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MicroRNA, mRNA, and Proteomics Biomarkers and Therapeutic Targets for Improving Lung Cancer Treatment Outcomes
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 ( = 109) and 91.7% in unsupervised classificat...
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Published in: | Cancers 2023-04, Vol.15 (8), p.2294 |
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description | 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 (
= 109) and 91.7% in unsupervised classification and 92.3% in supervised classification in the validation set (
= 375). Based on association with patient survival (
= 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. |
doi_str_mv | 10.3390/cancers15082294 |
format | article |
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= 109) and 91.7% in unsupervised classification and 92.3% in supervised classification in the validation set (
= 375). Based on association with patient survival (
= 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.</description><identifier>ISSN: 2072-6694</identifier><identifier>EISSN: 2072-6694</identifier><identifier>DOI: 10.3390/cancers15082294</identifier><identifier>PMID: 37190222</identifier><language>eng</language><publisher>Switzerland: MDPI AG</publisher><subject>AKT protein ; Anthracycline ; Artificial intelligence ; Bioinformatics ; Biological markers ; Biomarkers ; Cancer ; Cancer therapies ; Care and treatment ; Cell cycle ; CRISPR ; Daunorubicin ; Disease ; Drug development ; Drug therapy ; Ethylenediaminetetraacetic acid ; Gene expression ; Genes ; Genetic aspects ; Genomes ; Health aspects ; Lung cancer ; Medical prognosis ; Medical research ; Medicine, Experimental ; Messenger RNA ; Metastases ; Metastasis ; MicroRNA ; MicroRNAs ; miRNA ; mRNA ; Pathology ; Patient outcomes ; Patients ; Protein kinase inhibitors ; Proteins ; Proteomics ; Radiation therapy ; Respiratory agents ; RNA-mediated interference ; Survival ; Therapeutic targets ; Tumors</subject><ispartof>Cancers, 2023-04, Vol.15 (8), p.2294</ispartof><rights>COPYRIGHT 2023 MDPI AG</rights><rights>2023 by the authors. 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/). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.</rights><rights>2023 by the authors. 2023</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c489t-8574fbdbfaf37a2b677085a085e4a3de44de3205eaffd919d4f307f9cd50706c3</citedby><cites>FETCH-LOGICAL-c489t-8574fbdbfaf37a2b677085a085e4a3de44de3205eaffd919d4f307f9cd50706c3</cites><orcidid>0000-0002-8050-6268</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://www.proquest.com/docview/2806509320/fulltextPDF?pq-origsite=primo$$EPDF$$P50$$Gproquest$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://www.proquest.com/docview/2806509320?pq-origsite=primo$$EHTML$$P50$$Gproquest$$Hfree_for_read</linktohtml><link.rule.ids>230,314,723,776,780,881,25731,27901,27902,36989,36990,44566,53766,53768,74869</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/37190222$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Ye, Qing</creatorcontrib><creatorcontrib>Raese, Rebecca</creatorcontrib><creatorcontrib>Luo, Dajie</creatorcontrib><creatorcontrib>Cao, Shu</creatorcontrib><creatorcontrib>Wan, Ying-Wooi</creatorcontrib><creatorcontrib>Qian, Yong</creatorcontrib><creatorcontrib>Guo, Nancy Lan</creatorcontrib><title>MicroRNA, mRNA, and Proteomics Biomarkers and Therapeutic Targets for Improving Lung Cancer Treatment Outcomes</title><title>Cancers</title><addtitle>Cancers (Basel)</addtitle><description>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 (
= 109) and 91.7% in unsupervised classification and 92.3% in supervised classification in the validation set (
= 375). Based on association with patient survival (
