A Systematic Method for Detecting Abnormal mRNA Splicing and Assessing Its Clinical Impact in Individuals Undergoing Genetic Testing for Hereditary Cancer Syndromes.

Nearly 14% of disease-causing germline variants result from the disruption of mRNA splicing. Most (67%) DNA variants predicted in silico to disrupt splicing are classified as variants of uncertain significance. An analytic workflow-splice effect event resolver (SPEER)-was developed and validated to use mRNA sequencing to reveal significant deviations in splicing, pinpoint the DNA variants potentially involved, and measure the deleterious effects of the altered splicing on mRNA transcripts, providing evidence for assessing the pathogenicity of the variant. SPEER was used to analyze leukocyte RNA encoding 63 hereditary cancer syndrome-related genes in 20,317 patients. Among 3563 patients (17.5%) with at least one DNA variant predicted to affect splicing, 971 (4.8%) had altered splicing with a deleterious effect on the transcript, and 40 had altered splicing due to a DNA variant located outside of the reportable range of the test. Integrating SPEER results into the interpretation of variants allowed variants of uncertain significance to be reclassified as pathogenic or likely pathogenic in 0.4%, and as benign or likely benign in 5.9%, of the 20,317 patients. SPEER-based evidence was associated with a significantly greater effect on classifications of pathogenic or likely pathogenic and benign or likely benign in nonwhite versus non-Hispanic white patients, illustrating that evidence derived from mRNA splicing analysis may help to reduce ethnic/ancestral disparities in genetic testing.

Antigen presentation profiling reveals recognition of lymphoma immunoglobulin neoantigens.

Cancer somatic mutations can generate neoantigens that distinguish malignant from normal cells. However, the personalized identification and validation of neoantigens remains a major challenge. Here we discover neoantigens in human mantle-cell lymphomas by using an integrated genomic and proteomic strategy that interrogates tumour antigen peptides presented by major histocompatibility complex (MHC) class I and class II molecules. We applied this approach to systematically characterize MHC ligands from 17 patients. Remarkably, all discovered neoantigenic peptides were exclusively derived from the lymphoma immunoglobulin heavy- or light-chain variable regions. Although we identified MHC presentation of private polymorphic germline alleles, no mutated peptides were recovered from non-immunoglobulin somatically mutated genes. Somatic mutations within the immunoglobulin variable region were almost exclusively presented by MHC class II. We isolated circulating CD4+ T cells specific for immunoglobulin-derived neoantigens and found these cells could mediate killing of autologous lymphoma cells. These results demonstrate that an integrative approach combining MHC isolation, peptide identification, and exome sequencing is an effective platform to uncover tumour neoantigens. Application of this strategy to human lymphoma implicates immunoglobulin neoantigens as targets for lymphoma immunotherapy.

The prognostic value of clonal heterogeneity and quantitative assessment of plasma circulating clonal IG-VDJ sequences at diagnosis in patients with follicular lymphoma.

Recent advances in next-generation sequencing (NGS) have enabled the quantitation of circulating tumour DNA (ctDNA) encoding the clonal rearranged V(D)J immunoglobulin locus. We aimed to evaluate the clonal heterogeneity of follicular lymphoma (FL) in the tumour and the plasma at diagnosis and to assess the prognostic value of the ctDNA level. Plasma samples at diagnosis were available for 34 patients registered in the PRIMA trial (NCT00140582). One tumour clonotype or more could be detected for 29 (85%) and 25 (74%) patients, respectively, in the tumour or plasma samples. In 18 patients, several subclones were detected in the tumour (2 to 71 subclones/cases) and/or in the plasma (2 to 20 subclones/cases). In more than half of the cases, the distribution of subclones differed between the tumour and plasma samples, reflecting high clonal heterogeneity and diversity in lymphoma subclone dissemination. In multivariate analysis, a high level of ctDNA was the only independent factor associated with patients' progression-free survival (HR 4, IC 95 (1.1-37), p=.039). In conclusion, an NGS-based immunosequencing method reveals the marked clonal heterogeneity of follicular lymphoma in patients with FL, and quantification of ctDNA at diagnosis represents a potential powerful prognostic biomarker that needs to be investigated in larger cohorts.

