Donor Clonal Hematopoiesis and Recipient Outcomes After Transplantation

PURPOSE

Clonal hematopoiesis (CH) can be transmitted from a donor to a recipient during allogeneic hematopoietic cell transplantation. Exclusion of candidate donors with CH is controversial since its impact on recipient outcomes and graft alloimmune function is uncertain.

PATIENTS AND METHODS

We performed targeted error-corrected sequencing on samples from 1,727 donors age 40 years or older and assessed the effect of donor CH on recipient clinical outcomes. We measured long-term engraftment of 102 donor clones and cytokine levels in 256 recipients at 3 and 12 months after transplant.

RESULTS

CH was present in 22.5% of donors, with DNMT3A (14.6%) and TET2 (5.2%) mutations being most common; 85% of donor clones showed long-term engraftment in recipients after transplantation, including clones with a variant allele fraction < 0.01. DNMT3A-CH with a variant allele fraction ≥ 0.01, but not smaller clones, was associated with improved recipient overall (hazard ratio [HR], 0.79; P = .042) and progression-free survival (HR, 0.72; P = .003) after adjustment for significant clinical variables. In patients who received calcineurin-based graft-versus-host disease prophylaxis, donor DNMT3A-CH was associated with reduced relapse (subdistribution HR, 0.59; P = .014), increased chronic graft-versus-host disease (subdistribution HR, 1.36; P = .042), and higher interleukin-12p70 levels in recipients. No recipient of sole DNMT3A or TET2-CH developed donor cell leukemia (DCL). In seven of eight cases, DCL evolved from donor CH with rare TP53 or splicing factor mutations or from donors carrying germline DDX41 mutations.

CONCLUSION

Donor CH is closely associated with clinical outcomes in transplant recipients, with differential impact on graft alloimmune function and potential for leukemic transformation related to mutated gene and somatic clonal abundance. Donor DNMT3A-CH is associated with improved recipient survival because of reduced relapse risk and with an augmented network of inflammatory cytokines in recipients. Risk of DCL in allogeneic hematopoietic cell transplantation is driven by somatic myelodysplastic syndrome-associated mutations or germline predisposition in donors.

Donor Clonal Hematopoiesis and Recipient Outcomes After Transplantation

PURPOSE

Clonal hematopoiesis (CH) can be transmitted from a donor to a recipient during allogeneic hematopoietic cell transplantation. Exclusion of candidate donors with CH is controversial since its impact on recipient outcomes and graft alloimmune function is uncertain.

PATIENTS AND METHODS

We performed targeted error-corrected sequencing on samples from 1,727 donors age 40 years or older and assessed the effect of donor CH on recipient clinical outcomes. We measured long-term engraftment of 102 donor clones and cytokine levels in 256 recipients at 3 and 12 months after transplant.

RESULTS

CH was present in 22.5% of donors, with DNMT3A (14.6%) and TET2 (5.2%) mutations being most common; 85% of donor clones showed long-term engraftment in recipients after transplantation, including clones with a variant allele fraction < 0.01. DNMT3A-CH with a variant allele fraction ≥ 0.01, but not smaller clones, was associated with improved recipient overall (hazard ratio [HR], 0.79; P = .042) and progression-free survival (HR, 0.72; P = .003) after adjustment for significant clinical variables. In patients who received calcineurin-based graft-versus-host disease prophylaxis, donor DNMT3A-CH was associated with reduced relapse (subdistribution HR, 0.59; P = .014), increased chronic graft-versus-host disease (subdistribution HR, 1.36; P = .042), and higher interleukin-12p70 levels in recipients. No recipient of sole DNMT3A or TET2-CH developed donor cell leukemia (DCL). In seven of eight cases, DCL evolved from donor CH with rare TP53 or splicing factor mutations or from donors carrying germline DDX41 mutations.

CONCLUSION

Donor CH is closely associated with clinical outcomes in transplant recipients, with differential impact on graft alloimmune function and potential for leukemic transformation related to mutated gene and somatic clonal abundance. Donor DNMT3A-CH is associated with improved recipient survival because of reduced relapse risk and with an augmented network of inflammatory cytokines in recipients. Risk of DCL in allogeneic hematopoietic cell transplantation is driven by somatic myelodysplastic syndrome-associated mutations or germline predisposition in donors.

