COPS: A Sensitive and Accurate Tool for Detecting Somatic Copy Number Alterations Using Short-Read Sequence Data from Paired Samples

BackgroundSomatic copy number alterations (SCNAs) are an important class of genomic alteration in cancer. They are frequently observed in cancer samples, with studies showing that, on average, SCNAs affect 34% of a cancer cell’s genome. Furthermore, SCNAs have been shown to be major drivers of tumour development and have been associated with response to therapy and prognosis. Large-scale cancer genome studies suggest that tumours are driven by somatic copy number alterations (SCNAs) or single-nucleotide variants (SNVs). Despite the frequency of SCNAs and their clinical relevance, the use of genomics assays in the clinic is biased towards targeted gene panels, which identify SNVs but provide limited scope to detect SCNAs throughout the genome. There is a need for a comparably low-cost and simple method for high-resolution SCNA profiling.ResultsWe present conliga, a fully probabilistic method that infers SCNA profiles from a low-cost, simple, and clinically-relevant assay (FAST-SeqS). When applied to 11 high-purity oesophageal adenocarcinoma samples, we obtain good agreement (Spearman’s rank correlation coefficient, rs=0.94) between conliga’s inferred SCNA profiles using FAST-SeqS data (approximately £14 per sample) and those inferred by ASCAT using high-coverage WGS (gold-standard). We find that conliga outperforms CNVkit (rs=0.89), also applied to FAST-SeqS data, and is comparable to QDNAseq (rs=0.96) applied to low-coverage WGS, which is approximately four-fold more expensive, more laborious and less clinically-relevant. By performing an in silico dilution series experiment, we find that conliga is particularly suited to detecting SCNAs in low tumour purity samples. At two million reads per sample, conliga is able to detect SCNAs in all nine samples at 3% tumour purity and as low as 0.5% purity in one sample. Crucially, we show that conliga’s hidden state information can be used to decide when a sample is abnormal or normal, whereas CNVkit and QDNAseq cannot provide this critical information.ConclusionsWe show that conliga provides high-resolution SCNA profiles using a convenient, low-cost assay. We believe conliga makes FAST-SeqS a more clinically valuable assay as well as a useful research tool, enabling inexpensive and fast copy number profiling of pre-malignant and cancer samples.

Introduction: Retinoblastoma (Rb) is the most common childhood intraocular cancer. Tissue biopsy of Rb can cause tumor spread, so it is contraindicated. We demonstrated that aqueous humor (AH), an ocular fluid, is a high-yield liquid biopsy enabling in vivo detection of tumor-derived cell-free DNA (cfDNA) thus overcoming the contraindication of biopsy. Somatic genomic alterations, including both somatic copy number alterations (SCNAs) and single nucleotide variations (SNVs) on RB1 gene, have been able to be identified in the same clinical samples but with two separate sequencing runs. In this study, we first developed a single targeted sequencing method to identify both SCNAs and RB1 SNVs. With this method, we further investigated the degree of genomic concordance between paired tumor and AH samples from the same Rb eye. Materials and Methods: 11 paired AH and Rb tumor samples were included in the study. cfDNA of AH and tumor DNA of enucleated Rb eyes were isolated with QIAgen commercial kits. DNAs were constructed into whole genome libraries followed by hybridization target enrichment (Agilent SureSelect). The enrichment assay covers the whole length of RB1 and MycN genes, the all-exon regions of BCOR and CREBBP genes, and a whole genome CNV backbone. Libraries were submitted to Illumina HiSeq 4000 platform for fastq data generation with 2 × 150bp mode. The bioinformatics pipeline was optimized to generate SCNA profiles from targeted sequencing reads, along with SNV calling. Results: For SCNA profiles, 11/11 AH samples (100%) and 8/11 tumor samples (72.72%) have positive RB-SCNA signatures. Strong concordances were observed between AH and tumor SCNA profiles (median = 90.1%) with targeted sequencing reads. In total, 9 disease-driving RB1 SNVs were identified in 6 patients (54.5%). 7/9 (77.8%) of the variants were shared between AH and tumor samples, while the AH and tumor each contained one unique SNV. In all SNVs, the AH displayed a higher allele frequency. Notably, 4/11 samples have focal RB1 gene deletion detected with SCNA profiling, which may explain the difficulties of RB1 SNV detection in some samples. Further, one case was driven by a MYCN gene amplification with no RB1 alterations. Conclusions: This study presented highlights the utility of a single method to call both SVNs and SCNAs in a single clinical sample, with enriched tumor information detected in AH compared with tumor. This study further strengthens the utility of AH as a liquid biopsy platform for Rb eyes. Citation Format: Liya Xu, Mike J. Schmidt, Rishvanth K. Prakabar, Peter Kuhn, James Hicks, Jesse Berry. Simultaneous somatic copy number alterations and single nucleotide variants detection in paired aqueous humor and tumors from retinoblastoma eyes. [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 3553.

