B-allele Frequency Research Articles

A Novel Single Next-Generation Sequencing (NGS) Approach for the Molecular Karyotyping and Genotyping of Patients with Myelodysplastic Syndromes

Myelodysplastic Syndromes (MDS) are a heterogeneous group of diseases, characterized by the clonal acquisition of somatic point mutations and chromosomal alterations. Conventional karyotyping remains one of the most important tools for MDS diagnosis because several cytogenetics abnormalities can be used to stratify patients into subtypes with different prognoses. However, a non-informative cytogenetics due to normal or unsuccessful karyotype could lead to an erroneous estimation of the prognostic risk. To overcome this drawback, we assessed the reliability of a single Next-Generation Sequencing (NGS) assay to simultaneously detect Single Nucleotide Variations (SNVs), including small indels, as well as Copy Number Alterations (CNAs) and copy-neutral Loss of Heterozygosity (cnLOH) for diagnostic application.We combined a custom panel, targeting 40 genes frequently implicated in myeloid neoplasms, with a target enrichment design (OneSeq, Agilent®), having a genome-wide backbone resolution of 1 Mb and 10 Mb for CNAs and cnLOH, respectively. Sequencing libraries were prepared following the “SureSelectQXT Library Prep” protocol and sequenced using the NextSeq 500 platform (Illumina®). Data processing and variant annotation were performed using an integrated in-house bioinformatic pipeline. SNVs and small indels were selected based on allele frequency (VAF ≥ 3%), their absence in the healthy population (UCSC Common SNP; MAF < 1%) and their putative effect on splicing and protein. For CNAs and cnLOH detection, we combined the analysis of the sequencing depth, using the DECoN tool, with the B-allele frequency (BAF) for a selection of high minor allele frequency single nucleotide polymorphisms. The CNA pathogenicity was evaluated taking into account gene content, frequency in the general population (e.g . Database of Genomic Variants) and reports in the literature.We performed a pilot study with a cohort of 30 patients clinically diagnosed with primary MDS at La Fe University Hospital in Valencia. Samples were analysed in parallel by NGS and CytoScanTM HD array (Affymetrix®) in order to establish criteria and thresholds for accurate filtering of sequencing data, especially for CNA identification and calculation of analytical sensitivity. Currently, we are evaluating the reliability of these criteria in a separate cohort of 30 additional patients.Preliminary results in the test cohort showed that we were able to identify at least one point mutation in 29 of 30 patients, with an average of 2 mutations per sample (range 0-7). Mutations were detected in 20 of the 40 genes covered in the panel. The epigenetic modifier TET2 was the most frequently mutated gene in the cohort (9 of 30 cases), followed by two splicing genes, SF3B1 and SRSF2 (each 8 of 30). In addition, we observed some of the described gene correlations, such as the co-occurrence of mutations in IDH2 and SRSF2 genes and the mutually exclusive presence of SF3B1 and SRSF2 .Although cytogenetic studies identified chromosomal abnormalities in 9 of 30 of cases, the number of MDS-related copy number changes detected by sequencing increased to 20 cases, including 9 with normal and 1 with unsuccessful karyotype. We observed the frequent CNAs, such as chromosome 5q and 7q deletions, 4 and 3 cases, respectively, the complete duplication of chr21 in 1 case and 9 cnLOH events. Interestingly, in patients with normal karyotype, although we focused on large chromosomal abnormalities, we have detected at least 3 small events (6-14 Mb) leading to focal deletions of ETV6, BTG1 and RUNX1 genes, as well as 6 cnLOH events, 2 of which involved chr7q22q36.We obtained a high level of concordance between clinical relevant CNAs larger than 1 Mb identified by the CytoScanTM HD array and our sequencing approach. However, the variation in probe distribution in the two backbones was responsible for differences in the detected sizes of deletions and duplications in ~10% of the observed CNAs.This NGS strategy allowed the identification of point mutations and large chromosomal alterations with a resolution of 1 Mb using a single assay, as well as other alterations invisible to conventional cytogenetics, such as cnLOH. Although automating the bioinformatic pipeline is still ongoing, this study demonstrated that a comprehensive NGS-based genomic approach could contribute to improve MDS diagnosis and prognosis. DisclosuresSanz:Gamida Cell: Research Funding.

Detecting copy number alterations in RNA-Seq using SuperFreq.

Calling copy number alterations (CNAs) from RNA sequencing (RNA-Seq) is challenging, because of the marked variability in coverage across genes and paucity of single nucleotide polymorphisms (SNPs). We have adapted SuperFreq to call absolute and allele sensitive CNAs from RNA-Seq. SuperFreq uses an error-propagation framework to combine and maximize information from read counts and B-allele frequencies. We used datasets from The Cancer Genome Atlas (TCGA) to assess the validity of CNA calls from RNA-Seq. When ploidy estimates were consistent, we found agreement with DNA SNP-arrays for over 98% of the genome for acute myeloid leukaemia (TCGA-AML, n = 116) and 87% for colorectal cancer (TCGA-CRC, n = 377). The sensitivity of CNA calling from RNA-Seq was dependent on gene density. Using RNA-Seq, SuperFreq detected 78% of CNA calls covering 100 or more genes with a precision of 94%. Recall dropped for focal events, but this also depended on signal intensity. For example, in the CRC cohort SuperFreq identified all cases (7/7) with high-level amplification of ERBB2, where the copy number was typically >20, but identified only 6% of cases (1/17) with moderate amplification of IGF2, which occurs over a smaller interval. SuperFreq offers an integrated platform for identification of CNAs and point mutations. As evidence of how SuperFreq can be applied, we used it to reproduce the established relationship between somatic mutation load and CNA profile in CRC using RNA-Seq alone. SuperFreq is implemented in R and the code is available through GitHub: https://github.com/ChristofferFlensburg/SuperFreq/. Data and code to reproduce the figures are available at: https://gitlab.wehi.edu.au/flensburg.c/SuperFreq_RNA_paper. Data from TCGA (phs000178) was accessed from GDC following completion of a data access request through the database of Genotypes and Phenotypes (dbGaP). Data from the Leucegene consortium was downloaded from GEO (AML samples: GSE67040; normal CD34+ cells: GSE48846). Supplementary data are available at Bioinformatics online.