Pooling for SARS-CoV2 Surveillance: Validation and Strategy for Implementation in K-12 Schools

Repeated testing of a population is critical for limiting the spread of the SARS-CoV-2 virus and for the safe reopening of educational institutions such as kindergarten-grade 12 (K-12) schools and colleges. Many screening efforts utilize the CDC RT-PCR based assay which targets two regions of the novel Coronavirus nucleocapsid gene. The standard approach of testing each person individually, however, poses a financial burden to these institutions and is therefore a barrier to using testing for re-opening. Pooling samples from multiple individuals into a single test is an attractive alternate approach that promises significant cost savings-however the specificity and sensitivity of such approaches needs to be assessed prior to deployment. To this end, we conducted a pilot study to evaluate the feasibility of analyzing samples in pools of eight by the established RT-PCR assay. Participants (1,576) were recruited from amongst the Tufts University community undergoing regular screening. Each volunteer provided two swabs, one analyzed separately and the other in a pool of eight. Because the positivity rate was very low, we spiked approximately half of the pools with laboratory-generated swabs produced from known positive cases outside the Tufts testing program. The results of pooled tests had 100% correspondence with those of their respective individual tests. We conclude that pooling eight samples does not negatively impact the specificity or sensitivity of the RT-PCR assay and suggest that this approach can be utilized by institutions seeking to reduce surveillance costs.

Using viral load and epidemic dynamics to optimize pooled testing in resource-constrained settings

Virological testing is central to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) containment, but many settings face severe limitations on testing. Group testing offers a way to increase throughput by testing pools of combined samples; however, most proposed designs have not yet addressed key concerns over sensitivity loss and implementation feasibility. Here, we combined a mathematical model of epidemic spread and empirically derived viral kinetics for SARS-CoV-2 infections to identify pooling designs that are robust to changes in prevalence and to ratify sensitivity losses against the time course of individual infections. We show that prevalence can be accurately estimated across a broad range, from 0.02 to 20%, using only a few dozen pooled tests and using up to 400 times fewer tests than would be needed for individual identification. We then exhaustively evaluated the ability of different pooling designs to maximize the number of detected infections under various resource constraints, finding that simple pooling designs can identify up to 20 times as many true positives as individual testing with a given budget. Crucially, we confirmed that our theoretical results can be translated into practice using pooled human nasopharyngeal specimens by accurately estimating a 1% prevalence among 2304 samples using only 48 tests and through pooled sample identification in a panel of 960 samples. Our results show that accounting for variation in sampled viral loads provides a nuanced picture of how pooling affects sensitivity to detect infections. Using simple, practical group testing designs can vastly increase surveillance capabilities in resource-limited settings.

Using viral load and epidemic dynamics to optimize pooled testing in resource constrained settings

Extensive virological testing is central to SARS-CoV-2 containment, but many settings face severe limitations on testing. Group testing offers a way to increase throughput by testing pools of combined samples; however, most proposed designs have not yet addressed key concerns over sensitivity loss and implementation feasibility. Here, we combine a mathematical model of epidemic spread and empirically derived viral kinetics for SARS-CoV-2 infections to identify pooling designs that are robust to changes in prevalence, and to ratify losses in sensitivity against the time course of individual infections. Using this framework, we show that prevalence can be accurately estimated across four orders of magnitude using only a few dozen pooled tests without the need for individual identification. We then exhaustively evaluate the ability of different pooling designs to maximize the number of detected infections under various resource constraints, finding that simple pooling designs can identify up to 20 times as many positives compared to individual testing with a given budget. We illustrate how pooling affects sensitivity and overall detection capacity during an epidemic and on each day post infection, finding that sensitivity loss is mainly attributed to individuals sampled at the end of infection when detection for public health containment has minimal benefit. Crucially, we confirm that our theoretical results can be accurately translated into practice using pooled human nasopharyngeal specimens. Our results show that accounting for variation in sampled viral loads provides a nuanced picture of how pooling affects sensitivity to detect epidemiologically relevant infections. Using simple, practical group testing designs can vastly increase surveillance capabilities in resource-limited settings.

Sensitive Detection of Minimal Residual Disease in Patients Treated for Early-Stage Breast Cancer

PURPOSE

Existing cell-free DNA (cfDNA) methods lack the sensitivity needed for detecting minimal residual disease (MRD) following therapy. We developed a test for tracking hundreds of patient-specific mutations to detect MRD with a 1,000-fold lower error rate than conventional sequencing.