= 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.</description><subject>AKT protein</subject><subject>Anthracycline</subject><subject>Artificial intelligence</subject><subject>Bioinformatics</subject><subject>Biological markers</subject><subject>Biomarkers</subject><subject>Cancer</subject><subject>Cancer therapies</subject><subject>Care and treatment</subject><subject>Cell cycle</subject><subject>CRISPR</subject><subject>Daunorubicin</subject><subject>Disease</subject><subject>Drug development</subject><subject>Drug therapy</subject><subject>Ethylenediaminetetraacetic acid</subject><subject>Gene expression</subject><subject>Genes</subject><subject>Genetic aspects</subject><subject>Genomes</subject><subject>Health aspects</subject><subject>Lung cancer</subject><subject>Medical prognosis</subject><subject>Medical research</subject><subject>Medicine, Experimental</subject><subject>Messenger RNA</subject><subject>Metastases</subject><subject>Metastasis</subject><subject>MicroRNA</subject><subject>MicroRNAs</subject><subject>miRNA</subject><subject>mRNA</subject><subject>Pathology</subject><subject>Patient outcomes</subject><subject>Patients</subject><subject>Protein kinase inhibitors</subject><subject>Proteins</subject><subject>Proteomics</subject><subject>Radiation therapy</subject><subject>Respiratory agents</subject><subject>RNA-mediated interference</subject><subject>Survival</subject><subject>Therapeutic targets</subject><subject>Tumors</subject><issn>2072-6694</issn><issn>2072-6694</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2023</creationdate><recordtype>article</recordtype><sourceid>PIMPY</sourceid><recordid>eNptUktvEzEQthCIVqFnbsgSFw6k9WvX6xMKEY9KgSIUzpZjj1OXXTvYu5X49zhpKW2FLY8tzzffPBF6Sckp54qcWRMt5EIb0jGmxBN0zIhk87ZV4um99xE6KeWK1MU5la18jo64pIowxo5R_BJsTt-_Lt7i4SBNdPhbTiOkIdiC34c0mPyzujlo1peQzQ6mMVi8NnkLY8E-ZXw-7HK6DnGLV1MVy0NkeJ3BjAPEEV9Mo00DlBfomTd9gZPbe4Z-fPywXn6ery4-nS8Xq7kVnRrnXSOF37iNN55LwzatlKRrTD0gDHcghAPOSAPGe6eocsJzIr2yriGStJbP0Lsb3t20GcDZGkM2vd7lULP5rZMJ-qEmhku9TdeaElqL04nK8OaWIadfE5RRD6FY6HsTIU1Fs46KhknCZIW-fgS9SlOONb-KIm1DVI31H2pretAh-lQd2z2pXkghOVH7Bs3Q6X9QdTuo_UgRfKj_DwzObgxqG0vJ4O-SpETvx0Q_GpNq8ep-be7wf4eC_wEdurkZ</recordid><startdate>20230414</startdate><enddate>20230414</enddate><creator>Ye, Qing</creator><creator>Raese, Rebecca</creator><creator>Luo, Dajie</creator><creator>Cao, Shu</creator><creator>Wan, Ying-Wooi</creator><creator>Qian, Yong</creator><creator>Guo, Nancy Lan</creator><general>MDPI AG</general><general>MDPI</general><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>3V.</scope><scope>7T5</scope><scope>7TO</scope><scope>7XB</scope><scope>8FE</scope><scope>8FH</scope><scope>8FK</scope><scope>8G5</scope><scope>ABUWG</scope><scope>AFKRA</scope><scope>AZQEC</scope><scope>BBNVY</scope><scope>BENPR</scope><scope>BHPHI</scope><scope>CCPQU</scope><scope>DWQXO</scope><scope>GNUQQ</scope><scope>GUQSH</scope><scope>H94</scope><scope>HCIFZ</scope><scope>LK8</scope><scope>M2O</scope><scope>M7P</scope><scope>MBDVC</scope><scope>PIMPY</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PRINS</scope><scope>Q9U</scope><scope>7X8</scope><scope>5PM</scope><orcidid>https://orcid.org/0000-0002-8050-6268</orcidid></search><sort><creationdate>20230414</creationdate><title>MicroRNA, mRNA, and Proteomics Biomarkers and Therapeutic Targets for Improving Lung Cancer Treatment Outcomes</title><author>Ye, Qing ; Raese, Rebecca ; Luo, Dajie ; Cao, Shu ; Wan, Ying-Wooi ; Qian, Yong ; Guo, Nancy Lan</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c489t-8574fbdbfaf37a2b677085a085e4a3de44de3205eaffd919d4f307f9cd50706c3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2023</creationdate><topic>AKT protein</topic><topic>Anthracycline</topic><topic>Artificial intelligence</topic><topic>Bioinformatics</topic><topic>Biological markers</topic><topic>Biomarkers</topic><topic>Cancer</topic><topic>Cancer therapies</topic><topic>Care and treatment</topic><topic>Cell cycle</topic><topic>CRISPR</topic><topic>Daunorubicin</topic><topic>Disease</topic><topic>Drug development</topic><topic>Drug therapy</topic><topic>Ethylenediaminetetraacetic acid</topic><topic>Gene expression</topic><topic>Genes</topic><topic>Genetic aspects</topic><topic>Genomes</topic><topic>Health aspects</topic><topic>Lung cancer</topic><topic>Medical prognosis</topic><topic>Medical research</topic><topic>Medicine, Experimental</topic><topic>Messenger RNA</topic><topic>Metastases</topic><topic>Metastasis</topic><topic>MicroRNA</topic><topic>MicroRNAs</topic><topic>miRNA</topic><topic>mRNA</topic><topic>Pathology</topic><topic>Patient