Abstract 4742: Using 1ng of DNA to detect haplotype phasing and gene fusions from whole exome sequencing of cancer cell lines

Author(s):  
Mirna Jarosz ◽  
Michael Schnall-Levin ◽  
Grace X. Y. Zheng ◽  
Patrick Marks ◽  
Sofia Kyriazopoulou-Panagiotopoulou ◽  
...  
2019 ◽  
Vol 18 (8) ◽  
pp. 1460-1471 ◽  
Author(s):  
Sunetra Das ◽  
Rupa Idate ◽  
Kathryn E. Cronise ◽  
Daniel L. Gustafson ◽  
Dawn L. Duval

Author(s):  
Chi Song ◽  
Shih-Chi Su ◽  
Zhiguang Huo ◽  
Suleyman Vural ◽  
James E Galvin ◽  
...  

Abstract Summary In this article, we introduce a hierarchical clustering and Gaussian mixture model with expectation-maximization (EM) algorithm for detecting copy number variants (CNVs) using whole exome sequencing (WES) data. The R shiny package ‘HCMMCNVs’ is also developed for processing user-provided bam files, running CNVs detection algorithm and conducting visualization. Through applying our approach to 325 cancer cell lines in 22 tumor types from Cancer Cell Line Encyclopedia (CCLE), we show that our algorithm is competitive with other existing methods and feasible in using multiple cancer cell lines for CNVs estimation. In addition, by applying our approach to WES data of 120 oral squamous cell carcinoma (OSCC) samples, our algorithm, using the tumor sample only, exhibits more power in detecting CNVs as compared with the methods using both tumors and matched normal counterparts. Availability and implementation HCMMCNVs R shiny software is freely available at github repository https://github.com/lunching/HCMM_CNVs.and Zenodo https://doi.org/10.5281/zenodo.4593371. Supplementary information Supplementary data are available at Bioinformatics online.


PLoS ONE ◽  
2011 ◽  
Vol 6 (6) ◽  
pp. e21097 ◽  
Author(s):  
Han Chang ◽  
Donald G. Jackson ◽  
Paul S. Kayne ◽  
Petra B. Ross-Macdonald ◽  
Rolf-Peter Ryseck ◽  
...  

2020 ◽  
Vol 7 (1) ◽  
Author(s):  
Alessio Somaschini ◽  
Sebastiano Di Bella ◽  
Carlo Cusi ◽  
Laura Raddrizzani ◽  
Antonella Leone ◽  
...  

AbstractInhibition of kinase gene fusions (KGFs) has proven successful in cancer treatment and continues to represent an attractive research area, due to kinase druggability and clinical validation. Indeed, literature and public databases report a remarkable number of KGFs as potential drug targets, often identified by in vitro characterization of tumor cell line models and confirmed also in clinical samples. However, KGF molecular and experimental information can sometimes be sparse and partially overlapping, suggesting the need for a specific annotation database of KGFs, conveniently condensing all the molecular details that can support targeted drug development pipelines and diagnostic approaches. Here, we describe KuNG FU (KiNase Gene FUsion), a manually curated database collecting detailed annotations on KGFs that were identified and experimentally validated in human cancer cell lines from multiple sources, exclusively focusing on in-frame KGF events retaining an intact kinase domain, representing potentially active driver kinase targets. To our knowledge, KuNG FU represents to date the largest freely accessible homogeneous and curated database of kinase gene fusions in cell line models.


Blood ◽  
2016 ◽  
Vol 128 (22) ◽  
pp. 4449-4449
Author(s):  
James W Murray ◽  
Christopher Fegan ◽  
Chris Pepper

