Identification Of Somatic Mutations Research Articles

Genomic characterization of HBV-infected hepatocellular carcinoma patients using circulating tumor DNA.

575 Background: Hepatocellular carcinoma (HCC) is a leading cause of mortality, with Hepatitis B virus (HBV) infection as a dominant etiology. Surgery or ablation may be curative for early-stage HCC. Thus, effective detection strategies are needed. We investigated genomic aberrations in circulating tumor DNA (ctDNA) as a potential diagnostic marker of HCC in HBV-infected patients. Methods: We identified early stage (BCLC 0-A) HCC cases (n = 21) and cancer-free controls (n = 15) from a cohort of Asian patients with HBV, undergoing surveillance at Thomas Jefferson University Hospital between 2013-2017. Blood samples were collected. Circulating cell-free DNA was isolated from plasma and assayed by capture-based next-generation sequencing of a targeted panel of 23 genes implicated in HCC pathogenesis. Sequencing data analysis and somatic mutation identification were conducted using a computational pipeline. Using area under the curve (AUC) in receiver operating characteristic analysis, we evaluated gene alterations and clinical factors (age, gender, cirrhosis) in an exploratory early detection HCC model. Results: Mutant ARID1A, ATM, CDKN2A, CTNNB1, ERBB2, TP53 genes were increased in HCC cases relative to non-cancer patients (85.7% vs 53.3%, P = 0.058; 42.9% vs 6.7%, P = 0.025; 38.1% vs 6.7%, P = 0.051; 42.9% vs 0%, P = 0.005; 52.4% vs 13.3%, P = 0.016; 100% vs 66.7%, P = 0.008, respectively). HCC patients had higher prevalence of cirrhosis than controls (90.5% vs. 60%, P = 0.046). Using the 6 mutant genes alone, the AUC for discriminating HCC from non-cancer patients was 0.827 (95% confidence interval [CI]: 0.701-0.953), which was greater than the AUC for discriminating cirrhosis from non-cirrhosis (0.531). When the 6 mutant genes were combined with clinical factors, the AUC of the exploratory HCC detection model increased to 0.914 ( P= 0.045). Conclusions: We identified 6 genomic aberrations in ctDNA that were more prevalent in HCC patients compared with non-cancer patients. Combining these alterations with clinical factors may identify HCC in HBV-infected patients at an early stage. These findings warrant further validation in future studies.

Analysis of Molecular Pretreated Tumor Profiles as Predictive Biomarkers of Therapeutic Response and Survival Outcomes after Neoadjuvant Therapy for Rectal Cancer in Moroccan Population.

Pathologic features depending on tumor response to preoperative chemoradiotherapy are important to determine the outcomes in patients with rectal cancer. Evaluating the potential predictive roles of biomarker expression and their prognostic impact is a promising challenge. We reported here the immunohistochemical staining of a panel marker of mismatch repair protein (MMR), Ki67, HER-2, and p53. Additionally, identification of somatic mutations of KRAS, NRAS, and BRAF genes were performed by direct sequencing and pyrosequencing in pretreated biopsy tissues from 57 patients diagnosed for rectal cancer. Clinical features and pathological criteria for postneoadjuvant treatment surgical resection specimen's data were collected. Immunohistochemical expression and mutational status were correlated with therapeutic response, overall survival, and disease progression. The mean age of patients was 56 years. Seven (12.3%) out of 57 patients had a complete therapeutic response. Our analysis showed that when using complete therapeutic response (Dworak 4) and incomplete therapeutic response (Dworak 3, 2, and 1) as grouping factor, high p53 expression at the pretreatment biopsy was significantly associated to an incomplete response (p = 0.002). For 20 and 2 out of 57, KRAS and NRAS mutations were detected, respectively. The majority of these mutations affected codon 12. KRAS mutations detected at codon 146 (A146T, A146V) was associated with the appearance of recurrence and distant metastasis (p = 0.019). A high expression of HER-2 corresponding to score 3+ was observed in 3 pretreatment biopsy specimens. This class was significantly associated with a short relapse-free survival (p = 0.002). Furthermore, the high expression of Ki67 was moderately correlated with an older age (p = 0.016, r = 0.319). In addition, this shows that high p53 expression in the pretreatment biopsy was associated with an incomplete response in surgical resection specimens after neoadjuvant treatment, and a HER-2 score 3+ can be a predictive factor of distant metastasis and local recurrence. Larger, prospective, and more studies are needed.

Identification of a Gene Panel for Endometrioid Endometrial Cancer: a Possible Prognostic Value?

