Mutational Strand Asymmetries in Cancer Genomes Reveal Mechanisms of DNA Damage and Repair.

Mutational processes constantly shape the somatic genome, leading to immunity, aging, cancer, and other diseases. When cancer is the outcome, we are afforded a glimpse into these processes by the clonal expansion of the malignant cell. Here, we characterize a less explored layer of the mutational landscape of cancer: mutational asymmetries between the two DNA strands. Analyzing whole-genome sequences of 590 tumors from 14 different cancer types, we reveal widespread asymmetries across mutagenic processes, with transcriptional ("T-class") asymmetry dominating UV-, smoking-, and liver-cancer-associated mutations and replicative ("R-class") asymmetry dominating POLE-, APOBEC-, and MSI-associated mutations. We report a striking phenomenon of transcription-coupled damage (TCD) on the non-transcribed DNA strand and provide evidence that APOBEC mutagenesis occurs on the lagging-strand template during DNA replication. As more genomes are sequenced, studying and classifying their asymmetries will illuminate the underlying biological mechanisms of DNA damage and repair.

Evolution and impact of subclonal mutations in chronic lymphocytic leukemia.

Clonal evolution is a key feature of cancer progression and relapse. We studied intratumoral heterogeneity in 149 chronic lymphocytic leukemia (CLL) cases by integrating whole-exome sequence and copy number to measure the fraction of cancer cells harboring each somatic mutation. We identified driver mutations as predominantly clonal (e.g., MYD88, trisomy 12, and del(13q)) or subclonal (e.g., SF3B1 and TP53), corresponding to earlier and later events in CLL evolution. We sampled leukemia cells from 18 patients at two time points. Ten of twelve CLL cases treated with chemotherapy (but only one of six without treatment) underwent clonal evolution, predominantly involving subclones with driver mutations (e.g., SF3B1 and TP53) that expanded over time. Furthermore, presence of a subclonal driver mutation was an independent risk factor for rapid disease progression. Our study thus uncovers patterns of clonal evolution in CLL, providing insights into its stepwise transformation, and links the presence of subclones with adverse clinical outcomes.

Mapping the hallmarks of lung adenocarcinoma with massively parallel sequencing.

Lung adenocarcinoma, the most common subtype of non-small cell lung cancer, is responsible for more than 500,000 deaths per year worldwide. Here, we report exome and genome sequences of 183 lung adenocarcinoma tumor/normal DNA pairs. These analyses revealed a mean exonic somatic mutation rate of 12.0 events/megabase and identified the majority of genes previously reported as significantly mutated in lung adenocarcinoma. In addition, we identified statistically recurrent somatic mutations in the splicing factor gene U2AF1 and truncating mutations affecting RBM10 and ARID1A. Analysis of nucleotide context-specific mutation signatures grouped the sample set into distinct clusters that correlated with smoking history and alterations of reported lung adenocarcinoma genes. Whole-genome sequence analysis revealed frequent structural rearrangements, including in-frame exonic alterations within EGFR and SIK2 kinases. The candidate genes identified in this study are attractive targets for biological characterization and therapeutic targeting of lung adenocarcinoma.

Recurrent and functional regulatory mutations in breast cancer.

Genomic analysis of tumours has led to the identification of hundreds of cancer genes on the basis of the presence of mutations in protein-coding regions. By contrast, much less is known about cancer-causing mutations in non-coding regions. Here we perform deep sequencing in 360 primary breast cancers and develop computational methods to identify significantly mutated promoters. Clear signals are found in the promoters of three genes. FOXA1, a known driver of hormone-receptor positive breast cancer, harbours a mutational hotspot in its promoter leading to overexpression through increased E2F binding. RMRP and NEAT1, two non-coding RNA genes, carry mutations that affect protein binding to their promoters and alter expression levels. Our study shows that promoter regions harbour recurrent mutations in cancer with functional consequences and that the mutations occur at similar frequencies as in coding regions. Power analyses indicate that more such regions remain to be discovered through deep sequencing of adequately sized cohorts of patients.

Unpaired data empowers association tests.

