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Advanced and metastatic tumors with complex treatment histories drive cancer mortality. Here we describe the POG570 cohort, a comprehensive whole-genome, transcriptome and clinical dataset, amenable for exploration of the impacts of therapies on genomic landscapes. Previous exposure to DNA-damaging chemotherapies and mutations affecting DNA repair genes, including POLQ and genes encoding Polζ, were associated with genome-wide, therapy-induced mutagenesis. Exposure to platinum therapies coincided with signatures SBS31 and DSB5 and, when combined with DNA synthesis inhibitors, signature SBS17b. Alterations in ESR1, EGFR, CTNNB1, FGFR1, VEGFA and DPYD were consistent with drug resistance and sensitivity. Recurrent noncoding events were found in regulatory region hotspots of genes including TERT, PLEKHS1, AP2A1 and ADGRG6. Mutation burden and immune signatures corresponded with overall survival and response to immunotherapy. Our data offer a rich resource for investigation of advanced cancers and interpretation of whole-genome and transcriptome sequencing in the context of a cancer clinic. Marra and colleagues describe POG570, a pan-cancer, whole-genome, transcriptome and clinical dataset stressing the molecular interactions in advanced and post-therapy cancer patients.

PURPOSE This study investigated therapeutic potential of integrated genome and transcriptome profiling of metastatic sarcoma, a rare but extremely heterogeneous group of aggressive mesenchymal malignancies with few systemic therapeutic options. METHODS Forty-three adult patients with advanced or metastatic non-GI stromal tumor sarcomas of various histology subtypes who were enrolled in the Personalized OncoGenomics program at BC Cancer were included in this study. Fresh tumor tissues along with blood samples underwent whole-genome and transcriptome sequencing. RESULTS The most frequent genomic alterations in this cohort are large-scale structural variation and somatic copy number variation. Outlier RNA expression as well as somatic copy number variations, structural variations, and small mutations together suggest the presence of one or more potential therapeutic targets in the majority of patients in our cohort. Point mutations or deletions in known targetable cancer genes are rare; for example, tuberous sclerosis complex 2 provides a rationale for targeting the mammalian target of rapamycin pathway, resulting in a few patients with exceptional clinical benefit from everolimus. In addition, we observed recurrent 17p11-12 amplifications, which seem to be a sarcoma-specific event. This may suggest that this region harbors an oncogene(s) that is significant for sarcoma tumorigenesis. Furthermore, some sarcoma tumors carrying a distinct mutational signature suggestive of homologous recombination deficiency seem to demonstrate sensitivity to double-strand DNA–damaging agents. CONCLUSION Integrated large-scale genomic analysis may provide insights into potential therapeutic targets as well as novel biologic features of metastatic sarcomas that could fuel future experimental and clinical research and help design biomarker-driven basket clinical trials for novel therapeutic strategies.

Background Precision oncology involves analysis of individual cancer samples to understand the genes and pathways involved in the development and progression of a cancer. To improve patient care, knowledge of diagnostic, prognostic, predisposing, and drug response markers is essential. Several knowledgebases have been created by different groups to collate evidence for these associations. These include the open-access Clinical Interpretation of Variants in Cancer (CIViC) knowledgebase. These databases rely on time-consuming manual curation from skilled experts who read and interpret the relevant biomedical literature. Methods To aid in this curation and provide the greatest coverage for these databases, particularly CIViC, we propose the use of text mining approaches to extract these clinically relevant biomarkers from all available published literature. To this end, a group of cancer genomics experts annotated sentences that discussed biomarkers with their clinical associations and achieved good inter-annotator agreement. We then used a supervised learning approach to construct the CIViCmine knowledgebase. Results We extracted 121,589 relevant sentences from PubMed abstracts and PubMed Central Open Access full-text papers. CIViCmine contains over 87,412 biomarkers associated with 8035 genes, 337 drugs, and 572 cancer types, representing 25,818 abstracts and 39,795 full-text publications. Conclusions Through integration with CIVIC, we provide a prioritized list of curatable clinically relevant cancer biomarkers as well as a resource that is valuable to other knowledgebases and precision cancer analysts in general. All data is publically available and distributed with a Creative Commons Zero license. The CIViCmine knowledgebase is available at http://bionlp.bcgsc.ca/civicmine/.

