GSA: an independent development algorithm for calling copy number and detecting homologous recombination deficiency (HRD) from target capture sequencing

Abstract Background The gain or loss of large chromosomal regions or even whole chromosomes is termed as genomic scarring and can be observed as copy number variations resulting from the failure of DNA damage repair. Results In this study, a new algorithm called genomic scar analysis (GSA) has developed and validated to calculate homologous recombination deficiency (HRD) score. The two critical submodules were tree recursion (TR) segmentation and filtering, and the estimation and correction of the tumor purity and ploidy. Then, this study evaluated the rationality of segmentation and genotype identification by the GSA algorithm and compared with other two algorithms, PureCN and ASCAT, found that the segmentation result of GSA algorithm was more logical. In addition, the results indicated that the GSA algorithm had an excellent predictive effect on tumor purity and ploidy, if the tumor purity was more than 20%. Furtherly, this study evaluated the HRD scores and BRCA1/2 deficiency status of 195 clinical samples, and the results indicated that the accuracy was 0.98 (comparing with Affymetrix OncoScan™ assay) and the sensitivity was 95.2% (comparing with BRCA1/2 deficiency status), both were well-behaved. Finally, HRD scores and 16 genes mutations (TP53 and 15 HRR pathway genes) were analyzed in 17 cell lines, the results showed that there was higher frequency in HRR pathway genes in high HRD score samples. Conclusions This new algorithm, named as GSA, could effectively and accurately calculate the purity and ploidy of tumor samples through NGS data, and then reflect the degree of genomic instability and large-scale copy number variations of tumor samples.

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GSA: An Independent Development Algorithm for Calling Copy Number and Detecting Homologous Recombination Deficiency (HRD) from Target Capture Sequencing

10.1101/2021.08.02.454110 ◽

2021 ◽

Author(s):

Dongju Chen ◽

Minghui Shao ◽

Pei Meng ◽

Chunli Wang ◽

Qi Li ◽

...

Keyword(s):

Homologous Recombination ◽

Copy Number ◽

Large Scale ◽

Parp Inhibitors ◽

Copy Number Variations ◽

Clinical Samples ◽

Real World Data ◽

Homologous Recombination Deficiency ◽

Tumor Purity ◽

Platinum Based Chemotherapy

The gain or loss of large chromosomal regions or even whole chromosomes is termed as genomic scarring and can be observed as copy number variations resulting from the failure of DNA damage repair. Aneuploidy is a common event in cancers, and it may lead to more copy number variation, but not caused by homologous recombination deficiency (HRD). In this study, a new algorithm called Genomic Scar Analysis (GSA) has developed and validated, calculating HRD score, combined with loss of heterozygosity (LOH), telomeric allelic imbalance (TAI), and large-scale state transition (LST) scores. The two critical submodules were tree recursion (TR) segmentation and filtering, and the estimation and correction of the tumor purity and ploidy. Then, this study evaluated the rationality of segmentation and genotype identification by the GSA algorithm and compared with other two algorithms, PureCN and ASCAT, found that the segmentation result of GSA algorithm was more logical. In addition, the results indicated that the GSA algorithm had an excellent predictive effect on tumor purity (correlation coefficient R2 were 0.9813 and 0.9812, respectively, in tumor and cell line diluted samples), and more stable ploidy predictors, if the tumor purity was more than 20%. Furtherly, this study evaluated the HRD scores and BRCA1/2 deficiency status of 195 clinical samples, and the results indicated that the accuracy was 0.98 (comparing with Affymetrix OncoScan assay) and the sensitivity was 91.9% (comparing with BRCA1/2 deficiency status), both were well-behaved. Finally, HRD scores and 16 genes mutations (TP53 and 15 HRR pathway genes) were analyzed in 17 cell lines, the results showed that there was higher frequency in HRR pathway genes in high HRD score samples, but it still need more data on the efficacy of PARP inhibitors or platinum-based chemotherapy to validate the accuracy of GSA algorithm in the real-world data.