The incidence of endometrial cancer (EC) is increasing in developed countries. The most frequent is the endometrioid subtype with usually good prognosis; nevertheless, some cases escape this paradigm and may have recurrence. A recent study from The Cancer Genome Atlas suggested to implement the EC analysis by molecular profile for improving diagnosis, prognosis, and therapeutic treatment. The present preliminary study was performed on 15 G3 endometrioid endometrial cancers (G3 EEC) for the identification of somatic mutations in a panel of specific exons in selected genes as ARID1A, CTNNB1, KRAS, PIK3CA, POLE, PTEN, and TP53. The combined procedure, based on the Sanger sequencing and PCR-high-resolution melting analysis, allowed the identification of variations of the selected gene panel in most of patients (93%) of our cohort. The overall evaluation of mutational load exhibited that the most frequent mutated genes were PTEN (93%), followed by PIK3CA (47%) suggesting a deep involvement of PI3K pathway alteration in G3 EEC. Mutations in TP53 (27%), ARID1A (27%), POLE (13%), and at the lower level in KRAS and CTNNB1 (7%) were also observed (exclusively in FIGO III stage patients). The evaluation of the mutations of our proposed panel (ARID1A, CTNNB1, KRAS, PIK3CA, POLE, PTEN, TP53) is suitable to improve the characterization of G3 EEC and could suggest targetable pathways for development of personalized treatments.

Ensemble-Based Somatic Mutation Calling in Cancer Genomes.

Identification of somatic mutations in tumor tissue is challenged by both technical artifacts, diverse somatic mutational processes, and genetic heterogeneity in the tumors. Indeed, recent independent benchmark studies have revealed low concordance between different somatic mutation callers. Here, we describe Somatic Mutation calling method using a Random Forest (SMuRF), a portable ensemble method that combines the predictions and auxiliary features from individual mutation callers using supervised machine learning. SMuRF has improved prediction accuracy for both somatic point mutations (single nucleotide variants; SNVs) and small insertions/deletions (indels) in cancer genomes and exomes. Here, we describe the method and provide a tutorial on the installation and application of SMuRF.

Neoantigens in Hematological Malignancies-Ultimate Targets for Immunotherapy?

Neoantigens derive from non-synonymous somatic mutations in malignant cells. Recognition of neoantigens presented via human leukocyte antigen (HLA) molecules on the tumor cell surface by T cells holds promise to enable highly specific and effective anti-cancer immune responses and thus neoantigens provide an exceptionally attractive target for immunotherapy. While genome sequencing approaches already enable the reliable identification of somatic mutations in tumor samples, the identification of mutation-derived, naturally HLA-presented neoepitopes as targets for immunotherapy remains challenging, particularly in low mutational burden cancer entities, including hematological malignancies. Several approaches have been utilized to identify neoepitopes from primary tumor samples. Besides whole genome sequencing with subsequent in silico prediction of potential mutation-derived HLA ligands, mass spectrometry (MS) allows for the only unbiased identification of naturally presented mutation-derived HLA ligands. The feasibility of characterizing and targeting these novel antigens has recently been demonstrated in acute myeloid leukemia (AML). Several immunogenic, HLA-presented peptides derived from mutated Nucleophosmin 1 (NPM1) were identified, allowing for the generation of T-cell receptor-transduced NPM1mut-specific T cells with anti-leukemic activity in a xenograft mouse model. Neoantigen-specific T-cell responses have also been identified for peptides derived from mutated isocitrate dehydrogenase (IDHmut), and specific T-cell responses could be induced by IDHmut peptide vaccination. In this review, we give a comprehensive overview on known neoantigens in hematological malignancies, present possible prediction and discovery tools and discuss their role as targets for immunotherapy approaches.

Recurrent somatic mutations reveal new insights into consequences of mutagenic processes in cancer.

The sheer size of the human genome makes it improbable that identical somatic mutations at the exact same position are observed in multiple tumours solely by chance. The scarcity of cancer driver mutations also precludes positive selection as the sole explanation. Therefore, recurrent mutations may be highly informative of characteristics of mutational processes. To explore the potential, we use recurrence as a starting point to cluster >2,500 whole genomes of a pan-cancer cohort. We describe each genome with 13 recurrence-based and 29 general mutational features. Using principal component analysis we reduce the dimensionality and create independent features. We apply hierarchical clustering to the first 18 principal components followed by k-means clustering. We show that the resulting 16 clusters capture clinically relevant cancer phenotypes. High levels of recurrent substitutions separate the clusters that we link to UV-light exposure and deregulated activity of POLE from the one representing defective mismatch repair, which shows high levels of recurrent insertions/deletions. Recurrence of both mutation types characterizes cancer genomes with somatic hypermutation of immunoglobulin genes and the cluster of genomes exposed to gastric acid. Low levels of recurrence are observed for the cluster where tobacco-smoke exposure induces mutagenesis and the one linked to increased activity of cytidine deaminases. Notably, the majority of substitutions are recurrent in a single tumour type, while recurrent insertions/deletions point to shared processes between tumour types. Recurrence also reveals susceptible sequence motifs, including TT[C>A]TTT and AAC[T>G]T for the POLE and ‘gastric-acid exposure’ clusters, respectively. Moreover, we refine knowledge of mutagenesis, including increased C/G deletion levels in general for lung tumours and specifically in midsize homopolymer sequence contexts for microsatellite instable tumours. Our findings are an important step towards the development of a generic cancer diagnostic test for clinical practice based on whole-genome sequencing that could replace multiple diagnostics currently in use.