Manual interpretation of variants remains rate limiting in precision oncology. The increasing scale and complexity of molecular data generated from comprehensive sequencing of cancer samples requires advanced interpretative platforms as precision oncology expands beyond individual patients to entire populations. To address this unmet need, we created the Platform for Oncogenomic Reporting and Interpretation (PORI), comprising an analytic framework created to facilitate the interpretation and reporting of somatic variants in cancer. PORI is unique in its integration of reporting and graph knowledge base tools combined with support for manual curation at the reporting stage. PORI represents one of the first open-source platform alternatives to commercial reporting solutions suitable for comprehensive genomic data sets in precision oncology. We demonstrate the utility of PORI by matching 9,961 TCGA tumours to the graph knowledge base, revealing that 88.2% have at least one potentially targetable alteration, and making available reports describing select individual samples.

Purpose: Immune checkpoint inhibitors (ICI) have revolutionized the treatment of solid tumors with dramatic and durable responses seen across multiple tumor types. However, identifying patients who will respond to these drugs remains challenging, particularly in the context of advanced and previously treated cancers. Experimental Design: We characterized fresh tumor biopsies from a heterogeneous pan-cancer cohort of 98 patients with metastatic predominantly pretreated disease through the Personalized OncoGenomics program at BC Cancer (Vancouver, Canada) using whole genome and transcriptome analysis (WGTA). Baseline characteristics and follow-up data were collected retrospectively. Results: We found that tumor mutation burden, independent of mismatch repair status, was the most predictive marker of time to progression (P = 0.007), but immune-related CD8+ T-cell and M1-M2 macrophage ratio scores were more predictive for overall survival (OS; P = 0.0014 and 0.0012, respectively). While CD274 [programmed death-ligand 1 (PD-L1)] gene expression is comparable with protein levels detected by IHC, we did not observe a clinical benefit for patients with this marker. We demonstrate that a combination of markers based on WGTA provides the best stratification of patients (P = 0.00071, OS), and also present a case study of possible acquired resistance to pembrolizumab in a patient with non–small cell lung cancer. Conclusions: Interpreting the tumor-immune interface to predict ICI efficacy remains challenging. WGTA allows for identification of multiple biomarkers simultaneously that in combination may help to identify responders, particularly in the context of a heterogeneous population of advanced and previously treated cancers, thus precluding tumor type–specific testing.

Advanced and metastatic tumors with complex treatment histories drive cancer mortality. Here we describe the POG570 cohort, a comprehensive whole-genome, transcriptome and clinical dataset, amenable for exploration of the impacts of therapies on genomic landscapes. Previous exposure to DNA-damaging chemotherapies and mutations affecting DNA repair genes, including POLQ and genes encoding Polζ, were associated with genome-wide, therapy-induced mutagenesis. Exposure to platinum therapies coincided with signatures SBS31 and DSB5 and, when combined with DNA synthesis inhibitors, signature SBS17b. Alterations in ESR1, EGFR, CTNNB1, FGFR1, VEGFA and DPYD were consistent with drug resistance and sensitivity. Recurrent noncoding events were found in regulatory region hotspots of genes including TERT, PLEKHS1, AP2A1 and ADGRG6. Mutation burden and immune signatures corresponded with overall survival and response to immunotherapy. Our data offer a rich resource for investigation of advanced cancers and interpretation of whole-genome and transcriptome sequencing in the context of a cancer clinic.

