TY - JOUR
T1 - Novel Potential Therapeutic Targets of PTPN Families for Lung Cancer
AU - Wang, Chin Chou
AU - Shen, Wan Jou
AU - Anuraga, Gangga
AU - Khoa Ta, Hoang Dang
AU - Xuan, Do Thi Minh
AU - Chen, Sih Tong
AU - Shen, Chiu Fan
AU - Jiang, Jia Zhen
AU - Sun, Zhengda
AU - Wang, Chih Yang
AU - Wang, Wei Jan
N1 - Funding Information:
This research was supported by grants from the Ministry of Science and Technology (MOST) of Taiwan (MOST-110-2320-B-039-068 to W.-J.W. and 109-2320-B-038-009-MY2 to C.-Y.W.), National Science and Technology Council of Taiwan (NSTC-111-2314-B-182A-151 to C.-C.W.), Kaohsiung Chang Gung Memorial Hospital (CMRPG8E1661-3, CMRPG8F1441, CMRPG8F1351, CMRPG8H1201, CORPG8F1491-3, CMRPG8K0481-2, and CMRPG8L0521 to C-C.W.), China Medical University (CMU110-MF-47 to W.-J.W.), Taipei Medical University (TMU-108-AE1-B16 to C.-Y.W.), and the TMU Research Center of Cancer Translational Medicine from The Featured Areas Research Center Program within the framework of the Higher Education Sprout Project by the Ministry of Education (MOE) in Taiwan (DP2-111-21121-01-N-10 and DP2-111-21121-01-C-01-01).
Publisher Copyright:
© 2022 by the authors.
PY - 2022/12
Y1 - 2022/12
N2 - Despite the treatment of lung adenocarcinoma (LUAD) having partially improved in recent years, LUAD patients still have poor prognosis rates. Therefore, it is especially important to explore effective biomarkers and exploit novel therapeutic developments. High-throughput technologies are widely used as systematic approaches to explore differences in expressions of thousands of genes for both biological and genomic systems. Recently, using big data analyses in biomedicine research by integrating several high-throughput databases and tools, including The Cancer Genome Atlas (TCGA), cBioportal, Oncomine, and Kaplan–Meier plotter, is an important strategy to identify novel biomarkers for cancer therapy. Here, we used two different comprehensive bioinformatics analysis and revealed protein tyrosine phosphatase non-receptor type (PTPN) family genes, especially PTPN1 and PTPN22, were downregulated in lung cancer tissue in comparison with normal samples. The survival curves indicated that LUAD patients with high transcription levels of PTPN5 were significantly associated with a good prognosis. Meanwhile, Gene Ontology (GO) and MetaCore analyses indicated that co-expression of the PTPN1, PTPN5, and PTPN21 genes was significantly enriched in cancer development-related pathways, including GTPase activity, regulation of small GTPase-mediated signal transduction, response to mechanical stimuli, vasculogenesis, organ morphogenesis, regulation of stress fiber assembly, mitogen-activated protein kinase (MAPK) cascade, cell migration, and angiogenesis. Collectively, this study revealed that PTPN family members are both significant prognostic biomarkers for lung cancer progression and promising clinical therapeutic targets, which provide new targets for treating LUAD patients.
AB - Despite the treatment of lung adenocarcinoma (LUAD) having partially improved in recent years, LUAD patients still have poor prognosis rates. Therefore, it is especially important to explore effective biomarkers and exploit novel therapeutic developments. High-throughput technologies are widely used as systematic approaches to explore differences in expressions of thousands of genes for both biological and genomic systems. Recently, using big data analyses in biomedicine research by integrating several high-throughput databases and tools, including The Cancer Genome Atlas (TCGA), cBioportal, Oncomine, and Kaplan–Meier plotter, is an important strategy to identify novel biomarkers for cancer therapy. Here, we used two different comprehensive bioinformatics analysis and revealed protein tyrosine phosphatase non-receptor type (PTPN) family genes, especially PTPN1 and PTPN22, were downregulated in lung cancer tissue in comparison with normal samples. The survival curves indicated that LUAD patients with high transcription levels of PTPN5 were significantly associated with a good prognosis. Meanwhile, Gene Ontology (GO) and MetaCore analyses indicated that co-expression of the PTPN1, PTPN5, and PTPN21 genes was significantly enriched in cancer development-related pathways, including GTPase activity, regulation of small GTPase-mediated signal transduction, response to mechanical stimuli, vasculogenesis, organ morphogenesis, regulation of stress fiber assembly, mitogen-activated protein kinase (MAPK) cascade, cell migration, and angiogenesis. Collectively, this study revealed that PTPN family members are both significant prognostic biomarkers for lung cancer progression and promising clinical therapeutic targets, which provide new targets for treating LUAD patients.
KW - big data analysis
KW - bioinformatics
KW - lung cancer
KW - prognosis
KW - PTPN family genes
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U2 - 10.3390/jpm12121947
DO - 10.3390/jpm12121947
M3 - Article
AN - SCOPUS:85144665316
SN - 2075-4426
VL - 12
JO - Journal of Personalized Medicine
JF - Journal of Personalized Medicine
IS - 12
M1 - 1947
ER -