Network-based analysis identifies epigenetic biomarkers of esophageal squamous cell carcinoma progression

MOTIVATION

A rapid progression of esophageal squamous cell carcinoma (ESCC) causes a high mortality rate because of the propensity for metastasis driven by genetic and epigenetic alterations. The identification of prognostic biomarkers would help prevent or control metastatic progression. Expression analyses have been used to find such markers, but do not always validate in separate cohorts. Epigenetic marks, such as DNA methylation, are a potential source of more reliable and stable biomarkers. Importantly, the integration of both expression and epigenetic alterations is more likely to identify relevant biomarkers.

RESULTS

We present a new analysis framework, using ESCC progression-associated gene regulatory network (GRN escc), to identify differentially methylated CpG sites prognostic of ESCC progression. From the CpG loci differentially methylated in 50 tumor-normal pairs, we selected 44 CpG loci most highly associated with survival and located in the promoters of genes more likely to belong to GRN escc. Using an independent ESCC cohort, we confirmed that 8/10 of CpG loci in the promoter of GRN escc genes significantly correlated with patient survival. In contrast, 0/10 CpG loci in the promoter genes outside the GRN escc were correlated with patient survival. We further characterized the GRN escc network topology and observed that the genes with methylated CpG loci associated with survival deviated from the center of mass and were less likely to be hubs in the GRN escc. We postulate that our analysis framework improves the identification of bona fide prognostic biomarkers from DNA methylation studies, especially with partial genome coverage.

Homozygous GNAS 393C-allele carriers with locally advanced esophageal cancer fail to benefit from platinum-based preoperative chemoradiotherapy

BACKGROUND

Currently, patients with locally advanced esophageal cancer receive neoadjuvant chemoradiotherapy but only about half of these patients benefit from this treatment. GNAS T393C has been shown to predict the postoperative course in solid tumors and may therefore be useful for treatment stratification. The aim of the present study was to determine if the single-nucleotide polymorphism GNAS T393C can be used for treatment stratification in esophageal cancer patients.

METHODS

A total of 596 patients underwent surgical resection for esophageal carcinoma from 1996 to 2008; 279 patients received chemoradiotherapy prior to surgery (RTX-SURG group). All patients and a reference group of 820 healthy White individuals were genotyped for GNAS T393C.

RESULTS

The 5-year-survival rate for the 317 patients who underwent esophagectomy as initial treatment (SURG group) was 57 % for homozygous C-allele carriers (n = 99) and 43 % for T-allele carriers (n = 218; log- rank test p = 0.025). Multivariate analysis revealed the GNAS T393C genotype (p = 0.034), pT (p < 0.001), pN (p < 0.001) and age (p < 0.001) as prognostic of survival. Homozygous C-allele carriers with a locally advanced tumor stage (cT3/T4, n = 129) in the SURG group had a 5-year survival rate of 37 %, which, remarkably, exceeded the 5-year survival rate of 30 % for the entire RTX-SURG group (n = 279). In the RTX-SURG group, the GNAS T393C genotype did not show any prognostic significance.

CONCLUSIONS

Patients with a locally advanced esophageal cancer and an homozygous GNAS 393C genotype do not benefit from platinum-based neoadjuvant chemoradiotherapy, indicating that these patients should be treated by alternative treatment strategies.

MiningABs: mining associated biomarkers across multi-connected gene expression datasets

Background

Human disease often arises as a consequence of alterations in a set of associated genes rather than alterations to a set of unassociated individual genes. Most previous microarray-based meta-analyses identified disease-associated genes or biomarkers independent of genetic interactions. Therefore, in this study, we present the first meta-analysis method capable of taking gene combination effects into account to efficiently identify associated biomarkers (ABs) across different microarray platforms.

Results

We propose a new meta-analysis approach called MiningABs to mine ABs across different array-based datasets. The similarity between paired probe sequences is quantified as a bridge to connect these datasets together. The ABs can be subsequently identified from an “improved” common logit model (c-LM) by combining several sibling-like LMs in a heuristic genetic algorithm selection process. Our approach is evaluated with two sets of gene expression datasets: i) 4 esophageal squamous cell carcinoma and ii) 3 hepatocellular carcinoma datasets. Based on an unbiased reciprocal test, we demonstrate that each gene in a group of ABs is required to maintain high cancer sample classification accuracy, and we observe that ABs are not limited to genes common to all platforms. Investigating the ABs using Gene Ontology (GO) enrichment, literature survey, and network analyses indicated that our ABs are not only strongly related to cancer development but also highly connected in a diverse network of biological interactions.

