scholarly journals Decoding human cancer with whole genome sequencing: a review of PCAWG Project studies published in February 2020

2021 ◽  
Author(s):  
Simona Giunta
Keyword(s):  
Whole Genome Sequencing ◽  
Genome Sequencing ◽  
Cancer Genetics ◽  
Cancer Genome ◽  
The Cancer Genome Atlas ◽  
Driver Mutations ◽  
Causative Mutation ◽  
Whole Genome ◽  
Genetic Changes ◽  
Pan Cancer

AbstractCancer is underlined by genetic changes. In an unprecedented international effort, the Pan-Cancer Analysis of Whole Genomes (PCAWG) of the International Cancer Genome Consortium (ICGC) and The Cancer Genome Atlas (TCGA) sequenced the tumors of over two thousand five hundred patients across 38 different cancer types, as well as the corresponding healthy tissue, with the aim of identifying genome-wide mutations exclusively found in cancer and uncovering new genetic changes that drive tumor formation. What set this project apart from earlier efforts is the use of whole genome sequencing (WGS) that enabled to explore alterations beyond the coding DNA, into cancer’s non-coding genome. WGS of the entire cohort allowed to tease apart driving mutations that initiate and support carcinogenesis from passenger mutations that do not play an overt role in the disease. At least one causative mutation was found in 95% of all cancers, with many tumors showing an average of 5 driver mutations. The PCAWG Project also assessed the transcriptional output altered in cancer and rebuilt the evolutionary history of each tumor showing that initial driver mutations can occur years if not decades prior to a diagnosis. Here, I provide a concise review of the Pan-Cancer Project papers published on February 2020, along with key computational tools and the digital framework generated as part of the project. This represents an historic effort by hundreds of international collaborators, which provides a comprehensive understanding of cancer genetics, with publicly available data and resources representing a treasure trove of information to advance cancer research for years to come.

scholarly journals Whole-Genome Sequencing of Retinoblastoma Reveals the Diversity of Rearrangements Disrupting RB1 and Uncovers a Treatment-Related Mutational Signature

Cancers ◽  
2021 ◽  
Vol 13 (4) ◽  
pp. 754
Author(s):  
Helen R. Davies ◽  
Kevin D. Broad ◽  
Zerrin Onadim ◽  
Elizabeth A. Price ◽  
Xueqing Zou ◽  
...  
Keyword(s):  
Whole Genome Sequencing ◽  
Genome Sequencing ◽  
Driver Mutations ◽  
Whole Genome ◽  
Rb1 Gene ◽  
Clinical Screening ◽  
Genetic Changes ◽  
Alternative Pathways ◽  
Mutational Signature ◽  
New Mutations

The development of retinoblastoma is thought to require pathological genetic changes in both alleles of the RB1 gene. However, cases exist where RB1 mutations are undetectable, suggesting alternative pathways to malignancy. We used whole-genome sequencing (WGS) and transcriptomics to investigate the landscape of sporadic retinoblastomas derived from twenty patients, sought RB1 and other driver mutations and investigated mutational signatures. At least one RB1 mutation was identified in all retinoblastomas, including new mutations in addition to those previously identified by clinical screening. Ten tumours carried structural rearrangements involving RB1 ranging from relatively simple to extremely complex rearrangement patterns, including a chromothripsis-like pattern in one tumour. Bilateral tumours obtained from one patient harboured conserved germline but divergent somatic RB1 mutations, indicating independent evolution. Mutational signature analysis showed predominance of signatures associated with cell division, an absence of ultraviolet-related DNA damage and a profound platinum-related mutational signature in a chemotherapy-exposed tumour. Most RB1 mutations are identifiable by clinical screening. However, the increased resolution and ability to detect otherwise elusive rearrangements by WGS have important repercussions on clinical management and advice on recurrence risks.

scholarly journals Chromoanagenesis Landscape in 10,000 TCGA Patients

Cancers ◽  
2021 ◽  
Vol 13 (16) ◽  
pp. 4197
Author(s):  
Roni Rasnic ◽  
Michal Linial
Keyword(s):  
Whole Genome Sequencing ◽  
Genome Sequencing ◽  
Learning Algorithm ◽  
The Cancer Genome Atlas ◽  
Cancer Type ◽  
Whole Genome ◽  
Cancer Genome Atlas ◽  
Cancer Types ◽  
Tumor Biopsies ◽  
Pan Cancer

