High-throughput mutational analysis of the human cancer genome

2006 ◽  
Vol 7 (4) ◽  
pp. 597-612 ◽  
Author(s):  
Patrick C Ma ◽  
Xiaodong Zhang ◽  
Zhenghe J Wang
Author(s):  
Pieter-Jan van Dam ◽  
Steven Van Laere

Recent efforts by worldwide consortia such as The Cancer Genome Atlas and the International Cancer Genome Consortium have greatly accelerated our knowledge of human cancer biology. Nowadays, complete sets of human tumours that have been characterized at the genomic, epigenomic, transcriptomic, or proteomic level are available to the research community. The generation of these data was made possible thanks to the application of high-throughput molecular profiling techniques such as microarrays and next-generation sequencing. The primary conclusion from current profiling experiments is that human cancer is a complex disease characterized by extreme molecular heterogeneity, both between and within the classical, tissue-defined cancer types. This molecular variety necessitates a paradigm shift in patient management, away from generalized therapy schemes and towards more personalized treatments. This chapter provides an overview of how molecular cancer profiling can assist in facilitating this transition. First, the state-of-the-art of molecular breast cancer profiling is reviewed to provide a general background. Then, the most pertinent high-throughput molecular profiling techniques along with various data mining techniques (i.e. unsupervised clustering, statistical learning) are discussed. Finally, the challenges and perspectives with respect to molecular cancer profiling, also from the perspective of personalized medicine, are summarized.


2021 ◽  
pp. 247255522110006
Author(s):  
Lesley-Anne Pearson ◽  
Charlotte J. Green ◽  
De Lin ◽  
Alain-Pierre Petit ◽  
David W. Gray ◽  
...  

Severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) represents a significant threat to human health. Despite its similarity to related coronaviruses, there are currently no specific treatments for COVID-19 infection, and therefore there is an urgent need to develop therapies for this and future coronavirus outbreaks. Formation of the cap at the 5′ end of viral RNA has been shown to help coronaviruses evade host defenses. Nonstructural protein 14 (nsp14) is responsible for N7-methylation of the cap guanosine in coronaviruses. This enzyme is highly conserved among coronaviruses and is a bifunctional protein with both N7-methyltransferase and 3′-5′ exonuclease activities that distinguish nsp14 from its human equivalent. Mutational analysis of SARS-CoV nsp14 highlighted its role in viral replication and translation efficiency of the viral genome. In this paper, we describe the characterization and development of a high-throughput assay for nsp14 utilizing RapidFire technology. The assay has been used to screen a library of 1771 Food and Drug Administration (FDA)-approved drugs. From this, we have validated nitazoxanide as a selective inhibitor of the methyltransferase activity of nsp14. Although modestly active, this compound could serve as a starting point for further optimization.


2019 ◽  
Vol 11 (1) ◽  
Author(s):  
Hyunbin Kim ◽  
Andy Jinseok Lee ◽  
Jongkeun Lee ◽  
Hyonho Chun ◽  
Young Seok Ju ◽  
...  

