With more than 40 peer-reviewed scientific publications, findings from the POG program are influencing precision oncology approaches around the world.

POG publications

The Journal of Pathology: Clinical Research
Publication Abstract

In this study, we evaluate the impact of whole genome and transcriptome analysis (WGTA) on predictive molecular profiling and histologic diagnosis in a cohort of advanced malignancies. WGTA was used to generate reports including molecular alterations and site/tissue of origin prediction. Two reviewers analyzed genomic reports, clinical history, and tumor pathology. We used National Comprehensive Cancer Network (NCCN) consensus guidelines, Food and Drug Administration (FDA) approvals, and provincially reimbursed treatments to define genomic biomarkers associated with approved targeted therapeutic options (TTOs). Tumor tissue/site of origin was reassessed for most cases using genomic analysis, including a machine learning algorithm (Supervised Cancer Origin Prediction Using Expression [SCOPE]) trained on The Cancer Genome Atlas data. WGTA was performed on 652 cases, including a range of primary tumor types/tumor sites and 15 malignant tumors of uncertain histogenesis (MTUH). At the time WGTA was performed, alterations associated with an approved TTO were identified in 39 (6%) cases; 3 of these were not identified through routine pathology workup. In seven (1%) cases, the pathology workup either failed, was not performed, or gave a different result from the WGTA. Approved TTOs identified by WGTA increased to 103 (16%) when applying 2021 guidelines. The histopathologic diagnosis was reviewed in 389 cases and agreed with the diagnostic consensus after WGTA in 94% of non-MTUH cases (n = 374). The remainder included situations where the morphologic diagnosis was changed based on WGTA and clinical data (0.5%), or where the WGTA was non-contributory (5%). The 15 MTUH were all diagnosed as specific tumor types by WGTA. Tumor board reviews including WGTA agreed with almost all initial predictive molecular profile and histopathologic diagnoses. WGTA was a powerful tool to assign site/tissue of origin in MTUH. Current efforts focus on improving therapeutic predictive power and decreasing cost to enhance use of WGTA data as a routine clinical test.

BMC Medical Genomics
Authors
Emma Titmuss, Richard D Corbett, Scott Davidson, Sanna Abbasi, Laura M Williamson, Erin D Pleasance, Adam Shlien, Daniel J Renouf, Steven J M Jones, Janessa Laskin, Marco A Marra
Publication Abstract

Background: Tumor mutation burden (TMB) is a key characteristic used in a tumor-type agnostic context to inform the use of immune checkpoint inhibitors (ICI). Accurate and consistent measurement of TMB is crucial as it can significantly impact patient selection for therapy and clinical trials, with a threshold of 10 mutations/Mb commonly used as an inclusion criterion. Studies have shown that the most significant contributor to variability in mutation counts in whole genome sequence (WGS) data is differences in analysis methods, even more than differences in extraction or library construction methods. Therefore, tools for improving consistency in whole genome TMB estimation are of clinical importance.

Methods: We developed a distributable TMB analysis suite, TMBur, to address the need for genomic TMB estimate consistency in projects that span jurisdictions. TMBur is implemented in Nextflow and performs all analysis steps to generate TMB estimates directly from fastq files, incorporating somatic variant calling with Manta, Strelka2, and Mutect2, and microsatellite instability profiling with MSISensor. These tools are provided in a Singularity container downloaded by the workflow at runtime, allowing the entire workflow to be run identically on most computing platforms. To test the reproducibility of TMBur TMB estimates, we performed replicate runs on WGS data derived from the COLO829 and COLO829BL cell lines at multiple research centres. The clinical value of derived TMB estimates was then evaluated using a cohort of 90 patients with advanced, metastatic cancer that received ICIs following WGS analysis. Patients were split into groups based on a threshold of 10/Mb, and time to progression from initiation of ICIs was examined using Kaplan-Meier and cox-proportional hazards analyses.

Results: TMBur produced identical TMB estimates across replicates and at multiple analysis centres. The clinical utility of TMBur-derived TMB estimates were validated, with a genomic TMB ≥ 10/Mb demonstrating improved time to progression, even after correcting for differences in tumor type (HR = 0.39, p = 0.012).

Conclusions: TMBur, a shareable workflow, generates consistent whole genome derived TMB estimates predictive of response to ICIs across multiple analysis centres. Reproducible TMB estimates from this approach can improve collaboration and ensure equitable treatment and clinical trial access spanning jurisdictions.

Keywords: Immune checkpoint inhibitors; Tumor mutation burden; Whole genome and transcriptome analysis (WGTA).

