Somatic Single Nucleotide Variants Research Articles

Comparison of Pathogenicity Prediction Tools on Somatic Variants

Genomic sequencing is increasingly used in managing patients with cancer. Interpretation of somatic variants and their pathogenicity is often complex. Pathogenicity prediction tools are commonly used as part of the expert interpretation of somatic variants, but most of these tools were initially developed for germline variants. Our aim was to benchmark their performance for somatic variants. A gold standardlist was assembled of 4319 somatic single-nucleotide variants, classified as oncogenic (n = 2996) or neutral (n = 1323), based on their presence in curated databases or on their allele frequency in the general population. These variants were annotated with the most commonly used prediction tools [Database for Nonsynonymous SNPs' Functional Predictions (dbNSFP) and Universal Mutation Database Predictor (UMD-Predictor)] and computed performance calculations. Stratification of the prediction tools based on Matthews correlation coefficient and area under the receiver operating characteristic curve allowed the identification of the top-performing ones, namely, Combined Annotation-Dependent Depletion (CADD), Eigen or Eigen Principal Components (Eigen-PC), Polymorphism Phenotyping version 2 (PolyPhen-2), Protein Variation Effect Analyzer (PROVEAN), UMD-Predictor, and Rare Exome Variant Ensemble Learner (REVEL). Interestingly, Sorting Intolerant From Tolerant (SIFT), which is a commonly used prediction tool for somatic variants, was ranked in the second performance category. Combining tools two by two only marginally improved performances, mainly because of the occurrence of discordant predictions.

Signatures of somatic mutations and gene expression from p16INK4A positive head and neck squamous cell carcinomas (HNSCC).

Human papilloma virus (HPV) causes a subset of head and neck squamous cell carcinomas (HNSCC) of the oropharynx. We combined targeted DNA- and genome-wide RNA-sequencing to identify genetic variants and gene expression signatures respectively from patients with HNSCC including oropharyngeal squamous cell carcinomas (OPSCC). DNA and RNA were purified from 35- formalin fixed and paraffin embedded (FFPE) HNSCC tumor samples. Immuno-histochemical evaluation of tumors was performed to determine the expression levels of p16INK4A and classified tumor samples either p16+ or p16-. Using ClearSeq Comprehensive Cancer panel, we examined the distribution of somatic mutations. Somatic single-nucleotide variants (SNV) were called using GATK-Mutect2 ("tumor-only" mode) approach. Using RNA-seq, we identified a catalog of 1,044 and 8 genes as significantly expressed between p16+ and p16-, respectively at FDR 0.05 (5%) and 0.1 (10%). The clinicopathological characteristics of the patients including anatomical site, smoking and survival were analyzed when comparing p16+ and p16- tumors. The majority of tumors (65%) were p16+. Population sequence variant databases, including gnomAD, ExAC, COSMIC and dbSNP, were used to identify the mutational landscape of somatic sequence variants within sequenced genes. Hierarchical clustering of The Cancer Genome Atlas (TCGA) samples based on HPV-status was observed using differentially expressed genes. Using RNA-seq in parallel with targeted DNA-seq, we identified mutational and gene expression signatures characteristic of p16+ and p16- HNSCC. Our gene signatures are consistent with previously published data including TCGA and support the need to further explore the biologic relevance of these alterations in HNSCC.

Sarek: A portable workflow for whole-genome sequencing analysis of germline and somatic variants.

Whole-genome sequencing (WGS) is a fundamental technology for research to advance precision medicine, but the limited availability of portable and user-friendly workflows for WGS analyses poses a major challenge for many research groups and hampers scientific progress. Here we present Sarek, an open-source workflow to detect germline variants and somatic mutations based on sequencing data from WGS, whole-exome sequencing (WES), or gene panels. Sarek features (i) easy installation, (ii) robust portability across different computer environments, (iii) comprehensive documentation, (iv) transparent and easy-to-read code, and (v) extensive quality metrics reporting. Sarek is implemented in the Nextflow workflow language and supports both Docker and Singularity containers as well as Conda environments, making it ideal for easy deployment on any POSIX-compatible computers and cloud compute environments. Sarek follows the GATK best-practice recommendations for read alignment and pre-processing, and includes a wide range of software for the identification and annotation of germline and somatic single-nucleotide variants, insertion and deletion variants, structural variants, tumour sample purity, and variations in ploidy and copy number. Sarek offers easy, efficient, and reproducible WGS analyses, and can readily be used both as a production workflow at sequencing facilities and as a powerful stand-alone tool for individual research groups. The Sarek source code, documentation and installation instructions are freely available at https://github.com/nf-core/sarek and at https://nf-co.re/sarek/.