Abstract Background: Understanding the pathology of Multiple Myeloma and the testing of therapeutic options has relied heavily on isogeneic cell lines due to the inability to sustain myeloma plasma cells in long-term in vitro culture. The cell lines MM.1S and MM.1R are well recognised in the field of myeloma research, providing a model of glucocorticoid drug resistance, primarily believed to be through variable expression of the glucocorticoid receptor NR3C1 but here we found no evidence of a genetic basis for this. Here we set out to examine the phenotype, function and genotype of the MM.1S and MM.1R cell lines in order to explore the origins of glucocorticoid drug resistance manifested by MM.1R cells and establish whether exome analysis could identify sub-clones with preferential sensitivity to molecular targeted inhibitors. Methods: MM.1S and MM.1R cell lines were purchased from ATCC. A 10-colour flow cytometry panel (CD38, CD138, CD19, CD45, CD56, CD49d, CXCR4, MMP-9, Ki-67, IL-6) was analysed on a BD LSR Fortessa flow cytometer and MM.1S subsets were sorted using a FACS Aria III. Telomere length was assessed using Single Telomere Length Analysis (STELA) and drug toxicity assays using Annexin V-FITC/PI staining. Bioinformatics of whole exome sequencing was carried out on the GATK platform and gene list analysis using Enrichr. PI3K isoforms were analysed by quantitative PCR and immunoblotting. Results: The MM.1S cell line demonstrated bimodal CD38 expression, with a 1.5 log difference in CD38 expression (p<0.0001) between the two populations (termed MM.1Sdim and MM.1Sbright). In contrast the MM.1R cell line was uniformly CD38bright, with expression a further 0.5 log higher than MM.1Sbright. When cell sorted subsets of MM.1S cells were subjected to increasing concentrations of Dexamethasone, the MM.1Sbright cells had a significantly higher LC50 than the MM.1Sdim cells (62nM v 29nM respectively; p<0.0001). In contrast, these subsets showed no significant difference in sensitivity to bortezomib (p=0.84. Furthermore, MM.1Sbright cells had a shorter doubling time than both MM.1Sdim (p=0.0001) and MM.1R (p=0.048). This was underscored by an increased proportion of MM.1Sbright cells in S-phase coupled with shorter mean telomere length when compared with MM.1Sdim and MM.1R (2.58 Kb v 3.29Kb v 3.2Kb respectively). We next subjected purified MM.1Sbright, MM.1Sdim and MM.1R cells to whole exome sequencing. The common clonal origin of the three cell lines was evident from the analysis but each line possessed unique genetic lesions. For example, MM.1Sbright had a FIP1L1-PDGFRA fusion mutation that was not present in the MM.1Sdim cells. This was associated with increased expression of the p110d isoform in MM.1Sdim cells. We therefore analysed the effects of the PI3Kd inhibitor, Idelalisib, on the two cell lines and showed that MM.1Sdim cells were more sensitive (p=0.003) to the effects of this agent. The specific nature of this response was confirmed by the fact that the pan p13K inhibitor PKI-402, was equipotent in both MM.1Sbright and MM.1Sdim cells (p=0.89). Conclusion: Analysis of two phenotypically distinct subsets within the MM.1S cell line revealed differences in function and genetics thereby confirming the sub-clonal architecture within this cell line. Intriguingly, our data point to the pre-existence of a dexamethasone resistant sub-clone the MM.1Sbright (CD38+) population. The subsequent production of the dexamethasone resistant cell line (MM.1R) allowed us to perform comparative genomics thereby identifying the genetic origins of dexamethasone resistance (selection) in MM.1Sbright cells and to track the subsequent clonal evolution (induction) in the MM.1R cells. Furthermore, we showed the potential for developing bespoke treatment plans based on the identification of cell signalling pathway mutations via genomic sequencing. By selective targeting of of these genetic lesions it may be possible to remove multiple sub-clones thereby diminishing the potential for clonal tiding and the development of drug resistance. In theory this could result in longer time to relapse and ultimately improved overall survival. Disclosures Fegan: Roche: Honoraria; Gilead Sciences: Honoraria; AbbVie: Honoraria.


Author(s):  
Han Chang ◽  
Donald G. Jackson ◽  
Paul S. Kayne ◽  
Petra B. Ross-Macdonald ◽  
Rolf-Peter Ryseck ◽  
...  

2019 ◽  
Vol 116 (45) ◽  
pp. 22730-22736 ◽  
Author(s):  
Luca Zammataro ◽  
Salvatore Lopez ◽  
Stefania Bellone ◽  
Francesca Pettinella ◽  
Elena Bonazzoli ◽  
...  

