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Using RNA-sequencing to Detect Novel Splice Variants Related to Drug Resistance in In Vitro Cancer Models
Published on: December 9, 2016
ncDRMarker: a computational method for identifying non-coding RNA signatures of drug resistance based on
Haixiu Yang1, Yanjun Xu1, Desi Shang1
1College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, China.
Background:
Drug resistance is the primary cause of failure in the treatment of cancer. Identifying signatures of chemoresistance will help to overcome this problem. Current drug resistance studies focus on protein-coding genes and ignore non-coding RNAs (ncRNAs), rendering it a challenging task to systematically identify ncRNAs involved in drug resistance.
Methods:
In this study, protein-protein, miRNA-target gene, miRNA-lncRNA interactions were integrated to construct a mRNA-miRNA-lncRNA network. Then, the random walk with restart (RWR) method was extended to the network for identifying ncRNA signatures of drug resistance. The leave-one-out cross validation (LOOCV) and receiver operating characteristic curve (ROC) were used to estimate the performance of ncDRMarker. Wilcoxon rank-sum test was used to validate the identified ncRNAs in NCI-60 cancer cell lines. KEGG pathway enrichment analysis was implemented to characterize the biological function of some identified ncRNAs.
Results:
We performed this method on ten common clinical chemotherapy drugs and analyzed the results in detail. The region beneath the ROC was up to 0.881-0.951, which did not change significantly in the incomplete network, indicating the high performance and robustness of the method. Further, we confirmed the role of the identified ncRNAs in drug resistance, i.e., miR-92a-3p, a candidate chemoresistance ncRNA of tamoxifen and paclitaxel, can significantly classify cancer cell lines into sensitive or resistant to tamoxifen (or paclitaxel). We also dissected the mRNA-miRNA-lncRNA composite network and found that some hub ncRNAs, such as miR-124-3p, were involved in resistance of multiple drugs and engaged in many significant cancer-related pathways. Lastly, we have provided a ncDRMarker platform for users to identify candidate ncRNAs of drug resistance, which is available at http://bio-bigdata.hrbmu.edu.cn/ncDRMarker/index.
Conclusions:
Our findings suggest that ncDRMarker is an effective computational technique for prioritizing candidate ncRNAs of drug resistance. Additionally, the identified ncRNAs could be targeted to overcome drug resistance and help realize individualized treatment.
Insights
This study introduces ncDRMarker, a novel computational method to identify non-coding RNAs (ncRNAs) associated with cancer drug resistance. The identified ncRNAs can help overcome chemoresistance and enable personalized cancer treatment strategies.
Area of Science:
- Genomics
- Bioinformatics
- Cancer Research
Background:
- Drug resistance is a major challenge in cancer therapy, often stemming from protein-coding genes.
- Non-coding RNAs (ncRNAs) are frequently overlooked in drug resistance studies, hindering comprehensive analysis.
- Systematic identification of ncRNAs involved in chemoresistance is crucial for effective cancer treatment.
Purpose of the Study:
- To develop a computational method for identifying non-coding RNA (ncRNA) signatures of drug resistance.
- To integrate diverse interaction data for constructing a comprehensive mRNA-miRNA-lncRNA network.
- To provide a user-friendly platform (ncDRMarker) for discovering candidate ncRNAs in cancer drug resistance.
Main Methods:
- Constructed a mRNA-miRNA-lncRNA interaction network by integrating protein-protein, miRNA-target gene, and miRNA-lncRNA interactions.
- Extended the random walk with restart (RWR) algorithm to identify ncRNA signatures of drug resistance within the constructed network.
- Employed leave-one-out cross-validation (LOOCV) and receiver operating characteristic (ROC) curves to evaluate the ncDRMarker method's performance.
Main Results:
- The ncDRMarker method demonstrated high performance and robustness, with ROC values ranging from 0.881 to 0.951.
- Identified specific ncRNAs, such as miR-92a-3p, as key players in tamoxifen and paclitaxel resistance.
- Dissected the network to reveal hub ncRNAs like miR-124-3p involved in multi-drug resistance and significant cancer pathways.
Conclusions:
- ncDRMarker is an effective computational tool for prioritizing ncRNAs implicated in drug resistance.
- The identified ncRNAs offer potential therapeutic targets to overcome chemoresistance.
- Findings support the development of targeted therapies for individualized cancer treatment.
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