scholarly journals Concordance between somatic copy number loss and down-regulated expression: A pan-cancer study of cancer predisposition genes

2016 ◽  
Vol 6 (1) ◽  
Author(s):  
Ran Wei ◽  
Ming Zhao ◽  
Chun-Hou Zheng ◽  
Min Zhao ◽  
Junfeng Xia
Keyword(s):  
Copy Number ◽  
Cancer Predisposition ◽  
Copy Number Loss ◽  
Cancer Study ◽  
Regulated Expression ◽  
Predisposition Genes ◽  
Pan Cancer

scholarly journals Performance of In Silico Prediction Tools for the Detection of Germline Copy Number Variations in Cancer Predisposition Genes in 4208 Female Index Patients with Familial Breast and Ovarian Cancer

Cancers ◽  
2021 ◽  
Vol 13 (1) ◽  
pp. 118
Author(s):  
Louisa Lepkes ◽  
Mohamad Kayali ◽  
Britta Blümcke ◽  
Jonas Weber ◽  
Malwina Suszynska ◽  
...  
Keyword(s):  
Ovarian Cancer ◽  
In Silico ◽  
Copy Number ◽  
Gc Content ◽  
Copy Number Variations ◽  
Cancer Predisposition ◽  
Predictive Values ◽  
Prediction Tools ◽  
Predisposition Genes ◽  
Female Index

The identification of germline copy number variants (CNVs) by targeted next-generation sequencing (NGS) frequently relies on in silico CNV prediction tools with unknown sensitivities. We investigated the performances of four in silico CNV prediction tools, including one commercial (Sophia Genetics DDM) and three non-commercial tools (ExomeDepth, GATK gCNV, panelcn.MOPS) in 17 cancer predisposition genes in 4208 female index patients with familial breast and/or ovarian cancer (BC/OC). CNV predictions were verified via multiplex ligation-dependent probe amplification. We identified 77 CNVs in 76 out of 4208 patients (1.81%); 33 CNVs were identified in genes other than BRCA1/2, mostly in ATM, CHEK2, and RAD51C and less frequently in BARD1, MLH1, MSH2, PALB2, PMS2, RAD51D, and TP53. The Sophia Genetics DDM software showed the highest sensitivity; six CNVs were missed by at least one of the non-commercial tools. The positive predictive values ranged from 5.9% (74/1249) for panelcn.MOPS to 79.1% (72/91) for ExomeDepth. Verification of in silico predicted CNVs is required due to high frequencies of false positive predictions, particularly affecting target regions at the extremes of the GC content or target length distributions. CNV detection should not be restricted to BRCA1/2 due to the relevant proportion of CNVs in further BC/OC predisposition genes.

scholarly journals Analysis of Sequence and Copy Number Variants in Canadian Patient Cohort With Familial Cancer Syndromes Using a Unique Next Generation Sequencing Based Approach

2021 ◽  
Vol 12 ◽  
Author(s):  
Pratibha Bhai ◽  
Michael A. Levy ◽  
Kathleen Rooney ◽  
Deanna Alexis Carere ◽  
Jack Reilly ◽  
...  
Keyword(s):  
Genetic Testing ◽  
Next Generation Sequencing ◽  
Hereditary Cancer ◽  
Copy Number ◽  
Copy Number Variants ◽  
Cancer Predisposition ◽  
Sequence Variants ◽  
Predisposition Genes ◽  
Cancer Syndromes ◽  
Generation Sequencing

BackgroundHereditary cancer predisposition syndromes account for approximately 10% of cancer cases. Next generation sequencing (NGS) based multi-gene targeted panels is now a frontline approach to identify pathogenic mutations in cancer predisposition genes in high-risk families. Recent evolvement of NGS technologies have allowed simultaneous detection of sequence and copy number variants (CNVs) using a single platform. In this study, we have analyzed frequency and nature of sequence variants and CNVs, in a Canadian cohort of patients, suspected with hereditary cancer syndrome, referred for genetic testing following specific genetic testing guidelines based on patient’s personal and/or family history of cancer.MethodsA 2870 patients were subjected to a single NGS based multi-gene targeted hereditary cancer panel testing algorithm to identify sequence variants and CNVs in cancer predisposition genes at our reference laboratory in Southwestern Ontario. CNVs identified by NGS were confirmed by alternative techniques like Multiplex ligation-dependent probe amplification (MLPA).ResultsA 15% (431/2870) patients had a pathogenic variant and 36% (1032/2870) had a variant of unknown significance (VUS), in a cancer susceptibility gene. A total of 287 unique pathogenic variant were identified, out of which 23 (8%) were novel. CNVs identified by NGS based approach accounted for 9.5% (27/287) of pathogenic variants, confirmed by alternate techniques with high accuracy.ConclusionThis study emphasizes the utility of NGS based targeted testing approach to identify both sequence and CNVs in patients suspected with hereditary cancer syndromes in clinical setting and expands the mutational spectrum of high and moderate penetrance cancer predisposition genes.

