Identification of a competing endogenous RNA axis “SVIL‐AS1/miR‐103a/ICE1” associated with chemoresistance in lung adenocarcinoma by comprehensive bioinformatics analysis

Abstract Background Chemotherapy is an important treatment for lung cancer. The molecular mechanism of lung adenocarcinoma (LUAD) chemoresistance is not completely understood. Methods Weighted gene co‐expression network analysis (WGCNA) was applied to screen the modules related to chemosensitivity u...

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Main Authors: Lili Guo, Lina Ding, Junfang Tang
Format: Article
Language:English
Published: Wiley 2021-09-01
Series:Cancer Medicine
Subjects:
Online Access:https://doi.org/10.1002/cam4.4132
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spelling doaj-593ac3a913684367bb3b12456210783d2021-09-06T09:17:13ZengWileyCancer Medicine2045-76342021-09-0110176022603410.1002/cam4.4132Identification of a competing endogenous RNA axis “SVIL‐AS1/miR‐103a/ICE1” associated with chemoresistance in lung adenocarcinoma by comprehensive bioinformatics analysisLili Guo0Lina Ding1Junfang Tang2Department of Medical Oncology Beijing Tuberculosis and Thoracic Tumor Research Institute Beijing Chest Hospital Capital Medical University Beijing ChinaKey Laboratory of Henan Province for Drug Quality and Evaluation School of Pharmaceutical Sciences Ministry of Education of ChinaZhengzhou University Zhengzhou P.R. ChinaDepartment of Medical Oncology Beijing Tuberculosis and Thoracic Tumor Research Institute Beijing Chest Hospital Capital Medical University Beijing ChinaAbstract Background Chemotherapy is an important treatment for lung cancer. The molecular mechanism of lung adenocarcinoma (LUAD) chemoresistance is not completely understood. Methods Weighted gene co‐expression network analysis (WGCNA) was applied to screen the modules related to chemosensitivity using the data of LUAD patients receiving chemotherapy in The Cancer Genome Atlas database. GDCRNATools package was used to establish competing endogenous RNA (ceRNA) network based on the key chemotherapy‐related module. Kaplan–Meier and risk models were used to analyze the influence of genes in the ceRNA network on the prognosis of LUAD patients receiving chemotherapy. Cell counting kit‐8, reverse transcription‐quantitative PCR, and dual‐luciferase reporter assay were used to detect the effects of abnormal expression of genes in the ceRNA network on the proliferation and IC50 of cisplatin (DDP)‐resistant LUAD cells, and the targeting relationship of genes in the ceRNA network. The signaling pathways and functions of ICE1 in LUAD were analyzed by LinkOmics and CancerSEA databases, and validated by Western blot. Results Midnightblue module was the only WGCNA module positively correlated with chemosensitivity, in which the function of genes was related to cancer progression. SVIL‐AS1/miR‐103a/ICE1 was constructed based on midnightblue module. High expression of SVIl‐AS1 and ICE1 corresponded to a favorable prognosis. High expression of miR‐103a corresponded to a dismal prognosis. SVIl‐AS1 was downregulated in DDP‐resistant LUAD cells. SVIL‐AS1 overexpression retarded the proliferation and DDP resistance of DDP‐resistant LUAD cell. miR‐103a was sponged by SVIL‐AS1 and directly targeted ICE1. miR‐103a overexpression and ICE1 knockdown overturned the suppressive effect of SVIL‐AS1 overexpression on cell proliferation and DDP resistance. Further bioinformatics analysis and experimental verification showed that SVIL‐AS1/miR‐103a‐3p/ICE1 axis can enhance DNA damage caused by chemotherapeutic agents. Conclusions SVIL‐AS1 inhibited chemoresistance by acting as a sponge for miR‐103a and upregulating ICE1 expression, which may be a potential therapeutic target for chemotherapy in LUAD.https://doi.org/10.1002/cam4.4132chemoresistancecompeting endogenous RNAlung adenocarcinomaprognosisweighted gene co‐expression network analysis
collection DOAJ
language English
format Article
sources DOAJ
author Lili Guo
Lina Ding
Junfang Tang
