The implication of necroptosis-related lncRNAs in orchestrating immune infiltration and predicting therapeutic efficacy in colon adenocarcinoma: an integrated bioinformatic analysis with preliminarily experimental validation
Background: Necroptosis contributes significantly to colon adenocarcinoma (COAD). We aim to assess the relationship between immunoinfiltration and stemness in COAD patients through the development of a risk score profile using necroptosis-related long noncoding RNAs (NRLs).Methods: Our study was bas...
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| Format: | Article |
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Frontiers Media S.A.
2023-08-01
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| Series: | Frontiers in Genetics |
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| Online Access: | https://www.frontiersin.org/articles/10.3389/fgene.2023.1170640/full |
| _version_ | 1797756452933206016 |
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| author | Shizhe Li Shizhe Li Xiaotong Wang Xiaotong Wang Yajun Liu Junbo Xiao Junbo Xiao Jun Yi Jun Yi |
| author_facet | Shizhe Li Shizhe Li Xiaotong Wang Xiaotong Wang Yajun Liu Junbo Xiao Junbo Xiao Jun Yi Jun Yi |
| author_sort | Shizhe Li |
| collection | DOAJ |
| description | Background: Necroptosis contributes significantly to colon adenocarcinoma (COAD). We aim to assess the relationship between immunoinfiltration and stemness in COAD patients through the development of a risk score profile using necroptosis-related long noncoding RNAs (NRLs).Methods: Our study was based on gene expression data and relevant clinical information from The Cancer Genome Atlas (TCGA). Necroptosis-related genes (NRGs) were obtained from the Kyoto Encyclopedia of Genes and Genome (KEGG) database. Pearson correlation analysis, Cox regression, and least absolute shrinkage and selection operator (LASSO) regression were used to determine the NRL prognositic signature (NRLPS). NRLs expression was examined using qRT-PCR method. Several algorithms were used to identify relationships between immune cell infiltration and NRLPS risk scores. Further analysis of somatic mutations, tumor stemness index (TSI), and drug sensitivity were also explored.Results: To construct NRLPS, 15 lncRNAs were investigated. Furthermore, NRLPS patients with high-risk subgroups had lower survival rates than that of patients with low-risk subgroups. Using GSEA analysis, NRL was found to be enriched in Notch, Hedgehog and Smoothened pathways. Immune infiltration analysis showed significant differences in CD8+ T cells, dendritic cell DCs, and CD4+ T cells between the two risk groups. In addition, our NRLPS showed a relevance with the regulation of tumor microenvironment, tumor mutation burden (TMB) and stemness. Finally, NRLPS demonstrated potential applications in predicting the efficacy of immunotherapy and chemotherapy in patients with COAD.Conclusion: Based on NRLs, a prognostic model was developed for COAD patients that allows a personalized tailoring immunotherapy and chemotherapy to be tailored. |
| first_indexed | 2024-03-12T18:00:36Z |
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| issn | 1664-8021 |
| language | English |
| last_indexed | 2024-03-12T18:00:36Z |
| publishDate | 2023-08-01 |
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| series | Frontiers in Genetics |
| spelling | doaj.art-a68e12d3c33145e7bc2e111e7e7247582023-08-02T11:19:47ZengFrontiers Media S.A.Frontiers in Genetics1664-80212023-08-011410.3389/fgene.2023.11706401170640The implication of necroptosis-related lncRNAs in orchestrating immune infiltration and predicting therapeutic efficacy in colon adenocarcinoma: an integrated bioinformatic analysis with preliminarily experimental validationShizhe Li0Shizhe Li1Xiaotong Wang2Xiaotong Wang3Yajun Liu4Junbo Xiao5Junbo Xiao6Jun Yi7Jun Yi8Xiangya Hospital, Central South University, Changsha, ChinaHunan Provincial People’s Hospital, Changsha, Hunan, ChinaXiangya Hospital, Central South University, Changsha, ChinaHunan Provincial People’s Hospital, Changsha, Hunan, ChinaHunan Provincial People’s Hospital, Changsha, Hunan, ChinaXiangya Hospital, Central South University, Changsha, ChinaHunan Provincial People’s Hospital, Changsha, Hunan, ChinaXiangya Hospital, Central South