Conclusions

The proposed meta-analysis method called MiningABs is able to efficiently identify ABs from different independently performed array-based datasets, and we show its validity in cancer biology via GO enrichment, literature survey and network analyses. We postulate that the ABs may facilitate novel target and drug discovery, leading to improved clinical treatment. Java source code, tutorial, example and related materials are available at “http://sourceforge.net/projects/miningabs/”.

Genome-wide mutational landscape of mucinous carcinomatosis peritonei of appendiceal origin

BACKGROUND

Mucinous neoplasms of the appendix (MNA) are rare tumors which may progress from benign to malignant disease with an aggressive biological behavior. MNA is often diagnosed after metastasis to the peritoneal surfaces resulting in mucinous carcinomatosis peritonei (MCP). Genetic alterations in MNA are poorly characterized due to its low incidence, the hypo-cellularity of MCPs, and a lack of relevant pre-clinical models. As such, application of targeted therapies to this disease is limited to those developed for colorectal cancer and not based on molecular rationale.

METHODS

We sequenced the whole exomes of 10 MCPs of appendiceal origin to identify genome-wide somatic mutations and copy number aberrations and validated significant findings in 19 additional cases.

RESULTS

Our study demonstrates that MNA has a different molecular makeup than colorectal cancer. Most tumors have co-existing oncogenic mutations in KRAS (26/29) and GNAS (20/29) and are characterized by downstream PKA activation. High-grade tumors are GNAS wild-type (5/6), suggesting they do not progress from low-grade tumors. MNAs do share some genetic alterations with colorectal cancer including gain of 1q (5/10), Wnt, and TGFβ pathway alterations. In contrast, mutations in TP53 (1/10) and APC (0/10), common in colorectal cancer, are rare in MNA. Concurrent activation of the KRAS and GNAS mediated signaling pathways appears to be shared with pancreatic intraductal papillary mucinous neoplasm.

CONCLUSIONS

MNA genome-wide mutational analysis reveals genetic alterations distinct from colorectal cancer, in support of its unique pathophysiology and suggests new targeted therapeutic opportunities.

Whole genome sequencing of Ethiopian highlanders reveals conserved hypoxia tolerance genes

BACKGROUND

Although it has long been proposed that genetic factors contribute to adaptation to high altitude, such factors remain largely unverified. Recent advances in high-throughput sequencing have made it feasible to analyze genome-wide patterns of genetic variation in human populations. Since traditionally such studies surveyed only a small fraction of the genome, interpretation of the results was limited.

RESULTS

We report here the results of the first whole genome resequencing-based analysis identifying genes that likely modulate high altitude adaptation in native Ethiopians residing at 3,500 m above sea level on Bale Plateau or Chennek field in Ethiopia. Using cross-population tests of selection, we identify regions with a significant loss of diversity, indicative of a selective sweep. We focus on a 208 kbp gene-rich region on chromosome 19, which is significant in both of the Ethiopian subpopulations sampled. This region contains eight protein-coding genes and spans 135 SNPs. To elucidate its potential role in hypoxia tolerance, we experimentally tested whether individual genes from the region affect hypoxia tolerance in Drosophila. Three genes significantly impact survival rates in low oxygen: cic, an ortholog of human CIC, Hsl, an ortholog of human LIPE, and Paf-AHα, an ortholog of human PAFAH1B3.

CONCLUSIONS

Our study reveals evolutionarily conserved genes that modulate hypoxia tolerance. In addition, we show that many of our results would likely be unattainable using data from exome sequencing or microarray studies. This highlights the importance of whole genome sequencing for investigating adaptation by natural selection.

Genetic ancestry of participants in the National Children's Study

BACKGROUND

The National Children's Study (NCS) is a prospective epidemiological study in the USA tasked with identifying a nationally representative sample of 100,000 children, and following them from their gestation until they are 21 years of age. The objective of the study is to measure environmental and genetic influences on growth, development, and health. Determination of the ancestry of these NCS participants is important for assessing the diversity of study participants and for examining the effect of ancestry on various health outcomes.