EXPERIMENTAL DESIGN

We compared the sensitivity of our approach to digital droplet PCR (ddPCR) in a dilution series, then retrospectively identified two cohorts of patients who had undergone prospective plasma sampling and clinical data collection: 16 patients with ER+/HER2- metastatic breast cancer (MBC) sampled within 6 months following metastatic diagnosis and 142 patients with stage 0 to III breast cancer who received curative-intent treatment with most sampled at surgery and 1 year postoperative. We performed whole-exome sequencing of tumors and designed individualized MRD tests, which we applied to serial cfDNA samples.

RESULTS

Our approach was 100-fold more sensitive than ddPCR when tracking 488 mutations, but most patients had fewer identifiable tumor mutations to track in cfDNA (median = 57; range = 2-346). Clinical sensitivity was 81% (n = 13/16) in newly diagnosed MBC, 23% (n = 7/30) at postoperative and 19% (n = 6/32) at 1 year in early-stage disease, and highest in patients with the most tumor mutations available to track. MRD detection at 1 year was strongly associated with distant recurrence [HR = 20.8; 95% confidence interval, 7.3-58.9]. Median lead time from first positive sample to recurrence was 18.9 months (range = 3.4-39.2 months).

CONCLUSIONS

Tracking large numbers of individualized tumor mutations in cfDNA can improve MRD detection, but its sensitivity is driven by the number of tumor mutations available to track.

Abstract 455: Innovations in large scale liquid biopsy analysis and the Broad/IBM Cancer Resistance Project

Broad Genomics offers a comprehensive liquid biopsy sequencing platform designed to provide the optimal flexibility for conducting research studies in a broad range of applications including: biomarker discovery, treatment resistance monitoring, and clinical grade ctDNA profiling. By utilizing low cost, low coverage whole genome sequencing in conjunction with dual unique molecular indexed (UMI) libraries we can offer a range of analysis that allow researchers to select the most appropriate samples for whole exome profiling or for deeper coverage, higher sensitivity targeted gene panels. To date we have generated over 3000 liquid biopsy whole genome copy number profiles and purity estimates and are supporting driver projects including the Broad/IBM Cancer Resistance Project and Count Me In. The study design for the Broad/IBM effort takes advantage of the discovery potential of tissue-based sequencing combined with serial liquid biopsy analysis to elucidate resistance events by tracking clonal and subclonal populations in patient samples over time. Sourcing samples for this and other similar efforts is a major undertaking and a combination of methods for maximally broad and deep genomic profiling are required to assay patients throughout the course of care, as tumor fraction in blood fluctuates. Responding to this need, and other applications requiring increased sensitivity we have developed a high throughput, automated workflow to efficiently assay cfDNA samples with lower tumor content. Benchmarking data using healthy donor pooled cfDNA samples indicates our assay is capable of detecting &gt; 90% of variants present at ~1% minor allele fraction with less than 1 false positive variant called per megabase. This established laboratory and analytic process forms the basis of our 2Mb, 400 gene CLIA targeted assay currently undergoing validation. Through this suite of products we hope to enable an expansion of cfDNA sequencing efforts in support of clinical and research applications. Early results from emerging studies utilizing this platform to be presented.

Citation Format: Carrie Cibulskis, Brendan Blumenstiel, Matthew DeFelice, Mark Fleharty, Justin Abreu, Viktor Adalsteinsson, Laxmi Parida, Susanna Hamilton, Gad Getz, Niall Lennon. Innovations in large scale liquid biopsy analysis and the Broad/IBM Cancer Resistance Project [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2019; 2019 Mar 29-Apr 3; Atlanta, GA. Philadelphia (PA): AACR; Cancer Res 2019;79(13 Suppl):Abstract nr 455.

Noninvasive Immunohistochemical Diagnosis and Novel MUC1 Mutations Causing Autosomal Dominant Tubulointerstitial Kidney Disease

BACKGROUND

Autosomal dominant tubulointerstitial kidney disease caused by mucin-1 gene (MUC1) mutations (ADTKD-MUC1) is characterized by progressive kidney failure. Genetic evaluation for ADTKD-MUC1 specifically tests for a cytosine duplication that creates a unique frameshift protein (MUC1fs). Our goal was to develop immunohistochemical methods to detect the MUC1fs created by the cytosine duplication and, possibly, by other similar frameshift mutations and to identify novel MUC1 mutations in individuals with positive immunohistochemical staining for the MUC1fs protein.

