scholarly journals Exome Sequencing Reveals Comprehensive Genomic Alterations across Eight Cancer Cell Lines

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

2008 ◽  
Vol 267 (1) ◽  
pp. 49-54 ◽  
Author(s):  
Xueying Mao ◽  
Bryan D. Young ◽  
Tracy Chaplin ◽  
Janet Shipley ◽  
Yong-Jie Lu

2021 ◽  
Author(s):  
Niantao Deng ◽  
Andre Minoche ◽  
Kate Harvey ◽  
Andrei Goga ◽  
Alex Swarbrick

Abstract BackgroundBreast cancer cell lines (BCCLs) and patient-derived xenografts (PDX) are the most frequently used models in breast cancer research. Despite their widespread usage, genome sequencing of these models is incomplete, with previous studies only focusing on targeted gene panels, whole exome or shallow whole genome sequencing. Deep whole genome sequencing is the most sensitive and accurate method to detect single nucleotide variants and indels, gene copy number and structural events such as gene fusions. ResultsHere we describe deep whole genome sequencing (WGS) of commonly used BCCL and PDX models using the Illumina X10 platform with an average ~ 60x coverage. We identify novel genomic alterations, including point mutations and genomic rearrangements at base-pair resolution, compared to previously available sequencing data. Through integrative analysis with publicly available functional screening data, we annotate new genomic features likely to be of biological significance. CSMD1 , previously identified as a tumor suppressor gene in various cancer types, including head and neck, lung and breast cancers, has been identified with deletion in 50% of our PDX models, suggesting an important role in aggressive breast cancers. ConclusionsOur WGS data provides a comprehensive genome sequencing resource of these models.


2015 ◽  
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

2020 ◽  
Author(s):  
Tae Yoon Park ◽  
Mark D.M. Leiserson ◽  
Gunnar W. Klau ◽  
Benjamin J. Raphael

AbstractRecent genome-wide CRISPR-Cas9 loss-of-function screens have identified genetic dependencies across many cancer cell lines. Associations between these dependencies and genomic alterations in the same cell lines reveal phenomena such as oncogene addiction and synthetic lethality. However, comprehensive characterization of such associations is complicated by complex interactions between genes across genetically heterogeneous cancer types. We introduce SuperDendrix, an algorithm to identify differential dependencies across cell lines and to find associations between differential dependencies and combinations of genetic alterations and cell-type-specific markers. Application of SuperDendrix to CRISPR-Cas9 loss-of-function screens from 554 cancer cell lines reveals a landscape of associations between differential dependencies and genomic alterations across multiple cancer pathways in different combinations of cancer types. We find that these associations respect the position and type of interactions within pathways with increased dependencies on downstream activators of pathways, such as NFE2L2 and decreased dependencies on upstream activators of pathways, such as CDK6. SuperDendrix also reveals dozens of dependencies on lineage-specific transcription factors, identifies cancer-type-specific correlations between dependencies, and enables annotation of individual mutated residues.


Gut ◽  
2017 ◽  
Vol 67 (3) ◽  
pp. 508-520 ◽  
Author(s):  
Erik S Knudsen ◽  
Uthra Balaji ◽  
Brian Mannakee ◽  
Paris Vail ◽  
Cody Eslinger ◽  
...  

ObjectivePancreatic ductal adenocarcinoma (PDAC) is a therapy recalcitrant disease with the worst survival rate of common solid tumours. Preclinical models that accurately reflect the genetic and biological diversity of PDAC will be important for delineating features of tumour biology and therapeutic vulnerabilities.Design27 primary PDAC tumours were employed for genetic analysis and development of tumour models. Tumour tissue was used for derivation of xenografts and cell lines. Exome sequencing was performed on the originating tumour and developed models. RNA sequencing, histological and functional analyses were employed to determine the relationship of the patient-derived models to clinical presentation of PDAC.ResultsThe cohort employed captured the genetic diversity of PDAC. From most cases, both cell lines and xenograft models were developed. Exome sequencing confirmed preservation of the primary tumour mutations in developed cell lines, which remained stable with extended passaging. The level of genetic conservation in the cell lines was comparable to that observed with patient-derived xenograft (PDX) models. Unlike historically established PDAC cancer cell lines, patient-derived models recapitulated the histological architecture of the primary tumour and exhibited metastatic spread similar to that observed clinically. Detailed genetic analyses of tumours and derived models revealed features of ex vivo evolution and the clonal architecture of PDAC. Functional analysis was used to elucidate therapeutic vulnerabilities of relevance to treatment of PDAC.ConclusionsThese data illustrate that with the appropriate methods it is possible to develop cell lines that maintain genetic features of PDAC. Such models serve as important substrates for analysing the significance of genetic variants and create a unique biorepository of annotated cell lines and xenografts that were established simultaneously from same primary tumour. These models can be used to infer genetic and empirically determined therapeutic sensitivities that would be germane to the patient.


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