AIMS:Clinical case reports in oncology are an untapped resource of patient data that include relationships between molecular alterations, tumor types, and response to targeted therapy. A current challenge to widespread utilization of case reports in clinical practice is the lack of systematic organization of clinical evidence across disease types, patient outcomes, therapies, and associated molecular features. To address this challenge, we sought to demonstrate the utility of Cancer Knowledgebase (CKB) (https://ckb.genomenon.com/) in interpreting oncology case report data for health care providers. METHODS:We analyzed data from 5527 manually curated case reports in CKB to gain insights related to treatment options and patient response associated with specific molecular alterations. RESULTS:Each case report in CKB is represented as a unique efficacy evidence annotation and is associated with a specific molecular profile, therapy, indication, and response to therapy. Efficacy evidence from case reports spans over 500 genes, 2800 molecular profiles, and 300 tumor types, including several rare cancers and pediatric tumor types. CONCLUSION:CKB is a powerful resource for leveraging case reports to identify treatment options for patients with rare cancers and oncogenic variants, patients for whom multiple therapies exist, and patients experiencing resistance to first-line therapy.

Purpose The explosion of molecular biomarker and treatment information in the precision medicine era drastically exacerbated difficulty in identifying patient-relevant knowledge for clinical researchers and practitioners. Curated knowledgebases, such as the JAX Clinical Knowledgebase (CKB) are tools to organize and display knowledge in a readily accessible format; however, curators face the same challenges in comprehensively identifying clinically relevant information for curation. Natural language processing (NLP) has emerged as a promising direction for accelerating manual curation, but prior applications were often conceived as stand-alone efforts to automate curation, and the scope is often limited to simple entity and relation extraction. In this paper, we study the alternative paradigm of assisted curation and identify key desiderata to scale up knowledge curation with human-computer symbiosis. Methods We chose precision oncology for a case study and introduced self-supervised machine reading, which can automatically generate noisy training examples from unlabeled text. We developed a curation user interface (UI) for precision oncology and through iterative “curathons” (curation hackathons), conducted retrospective and prospective user studies for head-to-head comparison between manual and machine-assisted curation. Results Contrary to the prevailing assumption, we showed that high recall is more important for end-to-end assisted curation. In extensive user studies, we showed that assisted curation can double the curation speed and increase the number of findings by an order of magnitude for previously scarcely curated drugs. Conclusion We demonstrated that an iterative and thoughtful collaboration between professional curators and NLP researchers can facilitate rapid advances in assisted curation for precision medicine. Human-machine reading symbiosis can potentially be applicable to clinical care and research scenarios where curation is a major bottleneck.

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.

Background Understanding mechanisms underlying specific chemotherapeutic responses in subtypes of cancer may improve identification of treatment strategies most likely to benefit particular patients. For example, triple-negative breast cancer (TNBC) patients have variable response to the chemotherapeutic agent cisplatin. Understanding the basis of treatment response in cancer subtypes will lead to more informed decisions about selection of treatment strategies. Methods In this study we used an integrative functional genomics approach to investigate the molecular mechanisms underlying known cisplatin-response differences among subtypes of TNBC. To identify changes in gene expression that could explain mechanisms of resistance, we examined 102 evolutionarily conserved cisplatin-associated genes, evaluating their differential expression in the cisplatin-sensitive, basal-like 1 (BL1) and basal-like 2 (BL2) subtypes, and the two cisplatin-resistant, luminal androgen receptor (LAR) and mesenchymal (M) subtypes of TNBC. Results We found 20 genes that were differentially expressed in at least one subtype. Fifteen of the 20 genes are associated with cell death and are distributed among all TNBC subtypes. The less cisplatin-responsive LAR and M TNBC subtypes show different regulation of 13 genes compared to the more sensitive BL1 and BL2 subtypes. These 13 genes identify a variety of cisplatin-resistance mechanisms including increased transport and detoxification of cisplatin, and mis-regulation of the epithelial to mesenchymal transition. Conclusions We identified gene signatures in resistant TNBC subtypes indicative of mechanisms of cisplatin. Our results indicate that response to cisplatin in TNBC has a complex foundation based on impact of treatment on distinct cellular pathways. We find that examination of expression data in the context of heterogeneous data such as drug-gene interactions leads to a better understanding of mechanisms at work in cancer therapy response.

