Showing papers by "Oliver Hofmann published in 2017"

Identification of unique neoantigen qualities in long-term survivors of pancreatic cancer.

Abstract: Pancreatic ductal adenocarcinoma is a lethal cancer with fewer than 7% of patients surviving past 5 years. T-cell immunity has been linked to the exceptional outcome of the few long-term survivors, yet the relevant antigens remain unknown. Here we use genetic, immunohistochemical and transcriptional immunoprofiling, computational biophysics, and functional assays to identify T-cell antigens in long-term survivors of pancreatic cancer. Using whole-exome sequencing and in silico neoantigen prediction, we found that tumours with both the highest neoantigen number and the most abundant CD8+ T-cell infiltrates, but neither alone, stratified patients with the longest survival. Investigating the specific neoantigen qualities promoting T-cell activation in long-term survivors, we discovered that these individuals were enriched in neoantigen qualities defined by a fitness model, and neoantigens in the tumour antigen MUC16 (also known as CA125). A neoantigen quality fitness model conferring greater immunogenicity to neoantigens with differential presentation and homology to infectious disease-derived peptides identified long-term survivors in two independent datasets, whereas a neoantigen quantity model ascribing greater immunogenicity to increasing neoantigen number alone did not. We detected intratumoural and lasting circulating T-cell reactivity to both high-quality and MUC16 neoantigens in long-term survivors of pancreatic cancer, including clones with specificity to both high-quality neoantigens and predicted cross-reactive microbial epitopes, consistent with neoantigen molecular mimicry. Notably, we observed selective loss of high-quality and MUC16 neoantigenic clones on metastatic progression, suggesting neoantigen immunoediting. Our results identify neoantigens with unique qualities as T-cell targets in pancreatic ductal adenocarcinoma. More broadly, we identify neoantigen quality as a biomarker for immunogenic tumours that may guide the application of immunotherapies.

Copy-number signatures and mutational processes in ovarian carcinoma

Abstract: Tumours with profound copy-number aberration elude molecular stratification due to their genomic complexity. By representing this complexity as a mixture of copy-number signatures, we provide molecular explanations for differing clinical outcomes. Here we present a method for copy-number signature identification, deriving eight signatures in 117 shallow whole-genome sequenced high-grade serous ovarian cancers (HGSOC), which validated on independent cohorts of 95 deep whole-genome sequenced, and 402 SNP array-profiled cases. Three copy-number signatures predicted longer overall survival, while the others predicted poorer outcome. We found evidence for the mutational processes giving rise to copy-number change for six of the eight signatures via correlations with other genomic features. Our results provide insights into the pathogenesis of HGSOC by uncovering multiple mutational processes that shape genomes following TP53 mutation. Importantly, our work shows that most HGSOC have a mixture of mutational processes suggesting that targeting a single mutator phenotype may be therapeutically suboptimal.

Silencing of the Drosophila ortholog of SOX5 leads to abnormal neuronal development and behavioral impairment.

Abstract: SOX5 encodes a transcription factor that is expressed in multiple tissues including heart, lung and brain. Mutations in SOX5 have been previously found in patients with amyotrophic lateral sclerosis (ALS) and developmental delay, intellectual disability and dysmorphic features. To characterize the neuronal role of SOX5, we silenced the Drosophila ortholog of SOX5, Sox102F, by RNAi in various neuronal subtypes in Drosophila. Silencing of Sox102F led to misorientated and disorganized michrochaetes, neurons with shorter dendritic arborization (DA) and reduced complexity, diminished larval peristaltic contractions, loss of neuromuscular junction bouton structures, impaired olfactory perception, and severe neurodegeneration in brain. Silencing of SOX5 in human SH-SY5Y neuroblastoma cells resulted in a significant repression of WNT signaling activity and altered expression of WNT-related genes. Genetic association and meta-analyses of the results in several large family-based and case-control late-onset familial Alzheimer's disease (LOAD) samples of SOX5 variants revealed several variants that show significant association with AD disease status. In addition, analysis for rare and highly penetrate functional variants revealed four novel variants/mutations in SOX5, which taken together with functional prediction analysis, suggests a strong role of SOX5 causing AD in the carrier families. Collectively, these findings indicate that SOX5 is a novel candidate gene for LOAD with an important role in neuronal function. The genetic findings warrant further studies to identify and characterize SOX5 variants that confer risk for AD, ALS and intellectual disability.

Large-Scale Uniform Analysis of Cancer Whole Genomes in Multiple Computing Environments

Abstract: The International Cancer Genome Consortium (ICGC)9s Pan-Cancer Analysis of Whole Genomes (PCAWG) project aimed to categorize somatic and germline variations in both coding and non-coding regions in over 2,800 cancer patients. To provide this dataset to the research working groups for downstream analysis, the PCAWG Technical Working Group marshalled ~800TB of sequencing data from distributed geographical locations; developed portable software for uniform alignment, variant calling, artifact filtering and variant merging; performed the analysis in a geographically and technologically disparate collection of compute environments; and disseminated high-quality validated consensus variants to the working groups. The PCAWG dataset has been mirrored to multiple repositories and can be located using the ICGC Data Portal. The PCAWG workflows are also available as Docker images through Dockstore enabling researchers to replicate our analysis on their own data.

bcbioRNASeq: R package for bcbio RNA-seq analysis

Abstract: RNA-seq analysis involves multiple steps, from processing raw sequencing data to identifying, organizing, annotating, and reporting differentially expressed genes. bcbio is an open source, community-maintained framework providing automated and scalable RNA-seq methods for identifying gene abundance counts. We have developed bcbioRNASeq, a Bioconductor package that provides ready-to-render templates, objects and wrapper functions to post-process bcbio RNA sequencing output data. bcbioRNASeq helps automate the generation of high-level RNA-seq reports, facilitating the quality control analyses, identification of differentially expressed genes and functional enrichment analyses.

Prioritisation of structural variant calls in cancer genomes.

Abstract: Sensitivity of short read DNA-sequencing for gene fusion detection is improving, but is hampered by the significant amount of noise composed of uninteresting or false positive hits in the data. In this paper we describe a tiered prioritisation approach to extract high impact gene fusion events from existing structural variant calls. Using cell line and patient DNA sequence data we improve the annotation and interpretation of structural variant calls to best highlight likely cancer driving fusions. We also considerably improve on the automated visualisation of the high impact structural variants to highlight the effects of the variants on the resulting transcripts. The resulting framework greatly improves on readily detecting clinically actionable structural variants.