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KNNCNV: A K-Nearest Neighbor Based Method for Detection of Copy Number Variations Using NGS Data

Frontiers in Cell and Developmental Biology ◽

10.3389/fcell.2021.796249 ◽

2021 ◽

Vol 9 ◽

Author(s):

Kun Xie ◽

Kang Liu ◽

Haque A K Alvi ◽

Yuehui Chen ◽

Shuzhen Wang ◽

...

Keyword(s):

Copy Number ◽

Nearest Neighbor ◽

Human Cancer ◽

Gaussian Mixture ◽

Disease Diagnosis ◽

Copy Number Variations ◽

Sequencing Data ◽

K Nearest Neighbor ◽

Data Types ◽

Ngs Data

Copy number variation (CNV) is a well-known type of genomic mutation that is associated with the development of human cancer diseases. Detection of CNVs from the human genome is a crucial step for the pipeline of starting from mutation analysis to cancer disease diagnosis and treatment. Next-generation sequencing (NGS) data provides an unprecedented opportunity for CNVs detection at the base-level resolution, and currently, many methods have been developed for CNVs detection using NGS data. However, due to the intrinsic complexity of CNVs structures and NGS data itself, accurate detection of CNVs still faces many challenges. In this paper, we present an alternative method, called KNNCNV (K-Nearest Neighbor based CNV detection), for the detection of CNVs using NGS data. Compared to current methods, KNNCNV has several distinctive features: 1) it assigns an outlier score to each genome segment based solely on its first k nearest-neighbor distances, which is not only easy to extend to other data types but also improves the power of discovering CNVs, especially the local CNVs that are likely to be masked by their surrounding regions; 2) it employs the variational Bayesian Gaussian mixture model (VBGMM) to transform these scores into a series of binary labels without a user-defined threshold. To evaluate the performance of KNNCNV, we conduct both simulation and real sequencing data experiments and make comparisons with peer methods. The experimental results show that KNNCNV could derive better performance than others in terms of F1-score.

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A large-scale survey of genetic copy number variations among Han Chinese residing in Taiwan

BMC Genetics ◽

10.1186/1471-2156-9-92 ◽

2008 ◽

Vol 9 (1) ◽

pp. 92 ◽

Cited By ~ 17

Author(s):

Chien-Hsing Lin ◽

Ling-Hui Li ◽

Sheng-Feng Ho ◽

Tzu-Po Chuang ◽

Jer-Yuarn Wu ◽

...

Keyword(s):

Copy Number ◽

Large Scale ◽

Copy Number Variations ◽

Han Chinese ◽

Large Scale Survey

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MON-LB48 The Genomic Landscape of Sporadic Thyrotrophinomas

Journal of the Endocrine Society ◽

10.1210/jendso/bvaa046.2282 ◽

2020 ◽

Vol 4 (Supplement_1) ◽

Author(s):

Angeline shen ◽

Paul Wang ◽

Sunita M C De Sousa ◽

David J Torpy ◽

Hamish Scott ◽

...

Keyword(s):

