Cargando…

Establishment of a Lung Cancer Discriminative Model Based on an Optimized Support Vector Machine Algorithm and Study of Key Targets of Wogonin in Lung Cancer

An optimized support vector machine model was used to construct a lung cancer diagnosis model based on serological indicators, and a molecular regulation model of Wogonin, a component of Scutellaria baicalensis, was established. Serological indexes of patients were collected, the grid search method...

Descripción completa

Detalles Bibliográficos
Autores principales: Wang, Lin, Zhang, Jianhua, Shan, Guoyong, Liang, Junting, Jin, Wenwen, Li, Yingyue, Su, Fangchu, Ba, Yanhua, Tian, Xifeng, Sun, Xiaoyan, Zhang, Dayong, Zhang, Weihua, Chen, Chuan liang
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8493220/
https://www.ncbi.nlm.nih.gov/pubmed/34630106
http://dx.doi.org/10.3389/fphar.2021.728937
_version_ 1784579077101846528
author Wang, Lin
Zhang, Jianhua
Shan, Guoyong
Liang, Junting
Jin, Wenwen
Li, Yingyue
Su, Fangchu
Ba, Yanhua
Tian, Xifeng
Sun, Xiaoyan
Zhang, Dayong
Zhang, Weihua
Chen, Chuan liang
author_facet Wang, Lin
Zhang, Jianhua
Shan, Guoyong
Liang, Junting
Jin, Wenwen
Li, Yingyue
Su, Fangchu
Ba, Yanhua
Tian, Xifeng
Sun, Xiaoyan
Zhang, Dayong
Zhang, Weihua
Chen, Chuan liang
author_sort Wang, Lin
collection PubMed
description An optimized support vector machine model was used to construct a lung cancer diagnosis model based on serological indicators, and a molecular regulation model of Wogonin, a component of Scutellaria baicalensis, was established. Serological indexes of patients were collected, the grid search method was used to identify the optimal penalty coefficient C and parameter g of the support vector machine model, and the benign and malignant auxiliary diagnosis model of isolated pulmonary nodules based on serological indicators was established. The regulatory network and key targets of Wogonin in lung cancer were analyzed by network pharmacology, and key targets were detected by western blot. The relationship between serological susceptibility genes and key targets of Wogonin was established, and the signaling pathway of Wogonin regulating lung cancer was constructed. After support vector machine parameter optimization (C = 90.597, g = 32), the accuracy of the model was 90.8333%, with nine false positives and two false negative cases. Ontology functional analysis of 67 common genes between Wogonin targets and lung cancer–related genes showed that the targets were associated with biological processes involved in peptidye-serine modification and regulation of protein kinase B signaling; cell components in the membrane raft and chromosomal region; and molecular function in protein serine/threonine kinase activity and heme binding. Kyoto Encyclopedia of Genes and Genomes analysis showed that the regulation pathways involved the PI3K-Akt signaling pathway, ERBB signaling pathway, and EGFR tyrosine kinase inhibitor resistance. In vitro analyses using lung cancer cells showed that Wogonin led to significantly increased levels of cleaved caspase-3 and Bad and significantly decreased Bcl-2 expression in a concentration-dependent manner. ErbB4 expression also significantly decreased in lung cancer cells after treatment with Wogonin. A regulatory network of Wogonin regulating lung cancer cell apoptosis was constructed, including the participation of serological susceptibility genes. There is a certain regulatory effect between the serological indexes that can be used in the diagnosis of lung cancer and the key targets of Chinese herbal medicine treatment of lung cancer, which provides a new idea for the diagnosis, treatment and prognosis of clinical lung cancer.
format Online
Article
Text
id pubmed-8493220
institution National Center for Biotechnology Information
language English
publishDate 2021
publisher Frontiers Media S.A.
record_format MEDLINE/PubMed
spelling pubmed-84932202021-10-07 Establishment of a Lung Cancer Discriminative Model Based on an Optimized Support Vector Machine Algorithm and Study of Key Targets of Wogonin in Lung Cancer Wang, Lin Zhang, Jianhua Shan, Guoyong Liang, Junting Jin, Wenwen Li, Yingyue Su, Fangchu Ba, Yanhua Tian, Xifeng Sun, Xiaoyan Zhang, Dayong Zhang, Weihua Chen, Chuan liang Front Pharmacol Pharmacology An optimized support vector machine model was used to construct a lung cancer diagnosis model based on serological indicators, and a molecular regulation model of Wogonin, a component of Scutellaria baicalensis, was established. Serological indexes of patients were collected, the grid search method was used to identify the optimal penalty coefficient C and parameter g of the support vector machine model, and the benign and malignant auxiliary diagnosis model of isolated pulmonary nodules based on serological indicators was established. The regulatory network and key targets of Wogonin in lung cancer were analyzed by network pharmacology, and key targets were detected by western blot. The relationship between serological susceptibility genes and key targets of Wogonin was established, and the signaling pathway of Wogonin regulating lung cancer was constructed. After support vector machine parameter optimization (C = 90.597, g = 32), the accuracy of the model was 90.8333%, with nine false positives and two false negative cases. Ontology functional analysis of 67 common genes between Wogonin targets and lung cancer–related genes showed that the targets were associated with biological processes involved in peptidye-serine modification and regulation of protein kinase B signaling; cell components in the membrane raft and chromosomal region; and molecular function in protein serine/threonine kinase activity and heme binding. Kyoto Encyclopedia of Genes and Genomes analysis showed that the regulation pathways involved the PI3K-Akt signaling pathway, ERBB signaling pathway, and EGFR tyrosine kinase inhibitor resistance. In vitro analyses using lung cancer cells showed that Wogonin led to significantly increased levels of cleaved caspase-3 and Bad and significantly decreased Bcl-2 expression in a concentration-dependent manner. ErbB4 expression also significantly decreased in lung cancer cells after treatment with Wogonin. A regulatory network of Wogonin regulating lung cancer cell apoptosis was constructed, including the participation of serological susceptibility genes. There is a certain regulatory effect between the serological indexes that can be used in the diagnosis of lung cancer and the key targets of Chinese herbal medicine treatment of lung cancer, which provides a new idea for the diagnosis, treatment and prognosis of clinical lung cancer. Frontiers Media S.A. 2021-09-22 /pmc/articles/PMC8493220/ /pubmed/34630106 http://dx.doi.org/10.3389/fphar.2021.728937 Text en Copyright © 2021 Wang, Zhang, Shan, Liang, Jin, Li, Su, Ba, Tian, Sun, Zhang, Zhang and Chen. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Pharmacology
Wang, Lin
Zhang, Jianhua
Shan, Guoyong
Liang, Junting
Jin, Wenwen
Li, Yingyue
Su, Fangchu
Ba, Yanhua
Tian, Xifeng
Sun, Xiaoyan
Zhang, Dayong
Zhang, Weihua
Chen, Chuan liang
Establishment of a Lung Cancer Discriminative Model Based on an Optimized Support Vector Machine Algorithm and Study of Key Targets of Wogonin in Lung Cancer
title Establishment of a Lung Cancer Discriminative Model Based on an Optimized Support Vector Machine Algorithm and Study of Key Targets of Wogonin in Lung Cancer
title_full Establishment of a Lung Cancer Discriminative Model Based on an Optimized Support Vector Machine Algorithm and Study of Key Targets of Wogonin in Lung Cancer
title_fullStr Establishment of a Lung Cancer Discriminative Model Based on an Optimized Support Vector Machine Algorithm and Study of Key Targets of Wogonin in Lung Cancer
title_full_unstemmed Establishment of a Lung Cancer Discriminative Model Based on an Optimized Support Vector Machine Algorithm and Study of Key Targets of Wogonin in Lung Cancer
title_short Establishment of a Lung Cancer Discriminative Model Based on an Optimized Support Vector Machine Algorithm and Study of Key Targets of Wogonin in Lung Cancer
title_sort establishment of a lung cancer discriminative model based on an optimized support vector machine algorithm and study of key targets of wogonin in lung cancer
topic Pharmacology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8493220/
https://www.ncbi.nlm.nih.gov/pubmed/34630106
http://dx.doi.org/10.3389/fphar.2021.728937
work_keys_str_mv AT wanglin establishmentofalungcancerdiscriminativemodelbasedonanoptimizedsupportvectormachinealgorithmandstudyofkeytargetsofwogonininlungcancer
AT zhangjianhua establishmentofalungcancerdiscriminativemodelbasedonanoptimizedsupportvectormachinealgorithmandstudyofkeytargetsofwogonininlungcancer
AT shanguoyong establishmentofalungcancerdiscriminativemodelbasedonanoptimizedsupportvectormachinealgorithmandstudyofkeytargetsofwogonininlungcancer
AT liangjunting establishmentofalungcancerdiscriminativemodelbasedonanoptimizedsupportvectormachinealgorithmandstudyofkeytargetsofwogonininlungcancer
AT jinwenwen establishmentofalungcancerdiscriminativemodelbasedonanoptimizedsupportvectormachinealgorithmandstudyofkeytargetsofwogonininlungcancer
AT liyingyue establishmentofalungcancerdiscriminativemodelbasedonanoptimizedsupportvectormachinealgorithmandstudyofkeytargetsofwogonininlungcancer
AT sufangchu establishmentofalungcancerdiscriminativemodelbasedonanoptimizedsupportvectormachinealgorithmandstudyofkeytargetsofwogonininlungcancer
AT bayanhua establishmentofalungcancerdiscriminativemodelbasedonanoptimizedsupportvectormachinealgorithmandstudyofkeytargetsofwogonininlungcancer
AT tianxifeng establishmentofalungcancerdiscriminativemodelbasedonanoptimizedsupportvectormachinealgorithmandstudyofkeytargetsofwogonininlungcancer
AT sunxiaoyan establishmentofalungcancerdiscriminativemodelbasedonanoptimizedsupportvectormachinealgorithmandstudyofkeytargetsofwogonininlungcancer
AT zhangdayong establishmentofalungcancerdiscriminativemodelbasedonanoptimizedsupportvectormachinealgorithmandstudyofkeytargetsofwogonininlungcancer
AT zhangweihua establishmentofalungcancerdiscriminativemodelbasedonanoptimizedsupportvectormachinealgorithmandstudyofkeytargetsofwogonininlungcancer
AT chenchuanliang establishmentofalungcancerdiscriminativemodelbasedonanoptimizedsupportvectormachinealgorithmandstudyofkeytargetsofwogonininlungcancer