CIViCdb 2022: evolution of an open-access cancer variant interpretation knowledgebase.

CIViC (Clinical Interpretation of Variants in Cancer; civicdb.org) is a crowd-sourced, public domain knowledgebase composed of literature-derived evidence characterizing the clinical utility of cancer variants. As clinical sequencing becomes more prevalent in cancer management, the need for cancer variant interpretation has grown beyond the capability of any single institution. CIViC contains peer-reviewed, published literature curated and expertly-moderated into structured data units (Evidence Items) that can be accessed globally and in real time, reducing barriers to clinical variant knowledge sharing. We have extended CIViC's functionality to support emergent variant interpretation guidelines, increase interoperability with other variant resources, and promote widespread dissemination of structured curated data. To support the full breadth of variant interpretation from basic to translational, including integration of somatic and germline variant knowledge and inference of drug response, we have enabled curation of three new Evidence Types (Predisposing, Oncogenic and Functional). The growing CIViC knowledgebase has over 300 contributors and distributes clinically-relevant cancer variant data currently representing >3200 variants in >470 genes from >3100 publications.

A diagnostic challenge of KIT p.V559D and BRAF p.G469A mutations in a paragastric mass.

A patient with gastrointestinal stroma tumor (GIST) and KIT p.V559D and BRAF p.G469A alterations was referred to our institutional molecular tumor board (MTB) to discuss therapeutic implications. The patient had been diagnosed with B-cell chronic lymphocytic leukemia (CLL) years prior to the MTB presentation. GIST had been diagnosed 1 month earlier. After structured clinical annotation of the molecular alterations and interdisciplinary discussion, we considered BRAF/KIT co-mutation unlikely in a treatment-naïve GIST. Discordant variant allele frequencies furthermore suggested a second malignancy. NGS of a CLL sample revealed the identical class 2 BRAF alteration, thus supporting admixture of CLL cells in the paragastric mass, leading to the detection of 2 alterations. Following the MTB recommendation, the patient received imatinib and had a radiographic response. Structured annotation and interdisciplinary discussion in specialized tumor boards facilitate the clinical management of complex molecular findings. Coexisting malignancies and clonal hematopoiesis warrant consideration in case of complex and uncommon molecular findings.

Feasibility and outcome of reproducible clinical interpretation of high-dimensional molecular data: a comparison of two molecular tumor boards.

BACKGROUND: Structured and harmonized implementation of molecular tumor boards (MTB) for the clinical interpretation of molecular data presents a current challenge for precision oncology. Heterogeneity in the interpretation of molecular data was shown for patients even with a limited number of molecular alterations. Integration of high-dimensional molecular data, including RNA- (RNA-Seq) and whole-exome sequencing (WES), is expected to further complicate clinical application. To analyze challenges for MTB harmonization based on complex molecular datasets, we retrospectively compared clinical interpretation of WES and RNA-Seq data by two independent molecular tumor boards. METHODS: High-dimensional molecular cancer profiling including WES and RNA-Seq was performed for patients with advanced solid tumors, no available standard therapy, ECOG performance status of 0-1, and available fresh-frozen tissue within the DKTK-MASTER Program from 2016 to 2018. Identical molecular profiling data of 40 patients were independently discussed by two molecular tumor boards (MTB) after prior annotation by specialized physicians, following independent, but similar workflows. Identified biomarkers and resulting treatment options were compared between the MTBs and patients were followed up clinically. RESULTS: A median of 309 molecular aberrations from WES and RNA-Seq (n = 38) and 82 molecular aberrations from WES only (n = 3) were considered for clinical interpretation for 40 patients (one patient sequenced twice). A median of 3 and 2 targeted treatment options were identified per patient, respectively. Most treatment options were identified for receptor tyrosine kinase, PARP, and mTOR inhibitors, as well as immunotherapy. The mean overlap coefficient between both MTB was 66%. Highest agreement rates were observed with the interpretation of single nucleotide variants, clinical evidence levels 1 and 2, and monotherapy whereas the interpretation of gene expression changes, preclinical evidence levels 3 and 4, and combination therapy yielded lower agreement rates. Patients receiving treatment following concordant MTB recommendations had significantly longer overall survival than patients receiving treatment following discrepant recommendations or physician's choice. CONCLUSIONS: Reproducible clinical interpretation of high-dimensional molecular data is feasible and agreement rates are encouraging, when compared to previous reports. The interpretation of molecular aberrations beyond single nucleotide variants and preclinically validated biomarkers as well as combination therapies were identified as additional difficulties for ongoing harmonization efforts.

