Marco Marra

Professor

Research Classification

Genomics
Bioinformatics
Molecular Genetics
Cancer Genetics
Genes
Genetic Mapping

Research Interests

Cancer biology
genomics
Epigenomics
Bioinformatics
Genetics

Relevant Degree Programs

 

Research Methodology

Ultra high throughput DNA sequencing
Computational Biology
Single cell genomes and transcriptomes
molecular biology
biochemistry
cell culture

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Doctoral students
Postdoctoral Fellows
Any time / year round

Biomarker / gene signature discovery / Personalized genomic medicine / Cancer evolution / Cancer genome landscapes / Functional genomics

I am interested in hiring Co-op students for research placements.

Graduate Student Supervision

Doctoral Student Supervision (Jan 2008 - May 2019)
Bioinformatic approaches for identifying single nucleotide variants and profiling alternative expression in cancer transcriptomes (2018)

Over the last decade, the advent of high-throughput sequencing (HTS) has given us the ability to study DNA and RNA sequences at nucleotide resolution at an unprecedented speed and at a relatively low cost. This has been an invaluable tool in the study of cancer, allowing projects such as The Cancer Genome Atlas and the International Cancer Genome Consortium to sequence thousands of tumours from multiple cancer types. The ever-increasing amounts of data created by these projects demanded new analysis methods: in the first part of this thesis, I focus on method development for mutation calling in genome and transcriptome data. I present SNVMix, a single nucleotide variant (SNV) caller based on a set of probabilistic models created to adapt to variations in allele representation in a tumour. Differential allele representation in DNA can occur when multiple clones are present in the sequenced tumour, and in RNA can occur due to differences in gene expression or allele bias. These situations are nearly ubiquitously encountered in cancer sequencing studies, and thus need to be accounted for. I demonstrate that SNVMix was able to outperform another contemporary SNV caller that does not account for variations in allele representation. I also present BWA-R, an adaptation of the Burrows Wheeler Aligner, that can properly align RNA-Seq paired-end reads to a genome reference extended with exon-exon junction sequences formed through splicing. I show that BWA-R provides better alignments for SNV calling in transcriptomes, resulting in an increase in the proportion of true positive calls obtained. In the second part of this thesis, I analyze RNA-Seq data from a triple negative breast cancer (TNBC) cohort and describe the alternative splicing profiles of the previously defined Basal and NonBasal subgroups. TNBC is characterized by the absence of estrogen and progesterone receptors and human epidermal growth factor receptor 2 (HER2), which precludes the use of currently available targeted therapies. TNBC patients are thus treated with chemotherapy, and outcomes are generally poor. I identify alternatively expressed genes that may be relevant to the biology of these two subgroups and that could provide clues for further studies or treatment options.

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The MEF2B regulatory network (2017)

Myocyte enhancer factor 2B (MEF2B) is a transcription factor with somatic mutation hotspots at K4, Y69 and D83 in diffuse large B-cell lymphoma (DLBCL) and follicular lymphoma. The recurrence of these mutations indicates that they may drive lymphoma development. However, inferring the mechanisms by which they may drive lymphoma development was complicated by our limited understanding of MEF2B’s normal functions. To expand our understanding of the cellular activities of wildtype and mutant MEF2B, I developed and addressed two hypotheses: (1) identifying genes regulated by wildtype MEF2B will allow identification of cellular phenotypes affected by MEF2B activity and (2) contrasting the DNA binding sites, effects on gene expression and effects on cellular phenotypes of mutant and wildtype MEF2B will indicate mechanisms through which MEF2B mutations may contribute to lymphoma development. To address these hypotheses, I first identified genome-wide MEF2B binding sites and transcriptome-wide gene expression changes mediated by MEF2B. Using these data I identified and validated novel MEF2B target genes. I found that target genes of MEF2B included the cancer genes MYC, TGFB1, CARD11, NDRG1, RHOB, BCL2 and JUN. The identification of target genes led to findings that MEF2B promotes expression of mesenchymal markers, promotes HEK293A cell migration, and inhibits DLBCL cell chemotaxis. I then investigated how K4E, Y69H and D83V mutations change MEF2B’s activity. I found that K4E, Y69H and D83V mutations decreased MEF2B’s capacity to promote gene expression in both HEK293A and DLBCL cells. These mutations also reduced MEF2B’s capacity to alter HEK293A and DLBCL cell movement. Overall, these data support the concept that MEF2B mutations may promote lymphoma development by reducing expression of MEF2B target genes that would otherwise function to help confine germinal centre B-cells to germinal centres. My research demonstrates how observations from genome-scale data can aid in the functional characterization of candidate driver mutations. Moreover, my work provides a unique resource for exploring the role of MEF2B in cell biology. I map for the first time the MEF2B regulome, demonstrating connections between a relatively understudied transcription factor and genes significant to oncogenesis.