NPJ Precis Oncology
Authors
Erica S Tsang, Veronika Csizmok, Laura M Williamson, Erin Pleasance, James T Topham, Joanna M Karasinska, Emma Titmuss, Intan Schrader, Stephen Yip, Basile Tessier-Cloutier, Karen Mungall, Tony Ng, Sophie Sun, Howard J Lim, Jonathan M Loree, Janessa Laskin, Marco A Marra, Steven J M Jones, David F Schaeffer, Daniel J Renouf
Publication Abstract

There is emerging evidence about the predictive role of homologous recombination deficiency (HRD), but this is less defined in gastrointestinal (GI) and thoracic malignancies. We reviewed whole genome (WGS) and transcriptomic (RNA-Seq) data from advanced GI and thoracic cancers in the Personalized OncoGenomics trial (NCT02155621) to evaluate HRD scores and single base substitution (SBS)3, which is associated with BRCA1/2 mutations and potentially predictive of defective HRD. HRD scores were calculated by sum of loss of heterozygosity, telomeric allelic imbalance, and large-scale state transitions scores. Regression analyses examined the association between HRD and time to progression on platinum (TTPp). We included 223 patients with GI (n = 154) or thoracic (n = 69) malignancies. TTPp was associated with SBS3 (p < 0.01) but not HRD score in patients with GI malignancies, whereas neither was associated with TTPp in thoracic malignancies. Tumors with gBRCA1/2 mutations and a somatic second alteration exhibited high SBS3 and HRD scores, but these signatures were also present in several tumors with germline but no somatic second alterations, suggesting silencing of the wild-type allele or BRCA1/2 haploinsufficiency. Biallelic inactivation of an HR gene, including loss of XRCC2 and BARD1, was identified in BRCA1/2 wild-type HRD tumors and these patients had prolonged response to platinum. Thoracic cases with high HRD score were associated with high RECQL5 expression (p ≤ 0.025), indicating another potential mechanism of HRD. SBS3 was more strongly associated with TTPp in patients with GI malignancies and may be complementary to using HRD and BRCA status in identifying patients who benefit from platinum therapy.

Current Oncology
Authors
Emma Titmuss, Irene S Yu, Erin D Pleasance, Laura M Williamson, Karen Mungall, Andrew J Mungall, Daniel J Renouf, Richard Moore, Steven J M Jones, Marco A Marra, Janessa J Laskin, Kerry J Savage
Publication Abstract

Immune checkpoint inhibitors (ICIs) are increasingly used in the treatment of many tumor types, and durable responses can be observed in select populations. However, patients may exhibit significant immune-related adverse events (irAEs) that may lead to morbidity. There is limited information on whether the presence of specific germline mutations may highlight those at elevated risk of irAEs. We evaluated 117 patients with metastatic solid tumors or hematologic malignancies who underwent genomic analysis through the ongoing Personalized OncoGenomics (POG) program at BC Cancer and received an ICI during their treatment history. Charts were reviewed for irAEs. Whole genome sequencing of a fresh biopsy and matched normal specimens (blood) was performed at the time of POG enrollment. Notably, we found that MHC class I alleles in the HLA-B27 family, which have been previously associated with autoimmune conditions, were associated with grade 3 hepatitis and pneumonitis (q = 0.007) in patients treated with combination PD-1/PD-L1 and CTLA-4 inhibitors, and PD-1 inhibitors in combination with IDO-1 inhibitors. These data highlight that some patients may have a genetic predisposition to developing irAEs.

Nature Communications
Authors
Rebecca J Deyell, Yaoqing Shen, Emma Titmuss, Katherine Dixon, Laura M Williamson, Erin Pleasance, Jessica M T Nelson, Sanna Abbasi, Martin Krzywinski, Linlea Armstrong, Melika Bonakdar, Carolyn Ch'ng, Eric Chuah, Chris Dunham, Alexandra Fok, Martin Jones, Anna F Lee, Yussanne Ma, Richard A Moore, Andrew J Mungall, Karen L Mungall, Paul C Rogers, Kasmintan A Schrader, Alice Virani, Kathleen Wee, Sean S Young, Yongjun Zhao, Steven J M Jone, Janessa Laskin, Marco A Marra, Shahrad R Rassekh
Publication Abstract

The role for routine whole genome and transcriptome analysis (WGTA) for poor prognosis pediatric cancers remains undetermined. Here, we characterize somatic mutations, structural rearrangements, copy number variants, gene expression, immuno-profiles and germline cancer predisposition variants in children and adolescents with relapsed, refractory or poor prognosis malignancies who underwent somatic WGTA and matched germline sequencing. Seventy-nine participants with a median age at enrollment of 8.8 y (range 6 months to 21.2 y) are included. Germline pathogenic/likely pathogenic variants are identified in 12% of participants, of which 60% were not known prior. Therapeutically actionable variants are identified by targeted gene report and whole genome in 32% and 62% of participants, respectively, and increase to 96% after integrating transcriptome analyses. Thirty-two molecularly informed therapies are pursued in 28 participants with 54% achieving a clinical benefit rate; objective response or stable disease ≥6 months. Integrated WGTA identifies therapeutically actionable variants in almost all tumors and are directly translatable to clinical care of children with poor prognosis cancers.

