 mutation was also reproducible. DDR1 mutations were strongly associated with poor prognosis in UBC-TAM despite stringent false discovery correction (q = 0.0003). In conclusion, uncommon recurrent somatic mutations should be further explored to create a more complete explanation of the highly variable outcomes that typifies ER+ breast cancer.Unravelling the link between somatic mutation and prognosis in estrogen positive (ER+) breast cancer requires the use of long-term follow-up data. Here, combining archival formalin-fixed paraffin embedded tissue and targeted sequencing in three cohorts of ER+ breast cancer, the authors find associations with clinical outcome for NF1 frame-shift nonsense mutations, PIK3R1 mutation, and DDR1 mutations.

Spontaneous aggressive ERα+ mammary tumor model is driven by Kras activation

The NRL-PRL murine model, defined by mammary-selective transgenic rat prolactin ligand rPrl expression, establishes spontaneous ER+ mammary tumors, mimicking the association between elevated prolactin (PRL) and risk for development of ER+ breast cancer in postmenopausal women. Whole genome and exome sequencing in a discovery cohort (n=5) of end stage tumors revealed canonical activating mutations and copy number amplifications of Kras. The frequent mutations in this pathway were validated in an extension cohort, identifying activating Ras alterations in 79% (23/29) of tumors. Transcriptome analyses over the course of oncogenesis revealed marked alterations associated with Ras activity in established tumors, compared to preneoplastic tissues, in cell-intrinsic processes associated with mitosis, cell adhesion and invasion, as well as in the tumor microenvironment, including immune activity. These genomic analyses suggest that PRL induces a selective bottleneck for spontaneous Ras-driven tumors which may model a subset of aggressive clinical ER+ breast cancers.

Standard operating procedure for somatic variant refinement of sequencing data with paired tumor and normal samples

PurposeFollowing automated variant calling, manual review of aligned read sequences is required to identify a high-quality list of somatic variants. Despite widespread use in analyzing sequence data, methods to standardize manual review have not been described, resulting in high inter- and intralab variability.MethodsThis manual review standard operating procedure (SOP) consists of methods to annotate variants with four different calls and 19 tags. The calls indicate a reviewer’s confidence in each variant and the tags indicate commonly observed sequencing patterns and artifacts that inform the manual review call. Four individuals were asked to classify variants prior to, and after, reading the SOP and accuracy was assessed by comparing reviewer calls with orthogonal validation sequencing.ResultsAfter reading the SOP, average accuracy in somatic variant identification increased by 16.7% (p value = 0.0298) and average interreviewer agreement increased by 12.7% (p value < 0.001). Manual review conducted after reading the SOP did not significantly increase reviewer time.ConclusionThis SOP supports and enhances manual somatic variant detection by improving reviewer accuracy while reducing the interreviewer variability for variant calling and annotation.

Oral Cavity Squamous Cell Carcinoma Xenografts Retain Complex Genotypes and Intertumor Molecular Heterogeneity

SUMMARY Herein, we report an oral cavity squamous cell carcinoma (OCSCC) patient-derived xenograft (PDX) platform, with genomic annotation useful for co-clinical trial and mechanistic studies. Genomic analysis included whole-exome sequencing (WES) and transcriptome sequencing (RNA-seq) on 16 tumors and matched PDXs and additional whole-genome sequencing (WGS) on 9 of these pairs as a representative subset of a larger OCSCC PDX repository (n = 63). In 12 models with high purity, more than 90% of variants detected in the tumor were retained in the matched PDX. The genomic landscape across these PDXs reflected OCSCC molecular heterogeneity, including previously described basal, mesenchymal, and classical molecular subtypes. To demonstrate the integration of PDXs into a clinical trial framework, we show that pharmacological intervention in PDXs parallels clinical response and extends patient data. Together, these data describe a repository of OCSCC-specific PDXs and illustrate conservation of primary tumor genotypes, intratumoral heterogeneity, and co-clinical trial application.