Retinoblastoma is a pediatric retinal cancer that initiates in response to biallelic RB1 loss or MYCN amplification in a cone precursor cell of origin. After initial emergence, RB1-/- retinoblastomas progress to more aggressive forms by accumulation of single nucleotide variants (SNVs) and highly recurrent somatic copy number alterations including 1q+, 2p+, 6p+ and 16q- (RB SCNAs), resulting in heterogeneous mixtures of subclonal cell populations. SCNAs are enriched in highly evolved and aggressive tumor subtypes and show prognostic value in retinoblastoma liquid biopsies. However, the transcriptomic effects of retinoblastoma SCNAs are poorly understood. Single cell methods may enable comparison of tumor subclones within emerging retinoblastoma tumors and thereby provide insight into tumor progression. We retrieved single cell RNA sequencing data for 25 retinoblastoma tumors and inferred SCNAs and subclone phylogenies from scRNAseq information using a recently published tool, Numbat. We identified tumors with clonal variation in RB SCNAs and excluded samples with poor transcriptome quality or excessive additional SCNAs. We proceeded with analysis of 11 tumors with subclonal heterogeneity for an SCNA of interest, including 10 with 1q+, eight with 2p+, four with 6p+, and six with 16q-. After removal of nontumor cells, we defined cell clusters, cluster marker genes, and cell cycle phase gene signatures, and we compared cell state distributions for subclones with an acquired SCNA relative to their immediate antecedents. These analyses revealed recurrently discriminated transcriptomic clusters corresponding to six discrete cell cycle states (post-mitotic G1, G1, G1/S, S, S/G2, G2/M) and variable cell stress states, including a cluster with hypoxia and heat shock related marker gene expression in all samples. In each tumor, SCNA-defined tumor subclones had a distinct cell state distribution. Tumor subclones with acquired 1q+ were enriched in G2 states and depleted in G1 states. Subclones with 2p+ were enriched in G2 states. Subclones with 6p+ were enriched in S phase states. Subclones with 16q- were diminished in post-mitotic cell states. Tumor clones with 1q+ and 16q- were most strongly enriched for G2 phase cells. Such 1q+/16q- tumor cells were significantly differentially distributed in three tumor replicates. Tumor clones with other RB SCNAs were enriched over diploid clones in proliferating G2 cells without SCNA specific effects. To identify candidate drivers of SCNA-specific transcriptomic effects we measured RB SCNA clonal variation in gene expression within and across transcriptomic states. We identified recurrently differentially expressed in-segment genes in 1q+, 2p+, 6p+, and 16q-, as well as out-of-segment genes. Finally, we propose molecular mechanisms underlying SCNA recurrence that may enable tumor evolution in retinoblastoma. Citation Format: Kevin Stachelek, David E. Cobrinik. Transcriptomic effects of retinoblastoma progression-related somatic copy number alteration (SCNA) [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 6941.

Acquired copy number alterations of miRNA genes in acute myeloid leukemia are uncommon

7507 Background: Somatic copy number alterations (SCNAs) are common and clinically important genomic events in lymphomas. For example, MYC and BCL2 amplifications are associated with adverse outcomes (Quesada, ASH 2016), while PD-L1 ( CD274) amplifications are associated with improved response to checkpoint inhibitors (Ansell, NEJM 2015). However, noninvasive detection of these events from circulating tumor DNA (ctDNA) remains difficult. Using CAPP-Seq, a targeted high-throughput sequencing platform, we developed a method to profile both focal and broad SCNAs from plasma. Methods: We profiled plasmas from a cohort of 75 pretreatment diffuse large B-cell lymphoma patients and 48 healthy controls. Focal SCNAs were evaluated at ultra-high depths (~10,000x), allowing for detection of lesions at ~1% ctDNA fraction. Thresholds were tuned to allow a false positive rate of 1%, which was empirically validated in an independent healthy cohort (n = 15), yielding a panel-wide false discovery rate of ~2.3% (0% in our genes of interest). Sequencing reads outside the targeted regions were separately pooled and analyzed to evaluate arm and chromosome level SCNAs. Results: We detected SCNAs in clinically relevant genes at the frequencies reported in literature, including amplifications in MYC (8.0%), BCL2 (24.0%), and BCL6 (14.7%) and deletions in TP53 (13.3%) and CDKN2A (9.3%). Remarkably, 26.7% of the cohort demonstrated amplification of both PD-L1 and PD-L2 ( PDCD1LG2). Furthermore, we discovered amplifications in PD-L2, but not PD-L1, in 13.3% of our patients. Interestingly, PD-L1 amplifications were more common in patients with relapsed lymphoma than in those with treatment-naïve disease (43.5% vs 19.2%, p = 0.02). Most PD-L1 amplifications were focal (65%) while the remainder typically involved > 80% of Chr9p. Corresponding tissue profiling data is in progress and will also be presented. Conclusions: Noninvasive sampling of lymphoma ctDNA enables detection of both focal and broad SCNAs, including amplifications of MYC, BCL2, and PD-L1. The ability to noninvasively profile copy number altered regions allows for biopsy-free discovery of clinically significant structural alterations in lymphoma patients.