The prognosis of advanced/recurrent cervical cancer patients remains poor. We analyzed 54 fresh-frozen and 15 primary cervical cancer cell lines, along with matched-normal DNA, by whole-exome sequencing (WES), most of which harboring Human-Papillomavirus-type-16/18. We found recurrent somatic missense mutations in 22 genes (including PIK3CA, ERBB2, and GNAS) and a widespread APOBEC cytidine deaminase mutagenesis pattern (TCW motif) in both adenocarcinoma (ACC) and squamous cell carcinomas (SCCs). Somatic copy number variants (CNVs) identified 12 copy number gains and 40 losses, occurring more often than expected by chance, with the most frequent events in pathways similar to those found from analysis of single nucleotide variants (SNVs), including the ERBB2/PI3K/AKT/mTOR, apoptosis, chromatin remodeling, and cell cycle. To validate specific SNVs as targets, we took advantage of primary cervical tumor cell lines and xenografts to preclinically evaluate the activity of pan-HER (afatinib and neratinib) and PIK3CA (copanlisib) inhibitors, alone and in combination, against tumors harboring alterations in the ERBB2/PI3K/AKT/mTOR pathway (71%). Tumors harboring ERBB2 (5.8%) domain mutations were significantly more sensitive to single agents afatinib or neratinib when compared to wild-type tumors in preclinical in vitro and in vivo models (P = 0.001). In contrast, pan-HER and PIK3CA inhibitors demonstrated limited in vitro activity and were only transiently effective in controlling in vivo growth of PIK3CA-mutated cervical cancer xenografts. Importantly, combinations of copanlisib and neratinib were highly synergistic, inducing long-lasting regression of tumors harboring alterations in the ERBB2/PI3K/AKT/mTOR pathway. These findings define the genetic landscape of cervical cancer, suggesting that a large subset of cervical tumors might benefit from existing ERBB2/PIK3CA/AKT/mTOR-targeted drugs.


2021 ◽  
Vol 22 (1) ◽  
Author(s):  
Yiqun Zhang ◽  
Fengju Chen ◽  
Chad J. Creighton

Abstract Background Combined whole-genome sequencing (WGS) and RNA sequencing of cancers offer the opportunity to identify genes with altered expression due to genomic rearrangements. Somatic structural variants (SVs), as identified by WGS, can involve altered gene cis-regulation, gene fusions, copy number alterations, or gene disruption. The absence of computational tools to streamline integrative analysis steps may represent a barrier in identifying genes recurrently altered by genomic rearrangement. Results Here, we introduce SVExpress, a set of tools for carrying out integrative analysis of SV and gene expression data. SVExpress enables systematic cataloging of genes that consistently show increased or decreased expression in conjunction with the presence of nearby SV breakpoints. SVExpress can evaluate breakpoints in proximity to genes for potential enhancer translocation events or disruption of topologically associated domains, two mechanisms by which SVs may deregulate genes. The output from any commonly used SV calling algorithm may be easily adapted for use with SVExpress. SVExpress can readily analyze genomic datasets involving hundreds of cancer sample profiles. Here, we used SVExpress to analyze SV and expression data across 327 cancer cell lines with combined SV and expression data in the Cancer Cell Line Encyclopedia (CCLE). In the CCLE dataset, hundreds of genes showed altered gene expression in relation to nearby SV breakpoints. Altered genes involved TAD disruption, enhancer hijacking, and gene fusions. When comparing the top set of SV-altered genes from cancer cell lines with the top SV-altered genes previously reported for human tumors from The Cancer Genome Atlas and the Pan-Cancer Analysis of Whole Genomes datasets, a significant number of genes overlapped in the same direction for both cell lines and tumors, while some genes were significant for cell lines but not for human tumors and vice versa. Conclusion Our SVExpress tools allow computational biologists with a working knowledge of R to integrate gene expression with SV breakpoint data to identify recurrently altered genes. SVExpress is freely available for academic or commercial use at https://github.com/chadcreighton/SVExpress. SVExpress is implemented as a set of Excel macros and R code. All source code (R and Visual Basic for Applications) is available.


Blood ◽  
2014 ◽  
Vol 124 (21) ◽  
pp. 69-69
Author(s):  
Michelle Perugini ◽  
Saumya E Samaraweera ◽  
Anna L Brown ◽  
Nik Cummings ◽  
Silke Danner ◽  
...  

