scholarly journals Reconstructing cancer karyotypes from short read data: the half full and half empty glass

2017 ◽  
Author(s):  
Rami Eitan ◽  
Ron Shamir
Keyword(s):  
Cancer Progression ◽  
Copy Number ◽  
Point Mutations ◽  
Real Data ◽  
Cancer Genome ◽  
Patient Specific ◽  
Algorithmic Approach ◽  
Short Read ◽  
Base Scenario ◽  
Complete Accuracy

AbstractBackgroundDuring cancer progression genomes undergo point mutations as well as larger segmental changes. The latter include, among others, segmental deletions duplications, translocations and inversions. The result is a highly complex, patient-specific cancer karyotype. Using high-throughput technologies of deep sequencing and microarrays it is possible to interrogate a cancer genome and produce chromosomal copy number profiles and a list of breakpoints (“jumps”) relative to the normal genome. This information is very detailed but local, and does not give the overall picture of the cancer genome. One of the basic challenges in cancer genome research is to use such information to infer the cancer karyotype.We present here an algorithmic approach, based on graph theory and integer linear programming, that receives segmental copy number and breakpoint data as input and produces a cancer karyotype that is most concordant with them. We used simulations to evaluate the utility of our approach, and applied it to real data.ResultsBy using a simulation model, we were able to estimate the correctness and robustness of the algorithm in a spectrum of scenarios. Under our base scenario, designed according to observations in real data, the algorithm correctly inferred 69% of the karyotypes. However, when using less stringent correctness metrics that account for incomplete and noisy data, 87% of the reconstructed karyotypes were correct. Furthermore, in scenarios where the data were very clean and complete, accuracy rose to 90%-100%. Some examples of analysis of real data, and the karyotypes reconstructed by our algorithm, are also presented.ConclusionWhile reconstruction of complete, perfect karyotype based on short read data is very hard, a large portion of the reconstruction will still be correct and can provide useful information.

scholarly journals Cancer Genome Scanning in Plasma: Detection of Tumor-Associated Copy Number Aberrations, Single-Nucleotide Variants, and Tumoral Heterogeneity by Massively Parallel Sequencing

2013 ◽  
Vol 59 (1) ◽  
pp. 211-224 ◽  
Author(s):  
KC Allen Chan ◽  
Peiyong Jiang ◽  
Yama WL Zheng ◽  
Gary JW Liao ◽  
Hao Sun ◽  
...  
Keyword(s):  
Dna Sequencing ◽  
Cancer Patients ◽  
Copy Number ◽  
Massively Parallel Sequencing ◽  
Point Mutations ◽  
Cancer Genome ◽  
Massively Parallel ◽  
Plasma Dna ◽  
Parallel Sequencing ◽  
Copy Number Aberrations

BACKGROUND Tumor-derived DNA can be found in the plasma of cancer patients. In this study, we explored the use of shotgun massively parallel sequencing (MPS) of plasma DNA from cancer patients to scan a cancer genome noninvasively. METHODS Four hepatocellular carcinoma patients and a patient with synchronous breast and ovarian cancers were recruited. DNA was extracted from the tumor tissues, and the preoperative and postoperative plasma samples of these patients were analyzed with shotgun MPS. RESULTS We achieved the genomewide profiling of copy number aberrations and point mutations in the plasma of the cancer patients. By detecting and quantifying the genomewide aggregated allelic loss and point mutations, we determined the fractional concentrations of tumor-derived DNA in plasma and correlated these values with tumor size and surgical treatment. We also demonstrated the potential utility of this approach for the analysis of complex oncologic scenarios by studying the patient with 2 synchronous cancers. Through the use of multiregional sequencing of tumoral tissues and shotgun sequencing of plasma DNA, we have shown that plasma DNA sequencing is a valuable approach for studying tumoral heterogeneity. CONCLUSIONS Shotgun DNA sequencing of plasma is a potentially powerful tool for cancer detection, monitoring, and research.

scholarly journals Patient-Specific Network for Personalized Breast Cancer Therapy with Multi-Omics Data

Entropy ◽  
2021 ◽  
Vol 23 (2) ◽  
pp. 225
Author(s):  
Claudia Cava ◽  
Soudabeh Sabetian ◽  
Isabella Castiglioni
Keyword(s):  
Breast Cancer ◽  
Cancer Therapy ◽  
Protein Interaction Network ◽  
Copy Number ◽  
Tumor Heterogeneity ◽  
Copy Number Alteration ◽  
Interaction Network ◽  
Computational Approach ◽  
Patient Specific ◽  
Basal Breast Cancer

The development of new computational approaches that are able to design the correct personalized drugs is the crucial therapeutic issue in cancer research. However, tumor heterogeneity is the main obstacle to developing patient-specific single drugs or combinations of drugs that already exist in clinics. In this study, we developed a computational approach that integrates copy number alteration, gene expression, and a protein interaction network of 73 basal breast cancer samples. 2509 prognostic genes harboring a copy number alteration were identified using survival analysis, and a protein–protein interaction network considering the direct interactions was created. Each patient was described by a specific combination of seven altered hub proteins that fully characterize the 73 basal breast cancer patients. We suggested the optimal combination therapy for each patient considering drug–protein interactions. Our approach is able to confirm well-known cancer related genes and suggest novel potential drug target genes. In conclusion, we presented a new computational approach in breast cancer to deal with the intra-tumor heterogeneity towards personalized cancer therapy.

