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Updated: Jun 10, 2026
Establishing Intracranial Brain Tumor Xenografts With Subsequent Analysis of Tumor Growth and Response to Therapy using Bioluminescence Imaging
Published on: July 13, 2010
[Microarray analysis of tumor xenograft model]
Fumiko Fujita1, Masatoshi Shirane, Kazushige Mori
1Experimental Cancer Chemotherapy Research Laboratories Co., Ltd.
Abstract:
We carried out gene expression profiling of forty human tumor cells for research choice method of the most fitting anticancer drug, using unsupervised hierarchal clustering analysis. This clustering analysis is based on a tumor growth inhibition panel of nine antitumor drugs (MMC, CDDP, ACNU, CPT-11, CPA, FT-207, UFT, 5'-DFUR and ADM) for forty human cancers. These cancers(eleven stomach, seven colon, six breast, three pancreas, five lung, two esophageal carcinomas, one liver, one renal cell carcinoma, one uterus, two ovarian, and one melanoma) have been maintained by serial s. c. passages in nude mice of the same sex of donor patients. Nine antitumor drugs were divided into two groups, a 5-FU-related drug group (5'-DFUR, FT-207 and UFT) and another group. On the other hands, forty cells were clustered into four groups. By using GeneChip (Hu95Av2, Affymetrix), we investigated gene expression profiling of the matched tumor cells and selected specific genes in each group. Interestingly, a pathway analysis revealed that expressions of p53-related genes were up-regulated in the 5-FU-sensitive groups. This result suggested that chemosensitivity was predicted by gene expression profiling of tumor cells. We considered that microarray analysis would be a good tool for further tailor-made medications.
Insights
Gene expression profiling accurately predicts anticancer drug sensitivity in human tumors. This approach aids in selecting the most effective treatments, paving the way for personalized cancer medicine.
Area of Science:
- Oncology
- Genomics
- Pharmacology
Context:
- Personalized medicine aims to tailor cancer treatments to individual patients.
- Accurate prediction of drug response is crucial for effective cancer therapy.
- Gene expression profiling offers a potential method for predicting chemosensitivity.
Purpose:
- To investigate the utility of gene expression profiling for predicting anticancer drug efficacy.
- To cluster human tumor cells based on their response to nine antitumor drugs.
- To identify specific gene expression patterns associated with drug sensitivity.
Summary:
- Gene expression profiling was performed on forty human tumor cell lines using unsupervised hierarchical clustering analysis.
- Tumor cells were clustered into four groups based on their response to nine antitumor drugs, including a 5-fluorouracil (5-FU)-related group.
- Analysis revealed up-regulation of p53-related genes in 5-FU-sensitive tumor groups, suggesting a link between gene expression and drug response.
Impact:
- Gene expression profiling can predict chemosensitivity, enabling the selection of optimal anticancer drugs.
- Microarray analysis serves as a valuable tool for developing tailor-made cancer medications.
- This research supports the advancement of personalized oncology through molecular profiling.