Deep-sequencing approach for minimal residual disease detection in acute lymphoblastic leukemia.

The persistence of minimal residual disease (MRD) during therapy is the strongest adverse prognostic factor in acute lymphoblastic leukemia (ALL). We developed a high-throughput sequencing method that universally amplifies antigen-receptor gene segments and identifies all clonal gene rearrangements (ie, leukemia-specific sequences) at diagnosis, allowing monitoring of disease progression and clonal evolution during therapy. In the present study, the assay specifically detected 1 leukemic cell among greater than 1 million leukocytes in spike-in experiments. We compared this method with the gold-standard MRD assays multiparameter flow cytometry and allele-specific oligonucleotide polymerase chain reaction (ASO-PCR) using diagnostic and follow-up samples from 106 patients with ALL. Sequencing detected MRD in all 28 samples shown to be positive by flow cytometry and in 35 of the 36 shown to be positive by ASO-PCR and revealed MRD in 10 and 3 additional samples that were negative by flow cytometry and ASO-PCR, respectively. We conclude that this new method allows monitoring of treatment response in ALL and other lymphoid malignancies with great sensitivity and precision. The www.clinicaltrials.gov identifier number for the Total XV study is NCT00137111.

Massive evolution of the immunoglobulin heavy chain locus in children with B precursor acute lymphoblastic leukemia.

The ability to distinguish clonal B-cell populations based on the sequence of their rearranged immunoglobulin heavy chain (IgH) locus is an important tool for diagnosing B-cell neoplasms and monitoring treatment response. Leukemic precursor B cells may continue to undergo recombination of the IgH gene after malignant transformation; however, the magnitude of evolution at the IgH locus is currently unknown. We used next-generation sequencing to characterize the repertoire of IgH sequences in diagnostic samples of 51 children with B precursor acute lymphoblastic leukemia (B-ALL). We identified clonal IgH rearrangements in 43 of 51 (84%) cases and found that the number of evolved IgH sequences per patient ranged dramatically from 0 to 4024. We demonstrate that the evolved IgH sequences are not the result of amplification artifacts and are unique to leukemic precursor B cells. In addition, the evolution often follows an allelic exclusion pattern, where only 1 of 2 rearranged IgH loci exhibit ongoing recombination. Thus, precursor B-cell leukemias maintain evolution at the IgH locus at levels that were previously underappreciated. This finding sheds light on the mechanisms associated with leukemic clonal evolution and may fundamentally change approaches for monitoring minimal residual disease burden.

Diverse somatic mutation patterns and pathway alterations in human cancers.

The systematic characterization of somatic mutations in cancer genomes is essential for understanding the disease and for developing targeted therapeutics. Here we report the identification of 2,576 somatic mutations across approximately 1,800 megabases of DNA representing 1,507 coding genes from 441 tumours comprising breast, lung, ovarian and prostate cancer types and subtypes. We found that mutation rates and the sets of mutated genes varied substantially across tumour types and subtypes. Statistical analysis identified 77 significantly mutated genes including protein kinases, G-protein-coupled receptors such as GRM8, BAI3, AGTRL1 (also called APLNR) and LPHN3, and other druggable targets. Integrated analysis of somatic mutations and copy number alterations identified another 35 significantly altered genes including GNAS, indicating an expanded role for galpha subunits in multiple cancer types. Furthermore, our experimental analyses demonstrate the functional roles of mutant GNAO1 (a Galpha subunit) and mutant MAP2K4 (a member of the JNK signalling pathway) in oncogenesis. Our study provides an overview of the mutational spectra across major human cancers and identifies several potential therapeutic targets.