RNA Splicing Defects in Cancer-Linked Genes Indicate Mutation or Focal Gene Deletion and Are Associated with TKI Resistance in CML

Background Mutated cancer genes in patients (pts) with TKI failure and blast crisis (BC) CML have recently been described. RUNX1 mutations, namely single nucleotide variants (SNVs) and indels, were the most frequently detected besides BCR-ABL1 [reviewed in Branford, Kim Leuk 2019]. They were found in ~18% of pts, although splice variants were rarely described. RNA splicing events were associated with focal deletion of IKZF1 and RUNX1 in TKI resistant pts that were identified by copy number analysis and RNAseq [Branford Blood 2018]. Novel splicing associated with mutation of cancer genes is an unexplored area of study in resistance. RNA sequencing can assess the functional effect of splice site variants, which lead to splicing errors due to the use of alternative or cryptic splice sites and cause alterations to protein function. Aim We determined whether novel splicing can identify cancer genes with potential altered function. Methods RNAseq analysis was performed for 48 pts at diagnosis and 33 at BC using a protocol that preserved intron-retaining precursor RNA. Coverage of intron-exon borders was sufficient to detect intronic splice region variants. The STAR aligner was used to bioinformatically collate unannotated RNA splice junctions. 54 cancer genes were assessed and aberrant splice events were filtered based on the number of samples in which a splice junction occurred. Manual inspection of the splice junctions was performed using the Integrative Genomics Viewer. This approach identified previously verified aberrant splicing associated with IKZF1 and RUNX1 deletions. Results Ten previously undetected novel splice junctions were revealed in 9/33 pts (27%) in BC within key tumor suppressor genes CDKN2A/B (5), RB1 (1), ATM (1), and RUNX1 (3). The aberrant splicing pattern of CDKN2A and RB1 (Fig A/B) in 6 pts suggested large deletions, as previously described in our cohort with IKZF1 and RUNX1 deletions. Breakpoints associated with deletions ranging from 53 to 181 Kb were detected in the 5 pts with CDKN2A aberrant splicing. Similarly, a 90 Kb deletion of exons 18-27 of the RB1 gene led to the aberrant splicing. The pts transformed to lymphoid BC (median 5 months). 4 of these 6 pts were tested at diagnosis and the deletions were not detected, indicating they were gained at resistance. The aberrant splicing patterns of ATM and RUNX1 did not predict large deletions. These were related to somatic SNVs at canonical splice sites in ATM and in 2 of the pts with RUNX1 aberrant splicing. A splice acceptor site SNV in ATM resulted in skipping of exon 61 (Fig C) and protein truncation. This novel SNV has not been reported in any population or somatic variant database. Two pts in myeloid BC at 28 and 48 months after diagnosis had an identical somatic RUNX1 mutation at the canonical splice donor site of exon 5. The SNV was not detectable prior to imatinib treatment in both pts. The splice site SNV led to activation of a cryptic splice site within exon 5 in both pts (Fig D), which predicted premature termination. While this mutation is novel, an adjacent intronic SNV occurs in familial platelet disorder, leading to activation of the same cryptic splice site. The atypical RUNX1 splicing of the 3rd patient was associated with retention of 55 bp of intron 6 as a cryptic exon (Fig E), leading to protein truncation. A deep intronic SNV identified at lymphoid BC at 6 months of imatinib was detected near the cryptic exon by RNAseq and verified as somatic by DNA Sanger sequencing. This was predicted to activate cryptic RNA splicing elements and lead to intron sequence retention in a RUNX1 transcript. We sequenced the diagnosis sample using an RNA-based gene panel method under development that provides enhanced sensitivity of variant detection. The same pattern of atypical splicing was observed and the intronic SNV was present at low level. The RUNX1 mutation at diagnosis may have contributed to early BC. To our knowledge this is the first report of a RUNX1 truncating variant in CML involving a cryptic exon. Conclusion Enhanced bioinformatic analysis of RNAseq data has revealed a high proportion of pts with truncating mutations in cancer genes indicated by novel RNA splicing (27% pts in BC). Using RNA-based sequencing allows an evaluation of the potential functional effect of variants that are not apparent by DNA-based mutation analysis. We suggest that future studies include RNA sequencing to detect a broader spectrum of mutations associated with TKI resistance. Disclosures Shanmuganathan: Gilead: Other: Travel Support; Janssen: Other: Travel Support; Amgen: Other: Travel Support; Bristol-Myers Squibb: Honoraria, Other: Travel Support; Novartis: Honoraria, Other: Travel Support. Yeung:Novartis: Honoraria, Research Funding; BMS: Honoraria, Research Funding; Pfizer: Honoraria; Amgen: Honoraria. Scott:Celgene: Honoraria. Hughes:Novartis, Bristol-Myers Squibb, Celgene: Research Funding; Novartis, Bristol-Myers Squibb: Consultancy, Other: Travel. Branford:Cepheid: Consultancy, Honoraria; Qiagen: Consultancy, Honoraria; Novartis: Consultancy, Honoraria, Research Funding, Speakers Bureau; Bristol-Myers Squibb: Honoraria, Speakers Bureau.

