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A systematic study on drug-response associated genes using baseline gene expressions of the Cancer Cell Line
Xiaoming Liu1, Jiasheng Yang2, Yi Zhang3
1Department of Mathematics, Shanghai Normal University, Shanghai 200234, P. R. China.
Abstract:
We have studied drug-response associated (DRA) gene expressions by applying a systems biology framework to the Cancer Cell Line Encyclopedia data. More than 4,000 genes are inferred to be DRA for at least one drug, while the number of DRA genes for each drug varies dramatically from almost 0 to 1,226. Functional enrichment analysis shows that the DRA genes are significantly enriched in genes associated with cell cycle and plasma membrane. Moreover, there might be two patterns of DRA genes between genders. There are significantly shared DRA genes between male and female for most drugs, while very little DRA genes tend to be shared between the two genders for a few drugs targeting sex-specific cancers (e.g., PD-0332991 for breast cancer and ovarian cancer). Our analyses also show substantial difference for DRA genes between young and old samples, suggesting the necessity of considering the age effects for personalized medicine in cancers. Lastly, differential module and key driver analyses confirm cell cycle related modules as top differential ones for drug sensitivity. The analyses also reveal the role of TSPO, TP53, and many other immune or cell cycle related genes as important key drivers for DRA network modules. These key drivers provide new drug targets to improve the sensitivity of cancer therapy.
Insights
This study identifies over 4,000 drug-response associated genes, highlighting cell cycle and plasma membrane pathways. Findings suggest personalized cancer medicine considering gender and age for improved drug sensitivity.
Area of Science:
- Genomics
- Systems Biology
- Cancer Research
Background:
- Drug response varies significantly across cancer cell lines.
- Understanding gene expression patterns linked to drug response is crucial for personalized medicine.
Purpose of the Study:
- To identify drug-response associated (DRA) genes using a systems biology approach.
- To explore patterns of DRA genes related to gender, age, and cancer type.
- To uncover key drivers and pathways influencing drug sensitivity.
Main Methods:
- Applied a systems biology framework to Cancer Cell Line Encyclopedia data.
- Performed functional enrichment analysis on DRA genes.
- Conducted differential module and key driver analyses.
Main Results:
- Over 4,000 genes were identified as DRA for at least one drug.
- DRA genes were significantly enriched in cell cycle and plasma membrane pathways.
- Distinct DRA gene patterns were observed between genders and age groups, particularly for sex-specific cancers.
- Cell cycle modules and genes like TSPO and TP53 were identified as key drivers of drug sensitivity.
Conclusions:
- Drug response is influenced by a complex network of genes, with cell cycle pathways being particularly important.
- Considering patient gender and age is essential for developing effective personalized cancer therapies.
- Identified key drivers offer potential new targets for enhancing cancer treatment efficacy.
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