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Exploring a four-gene risk model based on doxorubicin resistance-associated lncRNAs in hepatocellular carcinoma
Liver cancer is a lethal cancer type among which hepatocellular carcinoma (HCC) is the most common manifestation globally. Drug resistance is a central problem impeding the efficiency of HCC treatment. Long non-coding RNAs reportedly result in drug resistance. This study aimed to identify key lncRNA...
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Published in: | Frontiers in pharmacology 2022-11, Vol.13, p.1015842 |
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creator | Zhang, Zunyi Chen, Weixun Luo, Chu Zhang, Wei |
description | Liver cancer is a lethal cancer type among which hepatocellular carcinoma (HCC) is the most common manifestation globally. Drug resistance is a central problem impeding the efficiency of HCC treatment. Long non-coding RNAs reportedly result in drug resistance. This study aimed to identify key lncRNAs associated with doxorubicin resistance and HCC prognosis.
HCC samples with gene expression profiles and clinical data were accessed from public databases. We applied differential analysis to identify key lncRNAs that differed between HCC and normal samples and between drug-fast and control samples. We also used univariate Cox regression analysis to screen lncRNAs or genes associated with HCC prognosis. The least absolute shrinkage and selection operator (LASSO) was used to identify the key prognostic genes. Finally, we used receiver operating characteristic analysis to validate the effectiveness of the risk model.
The results of this study revealed RNF157-AS1 as a key lncRNA associated with both doxorubicin resistance and HCC prognosis. Metabolic pathways such as fatty acid metabolism and oxidative phosphorylation were enriched in RNF157-AS1-related genes. LASSO identified four protein-coding genes-
,
,
, and
-to construct a risk model. The four-gene risk model effectively classified HCC samples into two risk groups with different overall survival. Finally, we established a nomogram, which showed superior performance in predicting the long-term prognosis of HCC.
RNF157-AS1 may be involved in doxorubicin resistance and may serve as a potential therapeutic target. The four-gene risk model showed potential for the prediction of HCC prognosis. |
doi_str_mv | 10.3389/fphar.2022.1015842 |
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fullrecord | <record><control><sourceid>proquest_doaj_</sourceid><recordid>TN_cdi_doaj_primary_oai_doaj_org_article_95943c2af3a44237a19bf667699f6701</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><doaj_id>oai_doaj_org_article_95943c2af3a44237a19bf667699f6701</doaj_id><sourcerecordid>2746391668</sourcerecordid><originalsourceid>FETCH-LOGICAL-c419t-1b99b656f1a47937d4bae3e160844e7b47bfb95d228d2ade894082415b969cbb3</originalsourceid><addsrcrecordid>eNpVkUtv1DAURiMEolXpH2CBvGSTwa_4sUGqqtJWqkBCsLauH5lxSeJgJ6j8ezydoWq9sK_s7x5bPk3znuANY0p_6ucd5A3FlG4IJp3i9FVzSoRgrVaEvn5WnzTnpdzjOpjWTPC3zUmdOymxPG3S1cM8pBynLQLUpzW32zAFlGP5hcbkw4AslOBRmpBPDymvNro4oRxKLAtMLrRQSnIRlhoaJvf960VBNbALMyzJhWFYB8jIQa5taYR3zZsehhLOj-tZ8_PL1Y_Lm_bu2_Xt5cVd6zjRS0us1lZ0oifApWbScwuBBSKw4jxIy6Xtre48pcpT8EFpjhXlpLNaaGctO2tuD1yf4N7MOY6Q_5oE0TxupLw1kJfohmB0pzlzFHoGnFMmgWjbCyGF1r2QmFTW5wNrXu0YvAvTkmF4AX15MsWd2aY_RkusmOIV8PEIyOn3Gspixlj2fwNTSGsxVHLBdBWmapQeoi6nUnLon64h2OzFm0fxZi_eHMXXpg_PH_jU8l8z-wcnFKwp</addsrcrecordid><sourcetype>Open Website</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>2746391668</pqid></control><display><type>article</type><title>Exploring a four-gene risk model based on doxorubicin resistance-associated lncRNAs in hepatocellular carcinoma</title><source>PubMed (Medline)</source><creator>Zhang, Zunyi ; Chen, Weixun ; Luo, Chu ; Zhang, Wei</creator><creatorcontrib>Zhang, Zunyi ; Chen, Weixun ; Luo, Chu ; Zhang, Wei</creatorcontrib><description>Liver cancer is a lethal cancer type among which hepatocellular carcinoma (HCC) is the most common manifestation globally. Drug resistance is a central problem impeding the efficiency of HCC treatment. Long non-coding RNAs reportedly result in drug resistance. This study aimed to identify key lncRNAs associated with doxorubicin resistance and HCC prognosis.