Cell Adhesion ◽

Rna Polymerase Ii ◽

Copy Number ◽

Large Scale ◽

Neutral Loss ◽

Copy Number Variations ◽

Driver Mutations ◽

Chromosomal Anomalies ◽

Tumour Type ◽

Genomic Landscape

Abstract Background: Thyrotrophinoma (TSHoma) is rare and knowledge on the genomic landscape of this tumour type is very limited. Aim: To perform whole-exome sequencing (WES) in a population of TSHomas to identify recurrent somatic genetic events Method: WES was performed on paired tumour and germline DNA of 7 patients with TSHomas. Three tissue samples were formalin-fixed paraffin-embedded and 4 fresh frozen tumour samples. Fresh blood samples were also collected from each patient. The average of mean depth of coverage amongst all samples was 129X, and 97% of target bases were covered ≥20X. Results:Four (57%) of the seven patients were male and median age at diagnosis was 52 years. (IQR 46, 60) Six patients (86%) had macroadenomas. Four patients (57%) had central thyrotoxicosis at diagnosis and three patients’ tumour stained positive for TSH on histology examination. Two patients (29%) had growth hormone co-secreting tumours. In total, 69 somatic variants were identified to be of potential interest, averaging 1.4 variants per million base-pair of DNA read. No variants were observed in more than one individual. According to the GTEx database, 9 of 69 genes (DRC3, HDAC5, KDM1A, POLR21, TCF25, THAP7, TTC13, UNC5D, UNC13A) were highly expressed in the pituitary (top 10%). Four of these genes appear to contribute to tumour development via epigenetic pathway. Specifically, three of these genes (HDAC5, KDM1A, THAP7) either interact with or form part of histone deacetylases whilst POLR21 encodes a subunit of RNA polymerase II which is responsible for mRNA synthesis. On the other hand, TCF25 gene is thought to act as transcriptional repressor and UNC5D plays a role in cell-cell adhesion. Large scale copy number variations involving gain or loss of whole chromosome or chromosome (chr) arm were observed in six (86%) tumour samples. Chr 5, 9, 13 and 19 were most commonly affected by chromosomal gains. Deletion of chr 1p was seen in two cases and mutations in KDM1A (p.Glu161fs/c.482_491delAGGAAGAAAA) and ADGRB2 gene (p.Leu1565Gln/c.4694T>A) were found in each of the remaining single copy of chr 1p. ADGRB2 gene is thought to be involved in cell adhesion and angiogenesis inhibition. Copy neutral loss-of-heterozygosity were present in two (29%) of the tumour samples (chr 2 and 12q). However, no somatic mutation was found in these regions. Gene level copy number analysis identified a potential deletion in TTI2 gene which encodes for a regulator in DNA damaging response as well as telomere length regulation. ConclusionOverall, the rate of somatic variant mutations in TSHomas is low, consistent with the relative benign nature of this tumour type. No classical driver mutations were identified by this study however, chromosomal anomalies and epigenetics may play an important part in TSHoma development.

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Higher prevalence of homologous recombination-deficiency in lung squamous carcinoma from African Americans

10.1101/651794 ◽

2019 ◽

Author(s):

Sanju Sinha ◽

Khadijah A. Mitchell ◽

Adriana Zingone ◽

Elise Bowman ◽

Neelam Sinha ◽

...

Keyword(s):

Homologous Recombination ◽

Copy Number ◽

Squamous Carcinoma ◽

The Cancer Genome Atlas ◽

Multiple Cancer ◽

Homologous Recombination Deficiency ◽

Molecular Features ◽

Incidence And Mortality ◽

Cancer Types ◽

Lung Squamous Carcinoma

AbstractTo improve our understanding of the longstanding disparities in incidence and mortality across multiple cancer types among minority populations, we performed a systematic comparative analysis of molecular features in tumors from African American (AA) and European American (EA) ancestry. Our pan-cancer analysis on the cancer genome atlas (TCGA) and a more focused analysis of genome-wide somatic copy number profiles integrated with tumor-normal RNA sequencing in a racially balanced cohort of 222 non-small cell lung cancers (NSCLC) reveals more aggressive genomic characteristics of AA tumors. In general, we find AA tumors exhibit higher genomic instability (GI), homologous recombination-deficiency (HRD) levels, and more aggressive molecular features such as chromothripsis across many cancer types, including lung squamous carcinoma (LUSC). GI and HRD levels are strongly correlated across AA tumors, indicating that HRD plays an important role in GI in these patients. The prevalence of germline HRD is higher in AA tumors, suggesting that the somatic differences observed have genetic ancestry origins. Finally, we identify AA-specific copy number-based arm, focal and gene level recurrent features in lung cancer, including a higher frequency of PTEN deletion and KRAS amplification and a lower frequency of CDKN2A deletion. These results highlight the importance of including minority and under-represented populations in genomics research and may have therapeutic implications.