During the past decade, whole-genome sequencing of tumor biopsies and individuals with congenital disorders highlighted the phenomenon of chromoanagenesis, a single chaotic event of chromosomal rearrangement. Chromoanagenesis was shown to be frequent in many types of cancers, to occur in early stages of cancer development, and significantly impact the tumor’s nature. However, an in-depth, cancer-type dependent analysis has been somewhat incomplete due to the shortage in whole genome sequencing of cancerous samples. In this study, we extracted data from The Pan-Cancer Analysis of Whole Genome (PCAWG) and The Cancer Genome Atlas (TCGA) to construct and test a machine learning algorithm that can detect chromoanagenesis with high accuracy (86%). The algorithm was applied to ~10,000 unlabeled TCGA cancer patients. We utilize the chromoanagenesis assignment results, to analyze cancer-type specific chromoanagenesis characteristics in 20 TCGA cancer types. Our results unveil prominent genes affected in either chromoanagenesis or non-chromoanagenesis tumorigenesis. The analysis reveals a mutual exclusivity relationship between the genes impaired in chromoanagenesis versus non-chromoanagenesis cases. We offer the discovered characteristics as possible targets for cancer diagnostic and therapeutic purposes.

scholarly journals Presence of Viral DNA in Whole-Genome Sequencing of Brain Tumor Tissues from The Cancer Genome Atlas

2013 ◽  
Vol 88 (1) ◽  
pp. 774-774 ◽  
Author(s):  
E. S. Amirian ◽  
M. L. Bondy ◽  
Q. Mo ◽  
M. N. Bainbridge ◽  
M. E. Scheurer
Keyword(s):  
Brain Tumor ◽  
Whole Genome Sequencing ◽  
Genome Sequencing ◽  
Cancer Genome ◽  
The Cancer Genome Atlas ◽  
Whole Genome ◽  
Viral Dna ◽  
Tumor Tissues ◽  
Cancer Genome Atlas ◽  
Genome Atlas

scholarly journals Retrospective evaluation of whole exome and genome mutation calls in 746 cancer samples

2020 ◽  
Vol 11 (1) ◽  
Author(s):  
Matthew H. Bailey ◽  
◽  
William U. Meyerson ◽  
Lewis Jonathan Dursi ◽  
Liang-Bo Wang ◽  
...  
Keyword(s):  
Whole Genome Sequencing ◽  
Genome Sequencing ◽  
Gc Content ◽  
Cancer Genome ◽  
The Cancer Genome Atlas ◽  
Whole Genome Sequencing Data ◽  
Whole Genome ◽  
Sequencing Data ◽  
Whole Exome ◽  
Cancer Genome Atlas

AbstractThe Cancer Genome Atlas (TCGA) and International Cancer Genome Consortium (ICGC) curated consensus somatic mutation calls using whole exome sequencing (WES) and whole genome sequencing (WGS), respectively. Here, as part of the ICGC/TCGA Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium, which aggregated whole genome sequencing data from 2,658 cancers across 38 tumour types, we compare WES and WGS side-by-side from 746 TCGA samples, finding that ~80% of mutations overlap in covered exonic regions. We estimate that low variant allele fraction (VAF < 15%) and clonal heterogeneity contribute up to 68% of private WGS mutations and 71% of private WES mutations. We observe that ~30% of private WGS mutations trace to mutations identified by a single variant caller in WES consensus efforts. WGS captures both ~50% more variation in exonic regions and un-observed mutations in loci with variable GC-content. Together, our analysis highlights technological divergences between two reproducible somatic variant detection efforts.

scholarly journals Chromoanagenesis landscape in 10,000 TCGA patients

2021 ◽  
Author(s):  
Roni Rasnic ◽  
Michal Linial
Keyword(s):  
Whole Genome Sequencing ◽  
Genome Sequencing ◽  
Learning Algorithm ◽  
The Cancer Genome Atlas ◽  
Cancer Type ◽  
Whole Genome ◽  
Cancer Genome Atlas ◽  
Cancer Types ◽  
Tumor Biopsies ◽  
Pan Cancer

During the past decade, whole-genome sequencing of tumor biopsies and individuals with congenital disorders highlighted the phenomenon of chromoanagenesis, a single chaotic event of chromosomal rearrangement. Chromoanagenesis was shown to be frequent in many types of cancers, to occur in early stages of cancer development, and significantly impact the tumors nature. However, an in-depth, cancer-type dependent analysis has been somewhat incomplete due to the shortage in whole genome sequencing of cancerous samples. In this study, we extracted data from The Pan-Cancer Analysis of Whole Genome (PCAWG) and The Cancer Genome Atlas (TCGA) to construct a machine learning algorithm that can detect chromoanagenesis with high accuracy (86%). The algorithm was applied to ~10,000 TCGA cancer patients. We utilize the chromoanagenesis assignment results, to analyze cancer-type specific chromoanagenesis characteristics in 20 TCGA cancer types. Our results unveil prominent genes affected in either chromoanagenesis or non-chromoanagenesis tumorigenesis. The analysis reveals a mutual exclusivity relationship between the genes impaired in chromoanagenesis versus non-chromoanagenesis cases. We offer the discovered characteristics as possible targets for cancer diagnostic and therapeutic purposes.

