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.

A pan-cancer compendium of chromosomal instability.

Chromosomal instability (CIN) results in the accumulation of large-scale losses, gains and rearrangements of DNA1. The broad genomic complexity caused by CIN is a hallmark of cancer2; however, there is no systematic framework to measure different types of CIN and their effect on clinical phenotypes pan-cancer. Here we evaluate the extent, diversity and origin of CIN across 7,880 tumours representing 33 cancer types. We present a compendium of 17 copy number signatures that characterize specific types of CIN, with putative aetiologies supported by multiple independent data sources. The signatures predict drug response and identify new drug targets. Our framework refines the understanding of impaired homologous recombination, which is one of the most therapeutically targetable types of CIN. Our results illuminate a fundamental structure underlying genomic complexity in human cancers and provide a resource to guide future CIN research.

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.

CNpare: matching DNA copy number profiles.

SUMMARY: Selecting the optimal cancer cell line for an experiment can be challenging given the diversity of lines available. Here, we present CNpare, which identifies similar cell line models based on genome-wide DNA copy number. AVAILABILITY AND IMPLEMENTATION: CNpare is available as an R package at https://github.com/macintyrelab/CNpare. All analysis performed in the manuscript can be reproduced via the code found at https://github.com/macintyrelab/CNpare_analyses. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Prognostic markers of inflammation in endometrioid and clear cell ovarian cancer.

OBJECTIVES: Cancer-related systemic inflammation has been associated with prognosis in multiple cancer types. Conversely, local inflammation, which is characterized by dense intratumoral immune infiltrates, is a favorable predictor of survival outcome. However, these survival associations are not well established in ovarian cancer, particularly in the less frequent endometrioid and clear cell endometriosis associated histotypes. METHODS: This retrospective study included 119 patients (63 endometrioid and 56 clear cell ovarian carcinomas). We performed a comprehensive survival association analysis of both systemic (neutrophil-to-lymphocyte ratio or presence of endometriosis) and local inflammation markers (CD3+ and CD8+ tumor infiltrating lymphocytes) using multivariate Cox proportional hazards models that account for confounding factors. RESULTS: Medium to high levels of intraepithelial CD8+ tumor infiltrating lymphocytes are associated with longer survival in endometrioid ovarian cancer (p=0.04). In addition, we found that intraepithelial CD8+ tumor infiltrating lymphocytes are prognostic in clear cell ovarian cancer (p=0.02), and that intraepithelial CD3+ tumor infiltrating lymphocytes are also associated with improved outcome (p=0.02). Furthermore, intratumoral CD3+ and CD8+ tumor infiltrating lymphocytes showed improved prognosis in the endometrioid subtype (p<0.1). No prognostic value was observed for systemic immune markers. CONCLUSIONS: In this study, patients with endometrioid and clear cell ovarian cancer with moderate to high CD8+ and CD3+ intraepithelial tumor infiltrating lymphocytes had longer overall survival. Higher expression of intratumoral CD3+ and CD8+ tumor infiltrating lymphocytes also showed an improved outcome in endometrioid ovarian cancer. In contrast, systemic inflammation, evaluated by neutrophil-to-lymphocyte ratio or presence of endometriosis, did not have a prognostic impact in these histologic subtypes.

Sequencing Structural Variants in Cancer for Precision Therapeutics.

The identification of mutations that guide therapy selection for patients with cancer is now routine in many clinical centres. The majority of assays used for solid tumour profiling use DNA sequencing to interrogate somatic point mutations because they are relatively easy to identify and interpret. Many cancers, however, including high-grade serous ovarian, oesophageal, and small-cell lung cancer, are driven by somatic structural variants that are not measured by these assays. Therefore, there is currently an unmet need for clinical assays that can cheaply and rapidly profile structural variants in solid tumours. In this review we survey the landscape of 'actionable' structural variants in cancer and identify promising detection strategies based on massively-parallel sequencing.

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.

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.

Workshops: a great way to enhance and supplement a degree.

As part of the International Society for Computational Biology Student Council (ISCB-SC), Regional Student Groups (RSGs) have helped organise workshops in the emerging fields of bioinformatics and computational biology. Workshops are a great way for students to gain hands-on experience and rapidly acquire knowledge in advanced research topics where curriculum-based education is yet to be developed. RSG workshops have improved dissemination of knowledge of the latest bioinformatics techniques and resources among student communities and young scientists, especially in developing nations. This article highlights some of the benefits and challenges encountered while running RSG workshops. Examples cover a variety of subjects, including introductory bioinformatics and advanced bioinformatics, as well as soft skills such as networking, career development, and socializing. The collective experience condensed in this article is a useful starting point for students wishing to organise their own tailor-made workshops.

Reducing the risk of false discovery enabling identification of biologically significant genome-wide methylation status using the HumanMethylation450 array.