Cancer genomic data is continually growing in complexity, necessitating improved methods for data capture and analysis. Tumors often contain multiple therapeutically relevant alterations, and co-occurring alterations may have a different influence on therapeutic response compared to if those alterations were present alone. One clinically important example of this is the existence of a resistance conferring alteration in combination with a therapeutic sensitizing mutation. The JAX Clinical Knowledgebase (JAX-CKB) (https://ckb.jax.org/) has incorporated the concept of the complex molecular profile, which enables association of therapeutic efficacy data with multiple genomic alterations simultaneously. This provides a mechanism for rapid and accurate assessment of complex cancer-related data, potentially aiding in streamlined clinical decision making. Using the JAX-CKB, we demonstrate the utility of associating data with complex profiles comprising ALK fusions with another variant, which have differing impacts on sensitivity to various ALK inhibitors depending on context.

Abstract Introduction In the constantly changing field of oncology precision medicine, it is exceedingly important to keep diagnostic and therapeutic assays clinically relevant. Next generation sequencing (NGS) panels in oncology are greatly impacted by new findings in clinical actionability. In order to ensure that cancer panels continue to provide the most beneficial results to patients, they must be regularly updated. In keeping with this idea, JAX has launched a new 212 oncology gene panel which focuses on genes and variants with documented actionability, referred to as ActionSeq. Methods Development of ActionSeq included the optimization of a new targeted capture assay. This process included running multiple batches of samples through the assay to determine appropriate DNA input, ligation times, PCR cycles, and pooling conditions. The fully optimized assay was then validated using 24 uncharacterized FFPE samples. The validation was executed in 5 phases: (1) confirm that assay optimizations yielded sufficient wet lab results; (2) LOD & sensitivity (3) inter-assay concordance; (4) intra-assay concordance; (5) specificity and accuracy. Results During development, the standard protocol was optimized using a 200ng input, 30 minute ligation period, 5 cycles of pre-PCR, and the pooling of 4 samples per hybridization reaction. Wet lab processing results of the first validation batch can be seen in Table 1. The inter- and intra-assay concordances were found to be ≥ 96% for variants and 100% for CNVs. The sensitivity was calculated to be 98.92% at a LOD of 3% for SNVs, 100% at a LOD of 8% for INDELs, 100% at a LOD of 6 copies for CNV amplifications, and 100% at a LOD of 0 copies for CNV deletions. The specificity and accuracy were found to be 100% for all mutation types. Conclusion Based on the success of this validation ActionSeq has been incorporated into the JAX clinical test menu. This addition accomplished the goal of providing a more clinically relevant (actionable) somatic tumor profiling assay to patients and clinicians. Table 1.This table displays the wet lab processing results for the 24 samples used to confirm the efficiency of the developmental optimizations made to the assay prior to beginning the clinical validation.SamplePost Prep ng/ulCapture Pool ng/ulAverage Base Pair SizeMean Target CoveragePercent Duplication1271.4130951123%2241.4130959423%3241.5230265922%4291.5230265221%5212.2229053516%6352.2229056013%7292.2329953017%8722.58304119614%9652.5830473214%10432.5830457113%1142230372218%12372.030361116%13272.030373518%14421.930973120%15401.930968319%16671.930967516%17481.930957320%18531.8930165519%19311.8930176322%20821.8930176117%21561.8930187719%22341.9932977118%23481.9932988616%24781.9932984115%Established Quality Control Cut Offs:Post Library Prep ng/ul:≥ 20Post Capture Pool ng/ul:≥ 0.5PC Average Base Pair Size:250-350Mean Target Coverage:≥ 500Percent Duplication:≤ 25% Citation Format: Samantha Helm, Vanessa Spotlow, Aleksandra Ras, Kevin Kelly, Guruprasad Ananda, Sara Patterson, Honey V. Reddi. Development and validation of the ActionSeqTM test system [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2017; 2017 Apr 1-5; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2017;77(13 Suppl):Abstract nr 757. doi:10.1158/1538-7445.AM2017-757

