scholarly journals Profiling copy number alterations in cell-free tumour DNA using a single-reference

2018 ◽  
Author(s):  
Alan J Robertson ◽  
Qinying Xu ◽  
Sarah Song ◽  
Devika Ganesamoorthy ◽  
Derek Benson ◽  
...  
Keyword(s):  
Cancer Patients ◽  
Copy Number ◽  
Read Depth ◽  
Reference Panel ◽  
Plasma Samples ◽  
Copy Number Profile ◽  
Copy Number Alterations ◽  
Healthy Individuals ◽  
A Cell ◽  
Sequencing Platforms

AbstractBackgroundThe accurate detection of copy number alterations from the analysis of circulating cell free tumour DNA (ctDNA) in blood is essential to realising the potential of liquid biopsies. However, currently available approaches require a large number of plasma samples from healthy individuals, sequenced using the same platform and protocols to act as a reference panel. Obtaining this reference panel can be challenging, prohibitively expensive and limits the ability to migrate to improved sequencing platforms and improved protocols.MethodsWe developed qCNV and sCNA-seq, two distinct tools that together provide a new approach for profiling somatic copy number alterations (sCNA) through the analysis of cell free DNA (cfDNA) without a reference panel. Our approach was designed to identify sCNA from cfDNA through the analysis of a single plasma sample and a matched normal DNA sample -both of which can be obtained from the same blood draw. qCNV is an efficient method for extracting read-depth from BAM files and sCNA-seq is a method that uses a probabilistic model of read depth to infer the copy number segmentation of the tumour. We compared the results from our pipeline to the established copy number profile of a cell-line, as well as the results from the plasma-Seq analysis of cfDNA-like mixtures and real, clinical data-sets.ResultsWith a single, unmatched, germline reference sample, our pipeline recapitulated the known copy number profile of a cell-line and demonstrated similar results to those obtained from plasma-Seq. With less than 1X genome coverage, our approach identified clinically relevant sCNA in samples with as little as 20 % tumour DNA. When applied to plasma samples from cancer patients, our pipeline identified clinically significant mutations.ConclusionsThese results show it is possible to identify therapeutically-relevant copy number mutations from plasma samples without the need to generate a reference panel from a large number of healthy individuals. Together with the range of sequencing platforms supported by our qCNV+sCNA-Seq pipeline, as well as the Galaxy implementation of this solution, this pipeline makes cfDNA profiling more accessible and makes it easier to identify sCNA from the plasma of cancer patients.

scholarly journals Tumor copy-number alterations predict response to immune-checkpoint-blockade in gastrointestinal cancer

2020 ◽  
Vol 8 (2) ◽  
pp. e000374 ◽  
Author(s):  
Zhihao Lu ◽  
Huan Chen ◽  
Shuang Li ◽  
Jifang Gong ◽  
Jian Li ◽  
...  
Keyword(s):  
Cancer Patients ◽  
Immune Checkpoint ◽  
Clinical Benefit ◽  
Copy Number ◽  
Validation Cohort ◽  
Predictive Biomarkers ◽  
Immune Checkpoint Blockade ◽  
Checkpoint Blockade ◽  
Copy Number Alterations ◽  
Gi Cancer

