Characterizing genetic intra-tumor heterogeneity across 2,658 human cancer genomes.

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.

Drosha controls dendritic cell development by cleaving messenger RNAs encoding inhibitors of myelopoiesis.

To investigate if the microRNA (miRNA) pathway is required for dendritic cell (DC) development, we assessed the effect of ablating Drosha and Dicer, the two enzymes central to miRNA biogenesis. We found that while Dicer deficiency had some effect, Drosha deficiency completely halted DC development and halted myelopoiesis more generally. This indicated that while the miRNA pathway did have a role, it was a non-miRNA function of Drosha that was particularly critical. Drosha repressed the expression of two mRNAs encoding inhibitors of myelopoiesis in early hematopoietic progenitors. We found that Drosha directly cleaved stem-loop structure within these mRNAs and that this mRNA degradation was necessary for myelopoiesis. We have therefore identified a mechanism that regulates the development of DCs and other myeloid cells.

The evolutionary history of 2,658 cancers.

Cancer develops through a process of somatic evolution1,2. Sequencing data from a single biopsy represent a snapshot of this process that can reveal the timing of specific genomic aberrations and the changing influence of mutational processes3. Here, by whole-genome sequencing analysis of 2,658 cancers 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)4, we reconstruct the life history and evolution of mutational processes and driver mutation sequences of 38 types of cancer. Early oncogenesis is characterized by mutations in a constrained set of driver genes, and specific copy number gains, such as trisomy 7 in glioblastoma and isochromosome 17q in medulloblastoma. The mutational spectrum changes significantly throughout tumour evolution in 40% of samples. A nearly fourfold diversification of driver genes and increased genomic instability are features of later stages. Copy number alterations often occur in mitotic crises, and lead to simultaneous gains of chromosomal segments. Timing analyses suggest that driver mutations often precede diagnosis by many years, if not decades. Together, these results determine the evolutionary trajectories of cancer, and highlight opportunities for early cancer detection.

Prostate cancer cell-intrinsic interferon signaling regulates dormancy and metastatic outgrowth in bone.

The latency associated with bone metastasis emergence in castrate-resistant prostate cancer is attributed to dormancy, a state in which cancer cells persist prior to overt lesion formation. Using single-cell transcriptomics and ex vivo profiling, we have uncovered the critical role of tumor-intrinsic immune signaling in the retention of cancer cell dormancy. We demonstrate that loss of tumor-intrinsic type I IFN occurs in proliferating prostate cancer cells in bone. This loss suppresses tumor immunogenicity and therapeutic response and promotes bone cell activation to drive cancer progression. Restoration of tumor-intrinsic IFN signaling by HDAC inhibition increased tumor cell visibility, promoted long-term antitumor immunity, and blocked cancer growth in bone. Key findings were validated in patients, including loss of tumor-intrinsic IFN signaling and immunogenicity in bone metastases compared to primary tumors. Data herein provide a rationale as to why current immunotherapeutics fail in bone-metastatic prostate cancer, and provide a new therapeutic strategy to overcome the inefficacy of immune-based therapies in solid cancers.

A urinary microRNA signature can predict the presence of bladder urothelial carcinoma in patients undergoing surveillance.

BACKGROUND: The objective of this study was to determine whether microRNA (miRNA) profiling of urine could identify the presence of urothelial carcinoma of the bladder (UCB) and to compare its performance characteristics to that of cystoscopy. METHODS: In the discovery cohort we screened 81 patients, which included 21 benign controls, 30 non-recurrers and 30 patients with active cancer (recurrers), using a panel of 12 miRNAs. Data analysis was performed using a machine learning approach of a Support Vector Machine classifier with a Student's t-test feature selection procedure. This was trained using a three-fold cross validation approach and performance was measured using the area under the receiver operator characteristic curve (AUC). The miRNA signature was validated in an independent cohort of a further 50 patients. RESULTS: The best predictor to distinguish patients with UCB from non-recurrers was achieved using a combination of six miRNAs (AUC=0.85). This validated in an independent cohort (AUC=0.74) and detected UCB with a high sensitivity (88%) and sufficient specificity (48%) with all significant cancers identified. The performance of the classifier was best in detecting clinically significant disease such as presence of T1 Stage disease (AUC=0.92) and high-volume disease (AUC=0.81). Cystoscopy rates in the validation cohort would have been reduced by 30%. CONCLUSIONS: Urinary profiling using this panel of miRNAs shows promise for detection of tumour recurrence in the surveillance of UCB. Such a panel may be useful in reducing the morbidity and costs associated with cystoscopic surveillance, and now merits prospective evaluation.

