43Metastatic castration-resistant prostate cancer (mCRPC) has a highly complex genomic landscape. 44With the recent development of novel treatments, accurate stratification strategies are needed. Here 45 we present the whole-genome sequencing (WGS) analysis of fresh-frozen metastatic biopsies from 46 197 mCRPC patients. Using unsupervised clustering based on genomic features, we define eight 47 distinct genomic clusters. We observe potentially clinically relevant genotypes, including microsatellite 48 instability (MSI), homologous recombination deficiency (HRD) enriched with genomic deletions and 49 BRCA2 aberrations, a tandem duplication genotype associated with CDK12 -/and a chromothripsis-50 enriched subgroup. Our data suggests that stratification on WGS characteristics may improve 51 identification of MSI, CDK12 -/and HRD patients. From WGS and ChIP-seq data, we show the 52 potential relevance of recurrent alterations in non-coding regions identified with WGS and highlight 53 the central role of AR signaling in tumor progression. These data underline the potential value of 54 using WGS to accurately stratify mCRPC patients into clinically actionable subgroups. 55 157This analysis did not reveal systematic biases due to pre-treatment in aberrations, such as TMB, 158 kataegis, chromothripsis, ETS fusions, or somatically altered genes ( Supplementary table 3). 159 Methods 657 Patient cohort and study procedures 658 b * * c i j k l m Cluster A Cluster B Cluster C Cluster D Cluster E Cluster F Cluster G Cluster H
Background
Fusion genes are typically identified by RNA sequencing (RNA-seq) without elucidating the causal genomic breakpoints. However, non–poly(A)-enriched RNA-seq contains large proportions of intronic reads that also span genomic breakpoints.
Results
We have developed an algorithm, Dr. Disco, that searches for fusion transcripts by taking an entire reference genome into account as search space. This includes exons but also introns, intergenic regions, and sequences that do not meet splice junction motifs. Using 1,275 RNA-seq samples, we investigated to what extent genomic breakpoints can be extracted from RNA-seq data and their implications regarding poly(A)-enriched and ribosomal RNA–minus RNA-seq data. Comparison with whole-genome sequencing data revealed that most genomic breakpoints are not, or minimally, transcribed while, in contrast, the genomic breakpoints of all 32 TMPRSS2-ERG–positive tumours were present at RNA level. We also revealed tumours in which the ERG breakpoint was located before ERG, which co-existed with additional deletions and messenger RNA that incorporated intergenic cryptic exons. In breast cancer we identified rearrangement hot spots near CCND1 and in glioma near CDK4 and MDM2 and could directly associate this with increased expression. Furthermore, in all datasets we find fusions to intergenic regions, often spanning multiple cryptic exons that potentially encode neo-antigens. Thus, fusion transcripts other than classical gene-to-gene fusions are prominently present and can be identified using RNA-seq.
Conclusion
By using the full potential of non–poly(A)-enriched RNA-seq data, sophisticated analysis can reliably identify expressed genomic breakpoints and their transcriptional effects.
Bauxite is mined and transported by conveyor to a processing plant, screened and washed, then placed into blended stockpiles to feed the alumina refinery. While being stacked to the stockpile, the ore is sampled. Completed stockpiles must be acceptably close to target grade (composition), not only in alumina, but also in residual silica, carbon and sodium carbonate. The mine is an open-cut pit. Each day the choice of ore to mine, from multiple locations in the pit, is based upon estimates of grade. Estimated grade, from exploration drilling of the area before mining, has both systematic and random error. This paper describes an information system to guide the daily choice of ore to mine. Continually updating the comparison between forecasts and sampled product, the system provides adjusted forecasts. Ore is selected to bring the exponentially smoothed grade to target, in each of the control minerals.
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