AACR Centennial Conference: Translational Cancer Medicine-- Nov 4-8, 2007; Singapore

PL02-05 

All cancers are due to abnormalities in DNA. The availability of the human genome sequence has led to the proposal that resequencing of cancer genomes will reveal the full complement of somatic mutations and hence all the cancer genes. To explore the nature of the information that will be derived from cancer genome sequencing we have sequenced the coding exons of the family of 518 protein kinases, ~1.3Mb DNA per cancer sample, in 210 cancers of diverse histological types. Despite the screen being directed toward the coding regions of a gene family that has previously been strongly implicated in oncogenesis, the results indicate that the majority of somatic mutations detected are “passengers”. There is considerable variation in the number and pattern of these mutations between individual cancers, indicating substantial diversity of processes of molecular evolution between cancers. The imprints of exogenous mutagenic exposures, mutagenic treatment regimes and DNA repair defects can all be seen in the distinctive mutational signatures of individual cancers. This systematic mutation screen and others have previously yielded a number of cancer genes that are frequently mutated in one or more cancer types and which are now anticancer drug targets (for example BRAF , PIK3CA , and EGFR ). However, detailed analyses of the data from our screen additionally suggest that there exist a large number of additional “driver” mutations which are distributed across a substantial number of genes. It therefore appears that cells may be able to utilise mutations in a large repertoire of potential cancer genes to acquire the neoplastic phenotype. However, many of these genes are employed only infrequently. These findings may have implications for future anticancer drug development.

Patterns of Somatic Mutation in Human Cancer Genomes

基礎講座 電気泳動(Electrophoresis)

Context: The interpretation of novel missense variants is a challenge with increasing numbers of such variants being identified and a responsibility to report the findings in the context of all available scientific evidence. Various in silico bioinformatic tools have been developed that predict the likely pathogenicity of missense variants; however, their utility within the diagnostic setting requires further investigation. Aim: The aim of our study was to test the predictive value of two of these tools, sorting intolerant from tolerant (SIFT) and polymorphism phenotyping (PolyPhen), in a set of 141 missense variants (131 pathogenic, 8 benign) identified in the ABCC8, GCK, and KCNJ11 genes. Methods: Sixty-six of the mutations caused a gain of protein function, while 67 were loss-of-function mutations. The evolutionary conservation at each residue was also investigated using multiple sequence alignments from the UCSC genome browser. Results: The sensitivity of SIFT and PolyPhen was reasonably high (69% and...

Using SIFT and PolyPhen to Predict Loss-of-Function and Gain-of-Function Mutations

Lamin A/C proteins are the major components of a thin proteinaceous filamentous meshwork, the lamina, that underlies the inner nuclear membrane. A few specific mutations in the lamin A/C gene cause a disease with remarkably different clinical features: FPLD, or familial partial lipodystrophy (Dunnigan-type), which mainly affects adipose tissue. Lamin A/C mutant R482W is the key variant that causes FPLD. Biomolecular interaction and molecular dynamics (MD) simulation analysis were performed to understand dynamic behavior of native and mutant structures at atomic level. Mutant lamin A/C (R482W) showed more interaction with its biological partners due to its expansion of interaction surface and flexible nature of binding residues than native lamin A/C. MD simulation clearly indicates that the flexibility of interacting residues of mutant are mainly due to less involvement in formation of inter and intramolecular hydrogen bonds. Our analysis of native and Mutant lamin A/C clearly shows that the structural and functional consequences of the mutation R482W causes FPLD. Because of the pivotal role of lamin A/C in maintaining dynamics of nuclear function, these differences likely contribute to or represent novel mechanisms in laminopathy development.

https://link.springer.com/content/pdf/10.1007%2Fs00726-011-1108-7.pdf

In silico investigation of molecular mechanism of laminopathy caused by a point mutation (R482W) in lamin A/C protein

