Cargando…

MicroRNA, mRNA, and Proteomics Biomarkers and Therapeutic Targets for Improving Lung Cancer Treatment Outcomes

SIMPLE SUMMARY: This study identified a set of 73 microRNAs (miRNAs) that can accurately detect lung cancer tumors from normal lung tissues. Based on the consistent expression patterns associated with patient survival outcomes and in tumors vs. normal lung tissues, 10 miRNAs were considered to be pu...

Descripción completa

Detalles Bibliográficos
Autores principales: Ye, Qing, Raese, Rebecca, Luo, Dajie, Cao, Shu, Wan, Ying-Wooi, Qian, Yong, Guo, Nancy Lan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10137184/
https://www.ncbi.nlm.nih.gov/pubmed/37190222
http://dx.doi.org/10.3390/cancers15082294
_version_ 1785032398908424192
author Ye, Qing
Raese, Rebecca
Luo, Dajie
Cao, Shu
Wan, Ying-Wooi
Qian, Yong
Guo, Nancy Lan
author_facet Ye, Qing
Raese, Rebecca
Luo, Dajie
Cao, Shu
Wan, Ying-Wooi
Qian, Yong
Guo, Nancy Lan
author_sort Ye, Qing
collection PubMed
description SIMPLE SUMMARY: This study identified a set of 73 microRNAs (miRNAs) that can accurately detect lung cancer tumors from normal lung tissues. Based on the consistent expression patterns associated with patient survival outcomes and in tumors vs. normal lung tissues, 10 miRNAs were considered to be putatively tumor suppressive and 4 miRNAs were deemed as oncogenic in lung cancer. From the list of genes that were targeted by the 73 diagnostic miRNAs, DGKE and WDR47 had significant associations with responses to both systemic therapies and radiotherapy in lung cancer. Based on our identified miRNA-regulated network, we discovered three drugs—BX-912, daunorubicin, and midostaurin—that can be repositioned to treat lung cancer, which was not known before. ABSTRACT: The majority of lung cancer patients are diagnosed with metastatic disease. This study identified a set of 73 microRNAs (miRNAs) that classified lung cancer tumors from normal lung tissues with an overall accuracy of 96.3% in the training patient cohort (n = 109) and 91.7% in unsupervised classification and 92.3% in supervised classification in the validation set (n = 375). Based on association with patient survival (n = 1016), 10 miRNAs were identified as potential tumor suppressors (hsa-miR-144, hsa-miR-195, hsa-miR-223, hsa-miR-30a, hsa-miR-30b, hsa-miR-30d, hsa-miR-335, hsa-miR-363, hsa-miR-451, and hsa-miR-99a), and 4 were identified as potential oncogenes (hsa-miR-21, hsa-miR-31, hsa-miR-411, and hsa-miR-494) in lung cancer. Experimentally confirmed target genes were identified for the 73 diagnostic miRNAs, from which proliferation genes were selected from CRISPR-Cas9/RNA interference (RNAi) screening assays. Pansensitive and panresistant genes to 21 NCCN-recommended drugs with concordant mRNA and protein expression were identified. DGKE and WDR47 were found with significant associations with responses to both systemic therapies and radiotherapy in lung cancer. Based on our identified miRNA-regulated molecular machinery, an inhibitor of PDK1/Akt BX-912, an anthracycline antibiotic daunorubicin, and a multi-targeted protein kinase inhibitor midostaurin were discovered as potential repositioning drugs for treating lung cancer. These findings have implications for improving lung cancer diagnosis, optimizing treatment selection, and discovering new drug options for better patient outcomes.
format Online
Article
Text
id pubmed-10137184
institution National Center for Biotechnology Information
language English
publishDate 2023
publisher MDPI
record_format MEDLINE/PubMed