Abstract Emergence of resistance to targeted therapies is a critical problem in cancer therapy, and understanding both the mechanisms of resistance and strategies for overcoming resistance are crucial to effective treatment of cancer patients. The JAX Clinical Knowledgebase (JAX-CKB), which incorporates data on therapeutic efficacy in the context of molecular alterations, enables rapid analysis of known therapy resistance mechanisms and current data surrounding strategies for overcoming resistance, both in the preclinical and clinical setting. Using the JAX-CKB, we have identified over 1250 lines of evidence corresponding to therapy resistance across tumor types. Of those lines, 147 correspond to therapy resistance in lung cancer. The JAX-CKB contains 22 variants in ALK associated with ALK therapy resistance. Within ALK fusion-positive lung cancer, evidence lines corresponding to ALK inhibitor resistance are associated primarily with complex molecular profiles containing secondary ALK mutations, and mechanisms for overcoming resistance in this setting were associated with use of novel agents. Within EGFR mutation positive lung cancer, lines associated with resistance to EGFR inhibitor therapy included copy number alterations, primary resistance mutations, secondary resistance mutations, and expression level changes. Strategies for overcoming resistance in these settings include novel agents and/or various combination therapies. The JAX-CKB provides a unique global view into current data on resistance to targeted therapies in oncology, which may enable more rapid assessment of effective therapy options and expose opportunities for additional research into strategies for overcoming resistance. Citation Format: Sara E. Patterson, Cara M. Statz, Taofei Yin, Susan M. Mockus. Analysis of drug resistance mechanisms and strategies for overcoming resistance in cancer therapy using a curated clinical knowledgebase [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2017; 2017 Apr 1-5; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2017;77(13 Suppl):Abstract nr 2600. doi:10.1158/1538-7445.AM2017-2600

Abstract Technological innovations have facilitated a greater understanding of how the tumor microenvironment contributes to cancer, leading to rapid FDA approval of four immunotherapies. To assess how these therapies are being further investigated in combination with other therapies and in tumor types outside of the current FDA approval, we performed a comprehensive analysis of the curated clinical trials in the JAX Clinical Knowledgebase (JAX-CKB). In brief, clinical trials investigating Atezolizumab, Nivolumab, Pembrolizumab, and Ipilimumab, curated from clinicaltrials.gov, were queried in the JAX-CKB and then analyzed for comparison. Further analyses were executed to illustrate possible unmet needs within the field of cancer therapeutics. Of the four immunotherapies, Pembrolizumab was identified with the greatest number of clinical trials overall, with 305 compared to Atezolizumab, 79, Nivolumab, 183, and Ipilimumab, 126. Of these trials the number of trials investigating Pembrolizumab, Atezolizumab, Nivolumab, or Ipilimumab in combination with another therapy was higher than those investigating one of the four immunotherapies as a monotherapy. Phase II trials for both single therapy and combinatorial therapies were greater than both Phase I and Phase III for the same groups, regardless of therapy. On average, 12% ± 3.8% of the combined trials for all four drugs included any advanced solid tumor. Nivolumab combined with Ipilimumab demonstrated the greatest number of trials (61) investigating an immunotherapy in combination with another immunotherapy. Among those, 30 were Phase II trials, 16 were Phase I, and 14 were Phase III. Across five cancer indications (lung, pancreatic, ovarian, prostate, and colon), lung cancer was most commonly indicated in the trials, among all four drugs. Prostate was indicated in the least number of trials, with Ipilimumab ranking the highest (10). The recent success with immunotherapies has garnered significant interest in understanding how these therapies will perform in different tumor types and whether specific combinations will have a greater impact. Interrogation of the clinical trial terrain in the JAX-CKB provides a basis for determining additional investigations that might be warranted. Citation Format: Cara M. Statz, Sara E. Patterson, Taofei Yin, Susan M. Mockus. A comprehensive analysis delineating the immunotherapeutic terrain of cancer-related clinical trials [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2017; 2017 Apr 1-5; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2017;77(13 Suppl):Abstract nr 541. doi:10.1158/1538-7445.AM2017-541

