Sir Peter MacCallum Department of Oncology - Research Publications
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ItemNo Preview AvailableEvolution of core archetypal phenotypes in progressive high grade serous ovarian cancer(NATURE PORTFOLIO, 2021-05-24)The evolution of resistance in high-grade serous ovarian cancer (HGSOC) cells following chemotherapy is only partially understood. To understand the selection of factors driving heterogeneity before and through adaptation to treatment, we profile single-cell RNA-sequencing (scRNA-seq) transcriptomes of HGSOC tumors collected longitudinally during therapy. We analyze scRNA-seq data from two independent patient cohorts to reveal that HGSOC is driven by three archetypal phenotypes, defined as oncogenic states that describe the majority of the transcriptome variation. Using a multi-task learning approach to identify the biological tasks of each archetype, we identify metabolism and proliferation, cellular defense response, and DNA repair signaling as consistent cell states found across patients. Our analysis demonstrates a shift in favor of the metabolism and proliferation archetype versus cellular defense response archetype in cancer cells that received multiple lines of treatment. While archetypes are not consistently associated with specific whole-genome driver mutations, they are closely associated with subclonal populations at the single-cell level, indicating that subclones within a tumor often specialize in unique biological tasks. Our study reveals the core archetypes found in progressive HGSOC and shows consistent enrichment of subclones with the metabolism and proliferation archetype as resistance is acquired to multiple lines of therapy.
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ItemPhenotypic Consequences of SLC25A40-ABCB1 Fusions beyond Drug Resistance in High-Grade Serous Ovarian Cancer(MDPI, 2021-11)Despite high response rates to initial chemotherapy, the majority of women diagnosed with High-Grade Serous Ovarian Cancer (HGSOC) ultimately develop drug resistance within 1-2 years of treatment. We previously identified the most common mechanism of acquired resistance in HGSOC to date, transcriptional fusions involving the ATP-binding cassette (ABC) transporter ABCB1, which has well established roles in multidrug resistance. However, the underlying biology of fusion-positive cells, as well as how clonal interactions between fusion-negative and positive populations influences proliferative fitness and therapeutic response remains unknown. Using a panel of fusion-negative and positive HGSOC single-cell clones, we demonstrate that in addition to mediating drug resistance, ABCB1 fusion-positive cells display impaired proliferative capacity, elevated oxidative metabolism, altered actin cellular morphology and an extracellular matrix/inflammatory enriched transcriptional profile. The co-culture of fusion-negative and positive populations had no effect on cellular proliferation but markedly altered drug sensitivity to doxorubicin, paclitaxel and cisplatin. Finally, high-throughput screening of 2907 FDA-approved compounds revealed 36 agents that induce equal cytotoxicity in both pure and mixed ABCB1 fusion populations. Collectively, our findings have unraveled the underlying biology of ABCB1 fusion-positive cells beyond drug resistance and identified novel therapeutic agents that may significantly improve the prognosis of relapsed HGSOC patients.
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ItemEvolution of core archetypal phenotypes in progressive high grade serous ovarian cancer.(AMER ASSOC CANCER RESEARCH, 2021-07-01)Abstract The evolution of resistance in high-grade serous ovarian cancer (HGSOC) cells following chemotherapy is only partially understood. To uncover phenotypic changes associated with chemotherapy resistance, we profiled single-cell RNA-sequencing (scRNA-seq) transcriptomes of HGSOC tumors collected longitudinally during patient treatment. Analysis of scRNA-seq data from two independent patient cohorts revealed that HGSOC is driven by three core archetypal phenotypes, defined as oncogenic tasks that describe the majority of the transcriptome variation. A multi-task learning approach to identify the biological tasks of each archetype identified metabolism and proliferation, cellular defense response, and DNA repair signaling. The metabolism and proliferation archetype evolved during treatment and was enriched in cancer cells from patients that received multiple-lines of treatment and had elevated tumor burden indicated by CA-125 levels. The emergence of archetypes was not consistently associated with specific whole-genome driver mutations. However, archetypes were closely associated with subclonal populations at the single-cell level, indicating that subclones within a tumor often specialize in unique biological tasks. Our study reveals the core archetypes found in progressive HGSOC and shows consistent enrichment of subclones with the metabolism archetype as resistance is acquired to multiple lines of therapy. Citation Format: Aritro Nath, Patrick Cosgrove, Benjamin Copeland, Hoda Mirsafian, Elizabeth Christie, Lance Pflieger, Sumana Majumdar, Mihaela Cristea, Ernest Han, Stephen Lee, Edward Wang, Sian Fereday, Nadia Traficante, Ravi Salgia, Theresa Werner, Adam Cohen, Phillip Moos, Jeffrey Chang, David Bowtell, Andrea Bild. Evolution of core archetypal phenotypes in progressive high grade serous ovarian cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2021; 2021 Apr 10-15 and May 17-21. Philadelphia (PA): AACR; Cancer Res 2021;81(13_Suppl):Abstract nr 3141.