Accurate quantification of copy-number aberrations and whole-genome duplications in multi-sample tumor sequencing data

Copy-number aberrations (CNAs) and whole-genome duplications (WGDs) are frequent somatic mutations in cancer but their quantification from DNA sequencing of bulk tumor samples is challenging. Standard methods for CNA inference analyze tumor samples individually; however, DNA sequencing of multiple samples from a cancer patient has recently become more common. We introduce HATCHet (Holistic Allele-specific Tumor Copy-number Heterogeneity), an algorithm that infers allele- and clone-specific CNAs and WGDs jointly across multiple tumor samples from the same patient. We show that HATCHet outperforms current state-of-the-art methods on multi-sample DNA sequencing data that we simulate using MASCoTE (Multiple Allele-specific Simulation of Copy-number Tumor Evolution). Applying HATCHet to 84 tumor samples from 14 prostate and pancreas cancer patients, we identify subclonal CNAs and WGDs that are more plausible than previously published analyses and more consistent with somatic single-nucleotide variants (SNVs) and small indels in the same samples.

Abstract LB-247: Sensitive detection of tumor mutations from blood and its application to immunotherapy prognosis

Abstract Liquid biopsy using cell-free DNA (cfDNA) is attractive for a wide range of clinical applications, including cancer detection, locating, and monitoring. However, developing these applications requires precise and sensitive calling of somatic single nucleotide variations (SNVs) from cfDNA sequencing data. To date, no SNV caller comprehensively addresses the unique challenges of cfDNA to provide reliable results. Here we present cfSNV, a revolutionary somatic SNV caller with five innovative techniques to overcome and exploit the unique properties of cfDNA: (1) a joint-genotype statistical model, to modeling the mixed nature of cfDNA and thus probabilistically deconvolute the mixture of tumor- and normal-derived reads; (2) hierarchical mutation profiling to detect clusters of mutations with different variant allele frequencies; (3) a data pre-processing step that exploits the overlapping read mates caused by short cfDNA fragments to improve data quality; (4) a new filtering procedure to remove misalignment errors that account for the non-random fragmentation pattern of cfDNA; and (5) a machine learning approach that incorporates the sequencing context to filter errors at the level of individual reads. These five techniques permit cfSNV to far outperform existing methods in sensitively and reliably detecting mutations in cfDNA, even with medium-coverage WES data. On both simulated data and real patient data, we demonstrate that cfSNV is superior to existing tools, especially for low-frequency somatic SNVs. On simulated data, without sacrificing precision, cfSNV showed 3.0- and 3.7-fold increase in sensitivity of all somatic SNVs, and specifically 11.1- and 138.5-fold increase in sensitivity of somatic SNVs with allele frequency < 1% comparing to MuTect and Strelka2 respectively. The superior performance of cfSNV has been further confirmed on real patient data from 18 metastatic breast cancer and prostate cancer patients. Besides comparison with existing tools, we also showed how the five novel techniques contribute to its performance. The applicability of cfSNV to WES data enables cfDNA to be used in a wide variety of clinical applications, and we present one example of such an application: a novel and effective immunotherapy response measure that we name truncal-bTMB. This measure exploits cfDNA's ability to provide comprehensive coverage of the mutation landscape and hence describe the clonal structure. We demonstrated this new marker allows a better selection of non-small-cell lung cancer patients for immunotherapy treatment. Citation Format: Shuo Li, Zorawar Noor, Weihua Zeng, Xiaohui Ni, Zuyang Yuan, Frank Alber, Wenyuan Li, Edward B. Garon, Xianghong Zhou, Wing Hung Wong, Vatche G. Agopian, Steven M. Dubinett M. Dubinett. Sensitive detection of tumor mutations from blood and its application to immunotherapy prognosis [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 LB-247.

Abstract 3535: Whole genome sequencing of single circulating tumor cells from localized high-risk prostate cancer patients: Laser microdissection and 3Dtelomere profile