Dramatic and durable responses to immune checkpoint inhibitors (ICIs) have been observed across multiple tumor types, but identifying the patients most likely to respond to these drugs remains challenging, particularly in the context of metastatic and pre-treated disease. Recent clinically approved biomarkers for patient selection are tumor agnostic, but currently all approved markers are evaluated independently. Through the Personalized Onco Genomics (POG) program at BC Cancer, we aimed to study the impact of evaluating multiple biomarkers in a tumor agnostic cohort. We performed whole genome and transcriptome analysis (WGTA) on fresh tumor biopsies from a heterogeneous pan-cancer cohort of 82 patients with advanced metastatic disease subsequently treated with ICIs. Established biomarkers, including tumor mutation burden (TMB) and CD8+ T cell scores, were able to distinguish responders in our advanced and pre-treated cohort. Additionally, we discovered that combining multiple biomarkers provided the best stratification of patients, suggesting a multifaceted approach, such as WGTA, may be suitable for more accurate identification of patients that may benefit from ICIs. As such, we have initiated a Phase II clinical trial, CAPTIV-8 (NCT04273061), which is distinctive in its use of WGTA to evaluate multiple markers including TMB, CD8+ T cell scores, an M1-M2 macrophage score and viral integration to select patients most likely to respond to atezolizumab. Clinical and genomic data prospectively collected from two hundred patients will be evaluated to test the efficacy of combining these biomarkers and identify additional biomarkers of response which can be used to guide treatment with ICIs. Citation Format: Emma Titmuss, Alexandra Pender, Erin Pleasance, Scott Brown, Cameron J. Grisdale, James Topham, Yaoqing Shen, Melika Bonakdar, Gregory A. Taylor, Laura Williamson, Karen Mungall, Eric Chuah, Andrew J. Mungall, Richard A. Moore, Jean-Michel Lavoie, Stephen Yip, Howard Lim, Daniel J. Renouf, Sophie Sun, Steven J. Jones, Robert Holt, Marco A. Marra, Janessa Laskin. CAPTIV-8: A prospective trial of atezolizumab using a multivariate model incorporating whole genome and transcriptome analysis [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2021; 2021 Apr 10-15 and May 17-21. Philadelphia (PA): AACR; Cancer Res 2021;81(13_Suppl):Abstract nr 1647.

Sequencing technology is increasingly essential in clinical cancer management. The majority of clinical cancer sequencing has focused on panel approaches, but recent trials have begun to report the use of transcriptome expression profiling to match patients to therapy. The Personalized OncoGenomics (POG) program at BC Cancer has sequenced over 500 patient tumors, integrating both whole genome and transcriptome data to inform treatment options for patients with advanced or metastatic disease. Here we present 570 patients who were sequenced from 2012 to 2017 and reviewed at the POG multidisciplinary molecular tumor board. Genome and transcriptome information identified clinically actionable targets in 83% (475/570) of sequenced cases, with 37% (209/570) receiving POG-informed therapy. Overall, 248 whole genome and transcriptome sequencing analysis (WGTA)-informed treatments were administered, with some patients receiving multiple treatment courses. Of the treated cases, 46% (114/248) were reported to have physician-assessed clinical benefit. Clinical benefit was assessed as per standard of care rather than strict timing as per RECIST criteria. Mutation, copy number, structural variant, expression, and genome signature data were all used individually or in combination to inform treatments. Treatments based in whole or in part from RNA expression data were the largest subgroup (66.9%, 166/248), and patients in this group had similar proportion of clinical benefit compared to those receiving treatments informed by DNA-based data. Importantly, the use of RNA data resulted in 14.5% (36/248) additional patients receiving WGTA-informed treatments with clinical benefit. Patients were directed to clinical trials, treated with therapeutics in off-label indications, or positioned to genomically-informed standard of care options. For a subset of 42 cases where the planned next line of therapy was documented prior to WGTA analysis, 76.2% (32/42) of genomically-informed standard therapies were different from those which would otherwise have been considered the next line of therapy by the treating clinician, or aided in a decision between multiple different therapy options under consideration. These results emphasize the importance of multiple data types, including expression information, to personalize treatment. We also observe that, in addition to positioning for trials or identifying cases for off-label treatment, choice of standard of care therapies is an important use of genomic data. Overall, our data supports the integration of whole genome and RNA sequencing data in the clinic, with implications both for cancer research and treatment, and ultimately the potential to improve cancer outcomes. Citation Format: Alexandra K. Bohm, Erin Pleasance, Emma Tittmus, Kathleen Wee, Gregory Taylor, Melika Bonakdar, Yaoqing Shen, Laura Williamson, Veronika Csizmok, Martin Jones, Jessica Nelson, Balvir Deol, Caralyn Reisle, Karen Mungall, Eric Chuah, Andrew Mungall, Richard Moore, Sophie Sun, Howard Lim, Daniel Renouf, Steven Jones, Marco Marra, Janessa Laskin. Personalized therapy choice integrating genome and expression data in advanced cancers [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2021; 2021 Apr 10-15 and May 17-21. Philadelphia (PA): AACR; Cancer Res 2021;81(13_Suppl):Abstract nr 98.

