Biomedical subjects

Tian-Li Wang

Publications and source records attributed to Tian-Li Wang.

4 recordsLinked to original sources

PubMed2003

Identifying tumor origin using a gene expression-based classification map.

Identifying the primary site in cases of metastatic carcinoma of unknown origin has profound clinical importance in managing cancer patients. Although transcriptional profiling promises molecular solutions to this clinical challenge, simpler and more reliable methods for this purpose are needed. A training set of 11 serial analysis of gene expression (SAGE) libraries was analyzed using a combination of supervised and unsupervised computational methods to select a small group of candidate genes with maximal power to discriminate carcinomas of different tissue origins. Quantitative real-time PCR was used to measure their expression levels in an independent validation set of 62 samples of ovarian, breast, colon, and pancreatic adenocarcinomas and normal ovarian surface epithelial controls. The diagnostic power of this set of genes was evaluated using unsupervised cluster analysis methods. From the training set of 21,321 unique SAGE transcript tags derived from 11 libraries, five genes were identified with expression patterns that distinguished four types of adenocarcinomas. Quantitative real-time PCR expression data obtained from the validation set clustered tumor samples in an unsupervised manner, generating a self-organized map with distinctive tumor site-specific domains. Eighty-one percent (50 of 62) of the carcinomas were correctly allocated in their corresponding diagnostic regions. Metastases clustered tightly with their corresponding primary tumors. A classification map diagnostic of tumor types was generated based on expression patterns of five genes selected from the SAGE database. This expression map analysis may provide a reliable and practical approach to determine tumor type in cases of metastatic carcinoma of clinically unknown origin.

Adenocarcinoma↗

PubMed2002

Digital karyotyping.

Alterations in the genetic content of a cell are the underlying cause of many human diseases, including cancers. We have developed a method, called digital karyotyping, that provides quantitative analysis of DNA copy number at high resolution. This approach involves the isolation and enumeration of short sequence tags from specific genomic loci. Analysis of human cancer cells by using this method identified gross chromosomal changes as well as amplifications and deletions, including regions not previously known to be altered. Foreign DNA sequences not present in the normal human genome could also be readily identified. Digital karyotyping provides a broadly applicable means for systematic detection of DNA copy number changes on a genomic scale.

Analog-Digital Conversion↗

PubMed2002

Light response of retinal ON bipolar cells requires a specific splice variant of Galpha(o).

Glutamate released onto retinal ON bipolar neurons binds to a metabotropic receptor to activate a heterotrimeric G-protein (G(o)) that ultimately closes a nonspecific cation channel. Signaling requires the alpha subunit (Galpha(o)), but its effector is unknown. Because Galpha(o) is transcribed into two splice variants (alpha(o1) and alpha(o2)) that differ in the key GTPase domain, the next step in elucidating this pathway was to determine which splice variant carries the signal. Here we show by reverse transcription-PCR and Western blots that retina expresses both splice variants. Furthermore, in situ hybridization and immunostaining on mouse retina deficient in one splice variant or the other show that both alpha(o1) and alpha(o2) are expressed by ON bipolar cells but that alpha(o1) is much more abundant. Finally, electroretinography performed on mice deficient for one splice variant or the other shows that the positive b-wave (response of ON bipolar cells to rod and cone input) requires alpha(o1) but not alpha(o2). Thus, the light response of the ON bipolar cell is probably carried by its strongly expressed splice variant, Galpha(o1).

Alternative Splicing↗

PubMed2002

Prevalence of somatic alterations in the colorectal cancer cell genome.

Although a small fraction of human cancers have increased rates of somatic mutation because of known deficiencies in DNA repair, little is known about the prevalence of somatic alterations in the vast majority of human cancers. To systematically assess nonsynonymous somatic alterations in colorectal neoplasia, we used DNA sequencing to analyze approximately 3.2 Mb of coding tumor DNA comprising 1,811 exons from 470 genes. In total, we identified only three distinct somatic mutations, comprising two missense changes and one 14-bp deletion, each in a different gene. The accumulation of approximately one nonsynonymous somatic change per Mb of tumor DNA is consistent with a rate of mutation in tumor cells that is similar to that of normal cells. These data suggest that most sporadic colorectal cancers do not display a mutator phenotype at the nucleotide level. They also have significant implications for the interpretation of somatic mutations in candidate tumor-suppressor genes.

Colorectal Neoplasms↗