scholarly journals Substantial Batch Effects in TCGA Exome Sequences Undermine Pan-Cancer Analysis of Germline Variants

2018 ◽  
Author(s):  
Roni Rasnic ◽  
Nadav Brandes ◽  
Or Zuk ◽  
Michal Linial
Keyword(s):  
Cancer Patients ◽  
Variant Calling ◽  
Batch Effect ◽  
Cancer Predisposition ◽  
The Cancer Genome Atlas ◽  
Batch Effects ◽  
Germline Variants ◽  
Predisposition Genes ◽  
Cancer Types ◽  
Pan Cancer

ABSTRACTBackgroundIn recent years, research on cancer predisposition germline variants has emerged as a prominent field. The identity of somatic mutations is based on a reliable mapping of the patient germline variants. In addition, the statistics of germline variants frequencies in healthy individuals and cancer patients is the basis for seeking candidates for cancer predisposition genes. The Cancer Genome Atlas (TCGA) is one of the main sources of such data, providing a diverse collection of molecular data including deep sequencing for more than 30 types of cancer from >10,000 patients.MethodsOur hypothesis in this study is that whole exome sequences from healthy blood samples of cancer patients are not expected to show systematic differences among cancer types. To test this hypothesis, we analyzed common and rare germline variants across six cancer types, covering 2,241 samples from TCGA. In our analysis we accounted for inherent variables in the data including the different variant calling protocols, sequencing platforms, and ethnicity.ResultsWe report on substantial batch effects in germline variants associated with cancer types. We attribute the effect to the specific sequencing centers that produced the data. Specifically, we measured 30% variability in the number of reported germline variants per sample across sequencing centers. The batch effect is further expressed in nucleotide composition and variant frequencies. Importantly, the batch effect causes substantial differences in germline variant distribution patterns across numerous genes, including prominent cancer predisposition genes such as BRCA1, RET, MAX, and KRAS. For most of known cancer predisposition genes, we found a distinct batch-dependent difference in germline variants.ConclusionTCGA germline data is exposed to strong batch effects with substantial variabilities among TCGA sequencing centers. We claim that those batch effects are consequential for numerous TCGA pan-cancer studies. In particular, these effects may compromise the reliability and the potency to detect new cancer predisposition genes. Furthermore, interpretation of pan-cancer analyses should be revisited in view of the source of the genomic data after accounting for the reported batch effects.

A pan-cancer study of copy number gain and up-regulation in human oncogenes

Life Sciences ◽  
2018 ◽  
Vol 211 ◽  
pp. 206-214 ◽  
Author(s):  
YongKiat Wee ◽  
TianFang Wang ◽  
Yining Liu ◽  
Xiaoyan Li ◽  
Min Zhao
Keyword(s):  
Copy Number ◽  
Copy Number Gain ◽  
Cancer Study ◽  
Pan Cancer

scholarly journals Chromosomal copy number heterogeneity predicts survival rates across cancers

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Erik van Dijk ◽  
Tom van den Bosch ◽  
Kristiaan J. Lenos ◽  
Khalid El Makrini ◽  
Lisanne E. Nijman ◽  
...  
Keyword(s):  
Copy Number ◽  
Cancer Survival ◽  
Survival Rates ◽  
Cancer Prognosis ◽  
Disease Outcomes ◽  
Distinct Disease ◽  
Cancer Types ◽  
Chromosomal Copy Number ◽  
Chromosomal Copy ◽  
Pan Cancer

AbstractSurvival rates of cancer patients vary widely within and between malignancies. While genetic aberrations are at the root of all cancers, individual genomic features cannot explain these distinct disease outcomes. In contrast, intra-tumour heterogeneity (ITH) has the potential to elucidate pan-cancer survival rates and the biology that drives cancer prognosis. Unfortunately, a comprehensive and effective framework to measure ITH across cancers is missing. Here, we introduce a scalable measure of chromosomal copy number heterogeneity (CNH) that predicts patient survival across cancers. We show that the level of ITH can be derived from a single-sample copy number profile. Using gene-expression data and live cell imaging we demonstrate that ongoing chromosomal instability underlies the observed heterogeneity. Analysing 11,534 primary cancer samples from 37 different malignancies, we find that copy number heterogeneity can be accurately deduced and predicts cancer survival across tissues of origin and stages of disease. Our results provide a unifying molecular explanation for the different survival rates observed between cancer types.

scholarly journals Identification of a Variety of Mutations in Cancer Predisposition Genes in Patients With Suspected Lynch Syndrome

2015 ◽  
Vol 149 (3) ◽  
pp. 604-613.e20 ◽  
Author(s):  
Matthew B. Yurgelun ◽  
Brian Allen ◽  
Rajesh R. Kaldate ◽  
Karla R. Bowles ◽  
Thaddeus Judkins ◽  
...  
Keyword(s):  
Lynch Syndrome ◽  
Cancer Predisposition ◽  
Predisposition Genes
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