scholarly journals Aneuploidy Spectrum Analysis as a Primer for Copy Number Profiling of Cancer Cells

2019 ◽  
Author(s):  
Ahmed Ibrahim Samir Khalil ◽  
Anupam Chattopadhyay ◽  
Amartya Sanyal
Keyword(s):  
Cancer Cells ◽  
Cell Lines ◽  
Cancer Cell ◽  
Ploidy Level ◽  
Copy Number ◽  
Sequencing Data ◽  
High Coverage ◽  
Cancer Data ◽  
Number Variation ◽  
Genome Ploidy

AbstractMotivationHyperploidy and segmental aneuploidy are hallmarks of cancer cells due to chromosome segregation errors and genomic instability. In such situations, accurate aneuploidy profiling of cancer data is critical for calibration of copy number (CN)-detection tools. Additionally, cancer cell populations suffer from different levels of clonal heterogeneity and aneuploidy alterations over time. The degree of heterogeneity adversely affects the segregation of the depth of coverage (DOC) signal into integral CN states. This, in turn, strongly influences the reliability of this data for ploidy profiling and copy number variation (CNV) analysis.ResultsWe developed AStra framework for aneuploidy profiling of cancer data and assessing their suitability for copy number analysis without any prior knowledge of the input sequencing data. AStra estimates the best-fit aneuploidy profile as the spectrum with most genomic segments around integral CN states. We employ this spectrum to extract the CN-associated features such as the homogeneity score (HS), whole-genome ploidy level, and CN correction factor. The HS measures the percentage of genomic regions around CN states. It is used as a reliability assessment of sequencing data for downstream aneuploidy profiling and CNV analysis. We evaluated the accuracy of AStra using 31 low-coverage datasets from 20 cancer cell lines. AStra successfully identified the aneuploidy spectrum of complex cell lines with HS greater than 75%. Benchmarking against nQuire tool showed that AStra is superior in detecting the ploidy level using both low- and high-coverage data. Furthermore, AStra accurately estimated the ploidy of 26/27 strains of MCF7 (hyperploid) cell line which exhibit varied levels of aneuploidy spectrum and heterogeneity. Remarkably, we found that HS is strongly correlated with the doubling time of these strains.Availability and implementationAStra is an open source software implemented in Python and is available at https://github.com/AISKhalil/AStra

Abstract 2993: Comparison of copy number variation using exome sequencing and affymetrix SNP6.0 genotype array in human cancer cell lines

2012 ◽  
Author(s):  
Jian Wang ◽  
Thompson N. Doman ◽  
Xiwen Ma ◽  
Dan S. Li ◽  
Amit Aggarwal ◽  
...  
Keyword(s):  
Copy Number Variation ◽  
Exome Sequencing ◽  
Cell Lines ◽  
Cancer Cell ◽  
Copy Number ◽  
Human Cancer ◽  
Human Cancer Cell ◽  
Human Cancer Cell Lines ◽  
Number Variation ◽  
Genotype Array

scholarly journals High Resolution Copy Number Variation Data in the NCI-60 Cancer Cell Lines from Whole Genome Microarrays Accessible through CellMiner

PLoS ONE ◽  
2014 ◽  
Vol 9 (3) ◽  
pp. e92047 ◽  
Author(s):  
Sudhir Varma ◽  
Yves Pommier ◽  
Margot Sunshine ◽  
John N. Weinstein ◽  
William C. Reinhold
Keyword(s):  
High Resolution ◽  
Copy Number Variation ◽  
Cell Lines ◽  
Cancer Cell ◽  
Copy Number ◽  
Cancer Cell Lines ◽  
Whole Genome ◽  
Variation Data ◽  
Number Variation ◽  
Copy Number Variation Data

scholarly journals Identification of copy number variations and translocations in cancer cells from Hi-C data

2017 ◽  
Author(s):  
Abhijit Chakraborty ◽  
Ferhat Ay
Keyword(s):  
Cancer Cells ◽  
Cell Lines ◽  
Cancer Cell ◽  
Copy Number ◽  
De Novo ◽  
3D Structure ◽  
Cancer Cell Lines ◽  
Copy Number Variations ◽  
Genomic Rearrangements ◽  
Link Type