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Inferring Homologous Recombination Deficiency of Ovarian Cancer From the Landscape of Copy Number Variation at Subchromosomal and Genetic Resolutions

Frontiers in Oncology ◽

10.3389/fonc.2021.772604 ◽

2021 ◽

Vol 11 ◽

Author(s):

Meng Zhang ◽

Si-Cong Ma ◽

Jia-Le Tan ◽

Jian Wang ◽

Xue Bai ◽

...

Keyword(s):

Ovarian Cancer ◽

Homologous Recombination ◽

Copy Number Variation ◽

Copy Number ◽

The Cancer Genome Atlas ◽

Homologous Recombination Deficiency ◽

Number Variation ◽

Cancer Genome Atlas ◽

Tumor Types ◽

Pan Cancer

BackgroundHomologous recombination deficiency (HRD) is characterized by overall genomic instability and has emerged as an indispensable therapeutic target across various tumor types, particularly in ovarian cancer (OV). Unfortunately, current detection assays are far from perfect for identifying every HRD patient. The purpose of this study was to infer HRD from the landscape of copy number variation (CNV).MethodsGenome-wide CNV landscape was measured in OV patients from the Australian Ovarian Cancer Study (AOCS) clinical cohort and >10,000 patients across 33 tumor types from The Cancer Genome Atlas (TCGA). HRD-predictive CNVs at subchromosomal resolution were identified through exploratory analysis depicting the CNV landscape of HRD versus non-HRD OV patients and independently validated using TCGA and AOCS cohorts. Gene-level CNVs were further analyzed to explore their potential predictive significance for HRD across tumor types at genetic resolution.ResultsAt subchromosomal resolution, 8q24.2 amplification and 5q13.2 deletion were predominantly witnessed in HRD patients (both p < 0.0001), whereas 19q12 amplification occurred mainly in non-HRD patients (p < 0.0001), compared with their corresponding counterparts within TCGA-OV. The predictive significance of 8q24.2 amplification (p < 0.0001), 5q13.2 deletion (p = 0.0056), and 19q12 amplification (p = 0.0034) was externally validated within AOCS. Remarkably, pan-cancer analysis confirmed a cross-tumor predictive role of 8q24.2 amplification for HRD (p < 0.0001). Further analysis of CNV in 8q24.2 at genetic resolution revealed that amplifications of the oncogenes, MYC (p = 0.0001) and NDRG1 (p = 0.0004), located on this fragment were also associated with HRD in a pan-cancer manner.ConclusionsThe CNV landscape serves as a generalized predictor of HRD in cancer patients not limited to OV. The detection of CNV at subchromosomal or genetic resolution could aid in the personalized treatment of HRD patients.

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Detection of copy-number variations from NGS data using read depth information: a diagnostic performance evaluation

European Journal of Human Genetics ◽

10.1038/s41431-020-0672-2 ◽

2020 ◽

Vol 29 (1) ◽

pp. 99-109 ◽

Cited By ~ 1

Author(s):

Olivier Quenez ◽

◽

Kevin Cassinari ◽

Sophie Coutant ◽

François Lecoquierre ◽

...

Keyword(s):

Performance Evaluation ◽

Copy Number ◽

Diagnostic Performance ◽

Read Depth ◽

Copy Number Variations ◽

Depth Information ◽

Ngs Data

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Effects of copy number variations on brain structure and risk for psychiatric illness: Large‐scale studies from the ENIGMA working groups on CNVs

Human Brain Mapping ◽

10.1002/hbm.25354 ◽

2021 ◽

Author(s):

Ida E. Sønderby ◽

Christopher R. K. Ching ◽

Sophia I. Thomopoulos ◽

Dennis Meer ◽

Daqiang Sun ◽

...