METHODS

We performed MUC1fs immunostaining on urinary cell smears and various tissues from ADTKD-MUC1-positive and -negative controls as well as in individuals from 37 ADTKD families that were negative for mutations in known ADTKD genes. We used novel analytic methods to identify MUC1 frameshift mutations.

RESULTS

After technique refinement, the sensitivity and specificity for MUC1fs immunostaining of urinary cell smears were 94.2% and 88.6%, respectively. Further genetic testing on 17 families with positive MUC1fs immunostaining revealed six families with five novel MUC1 frameshift mutations that all predict production of the identical MUC1fs protein.

CONCLUSIONS

We developed a noninvasive immunohistochemical method to detect MUC1fs that, after further validation, may be useful in the future for diagnostic testing. Production of the MUC1fs protein may be central to the pathogenesis of ADTKD-MUC1.

Abstract 3001: Broad/IBM Project: Discovery of treatment resistance mechanisms through use of liquid biopsy genomics services

The Broad/IBM Cancer Resistance Project has partnered with Broad Genomics to pilot the use of cutting edge sequencing technology for the analysis of cell free DNA in blood biopsies. Working closely with the Broad's Cancer Program, Broad Genomics has developed a suite of liquid biopsy sequencing products designed to provide optimal flexibility in conducting research studies with a broad range of applications including; biomarker discovery, treatment resistance monitoring, and detection of minimal residual disease (MRD) post-surgery. Cell-free DNA is extracted from the blood, and a dual unique-molecular-indexed library is created. From this library, low coverage whole genome (ultra-low-pass 0.1x coverage) data is generated to survey sample quality and evaluate the tumor fraction in the liquid specimen. Utilizing the same library, additional assays can be selected for processing based on the research aim (Targeted Panel Assays, MRD Detection or Whole Exomes). Since our approach utilizes the same genomic material for whole genome and targeted sequencing assays, it is possible to maximize the information learned from each valuable and limited liquid biopsy specimen. Our study design takes advantage of the discovery potential of combined tissue-based sequencing and serial liquid biopsy analysis to elucidate mechanisms of cancer resistance by tracking the evolution of clonal and subclonal populations in patients samples over time. This collaboration will utilize the ultra-low-pass sequencing and whole exome sequencing together with custom analysis pipelines to correlate the genomic events with patient clinical data. We aim to process 3,000 samples from 1,000 patients over the next 3 years. To date we have processed close to 500 samples through the ultra-low-pass pipeline and 100 samples through the whole exome sequencing pipeline (results to be provided).The ability to successfully investigate treatment resistant cancers from non-invasive liquid biopsies presents new opportunities for identifying markers, understanding dynamics and monitoring tumor dissemination and clonal evolution.

Citation Format: Gad Getz, Carrie Cibulskis, Ignaty Leshchiner, Megan Hanna, Dimitri Livitz, Kara Slowik, Chaya Levovitz, Filippo Utro, Kahn Rhrissorrakrai, Denisse Rotem, Gregory Gydush, Sarah C. Reed, Justin Rhoades, Gavin Ha, Samuel S. Freeman, Christopher Lo, Mark Fleharty, Justin Abreu, Katie Larkin, Michelle Cipicchio, Brendan Blumenstiel, Matt DeFelice, Jonna Grimsby, Susanna Hamilton, Niall Lennon, Viktor A. Adalsteinsson, Laxmi Parida. Broad/IBM Project: Discovery of treatment resistance mechanisms through use of liquid biopsy genomics services [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2018; 2018 Apr 14-18; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2018;78(13 Suppl):Abstract nr 3001.

Abstract 993: Whole exome sequencing of CTCs as a window into metastatic cancer

Comprehensive analysis of cancer genomes in clinical settings holds the promise to inform prognoses and guide the deployment of precise cancer treatments. A major barrier, however, is the inaccessibility of adequate metastatic tissue for accurate genomic analysis. The recognition that circulating tumor cells (CTCs) are present in many advanced cancer patients suggests an exciting opportunity to overcome this challenge. For instance, if CTCs could be comprehensively sequenced, it would be possible to obtain an orthogonal sample of the tumor burden_including subsets of transiting cells bound for metastatic colonization_potentially yielding new insights to complement the static sampling of resected or biopsied lesions.

