Haroon Naeem

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.

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

BackgroundThe 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.ResultsWe 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.ConclusionsOur 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.

miRSel: Automated extraction of associations between microRNAs and genes from the biomedical literature

BackgroundMicroRNAs have been discovered as important regulators of gene expression. To identify the target genes of microRNAs, several databases and prediction algorithms have been developed. Only few experimentally confirmed microRNA targets are available in databases. Many of the microRNA targets stored in databases were derived from large-scale experiments that are considered not very reliable. We propose to use text mining of publication abstracts for extracting microRNA-gene associations including microRNA-target relations to complement current repositories.ResultsThe microRNA-gene association database miRSel combines text-mining results with existing databases and computational predictions. Text mining enables the reliable extraction of microRNA, gene and protein occurrences as well as their relationships from texts. Thereby, we increased the number of human, mouse and rat miRNA-gene associations by at least three-fold as compared to e.g. TarBase, a resource for miRNA-gene associations.ConclusionsOur database miRSel offers the currently largest collection of literature derived miRNA-gene associations. Comprehensive collections of miRNA-gene associations are important for the development of miRNA target prediction tools and the analysis of regulatory networks. miRSel is updated daily and can be queried using a web-based interface via microRNA identifiers, gene and protein names, PubMed queries as well as gene ontology (GO) terms. miRSel is freely available online at http://services.bio.ifi.lmu.de/mirsel.

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.

MIRTFnet: Analysis of miRNA Regulated Transcription Factors

Background Several expression datasets of miRNA transfection experiments are available to analyze the regulatory mechanisms downstream of miRNA effects. The miRNA induced regulatory effects can be propagated via transcription factors (TFs). We propose the method MIRTFnet to identify miRNA controlled TFs as active regulators if their downstream target genes are differentially expressed. Methodology/Principal Findings MIRTFnet enables the determination of active transcription factors (TFs) and is sensitive enough to exploit the small expression changes induced by the activity of miRNAs. For this purpose, different statistical tests were evaluated and compared. Based on the identified TFs, databases, computational predictions and the literature we construct regulatory models downstream of miRNA actions. Transfecting miRNAs are connected to active regulators via a network of miRNA-TF, miRNA-kinase-TF as well as TF-TF relationships. Based on 43 transfection experiments involving 17 cancer relevant miRNAs we show that MIRTFnet detects active regulators reliably. Conclusions/Significance The consensus of the individual regulatory models shows that the examined miRNAs induce activity changes in a common core of transcription factors involved in cancer related processes such as proliferation or apoptosis.

Rigorous assessment of gene set enrichment tests

MOTIVATION Several statistical tests are available to detect the enrichment of differential expression in gene sets. Such tests were originally proposed for analyzing gene sets associated with biological processes. The objective evaluation of tests on real measurements has not been possible as it is difficult to decide a priori, which processes will be affected in given experiments. RESULTS We present a first large study to rigorously assess and compare the performance of gene set enrichment tests on real expression measurements. Gene sets are defined based on the targets of given regulators such as transcription factors (TFs) and microRNAs (miRNAs). In contrast to processes, TFs and miRNAs are amenable to direct perturbations, e.g. regulator over-expression or deletion. We assess the ability of 14 different statistical tests to predict the perturbations from expression measurements in Escherichia coli, Saccharomyces cerevisiae and human. We also analyze how performance depends on the quality and comprehensiveness of the regulator targets via a permutation approach. We find that ANOVA and Wilcoxons test consistently perform better than for instance Kolmogorov-Smirnov and hypergeometric tests. For scenarios where the optimal test is not known, we suggest to combine all evaluated tests into an unweighted consensus, which also performs well in our assessment. Our results provide a guide for the selection of existing tests as well as a basis for the development and assessment of novel tests.

Genome-Wide Measures of Peripheral Blood Dna Methylation and Prostate Cancer Risk in a Prospective Nested Case-Control Study

Global measures of peripheral blood DNA methylation have been associated with risk of some malignancies, including breast, bladder, and gastric cancer. Here, we examined genome‐wide measures of peripheral blood DNA methylation in prostate cancer and its non‐aggressive and aggressive disease forms.

Tracking clonal diversity in metastatic prostate cancer progression.

193 Background: Genomic heterogeneity has been observed in a number of tumor types including prostate cancer. However, how subclonal tumor diversity changes during metastasis and progression to lethality remains unexplored. Large scale genomic analyses have reported the most prevalent somatic aberrations associated with the dominant clone of the tumor without permitting an analysis of subclonal complexity or how this complexity impinges on metastatic potential or resistance to treatment. Methods: To understand and track the evolution of lethal prostate cancer from initial therapy to end stage metastases, we performed longitudinal and multiregional sampling of tumors from 7 patients with lethal prostate cancer. We performed whole-genome sequencing, RNA sequencing, and SNP profiling. Computational approaches were used to reconstruct the genetic relationships and evolution of the tumors. These evolutionary tree reconstructions allowed us to observe the dynamics of chromoplexy and mutational processes along s...