MOTIVATION: There is growing interest in the biomedical research community to incorporate retrospective data, available in healthcare systems, to shed light on associations between different biomarkers. Understanding the association between various types of biomedical data, such as genetic, blood biomarkers, imaging, etc. can provide a holistic understanding of human diseases. To formally test a hypothesized association between two types of data in Electronic Health Records (EHRs), one requires a substantial sample size with both data modalities to achieve a reasonable power. Current association test methods only allow using data from individuals who have both data modalities. Hence, researchers cannot take advantage of much larger EHR samples that includes individuals with at least one of the data types, which limits the power of the association test. RESULTS: We present a new method called the Semi-paired Association Test (SAT) that makes use of both paired and unpaired data. In contrast to classical approaches, incorporating unpaired data allows SAT to produce better control of false discovery and to improve the power of the association test. We study the properties of the new test theoretically and empirically, through a series of simulations and by applying our method on real studies in the context of Chronic Obstructive Pulmonary Disease. We are able to identify an association between the high-dimensional characterization of Computed Tomography chest images and several blood biomarkers as well as the expression of dozens of genes involved in the immune system. AVAILABILITY AND IMPLEMENTATION: Code is available on https://github.com/batmanlab/Semi-paired-Association-Test. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Discovery and saturation analysis of cancer genes across 21 tumour types.

Although a few cancer genes are mutated in a high proportion of tumours of a given type (>20%), most are mutated at intermediate frequencies (2-20%). To explore the feasibility of creating a comprehensive catalogue of cancer genes, we analysed somatic point mutations in exome sequences from 4,742 human cancers and their matched normal-tissue samples across 21 cancer types. We found that large-scale genomic analysis can identify nearly all known cancer genes in these tumour types. Our analysis also identified 33 genes that were not previously known to be significantly mutated in cancer, including genes related to proliferation, apoptosis, genome stability, chromatin regulation, immune evasion, RNA processing and protein homeostasis. Down-sampling analysis indicates that larger sample sizes will reveal many more genes mutated at clinically important frequencies. We estimate that near-saturation may be achieved with 600-5,000 samples per tumour type, depending on background mutation frequency. The results may help to guide the next stage of cancer genomics.

Mutational heterogeneity in cancer and the search for new cancer-associated genes.

Major international projects are underway that are aimed at creating a comprehensive catalogue of all the genes responsible for the initiation and progression of cancer. These studies involve the sequencing of matched tumour-normal samples followed by mathematical analysis to identify those genes in which mutations occur more frequently than expected by random chance. Here we describe a fundamental problem with cancer genome studies: as the sample size increases, the list of putatively significant genes produced by current analytical methods burgeons into the hundreds. The list includes many implausible genes (such as those encoding olfactory receptors and the muscle protein titin), suggesting extensive false-positive findings that overshadow true driver events. We show that this problem stems largely from mutational heterogeneity and provide a novel analytical methodology, MutSigCV, for resolving the problem. We apply MutSigCV to exome sequences from 3,083 tumour-normal pairs and discover extraordinary variation in mutation frequency and spectrum within cancer types, which sheds light on mutational processes and disease aetiology, and in mutation frequency across the genome, which is strongly correlated with DNA replication timing and also with transcriptional activity. By incorporating mutational heterogeneity into the analyses, MutSigCV is able to eliminate most of the apparent artefactual findings and enable the identification of genes truly associated with cancer.

Medulloblastoma exome sequencing uncovers subtype-specific somatic mutations.