RESULTS

We estimated the genetic ancestry of a convenience sample of 641 parents enrolled at the 7 original NCS Vanguard sites, by analyzing 30,000 markers on exome arrays, using the 1000 Genomes Project superpopulations as reference populations, and compared this with the measures of self-reported ethnicity and race. For 99% of the individuals, self-reported ethnicity and race agreed with the predicted superpopulation. NCS individuals self-reporting as Asian had genetic ancestry of either South Asian or East Asian groups, while those reporting as either Hispanic White or Hispanic Other had similar genetic ancestry. Of the 33 individuals who self-reported as Multiracial or Non-Hispanic Other, 33% matched the South Asian or East Asian groups, while these groups represented only 4.4% of the other reported categories.

CONCLUSIONS

Our data suggest that self-reported ethnicity and race have some limitations in accurately capturing Hispanic and South Asian populations. Overall, however, our data indicate that despite the complexity of the US population, individuals know their ancestral origins, and that self-reported ethnicity and race is a reliable indicator of genetic ancestry.

Evaluation of ultra-deep targeted sequencing for personalized breast cancer care

INTRODUCTION

The increasing number of targeted therapies, together with a deeper understanding of cancer genetics and drug response, have prompted major healthcare centers to implement personalized treatment approaches relying on high-throughput tumor DNA sequencing. However, the optimal way to implement this transformative methodology is not yet clear. Current assays may miss important clinical information such as the mutation allelic fraction, the presence of sub-clones or chromosomal rearrangements, or the distinction between inherited variants and somatic mutations. Here, we present the evaluation of ultra-deep targeted sequencing (UDT-Seq) to generate and interpret the molecular profile of 38 breast cancer patients from two academic medical centers.

METHODS

We sequenced 47 genes in matched germline and tumor DNA samples from 38 breast cancer patients. The selected genes, or the pathways they belong to, can be targeted by drugs or are important in familial cancer risk or drug metabolism.

RESULTS

Relying on the added value of sequencing matched tumor and germline DNA and using a dedicated analysis, UDT-Seq has a high sensitivity to identify mutations in tumors with low malignant cell content. Applying UDT-Seq to matched tumor and germline specimens from the 38 patients resulted in a proposal for at least one targeted therapy for 22 patients, the identification of tumor sub-clones in 3 patients, the suggestion of potential adverse drug effects in 3 patients and a recommendation for genetic counseling for 2 patients.

CONCLUSION

Overall our study highlights the additional benefits of a sequencing strategy, which includes germline DNA and is optimized for heterogeneous tumor tissues.

Identification of liver cancer progenitors whose malignant progression depends on autocrine IL-6 signaling

Hepatocellular carcinoma (HCC) is a slowly developing malignancy postulated to evolve from premalignant lesions in chronically damaged livers. However, it was never established that premalignant lesions actually contain tumor progenitors that give rise to cancer. Here, we describe isolation and characterization of HCC progenitor cells (HcPCs) from different mouse HCC models. Unlike fully malignant HCC, HcPCs give rise to cancer only when introduced into a liver undergoing chronic damage and compensatory proliferation. Although HcPCs exhibit a similar transcriptomic profile to bipotential hepatobiliary progenitors, the latter do not give rise to tumors. Cells resembling HcPCs reside within dysplastic lesions that appear several months before HCC nodules. Unlike early hepatocarcinogenesis, which depends on paracrine IL-6 production by inflammatory cells, due to upregulation of LIN28 expression, HcPCs had acquired autocrine IL-6 signaling that stimulates their in vivo growth and malignant progression. This may be a general mechanism that drives other IL-6-producing malignancies.

Whole-genome sequencing uncovers the genetic basis of chronic mountain sickness in Andean highlanders

The hypoxic conditions at high altitudes present a challenge for survival, causing pressure for adaptation. Interestingly, many high-altitude denizens (particularly in the Andes) are maladapted, with a condition known as chronic mountain sickness (CMS) or Monge disease. To decode the genetic basis of this disease, we sequenced and compared the whole genomes of 20 Andean subjects (10 with CMS and 10 without). We discovered 11 regions genome-wide with significant differences in haplotype frequencies consistent with selective sweeps. In these regions, two genes (an erythropoiesis regulator, SENP1, and an oncogene, ANP32D) had a higher transcriptional response to hypoxia in individuals with CMS relative to those without. We further found that downregulating the orthologs of these genes in flies dramatically enhanced survival rates under hypoxia, demonstrating that suppression of SENP1 and ANP32D plays an essential role in hypoxia tolerance. Our study provides an unbiased framework to identify and validate the genetic basis of adaptation to high altitudes and identifies potentially targetable mechanisms for CMS treatment.