BACKGROUND: The Illumina HumanMethylation450 BeadChip (HM450K) measures the DNA methylation of 485,512 CpGs in the human genome. The technology relies on hybridization of genomic fragments to probes on the chip. However, certain genomic factors may compromise the ability to measure methylation using the array such as single nucleotide polymorphisms (SNPs), small insertions and deletions (INDELs), repetitive DNA, and regions with reduced genomic complexity. Currently, there is no clear method or pipeline for determining which of the probes on the HM450K bead array should be retained for subsequent analysis in light of these issues. RESULTS: We comprehensively assessed the effects of SNPs, INDELs, repeats and bisulfite induced reduced genomic complexity by comparing HM450K bead array results with whole genome bisulfite sequencing. We determined which CpG probes provided accurate or noisy signals. From this, we derived a set of high-quality probes that provide unadulterated measurements of DNA methylation. CONCLUSIONS: Our method significantly reduces the risk of false discoveries when using the HM450K bead array, while maximising the power of the array to detect methylation status genome-wide. Additionally, we demonstrate the utility of our method through extraction of biologically relevant epigenetic changes in prostate cancer.

Genome-wide analysis distinguishes hyperglycemia regulated epigenetic signatures of primary vascular cells.

Emerging evidence suggests that poor glycemic control mediates post-translational modifications to the H3 histone tail. We are only beginning to understand the dynamic role of some of the diverse epigenetic changes mediated by hyperglycemia at single loci, yet elevated glucose levels are thought to regulate genome-wide changes, and this still remains poorly understood. In this article we describe genome-wide histone H3K9/K14 hyperacetylation and DNA methylation maps conferred by hyperglycemia in primary human vascular cells. Chromatin immunoprecipitation (ChIP) as well as CpG methylation (CpG) assays, followed by massive parallel sequencing (ChIP-seq and CpG-seq) identified unique hyperacetylation and CpG methylation signatures with proximal and distal patterns of regionalization associative with gene expression. Ingenuity knowledge-based pathway and gene ontology analyses indicate that hyperglycemia significantly affects human vascular chromatin with the transcriptional up-regulation of genes involved in metabolic and cardiovascular disease. We have generated the first installment of a reference collection of hyperglycemia-induced chromatin modifications using robust and reproducible platforms that allow parallel sequencing-by-synthesis of immunopurified content. We uncover that hyperglycemia-mediated induction of genes and pathways associated with endothelial dysfunction occur through modulation of acetylated H3K9/K14 inversely correlated with methyl-CpG content.

The regional student group program of the ISCB student council: stories from the road.

The International Society for Computational Biology (ISCB) Student Council was launched in 2004 to facilitate interaction between young scientists in the fields of bioinformatics and computational biology. Since then, the Student Council has successfully run events and programs to promote the development of the next generation of computational biologists. However, in its early years, the Student Council faced a major challenge, in that students from different geographical regions had different needs; no single activity or event could address the needs of all students. To overcome this challenge, the Student Council created the Regional Student Group (RSG) program. The program consists of locally organised and run student groups that address the specific needs of students in their region. These groups usually encompass a given country, and, via affiliation with the international Student Council, are provided with financial support, organisational support, and the ability to share information with other RSGs. In the last five years, RSGs have been created all over the world and organised activities that have helped develop dynamic bioinformatics student communities. In this article series, we present common themes emerging from RSG initiatives, explain their goals, and highlight the challenges and rewards through specific examples. This article, the first in the series, introduces the Student Council and provides a high-level overview of RSG activities. Our hope is that the article series will be a valuable source of information and inspiration for initiating similar activities in other regions and scientific communities.

Breaking the ice and forging links: the importance of socializing in research.

When meeting someone for the first time-whether another PhD student, or the Founding Editor-in-chief of PLOS Computational Biology-nothing breaks the ice like eating pancakes or having drinks together. A social atmosphere provides a relaxed, informal environment where people can connect, share ideas, and form collaborations. Being able to build a network and thrive in a social environment is crucial to a successful scientific career. This article highlights the importance of bringing people together who speak the same scientific language in an informal setting. Using examples of events held by Regional Student Groups of the ISCB's Student Council, this article shows that socializing is much more than simply sharing a drink.

scAbsolute: measuring single-cell ploidy and replication status.

Cancer cells often exhibit DNA copy number aberrations and can vary widely in their ploidy. Correct estimation of the ploidy of single-cell genomes is paramount for downstream analysis. Based only on single-cell DNA sequencing information, scAbsolute achieves accurate and unbiased measurement of single-cell ploidy and replication status, including whole-genome duplications. We demonstrate scAbsolute's capabilities using experimental cell multiplets, a FUCCI cell cycle expression system, and a benchmark against state-of-the-art methods. scAbsolute provides a robust foundation for single-cell DNA sequencing analysis across different technologies and has the potential to enable improvements in a number of downstream analyses.