Genomic Analysis of Hodgkin Lymphoma

The genetic analysis of the Hodgkin and Reed/Sternberg (HRS) tumor cells in Hodgkin lymphoma (HL) is very much hampered by the rarity of these cells, typically accounting for only about 1% of cells in the lymphoma tissue. Moreover, only very few cell lines were established from HL, partly with an uncertain origin. Thus, for the identification of somatic mutations in HRS cells, methods had to be established to isolate the rare HRS cells by microdissection from tissue sections or by cell sorting from cell suspensions. Initial studies were focussed on candidate gene approaches, often inspired by results from the prior analysis of HL cell lines. These early studies revealed numerous recurrent mutations in members of the NF-κB and JAK/STAT pathways, causing or at least contributing to the constitutive activation of these signaling pathways.1 The pathobiological relevance of the constitutive activation of NF-κB and JAK/STAT factors was validated by functional studies with HL cell lines. A first whole exome sequencing analysis of flow-sorted HRS cells was published by Reichel and colleagues.2 B2M was found to be inactivated by somatic mutations in 7/10 cases, and caused loss of major histocompatibility complex 1 expression. Although later studies with larger case series identified such mutations in only about 20-30% of cases,3,4 B2M inactivation is nevertheless an important factor for immune evasion of HRS cells and a frequently mutated gene in HL. A second exome sequencing study of HRS cells used microdissected tumor cells and revealed as a major novel finding frequent somatic mutations in the STAT6 gene (ca. 30% of cases).3 The genetic lesions in STAT6 are gain-of-function mutations. Overall nearly 90% of HL cases show genetic alterations in members of the JAK/STAT pathway, further demonstrating the major role of this pathway in HL pathogenesis. Our group is currently performing studies of microdissected HRS cells by whole genome sequencing, aiming to identify further genetic lesions in HRS cells beyond those affecting exons. An alternative attractive approach to uncover mutations in HRS cells is the genetic analysis of circulating DNA in plasma, because HRS cell-derived DNA fragments can be identified in most patients at the time of diagnosis. A targeted sequencing study of circulating tumor DNA showed the feasibility of this approach and validated, for example, the frequent occurrence of STAT6 mutations in HL. In rare instances, a HL can co-occur with another lymphoma in the same patient. Such composite lymphomas frequently show a common clonal origin of both lymphomas from a mature B cell.5 Composite lymphomas are therefore elegant models to study the multi-step transformation process in lymphomagenesis. We are currently performing a whole exome sequencing analysis of composite classical HL and B-cell Non-Hodgkin lymphomas, to reveal the pattern of early shared mutations and later distinct mutations. In each of the cases under investigations, such shared and distinct mutations were indeed identified. Küppers R, Engert A, Hansmann ML. Hodgkin lymphoma. J Clin Invest. 2012; 122: 3439. Reichel J, Chadburn A, Rubinstein PG, et al. Flow sorting and exome sequencing reveal the oncogenome of primary Hodgkin and Reed-Sternberg cells. Blood. 2015; 125: 1061. Tiacci E, Ladewig E, Schiavoni G, et al. Pervasive mutations of JAK-STAT pathway genes in classical Hodgkin lymphoma. Blood. 2018; 131: 2454. Spina V, Bruscaggin A, Cuccaro A, et al. Circulating tumor DNA reveals genetics, clonal evolution, and residual disease in classical Hodgkinlymphoma. Blood. 2018; 131: 2413. Küppers R, Dührsen U, Hansmann ML. Pathogenesis, diagnosis, and treatment of composite lymphomas. Lancet Oncol. 2014; 15: e435. Disclosures No relevant conflicts of interest to declare.

Recent Advances in Basic Research for Brain Arteriovenous Malformation.

Arteriovenous malformations (AVMs) are abnormal connections of vessels that shunt blood directly from arteries into veins. Rupture of brain AVMs (bAVMs) can cause life-threatening intracranial bleeding. Even though the majority of bAVM cases are sporadic without a family history, some cases are familial. Most of the familial cases of bAVMs are associated with a genetic disorder called hereditary hemorrhagic telangiectasia (HHT). The mechanism of bAVM formation is not fully understood. The most important advances in bAVM basic science research is the identification of somatic mutations of genes in RAS-MAPK pathways. However, the mechanisms by which mutations of these genes lead to AVM formation are largely unknown. In this review, we summarized the latest advance in bAVM studies and discussed some pathways that play important roles in bAVM pathogenesis. We also discussed the therapeutic implications of these pathways.

Identification of somatic mutations in single cell DNA-seq using a spatial model of allelic imbalance

Recent advances in single cell technology have enabled dissection of cellular heterogeneity in great detail. However, analysis of single cell DNA sequencing data remains challenging due to bias and artifacts that arise during DNA extraction and whole-genome amplification, including allelic imbalance and dropout. Here, we present a framework for statistical estimation of allele-specific amplification imbalance at any given position in single cell whole-genome sequencing data by utilizing the allele frequencies of heterozygous single nucleotide polymorphisms in the neighborhood. The resulting allelic imbalance profile is critical for determining whether the variant allele fraction of an observed mutation is consistent with the expected fraction for a true variant. This method, implemented in SCAN-SNV (Single Cell ANalysis of SNVs), substantially improves the identification of somatic variants in single cells. Our allele balance framework is broadly applicable to genotype analysis of any variant type in any data that might exhibit allelic imbalance.

