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Updated: Dec 31, 2025
Implementation of In Vitro Drug Resistance Assays: Maximizing the Potential for Uncovering Clinically Relevant Resistance Mechanisms
Published on: December 9, 2015
Identification of drug resistance associated ncRNAs based on comprehensive heterogeneous network
Yu-E Huang1, Shunheng Zhou1, Haizhou Liu1
1College of Automation Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing 211106, China.
Aims:
Chemotherapy and molecularly targeted therapy are main strategies for treatment of cancers. However, long-term treatment makes cancer cells acquire resistance to anti-cancer drugs, which severely limits the effects of cancer treatment. NcRNAs, especially miRNAs and lncRNAs, have been reported to play key roles in drug resistance and could restore drug responses in resistant cells.
Main Methods:
We presented a network-based framework to systematically identify drug resistance associated miRNAs and lncRNAs. First, we constructed a comprehensive heterogeneous miRNA-lncRNA regulatory network through integrating curated miRNA regulations to lncRNA, and significantly co-expressed miRNA-miRNA, lncRNA-lncRNA and miRNA-lncRNA interactions for each cancer type. Second, random walk with restart (RWR) was utilized to identify novel drug resistance associated ncRNAs.
Key Findings:
We predicted 470 associations of 34 miRNAs and 79 lncRNAs for 27 drugs in 10 cancer types. In addition, leave-one-out cross validation (LOOCV) demonstrated the effectiveness of the proposed approach. Next, we also demonstrated that the integrated heterogeneous cancer-specific network achieved better performance than the general curated miRNA-lncRNA regulatory network. What's more, we found that the drug resistance associated ncRNAs validated by high-throughput technology was also a reliable source for prediction.
Significance:
We proposed a new framework to identify novel and reliable drug resistance associated ncRNAs, which provides new perspectives for drug resistance mechanism and new guidance for clinical cancer treatment.
Insights
This study introduces a network framework to identify non-coding RNAs (ncRNAs), like microRNAs (miRNAs) and long non-coding RNAs (lncRNAs), linked to cancer drug resistance. The findings offer new insights into overcoming treatment resistance in cancer.
Area of Science:
- Oncology
- Genomics
- Bioinformatics
Background:
- Cancer therapies like chemotherapy and targeted therapy face limitations due to acquired drug resistance.
- Non-coding RNAs (ncRNAs), including microRNAs (miRNAs) and long non-coding RNAs (lncRNAs), are implicated in the development of cancer drug resistance.
- Identifying specific ncRNAs involved in drug resistance is crucial for developing effective treatment strategies.
Purpose of the Study:
- To develop and validate a network-based framework for systematically identifying novel drug resistance-associated miRNAs and lncRNAs.
- To explore the potential of ncRNAs in restoring drug responses in resistant cancer cells.
Main Methods:
- Construction of a comprehensive heterogeneous miRNA-lncRNA regulatory network integrating curated regulations and co-expression interactions for each cancer type.
- Application of Random Walk with Restart (RWR) algorithm to identify potential drug resistance-associated ncRNAs within the constructed network.
- Validation of the framework's effectiveness using leave-one-out cross-validation (LOOCV).
Main Results:
- Prediction of 470 associations between 34 miRNAs and 79 lncRNAs across 27 drugs and 10 cancer types.
- Demonstration that the integrated heterogeneous cancer-specific network outperforms a general curated network.
- Confirmation that ncRNAs validated by high-throughput technology serve as reliable predictors.
Conclusions:
- A novel framework for identifying reliable drug resistance-associated ncRNAs has been proposed.
- The findings provide new perspectives on the mechanisms of cancer drug resistance.
- This research offers potential guidance for improving clinical cancer treatment strategies by targeting ncRNAs.
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