Biomedical subjects

Ka Yin Kwong

Publications and source records attributed to Ka Yin Kwong.

7 recordsLinked to original sources

PubMed2006

Antitumor activity of an Ets protein, PEA3, in breast cancer cell lines MDA-MB-361DYT2 and BT474M1.

Polyomavirus enhancer activator 3 (PEA3) is a member of the Ets family of transcription factors. We demonstrated in a previous study that, by downregulating the HER-2/neu oncogene at the transcriptional level, PEA3 can inhibit the growth and development into tumors of HER-2/neu-overexpressing ovarian cancer cells. Here, we establish stable clones of the human breast cancer cell line MDA-MB-361DYT2 that express PEA3 under the control of a tetracycline-inducible promoter. Ectopic expression of PEA3 in this cell line inhibited cell growth and resulted in cell cycle accumulation in the G1 phase. We demonstrate that expression of PEA3 in an orthotopic breast cancer model inhibited tumor growth and prolonged the survival of tumor-bearing mice. In a parallel experiment with another breast cancer cell line, BT474M1, we were unable to obtain stable PEA3-inducible transfectants, suggesting that PEA3 may exert a strong growth inhibition effect in this cell line. Indeed, PEA3 coupled with the liposome SN2 demonstrated therapeutic effects in mice bearing tumors induced by BT474M1. These results provide evidence for the antitumor activity of PEA3 in human breast cancers.

Animals↗

PubMed2005

Molecular staging for survival prediction of colorectal cancer patients.

PURPOSE: The Dukes' staging system is the gold standard for predicting colorectal cancer prognosis; however, accurate classification of intermediate-stage cases is problematic. We hypothesized that molecular fingerprints could provide more accurate staging and potentially assist in directing adjuvant therapy. METHODS: A 32,000 cDNA microarray was used to evaluate 78 human colon cancer specimens, and these results were correlated with survival. Molecular classifiers were produced to predict outcome. RESULTS: Molecular staging, based on 43 core genes, was 90% accurate (93% sensitivity, 84% specificity) in predicting 36-month overall survival in 78 patients. This result was significantly better than Dukes' staging (P = .03878), discriminated patients into significantly different groups by survival time (P < .001, log-rank test), and was significantly different from chance (P < .001, 1,000 permutations). Furthermore, the classifier was able to discriminate a survival difference in an independent test set from Denmark. Molecular staging identifies patient prognosis (as represented by 36-month survival) more accurately than the traditional clinical staging, particularly for intermediate Dukes' stage B and C patients. The classifier was based on a core set of 43 genes, including osteopontin and neuregulin, which have biologic significance for this disease. CONCLUSION: These data support further evaluation of molecular staging to discriminate good from poor prognosis patients, with the potential to direct adjuvant therapy.

Adult↗

PubMed2005

Synchronous global assessment of gene and protein expression in colorectal cancer progression.

Well-established models of colorectal cancer progression are based on the idea that the disease evolves through a multistep process involving sequential genetic mutations, suggesting that progression through clinically defined stages should correlate with well-defined patterns of gene expression. The majority of studies to date, however, have assessed these processes one gene and one protein at a time. We report the first comprehensive assessment of both gene and protein expression performed in parallel across progressive stages of human colorectal neoplasia. Remarkably, despite the global nature of the gene expression assessment, very few genes could be linked with certainty to specific proteins through currently available annotations. Furthermore, the correlation of expression between identified genes and proteins was poor. Nevertheless, both produced expression signatures that differentiated normal mucosa and nonmalignant adenomas from each other and from the malignant carcinomas and both produced fairly consistent subclasses of the malignancies, suggesting that a molecular staging might be more appropriate provided that these profiles can be tied to clinical outcome. This is potentially important as clinical staging is widely used as a prognostic indicator and used in the decision to pursue adjuvant therapies.

Adenoma↗

PubMed2004

The limits of log-ratios.

BACKGROUND: DNA microarray assays typically compare two biological samples and present the results of those comparisons gene-by-gene as the logarithm base two of the ratio of the measured expression levels for the two samples. RESULTS: Because of the fixed dynamic range of fluorescence and other detection systems, there is a limit to the range of comparisons that can be made using any array technology, and this must be taken into account when interpreting the results of any such analysis. CONCLUSIONS: The dynamic range of microarray data collection systems results in limits in the comparative analyses that can be derived from such measurements and suggests that optimal results can be obtained by making measurements that avoid the boundaries of that dynamic range.