Standards for the classification of pathogenicity of somatic variants in cancer (oncogenicity): Joint recommendations of Clinical Genome Resource (ClinGen), Cancer Genomics Consortium (CGC), and Variant Interpretation for Cancer Consortium (VICC).

PURPOSE: Several professional societies have published guidelines for the clinical interpretation of somatic variants, which specifically address diagnostic, prognostic, and therapeutic implications. Although these guidelines for the clinical interpretation of variants include data types that may be used to determine the oncogenicity of a variant (eg, population frequency, functional, and in silico data or somatic frequency), they do not provide a direct, systematic, and comprehensive set of standards and rules to classify the oncogenicity of a somatic variant. This insufficient guidance leads to inconsistent classification of rare somatic variants in cancer, generates variability in their clinical interpretation, and, importantly, affects patient care. Therefore, it is essential to address this unmet need. METHODS: Clinical Genome Resource (ClinGen) Somatic Cancer Clinical Domain Working Group and ClinGen Germline/Somatic Variant Subcommittee, the Cancer Genomics Consortium, and the Variant Interpretation for Cancer Consortium used a consensus approach to develop a standard operating procedure (SOP) for the classification of oncogenicity of somatic variants. RESULTS: This comprehensive SOP has been developed to improve consistency in somatic variant classification and has been validated on 94 somatic variants in 10 common cancer-related genes. CONCLUSION: The comprehensive SOP is now available for classification of oncogenicity of somatic variants.

Distinct immune evasion in APOBEC-enriched, HPV-negative HNSCC.

Immune checkpoint inhibition leads to response in some patients with head and neck squamous cell carcinoma (HNSCC). Robust biomarkers are lacking to date. We analyzed viral status, gene expression signatures, mutational load and mutational signatures in whole exome and RNA-sequencing data of the HNSCC TCGA dataset (n = 496) and a validation set (DKTK MASTER cohort, n = 10). Public single-cell gene expression data from 17 HPV-negative HNSCC were separately reanalyzed. APOBEC3-associated TCW motif mutations but not total single nucleotide variant burden were significantly associated with inflammation. This association was restricted to HPV-negative HNSCC samples. An APOBEC-enriched, HPV-negative subgroup was identified, that showed higher T-cell inflammation and immune checkpoint expression, as well as expression of APOBEC3 genes. Mutations in immune-evasion pathways were also enriched in these tumors. Analysis of single-cell sequencing data identified expression of APOBEC3B and 3C genes in malignant cells. We identified an APOBEC-enriched subgroup of HPV-negative HNSCC with a distinct immunogenic phenotype, potentially mediating response to immunotherapy.

VIST - a Variant-Information Search Tool for precision oncology.

BACKGROUND: Diagnosis and treatment decisions in cancer increasingly depend on a detailed analysis of the mutational status of a patient's genome. This analysis relies on previously published information regarding the association of variations to disease progression and possible interventions. Clinicians to a large degree use biomedical search engines to obtain such information; however, the vast majority of scientific publications focus on basic science and have no direct clinical impact. We develop the Variant-Information Search Tool (VIST), a search engine designed for the targeted search of clinically relevant publications given an oncological mutation profile. RESULTS: VIST indexes all PubMed abstracts and content from ClinicalTrials.gov. It applies advanced text mining to identify mentions of genes, variants and drugs and uses machine learning based scoring to judge the clinical relevance of indexed abstracts. Its functionality is available through a fast and intuitive web interface. We perform several evaluations, showing that VIST's ranking is superior to that of PubMed or a pure vector space model with regard to the clinical relevance of a document's content. CONCLUSION: Different user groups search repositories of scientific publications with different intentions. This diversity is not adequately reflected in the standard search engines, often leading to poor performance in specialized settings. We develop a search engine for the specific case of finding documents that are clinically relevant in the course of cancer treatment. We believe that the architecture of our engine, heavily relying on machine learning algorithms, can also act as a blueprint for search engines in other, equally specific domains. VIST is freely available at https://vist.informatik.hu-berlin.de/.

