Systematic investigation of promoter substitutions resulting from somatic intrachromosomal structural alterations in diverse human cancers.

One of the ways in which genes can become activated in tumors is by somatic structural genomic rearrangements leading to promoter swapping events, typically in the context of gene fusions that cause a weak promoter to be substituted for a strong promoter. While identifiable by whole genome sequencing, limited availability of this type of data has prohibited comprehensive study of the phenomenon. Here, we leveraged the fact that copy number alterations (CNAs) arise as a result of structural alterations in DNA, and that they may therefore be informative of gene rearrangements, to pinpoint recurrent promoter swapping at a previously intractable scale. CNA data from nearly 9500 human tumors was combined with transcriptomic sequencing data to identify several cases of recurrent activating intrachromosomal promoter substitution events, either involving proper gene fusions or juxtaposition of strong promoters to gene upstream regions. Our computational screen demonstrates that a combination of CNA and expression data can be useful for identifying novel fusion events with potential driver roles in large cancer cohorts.

Mutational Signature and Transcriptomic Classification Analyses as the Decisive Diagnostic Tools for a Cancer of Unknown Primary.

PURPOSE: Cancer of unknown primary is a group of metastatic tumors in which the standard diagnostic workup fails to identify the site of origin of the tumor. The potential impact of precision oncology on this group of patients is large, because actionable driver mutations and a correct diagnosis could provide treatment options otherwise not available for patients with these fatal cancers. This study investigated if comprehensive genomic analyses could provide information on the origin of the tumor. PATIENTS AND METHODS: Here we describe a patient whose tumor was misdiagnosed at least three times. Next-generation sequencing, a patient-derived xenograft mouse model, and bioinformatics were used to identify an actionable mutation, predict resistance development to the targeted therapy, and correctly diagnose the origin of the tumor. Transcriptomic classification was benchmarked using The Cancer Genome Atlas (TCGA). RESULTS: Despite the lack of a known primary tumor site and the absence of diagnostic immunohistochemical markers, the origin of the patient's tumor was established using the novel bioinformatic workflow. This included a mutational signature analysis of the sequenced metastases and comparison of their transcriptomic profiles to a pan-cancer panel of tumors from TCGA. We further discuss the strengths and limitations of the latter approaches in the context of three potentially incorrectly diagnosed TCGA lung tumors. CONCLUSION: Comprehensive genomic analyses can provide information on the origin of tumors in patients with cancer of unknown primary.

Global analysis of somatic structural genomic alterations and their impact on gene expression in diverse human cancers.

Tumor genomes are mosaics of somatic structural variants (SVs) that may contribute to the activation of oncogenes or inactivation of tumor suppressors, for example, by altering gene copy number amplitude. However, there are multiple other ways in which SVs can modulate transcription, but the general impact of such events on tumor transcriptional output has not been systematically determined. Here we use whole-genome sequencing data to map SVs across 600 tumors and 18 cancers, and investigate the relationship between SVs, copy number alterations (CNAs), and mRNA expression. We find that 34% of CNA breakpoints can be clarified structurally and that most amplifications are due to tandem duplications. We observe frequent swapping of strong and weak promoters in the context of gene fusions, and find that this has a measurable global impact on mRNA levels. Interestingly, several long noncoding RNAs were strongly activated by this mechanism. Additionally, SVs were confirmed in telomere reverse transcriptase (TERT) upstream regions in several cancers, associated with elevated TERT mRNA levels. We also highlight high-confidence gene fusions supported by both genomic and transcriptomic evidence, including a previously undescribed paired box 8 (PAX8)-nuclear factor, erythroid 2 like 2 (NFE2L2) fusion in thyroid carcinoma. In summary, we combine SV, CNA, and expression data to provide insights into the structural basis of CNAs as well as the impact of SVs on gene expression in tumors.

Simultaneous DNA and RNA Mapping of Somatic Mitochondrial Mutations across Diverse Human Cancers.