INTRODUCTION Meningiomas are the most prevalent primary intracranial tumors in adults, with clinical management traditionally guided by the World Health Organization (WHO) grading system. However, discrepancies between histological grade and clinical behavior highlight the limitations of this system. Somatic copy number alterations (SCNAs) have been implicated in meningioma pathogenesis, correlating with tumor aggressiveness and recurrence risk. Their integration into prognostic models may enhance outcomes. This study investigates the influence of SCNAs on meningioma recurrence, focusing on their patterns of mutual exclusivity and co-occurrence. METHODS We analyzed 334 primary meningiomas, noting 23 recurrences (6.9%). Clinical data, including age, sex, WHO grade, and tumor characteristics, were collected. SCNAs and mutations were derived from whole-exome sequencing of tumor and matched blood samples. We employed univariate and multivariate Cox proportional hazards regression analyses to identify SCNAs associated with recurrence, fitting the regression model with the cumulative number of SCNAs as a factor covariate. The Kaplan-Meier estimator was utilized for visualizing survival curves. RESULTS Five SCNAs were significantly associated with recurrence risk (adjusted P < 0.05): 10qLOSS, 11pLOSS, 2pLOSS, 14qLOSS, and 18qLOSS. Each SCNA independently increased recurrence risk; a single SCNA tripled this risk, while two co-occurring SCNAs increased it more than ninefold (P = 0.00003). Notably, meningiomas with four co-occurring SCNAs exhibited a greater than 22-fold increase in recurrence risk. Importantly, all identified SCNAs contributed to chromosomal instability, suggesting a synergistic effect that enhances tumor recurrence potential. CONCLUSION The accumulation and specific combinations of these five SCNAs significantly enhance the likelihood of meningioma recurrence. Although chr1pLOSS did not independently predict recurrence, it promotes chromosomal instability that facilitates the accumulation of these risk SCNAs. Our findings underscore the potential of SCNAs in predicting meningioma recurrence across all grades, contributing to improved patient management strategies.