Whole transcriptome sequencing enables discovery and analysis of viruses in archived primary central nervous system lymphomas

Primary central nervous system lymphomas (PCNSL) have a dramatically increased prevalence among persons living with AIDS and are known to be associated with human Epstein Barr virus (EBV) infection. Previous work suggests that in some cases, co-infection with other viruses may be important for PCNSL pathogenesis. Viral transcription in tumor samples can be measured using next generation transcriptome sequencing. We demonstrate the ability of transcriptome sequencing to identify viruses, characterize viral expression, and identify viral variants by sequencing four archived AIDS-related PCNSL tissue samples and analyzing raw sequencing reads. EBV was detected in all four PCNSL samples and cytomegalovirus (CMV), JC polyomavirus (JCV), and HIV were also discovered, consistent with clinical diagnoses. CMV was found to express three long non-coding RNAs recently reported as expressed during active infection. Single nucleotide variants were observed in each of the viruses observed and three indels were found in CMV. No viruses were found in several control tumor types including 32 diffuse large B-cell lymphoma samples. This study demonstrates the ability of next generation transcriptome sequencing to accurately identify viruses, including DNA viruses, in solid human cancer tissue samples.

Mutascope: sensitive detection of somatic mutations from deep amplicon sequencing

Summary: We present Mutascope, a sequencing analysis pipeline specifically developed for the identification of somatic variants present at low-allelic fraction from high-throughput sequencing of amplicons from matched tumor-normal specimen. Using datasets reproducing tumor genetic heterogeneity, we demonstrate that Mutascope has a higher sensitivity and generates fewer false-positive calls than tools designed for shotgun sequencing or diploid genomes.

Availability: Freely available on the web at http://sourceforge.net/projects/mutascope/.

Contact:oharismendy@ucsd.edu

Supplementary information:Supplementary data are available at Bioinformatics online.

Transcriptome sequencing of tumor subpopulations reveals a spectrum of therapeutic options for squamous cell lung cancer

Background

The only therapeutic options that exist for squamous cell lung carcinoma (SCC) are standard radiation and cytotoxic chemotherapy. Cancer stem cells (CSCs) are hypothesized to account for therapeutic resistance, suggesting that CSCs must be specifically targeted. Here, we analyze the transcriptome of CSC and non-CSC subpopulations by RNA-seq to identify new potential therapeutic strategies for SCC.

Methods

We sorted a SCC into CD133− and CD133+ subpopulations and then examined both by copy number analysis (CNA) and whole genome and transcriptome sequencing. We analyzed The Cancer Genome Atlas (TCGA) transcriptome data of 221 SCCs to determine the generality of our observations.

Results

Both subpopulations highly expressed numerous mRNA isoforms whose protein products are active drug targets for other cancers; 31 (25%) correspond to 18 genes under active investigation as mAb targets and an additional 4 (3%) are of therapeutic interest. Moreover, we found evidence that both subpopulations were proliferatively driven by very high levels of c-Myc and the TRAIL long isoform (TRAIL_L) and that normal apoptotic responses to high expression of these genes was prevented through high levels of Mcl-1_L and Bcl-x_L and c-Flip_L—isoforms for which drugs are now in clinical development. SCC RNA-seq data (n = 221) from TCGA supported our findings. Our analysis is inconsistent with the CSC concept that most cells in a cancer have lost their proliferative potential. Furthermore, our study suggests how to target both the CSC and non-CSC subpopulations with one treatment strategy.

Conclusions

Our study is relevant to SCC in particular for it presents numerous potential options to standard therapy that target the entire tumor. In so doing, it demonstrates how transcriptome sequencing provides insights into the molecular underpinnings of cancer propagating cells that, importantly, can be leveraged to identify new potential therapeutic options for cancers beyond what is possible with DNA sequencing.