Genomic data analysis workflows for tumors from patient-derived xenografts (PDXs): challenges and guidelines

BackgroundPatient-derived xenograft (PDX) models are in vivo models of human cancer that have been used for translational cancer research and therapy selection for individual patients. The Jackson Laboratory (JAX) PDX resource comprises 455 models originating from 34 different primary sites (as of 05/08/2019). The models undergo rigorous quality control and are genomically characterized to identify somatic mutations, copy number alterations, and transcriptional profiles. Bioinformatics workflows for analyzing genomic data obtained from human tumors engrafted in a mouse host (i.e., Patient-Derived Xenografts; PDXs) must address challenges such as discriminating between mouse and human sequence reads and accurately identifying somatic mutations and copy number alterations when paired non-tumor DNA from the patient is not available for comparison.ResultsWe report here data analysis workflows and guidelines that address these challenges and achieve reliable identification of somatic mutations, copy number alterations, and transcriptomic profiles of tumors from PDX models that lack genomic data from paired non-tumor tissue for comparison. Our workflows incorporate commonly used software and public databases but are tailored to address the specific challenges of PDX genomics data analysis through parameter tuning and customized data filters and result in improved accuracy for the detection of somatic alterations in PDX models. We also report a gene expression-based classifier that can identify EBV-transformed tumors. We validated our analytical approaches using data simulations and demonstrated the overall concordance of the genomic properties of xenograft tumors with data from primary human tumors in The Cancer Genome Atlas (TCGA).ConclusionsThe analysis workflows that we have developed to accurately predict somatic profiles of tumors from PDX models that lack normal tissue for comparison enable the identification of the key oncogenic genomic and expression signatures to support model selection and/or biomarker development in therapeutic studies. A reference implementation of our analysis recommendations is available at https://github.com/TheJacksonLaboratory/PDX-Analysis-Workflows.

Abstract 2474: Automated somatic variant classifier to reduce false positives identified by tumor normal variant callers

Abstract Accurate identification of somatic mutations is key to targeted cancer therapies. However, due to the complexity of next-generation sequencing, there are many variables that give rise to sequencing and alignment artifacts. Most sequencing workflows using tumor normal paired samples rely on the intersection or union of mutations by more than one somatic variant caller such as Mutect2, Strelka, VarScan2, Muse, and SomaticSniper. Yet, they still contain a number of false positive and false negative calls. Therefore, there is a need for a manual review of variants using Integrative Genomics Viewer (IGV) to incorporate information that is difficult to take into account in automated workflows. To alleviate the burden of manual inspection, we present an automated classification method to pre classify detected somatic variants into true or false classes for further manual review. Methods: We created a false positive classifier that utilizes automated IGV visualization of somatic variants. Our somatic workflow involves tumor normal DNA sequencing, BWAMEM alignment, deduplication of reads via Picard, somatic calling using two somatic callers, followed by the union of the detected variants, SnpEff annotation, and extracting nonsilent variants with variant allele fractions greater than 5 percent. We used the data for 1,413 nonsilent variants from a set of 10 tumor normal pairs of various cancer types. The variants were scored by cancer analysts using IGV. Initial false positive rate was 28 percent. We fine tuned Residual Deep Neural Network which utilizes weights from the network with the same architecture trained on ImageNet. Discriminative fine tuning was performed in two stages: first unfreezing the last fully connected layer only, and then unfreezing all the layers and training with differential learning rates. Results and Conclusion: Our method achieves 93 percent overall accuracy. The classifier greatly reduces the false positive rate for the set of variant calls from 28 percent down to 4 percent at the expense of calling 3 percent of true variants false. Previously, deep neural networks have been shown to yield the state of the art performance in multiple domains including image processing, speech, and text processing. In this work, we describe a way to fine tune Residual Neural Network trained on a large image data set to perform false positive variant detection in tumor-normal variant alignment snapshots from IGV. Our general approach that significantly reduces false positive rate of putative variants can be extended to any subset of somatic callers. Citation Format: Alena S. Harley, Corine K. Lau, Eve Shinbrot. Automated somatic variant classifier to reduce false positives identified by tumor normal variant callers [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 2474.

Abstract 4699: Enriching tumor purity using a unique flow-sorting approach to elucidate clonal evolution in matched samples of squamous cell carcinoma of the lung