Background: Characterization of focal somatic copy number alterations (SCNAs) has led to the identification of many cancer genes, yet similar investigations of arm-level SCNAs remain challenging. The identity of driver genes within these broad SCNAs remains a critical unanswered question in cancer genetics. One of the most frequent arm-level SCNAs is 9p loss, which contains the tumor suppressor gene (TSG) CDKN2A. It is also believed that other TSGs exist on 9p, though their identity has yet to be revealed. Methods: We analyzed every arm-level SCNA in 28 cancer types from The Cancer Genome Atlas (TCGA) to clarify the relative impact of 9p loss across cancer. We also performed a multi-tiered genomic dissection of chromosome 9p in 540 patients from 3 independent lower grade glioma (LGG) datasets (TCGA, REMBRANDT, MSKCC) to pinpoint genetic loci that are tied to tumor aggressiveness and poor survival. Focal and arm-level SCNAs were determined by GISTIC2.0. As per recently proposed criteria, 3 LGG subtypes were clustered by IDH mutation and 1p/19q deletion status. Survival analyses were performed using log-rank tests or Cox regression. Results: We found that chromosome 9p loss is one of the most frequent and prognostic arm-level events across 28 TCGA cancer types. Of these, the strongest 9p survival association was found in LGG. We performed a large-scale associations test of 376 important clinical and molecular variables and revealed that 9p loss was only associated with 6q or 9q loss, and 9p loss alone was sufficient to predict poor prognosis. On subtype-specific analysis, 9p loss predicted worse overall survival (OS) in both IDH mutant LGG subtypes but not IDH wild-type (IDHwt). To identify underlying drivers on 9p, we identified 87 genes most frequently targeted by 9p loss. Additional genetic events were rare except for homozygous deletion (HD) at 9p21.3, which contains CDKN2A. In contrast, mRNA/miRNA expression at all gene loci was much more variable and poorly correlated to copy number status. Therefore, pan-LGG and subtype-specific gene expression analyses were used to identify several drivers of tumor aggressiveness, notably KLHL9, MTAP, PLAA, and PTPRD. Although CDKN2A HD was linked to worse OS in a pan-LGG analysis, this event significantly co-occurred with the LGG IDHwt subtype, a group with GBM-like survival outcomes. Further, CDKN2A copy number status and expression did not predict worse OS in any subtype. Discussion: We characterize the nature of 9p loss in LGG, pinpoint genes involved in worse survival, and redefine the role of the tumor suppressor CDKN2A. These results provide new critical insight into long-standing questions about the nature of chromosome 9p loss and establish a framework for examining other arm-level SCNAs in cancer. Citation Format: David M. Roy, Logan A. Walsh, Alexis Desrichard, Jianjiong Gao, Promita Bose, Jason T. Huse, William Lee, Timothy A. Chan. Multidimensional genomic dissection of chromosome 9p in glioma. [abstract]. In: Proceedings of the 106th Annual Meeting of the American Association for Cancer Research; 2015 Apr 18-22; Philadelphia, PA. Philadelphia (PA): AACR; Cancer Res 2015;75(15 Suppl):Abstract nr LB-169. doi:10.1158/1538-7445.AM2015-LB-169

Somatic copy number alterations are associated with EGFR amplification and shortened survival in patients with primary glioblastoma

Putative Drivers of Aggressiveness in TCEB1-mutant Renal Cell Carcinoma: An Emerging Entity with Variable Clinical Course

Molecular profiling using low coverage whole genome sequencing of cell free DNA (cfDNA) represents a non-targeted approach to identify multiple somatic copy number alterations (SCNA) across different lung cancer subtypes. We aim to establish that SCNA can be detected in cfDNA of lung cancer cases.Standard protocols were followed to process matched cfDNA, formalin-fixed paraffin embedded (FFPE) tumour and lymphocyte DNA. Copy number profiles for cfDNA or FFPE DNA were normalised to profiles from matched lymphocyte DNA with the software CNAnorm. Technical sensitivity was determined by spiking different proportions of FFPE tumour DNA into cfDNA from controls.The median genome coverage was 0.26X (range 0.05X-0.97X). For two advanced stage cases there was a positive correlation between copy number ratio profiles of matched cfDNA and FFPE DNA (r = 0.62, p < 0.0001 and r = 0.75, p < 0.0001). There was no correlation for four advanced and two early stage cases. There were low magnitude copy number aberrations detected in high-risk controls (N = 5). We detected spiked FFPE DNA derived SCNAs with a tumour fraction as low as 10 % of cfDNA.Our preliminary results demonstrate non-invasive detection of tumour-derived copy number alterations in advanced lung cancer cases with low coverage whole genome sequencing. Clinical characteristics and treatment may influence whether SCNA are detected in cfDNA.

BackgroundMost cancers exhibit somatic copy number alterations (SCNAs)—gains and losses of variable regions of DNA. SCNAs play a key role in cancer adaptation through modulation of gene expression, deletion of tumor suppressor genes, or amplification of oncogenes. Systematic analysis of SCNAs is now a routine task in both the clinic and research and can help identify novel cancer genes, improve our understanding of cancer gene regulation, and enable us to accurately reconstruct cancer phylogenies. However, to conduct such analyses, SCNA profiles have to be integrated between samples, patients, and cohorts—often a nontrivial task, for which dedicated toolkits are lacking.ResultsTo fill this gap, we developed CNSistent, a Python package for imputation, filtering, consistent segmentation, feature extraction, and visualization of cancer copy number profiles from heterogeneous datasets. We demonstrate the utility of CNSistent by applying it to the following publicly available cohorts: The Cancer Genome Atlas, Pan-Cancer Analysis of Whole Genomes, and TRAcking Cancer Evolution through therapy (Rx). We compare the effect of sample preprocessing and different segmentation and aggregation strategies on cancer type and subtype classification tasks using various classification models. We also evaluate how well a classifier trained on one cohort generalizes to another. Lastly, we introduce 2 segment-based peak and outlier scores to investigate relationships between segments, between samples, and between cancer types. Using these scores, we investigate non–small cell lung cancer samples, highlighting that SOX2 amplification is the dominant copy number alteration in lung squamous cell carcinoma and the main distinction to lung adenocarcinoma.ConclusionsCNSistent is a general-purpose toolkit for integrated processing of SCNA profiles across many patients and cohorts. It is available at https://bitbucket.org/schwarzlab/cnsistent. The Research Resource Identifier for CNSistent is SCR_027025.