Keyword(s):

Brain Structure ◽

Copy Number ◽

Psychiatric Illness ◽

Large Scale ◽

Copy Number Variations ◽

Working Groups

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CNest: A Novel Copy Number Association Discovery Method Uncovers 862 New Associations from 200,629 Whole Exome Sequence Datasets in the UK Biobank

10.1101/2021.08.19.456963 ◽

2021 ◽

Author(s):

Tomas W Fitzgerald ◽

Ewan Birney

Keyword(s):

Copy Number ◽

Large Scale ◽

Association Studies ◽

Genomic Variation ◽

Next Generation Sequencing Data ◽

Genome Wide Association Studies ◽

Uk Biobank ◽

Genome Wide ◽

The Uk ◽

Ngs Data

Copy number variation (CNV) has long been known to influence human traits having a rich history of research into common and rare genetic disease and although CNV is accepted as an important class of genomic variation, progress on copy number (CN) phenotype associations from Next Generation Sequencing data (NGS) has been limited, in part, due to the relative difficulty in CNV detection and an enrichment for large numbers of false positives. To date most successful CN genome wide association studies (CN-GWAS) have focused on using predictive measures of dosage intolerance or gene burden tests to gain sufficient power for detecting CN effects. Here we present a novel method for large scale CN analysis from NGS data generating robust CN estimates and allowing CN-GWAS to be performed genome wide in discovery mode. We provide a detailed analysis in the large scale UK BioBank resource and a specifically designed software package for deriving CN estimates from NGS data that are robust enough to be used for CN-GWAS. We use these methods to perform genome wide CN-GWAS analysis across 78 human traits discovering 862 genetic associations that are likely to contribute strongly to trait distributions based solely on their CN or by acting in concert with other genetic variation. Finally, we undertake an analysis comparing CNV and SNP association signals across the same traits and samples, defining specific CNV association classes based on whether they could be detected using standard SNP-GWAS in the UK Biobank.

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Translational Study of Copy Number Variations in Schizophrenia

International Journal of Molecular Sciences ◽

10.3390/ijms23010457 ◽

2021 ◽

Vol 23 (1) ◽

pp. 457

Author(s):

Min-Chih Cheng ◽

Wei-Hsien Chien ◽

Yu-Shu Huang ◽

Ting-Hsuan Fang ◽

Chia-Hsiang Chen

Keyword(s):

Screening Test ◽

Copy Number ◽

Large Scale ◽

Cost Effective ◽

Copy Number Variations ◽

Chromosomal Microarray ◽

Chromosomal Microarray Analysis ◽

Two Stage ◽

Translational Study ◽

Analysis Group

Rare copy number variations (CNVs) are part of the genetics of schizophrenia; they are highly heterogeneous and personalized. The CNV Analysis Group of the Psychiatric Genomic Consortium (PGC) conducted a large-scale analysis and discovered that recurrent CNVs at eight genetic loci were pathogenic to schizophrenia, including 1q21.1, 2p16.3 (NRXN1), 3q29, 7q11.23, 15q13.3, distal 16p11.2, proximal 16p11.2, and 22q11.2. We adopted a two-stage strategy to translate this knowledge into clinical psychiatric practice. As a screening test, we first developed a real-time quantitative PCR (RT-qPCR) panel that simultaneously detected these pathogenic CNVs. Then, we tested the utility of this screening panel by investigating a sample of 557 patients with schizophrenia. Chromosomal microarray analysis (CMA) was used to confirm positive cases from the screening test. We detected and confirmed thirteen patients who carried CNVs at these hot loci, including two patients at 1q21.1, one patient at 7q11.2, three patients at 15q13.3, two patients at 16p11.2, and five patients at 22q11.2. The detection rate in this sample was 2.3%, and the concordance rate between the RT-qPCR test panel and CMA was 100%. Our results suggest that a two-stage approach is cost-effective and reliable in achieving etiological diagnosis for some patients with schizophrenia and improving the understanding of schizophrenia genetics.

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