HCC samples with gene expression profiles and clinical data were accessed from public databases. We applied differential analysis to identify key lncRNAs that differed between HCC and normal samples and between drug-fast and control samples. We also used univariate Cox regression analysis to screen lncRNAs or genes associated with HCC prognosis. The least absolute shrinkage and selection operator (LASSO) was used to identify the key prognostic genes. Finally, we used receiver operating characteristic analysis to validate the effectiveness of the risk model.
The results of this study revealed RNF157-AS1 as a key lncRNA associated with both doxorubicin resistance and HCC prognosis. Metabolic pathways such as fatty acid metabolism and oxidative phosphorylation were enriched in RNF157-AS1-related genes. LASSO identified four protein-coding genes-
,
,
, and
-to construct a risk model. The four-gene risk model effectively classified HCC samples into two risk groups with different overall survival. Finally, we established a nomogram, which showed superior performance in predicting the long-term prognosis of HCC.
RNF157-AS1 may be involved in doxorubicin resistance and may serve as a potential therapeutic target. The four-gene risk model showed potential for the prediction of HCC prognosis.</description><identifier>ISSN: 1663-9812</identifier><identifier>EISSN: 1663-9812</identifier><identifier>DOI: 10.3389/fphar.2022.1015842</identifier><identifier>PMID: 36457707</identifier><language>eng</language><publisher>Switzerland: Frontiers Media S.A</publisher><subject>hepatocellular carcinoma ; lncRNAs ; long non-coding RNAs ; Pharmacology ; risk model ; RNF157-AS1</subject><ispartof>Frontiers in pharmacology, 2022-11, Vol.13, p.1015842</ispartof><rights>Copyright © 2022 Zhang, Chen, Luo and Zhang.</rights><rights>Copyright © 2022 Zhang, Chen, Luo and Zhang. 2022 Zhang, Chen, Luo and Zhang</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><cites>FETCH-LOGICAL-c419t-1b99b656f1a47937d4bae3e160844e7b47bfb95d228d2ade894082415b969cbb3</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC9708384/pdf/$$EPDF$$P50$$Gpubmedcentral$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC9708384/$$EHTML$$P50$$Gpubmedcentral$$Hfree_for_read</linktohtml><link.rule.ids>230,314,727,780,784,885,27924,27925,53791,53793</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/36457707$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Zhang, Zunyi</creatorcontrib><creatorcontrib>Chen, Weixun</creatorcontrib><creatorcontrib>Luo, Chu</creatorcontrib><creatorcontrib>Zhang, Wei</creatorcontrib><title>Exploring a four-gene risk model based on doxorubicin resistance-associated lncRNAs in hepatocellular carcinoma</title><title>Frontiers in pharmacology</title><addtitle>Front Pharmacol</addtitle><description>Liver cancer is a lethal cancer type among which hepatocellular carcinoma (HCC) is the most common manifestation globally. Drug resistance is a central problem impeding the efficiency of HCC treatment. Long non-coding RNAs reportedly result in drug resistance. This study aimed to identify key lncRNAs associated with doxorubicin resistance and HCC prognosis.
HCC samples with gene expression profiles and clinical data were accessed from public databases. We applied differential analysis to identify key lncRNAs that differed between HCC and normal samples and between drug-fast and control samples. We also used univariate Cox regression analysis to screen lncRNAs or genes associated with HCC prognosis. The least absolute shrinkage and selection operator (LASSO) was used to identify the key prognostic genes. Finally, we used receiver operating characteristic analysis to validate the effectiveness of the risk model.
The results of this study revealed RNF157-AS1 as a key lncRNA associated with both doxorubicin resistance and HCC prognosis. Metabolic pathways such as fatty acid metabolism and oxidative phosphorylation were enriched in RNF157-AS1-related genes. LASSO identified four protein-coding genes-
,
,
, and
-to construct a risk model. The four-gene risk model effectively classified HCC samples into two risk groups with different overall survival. Finally, we established a nomogram, which showed superior performance in predicting the long-term prognosis of HCC.