scholarly journals Genomic Landscape of Intramedullary Spinal Cord Tumors Suggests Distinct Genetic Origins Compared to Intracranial Histopathologic Counterparts

Neurosurgery ◽  
2019 ◽  
Vol 66 (Supplement_1) ◽  
Author(s):  
Tej D Azad ◽  
Ming Zhang ◽  
Rajiv Iyer ◽  
Qing Wang ◽  
Tomas Garzon-Muvdi ◽  
...  
Keyword(s):  
Spinal Cord ◽  
Whole Genome Sequencing ◽  
Genome Sequencing ◽  
Treatment Options ◽  
Driver Mutations ◽  
Whole Genome ◽  
Spinal Cord Tumors ◽  
Intramedullary Spinal Cord ◽  
Molecular Features ◽  
The Central Nervous System

Abstract INTRODUCTION Intramedullary spinal cord tumors (IMSCTs) are a rare, heterogeneous group of neoplasms with limited treatment options and high rates of morbidity and mortality. Next-generation sequencing has revealed opportunities for targeted therapies of the intracranial counterparts of IMSCT, but little is known about the molecular features of IMSCT. METHODS To better understand the genetic basis of these tumors we performed whole exome sequencing on fifty-one IMSCT and matched germline DNA, including 29 ependymomas, 16 astrocytomas, 4 gangliogliomas,1hemangioblastoma, and 1 oligodendroglioma. Whole-genome sequencing was further performed on 12 IMSCT to discover possible structural variants. RESULTS Though recurrent somatic mutations in IMSCTs were rare, we identified NF2 mutations in 15.7% of tumors (ependymoma, N = 7; astrocytoma, N = 1), RP1 mutations in 5.9% of tumors (ependymoma, N = 3), and ESX1 mutations in 5.9% of tumors (ependymoma, N = 3). We further identified copy number amplifications in CTU1 in 25% of myxopapillary ependymomas. Given the paucity of somatic driver mutations, we further performed whole-genome sequencing of 12 tumors (ependymoma, N = 9; astrocytoma, N = 3). Overall, we observed that IMSCTs with intracranial histologic counterparts did not harbor the canonical mutations associated with their intracranial counterparts (eg glioblastoma). CONCLUSION Our findings suggest that the origin of IMSCTs may be distinct from tumors arising within other compartments of the central nervous system and provides a framework to begin more biologically based therapeutic strategies.

scholarly journals Whole Genome Sequencing Highlights Genetic Changes Associated with Laboratory Domestication of C. elegans

PLoS ONE ◽  
2010 ◽  
Vol 5 (11) ◽  
pp. e13922 ◽  
Author(s):  
Katherine P. Weber ◽  
Subhajyoti De ◽  
Iwanka Kozarewa ◽  
Daniel J. Turner ◽  
M. Madan Babu ◽  
...  
Keyword(s):  
Whole Genome Sequencing ◽  
Genome Sequencing ◽  
Whole Genome ◽  
Genetic Changes ◽  
C Elegans

scholarly journals Mutational landscape of gastric adenocarcinoma in Chinese: Implications for prognosis and therapy

2015 ◽  
Vol 112 (4) ◽  
pp. 1107-1112 ◽  
Author(s):  
Kexin Chen ◽  
Da Yang ◽  
Xiangchun Li ◽  
Baocun Sun ◽  
Fengju Song ◽  
...  
Keyword(s):  
Whole Genome Sequencing ◽  
Genome Sequencing ◽  
Clonal Evolution ◽  
Treatment Strategies ◽  
The Cancer Genome Atlas ◽  
Whole Genome Sequencing Data ◽  
Whole Genome ◽  
Sequencing Data ◽  
Phylogenetic Tree Analysis ◽  
Primary Tumors