We report an integrated process to isolate, qualify, and sequence whole exomes of CTCs with high fidelity, using a census-based sequencing strategy. We isolated CTCs by magnetic bead purification (Illumina MagSweeper) from the blood of patients with prostate cancer, and integrated a nanowell platform to automatically image and recover candidate single CTCs. We then developed a strategy to qualify individual CTC-derived libraries for DNA sequencing after whole genome amplification, and established an analytical framework for accurate calling of mutations using census-based sequencing and MuTect. Whole exome sequencing was performed on 20 single CTCs, obtained from a patient with advanced prostate cancer. We validated our sequencing process by comparing CTC-derived mutations to mutations found in a lymph node metastasis and nine separate cores of the primary tumor. 51 of 73 CTC mutations (70%) were observed in the metastasis or the primary tumor. Moreover, we identified 9 early trunk mutations and 56 metastatic trunk mutations in the non-CTC tumor samples and found 100% and 73% of these, respectively, in CTC exomes. Our work demonstrates the feasibility of CTC sequencing and the ability to confidently call somatic mutations. CTCs may therefore represent a non-invasive window into the mutational landscape of metastatic cancer, and may have utility for genomics in clinical practice.

Citation Format: Viktor A. Adalsteinsson, Jens G. Lohr, Kristian Cibulskis, Atish D. Choudhury, Mara Rosenberg, Peter Cruz-Gordillo, Joshua Francis, ChengZhong Zhang, Alexander K. Shalek, Rahul Satija, John T. Trombetta, Diana Lu, Naren Tallapragada, Narmin T. Tahirova, Sora Kim, Brendan Blumenstiel, Carrie Sougnez, Daniel Auclair, Eliezer M. Van Allen, Mari Nakabayashi, Rosina T. Lis, Gwo-Shu M. Lee, Tiantian Li, Matthew S. Chabot, Mary-Ellen Taplin, Thomas E. Clancy, Massimo Loda, Aviv Regev, Matthew Meyerson, William C. Hahn, Philip W. Kantoff, Todd R. Golub, Gad Getz, Jesse S. Boehm, J Christopher Love. Whole exome sequencing of CTCs as a window into metastatic cancer. [abstract]. In: Proceedings of the 105th Annual Meeting of the American Association for Cancer Research; 2014 Apr 5-9; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2014;74(19 Suppl):Abstract nr 993. doi:10.1158/1538-7445.AM2014-993

EGFR variant heterogeneity in glioblastoma resolved through single-nucleus sequencing

Glioblastomas (GBM) with EGFR amplification represent approximately 50% of newly diagnosed cases, and recent studies have revealed frequent coexistence of multiple EGFR aberrations within the same tumor, which has implications for mutation cooperation and treatment resistance. However, bulk tumor sequencing studies cannot resolve the patterns of how the multiple EGFR aberrations coexist with other mutations within single tumor cells. Here, we applied a population-based single-cell whole-genome sequencing methodology to characterize genomic heterogeneity in EGFR-amplified glioblastomas. Our analysis effectively identified clonal events, including a novel translocation of a super enhancer to the TERT promoter, as well as subclonal LOH and multiple EGFR mutational variants within tumors. Correlating the EGFR mutations onto the cellular hierarchy revealed that EGFR truncation variants (EGFRvII and EGFR carboxyl-terminal deletions) identified in the bulk tumor segregate into nonoverlapping subclonal populations. In vitro and in vivo functional studies show that EGFRvII is oncogenic and sensitive to EGFR inhibitors currently in clinical trials. Thus, the association between diverse activating mutations in EGFR and other subclonal mutations within a single tumor supports an intrinsic mechanism for proliferative and clonal diversification with broad implications in resistance to treatment.

SIGNIFICANCE

We developed a novel single-cell sequencing methodology capable of identifying unique, nonoverlapping subclonal alterations from archived frozen clinical specimens. Using GBM as an example, we validated our method to successfully define tumor cell subpopulations containing distinct genetic and treatment resistance profiles and potentially mutually cooperative combinations of alterations in EGFR and other genes.

Whole-exome sequencing of circulating tumor cells provides a window into metastatic prostate cancer

Comprehensive analyses of cancer genomes promise to inform prognoses and precise cancer treatments. A major barrier, however, is inaccessibility of metastatic tissue. A potential solution is to characterize circulating tumor cells (CTCs), but this requires overcoming the challenges of isolating rare cells and sequencing low-input material. Here we report an integrated process to isolate, qualify and sequence whole exomes of CTCs with high fidelity using a census-based sequencing strategy. Power calculations suggest that mapping of >99.995% of the standard exome is possible in CTCs. We validated our process in two patients with prostate cancer, including one for whom we sequenced CTCs, a lymph node metastasis and nine cores of the primary tumor. Fifty-one of 73 CTC mutations (70%) were present in matched tissue. Moreover, we identified 10 early trunk and 56 metastatic trunk mutations in the non-CTC tumor samples and found 90% and 73% of these mutations, respectively, in CTC exomes. This study establishes a foundation for CTC genomics in the clinic.

