Biomedical subjects

Ajay N Jain

Publications and source records attributed to Ajay N Jain.

6 recordsLinked to original sources

PubMed2003

Surflex: fully automatic flexible molecular docking using a molecular similarity-based search engine.

Surflex is a fully automatic flexible molecular docking algorithm that combines the scoring function from the Hammerhead docking system with a search engine that relies on a surface-based molecular similarity method as a means to rapidly generate suitable putative poses for molecular fragments. Results are presented evaluating reliability and accuracy of dockings compared with crystallographic experimental results on 81 protein/ligand pairs of substantial structural diversity. In over 80% of the complexes, Surflex's highest scoring docked pose was within 2.5 A root-mean-square deviation (rmsd), with over 90% of the complexes having one of the top ranked poses within 2.5 A rmsd. Results are also presented assessing Surflex's utility as a screening tool on two protein targets (thymidine kinase and estrogen receptor) using data sets on which competing methods were run. Performance of Surflex was significantly better, with true positive rates of greater than 80% at false positive rates of less than 1%. Docking time was roughly linear in number of rotatable bonds, beginning with a few seconds for rigid molecules and adding approximately 10 s per rotatable bond.

Algorithms↗

PubMed2003

High-resolution analysis of paraffin-embedded and formalin-fixed prostate tumors using comparative genomic hybridization to genomic microarrays.

We have used prostate cancer, the most commonly diagnosed noncutaneous neoplasm among men, to investigate the feasibility of performing genomic array analyses of archival tissue. Prostate-specific antigen and a biopsy Gleason grade have not proven to be accurate in predicting clinical outcome, yet they remain the only accepted biomarkers for prostate cancer. It is likely that distinct spectra of genomic alterations underlie these phenotypic differences, and that once identified, may be used to differentiate between indolent and aggressive tumors. Array comparative genomic hybridization allows quantitative detection and mapping of copy number aberrations in tumors and subsequent associations to be made with clinical outcome. Archived tissues are needed to have patients with sufficient clinical follow-up. In this report, 20 formalin-fixed and paraffin-embedded prostate cancer samples originating from 1986 to 1996 were studied. We present a straightforward protocol and demonstrate the utility of archived tissue for array comparative genomic hybridization with a 2400 element BAC array that provides high-resolution detection of both deletions and amplifications.

Chromosome Aberrations↗

PubMed2002

Genomic copy number analysis of non-small cell lung cancer using array comparative genomic hybridization: implications of the phosphatidylinositol 3-kinase pathway.

Genomic abnormalities at 348 loci encoding genes that may contribute to lung cancer transformation and progression were assessed using array comparative genomic hybridization in 21 squamous carcinomas (SqCas) and 16 adenocarcinomas (AdCas). Hierarchical clustering showed a clear pattern of gains and losses for the SqCas, whereas the pattern for AdCas was less distinct. Cross-validated classification using a K-nearest-neighbor assigned, on average, 32 of 37 samples to their proper histological subtype. The most noticeable differences between SqCas and AdCas were gain of chromosome 3q22-q26 and loss of chromosome 3p. These occurred almost exclusively in SqCas. The region of recurrent increase is approximately 30 Mb in extent, ranging from EVI1 to TFRC. PIK3CA, the alpha catalytic subunit of phosphatidylinositol 3-kinase (PI3K), is in this region. The PIK3CA copy number increase was validated using fluorescence in situ hybridization to lung cancer tissue microarrays. Activity of the downstream PI3K effector protein kinase B (PKB) was higher in SqCas than in AdCas and was correlated with PIK3CA copy number (r = 0.75), suggesting that these copy number increases contribute to activation of PI3K signaling in SqCas of the lung.

Adenocarcinoma↗

PubMed2002

Array-based comparative genomic hybridization for the differential diagnosis of renal cell cancer.

Array-based comparative genomic hybridization (CGH) uses multiple genomic clones arrayed on a slide to detect relative copy number of tumor DNA sequences. Application of array CGH to tumor specimens makes genetic diagnosis of cancers possible and may help to differentiate relevant subsets of tumors, biologically and clinically, which would allow better prognostic and therapeutic decision making. In this study, we have used array-based CGH to detect DNA copy number alterations in distinct types of renal cell carcinomas for diagnostic purposes. We were able to correctly diagnose 33 of 34 malignant tumors by automated computational means and to group together eight benign neoplasms and normal kidney samples. These results indicate that array-based CGH is capable of diagnosing the vast majority of renal cell carcinomas based on their genetic profiles.

Carcinoma, Renal Cell↗

PubMed2002

Deriving quantitative conclusions from microarray expression data.

MOTIVATION: The last few years have seen the development of DNA microarray technology that allows simultaneous measurement of the expression levels of thousands of genes. While many methods have been developed to analyze such data, most have been visualization-based. Methods that yield quantitative conclusions have been diverse and complex. RESULTS: We present two straightforward methods for identifying specific genes whose expression is linked with a phenotype or outcome variable as well as for systematically predicting sample class membership: (1) a conservative, permutation-based approach to identifying differentially expressed genes; (2) an augmentation of K-nearest-neighbor pattern classification. Our analyses replicate the quantitative conclusions of Golub et al. (1999; Science, 286, 531-537) on leukemia data, with better classification results, using far simpler methods. With the breast tumor data of Perou et al. (2000; Nature, 406, 747-752), the methods lend rigorous quantitative support to the conclusions of the original paper. In the case of the lymphoma data in Alizadeh et al. (2000; Nature, 403, 503-511), our analyses only partially support the conclusions of the original authors. AVAILABILITY: The software and supplementary information are available freely to researchers at academic and non-profit institutions at http://cc.ucsf.edu/jain/public

Breast Neoplasms↗

PubMed2002

Fully automatic quantification of microarray image data.

DNA microarrays are now widely used to measure expression levels and DNA copy number in biological samples. Ratios of relative abundance of nucleic acids are derived from images of regular arrays of spots containing target genetic material to which fluorescently labeled samples are hybridized. Whereas there are a number of methods in use for the quantification of images, many of the software systems in wide use either encourage or require extensive human interaction at the level of individual spots on arrays. We present a fully automatic system for microarray image quantification. The system automatically locates both subarray grids and individual spots, requiring no user identification of any image coordinates. Ratios are computed based on explicit segmentation of each spot. On a typical image of 6000 spots, the entire process takes less than 20 sec. We present a quantitative assessment of performance on multiple replicates of genome-wide array-based comparative genomic hybridization experiments. By explicitly identifying the pixels in each spot, the system yields more accurate estimates of ratios than systems assuming spot circularity. The software, called, runs on Windows platforms and is available free of charge for academic use.

Breast Neoplasms↗