Melanoma Research
Authors
Irene S Yu, Kathleen Wee, Laura Williamson , Emma Titmuss, Jianghong An, Sheida Naderi-Azad, Corey Metcalf, Stephen Yip, Basil Horst, Steven J M Jones, Katherine Paton, Brad H Nelson, Marco Marra, Janessa J Laskin, Kerry J Savage.
Publication Abstract

Uveal melanoma is the most common intraocular malignancy and has a poor prognosis compared to other melanoma subtypes with a median overall survival of 6-10 months. With immune checkpoint inhibitor therapy, either PD-1 inhibitor alone or combination ipilimumab/nivolumab (anti-CTLA-4/anti-PD-1), responses are rare and often not durable. We present a case report of a now 66-year-old woman with diffuse metastatic uveal melanoma previously treated with a combination of ipilimumab/nivolumab, followed by maintenance nivolumab. Almost complete resolution of all sites of metastatic disease was observed except for one liver metastasis which regressed partially on immunotherapy. Notably, the patient had a significantly elevated BMI and developed widespread vitiligo on treatment. Whole-genome and transcriptome analysis was performed on the residual liver biopsy and molecular markers that may have contributed to the exceptional response were investigated. Several alterations were observed in genes involved in T-cell responses. Estimates of tumour infiltrating immune cells indicated a high level of plasma cells compared to other uveal melanoma cases, a finding previously associated with indolent disease. The patient also carried several germline SNPs that may have contributed to her treatment response as well as widespread vitiligo. Whole-genome and transcriptome sequencing have provided insight into potential molecular underpinnings of an exceptional treatment response in a tumour type typically associated with poor prognosis. Immunological findings suggest a role for plasma cells in the tumour microenvironment. Elevated BMI and the development of vitiligo may be clinically relevant factors for predicting response to immune checkpoint inhibitor therapy, warranting further studies in patients with uveal melanoma.

Annals of Oncology
Authors
Pleasance E, Bohm A, Williamson LM, Nelson JMT, Shen Y, Bonakdar M, Titmuss E, Csizmok V, Wee K, Hosseinzadeh S, Grisdale CJ, Reisle C, Taylor GA, Lewis E, Jones MR, Bleile D, Sadeghi S, Zhang W, Davies A, Pellegrini B, Wong T, Bowlby R, Chan SK, Mungall KL, Chuah E, Mungall AJ, Moore RA, Zhao Y, Deol B, Fisic A, Fok A, Regier DA, Weymann D, Schaeffer DF, Young S, Yip S, Schrader K, Levasseur N, Taylor SK, Feng X, Tinker A, Savage KJ, Chia S, Gelmon K, Sun S, Lim H, Renouf DJ, Jones SJM, Marra MA, Laskin J.
Publication Abstract

Background: Recent advances are enabling delivery of precision genomic medicine to cancer clinics. While the majority of approaches profile panels of selected genes or hotspot regions, comprehensive data provided by whole genome and transcriptome sequencing and analysis (WGTA) presents an opportunity to align a much larger proportion of patients to therapies.

Patients and methods: Samples from 570 patients with advanced or metastatic cancer of diverse types enrolled in the Personalized OncoGenomics (POG) program underwent WGTA. DNA-based data, including mutations, copy number, and mutation signatures, were combined with RNA-based data, including gene expression and fusions, to generate comprehensive WGTA profiles. A multidisciplinary molecular tumour board used WGTA profiles to identify and prioritize clinically actionable alterations and inform therapy. Patient responses to WGTA-informed therapies were collected.

Results: Clinically actionable targets were identified for 83% of patients, 37% of whom received WGTA-informed treatments. RNA expression data were particularly informative, contributing to 67% of WGTA-informed treatments; 25% of treatments were informed by RNA expression alone. Of a total 248 WGTA-informed treatments, 46% resulted in clinical benefit. RNA expression data were comparable to DNA-based mutation and copy number data in aligning to clinically beneficial treatments. Genome signatures also guided therapeutics including platinum, PARP inhibitors, and immunotherapies. Patients accessed WGTA-informed treatments through clinical trials (19%), off-label use (35%), and as standard therapies (46%) including those which would not otherwise have been the next choice of therapy, demonstrating the utility of genomic information to direct use of chemotherapies as well as targeted therapies.

Conclusions: Integrating RNA expression and genome data illuminated treatment options that resulted in 46% of treated patients experiencing positive clinical benefit, supporting the use of comprehensive WGTA profiling in clinical cancer care.