DGAT1 mutation is linked to a congenital diarrheal disorder

Congenital diarrheal disorders (CDDs) are a collection of rare, heterogeneous enteropathies with early onset and often severe outcomes. Here, we report a family of Ashkenazi Jewish descent, with 2 out of 3 children affected by CDD. Both affected children presented 3 days after birth with severe, intractable diarrhea. One child died from complications at age 17 months. The second child showed marked improvement, with resolution of most symptoms at 10 to 12 months of age. Using exome sequencing, we identified a rare splice site mutation in the DGAT1 gene and found that both affected children were homozygous carriers. Molecular analysis of the mutant allele indicated a total loss of function, with no detectable DGAT1 protein or activity produced. The precise cause of diarrhea is unknown, but we speculate that it relates to abnormal fat absorption and buildup of DGAT substrates in the intestinal mucosa. Our results identify DGAT1 loss-of-function mutations as a rare cause of CDDs. These findings prompt concern for DGAT1 inhibition in humans, which is being assessed for treating metabolic and other diseases.

High-throughput detection of actionable genomic alterations in clinical tumor samples by targeted, massively parallel sequencing

Knowledge of "actionable" somatic genomic alterations present in each tumor (e.g., point mutations, small insertions/deletions, and copy-number alterations that direct therapeutic options) should facilitate individualized approaches to cancer treatment. However, clinical implementation of systematic genomic profiling has rarely been achieved beyond limited numbers of oncogene point mutations. To address this challenge, we utilized a targeted, massively parallel sequencing approach to detect tumor genomic alterations in formalin-fixed, paraffin-embedded (FFPE) tumor samples. Nearly 400-fold mean sequence coverage was achieved, and single-nucleotide sequence variants, small insertions/deletions, and chromosomal copynumber alterations were detected simultaneously with high accuracy compared with other methods in clinical use. Putatively actionable genomic alterations, including those that predict sensitivity or resistance to established and experimental therapies, were detected in each tumor sample tested. Thus, targeted deep sequencing of clinical tumor material may enable mutation-driven clinical trials and, ultimately, "personalized" cancer treatment.

SIGNIFICANCE

Despite the rapid proliferation of targeted therapeutic agents, systematic methods to profile clinically relevant tumor genomic alterations remain underdeveloped. We describe a sequencingbased approach to identifying genomic alterations in FFPE tumor samples. These studies affirm the feasibility and clinical utility of targeted sequencing in the oncology arena and provide a foundation for genomics-based stratification of cancer patients.

A scalable, fully automated process for construction of sequence-ready human exome targeted capture libraries

Genome targeting methods enable cost-effective capture of specific subsets of the genome for sequencing. We present here an automated, highly scalable method for carrying out the Solution Hybrid Selection capture approach that provides a dramatic increase in scale and throughput of sequence-ready libraries produced. Significant process improvements and a series of in-process quality control checkpoints are also added. These process improvements can also be used in a manual version of the protocol.

Targeted exon sequencing by in-solution hybrid selection

This unit describes a protocol for the targeted enrichment of exons from randomly sheared genomic DNA libraries using an in-solution hybrid selection approach for sequencing on an Illumina Genome Analyzer II. The steps for designing and ordering a hybrid selection oligo pool are reviewed, as are critical steps for performing the preparation and hybrid selection of an Illumina paired-end library. Critical parameters, performance metrics, and analysis workflow are discussed.

Abstract LB-122: High-throughput tumor genomic profiling by massively parallel sequencing

The use of tumor genetic and molecular information to accurately predict a patient's response to therapy is critical to personalized cancer medicine. Knowledge of somatic genetic alterations in tumors - including mutations, copy number alterations, and pharmacogenomic polymorphisms - should ultimately facilitate individualized approaches to cancer treatment. However, the development and real-world implementation of comprehensive genomic profiling has not yet been achieved. Here, we describe the development of a high-throughput, massively parallel sequencing platform to detect tumor genomic alterations that may provide an efficient and cost-effective means to address this challenge.

