Publications

Recurrent activating point mutations in KRAS are critical drivers in pancreatic cancer and have been attributed to resistance to anti-epidermal growth factor receptor therapy in colorectal cancer. Although KRAS genotyping provides limited clinical utility in the diagnosis and management of pancreatic cancer patients at present, inferences about the fractional abundance of KRAS mutations may inform on tumor purity in traditionally challenging clinical specimens and their potential use in precision medicine. KRAS genetic testing has indeed become an essential tool to guide treatment decisions in colorectal cancer, but an unmet need for methods standardization exists. Here, we present a unique droplet digital PCR method that enables the simultaneous detection and quantification of KRAS exon 2, 3, and 4 point mutations and copy number alterations. We have validated 13 mutations (G12S, G12R, G12D, G12A, G12V, G12C, G13D, G60V, Q61H, Q61L, A146V, A146T, and A146P) and focal KRAS amplifications by conducting this assay in a cohort of 100 DNA samples extracted from fresh frozen tumor biopsies, formaldehyde-fixed, paraffin-embedded tissue, and liquid biopsy specimens. Despite its modest lower limit of detection (approximately 1%), this assay will be a rapid cost-effective means to infer the purity of biopsy specimens carrying KRAS mutations and can be used in noninvasive serial monitoring of circulating tumor DNA to evaluate clinical response and/or detect early signs of relapse.

Measuring gene expression of tumor clones at single-cell resolution links functional consequences to somatic alterations. Without scalable methods to simultaneously assay DNA and RNA from the same single cell, parallel single-cell DNA and RNA measurements from independent cell populations must be mapped for genome-transcriptome association. We present clonealign, which assigns gene expression states to cancer clones using single-cell RNA and DNA sequencing independently sampled from a heterogeneous population. We apply clonealign to triple-negative breast cancer patient-derived xenografts and high-grade serous ovarian cancer cell lines and discover clone-specific dysregulated biological pathways not visible using either sequencing method alone.

In its third edition, the Vancouver Autophagy Symposium presented a platform for vibrant discussion on the differential roles of macroautophagy/autophagy in disease. This one-day symposium was held at the BC Cancer Research Centre in Vancouver, BC, bringing together experts in cell biology, protein biochemistry and medicinal chemistry across several different disease models and model organisms. The Vancouver Autophagy Symposium featured 2 keynote speakers that are well known for their seminal contributions to autophagy research, Dr. David Rubinsztein (Cambridge Institute for Medical Research) and Dr. Kay F. Macleod (University of Chicago). Key discussions included the context-dependent roles and mechanisms of dysregulation of autophagy in diseases and the corresponding need to consider context-dependent autophagy modulation strategies. Additional highlights included the differential roles of bulk autophagy versus selective autophagy, novel autophagy regulators, and emerging chemical tools to study autophagy inhibition. Interdisciplinary discussions focused on addressing questions such as which stage of disease to target, which type of autophagy to target and which component to target for autophagy modulation. : AD: Alzheimer disease; AMFR/Gp78: autocrine motility factor receptor; CCCP: carbonyl cyanide -chlorophenylhydrazone; CML: chronic myeloid leukemia; CVB3: coxsackievirus B3; DRPLA: dentatorubral-pallidoluysian atrophy; ER: endoplasmic reticulum; ERAD: ER-associated degradation; FA: focal adhesion; HCQ: hydroxychloroquine; HD: Huntingtin disease; HIF1A/Hif1α: hypoxia inducible factor 1 subunit alpha; HTT: huntingtin; IM: imatinib mesylate; MAP1LC3B: microtubule associated protein 1 light chain 3 beta; NBR1: neighbour of BRCA1; OGA: O-GlcNAcase; PDAC: pancreatic ductal adenocarcinoma; PLEKHM1: pleckstrin homology and RUN domain containing M1; polyQ: poly-glutamine; ROS: reactive oxygen species; RP: retinitis pigmentosa; SNAP29: synaptosome associated protein 29; SPCA3: spinocerebellar ataxia type 3; TNBC: triple-negative breast cancer.

Antimicrobial peptides (AMPs) exhibit broad-spectrum antimicrobial activity, and have promise as new therapeutic agents. While the adult North American bullfrog (Rana [Lithobates] catesbeiana) is a prolific source of high-potency AMPs, the aquatic tadpole represents a relatively untapped source for new AMP discovery. The recent publication of the bullfrog genome and transcriptomic resources provides an opportune bridge between known AMPs and bioinformatics-based AMP discovery. The objective of the present study was to identify novel AMPs with therapeutic potential using a combined bioinformatics and wet lab-based approach. In the present study, we identified seven novel AMP precursor-encoding transcripts expressed in the tadpole. Comparison of their amino acid sequences with known AMPs revealed evidence of mature peptide sequence conservation with variation in the prepro sequence. Two mature peptide sequences were unique and demonstrated bacteriostatic and bactericidal activity against Mycobacteria but not Gram-negative or Gram-positive bacteria. Nine known and seven novel AMP-encoding transcripts were detected in premetamorphic tadpole back skin, olfactory epithelium, liver, and/or tail fin. Treatment of tadpoles with 10 nM 3,5,3'-triiodothyronine for 48 h did not affect transcript abundance in the back skin, and had limited impact on these transcripts in the other three tissues. Gene mapping revealed considerable diversity in size (1.6-15 kbp) and exon number (one to four) of AMP-encoding genes with clear evidence of alternative splicing leading to both prepro and mature amino acid sequence diversity. These findings verify the accuracy and utility of the bullfrog genome assembly, and set a firm foundation for bioinformatics-based AMP discovery.