Introduction: Comprehensive cancer genomic profiling provides the opportunity to expose the various molecular aberrations potentially driving tumor progression. Consequently, the identity of these genetic drivers can be utilized to match a patient to the most appropriate targeted therapy, thereby increasing the probability of improved clinical outcome. Despite its capability of informing patient care, the adoption of comprehensive cancer genomic profiling in the clinic has not been widespread. The barriers surrounding its universal acceptance are attributed to both physician and patient perspectives.Areas covered: The following report discusses the various obstacles in place, including those related to clinical utility, education, insurance coverage, and clinical trials, which can deter physicians and patients from utilizing genomic profiling for therapeutic decision-making.Expert commentary: The authors review the recent growth and potential of clinical utility studies over the last two years, provide a suggestive framework for educational support, and comment on the use of social media to enhance clinical trial recruitment.

Abstract The ability to capture data relevant to different types of oncology-related variations, including single nucleotide variations, deletions, insertions, copy number variations, and fusions in a single system is crucial to a comprehensive understanding of cancer biology. However, collectively linking these varied types of molecular alterations to capture their compound impact to clinically relevant efficacy evidence within a database can prove challenging. Thus, we have built the JAX Clinical Knowledgebase (JAX-CKB), a flexible relational database that allows curation of complex molecular profiles and provides the ability to associate these profiles with documented efficacy evidence, thereby providing a more detailed overview of therapeutic relevance. To demonstrate the utility of creating complex molecular signatures in relation to efficacy evidence, the JAX-CKB was queried to first determine the overall degree of efficacy evidence content related to complex profiles. Additionally, two specific types of complex molecular profiles were queried, which included EML4-ALK plus a missense mutation(s) and BRAF V600E plus any type of molecular alteration(s). Within the JAX-CKB, there are 1,383 unique efficacy evidence lines linked to complex molecular profiles. The complex molecular profiles consisting of EML4-ALK and one or more additional missense mutations were associated with 174 unique efficacy evidence lines. Of the 174 lines, 69 were annotated with a resistant response type, while 68 were annotated with a sensitive response type. The combination of BRAF V600E with one or more molecular alterations was linked to 229 unique efficacy evidence lines. The majority of the lines, 118, were specific to a resistant response type and 83 were associated with sensitivity. Comprehensive genomic profiling of cancer patient samples can often reveal complex molecular signatures. The JAX-CKB is an inclusive knowledgebase that allows one to interpret these complex signatures and rapidly identify appropriate targeted therapies, which could be critical in a clinical setting. Citation Format: Cara M. Statz, Sara E. Patterson, Taofei Yin, Susan M. Mockus. A model for capturing and integrating complex molecular alterations related to clinically relevant efficacy evidence [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2017; 2017 Apr 1-5; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2017;77(13 Suppl):Abstract nr 2583. doi:10.1158/1538-7445.AM2017-2583

Tumors often contain many different simultaneous variations, including single nucleotide variations, deletions, insertions, copy number variations, and/or fusions, which may interact to impact the growth of the tumor or prognosis of the patient. To fully assess the complex molecular landscape of a tumor and its relationship to actionability, it is necessary to have the ability to access evidence as it relates to multiple interacting variants. The JAX Clinical Knowledgebase (JAX-CKB) is a relational database that allows for capture of data related to different types of cancer -associated variations, alone or in combination. To demonstrate the utility of relating evidence to complex molecular signatures, focusing on fusion variants, the JAX-CKB was queried to assess the types of evidence related to fusions alone, or in the context of one or more additional variants. The JAX-CKB contains 898 fusion-associated evidence lines, with 533 related to complex molecular profiles. We additionally queried the JAX-CKB to identify the relationships of complex molecular profiles containing the fusion EML4-ALK or BCR-ABL1 evidence in the JAX-CKB. Complex profiles containing EML4-ALK were associated with 179 unique evidence lines. Of those, 66 were annotated with a resistant response type, while 76 were annotated with a sensitive response type. For BCR-ABL1, complex profiles were associated with 98 efficacy evidence lines, and of those 25 were associated with a resistant response type, and 46 with a sensitive response type. The JAX-CKB includes multiple types of evidence related to complex molecular signatures, thereby providing valuable information that could be translated to clinical application.