Cold Spring Harbor Molecular Case Studies
Authors
Jean-Michel Lavoie, Veronika Csizmok, Laura M Williamson, Luka Culibrk, Gang Wang, Marco A Marra, Janessa Laskin, Steven JM Jones, Daniel J Renouf, Christian K Kollmannsberger.
Publication Abstract

Adrenocortical cancer (ACC) is a rare cancer of the adrenal gland. Several driver mutations have been identified in both primary and metastatic ACCs, but the therapeutic options are still limited. We performed whole-genome and transcriptome sequencing on seven patients with metastatic ACC. Integrative analysis of mutations, RNA expression changes, mutation signature, and homologous recombination deficiency (HRD) analysis was performed. Mutations affecting CTNNB1 and TP53 and frequent loss of heterozygosity (LOH) events were observed in our cohort. Alterations affecting genes involved in cell cycle (RB1CDKN2ACDKN2B), DNA repair pathways (MUTYHBRCA2ATMRAD52MLH1MSH6), and telomere maintenance (TERF2 and TERT) consisting of somatic and germline mutations, structural variants, and expression outliers were also observed. HRDetect, which aggregates six HRD-associated mutation signatures, identified a subset of cases as HRD. Genomic alterations affecting genes involved in epigenetic regulation were also identified, including structural variants (SWI/SNF genes and histone methyltransferases), and copy gains and concurrent high expression of KDM5A, which may contribute to epigenomic deregulation. Findings from this study highlight HRD and epigenomic pathways as potential therapeutic targets and suggest a subgroup of patients may benefit from a diverse array of molecularly targeted therapies in ACC, a rare disease in urgent need of therapeutic strategies.

Journal of Molecular Diagnostics
Authors
Tammy TY Lau, Zahra Jalali Sefid Dashti, Emma Titmuss, Alexandra Pender, James T Topham, Joshua Bridgers, Jonathan M Loree, Xiaolan Feng, Erin D Pleasance, Daniel J Renouf, Kasmintan A Schrader, Sophie Sun, Cheryl Ho, Marco Marra, Janessa Laskin, Aly Karsan
Publication Abstract

Tumor mutation burden (TMB) is a measure to predict patient responsiveness to immune checkpoint immunotherapy since with increased mutation frequency, the likelihood of a greater neoantigen burden is increased. Although neoantigen prediction tools exist, tumor neoantigen burden (TNB) has not been adopted as measures to predict immunotherapy response. With both measures, current guidelines are limited to the coding regions, but ectopic expression of sequences in the noncoding space may potentially be a source of neoantigens. Here we analyzed a pan-cancer cohort of 574 advanced disease stage patients with whole genome and transcriptome sequencing to report mutation burden and neoantigen counts within the coding and noncoding regions. We evaluated the efficacy of TNB, reported as tumor neoantigen counts (TNC), including neoantigens derived from the expression of noncoding regions, compared to TMB as a predictor of response to immunotherapy for 80 patients who had received treatment. We found that TMB was the best predictor of response to immunotherapy, whereas expression derived TNC from the noncoding regions did not improve prediction of response. Therefore, there is minimal benefit in extending the calculation of TNC to the noncoding space for the purposes of predicting response. However, it is likely that there is a wealth of neoantigens derived from the noncoding space that may impact patient outcomes and treatments.

Journal of Community Genetics
Authors
Deirdre Weymann, Janessa Laskin, Steven JM Jones, Robyn Roscoe, Howard J Lim, Daniel J Renouf, Kasmintan A Schrader, Sophie Sun, Stephen Yip, Marco A Marra, Dean A Regier
Publication Abstract

Genomic research is driving discovery for future population beneft. Limited evidence exists on immediate patient and health system impacts of research participation. This study uses real-world data and quasi-experimental matching to examine early-stage cost and health impacts of research-based genomic sequencing. British Columbia’s Personalized OncoGenomics (POG) single-arm program applies whole genome and transcriptome analysis (WGTA) to characterize genomic landscapes in advanced cancers. Our cohort includes POG patients enrolled between 2014 and 2015 and 1:1 genetic algorithm–matched usual care controls. We undertake a cost consequence analysis and estimate 1-year efects of WGTA on patient management, patient survival, and health system costs reported in 2015 Canadian dollars. WGTA costs are imputed and forecast using system of equations modeling. We use Kaplan-Meier survival analysis to explore survival diferences and inverse probability of censoring weighted linear regression to estimate mean 1-year survival times and costs. Non-parametric bootstrapping simulates sampling distributions and enables scenario analysis, revealing drivers of incremental costs, survival, and net monetary beneft for assumed willingness to pay thresholds. We identifed 230 POG patients and 230 matched controls for cohort inclusion. The mean period cost of research-funded WGTA was $26,211 (SD: $14,191). Sequencing costs declined rapidly, with WGTA forecasts hitting $13,741 in 2021. The incremental healthcare system efect (non-research expenditures) was $5203 (95% CI: 75, 10,424) compared to usual care. No overall survival diferences were observed, but outcome heterogeneity was present. POG patients receiving WGTA-informed treatment experienced incremental survival gains of 2.49 months (95% CI: 1.32, 3.64). Future cost consequences became favorable as WGTA cost drivers declined and WGTAinformed treatment rates improved to 60%. Our study demonstrates the ability of real-world data to support evaluations of only-in-research health technologies. We identify situations where precision oncology research initiatives may produce survival beneft at a cost that is within healthcare systems’ willingness to pay. This economic evidence informs the early-stage healthcare impacts of precision oncology research.