RNF157-AS1 may be involved in doxorubicin resistance and may serve as a potential therapeutic target. The four-gene risk model showed potential for the prediction of HCC prognosis.</description><subject>hepatocellular carcinoma</subject><subject>lncRNAs</subject><subject>long non-coding RNAs</subject><subject>Pharmacology</subject><subject>risk model</subject><subject>RNF157-AS1</subject><issn>1663-9812</issn><issn>1663-9812</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2022</creationdate><recordtype>article</recordtype><sourceid>DOA</sourceid><recordid>eNpVkUtv1DAURiMEolXpH2CBvGSTwa_4sUGqqtJWqkBCsLauH5lxSeJgJ6j8ezydoWq9sK_s7x5bPk3znuANY0p_6ucd5A3FlG4IJp3i9FVzSoRgrVaEvn5WnzTnpdzjOpjWTPC3zUmdOymxPG3S1cM8pBynLQLUpzW32zAFlGP5hcbkw4AslOBRmpBPDymvNro4oRxKLAtMLrRQSnIRlhoaJvf960VBNbALMyzJhWFYB8jIQa5taYR3zZsehhLOj-tZ8_PL1Y_Lm_bu2_Xt5cVd6zjRS0us1lZ0oifApWbScwuBBSKw4jxIy6Xtre48pcpT8EFpjhXlpLNaaGctO2tuD1yf4N7MOY6Q_5oE0TxupLw1kJfohmB0pzlzFHoGnFMmgWjbCyGF1r2QmFTW5wNrXu0YvAvTkmF4AX15MsWd2aY_RkusmOIV8PEIyOn3Gspixlj2fwNTSGsxVHLBdBWmapQeoi6nUnLon64h2OzFm0fxZi_eHMXXpg_PH_jU8l8z-wcnFKwp</recordid><startdate>20221110</startdate><enddate>20221110</enddate><creator>Zhang, Zunyi</creator><creator>Chen, Weixun</creator><creator>Luo, Chu</creator><creator>Zhang, Wei</creator><general>Frontiers Media S.A</general><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7X8</scope><scope>5PM</scope><scope>DOA</scope></search><sort><creationdate>20221110</creationdate><title>Exploring a four-gene risk model based on doxorubicin resistance-associated lncRNAs in hepatocellular carcinoma</title><author>Zhang, Zunyi ; Chen, Weixun ; Luo, Chu ; Zhang, Wei</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c419t-1b99b656f1a47937d4bae3e160844e7b47bfb95d228d2ade894082415b969cbb3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2022</creationdate><topic>hepatocellular carcinoma</topic><topic>lncRNAs</topic><topic>long non-coding RNAs</topic><topic>Pharmacology</topic><topic>risk model</topic><topic>RNF157-AS1</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Zhang, Zunyi</creatorcontrib><creatorcontrib>Chen, Weixun</creatorcontrib><creatorcontrib>Luo, Chu</creatorcontrib><creatorcontrib>Zhang, Wei</creatorcontrib><collection>PubMed</collection><collection>CrossRef</collection><collection>MEDLINE - Academic</collection><collection>PubMed Central (Full Participant titles)</collection><collection>Directory of Open Access Journals</collection><jtitle>Frontiers in pharmacology</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Zhang, Zunyi</au><au>Chen, Weixun</au><au>Luo, Chu</au><au>Zhang, Wei</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Exploring a four-gene risk model based on doxorubicin resistance-associated lncRNAs in hepatocellular carcinoma</atitle><jtitle>Frontiers in pharmacology</jtitle><addtitle>Front Pharmacol</addtitle><date>2022-11-10</date><risdate>2022</risdate><volume>13</volume><spage>1015842</spage><pages>1015842-</pages><issn>1663-9812</issn><eissn>1663-9812</eissn><abstract>Liver cancer is a lethal cancer type among which hepatocellular carcinoma (HCC) is the most common manifestation globally. Drug resistance is a central problem impeding the efficiency of HCC treatment. Long non-coding RNAs reportedly result in drug resistance. This study aimed to identify key lncRNAs associated with doxorubicin resistance and HCC prognosis.
HCC samples with gene expression profiles and clinical data were accessed from public databases. We applied differential analysis to identify key lncRNAs that differed between HCC and normal samples and between drug-fast and control samples. We also used univariate Cox regression analysis to screen lncRNAs or genes associated with HCC prognosis. The least absolute shrinkage and selection operator (LASSO) was used to identify the key prognostic genes. Finally, we used receiver operating characteristic analysis to validate the effectiveness of the risk model.
The results of this study revealed RNF157-AS1 as a key lncRNA associated with both doxorubicin resistance and HCC prognosis. Metabolic pathways such as fatty acid metabolism and oxidative phosphorylation were enriched in RNF157-AS1-related genes. LASSO identified four protein-coding genes-
,
,
, and
-to construct a risk model. The four-gene risk model effectively classified HCC samples into two risk groups with different overall survival. Finally, we established a nomogram, which showed superior performance in predicting the long-term prognosis of HCC.
RNF157-AS1 may be involved in doxorubicin resistance and may serve as a potential therapeutic target. The four-gene risk model showed potential for the prediction of HCC prognosis.</abstract><cop>Switzerland</cop><pub>Frontiers Media S.A</pub><pmid>36457707</pmid><doi>10.3389/fphar.2022.1015842</doi><oa>free_for_read</oa></addata></record> |
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subjects | hepatocellular carcinoma lncRNAs long non-coding RNAs Pharmacology risk model RNF157-AS1 |
title | Exploring a four-gene risk model based on doxorubicin resistance-associated lncRNAs in hepatocellular carcinoma |
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