High-grade serous ovarian carcinoma organoids as models of chromosomal instability.

High-grade serous ovarian carcinoma (HGSOC) is the most genomically complex cancer, characterized by ubiquitous TP53 mutation, profound chromosomal instability, and heterogeneity. The mutational processes driving chromosomal instability in HGSOC can be distinguished by specific copy number signatures. To develop clinically relevant models of these mutational processes we derived 15 continuous HGSOC patient-derived organoids (PDOs) and characterized them using bulk transcriptomic, bulk genomic, single-cell genomic, and drug sensitivity assays. We show that HGSOC PDOs comprise communities of different clonal populations and represent models of different causes of chromosomal instability including homologous recombination deficiency, chromothripsis, tandem-duplicator phenotype, and whole genome duplication. We also show that these PDOs can be used as exploratory tools to study transcriptional effects of copy number alterations as well as compound-sensitivity tests. In summary, HGSOC PDO cultures provide validated genomic models for studies of specific mutational processes and precision therapeutics.

The copy number and mutational landscape of recurrent ovarian high-grade serous carcinoma.

The drivers of recurrence and resistance in ovarian high grade serous carcinoma remain unclear. We investigate the acquisition of resistance by collecting tumour biopsies from a cohort of 276 women with relapsed ovarian high grade serous carcinoma in the BriTROC-1 study. Panel sequencing shows close concordance between diagnosis and relapse, with only four discordant cases. There is also very strong concordance in copy number between diagnosis and relapse, with no significant difference in purity, ploidy or focal somatic copy number alterations, even when stratified by platinum sensitivity or prior chemotherapy lines. Copy number signatures are strongly correlated with immune cell infiltration, whilst diagnosis samples from patients with primary platinum resistance have increased rates of CCNE1 and KRAS amplification and copy number signature 1 exposure. Our data show that the ovarian high grade serous carcinoma genome is remarkably stable between diagnosis and relapse and acquired chemotherapy resistance does not select for common copy number drivers.

is-rSNP: a novel technique for in silico regulatory SNP detection.

MOTIVATION: Determining the functional impact of non-coding disease-associated single nucleotide polymorphisms (SNPs) identified by genome-wide association studies (GWAS) is challenging. Many of these SNPs are likely to be regulatory SNPs (rSNPs): variations which affect the ability of a transcription factor (TF) to bind to DNA. However, experimental procedures for identifying rSNPs are expensive and labour intensive. Therefore, in silico methods are required for rSNP prediction. By scoring two alleles with a TF position weight matrix (PWM), it can be determined which SNPs are likely rSNPs. However, predictions in this manner are noisy and no method exists that determines the statistical significance of a nucleotide variation on a PWM score. RESULTS: We have designed an algorithm for in silico rSNP detection called is-rSNP. We employ novel convolution methods to determine the complete distributions of PWM scores and ratios between allele scores, facilitating assignment of statistical significance to rSNP effects. We have tested our method on 41 experimentally verified rSNPs, correctly predicting the disrupted TF in 28 cases. We also analysed 146 disease-associated SNPs with no known functional impact in an attempt to identify candidate rSNPs. Of the 11 significantly predicted disrupted TFs, 9 had previous evidence of being associated with the disease in the literature. These results demonstrate that is-rSNP is suitable for high-throughput screening of SNPs for potential regulatory function. This is a useful and important tool in the interpretation of GWAS. AVAILABILITY: is-rSNP software is available for use at: www.genomics.csse.unimelb.edu.au/is-rSNP.

FrenchFISH: Poisson Models for Quantifying DNA Copy Number From Fluorescence In Situ Hybridization of Tissue Sections.

PURPOSE: Chromosomal aberration and DNA copy number change are robust hallmarks of cancer. The gold standard for detecting copy number changes in tumor cells is fluorescence in situ hybridization (FISH) using locus-specific probes that are imaged as fluorescent spots. However, spot counting often does not perform well on solid tumor tissue sections due to partially represented or overlapping nuclei. MATERIALS AND METHODS: To overcome these challenges, we have developed a computational approach called FrenchFISH, which comprises a nuclear volume correction method coupled with two types of Poisson models: either a Poisson model for improved manual spot counting without the need for control probes or a homogeneous Poisson point process model for automated spot counting. RESULTS: We benchmarked the performance of FrenchFISH against previous approaches using a controlled simulation scenario and tested it experimentally in 12 ovarian carcinoma FFPE-tissue sections for copy number alterations at three loci (c-Myc, hTERC, and SE7). FrenchFISH outperformed standard spot counting with 74% of the automated counts having < 1 copy number difference from the manual counts and 17% having < 2 copy number differences, while taking less than one third of the time of manual counting. CONCLUSION: FrenchFISH is a general approach that can be used to enhance clinical diagnosis on sections of any tissue by both speeding up and improving the accuracy of spot count estimates.

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.