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ItemCharacterizing genetic intra-tumor heterogeneity across 2,658 human cancer genomes(CELL PRESS, 2021-04-15)Intra-tumor heterogeneity (ITH) is a mechanism of therapeutic resistance and therefore an important clinical challenge. However, the extent, origin, and drivers of ITH across cancer types are poorly understood. To address this, we extensively characterize ITH across whole-genome sequences of 2,658 cancer samples spanning 38 cancer types. Nearly all informative samples (95.1%) contain evidence of distinct subclonal expansions with frequent branching relationships between subclones. We observe positive selection of subclonal driver mutations across most cancer types and identify cancer type-specific subclonal patterns of driver gene mutations, fusions, structural variants, and copy number alterations as well as dynamic changes in mutational processes between subclonal expansions. Our results underline the importance of ITH and its drivers in tumor evolution and provide a pan-cancer resource of comprehensively annotated subclonal events from whole-genome sequencing data.
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ItemGenomic footprints of activated telomere maintenance mechanisms in cancer(NATURE PORTFOLIO, 2020-02-05)Cancers require telomere maintenance mechanisms for unlimited replicative potential. They achieve this through TERT activation or alternative telomere lengthening associated with ATRX or DAXX loss. Here, as part of the ICGC/TCGA Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium, we dissect whole-genome sequencing data of over 2500 matched tumor-control samples from 36 different tumor types aggregated within the ICGC/TCGA Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium to characterize the genomic footprints of these mechanisms. While the telomere content of tumors with ATRX or DAXX mutations (ATRX/DAXXtrunc) is increased, tumors with TERT modifications show a moderate decrease of telomere content. One quarter of all tumor samples contain somatic integrations of telomeric sequences into non-telomeric DNA. This fraction is increased to 80% prevalence in ATRX/DAXXtrunc tumors, which carry an aberrant telomere variant repeat (TVR) distribution as another genomic marker. The latter feature includes enrichment or depletion of the previously undescribed singleton TVRs TTCGGG and TTTGGG, respectively. Our systematic analysis provides new insight into the recurrent genomic alterations associated with telomere maintenance mechanisms in cancer.
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ItemHigh-coverage whole-genome analysis of 1220 cancers reveals hundreds of genes deregulated by rearrangement-mediated cis-regulatory alterations(NATURE PUBLISHING GROUP, 2020-02-05)The impact of somatic structural variants (SVs) on gene expression in cancer is largely unknown. Here, as part of the ICGC/TCGA Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium, which aggregated whole-genome sequencing data and RNA sequencing from a common set of 1220 cancer cases, we report hundreds of genes for which the presence within 100 kb of an SV breakpoint associates with altered expression. For the majority of these genes, expression increases rather than decreases with corresponding breakpoint events. Up-regulated cancer-associated genes impacted by this phenomenon include TERT, MDM2, CDK4, ERBB2, CD274, PDCD1LG2, and IGF2. TERT-associated breakpoints involve ~3% of cases, most frequently in liver biliary, melanoma, sarcoma, stomach, and kidney cancers. SVs associated with up-regulation of PD1 and PDL1 genes involve ~1% of non-amplified cases. For many genes, SVs are significantly associated with increased numbers or greater proximity of enhancer regulatory elements near the gene. DNA methylation near the promoter is often increased with nearby SV breakpoint, which may involve inactivation of repressor elements.