Parthenogenetic mosaicism: generation via second polar body retention and unmasking of a likely causative PER2 variant for hypersomnia

BackgroundParthenogenetic mosaicism is an extremely rare condition identified only in five subjects to date. The previous studies indicate that this condition is mediated by parthenogenetic activation and is free from a specific phenotype ascribed to unmaking of a maternally inherited recessive variant in the parthenogenetic cell lineage.ResultsWe examined a 28-year-old Japanese 46,XX female with Silver-Russell syndrome and idiopathic hypersomnia. The results revealed (1) predominance of maternally derived alleles for all the differentially methylated regions examined; (2) no disease-related copy-number variant; (3) two types of regions for all chromosomes, i.e., four BAF (B-allele frequency) band regions with single major microsatellite peaks of maternal origin and single minor microsatellite peaks of non-maternal (paternal) origin, and six BAF band regions with single major microsatellite peaks of maternal origin and two minor microsatellite peaks of maternal and non-maternal (paternal) origin; (4) an unmasked extremely rare PER2 variant (c.1403G>A:p.(Arg468Gln)) with high predicted pathogenicity; (5) mildly affected local structure with altered hydrogen bonds of the p.Arg468Gln-PER2 protein; and (6) nucleus-dominant subcellular distribution of the p.Arg468Gln-PER2 protein.ConclusionsThe above findings imply that the second polar body retention occurred around fertilization, resulting in the generation of the parthenogenetic cell lineage by endoreplication of a female pronucleus and the normal cell lineage by fusion of male and female pronuclei, and that the homozygous PER2 variant in the parthenogenetic cells is the likely causative factor for idiopathic hypersomnia.

Genome-wide identification of Chiari malformation type I associated candidate genes and chromosomal variations.

Chiari malformation type I (CMI) is a brain malformation that is characterized by herniation of the cerebellum into the spinal canal. Chiari malformation type I is highly heterogeneous; therefore, an accurate explanation of the pathogenesis of the disease is often not possible. Although some studies showed the role of genetics in CMI, the involvement of genetic variations in CMI pathogenesis has not been thoroughly elucidated. Therefore, in the current study we aim to reveal CMI-associated genomic variations in familial cases.Four CMI patients and 7 unaffected healthy members of two distinct families were analyzed. A microarray analysis of the affected and unaffected individuals from two Turkish families with CMI was conducted. Analyses of single nucleotide variations (SNVs) and copy number variations (CNVs) were performed by calculation of B allele frequency (BAF) and log R ratio (LRR) values from whole genome SNV data. Two missense variations, OLFML2A (rs7874348) and SLC4A9 (rs6860077), and a 5’UTR variation of COL4A1 (rs9521687) were significantly associated with CMI. Moreover, 12 SNVs in the intronic regions of FAM155A, NR3C1, TRPC7, ASTN2, and TRAF1 were determined to be associated with CMI. The CNV analysis showed that the 11p15.4 chromosome region is inherited in one of the families. The use of familial studies to explain the molecular pathogenesis of complex diseases such as CMI is crucial. It has been suggested that variations in OLFML2A, SLC4A9, and COL4A1 play a role in CMI molecular pathogenesis. The CNV analysis of individuals in both families revealed a potential chromosomal region, 11p15.4, and risk regions that are associated with CMI.

Pre-Transplant Clonal Mosaicism Is Associated with Increased Relapse and Lower Survival in Acute Lymphoblastic Leukemia Patients Undergoing Allogeneic Hematopoietic Cell Transplant

Clonal mosaicism, detectable in peripheral blood, can be an important predictor of developing a hematological malignancy. We sought to determine if mosaic events, in addition to clinical and demographic variables, contributed independent information about acute lymphoblastic leukemia (ALL) patient survival and risk of relapse after allogeneic hematopoietic cell transplant (HCT). HumanOmniExpress-12v1_A BeadChip SNP array data were used to detect mosaicisms &amp;gt;=2Mb based on the log2 relative probe intensity ratio (LRR) and B allele frequency (BAF) for each SNP measured in 773 ALL patients from DISCOVeRY-BMT cohorts. DNA was extracted from recipient peripheral blood samples taken immediately prior to start of conditioning before allogeneic HCT for ALL (2000-2011). Mosaic events include copy-number gain (LRR &amp;gt;0), loss (LRR &amp;lt;0), or copy-neutral loss of heterozygosity (CNLOH), defined as a deviation from BAF heterozygosity without LRR changes. The impact of mosaicism on overall survival (OS) probability and cumulative incidence of relapse at 1-year post-HCT were calculated using the Kaplan-Meier estimator and cumulative incidence functions, respectively. The association of clonal mosaicism with OS was evaluated with multivariable Cox proportional hazard models. For disease relapse, competing risk models were used with transplant related mortality (TRM) treated as a competing event. Stratified survival analyses were performed by cytogenetic status at diagnosis. Statistical analyses were conducted using R 3.6.1. Thirty-four patients (4.4%) had 1 or more mosaicisms (82 total detected) with almost half having advanced disease (Table 1). The median proportion of affected cells was 61% (interquartile range = 39 - 93%). Copy-number losses on chromosomes 7 (13.4%) and 9 (8.54%) and 17 (6.10%) were the most frequently detected events (Figure 1). OS at 1-year post HCT in patients with and without a mosaic event was 26.5% and 60.1%, respectively, (P=8.2×10-8, Figure 2A) and normal cytogenetic patients with mosaicism had significantly lower survival compared to all other patients (OSnormal/mosaic+= 8.3% vs. OS= 60.6%, P=3.0×10-10, Figure 2B-C). ALL patients with a mosaic event also had an increased risk of disease relapse overall (Relapsemosaic+= 50% vs. Relapsemosaic-=26%, P=0.00067) and when stratified by cytogenetic abnormalities (P=0.015) and normal cytogenetics (P=0.041) (Figure 2D-F). Multivariable models of OS and relapse included age, race/ethnicity, complete remission or advanced disease status (Figure 3). Patients with a mosaic event had ~2.5 fold increase risk of death (P=2.5×10-5), independent from cytogenetics (P=8.6×10-5, Figure 3). OS associations are likely driven by the 2.8 fold increase risk of relapse (P= 5.9×10-5) which remains highly significant when stratified by cytogenetics (Figure 3). Almost half of the copy-number losses included well-known regions on chromosomes 7, 9 and 17 (Figure 1). Deletions of 7p have been shown to correlate with lower event-free survival in ALL pediatric patients. Our findings suggest mosaic loss of 7p might be an important indicator of poor OS across the lifespan, with 5/6 patients with 7p losses aged &amp;gt;18 years. Higher mortality was also associated with the loss of the chr9p21.3 locus, seen in all patients (N=5) with chromosome 9p losses. This region harbors tumor suppressor CDKN2A; inactivation of CDKN2A can lead to poor survival in both children and adults with ALL. Lastly, we found that all patients (N=4) with copy-number loss of 17p13.1, which contains tumor suppressor TP53 died within 1-year post-HCT. We identified detectable mosaicism prior to transplant in 4.4% of patients and showed that mosaicism was associated with lower survival and higher disease relapse at 1-year post-HCT. While mosaicism is more common in patients with advanced disease stage, mosaic events are an independent contributor to lower survival and higher relapse in the first year after transplant. This is the first study to show that mosaic events detectable in pre-transplant peripheral blood from ALL patients are correlated with poor survival. Future studies replicating these associations in different ethnicities and age groups and evaluating specific chromosomal regions could be informative in classifying patient risk post-HCT attributable to mosaic events. Disclosures McCarthy: Karyopharm: Consultancy, Honoraria; Magenta: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Other: Advisory Board; Janssen: Honoraria, Membership on an entity's Board of Directors or advisory committees, Other: Advisory Board; Takeda: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Other: Advisory Board; AbbVie: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Other: Advisory Board; Genentech: Consultancy, Honoraria; Starton: Honoraria, Membership on an entity's Board of Directors or advisory committees, Other: Advisory Board; Juno Therapeutics, a Bristol-Myers Squibb Company: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Other: Advisory Board , Research Funding is to Roswell Park, Research Funding. Pasquini:Bristol Myers Squibb: Consultancy; BMS: Membership on an entity's Board of Directors or advisory committees, Research Funding; Amgen: Other; Novartis: Research Funding; Kite: Research Funding. Lee:Pfizer: Consultancy, Research Funding; Novartis: Research Funding; Takeda: Research Funding; Amgen: Research Funding; Kadmon: Research Funding; Incyte: Consultancy, Research Funding; AstraZeneca: Research Funding; Syndax: Research Funding.