High-throughput method for analyzing methylation of CpGs in targeted genomic regions.

A unique microarray-based method for determining the extent of DNA methylation has been developed. It relies on a selective enrichment of the regions to be assayed by target amplification by capture and ligation (mTACL). The assay is quantitatively accurate, relatively precise, and lends itself to high-throughput determination using nanogram amounts of DNA. The measurements using mTACLs are highly reproducible and in excellent agreement with those obtained by sequencing (r = 0.94). In the present work, the methylation status of >145,000 CpGs from 5,472 promoters in 221 samples was measured. The methylation levels of nearby CpGs are correlated, but the correlation falls off dramatically over several hundred base pairs. In some instances, nearby CpGs have very different levels of methylation. Comparison of normal and tumor samples indicates that in tumors, the promoter regions of genes involved in differentiation and signaling are preferentially hypermethylated, whereas those of housekeeping genes remain hypomethylated. mTACL is a platform for profiling the state of methylation of a large number of CpG in many samples in a cost-effective fashion, and is capable of scaling to much larger numbers of CpGs than those collected here.

Prediction of epigenetically regulated genes in breast cancer cell lines.

BACKGROUND: Methylation of CpG islands within the DNA promoter regions is one mechanism that leads to aberrant gene expression in cancer. In particular, the abnormal methylation of CpG islands may silence associated genes. Therefore, using high-throughput microarrays to measure CpG island methylation will lead to better understanding of tumor pathobiology and progression, while revealing potentially new biomarkers. We have examined a recently developed high-throughput technology for measuring genome-wide methylation patterns called mTACL. Here, we propose a computational pipeline for integrating gene expression and CpG island methylation profiles to identify epigenetically regulated genes for a panel of 45 breast cancer cell lines, which is widely used in the Integrative Cancer Biology Program (ICBP). The pipeline (i) reduces the dimensionality of the methylation data, (ii) associates the reduced methylation data with gene expression data, and (iii) ranks methylation-expression associations according to their epigenetic regulation. Dimensionality reduction is performed in two steps: (i) methylation sites are grouped across the genome to identify regions of interest, and (ii) methylation profiles are clustered within each region. Associations between the clustered methylation and the gene expression data sets generate candidate matches within a fixed neighborhood around each gene. Finally, the methylation-expression associations are ranked through a logistic regression, and their significance is quantified through permutation analysis. RESULTS: Our two-step dimensionality reduction compressed 90% of the original data, reducing 137,688 methylation sites to 14,505 clusters. Methylation-expression associations produced 18,312 correspondences, which were used to further analyze epigenetic regulation. Logistic regression was used to identify 58 genes from these correspondences that showed a statistically significant negative correlation between methylation profiles and gene expression in the panel of breast cancer cell lines. Subnetwork enrichment of these genes has identified 35 common regulators with 6 or more predicted markers. In addition to identifying epigenetically regulated genes, we show evidence of differentially expressed methylation patterns between the basal and luminal subtypes. CONCLUSIONS: Our results indicate that the proposed computational protocol is a viable platform for identifying epigenetically regulated genes. Our protocol has generated a list of predictors including COL1A2, TOP2A, TFF1, and VAV3, genes whose key roles in epigenetic regulation is documented in the literature. Subnetwork enrichment of these predicted markers further suggests that epigenetic regulation of individual genes occurs in a coordinated fashion and through common regulators.

High-throughput, high-accuracy array-based resequencing.

