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Comprehensive Analysis of the Correlation Between Pyroptosis-Related LncRNAs and Tumor Microenvironment, Prognosis, and Immune Infiltration in Hepatocellular Carcinoma
Accumulating evidence shows that pyroptosis plays a crucial role in hepatocellular carcinoma (HCC). However, the relationship between pyroptosis-related long non-coding RNAs (lncRNAs) and HCC tumor characteristics remains enigmatic. We aimed to explore the predictive effect of pyroptosis-related lnc...
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Published in: | Frontiers in genetics 2022-04, Vol.13, p.867627-867627 |
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description | Accumulating evidence shows that pyroptosis plays a crucial role in hepatocellular carcinoma (HCC). However, the relationship between pyroptosis-related long non-coding RNAs (lncRNAs) and HCC tumor characteristics remains enigmatic. We aimed to explore the predictive effect of pyroptosis-related lncRNAs (PRLs) in the prognosis of HCC.
We comprehensively analyzed the role of the PRLs in the tumor microenvironment and HCC prognosis by integrating genomic data from patients of HCC. Consensus clustering analysis of PRLs was applied to identify HCC subtypes. A prognostic model was then established with a training cohort from The Cancer Genome Atlas (TCGA) using univariate and least absolute shrinkage and selection operator (LASSO) Cox regression analysis. Further, we evaluated the accuracy of this predictive model using a validation set. We predicted IC50s of commonly used chemotherapeutic and targeted drugs through the R package pRRophetic.
Based on pyroptosis-related lncRNAs, a prognostic risk signature composed of seven PRLs (MKLN1AS, AL031985.3, SNHG4, GHRLOS, AC005479.2, AC099850.4, and AC026412.3) was established. For long-term prognosis of HCC patients, our model shows excellent accuracy to forecast overall survival of HCC individuals both in training set and testing set. We found a significant correlation between clinical features and the risk score. Patients in the high-risk group had tumor characteristics associated with progression such as aggressive pathological grade and stage. Besides that, gene set enrichment analysis (GSEA) showed that cell cycle and focal adhesion were significantly enriched in the high-risk group.
The association of the risk model constituted by these seven pyroptosis-related lncRNAs with clinical prognosis, tumor microenvironment, chemotherapy and small molecule drugs was evaluated. Our study provides strong evidence for individualized prediction of prognosis, shedding light on immunotherapy in HCC patients. |
doi_str_mv | 10.3389/fgene.2022.867627 |
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We comprehensively analyzed the role of the PRLs in the tumor microenvironment and HCC prognosis by integrating genomic data from patients of HCC. Consensus clustering analysis of PRLs was applied to identify HCC subtypes. A prognostic model was then established with a training cohort from The Cancer Genome Atlas (TCGA) using univariate and least absolute shrinkage and selection operator (LASSO) Cox regression analysis. Further, we evaluated the accuracy of this predictive model using a validation set. We predicted IC50s of commonly used chemotherapeutic and targeted drugs through the R package pRRophetic.
Based on pyroptosis-related lncRNAs, a prognostic risk signature composed of seven PRLs (MKLN1AS, AL031985.3, SNHG4, GHRLOS, AC005479.2, AC099850.4, and AC026412.3) was established. For long-term prognosis of HCC patients, our model shows excellent accuracy to forecast overall survival of HCC individuals both in training set and testing set. We found a significant correlation between clinical features and the risk score. Patients in the high-risk group had tumor characteristics associated with progression such as aggressive pathological grade and stage. Besides that, gene set enrichment analysis (GSEA) showed that cell cycle and focal adhesion were significantly enriched in the high-risk group.