Mutational and Copy Number Profiling of Circulating Tumor DNA in Acute Myeloid Leukemia Using Targeted Next Generation Sequencing

The assessment of circulating tumor DNA (ctDNA), released by tumor cells undergoing apoptosis or necrosis, has established utility in solid tumors due to the advantage of a non-invasive "liquid biopsy" replacing multiple site-specific biopsies. However, its role in acute myeloid leukemia (AML) is uncertain, where a significant proportion of variants detected in the bone marrow (BM) may not be detected in ctDNA (Short, Blood Adv 2020). We have previously demonstrated the possibility of comprehensive genomic characterization of lymphoid malignancy from ctDNA using a single targeted next generation sequencing (NGS) hybridization-based panel (Blombery, BJH 2017). We aimed to assess the performance of this same genomic approach in ctDNA and to compare it against BM in AML. In addition, we aimed to assess the integration of a sensitive variant caller (Mutect2; Benjamin, bioRxiv 2019) to the bioinformatics suite in an attempt to improve low-level variant detection. Nineteen patients were identified from sequential patients with AML treated at our institutions where paired ctDNA and BM aspirate DNA were available. ctDNA was analyzed using a hybridization-based NGS panel targeting genes recurrently mutated in hematological malignancy followed by a suite of bioinformatics tools including HaplotypeCaller (GATK)/Mutect2 (GATK) for variant calling, CNSpector/CNSpectorX (Markham, Sci Reports 2019) for copy number variation (CNV) assessment and GRIDSS (Cameron, Genome Res 2017) for structural variant detection. The cohort clinical details are summarized in Table 1; none had documented extramedullary disease at time of collection. A total of 66 unique variants in 27 genes were detected, summarized in Figure 1. Median number of variants detected was 3 per patient sample, including NPM1 (n=6), IDH1/2 (n=4) and FLT3 point mutation (n=2). Three patient samples had FLT3-ITD detected by fragment length analysis; none were detected by the NGS panel in either ctDNA or BM. Variant allele frequency (VAF) from both compartments were highly correlated (R2 0.87). Higher VAFs in ctDNA were more commonly observed for kinase activating mutations (12/17 variants) and TP53 (5/6). Using HaplotypeCaller alone, 58 and 61 variants were detected in the BM and ctDNA, respectively. Of the 2 variants "specific" to the BM, both (IDH1 and NRAS) were called by Mutect2 in ctDNA and confirmed by visual inspection of sequence read alignments. Of the 5 variants "specific" to the ctDNA, 4 were detected in the BM at low VAF: CBL (n=2), KRAS and TET2. One discrepant case was patient #15 with prior breast cancer: KRAS G13D 21% in ctDNA but absent in the BM. Analysis by Mutect2 additionally detected 3 variants not called by HaplotypeCaller: NRAS and KIT in both ctDNA and BM, and TP53 P278R (VAF 6%) specific to the ctDNA in patient #9 with normal karyotype AML without history of prior malignancy. Overall, 3/5 variants in ctDNA and 6/6 in BM with low VAF were kinase activating mutations. We then performed genome-wide alignment of off-target reads to generate a low-resolution digital karyotype and CNV from ctDNA (Figure 2) which was compared with CNV and conventional karyotyping from BM. CNVs were detected in ctDNA in 10/11 patients with abnormal karyotype (Figure 1). Of these, 6/7 with non-complex abnormal karyotypes had consistent ctDNA CNVs including (i) 3 patients (#1, #10 and #15) with either rearranged/amplified KMT2A by FISH were all found to have gains at 11q23.3-qter, and (ii) 1 patient (#4) had 2 marker chromosomes of unknown origin on karyotyping which were resolved as additional copies of 4p using ctDNA sequencing. Although no CNVs were detected in all 8 patients with normal karyotype, analysis of B-allele frequency from ctDNA revealed one patient (#5) with copy neutral loss of heterozygosity (CN-LOH) in 7q (with a concurrent EZH2 mutation &amp;gt;95% VAF). In summary, we have demonstrated the ability to detect sequence variants, perform low-resolution digital karyotyping, CNV detection and CN-LOH detection from ctDNA in AML using a single hybridization based NGS assay. When using this approach, we show a high degree of concordance for both sequence variant and CNV detection, supporting the use of ctDNA as an alternative to BM (e.g. in cases of dry tap, hypocellular AML or failed karyotyping). Finally, using a sensitive variant caller, additional mutations were able to be detected in the ctDNA, the significance of which require evaluation in future studies. Disclosures Tiong: Amgen: Consultancy, Honoraria; Pfizer: Consultancy; Servier: Consultancy. Wilson:Illumina: Other: Illumina Diagnostic Genomics Scholarship. Bajel:Novartis: Honoraria; Astellas: Honoraria; Abbvie: Honoraria; Amgen: Honoraria, Speakers Bureau; Pfizer: Honoraria. Blombery:Invivoscribe: Honoraria; Novartis: Consultancy; Janssen: Honoraria; Amgen: Consultancy.