Algorithms↗

PubMed2004

Multi-platform, multi-site, microarray-based human tumor classification.

The introduction of gene expression profiling has resulted in the production of rich human data sets with potential for deciphering tumor diagnosis, prognosis, and therapy. Here we demonstrate how artificial neural networks (ANNs) can be applied to two completely different microarray platforms (cDNA and oligonucleotide), or a combination of both, to build tumor classifiers capable of deciphering the identity of most human cancers. First, 78 tumors representing eight different types of histologically similar adenocarcinoma, were evaluated with a 32k cDNA microarray and correctly classified by a cDNA-based ANN, using independent training and test sets, with a mean accuracy of 83%. To expand our approach, oligonucleotide data derived from six independent performance sites, representing 463 tumors and 21 tumor types, were assembled, normalized, and scaled. An oligonucleotide-based ANN, trained on a random fraction of the tumors (n = 343), was 88% accurate in predicting known pathological origin of the remaining fraction of tumors (n = 120) not exposed to the training algorithm. Finally, a mixed-platform classifier using a combination of both cDNA and oligonucleotide microarray data from seven performance sites, normalized and scaled from a large and diverse tumor set (n = 539), produced similar results (85% accuracy) on independent test sets. Further validation of our classifiers was achieved by accurately (84%) predicting the known primary site of origin for an independent set of metastatic lesions (n = 50), resected from brain, lung, and liver, potentially addressing the vexing classification problems imposed by unknown primary cancers. These cDNA- and oligonucleotide-based classifiers provide a first proof of principle that data derived from multiple platforms and performance sites can be exploited to build multi-tissue tumor classifiers.

Algorithms↗

PubMed2002

The suppression of colon cancer cell growth in nude mice by targeting beta-catenin/TCF pathway.

The adenomatous polyposis coli (APC) or beta-catenin genes are frequently mutated in colorectal cancers, leading to activation of downstream genes with beta-catenin/T-cell factor (Tcf)-responsive promoters. We have developed a gene therapy approach selectively targeting colorectal cancer cells in which beta-catenin/Tcf4 pathway is activated by using a recombinant adenovirus AdTOP-CMV-TK, which carries a herpes simplex virus thymidine kinase gene (HSV TK) under the control of a beta-catenin/Tcf-response promoter linking to a minimum CMV promoter. AdTOP-CMV-TK and ganciclovir (GCV) treatment significantly suppressed the growth of human DLD-1 colon cancer cells in nude mice. Furthermore, no significant tumor suppression effect was observed in human hepatoma cell line SK-HEP-1, in which the beta-catenin/Tcf pathway is not activated, as a control experiment. In summary, we demonstrated the selective targeting of colorectal cancers with activated beta-catenin by AdTOP-CMV-TK and GCV treatment in animal models, as well as its therapeutic potential for colon cancer metastasized to liver.

Animals↗

PubMed2002

Proapoptotic and antitumor activities of adenovirus-mediated p202 gene transfer.

PURPOSE AND EXPERIMENTAL DESIGN: p202, a mouse IFN-inducible protein, is a member of the 200-amino acid repeat family. Enforced p202 expression in stable cancer cell lines resulted in growth inhibition in vitro and tumor suppression in vivo. However, to study the immediate effect of p202 and test the potential efficacy of p202 treatment, an efficient gene delivery system for p202 is required. For these purposes, an adenoviral vector expressing the p202 gene (Ad-p202) was generated. We examined the effects of Ad-p202 infection on human breast cancer cells. Furthermore, we tested the efficacy of Ad-p202 treatment on breast and pancreatic cancer xenograft models. RESULTS: We found that Ad-p202 infection induces growth inhibition and sensitizes the otherwise resistant cells to tumor necrosis factor alpha-induced apoptosis. In addition, we demonstrated for the first time that Ad-p202 infection induces apoptosis and that activation of caspases is required for the full apoptotic effect. More importantly, we showed the efficacy of Ad-p202 treatment on breast cancer xenograft models, and this antitumor effect correlated well with enhanced apoptosis in Ad-p202-treated tumors. CONCLUSIONS: We conclude that Ad-p202 is a potent growth-inhibitory, proapoptotic, and tumor-suppressing agent. Ad-p202 may be further developed into an efficient therapeutic agent for human cancer gene therapy.

Adenoviridae↗