Abstract Background:All carcinomas contain a variable proportion of benign stromal and immune cells, limiting the sensitivity in the identification of somatic genetic alterations. The average tumor purity of squamous cell carcinomas (SCC) of the lung is only around 50%. Low tumor content in tumor samples represents a challenge in studying intratumoral genomic heterogeneity in cancer research. Here, we applied flow-sorting to enrich for tumor cell nuclei to investigate the clonal relationship of primary SCC and matched metastases. Methods:Tumor tissues from 16 patients with primary SCC of the lung and matched metastases were used. We implemented a flow-sorting based approach to enrich for tumor nuclei as followed: after extraction of nuclei from snap-frozen or FFPE tissue, they were flow-sorted by DNA content (ploidy) and cytokeratin expression of the adherent cytoplasm, using a pan-cytokeratin (pCK) antibody. Isolated diploid and aneuploid pCK-positive tumor cell populations were subjected to whole exome sequencing (WES). DNA from diploid pCK-negative populations was used as germline control. Mutational profile and copy number aberrations (CNA) were determined to infer the clonal relationship and evolution between the primary tumors and their metastases. Results:Our flow-sorting based approach was able to enrich tumor content from 20%-50% to more than 80%-90% and to distinguish between aneuploid and diploid tumor cell populations from bulk tumor tissues. It enabled the identification of somatic mutations and CNA in both, aneuploid and diploid tumor cell populations, including potential subclonal driver mutations in ARID1A and KDM6A at low allelic frequencies. Shared and private mutations were observed in matched longitudinal tumor samples of individual patients and in synchronous distant metastases. Ploidy did not change significantly between primary tumors and relapse or distant metastases. Conclusion:We present a flow-sorting based method to enrich for tumor cell nuclei to facilitate genomic analysis, which also enabled separate analysis of aneuploid and diploid tumor populations. Our results show that the enrichment approach can be used to decode the clonal evolutionary relationship between primary tumors and their matched metastases, even in samples with low tumor cell content. Citation Format: Arthur Krause, Maria R. De Filippo, Thomas Lorber, Tanja Dietsche, Valeria Perrina, Christian Ruiz, Michael T. Barrett, Salvatore Piscuoglio, Charlotte K. Ng, Lukas Bubendorf. Enriching tumor purity using a unique flow-sorting approach to elucidate clonal evolution in matched samples of squamous cell carcinoma of the lung [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 4699.

PipeIT: A Singularity Container for Molecular Diagnostic Somatic Variant Calling on the Ion Torrent Next-Generation Sequencing Platform

The accurate identification of somatic mutations has become a pivotal component of tumor profiling and precision medicine. In molecular diagnostics laboratories, somatic mutation analyses on the Ion Torrent sequencing platform are typically performed on the Ion Reporter platform, which requires extensive manual review of the results and lacks optimized analysis workflows for custom targeted sequencing panels. Alternative solutions that involve custom bioinformatics pipelines involve the sequential execution of software tools with numerous parameters, leading to poor reproducibility and portability. We describe PipeIT, a stand-alone Singularity container of a somatic mutation calling and filtering pipeline for matched tumor-normal Ion Torrent sequencing data. PipeIT is able to identify pathogenic variants in BRAF, KRAS, PIK3CA, CTNNB1, TP53, and other cancer genes that the clinical-grade Oncomine workflow identified. In addition, PipeIT analysis of tumor-normal paired data generated on a custom targeted sequencing panel achieved 100% positive predictive value and 99% sensitivity compared with the 68% to 80% positive predictive value and 92% to 96% sensitivity using the default tumor-normal paired Ion Reporter workflow, substantially reducing the need for manual curation of the results. PipeIT can be rapidly deployed to and ensures reproducible results in any laboratory and can be executed with a single command with minimal input files from the users.

Targeted deep sequencing of urothelial bladder cancers and associated urinary DNA: a 23-gene panel with utility for non-invasive diagnosis and risk stratification.

ObjectivesTo develop a focused panel of somatic mutations (SMs) present in the majority of urothelial bladder cancers (UBCs), to investigate the diagnostic and prognostic utility of this panel, and to compare the identification of SMs in urinary cell‐pellet (cp)DNA and cell‐free (cf)DNA as part of the development of a non‐invasive clinical assay.Patients and MethodsA panel of SMs was validated by targeted deep‐sequencing of tumour DNA from 956 patients with UBC. In addition, amplicon and capture‐based targeted sequencing measured mutant allele frequencies (MAFs) of SMs in 314 urine cpDNAs and 153 urine cfDNAs. The association of SMs with grade, stage, and clinical outcomes was investigated by univariate and multivariate Cox models. Concordance between SMs detected in tumour tissue and cpDNA and cfDNA was assessed.ResultsThe panel comprised SMs in 23 genes: TERT (promoter), FGFR3,PIK3CA,TP53,ERCC2,RHOB,ERBB2,HRAS,RXRA,ELF3,CDKN1A,KRAS,KDM6A,AKT1,FBXW7,ERBB3,SF3B1,CTNNB1,BRAF, C3orf70,CREBBP,CDKN2A, and NRAS; 93.5–98.3% of UBCs of all grades and stages harboured ≥1 SM (mean: 2.5 SMs/tumour). RAS mutations were associated with better overall survival (P = 0.04). Mutations in RXRA, RHOB and TERT (promoter) were associated with shorter time to recurrence (P < 0.05). MAFs in urinary cfDNA and cpDNA were highly correlated; using a capture‐based approach, >94% of tumour SMs were detected in both cpDNA and cfDNA.Conclusions SMs are reliably detected in urinary cpDNA and cfDNA. The technical capability to identify very low MAFs is essential to reliably detect UBC, regardless of the use of cpDNA or cfDNA. This 23‐gene panel shows promise for the non‐invasive diagnosis and risk stratification of UBC.

