In Silico Identification of Significant Detrimental Missense Mutations of EGFR and Their Effect with 4-Anilinoquinazoline-Based Drugs

Rajasekaran, R.; Sethumadhavan, Rao

doi:10.1007/s12010-009-8662-4

Cited by 14 publications

(9 citation statements)

References 38 publications

(53 reference statements)

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“…Results from paired archival/biopsy specimens obtained a median 33 months apart were concordant in 30/34 (88%) patients. Three somatic mutations, PDGFRA R718W, AKT1 E341K and EGFR Q787L, had unknown function based on review of public databases and published literature, although in silico studies suggest that an EGFR Q787R substitution may be activating 18…”

Section: Resultsmentioning

confidence: 99%

Feasibility of real time next generation sequencing of cancer genes linked to drug response: Results from a clinical trial

Tran

Brown

Bedard

et al. 2012

Intl Journal of Cancer

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The successes of targeted drugs with companion predictive biomarkers and the technological advances in gene sequencing have generated enthusiasm for evaluating personalized cancer medicine strategies using genomic profiling. We assessed the feasibility of incorporating real-time analysis of somatic mutations within exons of 19 genes into patient management. Blood, tumor biopsy and archived tumor samples were collected from 50 patients recruited from four cancer centers. Samples were analyzed using three technologies: targeted exon sequencing using Pacific Biosciences PacBio RS, multiplex somatic mutation genotyping using Sequenom MassARRAY and Sanger sequencing. An expert panel reviewed results prior to reporting to clinicians. A clinical laboratory verified actionable mutations. Fifty patients were recruited. Nineteen actionable mutations were identified in 16 (32%) patients. Across technologies, results were in agreement in 100% of biopsy specimens and 95% of archival specimens. Profiling results from paired archival/biopsy specimens were concordant in 30/34 (88%) patients. We demonstrated that the use of next generation sequencing for real-time genomic profiling in advanced cancer patients is feasible. Additionally, actionable mutations identified in this study were relatively stable between archival and biopsy samples, implying that cancer mutations that are good predictors of drug response may remain constant across clinical stages.International efforts to quantify and catalogue mutations, gene expression and epigenetic data for multiple forms of cancer, coupled with the successes of targeted agents in patients with molecularly defined tumors and improvements in genomic technology, have increased enthusiasm to adopt genomic profiling into clinical cancer practice. 1 As the numbers of clinically significant genetic variants have increased, clinical testing has evolved, moving from single mutations to multiplex hotspot evaluations in multiple cancer genes. Several pilot studies have demonstrated the feasibility and potential benefits of real-time multiplex hotspot evaluations in various cancer types. 2-8 However, as improvements in genomic technology overcome previous concerns of cost, complexity, time and tissue requirements, an increasing interest in adopting next generation sequencing (NGS) for genomic profiling in clinical cancer practice has developed. 6,9,10 Roychowdhury et al. recently reported the use of integrative sequencing in the clinic and demonstrated its potential to facilitate biomarker driven clinical trials. 11 However, it remains unclear whether the use of high-throughput, real-time NGS for genomic profiling is capable of generating results in a timeframe that allows for changes to patient management. Furthermore, the additional value of NGS over the multiplex hotspot genotyping approach is unclear, and

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Section: Resultsmentioning

confidence: 99%

Feasibility of real time next generation sequencing of cancer genes linked to drug response: Results from a clinical trial

Tran

Brown

Bedard

et al. 2012

Intl Journal of Cancer

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“…Hence, independent evidence of functionality of SNPs obtained by using prediction tools could also serve as additional argument to discriminate true associations from false positives [5], as shown recently by the functional SNP analysis of the BRCA1 , ABL1 , ERBB2 , CFTR , and EGFR genes [10–14]. …”

Section: Introductionmentioning

confidence: 99%

A ComprehensiveIn SilicoAnalysis of the Functional and Structural Impact of SNPs in theIGF1RGene