The use of comprehensive personal genomic data to guide cancer treatment decisions has demonstrated success in recent years. However, its application to pediatric cancer remains challenging. Most pediatric cancer genomes have relatively few somatic aberrations and the recognized oncogenic drivers are often not targetable. Here we describe a whole genome and transcriptome analysis approach to elucidate the impact of currently un-targetable disease drivers on pathways and regulatory networks within cancer cells, in an effort to identify aberrations that can be targeted therapeutically. In the pediatric personalized oncogenomics (PedsPOG) project, we have analyzed 81 pediatric and young adult cases representing diverse types of relapsed, refractory or very poor prognosis cancers (17 primary central nervous system (CNS), 5 hematopoietic and lymphoid malignancies, and 59 from a variety of non-CNS solid cancers). Patients' ages ranged from 0.4-20.7 years at enrollment, with a median of 11.5 years. For each patient, genomic sequencing data from tumour and normal samples were analysed to detect germline and somatic variants including simple mutations to more complex alterations such as gene fusions, mutation burden and mutation signatures. Tumour transcriptome data was analyzed to identify aberrant gene expression and calculate immune-related signatures such as presence and composition of T cells in the tumour sample. Combined interpretation of germline and somatic variants was used to understand the underlying tumour biology and provide rationale for treatment options. Using the integrated analysis of genomic and transcriptomic data, actionable targets were identified in 80 out of 81 patients (98%), while therapeutic targets would have been identified in only 32-50% of the patients if individual genomic variants were used separately (such as mutation, fusion, and copy number changes). RNA expression data appears to be highly informative, from which targets were detected in 90% of the patients, albeit at lower levels of evidence. In particular, prediction of outlier T-cell presence based on expression data was identified as a potential biomarker which led to favorable response to immune checkpoint inhibition. Twenty-four cases received PedsPOG-informed therapy and disease response was evaluated by RECIST or RANO criteria. Complete response was observed in four patients, and thirteen patients demonstrated partial response or stable disease. In conclusion, the use of whole genome sequencing and transcriptome sequencing has yielded novel findings and therapeutic options in children and adolescents with poor prognosis cancer. Citation Format: Yaoqing Shen, Melika Bonakdar, Laura Williamson, Erin Pleasance, Karen Mungall, Richard A. Moore, Andrew J. Mungall, Stephen Yip, Anna F. Lee, Christopher Dunham, Janessa Laskin, Marco M. Marra, Steven J. Jones, Shahrad R. Rassekh, Rebecca J. Deyell. Application of integrated analysis of whole genome sequencing and RNA sequencing to personalized therapy decision making in pediatric and young adult cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2021; 2021 Apr 10-15 and May 17-21. Philadelphia (PA): AACR; Cancer Res 2021;81(13_Suppl):Abstract nr 260.