A microRNA expression atlas of mouse dendritic cell development.

Dendritic cells (DCs) are sentinel cells of the immune system and are essential for inducing a proper immune response. The mechanisms driving the development of DCs are not fully understood. Although the roles of cytokines and transcription factors have been a major focus, there is now substantial interest in the role of microRNAs (miRNAs). miRNAs are small RNAs that regulate gene expression by targeting messenger RNAs for translational repression and ultimately degradation. By means of deep sequencing, we have assembled a comprehensive and quantitative resource of miRNA expression during DC development. We show that mature DCs and their hematopoietic progenitors can be distinguished based on miRNA expression profiles. On the other hand, we show that functionally distinct conventional and plasmacytoid DC subsets are indistinguishable based on miRNA profile. In addition, we identify differences between ex vivo purified conventional DCs and their in vitro Flt3L-generated counterparts. This miRNA expression atlas will provide a valuable resource for the study of miRNAs in DC development and function.

Socrates: identification of genomic rearrangements in tumour genomes by re-aligning soft clipped reads.

MOTIVATION: Methods for detecting somatic genome rearrangements in tumours using next-generation sequencing are vital in cancer genomics. Available algorithms use one or more sources of evidence, such as read depth, paired-end reads or split reads to predict structural variants. However, the problem remains challenging due to the significant computational burden and high false-positive or false-negative rates. RESULTS: In this article, we present Socrates (SOft Clip re-alignment To idEntify Structural variants), a highly efficient and effective method for detecting genomic rearrangements in tumours that uses only split-read data. Socrates has single-nucleotide resolution, identifies micro-homologies and untemplated sequence at break points, has high sensitivity and high specificity and takes advantage of parallelism for efficient use of resources. We demonstrate using simulated and real data that Socrates performs well compared with a number of existing structural variant detection tools. AVAILABILITY AND IMPLEMENTATION: Socrates is released as open source and available from http://bioinf.wehi.edu.au/socrates CONTACT: papenfuss@wehi.edu.au Supplementary information: Supplementary data are available at Bioinformatics online.

Slinker: Visualising novel splicing events in RNA-Seq data.

Visualisation of the transcriptome relative to a reference genome is fraught with sparsity. This is due to RNA sequencing (RNA-Seq) reads being predominantly mapped to exons that account for just under 3% of the human genome. Recently, we have used exon-only references, superTranscripts, to improve visualisation of aligned RNA-Seq data through the omission of supposedly unexpressed regions such as introns. However, variation within these regions can lead to novel splicing events that may drive a pathogenic phenotype. In these cases, the loss of information in only retaining annotated exons presents significant drawbacks. Here we present Slinker, a bioinformatics pipeline written in Python and Bpipe that uses a data-driven approach to assemble sample-specific superTranscripts. At its core, Slinker uses Stringtie2 to assemble transcripts with any sequence across any gene. This assembly is merged with reference transcripts, converted to a superTranscript, of which rich visualisations are made through Plotly with associated annotation and coverage information. Slinker was validated on five novel splicing events of rare disease samples from a cohort of primary muscular disorders. In addition, Slinker was shown to be effective in visualising deletion events within transcriptomes of tumour samples in the important leukemia gene, IKZF1. Slinker offers a succinct visualisation of RNA-Seq alignments across typically sparse regions and is freely available on Github.

MINTIE: identifying novel structural and splice variants in transcriptomes using RNA-seq data.

Calling fusion genes from RNA-seq data is well established, but other transcriptional variants are difficult to detect using existing approaches. To identify all types of variants in transcriptomes we developed MINTIE, an integrated pipeline for RNA-seq data. We take a reference-free approach, combining de novo assembly of transcripts with differential expression analysis to identify up-regulated novel variants in a case sample. We compare MINTIE with eight other approaches, detecting > 85% of variants while no other method is able to achieve this. We posit that MINTIE will be able to identify new disease variants across a range of disease types.