POG-associated publications

Nature Communications
Authors
Caralyn Reisle, Laura M Williamson, Erin Pleasance, Anna Davies, Brayden Pellegrini, Dustin W Bleile, Karen L Mungall, Eric Chuah, Martin R Jones, Yussanne Ma, Eleanor Lewis, Isaac Beckie, David Pham, Raphael Matiello Pletz, Amir Muhammadzadeh, Brandon M Pierce, Jacky Li, Ross Stevenson, Hansen Wong, Lance Bailey, Abbey Reisle, Matthew Douglas, Melika Bonakdar, Jessica MT Nelson, Cameron J Grisdale, Martin Krzywinski, Ana Fisic, Teresa Mitchell, Daniel J Renouf, Stephen Yip, Janessa Laskin, Marco A Marra, Steven JM Jones
Publication Abstract

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 introduce a Platform for Oncogenomic Reporting and Interpretation (PORI), comprising an analytic framework that facilitates the interpretation and reporting of somatic variants in cancer. PORI integrates reporting and graph knowledge base tools combined with support for manual curation at the reporting stage. PORI represents an open-source platform alternative to commercial reporting solutions suitable for comprehensive genomic data sets in precision oncology. We demonstrate the utility of PORI by matching 9,961 pan-cancer genome atlas tumours to the graph knowledge base, calculating therapeutically informative alterations, and making available reports describing select individual samples.

Cell Reports
Authors
Yiqun Zhang, Fengju Chen, Erin Pleasance, Laura Williamson, Cameron J Grisdale, Emma Titmuss, Janessa Laskin, Steven JM Jones, Isidro Cortes-Ciriano, Marco A Marra, Chad J Creighton
Publication Abstract

The global impact of somatic structural variants (SVs) on gene regulation in advanced tumors with complex treatment histories has been mostly uncharacterized. Here, using whole-genome and RNA sequencing from 570 recurrent or metastatic tumors, we report the altered expression of hundreds of genes in association with nearby SV breakpoints, including oncogenes and G-protein-coupled receptor-related genes such as PLEKHG2. A significant fraction of genes with SV-expression associations correlate with worse patient survival in primary and advanced cancers, including SRD5A1. In many instances, SV-expression associations involve retrotransposons being translocated near genes. High overall SV burden is associated with treatment with DNA alkylating agents or taxanes and altered expression of metabolism-associated genes. SV-expression associations within tumors from topoisomerase I inhibitor-treated patients include chromatin-related genes. Within anthracycline-treated tumors, SV breakpoints near chromosome 1p genes include PDE4B. Patient treatment and history can help understand the widespread SV-mediated cis-regulatory alterations found in cancer.

Frontiers in Genetics
Authors
Simon Haile, Richard D. Corbett, Veronique G. LeBlanc, Lisa Wei, Stephen Pleasance, Steve Bilobram, Ka Ming Nip, Kirstin Brown, Eva Trinh, Jillian Smith, Diane L. Trinh, Miruna Bala, Eric Chuah, Robin J. N. Coope, Richard A. Moore, Andrew J. Mungall, Karen L. Mungall, Yongjun Zhao, Martin Hirst, Samuel Aparicio, Inanc Birol, Steven J. M. Jones, Marco A. Marra
Publication Abstract

RNA sequencing (RNAseq) has been widely used to generate bulk gene expression measurements collected from pools of cells. Only relatively recently have single-cell RNAseq (scRNAseq) methods provided opportunities for gene expression analyses at the single-cell level, allowing researchers to study heterogeneous mixtures of cells at unprecedented resolution. Tumors tend to be composed of heterogeneous cellular mixtures and are frequently the subjects of such analyses. Extensive method developments have led to several protocols for scRNAseq but, owing to the small amounts of RNA in single cells, technical constraints have required compromises. For example, the majority of scRNAseq methods are limited to sequencing only the 3' or 5' termini of transcripts. Other protocols that facilitate full-length transcript profiling tend to capture only polyadenylated mRNAs and are generally limited to processing only 96 cells at a time. Here, we address these limitations and present a novel protocol that allows for the high-throughput sequencing of full-length, total RNA at single-cell resolution. We demonstrate that our method produced strand-specific sequencing data for both polyadenylated and non-polyadenylated transcripts, enabled the profiling of transcript regions beyond only transcript termini, and yielded data rich enough to allow identification of cell types from heterogeneous biological samples.