AbstractMotivationEukaryotic chromosomes adapt a complex and highly dynamic three-dimensional (3D) structure, which profoundly affects different cellular functions and outcomes including changes in epigenetic landscape and in gene expression. Making the scenario even more complex, cancer cells harbor chromosomal abnormalities (e.g., copy number variations (CNVs) and translocations) altering their genomes both at the sequence level and at the level of 3D organization. High-throughput chromosome conformation capture techniques (e.g., Hi-C), which are originally developed for decoding the 3D structure of the chromatin, provide a great opportunity to simultaneously identify the locations of genomic rearrangements and to investigate the 3D genome organization in cancer cells. Even though Hi-C data has been used for validating known rearrangements, computational methods that can distinguish rearrangement signals from the inherent biases of Hi-C data and from the actual 3D conformation of chromatin, and can precisely detect rearrangement locations de novo have been missing.ResultsIn this work, we characterize how intra and inter-chromosomal Hi-C contacts are distributed for normal and rearranged chromosomes to devise a new set of algorithms (i) to identify genomic segments that correspond to CNV regions such as amplifications and deletions (HiCnv), (ii) to call inter-chromosomal translocations and their boundaries (HiCtrans) from Hi-C experiments, and (iii) to simulate Hi-C data from genomes with desired rearrangements and abnormalities (AveSim) in order to select optimal parameters for and to benchmark the accuracy of our methods. Our results on 10 different cancer cell lines with Hi-C data show that we identify a total number of 105 amplifications and 45 deletions together with 90 translocations, whereas we identify virtually no such events for two karyotypically normal cell lines. Our CNV predictions correlate very well with whole genome sequencing (WGS) data among chromosomes with CNV events for a breast cancer cell line (r=0.89) and capture most of the CNVs we simulate using Avesim. For HiCtrans predictions, we report evidence from the literature for 30 out of 90 translocations for eight of our cancer cell lines. Further-more, we show that our tools identify and correctly classify relatively understudied rearrangements such as double minutes (DMs) and homogeneously staining regions (HSRs).ConclusionsConsidering the inherent limitations of existing techniques for karyotyping (i.e., missing balanced rearrangements and those near repetitive regions), the accurate identification of CNVs and translocations in a cost-effective and high-throughput setting is still a challenge. Our results show that the set of tools we develop effectively utilize moderately sequenced Hi-C libraries (100-300 million reads) to identify known and de novo chromosomal rearrangements/abnormalities in well-established cancer cell lines. With the decrease in required number of cells and the increase in attainable resolution, we believe that our framework will pave the way towards comprehensive mapping of genomic rearrangements in primary cells from cancer patients using Hi-C.AvailabilityCNV calling: https://github.com/ay-lab/HiCnvTranslocation calling: https://github.com/ay-lab/HiCtransHi-C simulation: https://github.com/ay-lab/AveSim

scholarly journals P16 methylation increases the sensitivity of cancer cells to the CDK4/6 inhibitor palbociclib

2019 ◽  
Author(s):  
Paiyun Li ◽  
Xuehong Zhang ◽  
Liankun Gu ◽  
Jing Zhou ◽  
Dajun Deng
Keyword(s):  
Dna Methylation ◽  
Cancer Cells ◽  
Cell Lines ◽  
Cancer Cell ◽  
Copy Number ◽  
Dna Methyltransferase ◽  
Gastric Cancer Cell Line ◽  
Cancer Cell Line ◽  
Cancer Cell Lines ◽  
Gene Copy

AbstractThe P16 (CDKN2Aink4a) gene is an endogenous CDK4/6 inhibitor. Palbociclib (PD0332991) is an anti-CDK4/6 chemical for cancer treatment. P16 is most frequently inactivated by copy number deletion and DNA methylation in cancers. It is well known that cancer cells with P16 deletion are more sensitive to palbociclib than those without. However, whether P16 methylation is related to palbociclib sensitivity is not known. By analyzing public pharmacogenomic datasets, we found that the IC50 of palbociclib in cancer cell lines (n=522) was positively correlated with both the P16 expression level and P16 gene copy number. Our experimental results further showed that cancer cell lines with P16 methylation were more sensitive to palbociclib than those without. To determine whether P16 methylation directly increased the sensitivity of cancer cells to palbociclib, we induced P16 methylation in the lung cancer cell lines H661 and HCC827 and the gastric cancer cell line BGC823 via an engineered P16-specific DNA methyltransferase (P16-Dnmt) and found that the sensitivity of these cells to palbociclib was significantly increased. The survival rate of P16-Dnmt cells was significantly lower than that of vector control cells 48 hrs post treatment with palbociclib (10 μM). Notably, palbociclib treatment also selectively inhibited the proliferation of the P16-methylated subpopulation of P16-Dnmt cells, further indicating that P16 methylation can increase the sensitivity of cells to this CDK4/6 inhibitor. These results were confirmed in an animal experiment. In conclusion, inactivation of the P16 gene by DNA methylation can increase the sensitivity of cancer cells to palbociclib.