Although genomewide association studies have successfully identified associations of many common single-nucleotide polymorphisms (SNPs) with common diseases, the SNPs implicated so far account for only a small proportion of the genetic variability of tested diseases. It has been suggested that common diseases may often be caused by rare alleles missed by genomewide association studies. To identify these rare alleles we need high-throughput, high-accuracy resequencing technologies. Although array-based genotyping has allowed genomewide association studies of common SNPs in tens of thousands of samples, array-based resequencing has been limited for 2 main reasons: the lack of a fully multiplexed pipeline for high-throughput sample processing, and failure to achieve sufficient performance. We have recently solved both of these problems and created a fully multiplexed high-throughput pipeline that results in high-quality data. The pipeline consists of target amplification from genomic DNA, followed by allele enrichment to generate pools of purified variant (or nonvariant) DNA and ends with interrogation of purified DNA on resequencing arrays. We have used this pipeline to resequence approximately 5 Mb of DNA (on 3 arrays) corresponding to the exons of 1,500 genes in >473 samples; in total >2,350 Mb were sequenced. In the context of this large-scale study we obtained a false positive rate of approximately 1 in 500,000 bp and a false negative rate of approximately 10%.

High quality copy number and genotype data from FFPE samples using Molecular Inversion Probe (MIP) microarrays.

BACKGROUND: A major challenge facing DNA copy number (CN) studies of tumors is that most banked samples with extensive clinical follow-up information are Formalin-Fixed Paraffin Embedded (FFPE). DNA from FFPE samples generally underperforms or suffers high failure rates compared to fresh frozen samples because of DNA degradation and cross-linking during FFPE fixation and processing. As FFPE protocols may vary widely between labs and samples may be stored for decades at room temperature, an ideal FFPE CN technology should work on diverse sample sets. Molecular Inversion Probe (MIP) technology has been applied successfully to obtain high quality CN and genotype data from cell line and frozen tumor DNA. Since the MIP probes require only a small (approximately 40 bp) target binding site, we reasoned they may be well suited to assess degraded FFPE DNA. We assessed CN with a MIP panel of 50,000 markers in 93 FFPE tumor samples from 7 diverse collections. For 38 FFPE samples from three collections we were also able to asses CN in matched fresh frozen tumor tissue. RESULTS: Using an input of 37 ng genomic DNA, we generated high quality CN data with MIP technology in 88% of FFPE samples from seven diverse collections. When matched fresh frozen tissue was available, the performance of FFPE DNA was comparable to that of DNA obtained from matched frozen tumor (genotype concordance averaged 99.9%), with only a modest loss in performance in FFPE. CONCLUSION: MIP technology can be used to generate high quality CN and genotype data in FFPE as well as fresh frozen samples.

Rapid identification of somatic mutations in colorectal and breast cancer tissues using mismatch repair detection (MRD).

Mismatch repair detection (MRD) was used to screen 93 matched tumor-normal sample pairs and 22 cell lines for somatic mutations in 30 cancer relevant genes. Using a starting amount of only 150 ng of genomic DNA, we screened 102 kb of sequence for somatic mutations in colon and breast cancer. A total of 152 somatic mutations were discovered, encompassing previously reported mutations, such as BRAF V600E and KRAS G12S, G12V, and G13D, as well as novel mutations, including some in genes in which somatic mutations have not previously been reported, such as MAP2K1 and MAP2K2. The distribution of mutations ranged widely within and across tumor types. The functional significance of many of these mutations is not understood, with patterns of selection only evident in KRAS and BRAF in colon cancer. These results present a novel approach to high-throughput mutation screening using small amounts of starting material and reveal a mutation spectrum across 30 genes in a large cohort of breast and colorectal cancers.

Highly efficient somatic-mutation identification using Escherichia coli mismatch-repair detection.

The discovery of somatic mutations in cancer tissue is extremely laborious, time-consuming and costly. In an evaluation comparing mismatch repair detection (MRD) against Sanger sequencing for somatic-mutation detection, we found that MRD had a specificity of 96% and a sensitivity of 92%. Our results showed that MRD is a robust and cost-effective alternative to Sanger sequencing for identifying somatic mutations in human tumors.

Functional single nucleotide polymorphism-based association studies.