Cancer Medicine, 2020
Authors
Julia R Naso, James T Topham, Joanna M Karasinska, Michael K C Lee, Steve E Kalloger, Hui-Li Wong, Jessica Nelson, Richard A Moore, Andrew J Mungall, Steven J M Jones, Janessa Laskin, Marco A Marra, Daniel J Renouf, David F Schaeffer
Publication Abstract

Background: RNA-sequencing-based classifiers can stratify pancreatic ductal adenocarcinoma (PDAC) into prognostically significant subgroups but are not practical for use in clinical workflows. Here, we assess whether histomorphological features may be used as surrogate markers for predicting molecular subgroup and overall survival in PDAC.

Methods: Ninety-six tissue samples from 50 patients with non-resectable PDAC were scored for gland formation, stromal maturity, mucin, necrosis, and neutrophil infiltration. Prognostic PDAC gene expression classifiers were run on all tumors using whole transcriptome sequencing data from the POG trial (NCT02155621). Findings were validated using digital TCGA slides (n = 50). Survival analysis used multivariate Cox proportional-hazards tests and log-rank tests.

Results: The combination of low gland formation and low neutrophil infiltration was significantly associated with the poor prognosis PDAC molecular subgroup (basal-like or squamous) and was an independent predictor of shorter overall survival, in both frozen section (n = 47) and formalin-fixed paraffin-embedded (n = 49) tissue samples from POG patients, and in the TCGA samples. This finding held true in the subgroup analysis of primary (n = 17) and metastatic samples (n = 79). The combination of high gland formation and high neutrophils had low sensitivity but high specificity for favorable prognosis subgroups.

Conclusions: The assessment of gland formation and neutrophil infiltration on routine histological sections can aid in prognostication and allow inferences to be made about molecular subtype, which may help guide patient management decisions and contribute to our understanding of heterogeneity in treatment response.

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The Journal Of Pathology, 2020
Publication Abstract

The practical application of genome-scale technologies to precision oncology research requires flexible tissue processing strategies that can be used to differentially select both tumour and normal cell populations from formalin-fixed paraffin-embedded tissues. As tumour sequencing scales towards clinical implementation, practical difficulties in scheduling and obtaining fresh tissue biopsies at scale, including blood samples as surrogates for matched "normal" DNA, have focused attention on the use of formalin-preserved clinical samples collected routinely for diagnostic purposes. In practice, such samples often contain both tumour and normal cells which, if correctly partitioned, could be used to profile both tumour and normal genomes, thus identifying somatic alterations. Here we report a semi-automated method for laser microdissecting entire slide-mounted tissue sections to enrich for cells of interest with sufficient yield for whole genome and transcriptome sequencing. Using this method, we demonstrated enrichment of tumour material from mixed tumour-normal samples by up to 67%. Leveraging new methods that allow for the extraction of high-quality nucleic acids from small amounts of formalin-fixed tissues, we further showed that the method was successful in yielding sequence data of sufficient quality for use in BC Cancer's Personalized OncoGenomics (POG) program.

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Clinical Cancer Research, 2020
Authors
James T Topham, Joanna M Karasinska, Michael Kuan-Ching Lee, Veronika Csizmok, Laura M Williamson, Gun Ho Jang, Robert E Denroche, Erica S Tsang, Steve E Kalloger, Hui-Li Wong, Grainne M O'Kane, Richard A Moore, Andrew J Mungall, Faiyaz Notta, Jonathan M Loree, Julie M Wilson, Oliver F Bathe, Patricia A Tang, Rachel A Goodwin, Jennifer J Knox, Steven Gallinger, Janessa Laskin, Marco A Marra, Steven JM Jones, Daniel J Renouf, David F Schaeffer.
Publication Abstract

Background RNA-sequencing-based subtyping of pancreatic ductal adenocarcinoma (PDAC) has been reported by multiple research groups, each using different methodologies and patient cohorts. 'Classical' and 'basal-like' PDAC subtypes are associated with survival differences, with basal-like tumors associated with worse prognosis. We amalgamated various PDAC subtyping tools to evaluate the potential of such tools to be reliable in clinical practice. Methods Sequencing data for 574 PDAC tumors was obtained from prospective trials and retrospective public databases. Six published PDAC subtyping strategies (Moffitt regression tools, clustering-based Moffitt, Collisson, Bailey, and Karasinska subtypes) were employed on each sample, and results were tested for subtype call consistency and association with survival. Results Basal-like and classical subtype calls were concordant in 88% of patient samples, and survival outcomes were significantly different (p<0.05) between prognostic subtypes. 12% of tumors had subtype-discordant calls across the different methods, showing intermediate survival in univariate and multivariate survival analyses. Transcriptional profiles compatible with that of a hybrid subtype signature were observed for subtype-discordant tumors, in which classical and basal-like genes were concomitantly expressed. Subtype-discordant tumors showed intermediate molecular characteristics, including subtyping gene expression (p<0.0001) and mutant KRAS allelic imbalance (p<0.001). Conclusions Nearly one in six patients with PDAC have tumors that fail to reliably fall into the classical or basal-like PDAC subtype categories, based on two regression tools aimed towards clinical practice. Rather, these patient tumors show intermediate prognostic and molecular traits. We propose close consideration of the non-binary nature of PDAC subtypes for future incorporation of subtyping into clinical practice.

