Abstract 3649: Targeted sequencing of 409 cancer-related genes for somatic mutations and copy number variations in human cancer using the semiconductor sequencers

2016 ◽  
Author(s):  
Yasushi Sasaki ◽  
Ryota Koyama ◽  
Takafumi Nakagaki ◽  
Miyuki Tamura ◽  
Masashi Idogawa ◽  
...  
Keyword(s):  
Copy Number ◽  
Somatic Mutations ◽  
Human Cancer ◽  
Copy Number Variations ◽  
Targeted Sequencing

scholarly journals HiCancer: accurate and complete cancer genome phasing with Hi-C reads

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Weihua Pan ◽  
Desheng Gong ◽  
Da Sun ◽  
Haohui Luo
Keyword(s):  
Copy Number ◽  
Somatic Mutations ◽  
Copy Number Variations ◽  
Cancer Genome ◽  
Structural Variations ◽  
Genome Map ◽  
Linkage Information ◽  
Suboptimal Solution ◽  
Allelic Copy Number ◽  
Very High

AbstractDue to the high complexity of cancer genome, it is too difficult to generate complete cancer genome map which contains the sequence of every DNA molecule until now. Nevertheless, phasing each chromosome in cancer genome into two haplotypes according to germline mutations provides a suboptimal solution to understand cancer genome. However, phasing cancer genome is also a challenging problem, due to the limit in experimental and computational technologies. Hi-C data is widely used in phasing in recent years due to its long-range linkage information and provides an opportunity for solving the problem of phasing cancer genome. The existing Hi-C based phasing methods can not be applied to cancer genome directly, because the somatic mutations in cancer genome such as somatic SNPs, copy number variations and structural variations greatly reduce the correctness and completeness. Here, we propose a new Hi-C based pipeline for phasing cancer genome called HiCancer. HiCancer solves different kinds of somatic mutations and variations, and take advantage of allelic copy number imbalance and linkage disequilibrium to improve the correctness and completeness of phasing. According to our experiments in K562 and KBM-7 cell lines, HiCancer is able to generate very high-quality chromosome-level haplotypes for cancer genome with only Hi-C data.

scholarly journals Genomic alterations caused by HPV integration in a cohort of Chinese endocervical adenocarcinomas

2021 ◽  
Author(s):  
Wenhui Li ◽  
Wanjun Lei ◽  
Xiaopei Chao ◽  
Xiaochen Song ◽  
Yalan Bi ◽  
...  
Keyword(s):  
Copy Number ◽  
Somatic Mutations ◽  
Hpv Infection ◽  
Copy Number Variations ◽  
Cervical Adenocarcinoma ◽  
Structural Variations ◽  
Driver Genes ◽  
Genetic Changes ◽  
Genomic Changes ◽  
Whole Exome

AbstractThe association between human papillomavirus (HPV) integration and relevant genomic changes in uterine cervical adenocarcinoma is poorly understood. This study is to depict the genomic mutational landscape in a cohort of 20 patients. HPV+ and HPV− groups were defined as patients with and without HPV integration in the host genome. The genetic changes between these two groups were described and compared by whole-genome sequencing (WGS) and whole-exome sequencing (WES). WGS identified 2916 copy number variations and 743 structural variations. WES identified 6113 somatic mutations, with a mutational burden of 2.4 mutations/Mb. Six genes were predicted as driver genes: PIK3CA, KRAS, TRAPPC12, NDN, GOLGA6L4 and BAIAP3. PIK3CA, NDN, GOLGA6L4, and BAIAP3 were recognized as significantly mutated genes (SMGs). HPV was detected in 95% (19/20) of patients with cervical adenocarcinoma, 7 of whom (36.8%) had HPV integration (HPV+ group). In total, 1036 genes with somatic mutations were confirmed in the HPV+ group, while 289 genes with somatic mutations were confirmed in the group without HPV integration (HPV− group); only 2.1% were shared between the two groups. In the HPV+ group, GOLGA6L4 and BAIAP3 were confirmed as SMGs, while PIK3CA, NDN, KRAS, FUT1, and GOLGA6L64 were identified in the HPV− group. ZDHHC3, PKD1P1, and TGIF2 showed copy number amplifications after HPV integration. In addition, the HPV+ group had significantly more neoantigens. HPV integration rather than HPV infection results in different genomic changes in cervical adenocarcinoma.