University, Changsha, ChinaHunan Provincial People’s Hospital, Changsha, Hunan, ChinaBackground: Necroptosis contributes significantly to colon adenocarcinoma (COAD). We aim to assess the relationship between immunoinfiltration and stemness in COAD patients through the development of a risk score profile using necroptosis-related long noncoding RNAs (NRLs).Methods: Our study was based on gene expression data and relevant clinical information from The Cancer Genome Atlas (TCGA). Necroptosis-related genes (NRGs) were obtained from the Kyoto Encyclopedia of Genes and Genome (KEGG) database. Pearson correlation analysis, Cox regression, and least absolute shrinkage and selection operator (LASSO) regression were used to determine the NRL prognositic signature (NRLPS). NRLs expression was examined using qRT-PCR method. Several algorithms were used to identify relationships between immune cell infiltration and NRLPS risk scores. Further analysis of somatic mutations, tumor stemness index (TSI), and drug sensitivity were also explored.Results: To construct NRLPS, 15 lncRNAs were investigated. Furthermore, NRLPS patients with high-risk subgroups had lower survival rates than that of patients with low-risk subgroups. Using GSEA analysis, NRL was found to be enriched in Notch, Hedgehog and Smoothened pathways. Immune infiltration analysis showed significant differences in CD8+ T cells, dendritic cell DCs, and CD4+ T cells between the two risk groups. In addition, our NRLPS showed a relevance with the regulation of tumor microenvironment, tumor mutation burden (TMB) and stemness. Finally, NRLPS demonstrated potential applications in predicting the efficacy of immunotherapy and chemotherapy in patients with COAD.Conclusion: Based on NRLs, a prognostic model was developed for COAD patients that allows a personalized tailoring immunotherapy and chemotherapy to be tailored.https://www.frontiersin.org/articles/10.3389/fgene.2023.1170640/fullnecroptosis-related genes and lncRNAscolon adenocarcinomastemnessbioinformatic analysis and experimental validationimmune infiltration |
| spellingShingle | Shizhe Li Shizhe Li Xiaotong Wang Xiaotong Wang Yajun Liu Junbo Xiao Junbo Xiao Jun Yi Jun Yi The implication of necroptosis-related lncRNAs in orchestrating immune infiltration and predicting therapeutic efficacy in colon adenocarcinoma: an integrated bioinformatic analysis with preliminarily experimental validation Frontiers in Genetics necroptosis-related genes and lncRNAs colon adenocarcinoma stemness bioinformatic analysis and experimental validation immune infiltration |
| title | The implication of necroptosis-related lncRNAs in orchestrating immune infiltration and predicting therapeutic efficacy in colon adenocarcinoma: an integrated bioinformatic analysis with preliminarily experimental validation |
| title_full | The implication of necroptosis-related lncRNAs in orchestrating immune infiltration and predicting therapeutic efficacy in colon adenocarcinoma: an integrated bioinformatic analysis with preliminarily experimental validation |
| title_fullStr | The implication of necroptosis-related lncRNAs in orchestrating immune infiltration and predicting therapeutic efficacy in colon adenocarcinoma: an integrated bioinformatic analysis with preliminarily experimental validation |
| title_full_unstemmed | The implication of necroptosis-related lncRNAs in orchestrating immune infiltration and predicting therapeutic efficacy in colon adenocarcinoma: an integrated bioinformatic analysis with preliminarily experimental validation |
| title_short | The implication of necroptosis-related lncRNAs in orchestrating immune infiltration and predicting therapeutic efficacy in colon adenocarcinoma: an integrated bioinformatic analysis with preliminarily experimental validation |
| title_sort | implication of necroptosis related lncrnas in orchestrating immune infiltration and predicting therapeutic efficacy in colon adenocarcinoma an integrated bioinformatic analysis with preliminarily experimental validation |
| topic | necroptosis-related genes and lncRNAs colon adenocarcinoma stemness bioinformatic analysis and experimental validation immune infiltration |
| url | https://www.frontiersin.org/articles/10.3389/fgene.2023.1170640/full |
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