Abstract Advances in the development of precision medicine for prostate cancer patients rely on accurate identification of the genomic features underlying a patient's tumor. Genomic analysis of circulating tumor cells (CTCs) could provide a unique and accessible representation of tumor diversity, however for the use of CTCs as a less-invasive sampling of prostate cancer and as biomarkers for patient stratification and selection of targeted therapy, complex platforms are necessary to ensure an efficient enrichment (isolation), detection (identification-imaging) and characterization strategies (molecular profiles). In this study, we combined a filtration-based CTC isolation technology with prostate cancer cell-specific antibodies to identify the prostate cancer CTCs. After identification, we performed the 3D telomere profiling prior to laser microdissection for whole genome sequencing of singles CTCs from 11 localized high-risk prostate cancer patient samples (36 CTCs in total). We identified unique and common somatic single nucleotide variants (SSNVs) and copy number alterations (CNAs) that can be used to predict high-risk lethal prostate cancer and treatment response in patients with clinically localized high- risk prostate cancers. The distribution of telomeres intensities show a range between 0 to 190.000 (a.u) and telomeres parameters were similar as described previously for high risk patients by our group. We analyzed 36 CTCs from 11 different patient samples and compared with normal lymphocytes from the same patient using whole genome sequencing (WGS). We identified 184 common mutated genes in all CTCs and two mutated genes with the same base pair (bp) mutation (PMS2 and EIF2AK4). We also identified 503 consensus mutations found in all patient but not in all CTCs and 1728 unique mutations found in all or any CTCs of only one patient, showing the heterogeneity that arises in single cells. The list of genes affected are all involved in potential pathways for tumor development such as immune system, signal transduction, homeostasis, gene expression, chromatin organization, DNA repair, cell cycle, programmed cell death, cell-cell communication and others. MCPH1, also known as BRIT1, is a key regulatory gene of the DNA damage response pathway and was mutated in all CTCs from prostate patients. MCPH1 deficiency promotes genomic instability and increases cancer susceptibility. The PMS2 gene is a member of a set of genes known as the mismatch repair (MMR) genes which promotes also genomic Instability. Those mutations can be closely linked with the genomic instability we found assessing the telomere profiles. The CDH17 gene is a member of the cadherin superfamily and in contrast to classic cadherins, such as E- and N-cadherin, LI-cadherin possess biological functions distinct from classic cadherins and reduced expression of LI-cadherin is closely associated with tumor progression and lymph node metastasis of human colorectal carcinoma. These mutations were also found in all CTCs. All this information is needed for individualized therapy and predict drug resistance, phenotypic transition which is heterogeneous from cell to cell from patient to patient. Citation Format: Aline Rangel Pozzo. Whole genome sequencing of single circulating tumor cells from localized high-risk prostate cancer patients: Laser microdissection and 3Dtelomere profile [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 3535.

Somatic structural variation targets neurodevelopmental genes and identifies SHANK2 as a tumor suppressor in neuroblastoma.

Neuroblastoma is a malignancy of the developing sympathetic nervous system that accounts for 12% of childhood cancer deaths. Like many childhood cancers, neuroblastoma shows a relative paucity of somatic single-nucleotide variants (SNVs) and small insertions and deletions (indels) compared to adult cancers. Here, we assessed the contribution of somatic structural variation (SV) in neuroblastoma using a combination of whole-genome sequencing (WGS) of tumor-normal pairs (n = 135) and single-nucleotide polymorphism (SNP) genotyping of primary tumors (n = 914). Our study design allowed for orthogonal validation and replication across platforms. SV frequency, type, and localization varied significantly among high-risk tumors. MYCN nonamplified high-risk tumors harbored an increased SV burden overall, including a significant excess of tandem duplication events across the genome. Genes disrupted by SV breakpoints were enriched in neuronal lineages and associated with phenotypes such as autism spectrum disorder (ASD). The postsynaptic adapter protein-coding gene, SHANK2, located on Chromosome 11q13, was disrupted by SVs in 14% of MYCN nonamplified high-risk tumors based on WGS and 10% in the SNP array cohort. Expression of SHANK2 was low across human-derived neuroblastoma cell lines and high-risk neuroblastoma tumors. Forced expression of SHANK2 in neuroblastoma cells resulted in significant growth inhibition (P = 2.6 × 10−2 to 3.4 × 10−5) and accelerated neuronal differentiation following treatment with all-trans retinoic acid (P = 3.1 × 10−13 to 2.4 × 10−30). These data further define the complex landscape of somatic structural variation in neuroblastoma and suggest that events leading to deregulation of neurodevelopmental processes, such as inactivation of SHANK2, are key mediators of tumorigenesis in this childhood cancer.

Landscape of G-quadruplex DNA structural regions in breast cancer.