Medulloblastomas are the most common malignant brain tumours in children. Identifying and understanding the genetic events that drive these tumours is critical for the development of more effective diagnostic, prognostic and therapeutic strategies. Recently, our group and others described distinct molecular subtypes of medulloblastoma on the basis of transcriptional and copy number profiles. Here we use whole-exome hybrid capture and deep sequencing to identify somatic mutations across the coding regions of 92 primary medulloblastoma/normal pairs. Overall, medulloblastomas have low mutation rates consistent with other paediatric tumours, with a median of 0.35 non-silent mutations per megabase. We identified twelve genes mutated at statistically significant frequencies, including previously known mutated genes in medulloblastoma such as CTNNB1, PTCH1, MLL2, SMARCA4 and TP53. Recurrent somatic mutations were newly identified in an RNA helicase gene, DDX3X, often concurrent with CTNNB1 mutations, and in the nuclear co-repressor (N-CoR) complex genes GPS2, BCOR and LDB1. We show that mutant DDX3X potentiates transactivation of a TCF promoter and enhances cell viability in combination with mutant, but not wild-type, ß-catenin. Together, our study reveals the alteration of WNT, hedgehog, histone methyltransferase and now N-CoR pathways across medulloblastomas and within specific subtypes of this disease, and nominates the RNA helicase DDX3X as a component of pathogenic ß-catenin signalling in medulloblastoma.

Melanoma genome sequencing reveals frequent PREX2 mutations.

Melanoma is notable for its metastatic propensity, lethality in the advanced setting and association with ultraviolet exposure early in life. To obtain a comprehensive genomic view of melanoma in humans, we sequenced the genomes of 25 metastatic melanomas and matched germline DNA. A wide range of point mutation rates was observed: lowest in melanomas whose primaries arose on non-ultraviolet-exposed hairless skin of the extremities (3 and 14 per megabase (Mb) of genome), intermediate in those originating from hair-bearing skin of the trunk (5-55 per Mb), and highest in a patient with a documented history of chronic sun exposure (111 per Mb). Analysis of whole-genome sequence data identified PREX2 (phosphatidylinositol-3,4,5-trisphosphate-dependent Rac exchange factor 2)--a PTEN-interacting protein and negative regulator of PTEN in breast cancer--as a significantly mutated gene with a mutation frequency of approximately 14% in an independent extension cohort of 107 human melanomas. PREX2 mutations are biologically relevant, as ectopic expression of mutant PREX2 accelerated tumour formation of immortalized human melanocytes in vivo. Thus, whole-genome sequencing of human melanoma tumours revealed genomic evidence of ultraviolet pathogenesis and discovered a new recurrently mutated gene in melanoma.

TET2 mutations predict response to hypomethylating agents in myelodysplastic syndrome patients.

Only a minority of myelodysplastic syndrome (MDS) patients respond to hypomethylating agents (HMAs), but strong predictors of response are unknown. We sequenced 40 recurrently mutated myeloid malignancy genes in tumor DNA from 213 MDS patients collected before treatment with azacitidine (AZA) or decitabine (DEC). Mutations were examined for association with response and overall survival. The overall response rate of 47% was not different between agents. Clonal TET2 mutations predicted response (odds ratio [OR] 1.99, P = .036) when subclones unlikely to be detected by Sanger sequencing (allele fraction <10%) were treated as wild-type (WT). Response rates were highest in the subset of TET2 mutant patients without clonal ASXL1 mutations (OR 3.65, P = .009). Mutations of TP53 (hazard ratio [HR] 2.01, P = .002) and PTPN11 (HR 3.26, P = .006) were associated with shorter overall survival but not drug response. Murine-competitive bone marrow transplantation followed by treatment with AZA demonstrated that Tet2-null cells have an engraftment advantage over Tet2-WT cells. AZA significantly decreased this advantage for Tet2-null cells (P = .002) but not Tet2-WT cells (P = .212). Overall, Tet2 loss appears to sensitize cells to treatment with AZA in vivo, and TET2 mutations can identify patients more likely to respond to HMAs.

Somatic mutation as a mechanism of Wnt/ß-catenin pathway activation in CLL.