outcomes</topic><topic>Patients</topic><topic>Protein kinase inhibitors</topic><topic>Proteins</topic><topic>Proteomics</topic><topic>Radiation therapy</topic><topic>Respiratory agents</topic><topic>RNA-mediated interference</topic><topic>Survival</topic><topic>Therapeutic targets</topic><topic>Tumors</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Ye, Qing</creatorcontrib><creatorcontrib>Raese, Rebecca</creatorcontrib><creatorcontrib>Luo, Dajie</creatorcontrib><creatorcontrib>Cao, Shu</creatorcontrib><creatorcontrib>Wan, Ying-Wooi</creatorcontrib><creatorcontrib>Qian, Yong</creatorcontrib><creatorcontrib>Guo, Nancy Lan</creatorcontrib><collection>PubMed</collection><collection>CrossRef</collection><collection>ProQuest Central (Corporate)</collection><collection>Immunology Abstracts</collection><collection>Oncogenes and Growth Factors Abstracts</collection><collection>ProQuest Central (purchase pre-March 2016)</collection><collection>ProQuest SciTech Collection</collection><collection>ProQuest Natural Science Collection</collection><collection>ProQuest Central (Alumni) (purchase pre-March 2016)</collection><collection>Research Library (Alumni Edition)</collection><collection>ProQuest Central (Alumni)</collection><collection>ProQuest Central UK/Ireland</collection><collection>ProQuest Central Essentials</collection><collection>Biological Science Collection</collection><collection>ProQuest Central</collection><collection>ProQuest Natural Science Collection</collection><collection>ProQuest One Community College</collection><collection>ProQuest Central</collection><collection>ProQuest Central Student</collection><collection>Research Library Prep</collection><collection>AIDS and Cancer Research Abstracts</collection><collection>SciTech Premium Collection</collection><collection>Biological Sciences</collection><collection>ProQuest Research Library</collection><collection>Biological Science Database</collection><collection>Research Library (Corporate)</collection><collection>Publicly Available Content Database</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><collection>ProQuest Central China</collection><collection>ProQuest Central Basic</collection><collection>MEDLINE - Academic</collection><collection>PubMed Central (Full Participant titles)</collection><jtitle>Cancers</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Ye, Qing</au><au>Raese, Rebecca</au><au>Luo, Dajie</au><au>Cao, Shu</au><au>Wan, Ying-Wooi</au><au>Qian, Yong</au><au>Guo, Nancy Lan</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>MicroRNA, mRNA, and Proteomics Biomarkers and Therapeutic Targets for Improving Lung Cancer Treatment Outcomes</atitle><jtitle>Cancers</jtitle><addtitle>Cancers (Basel)</addtitle><date>2023-04-14</date><risdate>2023</risdate><volume>15</volume><issue>8</issue><spage>2294</spage><pages>2294-</pages><issn>2072-6694</issn><eissn>2072-6694</eissn><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 (
= 109) and 91.7% in unsupervised classification and 92.3% in supervised classification in the validation set (
= 375). Based on association with patient survival (
= 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.</abstract><cop>Switzerland</cop><pub>MDPI AG</pub><pmid>37190222</pmid><doi>10.3390/cancers15082294</doi><orcidid>https://orcid.org/0000-0002-8050-6268</orcidid><oa>free_for_read</oa></addata></record> |
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subjects | AKT protein Anthracycline Artificial intelligence Bioinformatics Biological markers Biomarkers Cancer Cancer therapies Care and treatment Cell cycle CRISPR Daunorubicin Disease Drug development Drug therapy Ethylenediaminetetraacetic acid Gene expression Genes Genetic aspects Genomes Health aspects Lung cancer Medical prognosis Medical research Medicine, Experimental Messenger RNA Metastases Metastasis MicroRNA MicroRNAs miRNA mRNA Pathology Patient outcomes Patients Protein kinase inhibitors Proteins Proteomics Radiation therapy Respiratory agents RNA-mediated interference Survival Therapeutic targets Tumors |
title | MicroRNA, mRNA, and Proteomics Biomarkers and Therapeutic Targets for Improving Lung Cancer Treatment Outcomes |
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