Somatic mutations in the nuclear genome are required for tumor formation, but the functional consequences of somatic mitochondrial DNA (mtDNA) mutations are less understood. Here we identify somatic mtDNA mutations across 527 tumors and 14 cancer types, using an approach that takes advantage of evidence from both genomic and transcriptomic sequencing. We find that there is selective pressure against deleterious coding mutations, supporting that functional mitochondria are required in tumor cells, and also observe a strong mutational strand bias, compatible with endogenous replication-coupled errors as the major source of mutations. Interestingly, while allelic ratios in general were consistent in RNA compared to DNA, some mutations in tRNAs displayed strong allelic imbalances caused by accumulation of unprocessed tRNA precursors. The effect was explained by altered secondary structure, demonstrating that correct tRNA folding is a major determinant for processing of polycistronic mitochondrial transcripts. Additionally, the data suggest that tRNA clusters are preferably processed in the 3' to 5' direction. Our study gives insights into mtDNA function in cancer and answers questions regarding mitochondrial tRNA biogenesis that are difficult to address in controlled experimental systems.

Temporal separation of replication and transcription during S-phase progression.

Transcriptional events during S-phase are critical for cell cycle progression. Here, by using a nascent RNA capture assay coupled with high-throughput sequencing, we determined the temporal patterns of transcriptional events that occur during S-phase. We show that genes involved in critical S-phase-specific biological processes such as nucleosome assembly and DNA repair have temporal transcription patterns across S-phase that are not evident from total RNA levels. By comparing transcription timing with replication timing in S-phase, we show that early replicating genes show increased transcription late in S-phase whereas late replicating genes are predominantly transcribed early in S-phase. Global anti-correlation between replication and transcription timing was observed only based on nascent RNA but not total RNA. Our data provides a detailed view of ongoing transcriptional events during the S-phase of cell cycle, and supports that transcription and replication are temporally separated.

The landscape of viral expression and host gene fusion and adaptation in human cancer.

Viruses cause 10-15% of all human cancers. Massively parallel sequencing has recently proved effective for uncovering novel viruses and virus-tumour associations, but this approach has not yet been applied to comprehensive patient cohorts. Here we screen a diverse landscape of human cancer, encompassing 4,433 tumours and 19 cancer types, for known and novel expressed viruses based on >700 billion transcriptome sequencing reads from The Cancer Genome Atlas Research Network. The resulting map confirms and extends current knowledge. We observe recurrent fusion events, including human papillomavirus insertions in RAD51B and ERBB2. Patterns of coadaptation between host and viral gene expression give clues to papillomavirus oncogene function. Importantly, our analysis argues strongly against viral aetiology in several cancers where this has frequently been proposed. We provide a virus-tumour map of unprecedented scale that constitutes a reference for future studies of tumour-associated viruses using transcriptome sequencing data.

Limited evidence for evolutionarily conserved targeting of long non-coding RNAs by microRNAs.

BACKGROUND: Long non-coding RNAs (lncRNAs) are emerging as important regulators of cell physiology, but it is yet unknown to what extent lncRNAs have evolved to be targeted by microRNAs. Comparative genomics has previously revealed widespread evolutionarily conserved microRNA targeting of protein-coding mRNAs, and here we applied a similar approach to lncRNAs. FINDINGS: We used a map of putative microRNA target sites in lncRNAs where site conservation was evaluated based on 46 vertebrate species. We compared observed target site frequencies to those obtained with a random model, at variable prediction stringencies. While conserved sites were not present above random expectation in intergenic lncRNAs overall, we observed a marginal over-representation of highly conserved 8-mer sites in a small subset of cytoplasmic lncRNAs (12 sites in 8 lncRNAs at 56% false discovery rate, P = 0.10). CONCLUSIONS: Evolutionary conservation in lncRNAs is generally low but patch-wise high, and these patches could, in principle, harbor conserved target sites. However, while our analysis efficiently detected conserved targeting of mRNAs, it provided only limited and marginally significant support for conserved microRNA-lncRNA interactions. We conclude that conserved microRNA-lncRNA interactions could not be reliably detected with our methodology.