Response and resistance to anticancer therapies vary due to intertumor and intratumor heterogeneity1. Here, we map differentially enriched G-quadruplex (G4) DNA structure-forming regions (∆G4Rs) in 22 breast cancer patient-derived tumor xenograft (PDTX) models. ∆G4Rs are associated with the promoters of highly amplified genes showing high expression, and with somatic single-nucleotide variants. Differences in ΔG4R landscapes reveal seven transcription factor programs across PDTXs. ∆G4R abundance and locations stratify PDTXs into at least three G4-based subtypes. ∆G4Rs in most PDTXs (14 of 22) were found to associate with more than one breast cancer subtype, which we also call an integrative cluster (IC)2. This suggests the frequent coexistence of multiple breast cancer states within a PDTX model, the majority of which display aggressive triple-negative IC10 gene activity. Short-term cultures of PDTX models with increased ∆G4R levels are more sensitive to small molecules targeting G4 DNA. Thus, G4 landscapes reveal additional IC-related intratumor heterogeneity in PDTX biopsies, improving breast cancer stratification and potentially identifying new treatment strategies.

Abstract PR06: Genomic distinctions between metastatic lower and upper tract urothelial carcinoma revealed through rapid autopsy

Abstract Introduction: Exceedingly little is known about the genomic difference between metastatic urothelial carcinoma (LTUC) and upper tract urothelial carcinoma (UTUC). We evaluated and compared genomic features of primary and metastatic UTUC and LTUC tumors in a cohort of patients with end-stage disease. Methods: We performed whole-exome sequencing on 37 tumor samples from 7 patients with metastatic UC collected between 2015-2017 via rapid autopsy, with matched primary and metastatic tumor samples. Inter- and intrapatient analyses of mutational burden, mutational signatures, predicted deleterious mutations (somatic single nucleotide variations [sSNV] and insertions-deletions), and somatic copy alterations (sCNV) were conducted. Results: We investigated 3 patients with UTUC (3 primary samples, 13 metastases) and 4 patients with LTUC (4 primary samples, 17 metastases). Most patients were men, nonsmokers, and received cisplatin-based therapy. We found that sSNV burden was higher in metastatic LTUC compared to UTUC. Moreover, the APOBEC mutational signature that has been described in localized bladder cancer was pervasive in metastatic LTUC and less so in UTUC. Despite a lower overall sSNV burden, UTUC displayed greater inter- and intraindividual genomic distances at the copy number level between primary and metastatic tumors than LTUC. Our data also indicate that metastatic UTUC lesions can arise from small clonal populations present in the primary cancer. Importantly, putative druggable mutations were found across our patient population with the majority shared across all metastases within a patient. Conclusions: In these patients, metastatic UTUC demonstrated a lower overall mutational burden but greater structural variability compared to LTUC. Our findings suggest that metastatic UTUC displays a greater spectrum of copy number divergence from LTUC, which may in part explain differences in aggressive clinical behavior. Importantly, we identified druggable lesions shared across metastatic samples, which demonstrate a level of targetable homogeneity within individual patients. This abstract is also being presented as Poster B09. Citation Format: Brian R. Winters, Navonil De Sarkar, Sonali Arora, Hamid Bolouri, Sujata Jana, Funda Vakar-Lopez, Heather H. Cheng, Michael T. Schweizer, Evan Y. Yu, Petros Grivas, John K. Lee, Lori Kollath, Sarah K. Holt, Lisa McFerrin, Gavin Ha, Peter S. Nelson, Robert B. Montgomery, Jonathan L. Wright, Hung-Ming Lam, Andrew C. Hsieh. Genomic distinctions between metastatic lower and upper tract urothelial carcinoma revealed through rapid autopsy [abstract]. In: Proceedings of the AACR Special Conference on Bladder Cancer: Transforming the Field; 2019 May 18-21; Denver, CO. Philadelphia (PA): AACR; Clin Cancer Res 2020;26(15_Suppl):Abstract nr PR06.

Longitudinal monitoring of circulating tumour DNA improves prognostication and relapse detection in gastroesophageal adenocarcinoma

BackgroundGastroesophageal adenocarcinoma (GOA) has poor clinical outcomes and lacks reliable blood markers. Here we present circulating tumour DNA (ctDNA) as an emerging biomarker.MethodsForty patients (17 palliative and 23 curative) were followed by serial plasma monitoring. Primary tumour DNA was analysed by targeted next-generation sequencing to identify somatic single-nucleotide variants (SNVs), and Nanostring nCounter® to detect copy number alterations (CNAs). Patient-specific SNVs and CNA amplifications (CNAamp) were analysed in plasma using digital droplet PCR and quantitative PCR, respectively.ResultsThirty-five patients (13 palliative, 22 curative) had ≥1 SNVs and/or CNAamp detected in primary tumour DNA suitable for tracking in plasma. Eighteen of 35 patients (nine palliative, nine curative) had ≥1 ctDNA-positive plasma sample. Detection of postoperative ctDNA predicted short RFS (190 vs 934 days, HR = 3.7, p = 0.028) and subsequent relapse (PPV for relapse 0.83). High ctDNA levels (>60.5 copies/ml) at diagnosis of metastatic disease predicted poor OS (90 vs 372 days, HR = 11.7 p < 0.001).ConclusionSensitive ctDNA detection allows disease monitoring and prediction of short OS in metastatic patients. Presence of ctDNA postoperatively predicts relapse and defines a ‘molecular relapse’ before overt clinical disease. This lead time defines a potential therapeutic window for additional anticancer therapy.