PF196 IDENTICAL TWINS DO NOT DISPLAY INCREASED CONCORDANCE FOR CLONAL HEMATOPOIESIS

Background:Acquisition of leukemia‐associated somatic mutations by one or more haematopoietic stem cells (HSCs) is inevitable in healthy individuals by the age of 50–60 years1. However, the consequences of mutation acquisition are highly variable, even amongst those with identical mutations, and range from long‐term clinically silent clonal haematopoiesis (CH) to leukemic progression.Aims:To investigate the role of the inherited genome in determining CH emergence and behaviour, by studying CH concordance patterns in monozygotic (MZ) and dizygotic (DZ) twin pairs.Methods:154 individuals from the TwinsUK cohort were studied, comprising 52 MZ and 27 DZ twin pairs, aged 70–99 years2. Deep sequencing was performed on blood DNA, targeting 41 genes implicated in CH and myeloid malignancies (Agilent SureSelect, ELID 0735431). Somatic single nucleotide variants and small indels were called using the Shearwater algorithm (v.1.21.5) and verified using CaVEMan (v.1.11.2) and Pindel (v.2.2), and curation of variant oncogenicity was performed, as described previously3. Statistical analyses were performed in R (version 3.4.0). Fisher's Exact Test was used to assess twin concordance for CH. Null distributions of CH within the MZ and DZ groups were generated using random permutation (1000 iterations).Results:Using deep sequencing (mean 1650X) and sensitive variant‐calling, we identified CH (VAF≥0.5%) in 62% of individuals (95/154) (Figure 1A), with mutations in the epigenetic regulators DNMT3A and TET2 predominant (Figure 1B). The overall prevalence of CH was very similar among individuals belonging to the MZ and DZ groups (59% and 54% respectively; p = 0.70). We did not observe higher concordance for CH within MZ twin pairs as compared to DZ pairs (p = 0.59, Figure 1C). Furthermore, using random sample permutation to model the null distribution, we found no difference in the observed distribution of CH among either MZ or DZ twins as compared to that expected by chance (p = 1 for MZ; p = 0.86 for DZ; Figure 1C). Increased twin concordance was also not observed when separately considering CH with: (i) mutations in DNMT3A, (ii) mutations in TET2, and (iii) larger clones (VAF &gt; 2%).Despite the overall lack of concordance for CH, we identified two MZ twin pairs in which both twins harbored identical rare somatic nonsense mutations, KDM6A Q692X (NM_021140:c.C2074T) in one pair and DNMT3A R598X (NM_175629:c.C1792T) in the other.Finally, in 4 MZ twin pairs, serial blood samples taken after an interval of 4–5 years showed significant inter‐twin variability in clonal trajectories, even for clones harboring mutations in the same genes.Summary/Conclusion:We find no evidence for a strong heritable predisposition to age‐related CH. The variability in clonal dynamics over time between twins in MZ pairs supports an important role for the non‐inherited environment in determining clonal behaviour. The sharing of identical somatic mutations by twins in two MZ pairs, in view of the rarity of these particular mutations in CH and myeloid malignancies, suggests that mutation acquisition probably occurred during embryogenesis, either prior to twinning or more likely in an HSC whose progeny reached both twins through shared circulation in utero. While the sharing of somatic mutations has been demonstrated in other settings, including pediatric leukemia, this would be the first description of possible acquisition of adult‐type CH driver mutations during embryogenesis.image

MON-563 Quantitative Assessment Of BRAF Mutations In Thyroid Cancer Using Droplet Digital PCR.

Background:Identification of somatic mutations is crucial for guiding therapeutic decisions in patients with thyroid cancer. Droplet digital PCR (ddPCR) is a sensitive and particularly useful method of nucleic acid detection for quantification of gene mutations. This study aimed to determine the analytic and clinical validity of BRAF ddPCR mutational testing in thyroid cancer tissue. Material and Methods: Initially we examined a training cohort of 30 patients with thyroid cancer that had been previously tested for BRAF mutation with Sanger sequencing and included 15 BRAF positive and 15 BRAF negative subjects. A second group included 65 samples from 18 patients with thyroid cancer. Samples were obtained from central and invasive areas of tumors, normal thyroid tissue and lymph node metastasis. The DNA was extracted using Thermo Fisher Scientific King Fisher Duo Prime Purification System, and DNA concentration was measured by NanoDrop. Digital PCR was performed using a QuantStudio 3D Digital PCR platform. QuantStudio Software was used for relative and quantitative data analysis. Results: In the training set, BRAF mutations were detected in 15/15 BRAF-positive thyroid cancers and in 0/15 BRAF- negative tumors. Analysis of tissue samples from the second group of patients demonstrated detection of wild type BRAF alleles in normal thyroid as well as in thyroid cancer tissue. In contrast, BRAFV600 mutant alleles were detected only in thyroid cancer tissue samples (13/18 (72%) examined patients). In cancer samples, the ratios of mutant/total BRAF alleles ranged from 1.47% to 42.8% (average 24.6%). Quantification of BRAF mutant alleles did not reveal differences between male and female patients or patient age. The ratios of mutant/total BRAF did not correlate with tumor size, and were not different in central and invasive areas of the thyroid tumors. Metastases at the time of surgery were detected in 2/5 patients with BRAF-negative tumors, and in 6/13 patients with BRAF-positive tumors. The ratios of mutant/total BRAF alleles were higher in cancers presenting with metastases at the time of surgery (average 26.6%) compared to tumors without metastases (average 19.6%). However, these differences were not statistically significant. The quantifications of mutant BRAF alleles in metastatic lesions showed that the ratios of mutant/total BRAF were similar to corresponding primary tumors in 3 cases, and were decreased in 3 cases. Conclusion: Overall, droplet digital PCR allows specific, sensitive and rapid detection of BRAF mutations in thyroid tissue samples. Quantitative evaluation of BRAF mutations offers an opportunity for additional assessment of prognosis and potential response to treatment with tyrosine kinase inhibitors. Further research on implementation of ddPCR-based assays of thyroid tumors may provide important insights to the management of patients with thyroid cancer.