scholarly journals GMIEC: a shiny application for the identification of gene-targeted drugs for precision medicine

BMC Genomics ◽  
2020 ◽  
Vol 21 (1) ◽  
Author(s):  
Guidantonio Malagoli Tagliazucchi ◽  
Cristian Taccioli
Keyword(s):  
Precision Medicine ◽  
Copy Number ◽  
Next Generation Sequencing Data ◽  
Sequencing Data ◽  
Data Set ◽  
Cancer Data ◽  
R Shiny ◽  
Number Variation ◽  
New Treatments ◽  
Shiny Application

Abstract Background Precision medicine is a medical approach that takes into account individual genetic variability and often requires Next Generation Sequencing data in order to predict new treatments. Here we present GMIEC, Genomic Modules Identification et Characterization for genomics medicine, an application that is able to identify specific drugs at the level of single patient integrating multi-omics data such as RNA-sequencing, copy-number variation, methylation, Chromatin Immuno-Precipitation and Exome/Whole Genome sequencing. It is also possible to include clinical data related to each patient. GMIEC has been developed as a web-based R-Shiny platform and gives as output a table easy to use and explore. Results We present GMIEC, a Shiny application for genomics medicine. The tool allows the users the integration of two or more multiple omics datasets (e.g. gene-expression, copy-number), at sample level, to identify groups of genes that share common genomic and corresponding drugs. We demonstrate the characteristics of our application by using it to analyze a prostate cancer data set. Conclusions GMIEC provides a simple interface for genomics medicine. GMIEC was develop with Shiny to provide an application that does not require advanced programming skills. GMIEC consists of three sub-application for the analysis (GMIEC-AN), the visualization (GMIEC-VIS) and the exploration of results (GMIEC-RES). GMIEC is an open source software and is available at https://github.com/guidmt/GMIEC-shiny

scholarly journals DeCiFering the Elusive Cancer Cell Fraction in Tumor Heterogeneity and Evolution

2021 ◽  
Author(s):  
Gryte Satas ◽  
Simone Zaccaria ◽  
Mohammed El-Kebir ◽  
Benjamin J. Raphael
Keyword(s):  
Phylogenetic Analysis ◽  
Cancer Cells ◽  
Cancer Cell ◽  
Copy Number ◽  
Tumor Heterogeneity ◽  
Cell Fraction ◽  
Tumor Evolution ◽  
Sequencing Data ◽  
Single Nucleotide Variants ◽  
Cancer Cell Fraction

AbstractMost tumors are heterogeneous mixtures of normal cells and cancer cells, with individual cancer cells distinguished by somatic mutations that accumulated during the evolution of the tumor. The fundamental quantity used to measure tumor heterogeneity from somatic single-nucleotide variants (SNVs) is the Cancer Cell Fraction (CCF), or proportion of cancer cells that contain the SNV. However, in tumors containing copy-number aberrations (CNAs) – e.g. most solid tumors – the estimation of CCFs from DNA sequencing data is challenging because a CNA may alter the mutation multiplicity, or number of copies of an SNV. Existing methods to estimate CCFs rely on the restrictive Constant Mutation Multiplicity (CMM) assumption that the mutation multiplicity is constant across all tumor cells containing the mutation. However, the CMM assumption is commonly violated in tumors containing CNAs, and thus CCFs computed under the CMM assumption may yield unrealistic conclusions about tumor heterogeneity and evolution. The CCF also has a second limitation for phylogenetic analysis: the CCF measures the presence of a mutation at the present time, but SNVs may be lost during the evolution of a tumor due to deletions of chromosomal segments. Thus, SNVs that co-occur on the same phylogenetic branch may have different CCFs.In this work, we address these limitations of the CCF in two ways. First, we show how to compute the CCF of an SNV under a less restrictive and more realistic assumption called the Single Split Copy Number (SSCN) assumption. Second, we introduce a novel statistic, the descendant cell fraction (DCF), that quantifies both the prevalence of an SNV and the past evolutionary history of SNVs under an evolutionary model that allows for mutation losses. That is, SNVs that co-occur on the same phylogenetic branch will have the same DCF. We implement these ideas in an algorithm named DeCiFer. DeCiFer computes the DCFs of SNVs from read counts and copy-number proportions and also infers clusters of mutations that are suitable for phylogenetic analysis. We show that DeCiFer clusters SNVs more accurately than existing methods on simulated data containing mutation losses. We apply DeCiFer to sequencing data from 49 metastatic prostate cancer samples and show that DeCiFer produces more parsimonious and reasonable reconstructions of tumor evolution compared to previous approaches. Thus, DeCiFer enables more accurate quantification of intra-tumor heterogeneity and improves downstream inference of tumor evolution.Code availabilitySoftware is available at https://github.com/raphael-group/decifer