Variant information systems for precision oncology.

BACKGROUND: The decreasing cost of obtaining high-quality calls of genomic variants and the increasing availability of clinically relevant data on such variants are important drivers for personalized oncology. To allow rational genome-based decisions in diagnosis and treatment, clinicians need intuitive access to up-to-date and comprehensive variant information, encompassing, for instance, prevalence in populations and diseases, functional impact at the molecular level, associations to druggable targets, or results from clinical trials. In practice, collecting such comprehensive information on genomic variants is difficult since the underlying data is dispersed over a multitude of distributed, heterogeneous, sometimes conflicting, and quickly evolving data sources. To work efficiently, clinicians require powerful Variant Information Systems (VIS) which automatically collect and aggregate available evidences from such data sources without suppressing existing uncertainty. METHODS: We address the most important cornerstones of modeling a VIS: We take from emerging community standards regarding the necessary breadth of variant information and procedures for their clinical assessment, long standing experience in implementing biomedical databases and information systems, our own clinical record of diagnosis and treatment of cancer patients based on molecular profiles, and extensive literature review to derive a set of design principles along which we develop a relational data model for variant level data. In addition, we characterize a number of public variant data sources, and describe a data integration pipeline to integrate their data into a VIS. RESULTS: We provide a number of contributions that are fundamental to the design and implementation of a comprehensive, operational VIS. In particular, we (a) present a relational data model to accurately reflect data extracted from public databases relevant for clinical variant interpretation, (b) introduce a fault tolerant and performant integration pipeline for public variant data sources, and (c) offer recommendations regarding a number of intricate challenges encountered when integrating variant data for clincal interpretation. CONCLUSION: The analysis of requirements for representation of variant level data in an operational data model, together with the implementation-ready relational data model presented here, and the instructional description of methods to acquire comprehensive information to fill it, are an important step towards variant information systems for genomic medicine.

Systemic Treatment in HPV-Induced Recurrent or Metastatic HNSCC.

Recurrent or metastatic head and neck cancer describes tumor deposits that arise locally, regionally, or at distant sites after treatment or distant metastases at the time of primary diagnosis. Prognosis for R/M squamous cell carcinomas of the head and neck (HNSCC) is poor and treatment options are limited in this situation. Human papillomavirus (HPV) is an important risk factor for HNSCC. About 40 % of all HNSCC have been attributed to HPV in Europe. HPV positivity at initial diagnosis is the single best prognostic factor for survival. However, data for the prognostic and predictive value of HPV in the R/M situation are still scarce. Due to the rising incidence of HPV-associated cancers, the number of R/M HPV+ carcinomas is also expected to rise. This chapter therefore aims to give an overview of the current knowledge concerning the role of HPV as a prognostic and predictive marker in recurrent or metastatic HNSCC.

Renal Extramedullary Hematopoiesis in Mast Cell Leukemia with Bone Marrow Fibrosis.

Systemic mastocytosis is defined by the clonal proliferation of abnormal mast cells. The clinical course can range from indolent forms with normal life expectancy to advanced mast cell leukemia with dismal prognosis. An association with other diseases, including myeloproliferative neoplasia, has been described. We present a case of a 75-year patient with a history of cutaneous mastocytosis who was diagnosed with mast cell leukemia more than 9 years ago and did not receive treatment. The patient presented to our clinic with acute kidney failure because of renal extramedullary hematopoiesis. Bone marrow histopathology revealed extensive fibrosis and 50% infiltration by mast cells with a c-KIT D816V mutation. No mutations supporting primary myelofibrosis were identified. Treatment with midostaurin was started, and the patient was discharged after improvement of renal function. Here, we discuss diagnostic challenges between different forms of mast cell leukemia and overlaps with other hematological malignancies.