High-resolution mutational profiling suggests the genetic validity of glioblastoma patient-derived pre-clinical models

Recent advances in the ability to efficiently characterize tumor genomes is enabling targeted drug development, which requires rigorous biomarker-based patient selection to increase effectiveness. Consequently, representative DNA biomarkers become equally important in pre-clinical studies. However, it is still unclear how well these markers are maintained between the primary tumor and the patient-derived tumor models. Here, we report the comprehensive identification of somatic coding mutations and copy number aberrations in four glioblastoma (GBM) primary tumors and their matched pre-clinical models: serum-free neurospheres, adherent cell cultures, and mouse xenografts. We developed innovative methods to improve the data quality and allow a strict comparison of matched tumor samples. Our analysis identifies known GBM mutations altering PTEN and TP53 genes, and new actionable mutations such as the loss of PIK3R1, and reveals clear patient-to-patient differences. In contrast, for each patient, we do not observe any significant remodeling of the mutational profile between primary to model tumors and the few discrepancies can be attributed to stochastic errors or differences in sample purity. Similarly, we observe ∼96% primary-to-model concordance in copy number calls in the high-cellularity samples. In contrast to previous reports based on gene expression profiles, we do not observe significant differences at the DNA level between in vitro compared to in vivo models. This study suggests, at a remarkable resolution, the genome-wide conservation of a patient’s tumor genetics in various pre-clinical models, and therefore supports their use for the development and testing of personalized targeted therapies.

A Pan-BCL2 inhibitor renders bone-marrow-resident human leukemia stem cells sensitive to tyrosine kinase inhibition

Leukemia stem cells (LSCs) play a pivotal role in the resistance of chronic myeloid leukemia (CML) to tyrosine kinase inhibitors (TKIs) and its progression to blast crisis (BC), in part, through the alternative splicing of self-renewal and survival genes. To elucidate splice-isoform regulators of human BC LSC maintenance, we performed whole-transcriptome RNA sequencing, splice-isoform-specific quantitative RT-PCR (qRT-PCR), nanoproteomics, stromal coculture, and BC LSC xenotransplantation analyses. Cumulatively, these studies show that the alternative splicing of multiple prosurvival BCL2 family genes promotes malignant transformation of myeloid progenitors into BC LSCS that are quiescent in the marrow niche and that contribute to therapeutic resistance. Notably, sabutoclax, a pan-BCL2 inhibitor, renders marrow-niche-resident BC LSCs sensitive to TKIs at doses that spare normal progenitors. These findings underscore the importance of alternative BCL2 family splice-isoform expression in BC LSC maintenance and suggest that the combinatorial inhibition of prosurvival BCL2 family proteins and BCR-ABL may eliminate dormant LSCs and obviate resistance.

Implementing genomic medicine in the clinic: the future is here

Although the potential for genomics to contribute to clinical care has long been anticipated, the pace of defining the risks and benefits of incorporating genomic findings into medical practice has been relatively slow. Several institutions have recently begun genomic medicine programs, encountering many of the same obstacles and developing the same solutions, often independently. Recognizing that successful early experiences can inform subsequent efforts, the National Human Genome Research Institute brought together a number of these groups to describe their ongoing projects and challenges, identify common infrastructure and research needs, and outline an implementation framework for investigating and introducing similar programs elsewhere. Chief among the challenges were limited evidence and consensus on which genomic variants were medically relevant; lack of reimbursement for genomically driven interventions; and burden to patients and clinicians of assaying, reporting, intervening, and following up genomic findings. Key infrastructure needs included an openly accessible knowledge base capturing sequence variants and their phenotypic associations and a framework for defining and cataloging clinically actionable variants. Multiple institutions are actively engaged in using genomic information in clinical care. Much of this work is being done in isolation and would benefit from more structured collaboration and sharing of best practices.

Genet Med 2013:15(4):258–267

Abstract P2-06-01: Breast-to-breast metastasis can cause hormone-receptor positive/triple negative bilateral synchronous tumors

Background: Prior work suggests that synchronous bilateral breast cancers may be clonal, with one tumor a metastasis, although prior techniques lacked resolution to prove this relationship. We used deep whole exome and shallow whole genome sequencing to compare bilateral tumors in two cases. In both cases, tumors were invasive and node negative with one tumor ER+/PR+/HER2− (HR+) lobular and the other triple negative (TN) ductal. Case 1 is a 75-year-old African American woman and Case 2 a 70-year-old white woman. With 44 and 12 months of follow up, respectively, neither patient has recurred.