BackgroundDespite the great achievements made in immune-checkpoint-blockade (ICB) in cancer therapy, there are no effective predictive biomarkers in gastrointestinal (GI) cancer.MethodsThis study included 93 metastatic GI patients treated with ICBs. The first cohort comprising 73 GI cancer patients were randomly assigned into discovery (n=44) and validation (n=29) cohorts. Comprehensive genomic profiling was performed on all samples to determine tumor mutational burden (TMB) and copy-number alterations (CNAs). A subset of samples was collected for RNA immune oncology (IO) panel sequencing, microsatellite instability (MSI)/mismatch repair and program death ligand 1 (PD-L1) expression evaluation. In addition, 20 gastric cancer (GC) patients were recruited as the second validation cohort.ResultsIn the first cohort of 73 GI cancer patients, a lower burden of CNA was observed in patients with durable clinical benefit (DCB). In both the discovery (n=44) and validation (n=29) subsets, lower burden of CNA was associated with an improved clinical benefit and better overall survival (OS). Efficacy also correlated with a higher TMB. Of note, a combinatorial biomarker of TMB and CNA may better stratify DCB patients from ICB treatment, which was further confirmed in the second validation cohort of 20 GC patients. Finally, patients with lower burden of CNA revealed increased immune signatures in our cohort and The Cancer Genome Atlas data sets as well.ConclusionsOur results suggest that the burden of CNA may have superior predictive value compared with other signatures, including PD-L1, MSI and TMB. The joint biomarker of CNA burden and TMB may better stratify DCB patients, thereby providing a rational choice for GI patients treated with ICBs.

scholarly journals High Levels of Chromosomal Copy Number Alterations and TP53 Mutations Correlate with Poor Outcome in Younger Breast Cancer Patients

2020 ◽  
Vol 190 (8) ◽  
pp. 1643-1656
Author(s):  
Ayla Koçak ◽  
Kerstin Heselmeyer-Haddad ◽  
Annette Lischka ◽  
Daniela Hirsch ◽  
David Fiedler ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Cancer Patients ◽  
Copy Number ◽  
Copy Number Alterations ◽  
Breast Cancer Patients ◽  
Tp53 Mutations ◽  
Poor Outcome ◽  
Chromosomal Copy Number ◽  
Chromosomal Copy

scholarly journals Integrated sequence and gene expression analysis of mouse models of breast cancer reveals critical events with human parallels

2018 ◽  
Author(s):  
Jonathan P Rennhack ◽  
Matthew Swiatnicki ◽  
Yueqi Zhang ◽  
Caralynn Li ◽  
Evan Bylett ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Lung Cancer ◽  
Cancer Patients ◽  
Mouse Models ◽  
Copy Number ◽  
Human Breast Cancer ◽  
Human Cancer ◽  
Copy Number Alterations ◽  
Human Breast ◽  
Lung Cancer Patients

AbstractMouse models have an essential role in cancer research, yet little is known about how various models resemble human cancer at a genomic level. However, the shared genomic alterations in each model and corresponding human cancer are critical for translating findings in mice to the clinic. We have completed whole genome sequencing and transcriptome profiling of two widely used mouse models of breast cancer, MMTV-Neu and MMTV-PyMT. This genomic information was integrated with phenotypic data and CRISPR/Cas9 studies to understand the impact of key events on tumor biology. Despite the engineered initiating transgenic event in these mouse models, they contain similar copy number alterations, single nucleotide variants, and translocation events as human breast cancer. Through integrative in vitro and in vivo studies, we identified copy number alterations in key extracellular matrix proteins including Collagen 1 Type 1 alpha 1 (Col1a1) and Chondroadherin (CHAD) that drive metastasis in these mouse models. Importantly this amplification is also found in 25% of HER2+ human breast cancer and is associated with increased metastasis. In addition to copy number alterations, we observed a propensity of the tumors to modulate tyrosine kinase mediated signaling through mutation of phosphatases. Specifically, we found that 81% of MMTV-PyMT tumors have a mutation in the EGFR regulatory phosphatase, PTPRH. Mutation in PTPRH led to increased phospho-EGFR levels and decreased latency. Moreover, PTPRH mutations increased response to EGFR kinase inhibitors. Analogous PTPRH mutations are present in lung cancer patients and together this data suggests that a previously unidentified population of human lung cancer patients may respond to EGFR targeted therapy. These findings underscore the importance of understanding the complete genomic landscape of a mouse model and illustrate the utility this has in understanding human cancers.

scholarly journals Single-cell copy number calling and event history reconstruction

