Marra Lab

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.

Background: To support the implementation of high-throughput pipelines suitable for SARS-CoV-2 sequencing and analysis in a clinical laboratory, we developed an automated sample preparation and analysis workflow.

Methods: We used the established ARTIC protocol with ∼400 bp amplicons sequenced on Oxford Nanopore's MinION. Sequences were analyzed using Nextclade, assigning both a clade and quality score to each sample.

Results: 2,179 samples on twenty-five 96-well plates were sequenced. Plates of purified RNA were processed within 12 hours, sequencing required up to 24 hours and analysis of each pooled plate required one hour. The use of samples with known Ct values enabled normalization, acted as a QC check, and revealed a strong correlation between sample Ct values and successful analysis, with 85% of samples with Ct < 30 achieving a "Good" Nexclade score. Less abundant samples responded to enrichment with the fraction of Ct > 30 samples achieving a "Good" classification rising by 60% after addition of a post-ARTIC PCR normalization. Serial dilutions of three variant of concern samples, diluted from Ct∼16 to Ct∼50, demonstrated successful sequencing to Ct 37. The sample set contained a median of 24 mutations per sample and a total of 1,281 unique mutations with reduced sequence read coverage noted in some regions of some samples. A total of ten separate strains were observed in the sample set, including three variants of concern prevalent in British Columbia in the spring of 2021.

Conclusions: We demonstrated a robust automated sequencing pipeline that takes advantage of input Ct values to improve reliability.

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.

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.

Glioblastomas (GBMs) are aggressive brain tumors characterized by extensive inter- and intratumor heterogeneity. Patient-derived models, such as organoids and explants, have recently emerged as useful models to study such heterogeneity, although the extent to which they can recapitulate GBM genomic features remains unclear. Here, we analyze bulk exome and single-cell genome and transcriptome profiles of 12 IDH wild-type GBMs, including two recurrent tumors, and of patient-derived explants (PDEs) and gliomasphere (GS) lines derived from these tumors. We find that PDEs are genetically similar to, and variably retain gene expression characteristics of, their parent tumors. Notably, PDEs appear to exhibit similar levels of transcriptional heterogeneity compared with their parent tumors, whereas GS lines tend to be enriched for cells in a more uniform transcriptional state. The approaches and datasets introduced here will provide a valuable resource to help guide experiments using GBM-derived models, especially in the context of studying cellular heterogeneity.

Background: Classifying diffuse large B-cell lymphoma (DLBCL) into cell-of-origin (COO) subtypes could allow for personalized cancer control. Evidence suggests that subtype-guided treatment may be beneficial in the activated B-cell (ABC) subtype of DLBCL, among patients under the age of 60.

Methods: We estimated the cost-effectiveness of age- and subtype-specific treatment guided by gene expression profiling (GEP). A probabilistic Markov model examined costs and quality-adjusted life-years gained (QALY) accrued to patients under GEP-classified COO treatment over a 10-year time horizon. The model was calibrated to evaluate the adoption of ibrutinib as a first line treatment among patients under 60 years with ABC subtype DLBCL. The primary data source for efficacy was derived from published estimates of the PHOENIX trial. These inputs were supplemented with patient-level, real-world data from BC Cancer, which provides comprehensive cancer services to the population of British Columbia.

Results: We found the cost-effectiveness of GEP-guided treatment vs. standard care was $77,806 per QALY (24.3% probability of cost-effectiveness at a willingness-to-pay (WTP) of $50,000/QALY; 53.7% probability at a WTP of $100,000/QALY) for first-line treatment. Cost-effectiveness was dependent on assumptions around decision-makers' WTP and the cost of the assay.

Conclusions: We encourage further clinical trials to reduce uncertainty around the implementation of GEP-classified COO personalized treatment in this patient population.

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.

Glioblastomas harbor diverse cell populations, including rare glioblastoma stem cells (GSCs) that drive tumorigenesis. To characterize functional diversity within this population, we performed single-cell RNA sequencing on >69,000 GSCs cultured from the tumors of 26 patients. We observed a high degree of inter- and intra-GSC transcriptional heterogeneity that could not be fully explained by DNA somatic alterations. Instead, we found that GSCs mapped along a transcriptional gradient spanning two cellular states reminiscent of normal neural development and inflammatory wound response. Genome-wide CRISPR-Cas9 dropout screens independently recapitulated this observation, with each state characterized by unique essential genes. Further single-cell RNA sequencing of >56,000 malignant cells from primary tumors found that the majority organize along an orthogonal astrocyte maturation gradient yet retain expression of founder GSC transcriptional programs. We propose that glioblastomas grow out of a fundamental GSC-based neural wound response transcriptional program, which is a promising target for new therapy development.