Tuberculosis continues to be a global health threat. Pyrazinamide (PZA) is an important first-line drug in multidrug-resistant tuberculosis treatment. The emergence of strains resistant to PZA represents an important public health problem, as both first- and second-line treatment regimens include PZA. It becomes toxic to Mycobacterium tuberculosis when converted to pyrazinoic acid by the bacterial pyrazinamidase (PncA) enzyme. Resistance to PZA is caused mainly by the loss of enzyme activity by mutation, the mechanism of resistance is not completely understood. In our studies, we analysed three mutations (D8G, S104R and C138Y) of PncA which are involved in resistance towards PZA. Binding pocket analysis solvent accessibility analysis, molecular docking and interaction analysis were performed to understand the interaction behaviour of mutant enzymes with PZA. Molecular dynamics simulations were conducted to understand the three-dimensional (3D) conformational behaviour of native and mutants PncA. Our analy...

Drug resistance mechanism of PncA in Mycobacterium tuberculosis

Identification and in silico analysis of functional SNPs of the BRCA1 gene.

Targeting inflammatory mediators with ferulic acid, a dietary polyphenol, for the suppression of monosodium urate crystal-induced inflammation in rats.

Single Nucleotide Polymorphisms (SNPs) are being intensively studied to understand the biological basis of complex traits and diseases. The Genetics of human phenotype variation could be understood by knowing the functions of SNPs. In this study using computational methods, we analyzed the genetic variations that can alter the expression and function of the CFTR gene responsible candidate for causing cystic fibrosis. We applied an evolutionary perspective to screen the SNPs using a sequence homology-based SIFT tool, which suggested that 17 nsSNPs (44%) were found to be deleterious. The structure-based approach PolyPhen server suggested that 26 nsSNPS (66%) may disrupt protein function and structure. The PupaSuite tool predicted the phenotypic effect of SNPs on the structure and function of the affected protein. Structure analysis was carried out with the major mutation that occurred in the native protein coded by CFTR gene, and which is at amino acid position F508C for nsSNP with id (rs1800093). The amino acid residues in the native and mutant modeled protein were further analyzed for solvent accessibility, secondary structure and stabilizing residues to check the stability of the proteins. The SNPs were further subjected to iHAP analysis to identify htSNPs, and we report potential candidates for future studies on CFTR mutations.

/pdf/a-novel-computational-and-structural-analysis-of-nssnps-in-210jchbspg.pdf

A novel computational and structural analysis of nsSNPs in CFTR gene.

Single nucleotide polymorphisms (SNPs) are the most common type of genetic variations in humans Understanding the functions of SNPs can greatly help to understand the genetics of the human phenotype variation and especially the genetic basis of human complex diseases The method to identify functional SNPs from a pool, containing both functional and neutral SNPs is challenging by experimental protocols To explore possible relationships between genetic mutation and phenotypic variation, different computational algorithm tools like Sorting Intolerant from Tolerant, Polymorphism Phenotyping, UTRscan, FASTSNP, and PupaSuite were used for prioritization of high-risk SNPs in coding region (exonic nonsynonymous SNPs) and noncoding regions (intronic and exonic 5' and 3'-untranslated region (UTR) SNPs) In this work, we have analyzed the SNPs that can alter the expression and function of transcriptional factor TP53 as a pipeline and for providing a guide to experimental work We identified the possible mutations and proposed modeled structure for the mutant proteins and compared them with the native protein These nsSNPs play a critical role in cancer association studies aiming to explain the disparity in cancer treatment responses as well as to improve the effectiveness of the cancer treatments Our results endorse the study with in vivo experimental protocols

C. Sudandiradoss

Papers

Identification and in silico analysis of functional SNPs of the BRCA1 gene.

Targeting inflammatory mediators with ferulic acid, a dietary polyphenol, for the suppression of monosodium urate crystal-induced inflammation in rats.

A novel computational and structural analysis of nsSNPs in CFTR gene.

Applications of computational algorithm tools to identify functional SNPs

Computational and structural investigation of deleterious functional SNPs in breast cancer BRCA2 gene.