Targeted treatment in a case series of AR+, HRAS/PIK3CA co-mutated salivary duct carcinoma.

Background and purpose: A subgroup of salivary duct carcinoma (SDC) harbor overexpression of the androgen receptor (AR), and co-occurring mutations in the HRAS- and PIK3CA-genes. The impact of genomic complexity on targeted treatment strategies in advanced cancer is unknown. Materials and methods: We analyzed molecular and clinical data from an institutional molecular tumor board (MTB) to identify AR+, HRAS/PIK3CA co-mutated SDC. Follow-up was performed within the MTB registrational study or retrospective chart review after approval by the local ethics committee. Response was assessed by the investigator. A systematic literature search was performed in MEDLINE to identify additional clinically annotated cases. Results: 4 patients with AR+ HRAS/PIK3CA co-mutated SDC and clinical follow-up data were identified from the MTB. An additional 9 patients with clinical follow-up were identified from the literature. In addition to AR overexpression and HRAS and PIK3CA-alterations, PD-L1 expression and Tumor Mutational Burden > 10 Mutations per Megabase were identified as additional potentially targetable alterations. Among evaluable patients, androgen deprivation therapy (ADT) was initiated in 7 patients (1 Partial Response (PR), 2 Stable Disease (SD), 3 Progressive Disease (PD), 2 not evaluable), tipifarnib was initiated in 6 patients (1 PR, 4 SD, 1 PD). One patient each was treated with immune checkpoint inhibition (Mixed Response) and combination therapies of tipifarnib and ADT (SD) and alpelisib and ADT (PR). Conclusion: Available data further support comprehensive molecular profiling of SDC. Combination therapies, PI3K-inhibitors and immune therapy warrant further investigation, ideally in clinical trials. Future research should consider this rare subgroup of SDC.

Prognostic factors in surgically treated malignant salivary gland tumors.

OBJECTIVES: To identify prognostic factors for evidence-based risk stratification in malignant salivary gland tumors. METHODS: This retrospective study identified 162 patients who presented with malignant salivary gland tumors between 2010 and 2020. Final analysis included 91 patients who underwent surgical treatment at our institution and were followed-up for ≥ 1 year. Medical records were reviewed and patients were categorized according to their risk profile. RESULTS: This study included 91 patients (51 males, 40 females, mean age 61 years). The most frequent entities were adenoid cystic carcinoma (n = 13, 14.3%) and mucoepidermoid carcinoma (n = 12, 13.2%). Kaplan-Meier analysis demonstrated a five-year overall survival (OS) of 66.2% and a recurrence-free survival (RFS) of 50.5%. Age > 60 years (p = 0.011), categorization into high-risk group (p = 0.011), UICC stage (p = 0.020), T stage (p = 0.032), grading (p = 0.045) and vascular invasion (p < 0.001) were significantly associated with OS; age > 60 years (p = 0.014), categorization into high-risk group (p < 0.001), UICC stage (p = 0.021), T stage (p = 0.017), grading (p = 0.011), vascular invasion (p = 0.012) and lymphovascular invasion (p < 0.001) were significantly associated with RFS. Multivariate Cox regression with backward elimination identified T stage (HR 1.835; 95% CI 1.187-2.836; p = 0.006) and grading (HR 2.233; 95% CI 1.113-4.480; p = 0.024) as significant factors for OS. Grading (HR 2.499; 95% CI 1.344-4.648; p = 0.004) was confirmed as a significant factor for RFS. CONCLUSION: Considering the risk of recurrence and distant metastasis in malignant salivary gland tumors, locoregional surgical control may not be sufficient and adjuvant therapies such as radiotherapy and/or systemic therapies should be considered.

Tumour mutational burden and survival with molecularly matched therapy.