Abstract 6678: Sensitive HLA loss of heterozygosity detection reveals allele-specific neoantigen expansion as resistance mechanism to anti-PD-1 therapy

Abstract Loss of heterozygosity (LOH) in the HLA locus is increasingly being recognized as an important mechanism of immune escape and a proposed biomarker for immunotherapy response. Neoantigens that bind to a deleted HLA allele will no longer be presented to the immune system, potentially allowing subclones with these deletions to escape immune surveillance. Despite interest in the field, few methods exist to detect HLA LOH, and their sensitivity is not well understood. Moreover, the mechanistic impact of HLA LOH in response to immune checkpoint inhibitors (ICI) remains unexplored. Here, using a novel tool to detect HLA LOH, DASH (Deletion of Allele-Specific HLAs), we reveal allele-specific neoantigen expansion in response to ICIs in a head and neck carcinoma cohort and the widespread occurrence of HLA LOH across several tumor types. We performed exome sequencing with ImmunoID NeXT, which enhances coverage of the HLA locus, on tumor and normal samples from 260 patients to create a training dataset for our model. For each patient, we mapped reads to each of their allele-specific HLAs and manually annotated LOH. Then, using purity, ploidy and two novel features (normalized b-allele frequency and allele-specific coverage ratios), we trained an XGBoost model. To evaluate our tool, we compared DASH predictions on held out tumor samples to deletion calls from a standard copy number tool in the regions flanking each HLA gene (91% concordance, 0.73 F1-score), ascertained our sensitivity by diluting cell line data with known HLA LOH to imitate variable purity (100% accuracy in samples above 17% purity) and confirmed the functional impact of HLA LOH using immunopeptidomics data of tumor samples (average of 47% fewer unique peptides binding to lost alleles than kept). To explore the mechanistic impact of HLA LOH in response to ICIs, we studied a cohort of nine head and neck carcinoma patients who received a single dose of nivolumab, and sequenced pre- and posttreatment tumor biopsies for each patient. With DASH, we detected HLA LOH in four of the patients, pretreatment. For these patients, we found a significant posttreatment expansion of neoantigens predicted to bind to the deleted HLA alleles in comparison to the pretreatment biopsy (p=0.046, Wilcoxon signed-rank), revealing the evolutionary force of HLA LOH as a resistance mechanism during ICI therapy. To assess the pervasiveness of HLA LOH across tumor types, we applied DASH to over 500 pretreatment tumors across 13 tumor types and found highly variable frequencies of HLA LOH across the tumor types. In summary, we developed a sensitive method to detect HLA LOH and exposed neoantigen expansion to deleted HLA alleles in response to ICI therapy, emphasizing the limitations of deleted alleles to ignite an immune response. Moreover, we found widespread occurrences of HLA LOH across tumor types, highlighting the importance of accurate HLA LOH detection as a pan-cancer biomarker. Citation Format: Rachel Marty Pyke, Charles Abbott, Dattatreya Mellacheruvu, Simo V. Zhang, Nikita Bedi, A. Dimitrios Colevas, John Sunwoo, John West, Richard Chen, Sean Michael Boyle. Sensitive HLA loss of heterozygosity detection reveals allele-specific neoantigen expansion as resistance mechanism to anti-PD-1 therapy [abstract]. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr 6678.

Detection of tetraploidization in chromophobe renal cell carcinoma: Insights and pitfalls.

Chromosomal losses resulting in a marked hypodiploidy are a specificity of chromophobe renal cell carcinoma (ChRCC), the third most frequent type of kidney cancer. Its detection is useful in challenging cases. However some ChRCC, especially the eosinophilic variant, do not exhibit hypodiploidy and deserve to be better explored. Using comparative genomic hybridization (array-CGH) we observed chromosomal gains in five cases of nonmetastatic ChRCC. Our objective was to determine whether these apparent chromosomal gains were instead losses within a near-polyploid genome. We performed a retrospective and prospective molecular study of 26 cases of ChRCC retrieved among 643 renal tumors (2012-2019). All tumors were analyzed using array-CGH (Agilent) and array-CGH (Affymetrix) coupled to single nucleotide polymorphism analysis (array-SNP). In silico manual centralization of the fluorescence ratio, fluorescence in situ hybridization (FISH) and next generation sequencing were made in the five cases suspected of polyploidy. Tetraploidization was observed in 19% of our series of ChRCC. None of the methods used individually could identify both chromosomal losses and tetraploidy. Only the combination of manual recentring of array-CGH and FISH provided relevant results. B-allele frequency results indicated that tetraploidization occurred secondarily to chromosomal losses in four cases while it preceded losses in one case. Tetraploidization is a frequent but underestimated phenomenon in ChRCC that may be overlooked using the individual standard genomic methods. Its potential clinical consequences are not identified yet. Whether the mechanisms that induce chromosomal losses in ChRCC are the same that generate tetraploidization is not known.