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

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.

scholarly journals Somatic mutations and copy number variations in breast cancers with heterogeneous HER2 amplification

2020 ◽  
Vol 14 (4) ◽  
pp. 671-685 ◽  
Author(s):  
Mieke R. Van Bockstal ◽  
Marie Colombe Agahozo ◽  
Ronald van Marion ◽  
Peggy N. Atmodimedjo ◽  
Hein F. B. M. Sleddens ◽  
...  
Keyword(s):  
Copy Number ◽  
Somatic Mutations ◽  
Copy Number Variations ◽  
Breast Cancers ◽  
Her2 Amplification

scholarly journals Identification of rare germline copy number variations over-represented in five human cancer types

2015 ◽  
Vol 14 (1) ◽  
Author(s):  
Richard W Park ◽  
Tae-Min Kim ◽  
Simon Kasif ◽  
Peter J Park
Keyword(s):  
Copy Number ◽  
Human Cancer ◽  
Copy Number Variations ◽  
Cancer Types

scholarly journals Mutations and Copy Number Abnormalities of Hippo Pathway Components in Human Cancers

2021 ◽  
Vol 9 ◽  
Author(s):  
Zhengjin He ◽  
Ruihan Li ◽  
Hai Jiang
Keyword(s):  
Cell Proliferation ◽  
Cancer Cells ◽  
Copy Number ◽  
Human Cancer ◽  
Hippo Pathway ◽  
Copy Number Variations ◽  
Tissue Homeostasis ◽  
Hippo Signaling ◽  
Core Components ◽  
The Hippo Pathway

The Hippo pathway is highly conserved from Drosophila to mammals. As a key regulator of cell proliferation, the Hippo pathway controls tissue homeostasis and has a major impact on tumorigenesis. The originally defined core components of the Hippo pathway in mammals include STK3/4, LATS1/2, YAP1/TAZ, TEAD, VGLL4, and NF2. However, for most of these genes, mutations and copy number variations are relatively uncommon in human cancer. Several other recently identified upstream and downstream regulators of Hippo signaling, including FAT1, SHANK2, Gq/11, and SWI/SNF complex, are more commonly dysregulated in human cancer at the genomic level. This review will discuss major genomic events in human cancer that enable cancer cells to escape the tumor-suppressive effects of Hippo signaling.

Quantitation of DNA methylation and copy number variations by targeted sequencing of retrotransposon.

2016 ◽  
Vol 34 (15_suppl) ◽  
pp. e23139-e23139
Author(s):  
Jeffrey Buis ◽  
Tom Goodman ◽  
Julie Kim ◽  
Adele Kruger ◽  
Brendan Tarrier ◽  
...  
Keyword(s):  
Dna Methylation ◽  
Copy Number ◽  
Copy Number Variations ◽  
Targeted Sequencing

scholarly journals Association between the expression of secreted phosphoprotein - related genes and prognosis of human cancer

BMC Cancer ◽  
2019 ◽  
Vol 19 (1) ◽  
Author(s):  
Yaqin Tu ◽  
Cai Chen ◽  
Guorun Fan
Keyword(s):  
Copy Number ◽  
Prognostic Value ◽  
Prognostic Markers ◽  
Human Cancer ◽  
Copy Number Variations ◽  
Cancer Prognosis ◽  
Clinical Markers ◽  
Ppi Network ◽  
Protein Protein Interaction ◽  
Head Neck

Abstract Background While many studies have assessed the predictive value of secreted phosphoprotein (SPP) genes in cancer, the findings have been inconsistent. To resolve these inconsistencies, we systematically analyzed the available data to determine whether SPP1 and SPP2 are prognostic markers in the context of human cancer. Methods The expression of SPP1 and SPP2 was assessed by Oncomine analysis. The PrognoScan database was used to assess the prognostic value of SPP1 and SPP2, with cBioPortal used to assess copy number variations. The STRING database was used to generate a Protein - Protein Interaction (PPI) network for SPP genes. Results SPP1 was more likely to be over-expressed in breast, bladder, colorectal, head, neck, liver, lung, and esophageal cancers. SPP2 was expressed at lower levels in colorectal cancer, leukemia, liver cancer and pancreatic cancer. In addition, SPP1 and SPP2 mutations mainly occurred in cutaneous melanoma and endometrial cancer. Conclusions Our results suggest that SPP1 and SPP2 may be effective therapeutic or diagnostic targets in certain cancers. Further research is required to confirm these results and verify the value of SPP1 and SPP2 as clinical markers of cancer prognosis.

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