Our approach combines several recent innovations - solution phase hybrid selection, DNA barcoding and pooling, and massively parallel sequencing - to achieve a high-throughput genomic profiling platform. We designed and synthesized ∼7000 biotinylated RNA baits corresponding to the coding sequence of the top 150 “druggable” or potentially “actionable” genes known to undergo somatic genomic alterations in cancer. We obtained genomic DNA from cell lines with known genetic alterations and used this DNA to generate barcoded sequencing libraries. Following quantification of libraries, equimolar pools were generated consisting of up to 12 barcoded tumor DNAs and normal diploid control DNAs. These DNA pools were subjected to solution-phase hybrid capture with the biotinylated RNA baits followed by massively parallel sequencing. The sequencing data were deconvoluted to match all high-quality reads with the corresponding tumor samples and call base mutations and copy number alterations. In all samples tested, sequence reads were highly specific to the targeted exonic regions. In addition to detecting mutations, exon capture detected high-level amplifications and deletions, two types of “actionable” genomic alterations that are poorly detectable by mass spectrometric approaches to mutation profiling. Comparison with copy number data previously obtained using high-density SNP array data demonstrated a robust correlation. As a proof-of-principle, we performed the entire profiling approach on clinical tumor specimens from patients with refractory, aggressive cancers to assess the use of genomic profiling in a real-world situation where knowledge of “driver” genetic alterations might prove valuable.

Altogether, our data endorse this sequencing-based approach as a promising method to detect critical “actionable” genetic alterations in a large panel of cancer genes. The platform is scalable, refractory to contaminating stromal DNA or hyperploidy, and completed at a fraction of the cost of comparable sequencing approaches. By providing a rapid, sensitive, cost-effective means to sequence &gt;100 cancer genes deeply and simultaneously, this approach may ultimately empower the rational selection of specific drugs targeting the genetic alterations in each patient's tumor - clearly an unmet need in oncology.

Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 101st Annual Meeting of the American Association for Cancer Research; 2010 Apr 17-21; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2010;70(8 Suppl):Abstract nr LB-122.

Collaborative genome-wide association analysis supports a role for ANK3 and CACNA1C in bipolar disorder

To identify susceptibility loci for bipolar disorder, we tested 1.8 million variants in 4,387 cases and 6,209 controls and identified a region of strong association (rs10994336, P = 9.1 x 10(-9)) in ANK3 (ankyrin G). We also found further support for the previously reported CACNA1C (alpha 1C subunit of the L-type voltage-gated calcium channel; combined P = 7.0 x 10(-8), rs1006737). Our results suggest that ion channelopathies may be involved in the pathogenesis of bipolar disorder.

Whole-genome association study of bipolar disorder

We performed a genome-wide association scan in 1461 patients with bipolar (BP) 1 disorder, 2008 controls drawn from the Systematic Treatment Enhancement Program for Bipolar Disorder and the University College London sample collections with successful genotyping for 372,193 single nucleotide polymorphisms (SNPs). Our strongest single SNP results are found in myosin5B (MYO5B; P=1.66 x 10(-7)) and tetraspanin-8 (TSPAN8; P=6.11 x 10(-7)). Haplotype analysis further supported single SNP results highlighting MYO5B, TSPAN8 and the epidermal growth factor receptor (MYO5B; P=2.04 x 10(-8), TSPAN8; P=7.57 x 10(-7) and EGFR; P=8.36 x 10(-8)). For replication, we genotyped 304 SNPs in family-based NIMH samples (n=409 trios) and University of Edinburgh case-control samples (n=365 cases, 351 controls) that did not provide independent replication after correction for multiple testing. A comparison of our strongest associations with the genome-wide scan of 1868 patients with BP disorder and 2938 controls who completed the scan as part of the Wellcome Trust Case-Control Consortium indicates concordant signals for SNPs within the voltage-dependent calcium channel, L-type, alpha 1C subunit (CACNA1C) gene. Given the heritability of BP disorder, the lack of agreement between studies emphasizes that susceptibility alleles are likely to be modest in effect size and require even larger samples for detection.