Methods: Agilent SureSelect All Exon 50Mb Target Enrichment Kits were used for exome capture. Paired-end sequencing was performed with 200 base pair reads on the Illumina HiSeq 2000. Sequencing depth was targeted to cover 80% of the genome at 100x for three tumors with 70% cellularity, 200x for one tumor with 40% cellularity and 30x for germline. Tumor and germline exome results were compared to identify high confidence somatic single nucleotide variants (HC SNV). HC SNV's were called using GATK and stringent custom filtering to avoid false positives resulting from unrecognized germline single nucleotide polymorphisms. For each tumor pair, we define a clonality likelihood score (CLS) as the ratio of the number of HC SNV called at the same site and with the same alternate base in both tumors, to the total number of sites with an HC SNV called in either tumor. For comparison we analyzed the called SNV data from The Cancer Genome Atlas (TCGA) for exome sequenced HR+ or TN breast cancers.

Results: In Case 1, of 102 HC SNVs called in either tumor, 82 were shared, for a CLS of 80.3%. Additionally, 11 shared SNVs were synonymous, consistent with clonality. Lastly the non-shared HC SNVs were asymmetrically found in the TN tumor, consistent with clonal evolution during metastasis. Copy number analysis (CNA) showed Case 1 to have a deletion in 6q, including the ESR1 gene, unique to the TN tumor.

To assess significance of the CLS, we found three primary/metastatic clonal pairs in the TCGA to serve as positive controls. To serve as negative controls, from 357 ER+ and 46 TN primary TCGA tumors, we formed a total of 16,422 independent ER+/TN pairs. For the 3 clonal TCGA pairs, the CLS values were 39.3%, 58.5% and 60.0%. Most of the independent TCGA pairs had a CLS of zero (98.5%), with a maximum CLS of 2.8%. As the CLS for Case 1 lies above maximum observed CLS among 16,422 independent tumor pairs, we reject the hypothesis that this tumor pair is independent, at p &lt; 0.0001. For Case 2, of 222 HC SNV sites, 5 were shared for a CLS of 2.3%, consistent with independence.

Conclusion: Somatic single nucleotide mutations identified by exome sequencing found that the two tumors in Case 1 share &gt;80% of SNVs, consistent with clonal evolution of metastasis. The two tumors from Case 2 have few shared SNVs, consistent with independent origin. CNA results were consistent. This is the first clonality analysis reported from deep sequencing of phenotypically discordant synchronous bilateral breast cancers, and demonstrates that next-generation sequencing can distinguish clonal from independent tumor pairs with high confidence.

Funding: The Breast Cancer Research Foundation

Citation Information: Cancer Res 2012;72(24 Suppl):Abstract nr P2-06-01.

Abstract 5217: RNA editing enzyme ADAR1 drives leukemia stem cell differentiation and self-renewal in chronic myeloid leukemia