Genomic copy number variation correlates with survival outcomes in WHO grade IV glioma

Allele-specific copy number analysis of tumors (ASCAT) assesses copy number variations (CNV) while accounting for aberrant cell fraction and tumor ploidy. We evaluated if ASCAT-assessed CNV are associated with survival outcomes in 56 patients with WHO grade IV gliomas. Tumor data analyzed by Affymetrix OncoScan FFPE Assay yielded the log ratio (R) and B-allele frequency (BAF). Input into ASCAT quantified CNV using the segmentation function to measure copy number inflection points throughout the genome. Quantified CNV was reported as log R and BAF segment counts. Results were confirmed on The Cancer Genome Atlas (TCGA) glioblastoma dataset. 25 (44.6%) patients had MGMT hyper-methylated tumors, 6 (10.7%) were IDH1 mutated. Median follow-up was 36.4 months. Higher log R segment counts were associate with longer progression-free survival (PFS) [hazard ratio (HR) 0.32, p < 0.001], and overall survival (OS) [HR 0.45, p = 0.01], and was an independent predictor of PFS and OS on multivariable analysis. Higher BAF segment counts were linked to longer PFS (HR 0.49, p = 0.022) and OS (HR 0.49, p = 0.052). In the TCGA confirmation cohort, longer 12-month OS was seen in patients with higher BAF segment counts (62.3% vs. 51.9%, p = 0.0129) and higher log R (63.6% vs. 55.2%, p = 0.0696). Genomic CNV may be a novel prognostic biomarker for WHO grade IV glioma patient outcomes.

Abstract A19: HLA allele-specific loss of heterozygosity detection using augmented exome capture approach

Abstract Loss of human leukocyte antigen (HLA) is of increasing interest as a mechanism of cancer immune evasion and biomarker for cancer immunotherapy response. Each cancer patient has six class I HLA alleles that are capable of presenting a set of tumor-specific neoantigens. However, HLA alleles are often deleted in tumors, resulting in a loss of heterozygosity (LOH). When LOH occurs, neoantigen presentation is significantly impaired, potentially facilitating tumor immune evasion. Given the biologic impact of HLA LOH, there is a need for robust algorithms that can detect allele-specific HLA LOH in tumor samples. Here, we describe a novel computational approach to detect HLA LOH from exome sequencing, demonstrate the robustness of the method, and apply the method to calculate the frequencies of HLA LOH in key cancer types. We performed exome sequencing with augmented HLA region capture on the ImmunoID NeXT platform for tumor and normal samples of 184 patients across several cancer types and identified 430 nonhomozygous HLA genes. Next, we extracted the reads mapping to a custom HLA database and mapped them on to the patient-specific HLA alleles. For each allele, we calculated two key features: 1) the tumor b-allele frequency normalized by the native b-allele frequency and 2) the allele-specific tumor to normal coverage ratio. Using these two features, along with tumor purity and ploidy values, we trained a random forest model on a subset of the HLA genes (n=300). While standard copy-number variant (CNV) tools are unable to detect LOH in the polymorphic HLA genes, they can accurately measure deletions in their flanking regions, which we used to validate the accuracy of our allele-specific HLA LOH algorithm. In our test set (n=130), we found a high concordance between our allele-specific deletion calls and the generic deletion calls (94% accuracy, 0.85 F1 Score). When we constrained our test set to samples with high tumor content (&amp;gt;50%, n=40), we saw even stronger concordance (98% accuracy, 0.95 F1 Score). The only discordant call was a focal deletion within an HLA gene that was detected by our algorithm but missed by the CNV tool. Next, we ran our algorithm on patient samples of different cancer indications. For non-small cell lung cancer, we found a high frequency of patients affected by LOH (35%, 9 of 26), which is similar to frequencies previously reported in the literature. Furthermore, we found a lower frequency of melanoma tumors with LOH (15%, 7 of 48). In conclusion, we developed a novel algorithm to call allele-specific HLA LOH on the ImmunoID NeXT exome sequencing platform that augments coverage in the polymorphic HLA locus and demonstrated overall robust performance. The relatively high frequency of LOH events we detected in the melanoma and lung cancer samples suggests the importance of LOH analysis to inform cancer immunotherapy biomarker studies and personalized cancer therapies that depend on neoantigen presentation. Citation Format: Rachel Marty Pyke, Charles Abbott, Simo V. Zhang, Datta Mellacheruvu, John West, Richard Chen, Sean Michael Boyle. HLA allele-specific loss of heterozygosity detection using augmented exome capture approach [abstract]. In: Proceedings of the AACR Special Conference on Tumor Immunology and Immunotherapy; 2019 Nov 17-20; Boston, MA. Philadelphia (PA): AACR; Cancer Immunol Res 2020;8(3 Suppl):Abstract nr A19.

CaSpER identifies and visualizes CNV events by integrative analysis of single-cell or bulk RNA-sequencing data

RNA sequencing experiments generate large amounts of information about expression levels of genes. Although they are mainly used for quantifying expression levels, they contain much more biologically important information such as copy number variants (CNVs). Here, we present CaSpER, a signal processing approach for identification, visualization, and integrative analysis of focal and large-scale CNV events in multiscale resolution using either bulk or single-cell RNA sequencing data. CaSpER integrates the multiscale smoothing of expression signal and allelic shift signals for CNV calling. The allelic shift signal measures the loss-of-heterozygosity (LOH) which is valuable for CNV identification. CaSpER employs an efficient methodology for the generation of a genome-wide B-allele frequency (BAF) signal profile from the reads and utilizes it for correction of CNVs calls. CaSpER increases the utility of RNA-sequencing datasets and complements other tools for complete characterization and visualization of the genomic and transcriptomic landscape of single cell and bulk RNA sequencing data.