scholarly journals Transformed Canine and Murine Mesenchymal Stem Cells as a Model for Sarcoma with Complex Genomics

Cancers ◽  
2021 ◽  
Vol 13 (5) ◽  
pp. 1126
Author(s):  
Natasja Franceschini ◽  
Bas Verbruggen ◽  
Marianna A. Tryfonidou ◽  
Alwine B. Kruisselbrink ◽  
Hans Baelde ◽  
...  
Keyword(s):  
Copy Number ◽  
Point Mutations ◽  
Comparative Approach ◽  
Cell Of Origin ◽  
Mesenchymal Tumors ◽  
Spontaneous Transformation ◽  
Exon 2 ◽  
Species Analysis ◽  
Gains And Losses

Sarcomas are rare mesenchymal tumors with a broad histological spectrum, but they can be divided into two groups based on molecular pathology: sarcomas with simple or complex genomics. Tumors with complex genomics can have aneuploidy and copy number gains and losses, which hampers the detection of early, initiating events in tumorigenesis. Often, no benign precursors are known, which is why good models are essential. The mesenchymal stem cell (MSC) is the presumed cell of origin of sarcoma. In this study, MSCs of murine and canine origin are used as a model to identify driver events for sarcomas with complex genomic alterations as they transform spontaneously after long-term culture. All transformed murine but not canine MSCs formed sarcomas after subcutaneous injection in mice. Using whole genome sequencing, spontaneously transformed murine and canine MSCs displayed a complex karyotype with aneuploidy, point mutations, structural variants, inter-chromosomal translocations, and copy number gains and losses. Cross-species analysis revealed that point mutations in Tp53/Trp53 are common in transformed murine and canine MSCs. Murine MSCs with a cre-recombinase induced deletion of exon 2-10 of Trp53 transformed earlier compared to wild-type murine MSCs, confirming the contribution of loss of p53 to spontaneous transformation. Our comparative approach using transformed murine and canine MSCs points to a crucial role for p53 loss in the formation of sarcomas with complex genomics.

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 Integrated multi-omics analyses on patient-derived CRC organoids highlight altered molecular pathways in colorectal cancer progression involving PTEN

2021 ◽  
Vol 40 (1) ◽  
Author(s):  
Marta Codrich ◽  
Emiliano Dalla ◽  
Catia Mio ◽  
Giulia Antoniali ◽  
Matilde Clarissa Malfatti ◽  
...  
Keyword(s):  
Colorectal Cancer ◽  
Cancer Progression ◽  
Cell Model ◽  
Patient Specific ◽  
Driver Genes ◽  
Proteomic Data ◽  
Whole Exome ◽  
Molecular Stability ◽  
Culturing Conditions ◽  
Colorectal Cancer Progression

Abstract Background Colorectal cancer (CRC) represents the fourth leading cause of cancer-related deaths. The heterogeneity of CRC identity limits the usage of cell lines to study this type of tumor because of the limited representation of multiple features of the original malignancy. Patient-derived colon organoids (PDCOs) are a promising 3D-cell model to study tumor identity for personalized medicine, although this approach still lacks detailed characterization regarding molecular stability during culturing conditions. Correlation analysis that considers genomic, transcriptomic, and proteomic data, as well as thawing, timing, and culturing conditions, is missing. Methods Through integrated multi–omics strategies, we characterized PDCOs under different growing and timing conditions, to define their ability to recapitulate the original tumor. Results Whole Exome Sequencing allowed detecting temporal acquisition of somatic variants, in a patient-specific manner, having deleterious effects on driver genes CRC-associated. Moreover, the targeted NGS approach confirmed that organoids faithfully recapitulated patients’ tumor tissue. Using RNA-seq experiments, we identified 5125 differentially expressed transcripts in tumor versus normal organoids at different time points, in which the PTEN pathway resulted of particular interest, as also confirmed by further phospho-proteomics analysis. Interestingly, we identified the PTEN c.806_817dup (NM_000314) mutation, which has never been reported previously and is predicted to be deleterious according to the American College of Medical Genetics and Genomics (ACMG) classification. Conclusion The crosstalk of genomic, transcriptomic and phosphoproteomic data allowed to observe that PDCOs recapitulate, at the molecular level, the tumor of origin, accumulating mutations over time that potentially mimic the evolution of the patient’s tumor, underlining relevant potentialities of this 3D model.

scholarly journals CNV-BAC: Copy number Variation Detection in Bacterial Circular Genome