One major goal of cancer genome sequencing is to identify key genes and pathways that drive tumor pathogenesis. Although many studies have identified candidate driver genes based on recurrence of mutations in individual genes, subsets of genes with nonrecurrent mutations may also be defined as putative drivers if they affect a single biological pathway. In this fashion, we previously identified Wnt signaling as significantly mutated through large-scale massively parallel DNA sequencing of chronic lymphocytic leukemia (CLL). Here, we use a novel method of biomolecule delivery, vertical silicon nanowires, to efficiently introduce small interfering RNAs into CLL cells, and interrogate the effects of 8 of 15 mutated Wnt pathway members identified across 91 CLLs. In HEK293T cells, mutations in 2 genes did not generate functional changes, 3 led to dysregulated pathway activation, and 3 led to further activation or loss of repression of pathway activation. Silencing 4 of 8 mutated genes in CLL samples harboring the mutated alleles resulted in reduced viability compared with leukemia samples with wild-type alleles. We demonstrate that somatic mutations in CLL can generate dependence on this pathway for survival. These findings support the notion that nonrecurrent mutations at different nodes of the Wnt pathway can contribute to leukemogenesis.

Discovery and prioritization of somatic mutations in diffuse large B-cell lymphoma (DLBCL) by whole-exome sequencing.

To gain insight into the genomic basis of diffuse large B-cell lymphoma (DLBCL), we performed massively parallel whole-exome sequencing of 55 primary tumor samples from patients with DLBCL and matched normal tissue. We identified recurrent mutations in genes that are well known to be functionally relevant in DLBCL, including MYD88, CARD11, EZH2, and CREBBP. We also identified somatic mutations in genes for which a functional role in DLBCL has not been previously suspected. These genes include MEF2B, MLL2, BTG1, GNA13, ACTB, P2RY8, PCLO, and TNFRSF14. Further, we show that BCL2 mutations commonly occur in patients with BCL2/IgH rearrangements as a result of somatic hypermutation normally occurring at the IgH locus. The BCL2 point mutations are primarily synonymous, and likely caused by activation-induced cytidine deaminase-mediated somatic hypermutation, as shown by comprehensive analysis of enrichment of mutations in WRCY target motifs. Those nonsynonymous mutations that are observed tend to be found outside of the functionally important BH domains of the protein, suggesting that strong negative selection against BCL2 loss-of-function mutations is at play. Last, by using an algorithm designed to identify likely functionally relevant but infrequent mutations, we identify KRAS, BRAF, and NOTCH1 as likely drivers of DLBCL pathogenesis in some patients. Our data provide an unbiased view of the landscape of mutations in DLBCL, and this in turn may point toward new therapeutic strategies for the disease.

SF3B1 and other novel cancer genes in chronic lymphocytic leukemia.

BACKGROUND: The somatic genetic basis of chronic lymphocytic leukemia, a common and clinically heterogeneous leukemia occurring in adults, remains poorly understood. METHODS: We obtained DNA samples from leukemia cells in 91 patients with chronic lymphocytic leukemia and performed massively parallel sequencing of 88 whole exomes and whole genomes, together with sequencing of matched germline DNA, to characterize the spectrum of somatic mutations in this disease. RESULTS: Nine genes that are mutated at significant frequencies were identified, including four with established roles in chronic lymphocytic leukemia (TP53 in 15% of patients, ATM in 9%, MYD88 in 10%, and NOTCH1 in 4%) and five with unestablished roles (SF3B1, ZMYM3, MAPK1, FBXW7, and DDX3X). SF3B1, which functions at the catalytic core of the spliceosome, was the second most frequently mutated gene (with mutations occurring in 15% of patients). SF3B1 mutations occurred primarily in tumors with deletions in chromosome 11q, which are associated with a poor prognosis in patients with chronic lymphocytic leukemia. We further discovered that tumor samples with mutations in SF3B1 had alterations in pre-messenger RNA (mRNA) splicing. CONCLUSIONS: Our study defines the landscape of somatic mutations in chronic lymphocytic leukemia and highlights pre-mRNA splicing as a critical cellular process contributing to chronic lymphocytic leukemia.

Low-Dimensional Density Ratio Estimation for Covariate Shift Correction.