Efficient mutation screening for cervical cancers from circulating tumor DNA in blood

BackgroundEarly diagnosis and continuous monitoring are necessary for an efficient management of cervical cancers (CC). Liquid biopsy, such as detecting circulating tumor DNA (ctDNA) from blood, is a simple, non-invasive method for testing and monitoring cancer markers. However, tumor-specific alterations in ctDNA have not been extensively investigated or compared to other circulating biomarkers in the diagnosis and monitoring of the CC. Therfore, Next-generation sequencing (NGS) analysis with blood samples can be a new approach for highly accurate diagnosis and monitoring of the CC.MethodUsing a bioinformatics approach, we designed a panel of 24 genes associated with CC to detect and characterize patterns of somatic single-nucleotide variations, indels, and copy number variations. Our NGS CC panel covers most of the genes in The Cancer Genome Atlas (TCGA) as well as additional cancer driver and tumor suppressor genes. We profiled the variants in ctDNA from 24 CC patients who were being treated with systemic chemotherapy and local radiotherapy at the Jeonbuk National University Hospital, Korea.ResultEighteen out of 24 genes in our NGS CC panel had mutations across the 24 CC patients, including somatic alterations of mutated genes (ZFHX3–83%, KMT2C-79%, KMT2D-79%, NSD1–67%, ATM-38% and RNF213–27%). We demonstrated that the RNF213 mutation could be used potentially used as a monitoring marker for response to chemo- and radiotherapy.ConclusionWe developed our NGS CC panel and demostrated that our NGS panel can be useful for the diagnosis and monitoring of the CC, since the panel detected the common somatic variations in CC patients and we observed how these genetic variations change according to the treatment pattern of the patient.

Landscape of somatic single nucleotide variants and indels in colorectal cancer and impact on survival

Colorectal cancer (CRC) is a biologically heterogeneous disease. To characterize its mutational profile, we conduct targeted sequencing of 205 genes for 2,105 CRC cases with survival data. Our data shows several findings in addition to enhancing the existing knowledge of CRC. We identify PRKCI, SPZ1, MUTYH, MAP2K4, FETUB, and TGFBR2 as additional genes significantly mutated in CRC. We find that among hypermutated tumors, an increased mutation burden is associated with improved CRC-specific survival (HR = 0.42, 95% CI: 0.21–0.82). Mutations in TP53 are associated with poorer CRC-specific survival, which is most pronounced in cases carrying TP53 mutations with predicted 0% transcriptional activity (HR = 1.53, 95% CI: 1.21–1.94). Furthermore, we observe differences in mutational frequency of several genes and pathways by tumor location, stage, and sex. Overall, this large study provides deep insights into somatic mutations in CRC, and their potential relationships with survival and tumor features.

Sarek: A portable workflow for whole-genome sequencing analysis of germline and somatic variants

Whole-genome sequencing (WGS) is a fundamental technology for research to advance precision medicine, but the limited availability of portable and user-friendly workflows for WGS analyses poses a major challenge for many research groups and hampers scientific progress. Here we present Sarek, an open-source workflow to detect germline variants and somatic mutations based on sequencing data from WGS, whole-exome sequencing (WES), or gene panels. Sarek features (i) easy installation, (ii) robust portability across different computer environments, (iii) comprehensive documentation, (iv) transparent and easy-to-read code, and (v) extensive quality metrics reporting. Sarek is implemented in the Nextflow workflow language and supports both Docker and Singularity containers as well as Conda environments, making it ideal for easy deployment on any POSIX-compatible computers and cloud compute environments. Sarek follows the GATK best-practice recommendations for read alignment and pre-processing, and includes a wide range of software for the identification and annotation of germline and somatic single-nucleotide variants, insertion and deletion variants, structural variants, tumour sample purity, and variations in ploidy and copy number. Sarek offers easy, efficient, and reproducible WGS analyses, and can readily be used both as a production workflow at sequencing facilities and as a powerful stand-alone tool for individual research groups. The Sarek source code, documentation and installation instructions are freely available at https://github.com/nf-core/sarek and at https://nf-co.re/sarek/.