Abstract BACKGROUND: We have previously shown that one target of hyper-methylation in AML is the promoter of the tumour suppressor and stress-response mediator Growth Arrest and DNA Damage inducible 45A (GADD45A) (GADD45AmeHI; 42% of AML). In mice Gadd45a has recently been shown to play a critical role in HSC stress responses. Gadd45a deficiency leads to enhanced HSC self-renewal, DNA damage accumulation in HSC, increased susceptibility to leukemogenesis, and impairment in HSC apoptosis after genotoxic exposure (Chen et al, Blood 2014). These findings suggest that hypermethylation of the GADD45A gene may play an important role in the altered properties of HSC, leukaemic initiation and progression. Promoter hypermethylation of this gene defines a patient group with poor survival on standard therapy (Perugini et al, Leukaemia 2012). To explore further the molecular basis of the GADD45AmeHI patient group weperformed genetic profiling of diagnosis samples using a Sequenom multiplex mutation panel, or using whole exome sequencing for broader coverage (n=95 patients).Sequenom MassARRAY was used for quantitative detection of GADD45A promoter methylation in patient samples. For a cohort of matched diagnosis and relapse samples we used CpG methylation data for GADD45A determined by ERRBS (Akalin et al, PLoSGenetics 2012). Response to cytotoxic drugs and assessment of drug combinations with 5-Aza-deoxycytidine (decitabine, DAC) and anthracycline (Daunorubicin, DNR) was performed in AML cell lines, and with primary leukemic cell populations. RESULTS: The association of the GADD45AmeHI patient group with poor outcome was validated in an independent AML patient cohort of 48 patients from the Alfred Hospital, Melbourne, Australia (p=0.003; HR3.35). Whole exome sequencing and Sequenom multiplex analysis of 95 AML patients revealed a striking co-occurrence of the GADD45AmeHI phenotype with mutations in IDH1, IDH2, and TET2 (p<0.0001, Fisher’s exact test, Fig. 1). To test the prediction that GADD45A hypermethylation may be an important factor for relapse we investigated GADD45A promoter DNA methylation levels in paired diagnosis and relapse samples. In a paired analysis of 39 patients we show that relapse samples display a significant increase in GADD45A promoter CpG methylation (p=0.035, paired t-test). This is consistent with emergence in many patients following chemotherapy of a chemoresistant clone that has increased GADD45A methylation and reduced GADD45A activity. We next tested whether reactivation of GADD45A expression in GADD45AmeHI patient samples could be achieved through the use of hypo-methylation agents, and whether this is beneficial for response to chemotherapy. DAC treatment has been reported to induce DNA demethylation and GADD45A reactivation in primary AML samples (Klco et al, Blood 2013), and we observe reduced GADD45A promoter methylation and increased expression following DAC treatment of the GADD45AmeHI AML cell line (Mv4;11), consistent with DNA methylation-induced gene silencing of GADD45A. DAC pre-treatment of the GADD45AmeHI AML cell lines MOLM13 and Mv4;11, and three primary AML samples (GADD45AmeHI), resulted in increased GADD45A expression and increased DNR sensitivity. CONCLUSIONS: DNA methylation of the GADD45A proximal promoter marks a large percentage of AML patients at diagnosis including the majority of those with IDH1/2 and TET2 mutations (collectively these occur in 28% of AML (Network CGAR, N Engl J Med, 2013)), and is an independent predictor of poor outcome in two independent patient cohorts. Our data shows that silencing of GADD45A through increased promoter CpG methylation maybe an important early event in leukaemogenesis associated with impaired TET2 activity. Based on recent studies describing the properties of Gadd45a-deficient murine HSC we suggest reduced GADD45A activity in this subset of patients may contribute to the properties of pre-leukaemic HSC that have been associated with IDH1/2 mutation and reported to display clonal expansion, resistance to chemotherapy, and ultimately a high risk of relapse. In vitro drug experiments suggest that a priming schedule of DAC followed by DNR may provide a successful tailored treatment strategy for GADD45AmeHI patients, in combination with GADD45A expression as a biomarker predicting increased DNR sensitivity. Fig 1: Co-association of GADD45AmeHI with IDH1/2 and TET2 mutations in 95 AML patients Fig 1:. Co-association of GADD45AmeHI with IDH1/2 and TET2 mutations in 95 AML patients Disclosures No relevant conflicts of interest to declare.


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