2020 ◽  
Author(s):  
Jack Kuipers ◽  
Mustafa Anıl Tuncel ◽  
Pedro Ferreira ◽  
Katharina Jahn ◽  
Niko Beerenwinkel
Keyword(s):  
Dna Sequencing ◽  
Single Cell ◽  
Copy Number ◽  
Driving Forces ◽  
Simulated Data ◽  
Read Depth ◽  
Cancer Diagnostics ◽  
Whole Genome ◽  
Copy Number Alterations ◽  
Sequencing Data

Copy number alterations are driving forces of tumour development and the emergence of intra-tumour heterogeneity. A comprehensive picture of these genomic aberrations is therefore essential for the development of personalised and precise cancer diagnostics and therapies. Single-cell sequencing offers the highest resolution for copy number profiling down to the level of individual cells. Recent high-throughput protocols allow for the processing of hundreds of cells through shallow whole-genome DNA sequencing. The resulting low read-depth data poses substantial statistical and computational challenges to the identification of copy number alterations. We developed SCICoNE, a statistical model and MCMC algorithm tailored to single-cell copy number profiling from shallow whole-genome DNA sequencing data. SCICoNE reconstructs the history of copy number events in the tumour and uses these evolutionary relationships to identify the copy number profiles of the individual cells. We show the accuracy of this approach in evaluations on simulated data and demonstrate its practicability in applications to a xenograft breast cancer sample.

scholarly journals Combined landscape of single-nucleotide variants and copy-number alterations in clonal hematopoiesis

2021 ◽  
Author(s):  
Ryunosuke Saiki ◽  
Yukihide Momozawa ◽  
Yasuhito Nannya ◽  
Masahiro M Nakagawa ◽  
Yotaro Ochi ◽  
...  
Keyword(s):  
Cardiovascular Diseases ◽  
Copy Number ◽  
Blood Count ◽  
Hematological Malignancies ◽  
Copy Number Alterations ◽  
Healthy Individuals ◽  
Single Nucleotide Variants ◽  
Single Nucleotide ◽  
Clonal Hematopoiesis ◽  
Apparently Healthy

AbstractImplicated in the development of hematological malignancies (HM) and cardiovascular mortality, clonal hematopoiesis (CH) in apparently healthy individuals has been investigated by detecting either single-nucleotide variants and indels (SNVs/indels) or copy number alterations (CNAs), but not both. Here by combining targeted sequencing of 23 CH-related genes and array-based CNA detection of blood-derived DNA, we have delineated the landscape of CH-related SNVs/indels and CNAs in a general population of 11,234 individuals, including 672 with subsequent HM development. Both CH-related lesions significantly co-occurred, which combined, affected blood count, hypertension, and the mortality from HM and cardiovascular diseases depending on the total number of both lesions, highlighting the importance of detecting both lesions in the evaluation of CH.

scholarly journals Copy number alterations in cancer: detection and precision medicine

2021 ◽  
Vol 41 ◽  
pp. 02005
Author(s):  
Arief Gusnanto
Keyword(s):  
Next Generation Sequencing ◽  
Precision Medicine ◽  
Cancer Patients ◽  
Cancer Detection ◽  
Copy Number ◽  
Copy Number Alterations ◽  
Genomic Alterations ◽  
Genomic Markers ◽  
Next Generation Sequencing Ngs ◽  
Generation Sequencing

Copy number alterations (CNAs) are genomic alterations where some regions exhibit more or less copy number than the normal two copies. In this talk, I will describe two ideas: (1) how CNAs are estimated from data generated by next generation sequencing (NGS) and what steps are required to make the data interpretable, (2) how the CNA can be utilised for precision medicine in terms of prediction of tumour subtypes and prediction of cancer patients’ survival. If time permits, I will also discuss how to estimate genomic markers from CNA profile across cancer patients.