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miRNA sequence analysis reveals cancer subtypes that correlate with tumour characteristics and patient outcomes (2016)

microRNAs (miRNAs) are small 17-25nt RNA molecules that regulate gene expression at the post-transcriptional level. A given miRNA may have up to several hundred gene targets, and 60% of messenger RNAs (mRNAs) have binding sites for multiple miRNAs in their 3’- untranslated regions (UTRs). miRNAs have been implicated in the regulation of numerous biological processes, including cellular growth, differentiation and apoptosis, and miRNA dysregulation has been associated with diseases including cancers. miRNAs are stable and robust in a variety of fresh and preserved human tissues, and thus are useful in disease classification and subtype identification. They have also been used to infer dysregulation of regulatory pathways.With the aims of identifying cancer subtypes and relating these to clinical covariates and studying miRNA-mediated regulation, I analyzed miRNA-seq and mRNA-seq expression profiles from diffuse large B-cell lymphomas (DLBCL), pediatric acute myeloid leukemias (AML) and pediatric malignant rhabdoid tumours (MRT).My analyses provided comprehensive characterization of miRNA expression profiles, revealed molecular sub-groups within cancer types, novel miRNA species, putative miRNA prognostic markers, and candidate functional miRNA:mRNA interactions. Of note, I discovered a novel miRNA (miR-10393-3p) that was preferentially expressed in DLBCL samples, and further revealed that it could target genes involved in chromatin modification. I also found that the miR-106a-363 cluster was not only significantly associated with inferior patient outcomes in pediatric AML, but may also contribute to treatment resistance by modulating the expression of genes involved in oxidative phosphorylation. In addition, I performed hierarchical clustering of MRT miRNA profiles together with those of 11,753 other samples representing 36 cancer types and 26 normal tissue types. This analysis demonstrated that MRT samples are most similar to cerebellum and DLBCL samples, possibly reflecting a related cell of origin as these samples. Overall, the research presented in this thesis constitutes a step forward in our understanding of miRNA dysregulation within cancer types and identifies miRNAs that could be useful prognostic markers in guiding treatment selection.

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Computational tools for CNV detection using probe-level analysis of affymetrix SNP arrays: application to the study of CNVs in follicular lymphoma (2013)

No abstract available.

Genomic studies of the normal and malignant neural crest (2012)

Neuroblastoma (NBL) is an enigmatic pediatric tumor of the sympathetic nervous system that is lethal in most children diagnosed over 18 months of age with metastatic disease. NBL is thought to originate from a differentiation arrest of the neural crest, a vertebrate-specific cell lineage with one of the most diverse developmental potentials. Genomic studies of NBL have contributed to the development of new diagnostic and prognostic markers. In addition, somatic and germline mutations in the ALK oncogene have been identified and are being targeted clinically. Based on this prior work, two hypotheses were developed and addressed in this thesis: (1) characterization of NBL with higher resolution genomic technologies will lead to the identification of novel loci that contribute to the disease and (2) analysis of the transcriptome of normal neural crest cells will help identify loci of relevance to NBL. To address these hypotheses I used several datasets generated from microarrays as well as RNA and DNA sequencing experiments. Two key results have emerged from this analysis including the putative role of the BRCA1/BARD1 pathway in the development of NBL, and the heterogeneity of the genetic landscape of primary NBL tumors. Potential translational avenues for the results reported in this thesis are the exploration of AURKB and MAPK inhibitors as treatment agents for NBL.

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Mutation discovery and characterizaion in lymphoid neoplasms using massively parallel RNA and DNA sequencing (2012)

No abstract available.