Abstract Background Accurate identification of real somatic variants is a primary part of cancer genome studies and precision oncology. However, artifacts introduced in various steps of sequencing obfuscate confidence in variant calling. Current computational approaches to variant filtering involve intensive interrogation of Binary Alignment Map (BAM) files and require massive computing power, data storage, and manual labor. Recently, mutational signatures associated with sequencing artifacts have been extracted by the Pan-cancer Analysis of Whole Genomes (PCAWG) study. These spectrums can be used to evaluate refinement quality of a given set of somatic mutations. Results Here we introduce a novel variant refinement software, FIREVAT (FInding REliable Variants without ArTifacts), which uses known spectrums of sequencing artifacts extracted from one of the largest publicly available catalogs of human tumor samples. FIREVAT performs a quick and efficient variant refinement that accurately removes artifacts and greatly improves the precision and specificity of somatic calls. We validated FIREVAT refinement performance using orthogonal sequencing datasets totaling 384 tumor samples with respect to ground truth. Our novel method achieved the highest level of performance compared to existing filtering approaches. Application of FIREVAT on additional 308 The Cancer Genome Atlas (TCGA) samples demonstrated that FIREVAT refinement leads to identification of more biologically and clinically relevant mutational signatures as well as enrichment of sequence contexts associated with experimental errors. FIREVAT only requires a Variant Call Format file (VCF) and generates a comprehensive report of the variant refinement processes and outcomes for the user. Conclusions In summary, FIREVAT facilitates a novel refinement strategy using mutational signatures to distinguish artifactual point mutations called in human cancer samples. We anticipate that FIREVAT results will further contribute to precision oncology efforts that rely on accurate identification of variants, especially in the context of analyzing mutational signatures that bear prognostic and therapeutic significance. FIREVAT is freely available at https://github.com/cgab-ncc/FIREVAT


2012 ◽  
Author(s):  
Adam P. Butler ◽  
Jon W. Teague ◽  
Keiran M. Raine ◽  
Andrew Menzies ◽  
David Jones ◽  
...  

Author(s):  
Mark F Rogers ◽  
Tom R Gaunt ◽  
Colin Campbell

Abstract Sequencing technologies have led to the identification of many variants in the human genome which could act as disease-drivers. As a consequence, a variety of bioinformatics tools have been proposed for predicting which variants may drive disease, and which may be causatively neutral. After briefly reviewing generic tools, we focus on a subset of these methods specifically geared toward predicting which variants in the human cancer genome may act as enablers of unregulated cell proliferation. We consider the resultant view of the cancer genome indicated by these predictors and discuss ways in which these types of prediction tools may be progressed by further research.


2011 ◽  
Vol 108 (12) ◽  
pp. 1801-1807 ◽  
Author(s):  
Naomi Ogawa ◽  
Yasushi Imai ◽  
Yuji Takahashi ◽  
Kan Nawata ◽  
Kazuo Hara ◽  
...  

Small ◽  
2015 ◽  
Vol 11 (46) ◽  
pp. 6215-6224 ◽  
Author(s):  
Kyung Hoon Kim ◽  
Jung Kim ◽  
Jong Seob Choi ◽  
Sunwoong Bae ◽  
Donguk Kwon ◽  
...  

2011 ◽  
Vol 16 (4) ◽  
pp. 383-393 ◽  
Author(s):  
Hui-Fang Li ◽  
Adam Keeton ◽  
Michele Vitolo ◽  
Clinton Maddox ◽  
Lynn Rasmussen ◽  
...  

The PTEN tumor suppressor gene is one of the most commonly mutated genes in human cancer. Because inactivation of PTEN is a somatic event, PTEN mutations represent an important genetic difference between cancer cells and normal cells and therefore a potential anticancer drug target. However, it remains a substantial challenge to identify compounds that target loss-of-function events such as mutations of tumor suppressors. In an effort to identify small molecules that preferentially kill cells with mutations of PTEN, the authors developed and implemented a high-throughput, paired cell-based screen composed of parental HCT116 cells and their PTEN gene-targeted derivatives. From 138 758 compounds tested, two hits were identified, and one, N′-[(1-benzyl-1H-indol-3-yl)methylene]benzenesulfonohydrazide (CID1340132), was further studied using a variety of cell-based models, including HCT116, MCF10A, and HEC1A cells with targeted deletion of either their PTEN or PIK3CA genes. Preferential killing of PTEN and PIK3CA mutant cells was accompanied by DNA damage, inhibition of DNA synthesis, and apoptosis. Taken together, these data validate a cell-based screening approach for identifying lead compounds that target cells with specific tumor suppressor gene mutations and describe a novel compound with preferential killing activity toward PTEN and PIK3CA mutant cells.


Sign in / Sign up

Export Citation Format

Share Document