De Novo and Therapy-Related Acute Myeloid Leukemia and Myelodysplastic Syndrome: Similarities and Differences in SNP-Array Detected Chromosomal Aberrations in Pre-Transplant Blood Samples

De Novo and Therapy-Related Acute Myeloid Leukemia and Myelodysplastic Syndrome: Similarities and Differences in SNP-Array Detected Chromosomal Aberrations in Pre-Transplant Blood Samples

Cnspectorx - Copy Number Assessment at a Genome Level from Targeted Sequence Data Optimized for Hematological Malignancy

The detection of copy number abnormalities (CNAs) is of significant clinical relevance in hematological malignancy (e.g. TP53 CN loss in chronic lymphocytic leukemia). Whilst detection of CNAs is typically performed by FISH or SNP array, it is also possible from next generation sequencing (NGS) data. Given the rapid and global expansion of targeted sequencing for the diagnosis and management of hematological malignancy, we aimed to develop a copy number (CN) analysis tool specifically suited to reporting CN in hematological malignancy in the diagnostic laboratory. We describe CNspectorX, a comprehensive CNA solution from FASTQ to interactive whole genome CN visualization with significant advantages over existing bioinformatics tools. Detecting CNAs sensitively and specifically from NGS data requires a diploid baseline with minimal random variation (noise) and with non-random variation which can correct for systematic biases. An optimal baseline requires representation of recurrent technical artefacts in the reference set. Artefacts differ based on sample type and gender (amongst other variables), therefore CNspectorX creates a patient individualized reference by selecting samples from a specified cohort based on matching metadata to the analyzed sample. This corrects for systematic bias present in the diverse sample types seen in hematological malignancy, including blood, bone marrow aspirate, FFPE tissue and circulating tumor DNA (ctDNA). CNspectorX uses either a pre-built reference or can create one from samples within a single sequencing run and includes a web-based GUI (CNspector) where samples can be dynamically added to a reference to support interactive, real-time recalculation and display of CN calls. Moreover, CNspectorX computes references using a robust estimator allowing inclusion of other tumor samples in the reference set. This flexible and dynamic approach to reference generation is unique to CNspectorX when compared to callers such as CNVkit, CopywriteR and Sequenza. Despite enrichment of targeted areas, hybridization-based NGS panels contain a proportion of residual fragments which map uniquely at random locations throughout the genome. CNspectorX aligns these "off-target" reads to allow genome-wide CN in the absence of a genome-wide SNP backbone (Figure 1). Whilst resolution is lower in off-target regions, CNspectorX can detect clinically relevant aneuploidy, chromosomal arm deletions, and segmental deletion/amplification to approximately 1-3Mb in untargeted regions (Figure 1). CNspectorX also calculates and displays genome-wide B-allele frequency from off-target reads which can both provide further support for CN calls and also detect areas of copy number neutral loss of heterozygosity. CNspectorX has a user-friendly, interactive visualization interface that displays data at genome level, chromosomal arm level and gene/exon level, allowing the analyst to observe not only the local CN change but the surrounding genomic context which may be crucial for interpretation (Figure 1). Binning of CN calls is scaled at each level allowing accurate calling of CNA from chromosome to exon level. Morover, CNA calling by CNspectorX is model-free and not reliant on the measurement of allele frequencies. Hence CNspectorX works well with small gene panels where CNA calls are computed from read abundance alone. This also means that, unlike callers that use purity/ploidy models, CNspectorX is not confounded by heterogeneity that breaks assumptions of clonality. CNspectorX has been implemented in an accredited (ISO15189) diagnostic laboratory and has been used to analyze CNA in over 1500 samples from patients with hematological malignancy. With CNspectorX we have identified multiple clinically relevant somatic and germline CN abnormalities not detected by conventional testing including high level focal amplifications in CD274 (PD-L1), MYC, MCL1, XPO1/REL and CN losses involving TP53, ATM, RPS19, BIRC3 and CDKN2A/B. In summary, we have developed CNspectorX, a comprehensive CNA analysis tool that can calculate and display whole genome-level CN from targeted NGS panels. CNspectorX is able to take into account the diverse and specific technical artefacts from typical sample types (including ctDNA) tested by the diagnostic laboratory in the investigation of hematological malignancy resulting in accurate CN data for clinical interpretation. Disclosures Dickinson: GlaxoSmithKline: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Merck Sharpe and Dohme: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding, Speakers Bureau; Takeda: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding, Speakers Bureau; Celgene: Consultancy, Honoraria, Research Funding, Speakers Bureau; Novartis: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding, Speakers Bureau; Janssen: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding, Speakers Bureau; F. Hoffmann-La Roche Ltd: Consultancy, Honoraria, Research Funding, Speakers Bureau. Blombery:Novartis: Consultancy; Janssen: Honoraria; Invivoscribe: Honoraria.

Single Nucleotide Polymorphism Array-Based Signature of Genetic Ploidy Groups in Acute Lymphoblastic Leukemia