IntroductionBrain metastases (BM) severely affect the prognosis and quality of life of patients with NSCLC. Recently, molecularly targeted agents were found to have promising activity against BM in patients with NSCLC whose primary tumors carry “druggable” mutations. Nevertheless, it remains critical to identify specific pathogenic alterations that drive NSCLC-BM and that can provide novel and more effective therapeutic targets. MethodsTo identify potentially targetable pathogenic alterations in NSCLC-BM, we profiled somatic copy number alterations (SCNAs) in 51 matched pairs of primary NSCLC and BM samples from 33 patients with lung adenocarcinoma and 18 patients with lung squamous cell carcinoma. In addition, we performed multiregion copy number profiling on 15 BM samples and whole-exome sequencing on 40 of 51 NSCLC-BM pairs. ResultsBM consistently had a higher burden of SCNAs compared with the matched primary tumors, and SCNAs were typically homogeneously distributed within BM, suggesting BM do not undergo extensive evolution once formed. By comparing focal SCNAs in matched NSCLC-BM pairs, we identified putative BM-driving alterations affecting multiple cancer genes, including several potentially targetable alterations in genes such as CDK12, DDR2, ERBB2, and NTRK1, which we validated in an independent cohort of 84 BM samples. Finally, we identified putative pathogenic alterations in multiple cancer genes, including genes involved in epigenome editing and 3D genome organization, such as EP300, CTCF, and STAG2, which we validated by targeted sequencing of an independent cohort of 115 BM samples. ConclusionsOur study represents the most comprehensive genomic characterization of NSCLC-BM available to date, paving the way to functional studies aimed at assessing the potential of the identified pathogenic alterations as clinical biomarkers and targets.

Harnessing Cell-Free DNA Biological Features for Early Treatment Response Prediction in High Grade B-Cell Lymphoma

Jitter is inherent to the breakpoints of measured genome somatic copy number alterations (SCNAs). Therefore, an analysis of jitter is required to reduce errors in the SCNA estimation. The SCNA measurements are accompanied with intensive noise that may cause errors and ambiguities in the breakpoint detection with low signal-to-noise ratios (SNRs). We show that the asymmetric exponential power distribution (AEPD) provides much better approximation to the jitter distribution than the earlier proposed discrete skew Laplace distribution. Furthermore, we confirm that (AEP) distribution its suitable for computing the confidence upper and lower boundary limits in order to guarantee an existence of genomic changes with a required probability. We test some neuroblastoma SCNAs measurements by the upper and lower confidence bound masks with several probabilities.

Telomeres are DNA-protein structures at the ends of chromosomes essential in maintaining chromosomal stability. Observational studies have identified associations between telomeres and elevated cancer risk, including hematologic malignancies; but biologic mechanisms relating telomere length to cancer etiology remain unclear. Our study sought to better understand the relationship between telomere length and cancer risk by evaluating genetically-predicted telomere length (gTL) in relation to the presence of clonal somatic copy number alterations (SCNAs) in peripheral blood leukocytes. Genotyping array data were acquired from 431,507 participants in the UK Biobank and used to detect SCNAs from intensity information and infer telomere length using a polygenic risk score (PRS) of variants previously associated with leukocyte telomere length. In total, 15,236 (3.5%) of individuals had a detectable clonal SCNA on an autosomal chromosome. Overall, higher gTL value was positively associated with the presence of an autosomal SCNA (OR = 1.07, 95% CI = 1.05–1.09, P = 1.61×10−15). There was high consistency in effect estimates across strata of chromosomal event location (e.g., telomeric ends, interstitial or whole chromosome event; Phet = 0.37) and strata of copy number state (e.g., gain, loss, or neutral events; Phet = 0.05). Higher gTL value was associated with a greater cellular fraction of clones carrying autosomal SCNAs (β = 0.004, 95% CI = 0.002–0.007, P = 6.61×10−4). Our population-based examination of gTL and SCNAs suggests inherited components of telomere length do not preferentially impact autosomal SCNA event location or copy number status, but rather likely influence cellular replicative potential.