A second generation human haplotype map of over 3.1 million SNPs

We describe the Phase II HapMap, which characterizes over 3.1 million human single nucleotide polymorphisms (SNPs) genotyped in 270 individuals from four geographically diverse populations and includes 25-35% of common SNP variation in the populations surveyed. The map is estimated to capture untyped common variation with an average maximum r2 of between 0.9 and 0.96 depending on population. We demonstrate that the current generation of commercial genome-wide genotyping products captures common Phase II SNPs with an average maximum r2 of up to 0.8 in African and up to 0.95 in non-African populations, and that potential gains in power in association studies can be obtained through imputation. These data also reveal novel aspects of the structure of linkage disequilibrium. We show that 10-30% of pairs of individuals within a population share at least one region of extended genetic identity arising from recent ancestry and that up to 1% of all common variants are untaggable, primarily because they lie within recombination hotspots. We show that recombination rates vary systematically around genes and between genes of different function. Finally, we demonstrate increased differentiation at non-synonymous, compared to synonymous, SNPs, resulting from systematic differences in the strength or efficacy of natural selection between populations.

Two independent alleles at 6q23 associated with risk of rheumatoid arthritis

To identify susceptibility alleles associated with rheumatoid arthritis, we genotyped 397 individuals with rheumatoid arthritis for 116,204 SNPs and carried out an association analysis in comparison to publicly available genotype data for 1,211 related individuals from the Framingham Heart Study. After evaluating and adjusting for technical and population biases, we identified a SNP at 6q23 (rs10499194, approximately 150 kb from TNFAIP3 and OLIG3) that was reproducibly associated with rheumatoid arthritis both in the genome-wide association (GWA) scan and in 5,541 additional case-control samples (P = 10(-3), GWA scan; P < 10(-6), replication; P = 10(-9), combined). In a concurrent study, the Wellcome Trust Case Control Consortium (WTCCC) has reported strong association of rheumatoid arthritis susceptibility to a different SNP located 3.8 kb from rs10499194 (rs6920220; P = 5 x 10(-6) in WTCCC). We show that these two SNP associations are statistically independent, are each reproducible in the comparison of our data and WTCCC data, and define risk and protective haplotypes for rheumatoid arthritis at 6q23.

Genome-wide association analysis identifies loci for type 2 diabetes and triglyceride levels

New strategies for prevention and treatment of type 2 diabetes (T2D) require improved insight into disease etiology. We analyzed 386,731 common single-nucleotide polymorphisms (SNPs) in 1464 patients with T2D and 1467 matched controls, each characterized for measures of glucose metabolism, lipids, obesity, and blood pressure. With collaborators (FUSION and WTCCC/UKT2D), we identified and confirmed three loci associated with T2D-in a noncoding region near CDKN2A and CDKN2B, in an intron of IGF2BP2, and an intron of CDKAL1-and replicated associations near HHEX and in SLC30A8 found by a recent whole-genome association study. We identified and confirmed association of a SNP in an intron of glucokinase regulatory protein (GCKR) with serum triglycerides. The discovery of associated variants in unsuspected genes and outside coding regions illustrates the ability of genome-wide association studies to provide potentially important clues to the pathogenesis of common diseases.

The structure of haplotype blocks in the human genome

Haplotype-based methods offer a powerful approach to disease gene mapping, based on the association between causal mutations and the ancestral haplotypes on which they arose. As part of The SNP Consortium Allele Frequency Projects, we characterized haplotype patterns across 51 autosomal regions (spanning 13 megabases of the human genome) in samples from Africa, Europe, and Asia. We show that the human genome can be parsed objectively into haplotype blocks: sizable regions over which there is little evidence for historical recombination and within which only a few common haplotypes are observed. The boundaries of blocks and specific haplotypes they contain are highly correlated across populations. We demonstrate that such haplotype frameworks provide substantial statistical power in association studies of common genetic variation across each region. Our results provide a foundation for the construction of a haplotype map of the human genome, facilitating comprehensive genetic association studies of human disease.

A map of human genome sequence variation containing 1.42 million single nucleotide polymorphisms

We describe a map of 1.42 million single nucleotide polymorphisms (SNPs) distributed throughout the human genome, providing an average density on available sequence of one SNP every 1.9 kilobases. These SNPs were primarily discovered by two projects: The SNP Consortium and the analysis of clone overlaps by the International Human Genome Sequencing Consortium. The map integrates all publicly available SNPs with described genes and other genomic features. We estimate that 60,000 SNPs fall within exon (coding and untranslated regions), and 85% of exons are within 5 kb of the nearest SNP. Nucleotide diversity varies greatly across the genome, in a manner broadly consistent with a standard population genetic model of human history. This high-density SNP map provides a public resource for defining haplotype variation across the genome, and should help to identify biomedically important genes for diagnosis and therapy.