Bioinformatic analysis of cis-encoded antisense transcription (2011)

A key first step in understanding cellular processes is a quantitative and comprehensive measurement of gene expression profiles. The scale and complexity of the mammalian transcriptome is a significant challenge to efforts aiming to identify the complete set of expressed transcripts. Specifically, detection of low-abundance sequences, such as antisense transcripts, has historically been difficult to achieve using EST libraries, microarrays, or tag sequencing methods. Antisense transcripts are expressed from the opposite strand of a partner gene, and in some cases can regulate the processing of the sense transcript, highlighting their biological relevance. Recently, efficient profiling of low-frequency transcripts was made possible with the advent of next generation sequencing platforms. Thus, a major goal of my thesis was to assess the prevalence of antisense transcripts using Tag-seq, a tag sequencing method modified to take advantage of the Illumina sequencing platform. The increase in sampling depth provided by Tag-seq resulted in significantly improved detection of low abundance antisense transcripts, and allowed accurate measurements of their differential expression across normal and cancerous states. While antisense transcription is known to regulate sense transcript processing at a small number of loci, no genome wide assessments of this regulatory interaction exist. I addressed this knowledge gap using Affymetrix exon arrays, and found a significant correlation between antisense transcription and alternative splicing in normal human cells. Further exploring the biological relevance of antisense-correlated splicing events in human disease, I found that these events could be used to identify clinically distinct subtypes of cancer. Together, the findings in this thesis provide a new foundation for the investigation of antisense transcripts in the regulation of alternative transcript processing, and open new avenues of research into understanding the molecular heterogeneity of human cancers.

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Analysis of primary human cancers : from single genes to whole transcriptomes (2010)

Cells in the human body contain DNA genomes that encode instructions regulating their biology. Accumulation of somatic DNA sequence alterations such as point mutations and structural rearrangements can disrupt critical genes resulting in malignant cancer phenotypes. Identification of cancer “drivers” is a central goal of cancer genome analysis due to their causation of oncogenesis and potential as diagnostic and therapeutic targets. Analysis of normal polymorphisms can also impact the treatment of cancer by identifying individuals most likely to benefit from specific therapies. To uncover molecular correlates with treatment outcome, my graduate work has focused on applying DNA sequencing technology to clinical cancer patient samples. In an early example of medical oncogenomics, I evaluated mutations and amplifications of a single gene, EGFR, in patient tumour samples and investigated associations with response to an EGFR inhibitor, gefitinib. This study was challenged by limited nucleic acid quantities available from small or microdissected tissue biopsies. Therefore, I next characterized bias induced by a whole genome amplification technique and demonstrated genotype and copy number analysis using amplified material. To investigate the role that normal polymorphisms play in guiding cancer treatment, my third project sought to correlate DNA repair gene polymorphisms with the development of late side effects following radiation therapy for prostate cancer. Late side effects were associated with variants in three genes, uncovered by sequencing the exons of eight DNA repair genes in patients with varying degrees of radiosensitivity. Advancements in DNA sequencing technologies have enabled a move beyond candidate gene approaches towards gaining sequence and expression information from all expressed genes (i.e. the transcriptome). Utilizing second generation sequencing technology, my final project was a transcriptome analysis of lung tumours prior to treatment with the EGFR inhibitor, erlotinib. I uncovered gene expression profiles specific to clinical subgroups and, in one case, detected expression of the Epstein-Barr virus. The second phase of this project will validate putative somatic mutations identified by transcriptome sequencing and investigate viral involvement in other lung tumours. Genome sequence information is becoming readily extracted from clinical sources and there is great potential to use this information to effectively guide cancer treatment.

