Literature DB >> 25933723

Application of clinical bioinformatics in lung cancer-specific biomarkers.

Duojiao Wu1, Xiangdong Wang.   

Abstract

The fact that lung cancer is a heterogeneous disease suggests that there is a high likelihood that effective lung cancer biomarkers will need to address patient-specific molecular defects, clinical characters, and aspects of the tumor microenvironment. In this transition, clinical bioinformatics tools and resources are the most appropriate means to improve the analysis, as major biological databases are now containing clinical data alongside genomics, proteomics, and other biological data. Clinical bioinformatics comprises a series of concepts and approaches that have been used successfully both to delineate novel biological mechanisms and to drive translational advances in individualized healthcare. In this article, we outline several of emerging clinical bioinformatics-based strategies as they apply specifically to lung cancer.

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Year:  2015        PMID: 25933723     DOI: 10.1007/s10555-015-9564-2

Source DB:  PubMed          Journal:  Cancer Metastasis Rev        ISSN: 0167-7659            Impact factor:   9.264


  11 in total

1.  In silico bioinformatics analysis for identification of differentially expressed genes and therapeutic drug molecules in Glucocorticoid-resistant Multiple myeloma.

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Review 2.  Epithelial-Mesenchymal Transition-Inducing Factors Involved in the Progression of Lung Cancers.

Authors:  Min-Woo Nam; Cho-Won Kim; Kyung-Chul Choi
Journal:  Biomol Ther (Seoul)       Date:  2022-05-01       Impact factor: 4.634

3.  An individualised signature for predicting response with concordant survival benefit for lung adenocarcinoma patients receiving platinum-based chemotherapy.

Authors:  Lishuang Qi; Yang Li; Yuan Qin; Gengen Shi; Tianhao Li; Jiasheng Wang; Libin Chen; Yunyan Gu; Wenyuan Zhao; Zheng Guo
Journal:  Br J Cancer       Date:  2016-11-17       Impact factor: 7.640

4.  Estimation of Hub Genes and Infiltrating Immune Cells in Non-Smoking Females with Lung Adenocarcinoma by Integrated Bioinformatic Analysis.

Authors:  Jie Li; Ben Wang; Xin Li; Yuxi Zhu
Journal:  Med Sci Monit       Date:  2020-07-16

5.  Identification of prognosis-related alternative splicing events in kidney renal clear cell carcinoma.

Authors:  Yongdi Zuo; Liang Zhang; Weihao Tang; Wanxin Tang
Journal:  J Cell Mol Med       Date:  2019-09-05       Impact factor: 5.310

6.  A Novel mRNA-miRNA Regulatory Sub-Network Associated With Prognosis of Metastatic Clear Cell Renal Cell Carcinoma.

Authors:  Tianyu Yang; Xiaofen Miao; Zhanxiang Bai; Jian Tu; Shanshan Shen; Hui Niu; Wei Xia; Juan Wang; Yongsheng Zhang
Journal:  Front Oncol       Date:  2021-01-19       Impact factor: 6.244

7.  Identification of Novel Biomarkers Related to Lung Squamous Cell Carcinoma Using Integrated Bioinformatics Analysis.

Authors:  Haiyan Wang; Lizhi Huang; Li Chen; Jing Ji; Yuanyuan Zheng; Zhen Wang
Journal:  Comput Math Methods Med       Date:  2021-10-08       Impact factor: 2.238

Review 8.  Potentials of single-cell biology in identification and validation of disease biomarkers.

Authors:  Furong Niu; Diane C Wang; Jiapei Lu; Wei Wu; Xiangdong Wang
Journal:  J Cell Mol Med       Date:  2016-04-26       Impact factor: 5.310

Review 9.  Can glypican-3 be a disease-specific biomarker?

Authors:  Chaolei Chen; Xiaomin Huang; Zhaojian Ying; Dengmin Wu; Yani Yu; Xiangdong Wang; Chengshui Chen
Journal:  Clin Transl Med       Date:  2017-05-16

10.  Downregulation of m6A Reader YTHDC2 Promotes the Proliferation and Migration of Malignant Lung Cells via CYLD/NF-κB Pathway.

Authors:  Jin Wang; Lirong Tan; Beibei Jia; Xiaofan Yu; Ruixin Yao; Nan OUYang; Xueting Yu; Xiyuan Cao; Jian Tong; Tao Chen; Rui Chen; Jianxiang Li
Journal:  Int J Biol Sci       Date:  2021-06-22       Impact factor: 6.580

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