Publications by authors named "Siyao Dong"

5 Publications

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Strongly preserved modules between cancer tissue and cell line contribute to drug resistance analysis across multiple cancer types.

Genomics 2021 Feb 26;113(3):1026-1036. Epub 2021 Feb 26.

College of Bioinformatics Science and Technology, Harbin Medical University, Harbin 150081, China. Electronic address:

The existence and emergence of drug resistance in tumor cells is the main burden of cancer treatment. Most cancer drug resistance analyses are based entirely on cell line data and ignore the discordance between human tumors and cell lines, leading to biased preclinical model transformation. Based on cancer tissue data in TCGA and cancer cell line data in CCLE, this study identified and excluded non-preserved module (NP module) between cancer tissue and cell lines. We used strongly preserved module (SP module) for clinically relevant drug resistance analysis and identified 2068 "cancer-drug-module" pairs of 7 cancer types and 212 drugs based on data in GDSC. Furthermore, we identified potentially ineffective combination therapy (PICT) from multiple perspectives. Finally, we found 1608 sets of predictors that can predict drug response. These results provide insights and clues for the clinical selection of effective chemotherapy drugs to overcome cancer resistance in a new perspective.
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http://dx.doi.org/10.1016/j.ygeno.2021.02.015DOI Listing
February 2021

Identification of Primary and Metastatic Lung Cancer-Related lncRNAs and Potential Targeted Drugs Based on ceRNA Network.

Front Oncol 2020 3;10:628930. Epub 2021 Feb 3.

College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, China.

Lung cancer metastasis is the leading cause of poor prognosis and death for patients. Long noncoding RNAs (lncRNAs) have been validated the close correlation with lung cancer metastasis, but few comprehensive analyses have reported the specific association between lncRNA and cancer metastasis, especially both competing endogenous RNA (ceRNA) regulatory relationships and functional regulatory networks. Here, we constructed primary and metastatic ceRNA networks, identified 12 and 3 candidate lncRNAs for lung adenocarcinoma (LUAD) and lung squamous cell carcinoma (LUSC) respectively and excavated some drugs that might have potential therapeutic effects on lung cancer progression. In summary, this study systematically analyzed the competitive relationships and regulatory mechanism of the repeatedly dysregulated lncRNAs in lung cancer carcinogenesis and metastasis, and provided a new idea for screening potential therapeutic drugs for lung cancer.
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http://dx.doi.org/10.3389/fonc.2020.628930DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7886985PMC
February 2021

Identification of cancer prognosis-associated lncRNAs based on the miRNA-TF co-regulatory motifs and dosage sensitivity.

Mol Omics 2019 10;15(5):361-373

College of Bioinformatics Science and Technology, Harbin Medical University, Harbin 150081, China.

Long non-coding RNAs (lncRNAs) have been shown to be vital players in a majority of physiological and pathological processes, including tumorigenesis and tumor progression. The aim of this study was to identify lncRNAs that can serve as biomarkers for cancer prognosis. Based on dosage sensitivity, we utilized the biological features of known cancer-related lncRNAs, and identified microRNA and transcription factor (miRNA-TF) co-regulatory motifs in an effort to establish a holistic analysis framework and predict new cancer prognosis-associated lncRNAs. We found that lncRNAs with low dosage sensitivity regulated by more than 3 types of co-regulatory motifs were more likely to be associated with cancer. By the use of the integrative analysis of 3035 tumor samples across 9 types of cancer, a total of 33 cancer prognosis-associated lncRNAs were identified. Additionally, on the basis of the miRNA-TF co-regulatory network, we also predicted potential small molecule drugs such as Glucocorticoid and Ginsenoside Rh2 for treating KIRC by targeting miRNA. This study explains the causes of abnormalities in the genome from a new perspective, and provides new clues for cancer diagnosis and prognosis, and research for anti-cancer drugs.
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http://dx.doi.org/10.1039/c9mo00089eDOI Listing
October 2019

DNA co-methylation analysis of lincRNAs across nine cancer types reveals novel potential epigenetic biomarkers in cancer.

Epigenomics 2019 08 26;11(10):1177-1190. Epub 2019 Jul 26.

College of Bioinformatics Science & Technology, Harbin Medical University, Harbin 150081, PR China.

The potential functions and prognostic value of lincRNAs with co-methylation events are explored in 9 cancer types. Here, we evaluated the co-methylation events in promoter and gene-body regions between two lincRNAs across 9 cancer types by constructing a systematic biological framework. The co-methylation events in both promoter and gene-body regions tended to be highly cancer specific. Patient samples could be separated by tumor and normal types according to the eigengenes of universal co-methylation clusters. Functional enrichment results revealed the lincRNAs that brought promoter and gene-body co-methylation events that affected cancer progress through participating in different pathways and could serve as potential prognostic biomarkers. The study provides new insight into the epigenetic regulation in cancer and leads to a potential new direction for epigenetic biomarker discovery.
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http://dx.doi.org/10.2217/epi-2018-0138DOI Listing
August 2019

Systematic identification of dysregulated lncRNAs associated with platinum-based chemotherapy response across 11 cancer types.

Genomics 2020 03 11;112(2):1214-1222. Epub 2019 Jul 11.

College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, China. Electronic address:

Aberrant expression of long non-coding RNAs (lncRNAs) leads to the development of chemoresistance by regulating a series of biological processes, which is one of the major obstacles in the cancer treatment. This study aimed to identify some key lncRNAs that are associated with platinum-based chemoresistance in multiple cancers. Regulating the expression levels of these lncRNAs can enhance the sensitivity of patients to chemotherapy drugs and improve the therapeutic effect of cancer. By systematically analyzing 648 samples regarding platinum drug response from the Cancer Genome Atlas (TCGA), we have identified 32 dysregulated lncRNAs across 11 cancer types that could affect platinum-based chemotherapy response, of which 78.125% (25/32) were significantly down-regulated in drug-resistant samples. Drug response prediction model that had been constructed based on the expression pattern of these dysregulated lncRNAs could accurately predict the chemotherapy response of tumor patients, and the area under the curve (AUC) was between 0.8034 and 0.9984. In particular, all of these dysregulated lncRNAs that we identified were cancer-specific. They were significantly associated with the survival of tumor patients and could serve as cancer-specific biomarkers for prognosis. In conclusion, this study will contribute to improving the drug resistance of tumor patients during chemotherapy, and it is of real significance for selecting effective chemotherapy drugs and achieving precision medicine.
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http://dx.doi.org/10.1016/j.ygeno.2019.07.007DOI Listing
March 2020