BACKGROUND: The impact of tumour mutational burden (TMB) on outcome with molecularly matched therapy is unknown. Higher TMB could predict resistance to molecularly matched therapy through co-occurring driver mutations. METHODS: One hundred and four patients with advanced cancers underwent molecular profiling in the DKTK-MASTER program. Fifty-five patients received systemic therapy excluding immunotherapy. Patients with molecularly matched (n = 35) or non-molecularly informed therapy (n = 20) were analysed for TMB and survival. Results were validated in an independent cohort of patients receiving molecularly matched (n = 68) or non-molecularly informed therapy (n = 40). Co-occurring driver mutations and TMB were analysed in the exploratory cohort and The Cancer Genome Atlas (TCGA) datasets. RESULTS: Patients were stratified by the median TMB of 1.67 mutations per Megabase (mut/Mb) of 35 patients receiving molecularly matched therapy into TMB-high or TMB-low groups. Median overall survival (4 months [95% CI, 3.3-7.6] versus 12.8 months [95% CI, 10-not reached], p < 0.001) and progression-free survival (1.8 months [95% CI, 1.1-3.7] versus 7.9 months [95% CI, 2.8-17.0], p = 0.003) were significantly shorter in the TMB-high group compared to the TMB-low group. In the validation cohort, shorter OS and PFS were identified in the TMB-high group (TMB cut-off of 4 mut/Mb) treated with molecularly matched therapy. No differences were observed in patients receiving non-molecularly informed systemic therapy. A significant correlation between co-occurring driver mutations and TMB (n = 104, r = 0.78 [95% CI, 0.68-0.85], p < 0.001) was found in the exploratory cohort as well as the majority (24/33) of TCGA studies. CONCLUSION: A high TMB was associated with unfavourable outcome in patients receiving molecularly matched therapy, indicating untargeted resistance pathways. Therefore, TMB should be further investigated as a predictive biomarker in precision oncology programs.

Leveraging Large Language Models for Decision Support in Personalized Oncology.

Importance: Clinical interpretation of complex biomarkers for precision oncology currently requires manual investigations of previous studies and databases. Conversational large language models (LLMs) might be beneficial as automated tools for assisting clinical decision-making. Objective: To assess performance and define their role using 4 recent LLMs as support tools for precision oncology. Design, Setting, and Participants: This diagnostic study examined 10 fictional cases of patients with advanced cancer with genetic alterations. Each case was submitted to 4 different LLMs (ChatGPT, Galactica, Perplexity, and BioMedLM) and 1 expert physician to identify personalized treatment options in 2023. Treatment options were masked and presented to a molecular tumor board (MTB), whose members rated the likelihood of a treatment option coming from an LLM on a scale from 0 to 10 (0, extremely unlikely; 10, extremely likely) and decided whether the treatment option was clinically useful. Main Outcomes and Measures: Number of treatment options, precision, recall, F1 score of LLMs compared with human experts, recognizability, and usefulness of recommendations. Results: For 10 fictional cancer patients (4 with lung cancer, 6 with other; median [IQR] 3.5 [3.0-4.8] molecular alterations per patient), a median (IQR) number of 4.0 (4.0-4.0) compared with 3.0 (3.0-5.0), 7.5 (4.3-9.8), 11.5 (7.8-13.0), and 13.0 (11.3-21.5) treatment options each was identified by the human expert and 4 LLMs, respectively. When considering the expert as a criterion standard, LLM-proposed treatment options reached F1 scores of 0.04, 0.17, 0.14, and 0.19 across all patients combined. Combining treatment options from different LLMs allowed a precision of 0.29 and a recall of 0.29 for an F1 score of 0.29. LLM-generated treatment options were recognized as AI-generated with a median (IQR) 7.5 (5.3-9.0) points in contrast to 2.0 (1.0-3.0) points for manually annotated cases. A crucial reason for identifying AI-generated treatment options was insufficient accompanying evidence. For each patient, at least 1 LLM generated a treatment option that was considered helpful by MTB members. Two unique useful treatment options (including 1 unique treatment strategy) were identified only by LLM. Conclusions and Relevance: In this diagnostic study, treatment options of LLMs in precision oncology did not reach the quality and credibility of human experts; however, they generated helpful ideas that might have complemented established procedures. Considering technological progress, LLMs could play an increasingly important role in assisting with screening and selecting relevant biomedical literature to support evidence-based, personalized treatment decisions.