Alencar

Lopes

2010

Journal of Biomedicine and Biotechnology

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Insulin-like growth factor 1 receptor (IGF1R) acts as a critical mediator of cell proliferation and survival. Many single nucleotide polymorphisms (SNPs) found in the IGF1R gene have been associated with various diseases, including both breast and prostate cancer. The genetics of these diseases could be better understood by knowing the functions of these SNPs. In this study, we performed a comprehensive analysis of the functional and structural impact of all known SNPs in this gene using publicly available computational prediction tools. Out of a total of 2412 SNPs in IGF1R retrieved from dbSNP, we found 32 nsSNPs, 58 sSNPs, 83 mRNA 3′ UTR SNPs, and 2225 intronic SNPs. Among the nsSNPs, a total of six missense nsSNPs were found to be damaging by both a sequence homology-based tool (SIFT) and a structural homology-based method (PolyPhen), and one nonsense nsSNP was found. Further, we modeled mutant proteins and compared the total energy values with the native IGF1R protein, and showed that a mutation from arginine to cysteine at position 1216 (rs61740868) on the surface of the protein caused the greatest impact on stability. Also, the FASTSNP tool suggested that 31 sSNPs and 3 intronic SNPs might affect splicing regulation. Based on our investigation, we report potential candidate SNPs for future studies on IGF1R mutations.

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“…Change in total energy due to H-I Hydrophobic interaction within 5 Å , MC-MC main chain-main chain hydrogen bonds, MC-SC main chain-side chain hydrogen bonds, SC-SC side chain-side chain hydrogen bonds, I-I ionic interactions within 6 Å , A-A aromatic-aromatic interactions within 4.5 and 7 Å , A-S aromatic-sulfur interactions within 5.3 Å , C-p cation-pi interaction within 6 Å In silico analysis of detrimental mutations 129 mutation was noticeable in the 3QLN mutants ranging from -8,521.195 to -8,614.933 kJ/mol. Higher the total energy, lesser the stability of protein structure would be (Rajasekaran and Sethumadhavan 2010b). Since, all the 17 mutants had the total energy higher than the native structure; we considered these missense mutations to have deleterious effect based on structural stability.…”

Section: Computing Total Energy and Rmsd By Modeling Of Mutant Structmentioning

confidence: 99%

In silico analysis of detrimental mutations in ADD domain of chromatin remodeling protein ATRX that cause ATR-X syndrome: X-linked disorder

Chandrasekaran

Doss

Nisha³

et al. 2013

Netw Model Anal Health Inform Bioinforma

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Many biological functions involve specific interactions of proteins. Mutations in ATRX gene can change the sequence and structure of a protein thereby impairing its function. Thus, the dysfunction of chromatin remodeling protein ATRX as a result of amino acid substitution in ADD domain often underlies the human disease, ATR-X syndrome. In general, it is mainly caused by amino acid substitution that interfered with the interactions of interest at the interface level. Hence, the study of protein-protein interactions and the interface that mediate the interactions stand important for understanding of biological function. In this work, we address the loss of function in chromatin remodeling protein ATRX due to loss of structural stability that affect the functional activity in mutant ADD domain by 17 missense mutations viz., G175E, N179S, P190A, P190L, P190S, L192F, V194I, C200S, Q219P, C220R, C220Y, W222S, C243F, R246C, R246L, G249C, and G249D. Furthermore, the loss of binding affinity of ADD domain with their interacting partner namely histone H3-peptide were investigated by (1) computing the RMSD (root mean square deviation) for the ADD domain of native with all the 17 mutants, (2) computing intra-molecular interactions in ADD domain of native with all the mutants, (3) computing binding affinity of native and mutant structures of ADD domain with histone H3-peptide through docking studies, and (4) cross validating the loss of function on binding affinity through inter-molecular interactions and normal mode analysis. Finally, as from our computational result, we concluded that all the parameters mentioned above used for studying ADD domain of mutant structures showed the decreased potential values compared to native structure that underlie ATR-X syndrome.

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In Silico Identification of Significant Detrimental Missense Mutations of EGFR and Their Effect with 4-Anilinoquinazoline-Based Drugs

Cited by 14 publications

References 38 publications

Feasibility of real time next generation sequencing of cancer genes linked to drug response: Results from a clinical trial

Feasibility of real time next generation sequencing of cancer genes linked to drug response: Results from a clinical trial

A ComprehensiveIn SilicoAnalysis of the Functional and Structural Impact of SNPs in theIGF1RGene

In silico analysis of detrimental mutations in ADD domain of chromatin remodeling protein ATRX that cause ATR-X syndrome: X-linked disorder

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