Rare Tumor-Normal Matched Whole Exome Sequencing Identifies Novel Genomic Pathogenic Germline and Somatic Aberrations.

Whole exome sequencing (WES) of matched tumor-normal pairs in rare tumors has the potential to identify genome-wide mutations and copy number alterations (CNAs). We evaluated 27 rare cancer patients with tumor-normal matching by WES and tumor-only next generation sequencing (NGS) as a comparator. Our goal was to: 1) identify known and novel variants and CNAs in rare cancers with comparison to common cancers; 2) examine differences between germline and somatic variants and how that functionally impacts rare tumors; 3) detect and characterize alleles in biologically relevant genes-pathways that may be of clinical importance but not represented in classical cancer genes. We identified 3343 germline single nucleotide variants (SNVs) and small indel variants—1670 in oncogenes and 1673 in tumor suppressor genes—generating an average of 124 germline variants/case. The number of somatic SNVs and small indels detected in all cases was 523:306 in oncogenes and 217 in tumor suppressor genes. Of the germline variants, six were identified to be pathogenic or likely pathogenic. In the 27 analyzed rare cancer cases, CNAs are variable depending on tumor type, germline pathogenic variants are more common. Cell fate pathway mutations (e.g., Hippo, Notch, Wnt) dominate pathogenesis and double hit (mutation + CNV) represent ~18% cases.

Transcriptomic silencing as a potential mechanism of treatment resistance.

Next-generation sequencing (NGS) has not revealed all the mechanisms underlying resistance to genomically matched drugs. Here, we performed in 1417 tumors whole-exome tumor (somatic)/normal (germline) NGS and whole-transcriptome sequencing, the latter focusing on a clinically oriented 50-gene panel in order to examine transcriptomic silencing of putative driver alterations. In this large-scale study, approximately 13% of the somatic single nucleotide variants (SNVs) were unexpectedly not expressed as RNA; 23% of patients had ≥1 nonexpressed SNV. SNV-bearing genes consistently transcribed were TP53, PIK3CA, and KRAS; those with lower transcription rates were ALK, CSF1R, ERBB4, FLT3, GNAS, HNF1A, KDR, PDGFRA, RET, and SMO. We also determined the frequency of tumor mutations being germline, rather than somatic, in these and an additional 462 tumors with tumor/normal exomes; 33.8% of germline SNVs within the gene panel were rare (not found after filtering through variant information domains) and at risk of being falsely reported as somatic. Both the frequency of silenced variant transcription and the risk of falsely identifying germline mutations as somatic/tumor related are important phenomena. Therefore, transcriptomics is a critical adjunct to genomics when interrogating patient tumors for actionable alterations, because, without expression of the target aberrations, there will likely be therapeutic resistance.

Genetic landscape and PD-L1 expression of Chinese patients with small cell lung cancer.

e21099 Background: Small cell lung cancer (SCLC) is a highly aggressive carcinoma of the lung. Whereas, precise treatment options for SCLC are limited. Genomic profiling would be essential to understand drug resistance related mechanism. So far, little is known about an in-depth molecular characterization for SCLC in Chinese patients. Here we described the mutational landscape and programmed cell death-1 (PD-L1) expression profile in Chinese patients with SCLC by next-generation sequencing (NGS) assay. Methods: Chinese patients with SCLC were included in this study. Genomic profiling of DNA was performed on formalin-fixed paraffin-embedded tumor samples and matched blood through a NGS with 381 cancer-related genes panel. PD-L1 expression status of tumor tissue was determined by immunohistochemistry. Results: In total, 115 patients with SCLC were included in the present study. We identified 2,948 mutations, spanning 434 genes, with TP53, RB1 and LRP1B being the most frequently mutated genes, occurring in 109(94.78%), 88(76.52%) and 48(41.74%) of SCLC patients, respectively. For somatic single nucleotide variant (SNV), TP53 (108/115, 93.91%), RB1 (82/115, 71.30%) and LRP1B (43/115, 37.39%) were frequently mutated, which exhibited the similar mutation frequencies with TCGA database. To be noted, 79 (68.70%) SCLC patients harbored both RB1 and TP53 mutations, which was comparable with TCGA data (84/110, 76.36%). Germline SNV spectrum varied significantly compare with somatic SNV. BLM, MSH2 and VEGFA were the most frequently germline mutated genes. In our dataset, the tumor mutation burden (TMB) of 108 patients, PD-L1 expression status of 95 patients and microsatellite stabilities/instabilities (MSS/MSI) status of 112 patients were also analyzed. The median TMB was 10.61/MB. The positive rate of PD-L1 expression was 12.63%. All patients were MSS. Conclusions: Our study revealed the genetic landscape and PD-L1 expression of SCLC. The data may provide the support on immunotherapy and targeted therapy research.