Eccrine porocarcinomas (EPs) are rare malignant tumours of the intraepidermic sweat gland duct and most often arise from benign eccrine poromas. Some recurrent somatic genomic events have been identified in these malignancies, but very little is known about the complexity of their molecular pathophysiology. We describe the whole genome and whole transcriptome genomic profiling of a metastatic EP in a 66-year-old male patient with a previous history of localized porocarcinoma of the scalp. Whole genome and whole transcriptome genomic profiling was performed on the metastatic EP. Whole genome sequencing was performed on blood-derived DNA in order to allow a comparison between germline and somatic events. We found somatic copy losses of several tumour suppressor genes including APC, PTEN and CDKN2A, CDKN2B and CDKN1A. We identified a somatic hemizygous CDKN2A pathogenic splice site variant. De novo transcriptome assembly revealed abnormal splicing of CDKN2A p14ARF and p16INK4a. Elevated expression of oncogenes EGFR and NOTCH1 was noted and no somatic mutations were found in these genes. Wnt pathway somatic alterations were also observed. In conclusion, our results suggest that the molecular pathophysiology of malignant EP features high complexity and subtle interactions of multiple key genes. Cell cycle dysregulation and CDKN2A loss of function was found to be a new potential driver in EP tumourigenesis. Moreover, the combination of somatic copy number variants and abnormal gene expression perhaps partly related to epigenetic mechanisms, all likely contribute to the development of this rare malignancy in our patient.

Metastatic adenoid cystic carcinomas (ACCs) can cause significant morbidity and mortality. Because of their slow growth and relative rarity, there is limited evidence for systemic therapy regimens. Recently, molecular profiling studies have begun to reveal the genetic landscape of these poorly understood cancers, and new treatment possibilities are beginning to emerge. The objective is to use whole-genome and transcriptome sequencing and analysis to better understand the genetic alterations underlying the pathology of metastatic and rare ACCs and determine potentially actionable therapeutic targets. We report five cases of metastatic ACC, not originating in the salivary glands, in patients enrolled in the Personalized Oncogenomics (POG) Program at the BC Cancer Agency. Genomic workup included whole-genome and transcriptome sequencing, detailed analysis of tumor alterations, and integration with existing knowledge of drug–target combinations to identify potential therapeutic targets. Analysis reveals low mutational burden in these five ACC cases, and mutation signatures that are commonly observed in multiple cancer types. Notably, the only recurrent structural aberration identified was the well-described MYB-NFIB fusion that was present in four of five cases, and one case exhibited a closely related MYBL1-NFIB fusion. Recurrent mutations were also identified in BAP1 and BCOR, with additional mutations in individual samples affecting NOTCH1 and the epigenetic regulators ARID2, SMARCA2, and SMARCB1. Copy changes were rare, and they included amplification of MYC and homozygous loss of CDKN2A in individual samples. Genomic analysis revealed therapeutic targets in all five cases and served to inform a therapeutic choice in three of the cases to date.