scholarly journals Computational correction of copy-number effect improves specificity of CRISPR-Cas9 essentiality screens in cancer cells

2017 ◽  
Author(s):  
Robin M. Meyers ◽  
Jordan G. Bryan ◽  
James M. McFarland ◽  
Barbara A. Weir ◽  
Ann E. Sizemore ◽  
...  
Keyword(s):  
Cancer Cells ◽  
Cell Lines ◽  
Cancer Cell ◽  
Dna Cleavage ◽  
False Positive ◽  
Copy Number ◽  
Specific Effect ◽  
Cancer Cell Lines ◽  
Genome Scale ◽  
Positive Results

The CRISPR-Cas9 system has revolutionized gene editing both on single genes and in multiplexed loss-of-function screens, enabling precise genome-scale identification of genes essential to proliferation and survival of cancer cells. However, previous studies reported that an anti-proliferative effect of Cas9-mediated DNA cleavage confounds such measurement of genetic dependency, particularly in the setting of copy number gain1-4. We performed genome-scale CRISPR-Cas9 essentiality screens on 342 cancer cell lines and found that this effect is common to all lines, leading to false positive results when targeting genes in copy number amplified regions. We developed CERES, a computational method to estimate gene dependency levels from CRISPR-Cas9 essentiality screens while accounting for the copy-number-specific effect, as well as variable sgRNA activity. We applied CERES to sets of screens performed with different sgRNA libraries and found that it reduces false positive results and provides meaningful estimates of sgRNA activity. As a result, the application of CERES improves confidence in the interpretation of genetic dependency data from CRISPR-Cas9 essentiality screens of cancer cell lines.

Synthesis and Characterization of Quinoline-3-Carboxamide Derivatives as Inhibitors of the ATM Kinase

2020 ◽  
Vol 20 (23) ◽  
pp. 2070-2079
Author(s):  
Srimadhavi Ravi ◽  
Sugata Barui ◽  
Sivapriya Kirubakaran ◽  
Parul Duhan ◽  
Kaushik Bhowmik
Keyword(s):  
Western Blot ◽  
Cancer Cells ◽  
Cell Line ◽  
Cell Lines ◽  
Cancer Cell ◽  
Blot Analysis ◽  
Western Blot Analysis ◽  
Cancer Cell Lines ◽  
Atm Kinase ◽  
Cytotoxicity Studies

Background: The importance of inhibiting the kinases of the DDR pathway for radiosensitizing cancer cells is well established. Cancer cells exploit these kinases for their survival, which leads to the development of resistance towards DNA damaging therapeutics. Objective: In this article, the focus is on targeting the key mediator of the DDR pathway, the ATM kinase. A new set of quinoline-3-carboxamides, as potential inhibitors of ATM, is reported. Methods: Quinoline-3-carboxamide derivatives were synthesized and cytotoxicity assay was performed to analyze the effect of molecules on different cancer cell lines like HCT116, MDA-MB-468, and MDA-MB-231. Results: Three of the synthesized compounds showed promising cytotoxicity towards a selected set of cancer cell lines. Western Blot analysis was also performed by pre-treating the cells with quercetin, a known ATM upregulator, by causing DNA double-strand breaks. SAR studies suggested the importance of the electron-donating nature of the R group for the molecule to be toxic. Finally, Western-Blot analysis confirmed the down-regulation of ATM in the cells. Additionally, the PTEN negative cell line, MDA-MB-468, was more sensitive towards the compounds in comparison with the PTEN positive cell line, MDA-MB-231. Cytotoxicity studies against 293T cells showed that the compounds were at least three times less toxic when compared with HCT116. Conclusion: In conclusion, these experiments will lay the groundwork for the evolution of potent and selective ATM inhibitors for the radio- and chemo-sensitization of cancer cells.