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Methods for transcript variant discovery and alternative expression analysis : application to the study of fluorouracil resistance in colorectal cancer (2010)

RNA transcripts are expressed from tens of thousands of loci across the human genome. Several studies have suggested that many genes are alternatively expressed to produced multiple mRNA isoforms and many of these remain undiscovered. Identifying specific isoforms associated with human diseases such as cancer has potential to lead to improved treatments. The scale and complexity of the transcriptome present significant barriers to (1) identifying isoforms and (2) applying knowledge to human disease research. Recent advances in genome-wide microarray and sequencing platforms have begun to provide the capacity and resolution to address these challenges. The goal of this thesis was to develop novel methods that allow genome-wide identification and quantification of mRNA isoforms. I first approached this problem by creating a microarray design platform for alternative expression analysis called 'ALEXA-array' (www.AlexaPlatform.org). To evaluate the ALEXA-array approach I used it to generate a microarray design that I then used to measure differential expression of mRNA isoforms in 5-fluorouracil (5-FU) sensitive and resistant colorectal cancer cell lines. This approach identified several isoforms potentially involved in 5-FU resistance. While the ALEXA-array approach was successful, I identified several limitations of the method. For example, the approach was insensitive to isoforms with small differences in sequence content and limited by both the transcriptome annotations and the number of microarray features available at design time. I developed a second method, ‘ALEXA-seq’, to take advantage of advances in massively parallel sequencing. Applying this method to the same cell lines I showed that the approach was able to overcome many limitations of the microarray approach. Several additional candidate 5-FU resistance isoforms were identified. Both the ALEXA-array and ALEXA-seq approaches identified expression of an aberrant isoform of the uridine monophosphate synthetase as a top candidate. Interestingly, this gene was suspected to function in the conversion of 5-FU to active anti-cancer metabolites. Additional characterization was performed to elucidate the expression pattern, transcript diversity and sequence variation of this gene in a panel of cell lines and tumours. The methods presented here should help to identify mRNA isoforms with potential utility as therapeutic targets or as prognostic or diagnostic markers.

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Identification of Echinus and Characterization of its Role in Drosophila Eye Development (2008)

No abstract available.

Master's Student Supervision (2010 - 2018)
A case study of apparent immune activation following treatment of a colorectal cancer patient with an angiotensin receptor blocker (2018)

Despite being one of the most preventable cancers, colorectal cancer (CRC) affects a large proportion of the population and results in ~12% of all deaths due to cancer in Canada (Canadian Cancer Society, 2017). Standard treatments for CRC are chemotherapy based, but more targeted therapies are emerging as highly effective treatments across multiple disease types. The Personalised Oncogenomics (POG) program at BC Cancer aims to discover actionable genomic alterations using whole genome and transcriptome sequence analysis of incurable cancer patients (Laskin et al., 2015). Occasionally, selected patients may be offered a treatment predicted by the POG analysis. One particular metastatic CRC POG patient displayed a profound response upon treatment with an antihypertensive drug, irbesartan (Avapro), prescribed following genomic analysis of a biopsy sample that had revealed unusually high expression of FOS and JUN transcripts, downstream components of the pathway on which irbesartan acts. After a durable 18-month response to irbesartan, the patient relapsed and a second biopsy was taken, providing a unique opportunity to study the mechanisms underpinning the response and relapse of the patient. Gene set enrichment analysis of RNA and protein expression data revealed an increase in abundance of genes involved in immune system pathways following treatment with irbesartan, and results from multiplex immunohistochemistry panels indicated increased cytotoxic T cell infiltration following treatment. Combined with increases in protein and RNA abundance of negative immune checkpoints (often a resistance mechanism to immune activation), and a large repertoire of candidate neo-antigens, there is evidence to support the hypothesis that irbesartan stimulated an anti-tumour immune response. In contrast with immunotherapy agents such as immune checkpoint inhibitors (ICIs), irbesartan is substantially cheaper, and exhibits fewer side effects. If a biomarker of response to irbesartan can be identified, there may be future potential for this drug to be tested for clinical activity in a larger patient population. Furthermore, this case study demonstrates the utility of whole genome and transcriptome sequencing to study response and resistance to therapies and how these methods might be used to inform clinical decision making.