3080 Background: The genomic profiling of breast cancers has led to a greater understanding of the mutational landscape of metastatic breast cancer (MBC) with potential therapeutic implications. Despite these advances, there is a paucity of data regarding the additive value and relevance of gene expression across histological and molecular subtypes, which represents the majority of informative and actionable findings identified in the BC Cancer personalized oncogenomics program (POG). Methods: Informative findings with potential clinical application from whole genome sequencing (WGS) and whole transcriptome sequencing (WTS) in MBC patients between 2012-2018 were reviewed. Variants observed in pathway genes of potential clinical relevance, as defined by a curated list of genes, were examined across histological subtypes. High and low expression outliers relative to TCGA breast cases, defined as expression greater than 98th percentile and FC > 2 compared to Illumina breast dataset and lower than 25th percentile and FC < -2 compared to Illumina breast dataset, respectively, were then analyzed to establish how many outliers were observed in pathways of potential clinical relevance. Results: A total of 113 cases were included. WGS revealed that TP53 was the most frequent single nucleotide variant (SNV) in triple negative breast cancer (23/30, 77%), whereas PIK3CA (37/78, 47%), PTEN (11/78, 14%) and ESR1 (19/78, 24%) were most frequent in ER positive cases and CDKN2A (2/18, 11%) in HER2 positive cases. Across all subtypes, the mTOR and cell cycle pathways were found to have the highest frequency of SNVs, with the identification of 86 and 71 variants, respectively. Expression data for 113 RNA-sequenced patients revealed a high frequency of expression outliers in the mTOR pathway (26 high expression and 424 low expression outlier genes) and cell cycle pathways (35 high expression and 331 low expression outlier genes), but also in the WNT pathway (96 high expression and 490 lower expression outlier genes) and NOTCH pathway (84 high expression and 564 low expression outlier genes). Conclusions: Frequently identified SNVs across histological subtypes were correlated with expression outliers in pathways of clinical relevance in breast cancer. Additional informative findings, in pathways of potential clinical relevance not historically targeted in breast cancer, were identified with WTS. The clinical utility of these findings warrants further study.

We report a case of early-onset pancreatic ductal adenocarcinoma in a patient harboring biallelic MUTYH germline mutations, whose tumor featured somatic mutational signatures consistent with defective MUTYH-mediated base excision repair and the associated driver KRAS transversion mutation p.Gly12Cys. Analysis of an additional 730 advanced cancer cases (N = 731) was undertaken to determine whether the mutational signatures were also present in tumors from germline MUTYH heterozygote carriers or if instead the signatures were only seen in those with biallelic loss of function. We identified two patients with breast cancer each carrying a pathogenic germline MUTYH variant with a somatic MUTYH copy loss leading to the germline variant being homozygous in the tumor and demonstrating the same somatic signatures. Our results suggest that monoallelic inactivation of MUTYH is not sufficient for C:G>A:T transversion signatures previously linked to MUTYH deficiency to arise (N = 9), but that biallelic complete loss of MUTYH function can cause such signatures to arise even in tumors not classically seen in MUTYH-associated polyposis (N = 3). Although defective MUTYH is not the only determinant of these signatures, MUTYH germline variants may be present in a subset of patients with tumors demonstrating elevated somatic signatures possibly suggestive of MUTYH deficiency (e.g., COSMIC Signature 18, SigProfiler SBS18/SBS36, SignatureAnalyzer SBS18/SBS36).

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.

ERBB2 amplification has been identified in ∼5% of KRAS wild-type colorectal cancers (CRCs). A recent clinical trial showed response to HER2-directed therapy in a subset of ERBB2-amplified metastatic CRCs resistant to chemotherapy and EGFR-directed therapy. With the aim of better understanding mechanisms of resistance to HER2-directed and EGFR-directed therapies, we report the complete molecular characterization of two cases of ERBB2-amplified CRC. PCR-free whole-genome sequencing was used to identify mutations, copy-number alterations, structural variations, and losses of heterozygosity. ERBB2 copy number was also measured by fluorescence in situ hybridization. Single-stranded mRNA sequencing was used for gene expression profiling. Immunohistochemistry and protein mass spectrometry were used to quantify HER2 protein expression. The cases showed ERBB2 copy number of 86 and 92, respectively. Both cases were immunohistochemically positive for HER2 according to CRC-specific scoring criteria. Fluorescence in situ hybridization and protein mass spectrometry corroborated significantly elevated ERBB2 copy number and abundance of HER2 protein. Both cases were microsatellite stable and without mutation of RAS pathway genes. Additional findings included altered expression of PTEN, MET, and MUC1 and mutation of PIK3CA. The potential effects of the molecular alterations on sensitivity to EGFR and HER2-directed therapies were discussed. Identification of ERBB2 amplification in CRC is necessary to select patients who may respond to HER2-directed therapy. An improved understanding of the molecular characteristics of ERBB2-amplified CRCs and their potential mechanisms of resistance will be useful for future research into targeted therapies and may eventually inform therapeutic decision-making.