Super-Seniors are healthy, long-lived individuals who were recruited at age 85 years or older with no history of cancer, cardiovascular disease, diabetes, dementia, or major pulmonary disease. In a 10-year follow-up, we aimed to determine whether surviving Super-Seniors showed compression of morbidity, and to test whether the allele frequencies of longevity-associated variants in APOE and FOXO3 were more extreme in such long-term survivors.

Optimizing the quality of proteomics data collected from a mass spectrometer (MS) requires careful selection of acquisition parameters and proper assessment of instrument performance. Software tools capable of extracting a broad set of information from raw files, including meta, scan, quantification, and identification data, are needed to provide guidance for MS system management. In this work, direct extraction and utilization of these data is demonstrated using RawTools, a standalone tool for extracting meta and scan data directly from raw MS files generated on Thermo Orbitrap instruments. RawTools generates summarized and detailed plain text outputs after parsing individual raw files, including scan rates and durations, duty cycle characteristics, precursor and reporter ion quantification, and chromatography performance. RawTools also contains a diagnostic module that includes an optional "preview" database search for facilitating informed decision-making related to optimization of MS performance based on a variety of metrics. RawTools has been developed in C# and utilizes the Thermo RawFileReader library and thus can process raw MS files with high speed and high efficiency on all major operating systems (Windows, MacOS, Linux). To demonstrate the utility of RawTools, the extraction of meta and scan data from both individual and large collections of raw MS files was carried out to identify problematic characteristics of instrument performance. Taken together, the combined rich feature-set of RawTools with the capability for interrogation of MS and experiment performance makes this software a valuable tool for proteomics researchers.

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.

The self-immunopeptidome is the repertoire of all self-peptides that can be presented by the combination of MHC variants carried by an individual, defined by their HLA genotype. Each MHC variant presents a distinct set of self-peptides, and the number of peptides in a set is variable. Subjects carrying MHC variants that present fewer self-peptides should also present fewer mutated peptides, resulting in decreased immune pressure on tumor cells. To explore this, we predicted peptide-MHC binding values using all unique 8-11mer human peptides in the human proteome and all available HLA class I allelic variants, for a total of 134 billion unique peptide--MHC binding predictions. From these predictions, we observe that most peptides are able to be presented by relatively few (< 250) MHC, while some can be presented by upwards of 1,500 different MHC. There is substantial overlap among the repertoires of peptides presented by different MHC and no relationship between the number of peptides presented and HLA population frequency. Nearly 30% of self-peptides are presentable by at least one MHC, leaving 70% of the human peptidome unsurveyed by T cells. We observed similar distributions of predicted self-immunopeptidome sizes in cancer subjects compared to controls, and within the pan-cancer population, predicted self-immunopeptidome size combined with mutational load to predict survival. Self-immunopeptidome analysis revealed evidence for tumor immunoediting and identified specific peptide positions that most influence immunogenicity. Because self-immunopeptidome size is defined by HLA genotypes and approximates neoantigen load, HLA genotyping could offer a rapid predictive biomarker for response to immunotherapy.

Liquid biopsies are rapidly emerging as powerful tools for the early detection of cancer, noninvasive genomic profiling of localized or metastatic tumors, prompt detection of treatment resistance-associated mutations, and monitoring of therapeutic response and minimal residual disease in patients during clinical follow-up. Growing evidence strongly supports the utility of circulating tumor DNA (ctDNA) as a biomarker for the stratification and clinical management of lymphoma patients. However, ctDNA is diluted by variable amounts of cell-free DNA (cfDNA) shed by nonneoplastic cells causing a background signal of wild-type DNA that limits the sensitivity of methods that rely on DNA sequencing. Here, we describe an error suppression method for single-molecule counting that relies on targeted sequencing of cfDNA libraries constructed with semi-degenerate barcode adapters. Custom pools of biotinylated DNA baits for target enrichment can be designed to specifically track somatic mutations in one patient, survey mutation hotspots with diagnostic and prognostic value or be comprised of comprehensive gene panels with broad patient coverage in lymphoma. Such methods are amenable to track ctDNA levels during longitudinal liquid biopsy testing with high specificity and sensitivity and characterize, in real time, the genetic profiles of tumors without the need of standard invasive biopsies. The analysis of ultra-deep sequencing data according to the bioinformatics pipelines also described in this chapter affords to harness lower limits of detection for ctDNA below 0.1%.