SAT-352 Comprehensive Genetic Analysis of Cortisol-Producing Adenomas

Background: Cortisol-producing adenomas (CPA) are the most common cause of adrenal Cushing’s syndrome. Next-generation sequencing (NGS) has recently facilitated the identification of somatic mutations that cause autonomous cortisol production by these tumors. The most commonly mutated gene in CPAs is PRKACA, resulting in hyper-activation of the protein kinase A (PKA) signaling pathway. Somatic mutations of GNAS, PRKAR1A, and CTNNB1 have also been identified in CPAs. However, direct mutation analysis of CPAs using formalin-fixed paraffin-embedded (FFPE) materials and immunohistochemistry (IHC)-guided targeted NGS has not been done before. Objective: To investigate the prevalence of somatic mutations in CPAs using FFPE tissue sections and targeted NGS. Methods: FFPE adrenal tumor tissue from 37 patients with Cushing’s syndrome who underwent adrenalectomy in our institution was used. IHC of HSD3B2 and CYP17A1 was performed. Aldosterone synthase (CYP11B2) IHC was also performed on tumors with low CYP17A1 expression and one from a patient with concomitant primary aldosteronism with Cushing’s syndrome. IHC-guided gDNA isolation was performed from 40 functional tumor samples [38 CPAs and two CPA-adjacent aldosterone-producing adenomas (APAs)]. Targeted NGS was implemented to identify somatic mutations involved in the tumors. The panel of targeted NGS included PKA pathway related genes (PRKACA, PRKAR1A, GNAS) and β-catenin (CTNNB1), as well as aldosterone-driver genes (KCNJ5, CACNA1D, ATP1A1, ATP2B3). Results: Somatic mutations were found in 63% (24/38) of CPAs. The two most commonly mutated genes were PRKACA (29%, n= 11/38) and CTNNB1 (24%, n= 9/38). GNAS mutations were found in 8% (3/38) of the CPAs and a PRKAR1A mutation was found in one CPA (3%). Of the two CPA-adjacent APAs, one had a KCNJ5 mutation, while the other had a CACNA1D mutation. Clinically, the autonomous cortisol production resulting from these CPAs was dichotomized into either overt or subclinical Cushing’s syndrome. Intriguingly, the majority of PRKACA mutations were found in the overt Cushing’s syndrome group (62%, n= 8/13) compared to only 1/23 (4%) of the subclinical Cushing’s syndrome cohort. The overt Cushing’s syndrome group also contained the single PRKAR1A mutation (8%, n=1/13). Furthermore, CTNNB1 (39%, n= 9/23) and GNAS (13%, n= 3/23) mutations were exclusively observed in subclinical Cushing’s syndrome patients. Conclusion: Targeted NGS on FFPE CPA tissue identified somatic mutations in 63% of tumors. CPAs causing overt Cushing’s syndrome appear to have a distinct mutation profile compared to the tumors observed in subclinical Cushing’s syndrome.

The role of somatic mutational events in the pathogenesis of epilepsy.

There has been rapid progress in defining novel causative gene variants responsible for a large spectrum of human epilepsy syndromes and subtypes. Of particular interest is the discovery that somatic mutations, for example, noninherited mutations occurring in neuroglial progenitor cells during embryonic brain development, are highly linked to malformations of cortical development (MCD) such as focal cortical dysplasia (FCD) type II and hemimegalencephaly. Somatic gene variants have been identified in genes encoding regulatory proteins within the mechanistic target of rapamycin (mTOR) signaling cascade and have thus comprised the group classified as mTORopathies. FCD II and hemimegalencephaly often result from mutations in identical genes suggesting that these are spectrum disorders. An exciting recent development has been the identification of somatic mutations causing both FCD Ia and nonlesional neocortical epilepsy. Defining somatic gene mutations in brain tissue specimens has shed new light on how MCD form and the mechanisms of epileptogenesis associated with MCD. Trials of mTOR inhibitors in tuberous sclerosis complex have demonstrated that inhibition of mTOR activation in mTORopathies can reduce seizure frequency. New somatic mutations found for a variety of epilepsy syndromes may provide new targets for clinical therapeutics.

Conbase: a software for unsupervised discovery of clonal somatic mutations in single cells through read phasing

Accurate variant calling and genotyping represent major limiting factors for downstream applications of single-cell genomics. Here, we report Conbase for the identification of somatic mutations in single-cell DNA sequencing data. Conbase leverages phased read data from multiple samples in a dataset to achieve increased confidence in somatic variant calls and genotype predictions. Comparing the performance of Conbase to three other methods, we find that Conbase performs best in terms of false discovery rate and specificity and provides superior robustness on simulated data, in vitro expanded fibroblasts and clonal lymphocyte populations isolated directly from a healthy human donor.