Aim: To investigate feasibility and utility of whole genome and RNA sequencing in cancer care. The use of comprehensive personal genomic information to guide cancer treatment decisions has gained momentum in recent years. Here we present the Personalized Oncogenomics (POG) project launched at British Columbia Cancer Agency in 2012. This project uses paired tumor/normal whole genome and transcriptome sequencing to characterize a patient's tumor and inform treatment options within a clinically relevant time frame. In the past 5 years, around 600 patients with metastatic cancers (including 49 pediatric cases) have been sequenced and analyzed, representing over 50 cancer types. The breadth and depth of data in POG enable the detection of multiple types of alterations, from simple mutations, indels, and copy number changes, to more complex alterations such as gene fusion, mutation signatures, and homologous recombination deficiency score. Incorporation of gene expression data through transcriptome sequencing informs on the impact of observed genomic alterations, and provides information regarding specific diagnosis via expression comparison to other cancer subtypes. All genomic and transcriptomic variants are integrated to build a personalized tumor-specific molecular profile, identify actionable items supported by an in-house knowledgebase and publically available molecular oncology, and characterize each individual tumor by intensive pathway analysis and literature search. Such multidimensional data also impose challenges in interpretation and communication. We developed a pipeline to translate complex genomic data into clinically actionable and hypothetical recommendations for the treatment of individual patients. The pipeline produces two reports: a panel-like report that contains known SNVs and fusions with therapeutic relevance from a collection of more than 4000 events, and a second comprehensive and manually curated report to fully characterize the tumor using the whole genome and transcriptome datasets. Genomic data are presented and discussed at a multidisciplinary molecular tumor board consisting of medical oncologists, pathologists, bioinformaticians, geneticists, and biologists. This approach has enabled clinicians to make informed clinical decisions based on the genomic data integrated with other clinical features, as well as to form new treatment-related hypothesis. POG has shown that use of both whole genome and transcriptome sequencing allows identification of therapeutic targets in a significant proportion of patients. Almost 80% cases were found to have one or more actionable alterations (100% in pediatric cases), and almost one-third of these are defined only using RNA data. Based on molecular tumor board discussion, patients are directed to clinical trials, positioned to genomically informed standard-of-care options, or treated with off-label drugs. With demonstrated effectiveness, the integrative approach developed by POG not only provides molecular insight and treatment options into individual tumors, but also provides a rich resource of molecular data with matched clinical information that will aid our understanding of tumor biology and therapy response mechanisms to inform treatment strategies in the future. Citation Format: Yaoqing Shen, Martin R. Jones, Erin Pleasance, Melika Bonakdar, Carolyn Ch'ng, Caralyn Reisle, Laura Williamson, Elisa Majounie, Greg Taylor, Simon Chan, Brandon Pierce, Wei Zhang, Amir Muhammadzadeh, Eric Y. Zhao, Dustin Bleile, Karen Mungall, Nina Thiessen, Eric Chuah, Tina Wong, Richard Corbett, Yussanne Ma, Richard A. Moore, Andrew J. Mungall, Yongjun Zhao, Stephen Yip, Anna F. Lee, Rod Rassekh, Rebecca Deyell, Howard Lim, Daniel Renouf, Robyn Roscoe, Steven J.M Jones, Janessa Laskin, Marco A. Marra. Clinical application of whole genome and transcriptome sequencing in cancer care [abstract]. In: Proceedings of the AACR-NCI-EORTC International Conference: Molecular Targets and Cancer Therapeutics; 2017 Oct 26-30; Philadelphia, PA. Philadelphia (PA): AACR; Mol Cancer Ther 2018;17(1 Suppl):Abstract nr A184.