Loss of SNAI2 in Prostate Cancer Correlates With Clinical Response to Androgen Deprivation Therapy.

PURPOSE: Androgen receptor (AR) signaling is important in prostate cancer progression, and therapies that target this pathway have been the mainstay of treatment for advanced disease for over 70 years. Tumors eventually progress despite castration through a number of well-characterized mechanisms; however, little is known about what determines the magnitude of response to short-term pathway inhibition. METHODS: We evaluated a novel combination of AR-targeting therapies (degarelix, abiraterone, and bicalutamide) and noted that the objective patient response to therapy was highly variable. To investigate what was driving treatment resistance in poorly responding patients, as a secondary outcome we comprehensively characterized pre- and post-treatment samples using both whole-genome and RNA sequencing. RESULTS: We find that resistance following short-term treatment differs molecularly from typical progressive castration-resistant disease, associated with transcriptional reprogramming, to a transitional epithelial-to-mesenchymal transition (EMT) phenotype rather than an upregulation of AR signaling. Unexpectedly, tolerance to therapy appears to be the default state, with treatment response correlating with the prevalence of tumor cells deficient for SNAI2, a key regulator of EMT reprogramming. CONCLUSION: We show that EMT characterizes acutely resistant prostate tumors and that deletion of SNAI2, a key transcriptional regulator of EMT, correlates with clinical response.

MSH2-deficient prostate tumours have a distinct immune response and clinical outcome compared to MSH2-deficient colorectal or endometrial cancer.

BACKGROUND: Recent publications have shown patients with defects in the DNA mismatch repair (MMR) pathway driven by either MSH2 or MSH6 loss experience a significant increase in the incidence of prostate cancer. Moreover, this increased incidence of prostate cancer is accompanied by rapid disease progression and poor clinical outcomes. METHODS AND RESULTS: We show that androgen-receptor activation, a key driver of prostate carcinogenesis, can disrupt the MSH2 gene in prostate cancer. We screened tumours from two cohorts (recurrent/non-recurrent) of prostate cancer patients to confirm the loss of MSH2 protein expression and identified decreased MSH2 expression in recurrent cases. Stratifying the independent TCGA prostate cancer cohort for MSH2/6 expression revealed that patients with lower levels of MSH2/6 had significant worse outcomes, in contrast, endometrial and colorectal cancer patients with lower MSH2/6 levels. MMRd endometrial and colorectal tumours showed the expected increase in mutational burden, microsatellite instability and enhanced immune cell mobilisation but this was not evident in prostate tumours. CONCLUSIONS: We have shown that loss or reduced levels of MSH2/MSH6 protein in prostate cancer is associated with poor outcome. However, our data indicate that this is not associated with a statistically significant increase in mutational burden, microsatellite instability or immune cell mobilisation in a cohort of primary prostate cancers.

Inferring structural variant cancer cell fraction.

We present SVclone, a computational method for inferring the cancer cell fraction of structural variant (SV) breakpoints from whole-genome sequencing data. SVclone accurately determines the variant allele frequencies of both SV breakends, then simultaneously estimates the cancer cell fraction and SV copy number. We assess performance using in silico mixtures of real samples, at known proportions, created from two clonal metastases from the same patient. We find that SVclone's performance is comparable to single-nucleotide variant-based methods, despite having an order of magnitude fewer data points. As part of the Pan-Cancer Analysis of Whole Genomes (PCAWG) consortium, which aggregated whole-genome sequencing data from 2658 cancers across 38 tumour types, we use SVclone to reveal a subset of liver, ovarian and pancreatic cancers with subclonally enriched copy-number neutral rearrangements that show decreased overall survival. SVclone enables improved characterisation of SV intra-tumour heterogeneity.

Using equivalence class counts for fast and accurate testing of differential transcript usage.