Biomarker-driven therapies for metastatic uveal melanoma: A prospective precision oncology feasibility study.

BACKGROUND: Targeted therapies for metastatic uveal melanoma have shown limited benefit in biomarker-unselected populations. The Treat20 Plus study prospectively evaluated the feasibility of a precision oncology strategy in routine clinical practice. PATIENTS AND METHODS: Fresh biopsies were analyzed by high-throughput genomics (whole-genome, whole-exome, and RNA sequencing). A multidisciplinary molecular and immunologic tumor board (MiTB) made individualized treatment recommendations based on identified molecular aberrations, patient situation, drug, and clinical trial availability. Therapy selection was at the discretion of the treating physician. The primary endpoint was the feasibility of the precision oncology clinical program. RESULTS: Molecular analyses were available for 39/45 patients (87%). The MiTB provided treatment recommendations for 40/45 patients (89%), of whom 27/45 (60%) received ≥1 matched therapy. First-line matched therapies included MEK inhibitors (n = 15), MET inhibitors (n = 10), sorafenib (n = 1), and nivolumab (n = 1). The best response to first-line matched therapy was partial response in one patient (nivolumab based on tumor mutational burden), mixed response in two patients, and stable disease in 12 patients for a clinical benefit of 56%. The matched therapy population had a median progression-free survival and overall survival of 3.3 and 13.9 months, respectively. The growth modulation index with matched therapy was >1.33 in 6/17 patients (35%) with prior systemic therapy, suggesting clinical benefit. CONCLUSIONS: A precision oncology approach was feasible for patients with metastatic uveal melanoma, with 60% receiving a therapy matched to identify molecular aberrations. The clinical benefit after checkpoint inhibitors highlights the value of tumor mutational burden testing.

Annotation and initial evaluation of a large annotated German oncological corpus.

OBJECTIVE: We present the Berlin-Tübingen-Oncology corpus (BRONCO), a large and freely available corpus of shuffled sentences from German oncological discharge summaries annotated with diagnosis, treatments, medications, and further attributes including negation and speculation. The aim of BRONCO is to foster reproducible and openly available research on Information Extraction from German medical texts. MATERIALS AND METHODS: BRONCO consists of 200 manually deidentified discharge summaries of cancer patients. Annotation followed a structured and quality-controlled process involving 2 groups of medical experts to ensure consistency, comprehensiveness, and high quality of annotations. We present results of several state-of-the-art techniques for different IE tasks as baselines for subsequent research. RESULTS: The annotated corpus consists of 11 434 sentences and 89 942 tokens, annotated with 11 124 annotations for medical entities and 3118 annotations of related attributes. We publish 75% of the corpus as a set of shuffled sentences, and keep 25% as held-out data set for unbiased evaluation of future IE tools. On this held-out dataset, our baselines reach depending on the specific entity types F1-scores of 0.72-0.90 for named entity recognition, 0.10-0.68 for entity normalization, 0.55 for negation detection, and 0.33 for speculation detection. DISCUSSION: Medical corpus annotation is a complex and time-consuming task. This makes sharing of such resources even more important. CONCLUSION: To our knowledge, BRONCO is the first sizable and freely available German medical corpus. Our baseline results show that more research efforts are necessary to lift the quality of information extraction in German medical texts to the level already possible for English.

Support of a molecular tumour board by an evidence-based decision management system for precision oncology.