The association of the risk model constituted by these seven pyroptosis-related lncRNAs with clinical prognosis, tumor microenvironment, chemotherapy and small molecule drugs was evaluated. Our study provides strong evidence for individualized prediction of prognosis, shedding light on immunotherapy in HCC patients.</description><identifier>ISSN: 1664-8021</identifier><identifier>EISSN: 1664-8021</identifier><identifier>DOI: 10.3389/fgene.2022.867627</identifier><identifier>PMID: 35559014</identifier><language>eng</language><publisher>Switzerland: Frontiers Media S.A</publisher><subject>Genetics ; hepatocellular carcinoma ; immunotherapy ; lncRNAs ; pyroptosis ; risk signature ; tumor environment</subject><ispartof>Frontiers in genetics, 2022-04, Vol.13, p.867627-867627</ispartof><rights>Copyright © 2022 Qu, Wang, Xu and Guo.</rights><rights>Copyright © 2022 Qu, Wang, Xu and Guo. 2022 Qu, Wang, Xu and Guo</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c395t-1dae047e3f4c0a334f45d259d7b564c041b476c5e9c395d94e4aa8edfe0a18f73</citedby><cites>FETCH-LOGICAL-c395t-1dae047e3f4c0a334f45d259d7b564c041b476c5e9c395d94e4aa8edfe0a18f73</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/PMC9087742/pdf/$$EPDF$$P50$$Gpubmedcentral$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC9087742/$$EHTML$$P50$$Gpubmedcentral$$Hfree_for_read</linktohtml><link.rule.ids>230,314,727,780,784,885,27922,27923,53789,53791</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/35559014$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Qu, Guangzhen</creatorcontrib><creatorcontrib>Wang, Dong</creatorcontrib><creatorcontrib>Xu, Weiyu</creatorcontrib><creatorcontrib>Guo, Wei</creatorcontrib><title>Comprehensive Analysis of the Correlation Between Pyroptosis-Related LncRNAs and Tumor Microenvironment, Prognosis, and Immune Infiltration in Hepatocellular Carcinoma</title><title>Frontiers in genetics</title><addtitle>Front Genet</addtitle><description>Accumulating evidence shows that pyroptosis plays a crucial role in hepatocellular carcinoma (HCC). However, the relationship between pyroptosis-related long non-coding RNAs (lncRNAs) and HCC tumor characteristics remains enigmatic. We aimed to explore the predictive effect of pyroptosis-related lncRNAs (PRLs) in the prognosis of HCC.
We comprehensively analyzed the role of the PRLs in the tumor microenvironment and HCC prognosis by integrating genomic data from patients of HCC. Consensus clustering analysis of PRLs was applied to identify HCC subtypes. A prognostic model was then established with a training cohort from The Cancer Genome Atlas (TCGA) using univariate and least absolute shrinkage and selection operator (LASSO) Cox regression analysis. Further, we evaluated the accuracy of this predictive model using a validation set. We predicted IC50s of commonly used chemotherapeutic and targeted drugs through the R package pRRophetic.
Based on pyroptosis-related lncRNAs, a prognostic risk signature composed of seven PRLs (MKLN1AS, AL031985.3, SNHG4, GHRLOS, AC005479.2, AC099850.4, and AC026412.3) was established. For long-term prognosis of HCC patients, our model shows excellent accuracy to forecast overall survival of HCC individuals both in training set and testing set. We found a significant correlation between clinical features and the risk score. Patients in the high-risk group had tumor characteristics associated with progression such as aggressive pathological grade and stage. Besides that, gene set enrichment analysis (GSEA) showed that cell cycle and focal adhesion were significantly enriched in the high-risk group.
The association of the risk model constituted by these seven pyroptosis-related lncRNAs with clinical prognosis, tumor microenvironment, chemotherapy and small molecule drugs was evaluated. Our study provides strong evidence for individualized prediction of prognosis, shedding light on immunotherapy in HCC patients.</description><subject>Genetics</subject><subject>hepatocellular carcinoma</subject><subject>immunotherapy</subject><subject>lncRNAs</subject><subject>pyroptosis</subject><subject>risk signature</subject><subject>tumor environment</subject><issn>1664-8021</issn><issn>1664-8021</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2022</creationdate><recordtype>article</recordtype><sourceid>DOA</sourceid><recordid>eNpVksFu1DAQhiMEolXpA3BBPnJoFid24uSCtKwKXWmBqipna-KMd10ldrCTRftEvCbObqlaX2zN_PONPf6T5H1GF4xV9Se9RYuLnOb5oipFmYtXyXlWljytaJ69fnY-Sy5DeKBx8Zoxxt8mZ6woippm_Dz5u3L94HGHNpg9kqWF7hBMIE6TcYdk5bzHDkbjLPmC4x9ES24P3g2ji6r0bs5hSzZW3f1YBgK2JfdT7zz5bpR3aPfGO9ujHa_IrXdbO1ddHWXrvp8skrXVphv9qYOx5AYHGJ3Crps68GQFXhnreniXvNHQBbx83C-SX1-v71c36ebnt_VquUkVq4sxzVpAygUyzRWF-FjNizYv6lY0RRlDPGu4KFWB9axva44coMJWI4Ws0oJdJOsTt3XwIAdvevAH6cDIY8D5rQQ_GtWhBJ3lDauUKOuWl7wBrcqGVqJkDFVR6cj6fGINU9Njq-IYPHQvoC8z1uzk1u1lHSmC5xHw8RHg3e8Jwyh7E-bZgEU3BZnHL66oEJRFaXaSxrGH4FE_tcmonP0ij36Rs1_kyS-x5sPz-z1V_HcH-weV7sHz</recordid><startdate>20220426</startdate><enddate>20220426</enddate><creator>Qu, Guangzhen</creator><creator>Wang, Dong</creator><creator>Xu, Weiyu</creator><creator>Guo, 