Chronic myeloid leukemia (CML) is the first cancer that was shown to originate from a genetic abnormality - the Philadelphia chromosome translocation, and production of its constitutively active protein tyrosine kinase product, BCR-ABL. The disease progresses slowly from chronic phase to accelerated phase, and later transforms to blast crisis (BC) stage. Cancer stem cells (CSCs) are a subset of tumor cells that have acquired certain treatment-resistant stem cell properties. High levels of RNA editing are associated with a primitive transcriptional program typical of human embryonic stem cells, and RNA editing plays an important role in both embryonic hematopoietic cell fate determination and in maintenance of normal hematopoiesis. Human RNA editing occurs primarily in secondary structures created by Alu retroelements and is carried out by enzymes such as the adenosine deaminase acting on RNA (ADAR) family. Among these, ADAR1 was also recently shown to be required for normal hematopoiesis by suppressing interferon-induced apoptosis. Our research focuses on dissecting the role of ADAR-mediated RNA editing in normal human hematopoietic progenitor cell development compared with malignant editing programs that may be activated in leukemia stem cells (LSC) during the progression of human CML. Our data demonstrates that BC LSC harbor increased levels of the interferon-responsive ADAR1 p150 isoform compared with chronic phase (CP) progenitors and normal cord blood progenitors. Expression of this isoform also exhibits a positive correlation with BCR-ABL expression levels - an effect which is specific to BC progenitors, suggesting that ADAR1 expression correlates with disease progression from CP to BC. In vitro hematopoietic progenitor assays with normal cord blood progenitors and CP samples transduced with lentiviral vectors overexpressing human ADAR1 reveals a significant shift in cell differentiation fate towards granulocyte-macrophage progenitor (GMP) colonies, which has been shown to be the initiating LSC population in CML Correspondingly, a progression towards erythroid lineage was observed in BC CML LSC transduced with lentiviral vectors expressing shRNA targeting ADAR1. Further qRT-PCR analyses revealed that the mechanism through which ADAR1 drives LSC and HSC differentiation towards myelopoiesis involves regulation of PU.1, which in turn inhibits GATA1 expression. Moreover, in vivo studies in a robust humanized CML mouse model showed a significant decrease in LSC serial transplantation potential of lentiviral shADAR1-transduced BC progenitors transplanted into neonatal RAG2-/-γc-/- mice. Together, these data support a crucial role for ADAR1 in cell fate determination and self-renewal potential of hematopoietic stem cells in both normal human progenitors and in malignant LSC that drive disease progression and therapeutic resistance.

Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 103rd Annual Meeting of the American Association for Cancer Research; 2012 Mar 31-Apr 4; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2012;72(8 Suppl):Abstract nr 5217. doi:1538-7445.AM2012-5217

Identification of high-confidence somatic mutations in whole genome sequence of formalin-fixed breast cancer specimens

The utilization of archived, formalin-fixed paraffin-embedded (FFPE) tumor samples for massive parallel sequencing has been challenging due to DNA damage and contamination with normal stroma. Here, we perform whole genome sequencing of DNA isolated from two triple-negative breast cancer tumors archived for >11 years as 5 µm FFPE sections and matched germline DNA. The tumor samples show differing amounts of FFPE damaged DNA sequencing reads revealed as relatively high alignment mismatch rates enriched for C · G > T · A substitutions compared to germline samples. This increase in mismatch rate is observable with as few as one million reads, allowing for an upfront evaluation of the sample integrity before whole genome sequencing. By applying innovative quality filters incorporating global nucleotide mismatch rates and local mismatch rates, we present a method to identify high-confidence somatic mutations even in the presence of FFPE induced DNA damage. This results in a breast cancer mutational profile consistent with previous studies and revealing potentially important functional mutations. Our study demonstrates the feasibility of performing genome-wide deep sequencing analysis of FFPE archived tumors of limited sample size such as residual cancer after treatment or metastatic biopsies.

Detection of low prevalence somatic mutations in solid tumors with ultra-deep targeted sequencing

Ultra-deep targeted sequencing (UDT-Seq) can identify subclonal somatic mutations in tumor samples. Early assays' limited breadth and depth restrict their clinical utility. Here, we target 71 kb of mutational hotspots in 42 cancer genes. We present novel methods enhancing both laboratory workflow and mutation detection. We evaluate UDT-Seq true sensitivity and specificity (> 94% and > 99%, respectively) for low prevalence mutations in a mixing experiment and demonstrate its utility using six tumor samples. With an improved performance when run on the Illumina Miseq, the UDT-Seq assay is well suited for clinical applications to guide therapy and study clonal selection in heterogeneous samples.

Abstract 4826: Identification of low prevalence somatic mutations in heterogeneous tumor samples