Acute lymphoblastic leukemia (ALL) is characterised by a number of recurrent chromosomal abnormalities which inform prognosis. Low hypodiploidy (HoTr) and high hyperdiploidy (HeH) are genetic subgroups associated with large non-random ploidy shifts, specifically 30-39 chromosomes and 51-65 chromosomes respectively. HoTr ALL often presents with a near triploid karyotype of 60-78 chromosomes through chromosomal endoreduplication without cytokinesis. This presents a diagnostic challenge in distinguishing this poor risk entity from good risk HeH ALL. To date, classification of such challenging cases has been based on the modal chromosome number, the pattern of specific gains, and identification of loss of heterozygosity (LOH) using single nucleotide polymorphism (SNP) arrays where possible. However, loss of cellular context and mixed cell populations (normal diploid, low hypodiploid and near-triploid) when analysing SNP arrays can pose additional analytical difficulty. The aim of this SNP array study was to (1) determine the level of inaccurate genetic subgrouping when cytogenetics only was used to distinguish HeH from doubled up HoTr and (2) develop a diagnostic algorithm to reliably call HeH and HoTr without supporting cytogenetic analysis. SNP arrays were performed on diagnostic ALL samples of 85 patients (46 HoTr, 39 HeH) using Illumina CytoSNP 850k (n=80) or Affymetrix Cytoscan HD (n=5) arrays. Probe level data were uploaded to Nexus Copy Number 10 (BioDiscovery) and manual segments spanning the length of each chromosome were created. No further data pre-processing was carried out and log2 ratio of 0 was automatically assigned to the median log2 ratio of the sample. Chromosomal log2 ratios were normalized within each sample and a variety of machine-learning techniques used to cluster the samples independently of assigned diagnosis. Cases residing in the incorrect cluster based on initial diagnosis were examined in detail using information from cytogenetics and SNP array interpretation. SNP arrays were analysed from 46 HoTr (median age 50.5 years (range 7-87), 43% male) and 39 HeH (median age 7 years (range 1-58), 56% male) patients. Unsupervised clustering of log2 ratios showed a clear distinction between HeH and HoTr patients (figure (A)). Six cases clustered incorrectly based on cytogenetic diagnosis. After detailed interpretation of all cases, including identifying LOH affecting chromosomes 3, 7, 15, 16 and 17, 3/6 cases initially classified as HeH were highly suggestive of HoTr ALL despite having &amp;lt;60 chromosomes. Similarly, 1/6 cases was cytogenetically diagnosed with HoTr but had a SNP array pattern typical of HeH ALL. We identified chromosomes 1, 4, 11, 17, 19, and 21 as those contributing most to the distinction in the HoTr and HeH signatures with the log2 ratio of chromosome 1 the most highly discriminatory in this cohort. Using whole chromosome log2 ratios, HoTr and HeH ALL have distinct profiles. SNP array analysis highlighted at least 4 patients whose ploidy subgroups appeared incorrectly called by cytogenetics, which can affect risk stratification. Crucially, these data call into question the accepted modal chromosome numbers for HeH and HoTr in the near triploid phase and suggest this alone cannot be used to classify patients into these ploidy groups. All samples incorrectly classified as HeH ALL were from adults aged &amp;gt;40 years, suggesting this good risk subgroup is even rarer than previously thought in older adults. After re-classification, our cohort only contained 5/41 adults &amp;gt;40 years with HeH ALL, signifying that HoTr ALL is the commonest genetic ploidy group in older adults with ALL and must still be considered in cases with 50-60 chromosomes. Copy number analysis from SNP arrays is challenging in samples with marked ploidy shift and mixed cell populations. Importantly, a number of our samples had significant contaminating normal DNA and LOH could not be confirmed visually (figure (B)), underlying the need for additional factors to aid classification. Our analysis only takes into account log2 ratio of entire chromosomes, thus permitting a measure of the relative over and under-representation of specific chromosomes within the sample. This method accurately clusters patients even when LOH cannot be clearly visualized from B-allele frequency due to contaminating non-leukemic DNA and supports the development of a diagnostic classifier based on chromosomal log2 ratios. Disclosures Fielding: Amgen: Consultancy; Novartis: Consultancy; Pfizer: Consultancy; Incyte: Consultancy.

CLONAL HEMATOPOIESIS IN A CENTENARIAN COHORT

Mosaicism, the presence of two or more genotypically or karyotypically distinct populations of cells in a single individual, plays an important role in human disease. Mosaicism can result in mutations and/or chromosomal alterations such as loss, gain, or copy-number neutral loss of heterozygosity. Clonal mosaicism and its relationship to aging and cancer, has been previously studied, and earlier work suggests that clonal mosaicism tends to increase with age. The aim of our research is to use genotype data of centenarians to explore the relationship between extreme longevity and mosaic chromosomal alterations (mCAs). To this end, we analyzed genome-wide genotypes from blood-derived DNA of 338 individuals from the New England Centenarian Study. The participants in this dataset ranged from 45 to 112 years of age. For the detection of mCA events, we used MoChA (https://github.com/freeseek/mocha), a bcftools extension, that predicts mCAs based on B-allele frequency (BAF) and log2 intensity(R) ratio (LRR), and uses long-range phase information to increase sensitivity. Chromosomal alteration events, including whole chromosome events, were detected in 180 out of the 338 individuals. A total of 165 duplications, 97 deletions, and 9 copy-number neutral loss of heterozygosity were detected. Additionally, there were 42 events whose copy number state could not be determined with high confidence. 236 events out of the 313 were detected in individuals aged 100 and older. Our analysis of chromosomal alteration frequency by age indicates that, within centenarians, the proportion of individuals with mCAs significantly decreases with increased age (p < 0.05, correlation -0.73).

Genome-wide single nucleotide polymorphism array analysis unveils the origin of heterozygous androgenetic complete moles

Hydatidiform moles are abnormal pregnancies, which show trophoblastic hyperplasia. Most often, the nuclear genome in complete hydatidiform moles (CHMs) is composed of only paternal chromosomes. Diploid androgenetic conceptuses can be divided into homozygous and heterozygous CHMs. Heterozygous CHMs originate from two sperms or a diploid sperm, the distinction of which has not been established. Here, we assessed the origin of heterozygous CHMs using single nucleotide polymorphism (SNP) array. Thirteen heterozygous CHMs were analysed using B allele frequency (BAF) plotting to determine the centromeric zygosity status of all chromosomes. One case was from the duplication of a single sperm with an XY chromosome. In the other twelve cases, centromeric zygosity was random, i.e. mixed status. Thus, the twelve heterozygous CHMs were considered to be of dispermic origin but not diploid sperm origin. BAF plotting of SNP array can be a powerful tool to estimate the type of hydatidiform moles.

Abstract 2476: RECUR: Algorithm for directional allelic imbalance profiling and visualization from multi-sample data