Background The progression of prostate cancer to castration-resistant prostate cancer (CRPC) is often a result of somatic alterations in the PI3K/Akt/mTOR (mammalian target of rapamycin) pathway, suggesting that therapies targeting this pathway might lead to improved survival and efficacy. Here, we systematically evaluate the results of clinical trials investigating mTOR inhibition in CRPC and utilize preclinical data to predict clinical outcomes. Methods Trials included in the study were identified through PubMed and via review of conference abstracts cited by relevant review articles. The eligibility of trials was independent of sample size, clinical setting, or date. Results A total of 14 studies were eligible for qualitative analysis. The clinical setting was variable among studies, and all utilized an allosteric mTOR inhibitor as either a monotherapy or in combination. Molecular criteria were evaluated in three trials. Among most studies, the prostate-specific antigen level declined during treatment, but often increased shortly thereafter. Partial responses to treatment were minimal, and no complete responses were reported. Two studies exploring therapy with an mTOR inhibitor in combination with bicalutamide resulted in minimal efficacy. Overall, allosteric mTOR inhibition was deemed to be inadequate for the treatment of CRPC. Conclusion Preclinical data suggest that a reciprocal feedback mechanism between PI3K and androgen receptor signaling is a potential mechanism behind the clinical inefficacy of mTOR inhibitors in CRPC, indicating combinatorial targeting of PI3K, mTORC1/2, and the androgen receptor might be more effective. Comprehensive analysis of preclinical data to assess clinical trial targets and efficacy may reduce the number of unproductive trials and identify potentially beneficial combinatorial therapies for resistant disease.

Abstract In the era of personalized medicine, comprehensive cancer genomic databases represent critical tools for interpreting gene variants and their relevant therapies. As the number of cancer genomic databases grow, it is challenging for users to compare and assess the data integrity and validity of such databases. The lack of disclosure of curation processes makes it difficult to cross reference different databases. The JAX Clinical Knowledgebase (CKB) is a comprehensive relational database providing evidence-based information on gene variants, targeted therapies, efficacy evidence, and clinical trials. At the Jackson Laboratory for Genomic Medicine, we have developed a curation paradigm to ensure curation transparency and consistency of the JAX-CKB. First, to ensure standardization of nomenclature, we have integrated standard nomenclature and ontologies, including HGNC approved nomenclatures for genes, HGVS guidelines for variants, and the Disease Ontology for indications/tumor types. Second, we implemented decision matrices to maintain uniformity of our evaluation of scientific and clinical data. For example, evaluation of the effect of gene variants on protein function is solely based on changes in the intrinsic activity of the protein instead of downstream pathway activation or the effects on pathogenesis; the response type of gene variants to therapies are classified based on the evidence of targeting specificity; and the efficacy evidence are further classified as actionable, diagnostic, prognostic, risk factor, emerging, or not active centered on the response type and the strength of the evidence. Third, to provide convenient evaluation of the clinical relevance of efficacy data, we further developed a tier ranking system based on emerging consensus guidelines, which takes response type, evidence type, and approval status into consideration. Finally, all decision matrices are clearly outlined on the JAX-CKB open access website for users’ reference. In summary, we have curated a highly structured and semantically consistent cancer genomic database following a set of specific curation guidelines. As a result, JAX-CKB open access has become a valuable resource for both the clinical and research communities, and is utilized by numerous independent groups for variant interpretation. Citation Format: Taofei Yin, Sara E. Patterson, Cara M. Statz, Anuradha Lakshminarayana, Daniel Durkin, Susan M. Mockus. Paradigm to ensure curation transparency and consistency of a cancer genomic database - the JAX Clinical Knowledgebase (CKB) [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2017; 2017 Apr 1-5; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2017;77(13 Suppl):Abstract nr 2598. doi:10.1158/1538-7445.AM2017-2598