High throughput sequencing enables the digital measurement of each allele in a DNA sample. This provides an ideal method to interrogate mutations present in heterogeneous samples such as solid tumors in which clonal selection or contamination with stroma can hinder the identification of important somatic mutations. We developed an ultra-deep targeted sequencing (UDT-Seq) assay to screen 46 cancer genes via microdroplet PCR (RainDance Technologies) and direct sequencing of the amplicons on the Illumina GA. This UDT-Seq library interrogates ∼86 kb of DNA located in cancer mutational hotspots (87% of all COSMIC mutations) and ∼29 kb located in exons sequenced in HapMap samples for the assay calibration and performance evaluation. We devised a statistical filtering of the mutations by using both experimental estimation and statistical modeling of the sequencing error rate. We measured the performance of our assay by processing 4 blends of 4 HapMap samples, interrogating 160 SNPs with known prevalence in each blend. The sensitivity and specificity of our method is &gt;90% and &gt;99% respectively for variants present at 5% prevalence or greater. We next interrogated 4 cancer samples (xenografts, 2 of which with matching primary samples) from 4 different tissues. We were able to detect low-prevalence somatic mutations in all samples of which some are well-known driver mutations. Interestingly, the mutational profile from primary to xenograft is conserved for one sample but different for another. Finally, we analyzed the robustness of the detection and prevalence measurement after performing whole-genome amplification on DNA extracted from fresh frozen and FFPE tissue using Single Primer Isothermal Amplification technology (SPIA® -NuGEN Technologies). Featuring a streamlined sample preparation to interrogate a large number of bases, this assay is well suited for clinical applications to study clonal selection in cancer progression or treatment with sub-optimal heterogeneous cancer samples.

Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 102nd Annual Meeting of the American Association for Cancer Research; 2011 Apr 2-6; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2011;71(8 Suppl):Abstract nr 4826. doi:10.1158/1538-7445.AM2011-4826

Sensitive gene fusion detection using ambiguously mapping RNA-Seq read pairs

MOTIVATION

Paired-end whole transcriptome sequencing provides evidence for fusion transcripts. However, due to the repetitiveness of the transcriptome, many reads have multiple high-quality mappings. Previous methods to find gene fusions either ignored these reads or required additional longer single reads. This can obscure up to 30% of fusions and unnecessarily discards much of the data.

RESULTS

We present a method for using paired-end reads to find fusion transcripts without requiring unique mappings or additional single read sequencing. Using simulated data and data from tumors and cell lines, we show that our method can find fusions with ambiguously mapping read pairs without generating numerous spurious fusions from the many mapping locations.

AVAILABILITY

A C++ and Python implementation of the method demonstrated in this article is available at http://exon.ucsd.edu/ShortFuse.

CONTACT

mckinsel@ucsd.edu

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Accurate detection and genotyping of SNPs utilizing population sequencing data

Next-generation sequencing technologies have made it possible to sequence targeted regions of the human genome in hundreds of individuals. Deep sequencing represents a powerful approach for the discovery of the complete spectrum of DNA sequence variants in functionally important genomic intervals. Current methods for single nucleotide polymorphism (SNP) detection are designed to detect SNPs from single individual sequence data sets. Here, we describe a novel method SNIP-Seq (single nucleotide polymorphism identification from population sequence data) that leverages sequence data from a population of individuals to detect SNPs and assign genotypes to individuals. To evaluate our method, we utilized sequence data from a 200-kilobase (kb) region on chromosome 9p21 of the human genome. This region was sequenced in 48 individuals (five sequenced in duplicate) using the Illumina GA platform. Using this data set, we demonstrate that our method is highly accurate for detecting variants and can filter out false SNPs that are attributable to sequencing errors. The concordance of sequencing-based genotype assignments between duplicate samples was 98.8%. The 200-kb region was independently sequenced to a high depth of coverage using two sequence pools containing the 48 individuals. Many of the novel SNPs identified by SNIP-Seq from the individual sequencing were validated by the pooled sequencing data and were subsequently confirmed by Sanger sequencing. We estimate that SNIP-Seq achieves a low false-positive rate of approximately 2%, improving upon the higher false-positive rate for existing methods that do not utilize population sequence data. Collectively, these results suggest that analysis of population sequencing data is a powerful approach for the accurate detection of SNPs and the assignment of genotypes to individual samples.

Enrichment of sequencing targets from the human genome by solution hybridization

A method for target sequence enrichment from the human genome is described. This hybridization-based approach using oligonucleotide probes in solution has excellent sensitivity and accuracy for calling SNPs

To exploit fully the potential of current sequencing technologies for population-based studies, one must enrich for loci from the human genome. Here we evaluate the hybridization-based approach by using oligonucleotide capture probes in solution to enrich for approximately 3.9 Mb of sequence target. We demonstrate that the tiling probe frequency is important for generating sequence data with high uniform coverage of targets. We obtained 93% sensitivity to detect SNPs, with a calling accuracy greater than 99%.