Clinical Cancer Research, 2020
Authors
Erica S Tsang, James T Topham, Joanna M Karasinska, Michael Kuan-Ching Lee, Laura M Williamson, Shehara Mendis, Robert E Denroche, Gun Ho Jang, Steve E Kalloger, Richard A Moore, Andrew J Mungall, Oliver F Bathe, Patricia A Tang, Faiyaz Notta, Julie M Wilson, Janessa Laskin, Grainne M O'Kane, Jennifer J Knox, Rachel A Goodwin, Jonathan M Loree, Steven JM Jones, Marco A Marra, Steven Gallinger, David F Schaeffer, Daniel J Renouf
Publication Abstract

Purpose: With the rising incidence of early-onset pancreatic cancer (EOPC), molecular characteristics that distinguish early-onset pancreatic ductal adenocarcinoma (PDAC) tumors from those arising at a later age are not well understood.

Experimental design: We performed bioinformatic analysis of genomic and transcriptomic data generated from 269 advanced (metastatic or locally advanced) and 277 resectable PDAC tumor samples. Patient samples were stratified into EOPC (age of onset ≤55 years; n = 117), intermediate (age of onset 55-70 years; n = 264), and average (age of onset ≥70 years; n = 165) groups. Frequency of somatic mutations affecting genes commonly implicated in PDAC, as well as gene expression patterns, were compared between EOPC and all other groups.

Results: EOPC tumors showed significantly lower frequency of somatic single-nucleotide variant (SNV)/insertions/deletions (indel) in CDKN2A (P = 0.0017), and were more likely to achieve biallelic mutation of CDKN2A through homozygous copy loss as opposed to heterozygous copy loss coupled with a loss-of-function SNV/indel mutation, the latter of which was more common for tumors with later ages of onset (P = 1.5e-4). Transcription factor forkhead box protein C2 (FOXC2) was significantly upregulated in EOPC tumors (P = 0.032). Genes significantly correlated with FOXC2 in PDAC samples were enriched for gene sets related to epithelial-to-mesenchymal transition (EMT) and included VIM (P = 1.8e-8), CDH11 (P = 6.5e-5), and CDH2 (P = 2.4e-2).

Conclusions: Our comprehensive analysis of sequencing data generated from a large cohort of PDAC patient samples highlights a distinctive pattern of biallelic CDKN2A mutation in EOPC tumors. Increased expression of FOXC2 in EOPC, with the correlation between FOXC2 and EMT pathways, represents novel molecular characteristics of EOPC.

Molecular Cancer Therapeutics, 2020
Authors
James T. Topham, Emma Titmuss, Erin D Pleasance, Laura M Williamson, Joanna M Karasinska, Luka Culibrk, Michael Kuan-Ching Lee, Shehara Mendis, Robert E Denroche, Gun-Ho Jang, Steve E Kalloger, Hui-Li Wong, Richard A Moore, Andrew J. Mungall, Grainne M O'Kane, Jennifer J. Knox, Steven Gallinger, Jonathan M Loree, Dixie L Mager, Janessa Laskin, Marco A. Marra, Steven JM Jones, David F Schaeffer and Daniel J Renouf
Publication Abstract

Next-generation sequencing of solid tumors has revealed variable signatures of immunogenicity across tumors, but underlying molecular characteristics driving such variation are not fully understood. While expression of endogenous retrovirus (ERV)-containing transcripts can provide a source of tumor-specific neoantigen in some cancer models, associations between ERV levels and immunogenicity across different types of metastatic cancer are not well established. We performed bioinformatics analysis of genomic, transcriptomic and clinical data across an integrated cohort of 199 metastatic breast, colorectal and pancreatic ductal adenocarcinoma (PDAC) patient tumors. Within each cancer type, we identified a subgroup of viral mimicry tumors in which increased ERV levels were coupled with transcriptional signatures of autonomous antiviral response and immunogenicity. In addition, viral mimicry colorectal and pancreatic tumors showed increased expression of DNA demethylation gene TET2. Taken together, these data demonstrate the existence of an ERV-associated viral mimicry phenotype across three distinct metastatic cancer types, while indicating links between ERV abundance, epigenetic dysregulation and immunogenicity.