Laura J. Tafe, Kristen E. Muller, Guruprasad Ananda, Talia Mitchell, Vanessa Spotlow, Sara E. Patterson, Gregory J. Tsongalis, and Susan M. Mockus 88 89 90 From the Dartmouth-Hitchcock Medical Center and Norris Cotton Cancer Center,* Lebanon, and the Geisel School of Medicine at Dartmouth, Hanover, New Hampshire; and The Jackson Laboratory for Genomic Medicine,y Farmington, Connecticut 91 92 93 Accepted for publication

e23242 Background: Clinical trials in precision oncology generally require the presence or absence of specific mutations as part of the criteria for patient eligibility. Identification of these trials is hampered by the lack of open clinical trial registries with systematic methods to capture and search mutational eligibility requirements. Methods: We have built a Clinical Knowledgebase (CKB) to support our own internal clinical NGS pipeline and have now launched CKB as an open-source tool to assist others traversing similar hurdles. CKB is a manually curated resource that contains data attributes on gene variants, targeted therapies, efficacy evidence, and clinical trials; all curated through interoperable controlled vocabularies and HGVS and HGNC nomenclature standards. The clinical trial component systematically captures mutational profiles that are required or excluded from trial eligibility criteria. A nightly script updates the recruitment status for each trial, enabling searching in real-time. Results: Content in CKB currently contains 16,836 gene variants, 1250 targeted therapies, 3715 efficacy evidences, and 3193 clinical trials. A web interface allows users to browse any of the data attributes or to run specific clinical reporting queries based on the patient’s indication and somatic mutational profile. The clinical trial component currently contains 944 trials with mutational requirements and new trials are regularly curated through backend tools that enable triaging of clinicaltrials.gov query retrievals through bulk gene or targeted therapy lists. Examples of the searchable clinical trial content in CKB include 11 trials recruiting on EGFR T790M, 4 trials excluding patients with BRAF V600 mutations, and 3 trials requiring TP53 mutations. Inputting the patient’s indication through a drop down list of cancer terms from the Disease Ontology further refines trial results. Conclusions: We have created and launched a web-enabled open-source clinical knowledgebase for sharing content, disseminating methods, and fostering community development of interpretation of somatic mutations and clinical trial identification in precision oncology.

BACKGROUND:Availability of genomic information used in the management of cancer treatment has outpaced both regulatory and reimbursement efforts. Many types of clinical trials are underway to validate the utility of emerging genome-based biomarkers for diagnostic, prognostic, and predictive applications. Clinical trials are a key source of evidence required for US Food and Drug Administration approval of therapies and companion diagnostics and for establishing the acceptance criteria for reimbursement.CONTENT:Determining the eligibility of patients for molecular-based clinical trials and the interpretation of data emerging from clinical trials is significantly hampered by 2 primary factors: the lack of specific reporting standards for biomarkers in clinical trials and the lack of adherence to official gene and variant naming standards. Clinical trial registries need specifics on the mutation required for enrollment as opposed to allowing a generic mutation entry such as, "EGFR mutation." The use of clinical trials data in bioinformatics analysis and reporting is also gated by the lack of robust, state of the art programmatic access support. An initiative is needed to develop community standards for clinical trial descriptions and outcome reporting that are modeled after similar efforts in the genomics research community.SUMMARY:Systematic implementation of reporting standards is needed to insure consistency and specificity of biomarker data, which will in turn enable better comparison and assessment of clinical trial outcomes across multiple studies. Reporting standards will facilitate improved identification of relevant clinical trials, aggregation and comparison of information across independent trials, and programmatic access to clinical trials databases.