Covariate shift is a prevalent setting for supervised learning in the wild when the training and test data are drawn from different time periods, different but related domains, or via different sampling strategies. This paper addresses a transfer learning setting, with covariate shift between source and target domains. Most existing methods for correcting covariate shift exploit density ratios of the features to reweight the source-domain data, and when the features are high-dimensional, the estimated density ratios may suffer large estimation variances, leading to poor prediction performance. In this work, we investigate the dependence of covariate shift correction performance on the dimensionality of the features, and propose a correction method that finds a low-dimensional representation of the features, which takes into account feature relevant to the target Y, and exploits the density ratio of this representation for importance reweighting. We discuss the factors affecting the performance of our method and demonstrate its capabilities on both pseudo-real and real-world data.

Data-Driven Approach to Multiple-Source Domain Adaptation.

A key problem in domain adaptation is determining what to transfer across different domains. We propose a data-driven method to represent these changes across multiple source domains and perform unsupervised domain adaptation. We assume that the joint distributions follow a specific generating process and have a small number of identifiable changing parameters, and develop a data-driven method to identify the changing parameters by learning low-dimensional representations of the changing class-conditional distributions across multiple source domains. The learned low-dimensional representations enable us to reconstruct the target-domain joint distribution from unlabeled target-domain data, and further enable predicting the labels in the target domain. We demonstrate the efficacy of this method by conducting experiments on synthetic and real datasets.

Permanent endovenous pediatric pacing: absence of lead failure--20 years follow-up study.

BACKGROUND: The aim of the study was to analyze endovenous pacing lead survival in pediatric population implanted by cephalic cut down, or by axillary vein puncture. METHODS: All implantations were performed in total endotracheal anesthesia, by the same surgeon. Implantations of ventricular leads were performed by cephalic vein cut down or by external jugular vein preparation. In dual-chamber pacing, atrial leads were implanted via cephalic vein (along with ventricular lead), by axillary vein puncture or via external jugular vein. All implanted leads were secured by resorbable suture. RESULTS: Over the 20-year follow-up period, 105 children of 5.7 years average age (range 1 day-15 years) were implanted with a permanent endovenous pacing system for congenital or postsurgical complete atrioventricular block or sinus node disease. Within the group, 27 patients (25.7%) weighed less than 10 kg on implantation. A total of 121 endovenous leads were implanted. All ventricular leads were with a passive fixation mechanism, and most of them unipolar (87.6%) and steroid eluting (94.2%). Leads implanted in atrial position were 82% bipolar, predominantly with active fixation (94%), and all steroid eluting. The most frequently used mode of stimulation was VVIR (66.6%). No acute or chronic lead displacement, exit block, sensing problem, lead conductor fracture, insulation defect or infections were observed during the total follow-up of 709 pacing years (average 6.9, range 0-20 years). CONCLUSION: Implantation of the endovenous leads by preparation of the cephalic or puncture of the axillary vein, with lead fixation by resorbable suture represents a method of choice.

Reconstructing cancer drug response networks using multitask learning.

BACKGROUND: Translating in vitro results to clinical tests is a major challenge in systems biology. Here we present a new Multi-Task learning framework which integrates thousands of cell line expression experiments to reconstruct drug specific response networks in cancer. RESULTS: The reconstructed networks correctly identify several shared key proteins and pathways while simultaneously highlighting many cell type specific proteins. We used top proteins from each drug network to predict survival for patients prescribed the drug. CONCLUSIONS: Predictions based on proteins from the in-vitro derived networks significantly outperformed predictions based on known cancer genes indicating that Multi-Task learning can indeed identify accurate drug response networks.

Low incidence of complications after cephalic vein cutdown for pacemaker lead implantation in children weighing less than 10 kilograms: A single-center experience with long-term follow-up.