Design, Synthesis and Biological Evaluation: 5-amino-1H-pyrazole-1- carbonyl derivatives as FGFR Inhibitors

2020 ◽  
Vol 17 (11) ◽  
pp. 1330-1341
Author(s):  
Yan Zhang ◽  
Niefang Yu
Keyword(s):  
Cancer Cells ◽  
Cell Lines ◽  
Cancer Cell ◽  
Cancer Cell Lines ◽  
Biological Evaluation ◽  
Human Gastric Cancer ◽  
Design Synthesis ◽  
Carbonyl Derivatives ◽  
Ic50 Values ◽  
Inhibitory Activities

Background: Fibroblast growth factors (FGFs) and their high affinity receptors (FGFRs) play a major role in cell proliferation, differentiation, migration, and apoptosis. Aberrant FGFR signaling pathway might accelerate development in a broad panel of malignant solid tumors. However, the full application of most existing small molecule FGFR inhibitors has become a challenge due to the potential target mutation. Hence, it has attracted a great deal of attention from both academic and industrial fields for hunting for novel FGFR inhibitors with potent inhibitory activities and high selectivity. Objective: Novel 5-amino-1H-pyrazole-1-carbonyl derivatives were designed, synthesized, and evaluated as FGFR inhibitors. Methods: A series of 5-amino-1H-pyrazole-1-carbonyl derivatives were established by a condensation of the suitable formyl acetonitrile derivatives with either hydrazine or hydrazide derivatives in the presence of anhydrous ethanol or toluene. The inhibitory activities of the target compounds were screened against the FGFRs and two representative cancer cell lines. Tests were carried out to observe the inhibition of 8e against FGFR phosphorylation and downstream signal phosphorylation in human gastric cancer cell lines (SNU-16). The molecular docking of all the compounds were performed using Molecular Operating Environment in order to evaluate their binding abilities with the corresponding protein kinase. Results: A series of 5-amino-1H-pyrazole-1-carbonyl derivatives have been designed and synthesized, screened for their inhibitory activities against FGFRs and cancer cell lines. Most of the target compounds showed moderate to good anti-proliferate activities against the tested enzymes and cell lines. The most promising compounds 8e suppressed FGFR1-3 with IC50 values of 56.4, 35.2, 95.5 nM, and potently inhibited the SNU-16 and MCF-7 cancer cells with IC50 values of 0.71 1.26 μM, respectively. And 8e inhibited the growth of cancer cells containing FGFR activated by multiple mechanisms. In addition, the binding interactions were quite similar in the molecular models between generated compounds and Debio-1347 with the FGFR1. Conclusion: According to the experimental findings, 5-amino-1H-pyrazole-1-carbonyl might serve as a promising template of an FGFR inhibitor.

Small Molecular Leads Differentially Active Against HER2 Positive and Triple Negative Breast Cancer Cell Lines

2019 ◽  
Vol 15 (7) ◽  
pp. 738-742 ◽  
Author(s):  
Adnan Badran ◽  
Atia-tul-Wahab ◽  
Sharmeen Fayyaz ◽  
Elias Baydoun ◽  
Muhammad Iqbal Choudhary
Keyword(s):  
Breast Cancer ◽  
Cancer Cells ◽  
Cell Lines ◽  
Cancer Cell ◽  
Breast Cancer Cell ◽  
Triple Negative ◽  
Cancer Cell Lines ◽  
Breast Cancer Cell Lines ◽  
Cancer Type

Background:Breast cancer is the most prevalent cancer type in women globally. It is characterized by distinct subtypes depending on different gene expression patterns. Oncogene HER2 is expressed on the surface of cell and is responsible for cell growth regulation. Increase in HER2 receptor protein due to gene amplification, results in aggressive growth, and high metastasis in cancer cells.Methods:The current study evaluates and compares the anti-breast cancer effect of commercially available compounds against HER2 overexpressing BT-474, and triple negative MDA-MB-231 breast cancer cell lines.Results:Preliminary in vitro cell viability assays on these cell lines identified 6 lead molecules active against breast cancer. Convallatoxin (4), a steroidal lactone glycoside, showed the most potent activity with IC50 values of 0.63 ± 0.56, and 0.69 ± 0.59 µM against BT-474 and MDA-MB-231, respectively, whereas 4-[4-(Trifluoromethyl)-phenoxy] phenol (3) a phenol derivative, and Reserpine (5) an indole alkaloid selectively inhibited the growth of BT-474, and MDA-MB-231 breast cancer cells, respectively.Conclusion:These results exhibited the potential of small molecules in the treatment of HER2 amplified and triple negative breast cancers in vitro.

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