spellingShingle Lili Guo
Lina Ding
Junfang Tang
Identification of a competing endogenous RNA axis “SVIL‐AS1/miR‐103a/ICE1” associated with chemoresistance in lung adenocarcinoma by comprehensive bioinformatics analysis
Cancer Medicine
chemoresistance
competing endogenous RNA
lung adenocarcinoma
prognosis
weighted gene co‐expression network analysis
author_facet Lili Guo
Lina Ding
Junfang Tang
author_sort Lili Guo
title Identification of a competing endogenous RNA axis “SVIL‐AS1/miR‐103a/ICE1” associated with chemoresistance in lung adenocarcinoma by comprehensive bioinformatics analysis
title_short Identification of a competing endogenous RNA axis “SVIL‐AS1/miR‐103a/ICE1” associated with chemoresistance in lung adenocarcinoma by comprehensive bioinformatics analysis
title_full Identification of a competing endogenous RNA axis “SVIL‐AS1/miR‐103a/ICE1” associated with chemoresistance in lung adenocarcinoma by comprehensive bioinformatics analysis
title_fullStr Identification of a competing endogenous RNA axis “SVIL‐AS1/miR‐103a/ICE1” associated with chemoresistance in lung adenocarcinoma by comprehensive bioinformatics analysis
title_full_unstemmed Identification of a competing endogenous RNA axis “SVIL‐AS1/miR‐103a/ICE1” associated with chemoresistance in lung adenocarcinoma by comprehensive bioinformatics analysis
title_sort identification of a competing endogenous rna axis “svil‐as1/mir‐103a/ice1” associated with chemoresistance in lung adenocarcinoma by comprehensive bioinformatics analysis
publisher Wiley
series Cancer Medicine
issn 2045-7634
publishDate 2021-09-01
description Abstract Background Chemotherapy is an important treatment for lung cancer. The molecular mechanism of lung adenocarcinoma (LUAD) chemoresistance is not completely understood. Methods Weighted gene co‐expression network analysis (WGCNA) was applied to screen the modules related to chemosensitivity using the data of LUAD patients receiving chemotherapy in The Cancer Genome Atlas database. GDCRNATools package was used to establish competing endogenous RNA (ceRNA) network based on the key chemotherapy‐related module. Kaplan–Meier and risk models were used to analyze the influence of genes in the ceRNA network on the prognosis of LUAD patients receiving chemotherapy. Cell counting kit‐8, reverse transcription‐quantitative PCR, and dual‐luciferase reporter assay were used to detect the effects of abnormal expression of genes in the ceRNA network on the proliferation and IC50 of cisplatin (DDP)‐resistant LUAD cells, and the targeting relationship of genes in the ceRNA network. The signaling pathways and functions of ICE1 in LUAD were analyzed by LinkOmics and CancerSEA databases, and validated by Western blot. Results Midnightblue module was the only WGCNA module positively correlated with chemosensitivity, in which the function of genes was related to cancer progression. SVIL‐AS1/miR‐103a/ICE1 was constructed based on midnightblue module. High expression of SVIl‐AS1 and ICE1 corresponded to a favorable prognosis. High expression of miR‐103a corresponded to a dismal prognosis. SVIl‐AS1 was downregulated in DDP‐resistant LUAD cells. SVIL‐AS1 overexpression retarded the proliferation and DDP resistance of DDP‐resistant LUAD cell. miR‐103a was sponged by SVIL‐AS1 and directly targeted ICE1. miR‐103a overexpression and ICE1 knockdown overturned the suppressive effect of SVIL‐AS1 overexpression on cell proliferation and DDP resistance. Further bioinformatics analysis and experimental verification showed that SVIL‐AS1/miR‐103a‐3p/ICE1 axis can enhance DNA damage caused by chemotherapeutic agents. Conclusions SVIL‐AS1 inhibited chemoresistance by acting as a sponge for miR‐103a and upregulating ICE1 expression, which may be a potential therapeutic target for chemotherapy in LUAD.
topic chemoresistance
competing endogenous RNA
lung adenocarcinoma
prognosis
weighted gene co‐expression network analysis
url https://doi.org/10.1002/cam4.4132
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