BACKGROUND: Only a few studies on the cephalic vein cutdown technique for pacemaker lead implantation in children weighing ≤10 kg have been reported even though the procedure is widely accepted in adults. OBJECTIVE: The purpose of this study was to prove that cephalic vein cutdown for pacemaker lead implantation is a reliable technique with a low incidence of complications in children weighing ≤10 kg. METHODS: The study included 44 children weighing ≤10 kg with an endocardial pacemaker. Cephalic, subclavian, and axillary vein diameters were measured by ultrasound before implantation. The measured diameters were used to select either an endocardial or epicardial surgical technique. Regular 6-month follow-up visits included pacemaker interrogation and clinical and ultrasound examinations. RESULTS: Two dual-chamber and 42 single-chamber pacemakers were implanted. Mean weight at implantation was 6.24 kg (range 2.25-10.40 kg), and mean age was 11.4 months (range 1 day-47 months). In 40 children (90.1%), the ventricular leads were implanted using the cephalic vein cutdown technique, and implantation was accomplished via the prepared right external jugular vein in 4 of the children (9.9%). The atrial leads were implanted using axillary vein puncture and external jugular vein preparations. Mean follow-up was 8.9 years (range 0-20.9 years). Only 1 pacemaker-related complication was detected (a lead fracture near the connector that was successfully resolved using a lead repair kit). CONCLUSION: The cephalic vein cutdown technique is feasible and reliable in children weighing ≤10 kg, which justifies the application of additional surgical effort in the treatment of these small patients.

Integrative and comparative genomic analysis of HPV-positive and HPV-negative head and neck squamous cell carcinomas.

PURPOSE: The genetic differences between human papilloma virus (HPV)-positive and -negative head and neck squamous cell carcinomas (HNSCC) remain largely unknown. To identify differential biology and novel therapeutic targets for both entities, we determined mutations and copy-number aberrations in a large cohort of locoregionally advanced HNSCC. EXPERIMENTAL DESIGN: We performed massively parallel sequencing of 617 cancer-associated genes in 120 matched tumor/normal samples (42.5% HPV-positive). Mutations and copy-number aberrations were determined and results validated with a secondary method. RESULTS: The overall mutational burden in HPV-negative and HPV-positive HNSCC was similar with an average of 15.2 versus 14.4 somatic exonic mutations in the targeted cancer-associated genes. HPV-negative tumors showed a mutational spectrum concordant with published lung squamous cell carcinoma analyses with enrichment for mutations in TP53, CDKN2A, MLL2, CUL3, NSD1, PIK3CA, and NOTCH genes. HPV-positive tumors showed unique mutations in DDX3X, FGFR2/3 and aberrations in PIK3CA, KRAS, MLL2/3, and NOTCH1 were enriched in HPV-positive tumors. Currently targetable genomic alterations were identified in FGFR1, DDR2, EGFR, FGFR2/3, EPHA2, and PIK3CA. EGFR, CCND1, and FGFR1 amplifications occurred in HPV-negative tumors, whereas 17.6% of HPV-positive tumors harbored mutations in fibroblast growth factor receptor genes (FGFR2/3), including six recurrent FGFR3 S249C mutations. HPV-positive tumors showed a 5.8% incidence of KRAS mutations, and DNA-repair gene aberrations, including 7.8% BRCA1/2 mutations, were identified. CONCLUSIONS: The mutational makeup of HPV-positive and HPV-negative HNSCC differs significantly, including targetable genes. HNSCC harbors multiple therapeutically important genetic aberrations, including frequent aberrations in the FGFR and PI3K pathway genes. See related commentary by Krigsfeld and Chung, p. 495.

Paired exome analysis of Barrett's esophagus and adenocarcinoma.

Barrett's esophagus is thought to progress to esophageal adenocarcinoma (EAC) through a stepwise progression with loss of CDKN2A followed by TP53 inactivation and aneuploidy. Here we present whole-exome sequencing from 25 pairs of EAC and Barrett's esophagus and from 5 patients whose Barrett's esophagus and tumor were extensively sampled. Our analysis showed that oncogene amplification typically occurred as a late event and that TP53 mutations often occurred early in Barrett's esophagus progression, including in non-dysplastic epithelium. Reanalysis of additional EAC exome data showed that the majority (62.5%) of EACs emerged following genome doubling and that tumors with genomic doubling had different patterns of genomic alterations, with more frequent oncogenic amplification and less frequent inactivation of tumor suppressors, including CDKN2A. These data suggest that many EACs emerge not through the gradual accumulation of tumor-suppressor alterations but rather through a more direct path whereby a TP53-mutant cell undergoes genome doubling, followed by the acquisition of oncogenic amplifications.