BACKGROUND: Reliable and reproducible interpretation of molecular aberrations constitutes a bottleneck of precision medicine. Evidence-based decision management systems may improve rational therapy recommendations. To cope with an increasing amount of complex molecular data in the clinical care of patients with cancer, we established a workflow for the interpretation of molecular analyses. METHODS: A specialized physician screened results from molecular analyses for potential biomarkers, irrespective of the diagnostic modality. Best available evidence was retrieved and categorized through establishment of an in-house database and interrogation of publicly available databases. Annotated biomarkers were ranked using predefined evidence levels and subsequently discussed at a molecular tumour board (MTB), which generated treatment recommendations. Subsequent translation into patient treatment and clinical outcomes were followed up. RESULTS: One hundred patients were discussed in the MTB between January 2016 and May 2017. Molecular data were obtained for 70 of 100 patients (50 whole exome/RNA sequencing, 18 panel sequencing, 2 immunohistochemistry (IHC)/microsatellite instability analysis). The MTB generated a median of two treatment recommendations each for 63 patients. Thirty-nine patients were treated: 6 partial responses and 12 stable diseases were achieved as best responses. Genetic counselling for germline events was recommended for seven patients. CONCLUSION: The development of an evidence-based workflow allowed for the clinical interpretation of complex molecular data and facilitated the translation of personalized treatment strategies into routine clinical care. The high number of treatment recommendations in patients with comprehensive genomic data and promising responses in patients treated with combination therapy warrant larger clinical studies.

A harmonized meta-knowledgebase of clinical interpretations of somatic genomic variants in cancer.

Precision oncology relies on accurate discovery and interpretation of genomic variants, enabling individualized diagnosis, prognosis and therapy selection. We found that six prominent somatic cancer variant knowledgebases were highly disparate in content, structure and supporting primary literature, impeding consensus when evaluating variants and their relevance in a clinical setting. We developed a framework for harmonizing variant interpretations to produce a meta-knowledgebase of 12,856 aggregate interpretations. We demonstrated large gains in overlap between resources across variants, diseases and drugs as a result of this harmonization. We subsequently demonstrated improved matching between a patient cohort and harmonized interpretations of potential clinical significance, observing an increase from an average of 33% per individual knowledgebase to 57% in aggregate. Our analyses illuminate the need for open, interoperable sharing of variant interpretation data. We also provide a freely available web interface (search.cancervariants.org) for exploring the harmonized interpretations from these six knowledgebases.

Comparative Analysis of Public Knowledge Bases for Precision Oncology.

PURPOSE: Precision oncology depends on the availability of up-to-date, comprehensive, and accurate information about associations between genetic variants and therapeutic options. Recently, a number of knowledge bases (KBs) have been developed that gather such information on the basis of expert curation of the scientific literature. We performed a quantitative and qualitative comparison of Clinical Interpretations of Variants in Cancer, OncoKB, Cancer Gene Census, Database of Curated Mutations, CGI Biomarkers (the cancer genome interpreter biomarker database), Tumor Alterations Relevant for Genomics-Driven Therapy, and the Precision Medicine Knowledge Base. METHODS: We downloaded each KB and restructured their content to describe variants, genes, drugs, and gene-drug associations in a common format. We normalized gene names to Entrez Gene IDs and drug names to ChEMBL and DrugBank IDs. For the analysis of clinically relevant gene-drug associations, we obtained lists of genes affected by genetic alterations and putative drug therapies for 113 patients with cancer whose cases were presented at the Molecular Tumor Board (MTB) of the Charité Comprehensive Cancer Center. RESULTS: Our analysis revealed that the KBs are largely overlapping but also that each source harbors a notable amount of unique information. Although some KBs cover more genes, others contain more data about gene-drug associations. Retrospective comparisons with findings of the Charitè MTB at the gene level showed that use of multiple KBs may considerably improve retrieval results. The relative importance of a KB in terms of cancer genes was assessed in more detail by logistic regression, which revealed that all but one source had a notable impact on result quality. We confirmed these findings using a second data set obtained from an independent MTB. CONCLUSION: To date, none of the existing publicly available KBs on gene-drug associations in precision oncology fully subsumes the others, but all of them exhibit specific strengths and weaknesses. Consideration of multiple KBs, therefore, is essential to obtain comprehensive results.