Concurrent DNA Copy-Number Alterations and Mutations in Genes Related to Maintenance of Genome Stability in Uninvolved Mammary Glandular Tissue from Breast Cancer Patients

2015 ◽  
Vol 36 (11) ◽  
pp. 1088-1099 ◽  
Author(s):  
Anna Ronowicz ◽  
Anna Janaszak-Jasiecka ◽  
Jarosław Skokowski ◽  
Piotr Madanecki ◽  
Rafal Bartoszewski ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Cancer Patients ◽  
Copy Number ◽  
Genome Stability ◽  
Glandular Tissue ◽  
Copy Number Alterations ◽  
Breast Cancer Patients ◽  
Dna Copy Number ◽  
Dna Copy Number Alterations

scholarly journals Detecting copy number alterations in RNA-Seq using SuperFreq

2020 ◽  
Author(s):  
Christoffer Flensburg ◽  
Alicia Oshlack ◽  
Ian J. Majewski
Keyword(s):  
Copy Number ◽  
Point Mutations ◽  
Variant Calling ◽  
Read Depth ◽  
The Cancer Genome Atlas ◽  
Nucleotide Polymorphisms ◽  
Rna Seq ◽  
Copy Number Alterations ◽  
Cancer Genome Atlas ◽  
High Level

AbstractCalling copy number alterations (CNAs) from RNA-Seq is challenging, because differences in gene expression mean that read depth across genes varies by several orders of magnitude and there is a paucity of informative single nucleotide polymorphisms (SNPs). We previously developed SuperFreq to analyse exome data of tumours by combining variant calling and copy number estimation in an integrated pipeline. Here we have used the SuperFreq framework for the analysis of RNA sequencing (RNA-Seq) data, which allows for the detection of absolute and allele sensitive CNAs. SuperFreq uses an error-propagation framework to combine and maximise the information available in the read depth and B-allele frequencies of SNPs (BAFs) to make CNA calls on RNA-seq data. We used data from The Cancer Genome Atlas (TCGA) to evaluate the CNA called from RNA-Seq with those generated from SNP-arrays. When ploidy estimates were consistent, we found excellent agreement with CNAs called from DNA of over 98% of the genome for acute myeloid leukaemia (TCGA-AML, n=116) and 87% for colorectal cancer (TCGA-CRC, n=377), which has a much higher CNA burden. As expected, the sensitivity of CNA calling from RNA-Seq was dependent on gene density. Nonetheless, using RNA-Seq SuperFreq detected 78% of CNA calls covering 100 or more genes with a precision of 94%. Recall dropped markedly for focal events, but this also depended on the signal intensity. For example, in the CRC cohort SuperFreq identified 100% (7/7) of cases with high-level amplification of ERBB2, where the copy number was typically >20, but identified only 6% (1/17) of cases with moderate amplification of IGF2, typically 4 or 5 copies over a smaller region (median 5 flanking genes for IGF2, compared to 20 for ERBB2). We were able to reproduce the relationship between mutational load and CNA profile in CRC using RNA-Seq alone. SuperFreq offers an integrated platform for identification of CNAs and point mutations from RNA-seq in cancer transcriptomes.The software is implemented in R and is available through GitHub: https://github.com/ChristofferFlensburg/SuperFreq.

scholarly journals Correlation of HER2, MDM2, c-MYC, c-MET, and TP53 Copy Number Alterations in Circulating Tumor Cells with Tissue in Gastric Cancer Patients: A Pilot Study

2020 ◽  
Vol 24 (1) ◽  
pp. 47-53 ◽  
Author(s):  
Fatemeh Nevisi ◽  
Marjan Yaghmaie ◽  
Hossein Pashaiefar ◽  
Kamran Alimoghaddam ◽  
Masoud Iravani ◽  
...  
Keyword(s):  
Gastric Cancer ◽  
Pilot Study ◽  
Cancer Patients ◽  
Tumor Cells ◽  
Circulating Tumor Cells ◽  
Copy Number ◽  
Copy Number Alterations ◽  
Gastric Cancer Patients
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