Tumor methylation patterns to measure tumor fraction in cell-free DNA.

3052 Background: Cell-free DNA (cfDNA) tumor fraction (TF), the proportion of tumor molecules in a cfDNA sample, is a direct measurement of signal for cfDNA cancer applications. The Circulating Cell-free Genome Atlas study (CCGA; NCT02889978) is a prospective, multi-center, observational, case-control study designed to support development of a methylation-based, multi-cancer detection test in which a classifier is trained to distinguish cancer from non-cancer. Here we leveraged CCGA data to examine the relationship between cfDNA containing tumor DNA methylation patterns, TF, and cancer classification performance. Methods: The CCGA classifier was trained on whole-genome bisulfite sequencing (WGBS) and targeted methylation (TM) sequencing data to detect cancer versus non-cancer. 822 samples had biopsy WGBS performed; of those, 231 also had cfDNA targeted methylation (TM) and cfDNA whole-genome sequencing (WGS). Biopsy WGBS identified somatic single nucleotide variants (SNV) and methylation variants (MV; defined as methylation patterns in sequenced DNA fragments observed commonly in biopsy but rarely [ &lt; 1/10,000] in the cfDNA of non-cancer controls [n = 898]). Observed tumor fragment counts (SNV in WGS; MV in TM), were modeled as a Poisson process with rate dependent on TF. TF and classifier limits of detection (LOD) were each assessed using Bayesian logistic regression. Results: Across biopsy samples, a median of 2,635 MV was distributed across the genome, with a median of 86.8% shared with ≥1 participant, and a median of 69.3% targeted by the TM assay. TF LOD from MV was 0.00050 (95% credible interval [CI]: 0.00041 - 0.00061); MV and SNV estimates were concordant (Spearman’s Rho: 0.820). MV TF estimates explained classifier performance (Spearman’s Rho: 0.856) and allowed determination of the classifier LOD (0.00082 [95% CI: 0.00057 - 0.00115]). Conclusions: These data demonstrate the existence of methylation patterns in tumor-derived cfDNA fragments that are rarely found in individuals without cancer; their abundance directly measured TF, and was a major factor influencing classification performance. Finally, the low classifier LOD (~0.1%) motivates further clinical development of a methylation-based assay for cancer detection. Clinical trial information: NCT02889978 .

Genomic characterization of circulating tumor DNA from Chinese advanced small-cell lung cancer to reveal potential therapeutic opportunities.

e21111 Background: Molecular profiling via next-generation sequencing (NGS) has been applied to select patients benefiting from targeted therapy or immunotherapy. Sequencing of blood-derived circulating tumor DNA (ctDNA) presents an alternative for advanced cancers given the challenge of obtaining tumor biopsies. We identified potentially actionable genomic alterations (GAs) in Chinese advanced small-cell lung cancer (SCLC) patients using ctDNA testing. Methods: Blood samples from 119 patients with advanced SCLC were sequenced via target deep sequencing covering 150 or 189 cancer-related genes and 100 microsatellite loci. Blood tumor mutation burden (bTMB), defined as the number of somatic single-nucleotide variants, short insertions and deletions (SNV/Indels) in examined coding region, was calculated in 93 patients. High bTMB was set to 10 that ranks top 25% in all SCLC patients. Results: The total number of GAs was 1156 in 127 genes, with an average of 9.7 GAs per sample ranging from 1 to 31. All patients harbored at least one GA and 107/119 patients had at least one GA with clinical significance. TP53 (82.4%) was the commonly altered gene followed by RB1 (57.1%), LRP1B (41.2%), FAT1 (25.2%), FAM135B (23.5%), PIK3CA (21%). GAs were detected frequently in cell cycle pathway (83.2%), PI3K/AKT/mTOR pathway (33.6%), RTK-RAS-MAPK pathway (29.4%), and DDR pathway (10.1%). Overall, 54 (45.4%) patients had alterations with therapeutic relevance, including 2 high blood microsatellite instability and 23 high bTMB that might benefit from immune checkpoint inhibitors. Actionable SNV/Indels were identified, including EGFR mutation (3), KRAS/HRAS mutation (5), DNA damage repair (DDR) pathway (4; including ATM, BRCA1, BRCA2), and PI3K/AKT/mTOR pathway (10; including PIK3CA, PTEN) that might benefit from EGFR tyrosine kinase inhibitors, RAS inhibitors, PARP inhibitors and mTOR inhibitors, respectively. We also found amplification of HER2 (3), FGFR1 (14), and MET (3) that might benefit from anti-HER2 antibodies, FGFR1 inhibitors and MET inhibitors, respectively. Conclusions: To our knowledge, this is the first large-scale analysis of blood-derived ctDNA in Chinese advanced SCLC. Potentially actionable GAs were detected in 45.4% patients. Deep sequencing of ctDNA could provide molecular profiles and might optimize treatment decision in advanced SCLC.