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Comprehensive and integrative analysis of the KMT2D regulome (2017)

Lysine (K)-specific methyltransferase 2D (KMT2D) is a critical component of epigenetic regulation through its role in mono-methylation of lysine 4 of histone H3 (H3K4me1). KMT2D is among the most frequently mutated genes in many forms of cancer, with particularly high occurrence of mutation in lymphoid malignancies. Despite being the recurrent target of somatic alteration across many cancer types, the consequences of KMT2D mutation, and their relevance to tumorigenesis, remain unclear. To expand on the current understanding of KMT2D loss, I performed comprehensive and integrative bioinformatics analyses of the epigenetic and transcriptome landscapes of isogenic KMT2D-mutant HEK293A cell lines. Analysis of ChIP-sequencing data from KMT2D-mutant cells showed genome-wide alterations in the distribution of H3K4me1, with loss of H3K4me1 occurring at active and poised enhancer regions. Interestingly, epigenetic disruption of enhancers in KMT2D-mutant cells was not sufficient for inducing transcriptional alteration of nearby genes, indicating a possible requirement for additional co-factors to be present in order to observe the consequences of KMT2D-dependent enhancer loss. Genes associated with KMT2D-dependent enhancers were enriched for members of the TGF-beta and retinoic acid (RA) signaling networks, highlighting transcriptional response to these pathways as candidate processes in which functional KMT2D-dependent enhancers may be required. Given the roles of both TGF-beta and RA signaling in cancer, identification of the convergence between the KMT2D regulome and these signaling axes provides a potential means by which KMT2D mutations may contribute to tumorigenesis.

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Generation and characterization of a lysine (K)-specific methyltransferase 2D knockout human cell line (2015)

Lysine (K)-specific methyltransferase 2D (KMT2D) encodes a histone-lysine N-methyltransferase that catalyzes the methylation of histone 3 lysine 4 (H3K4me), which is an epigenetic modification involved in transcriptional regulation. KMT2D is a recurrent target of somatic mutation in at least 27 types of cancer, with the majority of KMT2D mutations (54%) predicted to result in the loss of protein function. In particular, KMT2D is mutated in ~85% of patients with follicular lymphoma, with ~50% of cases harboring multiple mutations in KMT2D. Disruption of KMT2D function has been linked to a rare pediatric disorder named Kabuki syndrome where ~75% of patients harbour heterozygous loss of function (LOF) mutations. To investigate the impact of LOF KMT2D mutations on H3K4 methylation and transcription I inactivated KMT2D using zinc finger nuclease (ZFN) technology in the human cell line HEK293A. Consistent with previous studies, HEK293 KMT2D LOF cell lines demonstrated loss of KMT2D was sufficient to reduce bulk mono- and dimethylation of H3K4 in the cell. Previous studies have demonstrated that KMT2D’s epigenetic function is involved in nuclear hormone transactivation, and that disruption of nuclear hormone signaling via the retinoic acid receptor (RAR) leads to lymphomagenesis in mouse models. To study the link between RAR signaling and KMT2D, I investigated RAR signaling in HEK293 KMT2D LOF cell lines. I observed KMT2D was necessary for robust induction of RAR response genes RARA2, RARB2, and RARG in the presence of 9-cis-retinoic acid. These results are compatible with the notion that LOF KMT2D mutations may aid cancer cells in escaping RA induced differentiation by impairing RA dependent transcription of differentiation promoting genes.

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The regulatory landscape of the glioma-associated transcription factor Capicua (2015)

The metazoan developmental gene capicua transcriptional repressor (CIC) encodes a transcription factor that transduces receptor tyrosine kinase signaling into gene expression changes. Aberrant CIC function is implicated in oligodendroglioma (ODG) development since one CIC allele is lost while the other is mutated in ~70% of ODGs. We therefore investigated how CIC can affect gene expression at a genome-wide level by inactivating CIC in HEK293a cells and subsequently measuring gene expression changes using microarrays. From this, gene expression changes spanning entire chromosomes were detected. Additionally, 24 candidate CIC-regulated genes were identified in HEK293a cells that also have evidence of CIC-dependent regulation in ODGs sequenced by The Cancer Genome Atlas (TCGA). Of these 24 genes, 5 genes (CNTFR, DUSP6, GPR3, SHC3, and SPRY4) with reported functions in mitogen-activated protein kinase (MAPK) signaling and central nervous system (CNS) development were further validated to undergo CIC-dependent regulation in HeLa cells. Finally, investigating how different CIC mutations affect gene expression revealed that different types of ODG-associated CIC mutations either abrogated or potentially preserved CIC’s transcriptionally repressive activity. These findings shed insight into possible roles for CIC in regulating gene expression at a chromosome-wide scale, MAPK signaling, CNS development, and ODG development.

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Publications

 
 

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