Association studies hold great promise for the elucidation of the genetic basis of diseases. Studies based on functional single nucleotide polymorphisms (SNPs) or on linkage disequilibrium (LD) represent two main types of designs. LD-based association studies can be comprehensive for common causative variants, but they perform poorly for rare alleles. Conversely, functional SNP-based studies are efficient because they focus on the SNPs with the highest a priori chance of being associated. Our poor ability to predict the functional effect of SNPs, however, hampers attempts to make these studies comprehensive. Recent progress in comparative genomics, and evidence that functional elements tend to lie in conserved regions, promises to change the landscape, permitting functional SNP association studies to be carried out that comprehensively assess common and rare alleles. SNP genotyping technologies are already sufficient for such studies, but studies will require continued genomic sequencing of multiple species, research on the functional role of conserved sequences and additional SNP discovery and validation efforts (including targeted SNP discovery to identify the rare alleles in functional regions). With these resources, we expect that comprehensive functional SNP association studies will soon be possible.

Large-scale characterization of public database SNPs causing non-synonymous changes in three ethnic groups.

Single nucleotide polymorphisms (SNPs) that lead to non-synonymous changes in proteins may have functional effects and be subject to selection. Hence they are of particular interest in the study of genetic diseases. We have genotyped approximately 28,000 such SNPs in three ethnic populations (the HapMap plates) and ten primate species and analyzed these data for evidence of selection. We find SNPs predicted by PolyPhen to be damaging, have lower allele frequencies, and are particularly likely to be population-specific. We have also grouped SNPs by molecular function or biological process of the associated genes and find evidence that selection may be acting in concert on classes of genes.

PTPN22 genetic variation: evidence for multiple variants associated with rheumatoid arthritis.

The minor allele of the R620W missense single-nucleotide polymorphism (SNP) (rs2476601) in the hematopoietic-specific protein tyrosine phosphatase gene, PTPN22, has been associated with multiple autoimmune diseases, including rheumatoid arthritis (RA). These genetic data, combined with biochemical evidence that this SNP affects PTPN22 function, suggest that this phosphatase is a key regulator of autoimmunity. To determine whether other genetic variants in PTPN22 contribute to the development of RA, we sequenced the coding regions of this gene in 48 white North American patients with RA and identified 15 previously unreported SNPs, including 2 coding SNPs in the catalytic domain. We then genotyped 37 SNPs in or near PTPN22 in 475 patients with RA and 475 individually matched controls (sample set 1) and selected a subset of markers for replication in an additional 661 patients with RA and 1,322 individually matched controls (sample set 2). Analyses of these results predict 10 common (frequency >1%) PTPN22 haplotypes in white North Americans. The sole haplotype found to carry the previously identified W620 risk allele was strongly associated with disease in both sample sets, whereas another haplotype, identical at all other SNPs but carrying the R620 allele, showed no association. R620W, however, does not fully explain the association between PTPN22 and RA, since significant differences between cases and controls persisted in both sample sets after the haplotype data were stratified by R620W. Additional analyses identified two SNPs on a single common haplotype that are associated with RA independent of R620W, suggesting that R620W and at least one additional variant in the PTPN22 gene region influence RA susceptibility.

Analysis of families in the multiple autoimmune disease genetics consortium (MADGC) collection: the PTPN22 620W allele associates with multiple autoimmune phenotypes.

Autoimmune disorders constitute a diverse group of phenotypes with overlapping features and a tendency toward familial aggregation. It is likely that common underlying genes are involved in these disorders. Until very recently, no specific alleles--aside from a few common human leukocyte antigen class II genes--had been identified that clearly associate with multiple different autoimmune diseases. In this study, we describe a unique collection of 265 multiplex families assembled by the Multiple Autoimmune Disease Genetics Consortium (MADGC). At least two of nine "core" autoimmune diseases are present in each of these families. These core diseases include rheumatoid arthritis (RA), systemic lupus erythematosus (SLE), type 1 diabetes (T1D), multiple sclerosis (MS), autoimmune thyroid disease (Hashimoto thyroiditis or Graves disease), juvenile RA, inflammatory bowel disease (Crohn disease or ulcerative colitis), psoriasis, and primary Sjogren syndrome. We report that a recently described functional single-nucleotide polymorphism (rs2476601, encoding R620W) in the intracellular tyrosine phosphatase (PTPN22) confers risk of four separate autoimmune phenotypes in these families: T1D, RA, SLE, and Hashimoto thyroiditis. MS did not show association with the PTPN22 risk allele. These findings suggest a common underlying etiologic pathway for some, but not all, autoimmune disorders, and they suggest that MS may have a pathogenesis that is distinct from RA, SLE, and T1D. DNA and clinical data for the MADGC families are available to the scientific community; these data will provide a valuable resource for the dissection of the complex genetic factors that underlie the various autoimmune phenotypes.