Abstract Somatic chromosomal alterations play an important role in the development and progression of cancer. Allelic imbalance (AI) resulting from such changes (gain, loss, or copy-neutral loss-of-heterozygosity; cnLOH) is defined as a deviation from the 1:1 ratio of inherited parental haplotypes. Observed “B allele” frequencies (BAFs) at germline heterozygous loci, from SNP array or next-generation sequencing data, are used to detect AI. In addition, log R ratio or read-depth data, can be analyzed alone or jointly with BAFs to detect gains and losses. When AI is detected in multiple intra-individual samples, spanning similar loci, it is natural to assess whether these signals reflect the same underlying mutation. One way to do this would be to note if the observed AI differs in mutation type (gain, loss), an approach that falls short for events of the same type and subtle AI events that cannot be classified as gains, losses, or cnLOH. In such a case, or with two mutations of the same type, samples may differ in their maternal/paternal haplotype balance and consequently their alleles will shift in opposite directions. This phenomenon is indicative of a recurrent or independent mutation, or an error in chromosome segregation that generates two “mirrored” clones, one with a gain and the other with a loss. Recent studies have used such a directional AI analysis to yield important insights into cancer initiation and progression (Jakubek et al. Cancer Research 2016, Jamal-Hanjani et al. New England Journal of Medicine 2017, Turajlic et al. Cell 2018). We developed REpeat Chromosomal changes Uncovered by Reflection (RECUR) to explicitly test directionality of AI from multiple samples with overlapping AI segments through the comparative analysis of AI profiles derived from SNP array and next-generation sequencing data. The algorithm accepts genotype calls and BAFs from at least 2 samples derived from the same individual. For a predefined set of genomic regions with AI, RECUR compares BAF values among samples. In the presence of AI, the expected value of a BAF can shift in two possible directions, reflecting an increased or decreased abundance of the maternal haplotype, relative to the paternal. RECUR detects such genomic segments of opposite haplotypes in imbalance and plots BAF values for all samples, using a two-color scheme for intuitive visualization. It can help identify genomic regions under selective pressure for example recurrent deletions/gains in the same genomic loci and/or regions with generalized genomic instability. Integration of directional AI, copy number, and somatic mutation data can help build more accurate phylogenetic trees and further illuminate the timing and distribution of somatic chromosomal aberrations to offer insights into cancer initiation and progression. RECUR is available at scheet.org Citation Format: Yasminka A. Jakubek, F. Anthony San Lucas, Paul Scheet. RECUR: Algorithm for directional allelic imbalance profiling and visualization from multi-sample data [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 2476.

Monoallelic expression in melanoma

BackgroundMonoallelic expression (MAE) is a frequent genomic phenomenon in normal tissues, however its role in cancer is yet to be fully understood. MAE is defined as the expression of a gene that is restricted to one allele in the presence of a diploid heterozygous genome. Constitutive MAE occurs for imprinted genes, odorant receptors and random X inactivation. Several studies in normal tissues have showed MAE in approximately 5–20% of the cases. However, little information exists on the MAE rate in cancer. In this study we assessed the presence and rate of MAE in melanoma. The genetic basis of melanoma has been studied in depth over the past decades, leading to the identification of mutations/genetic alterations responsible for melanoma development.MethodsTo examine the role of MAE in melanoma we used 15 melanoma cell lines and compared their RNA-seq data with genotyping data obtained by the parental TIL (tumor infiltrating lymphocytes). Genotyping was performed using the Illumina HumanOmni1 beadchip. The RNA-seq library preparation and sequencing was performed using the Illumina TruSeq Stranded Total RNA Human Kit and subsequently sequenced using a HiSeq 2500 according to manufacturer’s guidelines. By comparing genotyping data with RNA-seq data, we identified SNPs in which DNA genotypes were heterozygous and corresponding RNA genotypes were homozygous. All homozygous DNA genotypes were removed prior to the analysis. To confirm the validity to detect MAE, we examined heterozygous DNA genotypes from X chromosome of female samples as well as for imprinted and olfactory receptor genes and confirmed MAE.ResultsMAE was detected in all 15 cell lines although to a different rate. When looking at the B-allele frequencies we found a preferential pattern of complete monoallelic expression rather then differential monoallelic expression across the 15 melanoma cell lines. As some samples showed high differences in the homozygous and heterozygous call rate, we looked at the single chromosomes and showed that MAE may be explained by underlying large copy number imbalances in some instances. Interestingly these regions included genes known to play a role in melanoma initiation and progression. Nevertheless, some chromosome regions showed MAE without CN imbalances suggesting that additional mechanisms (including epigenetic silencing) may explain MAE in melanoma.ConclusionThe biological implications of MAE are yet to be realized. Nevertheless, our findings suggest that MAE is a common phenomenon in melanoma cell lines. Further analyses are currently being undertaken to evaluate whether MAE is gene/pathway specific and to understand whether MAE can be employed by cancers to achieve a more aggressive phenotype.

Recommendations for the clinical interpretation and reporting of copy number gains using gene panel NGS analysis in routine diagnostics

Next-generation sequencing (NGS) panel analysis on DNA from formalin-fixed paraffin-embedded (FFPE) tissue is increasingly used to also identify actionable copy number gains (gene amplifications) in addition to sequence variants. While guidelines for the reporting of sequence variants are available, guidance with respect to reporting copy number gains from gene-panel NGS data is limited. Here, we report on Dutch consensus recommendations obtained in the context of the national Predictive Analysis for THerapy (PATH) project, which aims to optimize and harmonize routine diagnostics in molecular pathology. We briefly discuss two common approaches to detect gene copy number gains from NGS data, i.e., the relative coverage and B-allele frequencies. In addition, we provide recommendations for reporting gene copy gains for clinical purposes. In addition to general QC metrics associated with NGS in routine diagnostics, it is recommended to include clinically relevant quantitative parameters of copy number gains in the clinical report, such as (i) relative coverage and estimated copy numbers in neoplastic cells, (ii) statistical scores to show significance (e.g., z-scores), and (iii) the sensitivity of the assay and restrictions of NGS-based detection of copy number gains. Collectively, this information can guide clinical and analytical decisions such as the reliable detection of high-level gene amplifications and the requirement for additional in situ assays in case of borderline results or limited sensitivity.

Reprogramming Captures the Genetic and Tumorigenic Properties of Neurofibromatosis Type 1 Plexiform Neurofibromas.

SummaryNeurofibromatosis type 1 (NF1) is a tumor predisposition genetic disease caused by mutations in the NF1 tumor suppressor gene. Plexiform neurofibromas (PNFs) are benign Schwann cell (SC) tumors of the peripheral nerve sheath that develop through NF1 inactivation and can progress toward a malignant soft tissue sarcoma. There is a lack of non-perishable model systems to investigate PNF development. We reprogrammed PNF-derived NF1(−/−) cells, descendants from the tumor originating cell. These NF1(−/−)-induced pluripotent stem cells (iPSCs) captured the genomic status of PNFs and were able to differentiate toward neural crest stem cells and further to SCs. iPSC-derived NF1(−/−) SCs exhibited a continuous high proliferation rate, poor myelination ability, and a tendency to form 3D spheres that expressed the same markers as their PNF-derived primary SC counterparts. They represent a valuable model to study and treat PNFs. PNF-derived iPSC lines were banked for making them available.