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>20220426</creationdate><title>Comprehensive Analysis of the Correlation Between Pyroptosis-Related LncRNAs and Tumor Microenvironment, Prognosis, and Immune Infiltration in Hepatocellular Carcinoma</title><author>Qu, Guangzhen ; Wang, Dong ; Xu, Weiyu ; Guo, Wei</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c395t-1dae047e3f4c0a334f45d259d7b564c041b476c5e9c395d94e4aa8edfe0a18f73</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2022</creationdate><topic>Genetics</topic><topic>hepatocellular carcinoma</topic><topic>immunotherapy</topic><topic>lncRNAs</topic><topic>pyroptosis</topic><topic>risk signature</topic><topic>tumor environment</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Qu, Guangzhen</creatorcontrib><creatorcontrib>Wang, Dong</creatorcontrib><creatorcontrib>Xu, Weiyu</creatorcontrib><creatorcontrib>Guo, Wei</creatorcontrib><collection>PubMed</collection><collection>CrossRef</collection><collection>MEDLINE - Academic</collection><collection>PubMed Central (Full Participant titles)</collection><collection>DOAJ Directory of Open Access Journals</collection><jtitle>Frontiers in genetics</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Qu, Guangzhen</au><au>Wang, Dong</au><au>Xu, Weiyu</au><au>Guo, Wei</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Comprehensive Analysis of the Correlation Between Pyroptosis-Related LncRNAs and Tumor Microenvironment, Prognosis, and Immune Infiltration in Hepatocellular Carcinoma</atitle><jtitle>Frontiers in genetics</jtitle><addtitle>Front Genet</addtitle><date>2022-04-26</date><risdate>2022</risdate><volume>13</volume><spage>867627</spage><epage>867627</epage><pages>867627-867627</pages><issn>1664-8021</issn><eissn>1664-8021</eissn><abstract>Accumulating evidence shows that pyroptosis plays a crucial role in hepatocellular carcinoma (HCC). However, the relationship between pyroptosis-related long non-coding RNAs (lncRNAs) and HCC tumor characteristics remains enigmatic. We aimed to explore the predictive effect of pyroptosis-related lncRNAs (PRLs) in the prognosis of HCC.
We comprehensively analyzed the role of the PRLs in the tumor microenvironment and HCC prognosis by integrating genomic data from patients of HCC. Consensus clustering analysis of PRLs was applied to identify HCC subtypes. A prognostic model was then established with a training cohort from The Cancer Genome Atlas (TCGA) using univariate and least absolute shrinkage and selection operator (LASSO) Cox regression analysis. Further, we evaluated the accuracy of this predictive model using a validation set. We predicted IC50s of commonly used chemotherapeutic and targeted drugs through the R package pRRophetic.
Based on pyroptosis-related lncRNAs, a prognostic risk signature composed of seven PRLs (MKLN1AS, AL031985.3, SNHG4, GHRLOS, AC005479.2, AC099850.4, and AC026412.3) was established. For long-term prognosis of HCC patients, our model shows excellent accuracy to forecast overall survival of HCC individuals both in training set and testing set. We found a significant correlation between clinical features and the risk score. Patients in the high-risk group had tumor characteristics associated with progression such as aggressive pathological grade and stage. Besides that, gene set enrichment analysis (GSEA) showed that cell cycle and focal adhesion were significantly enriched in the high-risk group.
The association of the risk model constituted by these seven pyroptosis-related lncRNAs with clinical prognosis, tumor microenvironment, chemotherapy and small molecule drugs was evaluated. Our study provides strong evidence for individualized prediction of prognosis, shedding light on immunotherapy in HCC patients.</abstract><cop>Switzerland</cop><pub>Frontiers Media S.A</pub><pmid>35559014</pmid><doi>10.3389/fgene.2022.867627</doi><tpages>1</tpages><oa>free_for_read</oa></addata></record> |
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title | Comprehensive Analysis of the Correlation Between Pyroptosis-Related LncRNAs and Tumor Microenvironment, Prognosis, and Immune Infiltration in Hepatocellular Carcinoma |
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