JAMA Network Open, 2019
Authors
Olena M. Vaske, Isabel Bjork, Sofie R. Salama, Holly Beale, Avanthi Tayi Shah, Lauren Sanders, Jacob Pfeil, Du L. Lam, Katrina Learned, Ann Durbin, Ellen T. Kephart, Rob Currie, Yulia Newton, Teresa Swatloski, Duncan McColl, John Vivian, Jingchun Zhu, Alex G. Lee, Stanley G. Leung, Aviv Spillinger, Heng-Yi Liu, Winnie S. Liang, Sara A. Byron, Michael E. Berens, Adam C. Resnick, Norman Lacayo, Sheri L. Spunt, Arun Rangaswami, Van Huynh, Lilibeth Torno, Ashley Plant, Ivan Kirov, Keri B. Zabokrtsky, S. Rod Rassekh, Rebecca J. Deyell, Janessa Laskin, Marco A. Marra, Leonard S. Sender, Sabine Mueller, E. Alejandro Sweet-Cordero, Theodore C. Goldstein, David Haussler,
Publication Abstract

Importance: Pediatric cancers are epigenetic diseases; therefore, considering tumor gene expression information is necessary for a complete understanding of the tumorigenic processes.

Objective: To evaluate the feasibility and utility of incorporating comparative gene expression information into the precision medicine framework for difficult-to-treat pediatric and young adult patients with cancer.

Design, setting, and participants: This cohort study was conducted as a consortium between the University of California, Santa Cruz (UCSC) Treehouse Childhood Cancer Initiative and clinical genomic trials. RNA sequencing (RNA-Seq) data were obtained from the following 4 clinical sites and analyzed at UCSC: British Columbia Children's Hospital (n = 31), Lucile Packard Children's Hospital at Stanford University (n = 80), CHOC Children's Hospital and Hyundai Cancer Institute (n = 46), and the Pacific Pediatric Neuro-Oncology Consortium (n = 24). The study dates were January 1, 2016, to March 22, 2017.

Exposures: Participants underwent tumor RNA-Seq profiling as part of 4 separate clinical trials at partner hospitals. The UCSC either downloaded RNA-Seq data from a partner institution for analysis in the cloud or provided a Docker pipeline that performed the same analysis at a partner institution. The UCSC then compared each participant's tumor RNA-Seq profile with more than 11 000 uniformly analyzed tumor profiles from pediatric and young adult patients with cancer, downloaded from public data repositories. These comparisons were used to identify genes and pathways that are significantly overexpressed in each patient's tumor. Results of the UCSC analysis were presented to clinical partners.

Main outcomes and measures: Feasibility of a third-party institution (UCSC Treehouse Childhood Cancer Initiative) to obtain tumor RNA-Seq data from patients, conduct comparative analysis, and present analysis results to clinicians; and proportion of patients for whom comparative tumor gene expression analysis provided useful clinical and biological information.

Results: Among 144 samples from children and young adults (median age at diagnosis, 9 years; range, 0-26 years; 72 of 118 [61.0%] male [26 patients sex unknown]) with a relapsed, refractory, or rare cancer treated on precision medicine protocols, RNA-Seq-derived gene expression was potentially useful for 99 of 144 samples (68.8%) compared with DNA mutation information that was potentially useful for only 34 of 74 samples (45.9%).

Conclusions and relevance: This study's findings suggest that tumor RNA-Seq comparisons may be feasible and highlight the potential clinical utility of incorporating such comparisons into the clinical genomic interpretation framework for difficult-to-treat pediatric and young adult patients with cancer. The study also highlights for the first time to date the potential clinical utility of harmonized publicly available genomic data sets.

Biotechniques, 2019
Authors
Pawan K Pandoh, Richard D Corbett, Helen McDonald, Miguel Alcaide, Heather Kirk, Eva Trinh, Simon Haile, Tina MacLeod, Duane Smailus, Steve Bilobram, Andrew J Mungall, Yussanne Ma, Richard A Moore, Robin Coope, Yongjun Zhao, Steven JM Jones, Robert A Holt, Aly Karsan, Ryan D Morin, Marco A Marra
Publication Abstract

The analysis of cell-free circulating tumor DNA (ctDNA) is potentially a less invasive, more dynamic assessment of cancer progression and treatment response than characterizing solid tumor biopsies. Standard isolation methods require separation of plasma by centrifugation, a time-consuming step that complicates automation. To address these limitations, we present an automatable magnetic bead-based ctDNA isolation method that eliminates centrifugation to purify ctDNA directly from peripheral blood (PB). To develop and test our method, ctDNA from cancer patients was purified from PB and plasma. We found that allelic fractions of somatic single-nucleotide variants from target gene capture libraries were comparable, indicating that the PB ctDNA purification method may be a suitable replacement for the plasma-based protocols currently in use.

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