Gastric cancer (GC) is a highly heterogeneous disease. To identify potential clinically actionable therapeutic targets that may inform individualized treatment strategies, we performed whole-exome sequencing on 78 GCs of differing histologies and anatomic locations, as well as whole-genome sequencing on two GC cases, each with three primary tumors and two matching lymph node metastases. The data showed two distinct GC subtypes with either high-clonality (HiC) or low-clonality (LoC). The HiC subtype of intratumoral heterogeneity was associated with older age, TP53 (tumor protein P53) mutation, enriched C > G transition, and significantly shorter survival, whereas the LoC subtype was associated with younger age, ARID1A (AT rich interactive domain 1A) mutation, and significantly longer survival. Phylogenetic tree analysis of whole-genome sequencing data from multiple samples of two patients supported the clonal evolution of GC metastasis and revealed the accumulation of genetic defects that necessitate combination therapeutics. The most recurrently mutated genes, which were validated in a separate cohort of 216 cases by targeted sequencing, were members of the homologous recombination DNA repair, Wnt, and PI3K-ERBB pathways. Notably, the drugable NRG1 (neuregulin-1) and ERBB4 (V-Erb-B2 avian erythroblastic leukemia viral oncogene homolog 4) ligand-receptor pair were mutated in 10% of GC cases. Mutations of the BRCA2 (breast cancer 2, early onset) gene, found in 8% of our cohort and validated in The Cancer Genome Atlas GC cohort, were associated with significantly longer survivals. These data define distinct clinicogenetic forms of GC in the Chinese population that are characterized by specific mutation sets that can be investigated for efficacy of single and combination therapies.

scholarly journals Allele-Specific Quantification of Structural Variations in Cancer Genomes

2016 ◽  
Author(s):  
Yang Li ◽  
Shiguo Zhou ◽  
David C. Schwartz ◽  
Jian Ma
Keyword(s):  
Whole Genome Sequencing ◽  
Genome Sequencing ◽  
Copy Number ◽  
Graphical Model ◽  
Genome Structure ◽  
Cancer Genome ◽  
Whole Genome ◽  
Structural Variations ◽  
Cancer Genomes ◽  
Allele Specific

AbstractOne of the hallmarks of cancer genome is aneuploidy, resulting in abnormal copy numbers of alleles. Structural variations (SVs) can further modify the aneuploid cancer genomes into a mixture of rearranged genomic segments with extensive range of somatic copy number alterations (CNAs). Indeed, aneuploid cancer genomes have significantly higher rate of CNAs and SVs. However, although methods have been developed to identify SVs and allele-specific copy number of genome (ASCNG) separately, no existing algorithm can simultaneously analyze SVs and ASCNG. Such integrated approach is particularly important to fully understand the complexity of cancer genomes. Here we introduce a new algorithm called Weaver to provide allele-specific quantification of SVs and CNAs in aneuploid cancer genomes. Weaver uses a probabilistic graphical model by utilizing cancer whole genome sequencing data to simultaneously estimate the digital copy number and inter-connectivity of SVs. Our simulation evaluation, comparison with single-molecule Optical Mapping analysis, and real data applications (including MCF-7, HeLa, and TCGA whole genome sequencing samples) demonstrated that Weaver is highly accurate and can greatly refine the analysis of complex cancer genome structure.

scholarly journals Pan-cancer pharmacogenetics: targeted sequencing panels or exome sequencing?

2020 ◽  
Vol 21 (15) ◽  
pp. 1073-1084
Author(s):  
Laurentijn Tilleman ◽  
Björn Heindryckx ◽  
Dieter Deforce ◽  
Filip Van Nieuwerburgh
Keyword(s):  
Drug Interactions ◽  
Exome Sequencing ◽  
Informed Choice ◽  
Cancer Genome ◽  
The Cancer Genome Atlas ◽  
Targeted Sequencing ◽  
Driver Mutations ◽  
Cancer Genome Atlas ◽  
Pan Cancer ◽  
Genome Atlas

Aim: This study provides clinicians and researchers with an informed choice between current commercially available targeted sequencing panels and exome sequencing panels in the context of pan-cancer pharmacogenetics. Materials & methods: Nine contemporary commercially available targeted pan-cancer panels and the xGen Exome Research Panel v2 were investigated to determine to what extent they cover the pharmacogenetic variant–drug interactions in five available cancer knowledgebases, and the driver mutations and fusion genes in the Cancer Genome Atlas. Results: xGen Exome Research Panel v2 and TrueSight Oncology 500 target 71.0 and 68.9% of the pharmacogenetic interactions in the available knowledgebases; and 93.7 and 86.0% of the driver mutations in the Cancer Genome Atlas, respectively. All other studied panels target lower percentages. Conclusion: Exome sequencing outperforms pan-cancer targeted sequencing panels in terms of covered cancer pharmacogenetic variant–drug interactions and pharmacogenetic cancer variants.

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