Poorly differentiated chordoma (PDC) is a recently recognized subtype of chordoma characterized by expression of the embryonic transcription factor, brachyury, and loss of INI1. PDC primarily affects children and is associated with a poor prognosis and limited treatment options. Here we describe the molecular and immune tumour microenvironment profiles of two paediatric PDCs produced using whole-genome, transcriptome and whole-genome bisulfite sequencing (WGBS) and multiplex immunohistochemistry. Our analyses revealed the presence of tumour-associated immune cells, including CD8+ T cells, and expression of the immune checkpoint protein, PD-L1, in both patient samples. Molecular profiling provided the rationale for immune checkpoint inhibitor (ICI) therapy, which resulted in a clinical and radiographic response. A dominant T cell receptor (TCR) clone specific for a brachyury peptide-MHC complex was identified from bulk RNA sequencing, suggesting that targeting of the brachyury tumour antigen by tumour-associated T cells may underlie this clinical response to ICI. Correlative analysis with rhabdoid tumours, another INI1-deficient paediatric malignancy, suggests that a subset of tumours may share common immune phenotypes, indicating the potential for a therapeutically targetable subgroup of challenging paediatric cancers.

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.

Capicua (CIC)'s transcriptional repressor function is implicated in neurodevelopment and in oligodendroglioma (ODG) aetiology. However, CIC's role in these contexts remains obscure, primarily from our currently limited knowledge regarding its biological functions. Moreover, CIC mutations in ODG invariably co-occur with a neomorphic IDH1/2 mutation, yet the functional relationship between these two genetic events is unknown. Here, we analysed models derived from an E6/E7/hTERT-immortalized (i.e. p53- and RB-deficient) normal human astrocyte cell line. To examine the consequences of CIC loss, we compared transcriptomic and epigenomic profiles between CIC wildtype and knockout cell lines, with and without mutant IDH1 expression. Our analyses revealed dysregulation of neurodevelopmental genes in association with CIC loss. CIC ChIP-seq was also performed to expand upon the currently limited ensemble of known CIC target genes. Among the newly identified direct CIC target genes were EPHA2 and ID1, whose functions are linked to neurodevelopment and the tumourigenicity of in vivo glioma tumour models. NFIA, a known mediator of gliogenesis, was discovered to be uniquely overexpressed in double mutant cells (CIC-knockout + IDH1-mutant). These results identify neurodevelopment and specific genes within this context as candidate targets through which CIC alterations may contribute to the progression of IDH-mutant gliomas. This article is protected by copyright. All rights reserved.

Pancreatic neuroendocrine neoplasms (PNENs) are biologically and clinically heterogeneous. Here, we use a multi-omics approach to uncover the molecular factors underlying this heterogeneity. Transcriptomic analysis of 84 PNEN specimens, drawn from two cohorts, is substantiated with proteomic profiling and identifies four subgroups: Proliferative, PDX1-high, Alpha cell-like and Stromal/Mesenchymal. The Proliferative subgroup, consisting of both well- and poorly differentiated specimens, is associated with inferior overall survival probability. The PDX1-high and Alpha cell-like subgroups partially resemble previously described subtypes, and we further uncover distinctive metabolism-related features in the Alpha cell-like subgroup. The Stromal/Mesenchymal subgroup exhibits molecular characteristics of YAP1/WWTR1(TAZ) activation suggestive of Hippo signaling pathway involvement in PNENs. Whole-exome sequencing reveals subgroup-enriched mutational differences, supported by activity inference analysis, and identifies hypermorphic proto-oncogene variants in 14.3% of sequenced PNENs. Our study reveals differences in cellular signaling axes that provide potential directions for PNEN patient stratification and treatment strategies.

Glioblastomas harbor diverse cell populations, including rare glioblastoma stem cells (GSCs) that drive tumorigenesis. To characterize functional diversity within this population, we performed single-cell RNA sequencing on >69,000 GSCs cultured from the tumors of 26 patients. We observed a high degree of inter- and intra-GSC transcriptional heterogeneity that could not be fully explained by DNA somatic alterations. Instead, we found that GSCs mapped along a transcriptional gradient spanning two cellular states reminiscent of normal neural development and inflammatory wound response. Genome-wide CRISPR–Cas9 dropout screens independently recapitulated this observation, with each state characterized by unique essential genes. Further single-cell RNA sequencing of >56,000 malignant cells from primary tumors found that the majority organize along an orthogonal astrocyte maturation gradient yet retain expression of founder GSC transcriptional programs. We propose that glioblastomas grow out of a fundamental GSC-based neural wound response transcriptional program, which is a promising target for new therapy development.

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