A novel highly frequent single‑nucleotide polymorphism site of cadherin 23 in clear cell renal cell carcinoma with sarcomatoid differentiation based on whole exome sequencing.

Clear cell renal cell carcinoma (CCRCC) with sarcomatoid differentiation (CCRCCS) displays invasive behavior, poor prognosis, and poor therapeutic response. The present study was aimed to gain new insights into the molecular mechanisms of sarcomatoid transformation, and identify new prognostic and therapeutic targets for CCRCCS. Whole exome sequencing was performed on matched carcinomatous and sarcomatoid elements from five specimens with CCRCCS. A non‑synonymous single‑nucleotide polymorphism (SNP) of cadherin23 (CDH23) was further studied through Sanger sequencing in expanded 40specimens with CCRCCS and 50specimens with CCRCC. Carcinomatous and sarcomatoid elements shared most somatic single‑nucleotide variants (SSNVs) as revealed through whole exome sequencing. Sarcomatoid element had higher overall SSNVs than carcinomatous element. A highly frequent mutation of CDH23 (rs3802711) was observed in CCRCCS that resulted in an alteration in the highly conserved calcium‑binding site in the three‑dimensional (3D) structure mediating the functions of cadherins. In the expanded 90 specimens, CDH23 SNP (rs3802711) was a highly frequent mutation in CCRCCS than that in all CCRCC samples and even high grade CCRCC. Cox multivariate analysis indicated that CDH23 (rs3802711) genotype was an independent prognostic factor affecting the overall survival of the cohort. CDH23 gene and protein were negatively or weakly expressed in most CCRCCS specimens with CDH23 mutation. The present study revealed, for the first time, that the CDH23 (rs3802711) was a highly genetic risk factor for CCRCCS. It was associated with the decreased expression of CDH23 protein, resulting in the absence of cadherin function of CDH23, indicating that the CDH23 mutation may be involved in the sarcomatoid transformation in CCRCCS. Collectively, a novel and specific SNP of CDH23 was identified in CCRCCS and a new candidate cadherin involved in EMT was revealed. Furthermore, a new prognostic evaluation factor and potential therapeutic target for CCRCCS was identified.

Sex disparities in head & neck cancer driver genes: An analysis of the TCGA dataset.

Survival in head and neck squamous cell carcinoma (HNSCC) has been associated with patient sex, typically with males experiencing poorer outcomes. It is unclear if this disparity is based in divergent tumor biology. We analyzed the TCGA HNSCC cohort to uncover disparities in the somatic single nucleotide variation (SNV), copy number alteration (CNA) and mRNA abundance profiles between males and females. Critically, we stratified our results by tumor HPV status to control for this significant confounder. SNV, CNA and mRNA abundance differences between males and females were compared separately for the HPV-positive (n=67) and negative (n=431) TCGA HNSCC cohorts. Overall survival outcomes were compared in males and females in both HPV-positive and HPV-negative subsets of patients. Females were found to have poorer overall survival than males (p=0.048), largely due to higher rates of HPV-positive disease among men. SNV analysis revealed that in HPV-positive disease, there were no differences by sex after accounting for the false discovery rate (FDR). In HPV-negative tumors, BRWD3 mutations occurred more frequently in the tumors of female patients compared to males after adjusting for the FDR (p=0.02). Further, HPV-negative BRWD3 mutant tumors were found to have significantly worse 5-year overall survival compared to wildtype on multivariate analysis (p=0.02). There were 88 heterozygous deletions and 14 amplifications that were differentially altered between male and female HPV-negative tumors and associated with expression changes. Pathway analysis of these genes revealed that tumors from males were enriched in five pathways including chemokine and phosphophatidylinositol signaling. Reanalysis of the TCGA HNSCC dataset stratified by sex revealed that males in this cohort had a significant survival advantage, due to a higher proportion of HPV-positive disease. Mutations in BRWD3 were more frequent in HPV-negative tumors of females and were associated with poorer overall survival. BRWD3 may represent a novel biomarker of patient outcomes, but will require additional validation.