2020 ◽  
Vol 36 (12) ◽  
pp. 3890-3891
Author(s):  
Linjie Wu ◽  
Han Wang ◽  
Yuchao Xia ◽  
Ruibin Xi
Keyword(s):  
Copy Number Variation ◽  
Copy Number ◽  
Genome Structure ◽  
Real Data ◽  
Read Depth ◽  
Supplementary Information ◽  
Circular Genome ◽  
Number Variation ◽  
Copy Number Variation Detection ◽  
Cnv Detection

Abstract Motivation Whole-genome sequencing (WGS) is widely used for copy number variation (CNV) detection. However, for most bacteria, their circular genome structure and high replication rate make reads more enriched near the replication origin. CNV detection based on read depth could be seriously influenced by such replication bias. Results We show that the replication bias is widespread using ∼200 bacterial WGS data. We develop CNV-BAC (CNV-Bacteria) that can properly normalize the replication bias and other known biases in bacterial WGS data and can accurately detect CNVs. Simulation and real data analysis show that CNV-BAC achieves the best performance in CNV detection compared with available algorithms. Availability and implementation CNV-BAC is available at https://github.com/XiDsLab/CNV-BAC. Supplementary information Supplementary data are available at Bioinformatics online.

scholarly journals SNP array analysis in hematologic malignancies: avoiding false discoveries

Blood ◽  
2010 ◽  
Vol 115 (21) ◽  
pp. 4157-4161 ◽  
Author(s):  
Stefan Heinrichs ◽  
Cheng Li ◽  
A. Thomas Look
Keyword(s):  
Single Nucleotide Polymorphism ◽  
High Resolution ◽  
Snp Array ◽  
Hematologic Malignancies ◽  
Cancer Genome ◽  
Patient Specific ◽  
Nucleotide Polymorphism ◽  
Array Analysis ◽  
Single Nucleotide ◽  
Therapeutic Decisions

Comprehensive analysis of the cancer genome has become a standard approach to identifying new disease loci, and ultimately will guide therapeutic decisions. A key technology in this effort, single nucleotide polymorphism arrays, has been applied in hematologic malignancies to detect deletions, amplifications, and loss of heterozygosity (LOH) at high resolution. An inherent challenge of such studies lies in correctly distinguishing somatically acquired, cancer-specific lesions from patient-specific inherited copy number variations or segments of homozygosity. Failure to include appropriate normal DNA reference samples for each patient in retrospective or prospective studies makes it difficult to identify small somatic deletions not evident by standard cytogenetic analysis. In addition, the lack of proper controls can also lead to vastly overestimated frequencies of LOH without accompanying loss of DNA copies, so-called copy-neutral LOH. Here we use examples from patients with myeloid malignancies to demonstrate the superiority of matched tumor and normal DNA samples (paired studies) over multiple unpaired samples with respect to reducing false discovery rates in high-resolution single nucleotide polymorphism array analysis. Comparisons between matched tumor and normal samples will continue to be critical as the field moves from high resolution array analysis to deep sequencing to detect abnormalities in the cancer genome.

Analysis of point mutations and copy number variation in Grade II and III meningioma

2018 ◽  
Vol 105 (3) ◽  
pp. 328-333 ◽  
Author(s):  
Samantha N. McNulty ◽  
Katherine Schwetye ◽  
Michael Goldstein ◽  
Jamal Carter ◽  
Robert E. Schmidt ◽  
...  
Keyword(s):  
Copy Number Variation ◽  
Copy Number ◽  
Point Mutations ◽  
Number Variation ◽  
Grade Ii

scholarly journals A genetic-algorithm approach to simulating human immunodeficiency virus evolution reveals the strong impact of multiply infected cells and recombination

2005 ◽  
Vol 86 (11) ◽  
pp. 3109-3118 ◽  
Author(s):  
Gennady Bocharov ◽  
Neville J. Ford ◽  
John Edwards ◽  
Tanja Breinig ◽  
Simon Wain-Hobson ◽  
...  
Keyword(s):  
Human Immunodeficiency Virus ◽  
Copy Number ◽  
Hamming Distance ◽  
Point Mutations ◽  
Strong Impact ◽  
Hiv Replication ◽  
Immunodeficiency Virus ◽  
Genetic Algorithm Approach ◽  
Infected Cells

It has been previously shown that the majority of human immunodeficiency virus type 1 (HIV-1)-infected splenocytes can harbour multiple, divergent proviruses with a copy number ranging from one to eight. This implies that, besides point mutations, recombination should be considered as an important mechanism in the evolution of HIV within an infected host. To explore in detail the possible contributions of multi-infection and recombination to HIV evolution, the effects of major microscopic parameters of HIV replication (i.e. the point-mutation rate, the crossover number, the recombination rate and the provirus copy number) on macroscopic characteristics (such as the Hamming distance and the abundance of n-point mutants) have been simulated in silico. Simulations predict that multiple provirus copies per infected cell and recombination act in synergy to speed up the development of sequence diversity. Point mutations can be fixed for some time without fitness selection. The time needed for the selection of multiple mutations with increased fitness is highly variable, supporting the view that stochastic processes may contribute substantially to the kinetics of HIV variation in vivo.

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