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ItemComprehensive analysis of chromothripsis in 2,658 human cancers using whole-genome sequencing(Nature Research, 2020-03)Chromothripsis is a mutational phenomenon characterized by massive, clustered genomic rearrangements that occurs in cancer and other diseases. Recent studies in selected cancer types have suggested that chromothripsis may be more common than initially inferred from low-resolution copy-number data. Here, as part of the Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium of the International Cancer Genome Consortium (ICGC) and The Cancer Genome Atlas (TCGA), we analyze patterns of chromothripsis across 2,658 tumors from 38 cancer types using whole-genome sequencing data. We find that chromothripsis events are pervasive across cancers, with a frequency of more than 50% in several cancer types. Whereas canonical chromothripsis profiles display oscillations between two copy-number states, a considerable fraction of events involve multiple chromosomes and additional structural alterations. In addition to non-homologous end joining, we detect signatures of replication-associated processes and templated insertions. Chromothripsis contributes to oncogene amplification and to inactivation of genes such as mismatch-repair-related genes. These findings show that chromothripsis is a major process that drives genome evolution in human cancer.
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ItemCancer LncRNA Census reveals evidence for deep functional conservation of long noncoding RNAs in tumorigenesis(NATURE PUBLISHING GROUP, 2020-02-05)Long non-coding RNAs (lncRNAs) are a growing focus of cancer genomics studies, creating the need for a resource of lncRNAs with validated cancer roles. Furthermore, it remains debated whether mutated lncRNAs can drive tumorigenesis, and whether such functions could be conserved during evolution. Here, as part of the ICGC/TCGA Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium, we introduce the Cancer LncRNA Census (CLC), a compilation of 122 GENCODE lncRNAs with causal roles in cancer phenotypes. In contrast to existing databases, CLC requires strong functional or genetic evidence. CLC genes are enriched amongst driver genes predicted from somatic mutations, and display characteristic genomic features. Strikingly, CLC genes are enriched for driver mutations from unbiased, genome-wide transposon-mutagenesis screens in mice. We identified 10 tumour-causing mutations in orthologues of 8 lncRNAs, including LINC-PINT and NEAT1, but not MALAT1. Thus CLC represents a dataset of high-confidence cancer lncRNAs. Mutagenesis maps are a novel means for identifying deeply-conserved roles of lncRNAs in tumorigenesis.
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ItemIntegrative pathway enrichment analysis of multivariate omics data(NATURE PUBLISHING GROUP, 2020-02-05)Multi-omics datasets represent distinct aspects of the central dogma of molecular biology. Such high-dimensional molecular profiles pose challenges to data interpretation and hypothesis generation. ActivePathways is an integrative method that discovers significantly enriched pathways across multiple datasets using statistical data fusion, rationalizes contributing evidence and highlights associated genes. As part of the ICGC/TCGA Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium, which aggregated whole genome sequencing data from 2658 cancers across 38 tumor types, we integrated genes with coding and non-coding mutations and revealed frequently mutated pathways and additional cancer genes with infrequent mutations. We also analyzed prognostic molecular pathways by integrating genomic and transcriptomic features of 1780 breast cancers and highlighted associations with immune response and anti-apoptotic signaling. Integration of ChIP-seq and RNA-seq data for master regulators of the Hippo pathway across normal human tissues identified processes of tissue regeneration and stem cell regulation. ActivePathways is a versatile method that improves systems-level understanding of cellular organization in health and disease through integration of multiple molecular datasets and pathway annotations.
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ItemReconstructing evolutionary trajectories of mutation signature activities in cancer using TrackSig(Nature Research (part of Springer Nature), 2020-02-05)The type and genomic context of cancer mutations depend on their causes. These causes have been characterized using signatures that represent mutation types that co-occur in the same tumours. However, it remains unclear how mutation processes change during cancer evolution due to the lack of reliable methods to reconstruct evolutionary trajectories of mutational signature activity. Here, as part of the ICGC/TCGA Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium, which aggregated whole-genome sequencing data from 2658 cancers across 38 tumour types, we present TrackSig, a new method that reconstructs these trajectories using optimal, joint segmentation and deconvolution of mutation type and allele frequencies from a single tumour sample. In simulations, we find TrackSig has a 3-5% activity reconstruction error, and 12% false detection rate. It outperforms an aggressive baseline in situations with branching evolution, CNA gain, and neutral mutations. Applied to data from 2658 tumours and 38 cancer types, TrackSig permits pan-cancer insight into evolutionary changes in mutational processes.