spelling pubmed-101371842023-04-28 MicroRNA, mRNA, and Proteomics Biomarkers and Therapeutic Targets for Improving Lung Cancer Treatment Outcomes Ye, Qing Raese, Rebecca Luo, Dajie Cao, Shu Wan, Ying-Wooi Qian, Yong Guo, Nancy Lan Cancers (Basel) Article SIMPLE SUMMARY: This study identified a set of 73 microRNAs (miRNAs) that can accurately detect lung cancer tumors from normal lung tissues. Based on the consistent expression patterns associated with patient survival outcomes and in tumors vs. normal lung tissues, 10 miRNAs were considered to be putatively tumor suppressive and 4 miRNAs were deemed as oncogenic in lung cancer. From the list of genes that were targeted by the 73 diagnostic miRNAs, DGKE and WDR47 had significant associations with responses to both systemic therapies and radiotherapy in lung cancer. Based on our identified miRNA-regulated network, we discovered three drugs—BX-912, daunorubicin, and midostaurin—that can be repositioned to treat lung cancer, which was not known before. ABSTRACT: The majority of lung cancer patients are diagnosed with metastatic disease. This study identified a set of 73 microRNAs (miRNAs) that classified lung cancer tumors from normal lung tissues with an overall accuracy of 96.3% in the training patient cohort (n = 109) and 91.7% in unsupervised classification and 92.3% in supervised classification in the validation set (n = 375). Based on association with patient survival (n = 1016), 10 miRNAs were identified as potential tumor suppressors (hsa-miR-144, hsa-miR-195, hsa-miR-223, hsa-miR-30a, hsa-miR-30b, hsa-miR-30d, hsa-miR-335, hsa-miR-363, hsa-miR-451, and hsa-miR-99a), and 4 were identified as potential oncogenes (hsa-miR-21, hsa-miR-31, hsa-miR-411, and hsa-miR-494) in lung cancer. Experimentally confirmed target genes were identified for the 73 diagnostic miRNAs, from which proliferation genes were selected from CRISPR-Cas9/RNA interference (RNAi) screening assays. Pansensitive and panresistant genes to 21 NCCN-recommended drugs with concordant mRNA and protein expression were identified. DGKE and WDR47 were found with significant associations with responses to both systemic therapies and radiotherapy in lung cancer. Based on our identified miRNA-regulated molecular machinery, an inhibitor of PDK1/Akt BX-912, an anthracycline antibiotic daunorubicin, and a multi-targeted protein kinase inhibitor midostaurin were discovered as potential repositioning drugs for treating lung cancer. These findings have implications for improving lung cancer diagnosis, optimizing treatment selection, and discovering new drug options for better patient outcomes. MDPI 2023-04-14 /pmc/articles/PMC10137184/ /pubmed/37190222 http://dx.doi.org/10.3390/cancers15082294 Text en © 2023 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Ye, Qing
Raese, Rebecca
Luo, Dajie
Cao, Shu
Wan, Ying-Wooi
Qian, Yong
Guo, Nancy Lan
MicroRNA, mRNA, and Proteomics Biomarkers and Therapeutic Targets for Improving Lung Cancer Treatment Outcomes
title MicroRNA, mRNA, and Proteomics Biomarkers and Therapeutic Targets for Improving Lung Cancer Treatment Outcomes
title_full MicroRNA, mRNA, and Proteomics Biomarkers and Therapeutic Targets for Improving Lung Cancer Treatment Outcomes
title_fullStr MicroRNA, mRNA, and Proteomics Biomarkers and Therapeutic Targets for Improving Lung Cancer Treatment Outcomes
title_full_unstemmed MicroRNA, mRNA, and Proteomics Biomarkers and Therapeutic Targets for Improving Lung Cancer Treatment Outcomes
title_short MicroRNA, mRNA, and Proteomics Biomarkers and Therapeutic Targets for Improving Lung Cancer Treatment Outcomes
title_sort microrna, mrna, and proteomics biomarkers and therapeutic targets for improving lung cancer treatment outcomes
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10137184/
https://www.ncbi.nlm.nih.gov/pubmed/37190222
http://dx.doi.org/10.3390/cancers15082294
work_keys_str_mv AT yeqing micrornamrnaandproteomicsbiomarkersandtherapeutictargetsforimprovinglungcancertreatmentoutcomes
AT raeserebecca micrornamrnaandproteomicsbiomarkersandtherapeutictargetsforimprovinglungcancertreatmentoutcomes
AT luodajie micrornamrnaandproteomicsbiomarkersandtherapeutictargetsforimprovinglungcancertreatmentoutcomes
AT caoshu micrornamrnaandproteomicsbiomarkersandtherapeutictargetsforimprovinglungcancertreatmentoutcomes
AT wanyingwooi micrornamrnaandproteomicsbiomarkersandtherapeutictargetsforimprovinglungcancertreatmentoutcomes
AT qianyong micrornamrnaandproteomicsbiomarkersandtherapeutictargetsforimprovinglungcancertreatmentoutcomes
AT guonancylan micrornamrnaandproteomicsbiomarkersandtherapeutictargetsforimprovinglungcancertreatmentoutcomes