Genetic association of the R620W polymorphism of protein tyrosine phosphatase PTPN22 with human SLE.

We genotyped 525 independent North American white individuals with systemic lupus erythematosus (SLE) for the PTPN22 R620W polymorphism and compared the results with data generated from 1,961 white control individuals. The R620W SNP was associated with SLE (genotypic P=.00009), with estimated minor (T) allele frequencies of 12.67% in SLE cases and 8.64% in controls. A single copy of the T allele (W620) increases risk of SLE (odds ratio [OR]=1.37; 95% confidence interval [CI] 1.07-1.75), and two copies of the allele more than double this risk (OR=4.37; 95% CI 1.98-9.65). Together with recent evidence showing association of this SNP with type 1 diabetes and rheumatoid arthritis, these data provide compelling evidence that PTPN22 plays a fundamental role in regulating the immune system and the development of autoimmunity.

A missense single-nucleotide polymorphism in a gene encoding a protein tyrosine phosphatase (PTPN22) is associated with rheumatoid arthritis.

Rheumatoid arthritis (RA) is the most common systemic autoimmune disease, affecting approximately 1% of the adult population worldwide, with an estimated heritability of 60%. To identify genes involved in RA susceptibility, we investigated the association between putative functional single-nucleotide polymorphisms (SNPs) and RA among white individuals by use of a case-control study design; a second sample was tested for replication. Here we report the association of RA susceptibility with the minor allele of a missense SNP in PTPN22 (discovery-study allelic P=6.6 x 10(-4); replication-study allelic P=5.6 x 10(-8)), which encodes a hematopoietic-specific protein tyrosine phosphatase also known as "Lyp." We show that the risk allele, which is present in approximately 17% of white individuals from the general population and in approximately 28% of white individuals with RA, disrupts the P1 proline-rich motif that is important for interaction with Csk, potentially altering these proteins' normal function as negative regulators of T-cell activation. The minor allele of this SNP recently was implicated in type 1 diabetes, suggesting that the variant phosphatase may increase overall reactivity of the immune system and may heighten an individual carrier's risk for autoimmune disease.

Molecular basis of intrahepatic cholestasis.

Intrahepatic cholestasis, or impairment of bile flow, is an important manifestation of inherited and acquired liver disease. In recent years, human genetic and molecular studies have identified several genes, the disruption of which results in cholestasis. ATP8B1 (FIC1), ABCB11 (BSEP), and ABCB4 (MDR3) are disrupted in forms of progressive familial intrahepatic cholestasis (PFIC) and related disorders. Mutations in BAAT, TJP2 (ZO-2), and EPHX1 have been identified in patients with hypercholanemia. A CLDN1 mutation was recently reported in patients with ichthyosis, leukocyte vacuoles, alopecia and sclerosing cholangitis (ILVASC), and North American Indian childhood cirrhosis (NAIC) is associated with a missense mutation in CIRH1A. Alagille syndrome patients carry mutations in JAG1, and mutations in VPS33B have been identified in patients with arthrogryposis, renal dysfunction and cholestasis syndrome (ARC). Identification of these genes, and characterization of the proteins they encode, is enhancing our understanding of the biology of the enterohepatic circulation in health and disease.