Background: RNA sequencing has enabled high-throughput and fine-grained quantitative analyses of the transcriptome. While differential gene expression is the most widely used application of this technology, RNA-seq data also has the resolution to infer differential transcript usage (DTU), which can elucidate the role of different transcript isoforms between experimental conditions, cell types or tissues. DTU has typically been inferred from exon-count data, which has issues with assigning reads unambiguously to counting bins, and requires alignment of reads to the genome. Recently, approaches have emerged that use transcript quantifications estimates directly for DTU. Transcript counts can be inferred from 'pseudo' or lightweight aligners, which are significantly faster than traditional genome alignment. However, recent evaluations show lower sensitivity in DTU analysis. Transcript abundances are estimated from equivalence classes (ECs), which determine the transcripts that any given read is compatible with. Recent work has proposed performing differential expression testing directly on equivalence class read counts (ECs). Methods: Here we demonstrate that ECs can be used effectively with existing count-based methods for detecting DTU. We evaluate this approach on simulated human and drosophila data, as well as on a real dataset through subset testing. Results: We find that ECs counts have similar sensitivity and false discovery rates as exon-level counts but can be generated in a fraction of the time through the use of pseudo-aligners. Conclusions: We posit that equivalence class read counts are a natural unit on which to perform many types of analysis.

Comparing nodal versus bony metastatic spread using tumour phylogenies.

The role of lymph node metastases in distant prostate cancer dissemination and lethality is ill defined. Patients with metastases restricted to lymph nodes have a better prognosis than those with distant metastatic spread, suggesting the possibility of distinct aetiologies. To explore this, we traced patterns of cancer dissemination using tumour phylogenies inferred from genome-wide copy-number profiling of 48 samples across 3 patients with lymph node metastatic disease and 3 patients with osseous metastatic disease. Our results show that metastatic cells in regional lymph nodes originate from evolutionary advanced extraprostatic tumour cells rather than less advanced central tumour cell populations. In contrast, osseous metastases do not exhibit such a constrained developmental lineage, arising from either intra or extraprostatic tumour cell populations, at early and late stages in the evolution of the primary. Collectively, this comparison suggests that lymph node metastases may not be an intermediate developmental step for distant osseous metastases, but rather represent a distinct metastatic lineage.

Reduction in expression of the benign AR transcriptome is a hallmark of localised prostate cancer progression.

BACKGROUND: Despite the importance of androgen receptor (AR) signalling to prostate cancer development, little is known about how this signalling pathway changes with increasing grade and stage of the disease. OBJECTIVE: To explore changes in the normal AR transcriptome in localised prostate cancer, and its relation to adverse pathological features and disease recurrence. DESIGN: Publically accessible human prostate cancer expression arrays as well as RNA sequencing data from the prostate TCGA. Tumour associated PSA and PSAD were calculated for a large cohort of men (n=1108) undergoing prostatectomy. OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS: We performed a meta-analysis of the expression of an androgen-regulated gene set across datasets using Oncomine. Differential expression of selected genes in the prostate TCGA database was probed using the edgeR Bioconductor package. Changes in tumour PSA density with stage and grade were assessed by Student's t-test, and its association with biochemical recurrence explored by Kaplan-Meier curves and Cox regression. RESULTS: Meta-analysis revealed a systematic decline in the expression of a previously identified benign prostate androgen-regulated gene set with increasing tumour grade, reaching significance in nine of 25 genes tested despite increasing AR expression. These results were confirmed in a large independent dataset from the TCGA. At the protein level, when serum PSA was corrected for tumour volume, significantly lower levels were observed with increasing tumour grade and stage, and predicted disease recurrence. CONCLUSIONS: Lower PSA secretion-per-tumour-volume is associated with increasing grade and stage of prostate cancer, has prognostic relevance, and reflects a systematic perturbation of androgen signalling.

Tracking the origins and drivers of subclonal metastatic expansion in prostate cancer.

Tumour heterogeneity in primary prostate cancer is a well-established phenomenon. However, how the subclonal diversity of tumours changes during metastasis and progression to lethality is poorly understood. Here we reveal the precise direction of metastatic spread across four lethal prostate cancer patients using whole-genome and ultra-deep targeted sequencing of longitudinally collected primary and metastatic tumours. We find one case of metastatic spread to the surgical bed causing local recurrence, and another case of cross-metastatic site seeding combining with dynamic remoulding of subclonal mixtures in response to therapy. By ultra-deep sequencing end-stage blood, we detect both metastatic and primary tumour clones, even years after removal of the prostate. Analysis of mutations associated with metastasis reveals an enrichment of TP53 mutations, and additional sequencing of metastases from 19 patients demonstrates that acquisition of TP53 mutations is linked with the expansion of subclones with metastatic potential which we can detect in the blood.