Benign ovarian Brenner tumors often are associated with mucinous cystic neoplasms, which are hypothesized to share a histogenic origin and progression, however, supporting molecular characterization is limited. Our goal was to identify molecular mechanisms linking these tumors. DNA from six Brenner tumors with paired mucinous tumors, two Brenner tumors not associated with a mucinous neoplasm, and two atypical proliferative (borderline) Brenner tumors was extracted from formalin-fixed, paraffin-embedded tumor samples and sequenced using a 358-gene next-generation sequencing assay. Variant calls were compared within tumor groups to assess somatic mutation profiles. There was high concordance of the variants between paired samples (40% to 75%; P < 0.0001). Four of the six tumor pairs showed KRAS hotspot driver mutations specifically in the mucinous tumor. In the two paired samples that lacked KRAS mutations, MYC amplification was detected in both of the mucinous and the Brenner components; MYC amplification also was detected in a third Brenner tumor. Five of the Brenner tumors had no reportable potential driver alterations. The two atypical proliferative (borderline) Brenner tumors both had RAS mutations. The high degree of coordinate variants between paired Brenner and mucinous tumors supports a shared origin or progression. Differences observed in affected genes and pathways, particularly involving RAS and MYC, may point to molecular drivers of a divergent phenotype and progression of these tumors.

Abstract Clear cell renal cell carcinoma (CCRCC), the most common subtype of renal cell carcinoma, is a heterogeneous cancer with variable outcomes and molecular aberrations. Further elucidation of mutational profiles and actionable mutations may improve patient outcomes in CCRCC. Somatic mutational profiling via next-generation sequencing was conducted on 30 CCRCC whole section FFPE patient samples to determine the mutational burden as compared to other solid tumor types. The sequencing failure rate for these samples was 20% (6/30). A 358-gene panel was also run on an additional 57 non-CCRCC solid tumor FFPE patient samples (81 samples in total). FASTQ files generated from Illumina's CASAVA software were submitted to the JAX Clinical Genome Analytics (CGA) data analysis pipeline to perform automated read quality assessment, alignment, and variant calling. Identified variants were then submitted for clinical curation using the JAX Clinical Knowledgebase (CKB) for actionable mutational analysis and overall mutational burden. Of the CCRCC sample set, 33% had one or more actionable mutations. This was low compared to actionable mutations in colon (16/16, 100% actionable), TNBC (18/20, 90% actionable), squamous lung (8/9, 89% actionable), and pancreatic (8/12, 67% actionable). Furthermore, the CCRCC set had a low overall mutational burden with 22 ± 6.7 nonsynonymous SNV's as compared to colon (29 ± 11), squamous lung (43 ± 17), and TNBC (31.5 ± 12). However, the pancreatic set had even lower SNV's at 12.7 ± 3.4. The number of indels was comparable across the five sets, except for colon, which averaged 6.9 ± 8.3. Significant copy number variations (CNV’s; amplification validated at greater than or equal to 6 copies) also had a wide range with squamous lung at the highest (11 ± 11), followed by TNBC (5.6 ± 5.0), and then colon (2.3 ± 3.0). Both the CCRCC and pancreatic sets had few CNV's at 0.8 ± 1.5 and 0.17 ± 0.40, respectively. Common mutations identified in the CCRCC set included EPHB6 duplications near S166, which were identified in 25% of samples. Gene specific mutations in CCRCC were also identified in VHL (54%) and SETD2 (21%). These three genes, EPHB6, VHL, and SETD2 have been previously implicated in CCRCC pathogenesis. Six variants identified in VHL were C77*, P86R, Q132fs, A149D, R177fs, and L184fs. Due to the low mutational burden and/or actionable mutations in CCRCC, even large NGS panels may not be adequate to profile somatic mutations and whole exome or whole genome may be more conducive for molecular subtyping of renal cell carcinoma. Citation Format: Susan M. Mockus, Sara E. Patterson, Jason R. Pettus, Gregory J. Tsongalis. Actionable mutations and mutational burden in renal cell carcinoma. [abstract]. In: Proceedings of the 107th Annual Meeting of the American Association for Cancer Research; 2016 Apr 16-20; New Orleans, LA. Philadelphia (PA): AACR; Cancer Res 2016;76(14 Suppl):Abstract nr 4503.