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Integrated in silico analysis of LRP2 mutations to immunotherapy efficacy in pan-cancer cohort
PURPOSE: Immunotherapy has emerged as a novel therapy, while many patients are refractory. Although, several biomarkers have been identified as predictive biomarkers for immunotherapy, such as tumor specific genes, PD-1/PD-L1, tumor mutation burn (TMB), and microsatellite instability (MSI), results...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer US
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9283634/ https://www.ncbi.nlm.nih.gov/pubmed/35834061 http://dx.doi.org/10.1007/s12672-022-00528-8 |
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author | Li, Chunbo Ding, Yan Zhang, Xuyin Hua, Keqin |
author_facet | Li, Chunbo Ding, Yan Zhang, Xuyin Hua, Keqin |
author_sort | Li, Chunbo |
collection | PubMed |
description | PURPOSE: Immunotherapy has emerged as a novel therapy, while many patients are refractory. Although, several biomarkers have been identified as predictive biomarkers for immunotherapy, such as tumor specific genes, PD-1/PD-L1, tumor mutation burn (TMB), and microsatellite instability (MSI), results remain unsatisfactory. The aim of this study is to evaluate the value of LRP2 mutations in predicating cancer immunotherapy. METHODS: We investigated the characteristics of low-density lipoprotein receptor-related protein 2 (LRP2) mutation in the cancer genome atlas (TCGA) and explored the potential association of LRP2 mutations with immunotherapy. Characteristics of LRP2 mutations in 33 cancer types were analyzed using large-scale public data. The association of LRP2 mutations with immune cell infiltration and immunotherapy efficacy was evaluated. Finally, a LPR2 mutation signature (LMS) was developed and validated by TCGA-UCEC and pan-cancer cohorts. Furthermore, we demonstrated the predictive power of LMS score in independent immunotherapy cohorts by performing a meta-analysis. RESULTS: Our results revealed that patients with LRP2 mutant had higher TMB and MSI compared with patients without LRP2 mutations. LRP2 mutations were associated with high levels of immune cells infiltration, immune-related genes expression and enrichment of immune related signaling pathways. Importantly, LRP2-mutated patients had a long overall survival (OS) after immunotherapy. In the endometrial cancer (EC) cohort, we found that patients with LRP2 mutations belonged to the POLE and MSI-H type and had a better prognosis. Finally, we developed a LRP2 mutations signature (LMS), that was significantly associated with prognosis in patients receiving immunotherapy. CONCLUSION: These results indicated that LRP2 mutations can serve as a biomarker for personalized tumor immunotherapy. Importantly, LMS is a potential predictor of patients’ prognosis after immunotherapy. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s12672-022-00528-8. |
format | Online Article Text |
id | pubmed-9283634 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Springer US |
record_format | MEDLINE/PubMed |
spelling | pubmed-92836342022-07-16 Integrated in silico analysis of LRP2 mutations to immunotherapy efficacy in pan-cancer cohort Li, Chunbo Ding, Yan Zhang, Xuyin Hua, Keqin Discov Oncol Research PURPOSE: Immunotherapy has emerged as a novel therapy, while many patients are refractory. Although, several biomarkers have been identified as predictive biomarkers for immunotherapy, such as tumor specific genes, PD-1/PD-L1, tumor mutation burn (TMB), and microsatellite instability (MSI), results remain unsatisfactory. The aim of this study is to evaluate the value of LRP2 mutations in predicating cancer immunotherapy. METHODS: We investigated the characteristics of low-density lipoprotein receptor-related protein 2 (LRP2) mutation in the cancer genome atlas (TCGA) and explored the potential association of LRP2 mutations with immunotherapy. Characteristics of LRP2 mutations in 33 cancer types were analyzed using large-scale public data. The association of LRP2 mutations with immune cell infiltration and immunotherapy efficacy was evaluated. Finally, a LPR2 mutation signature (LMS) was developed and validated by TCGA-UCEC and pan-cancer cohorts. Furthermore, we demonstrated the predictive power of LMS score in independent immunotherapy cohorts by performing a meta-analysis. RESULTS: Our results revealed that patients with LRP2 mutant had higher TMB and MSI compared with patients without LRP2 mutations. LRP2 mutations were associated with high levels of immune cells infiltration, immune-related genes expression and enrichment of immune related signaling pathways. Importantly, LRP2-mutated patients had a long overall survival (OS) after immunotherapy. In the endometrial cancer (EC) cohort, we found that patients with LRP2 mutations belonged to the POLE and MSI-H type and had a better prognosis. Finally, we developed a LRP2 mutations signature (LMS), that was significantly associated with prognosis in patients receiving immunotherapy. CONCLUSION: These results indicated that LRP2 mutations can serve as a biomarker for personalized tumor immunotherapy. Importantly, LMS is a potential predictor of patients’ prognosis after immunotherapy. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s12672-022-00528-8. Springer US 2022-07-14 /pmc/articles/PMC9283634/ /pubmed/35834061 http://dx.doi.org/10.1007/s12672-022-00528-8 Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . |
spellingShingle | Research Li, Chunbo Ding, Yan Zhang, Xuyin Hua, Keqin Integrated in silico analysis of LRP2 mutations to immunotherapy efficacy in pan-cancer cohort |
title | Integrated in silico analysis of LRP2 mutations to immunotherapy efficacy in pan-cancer cohort |
title_full | Integrated in silico analysis of LRP2 mutations to immunotherapy efficacy in pan-cancer cohort |
title_fullStr | Integrated in silico analysis of LRP2 mutations to immunotherapy efficacy in pan-cancer cohort |
title_full_unstemmed | Integrated in silico analysis of LRP2 mutations to immunotherapy efficacy in pan-cancer cohort |
title_short | Integrated in silico analysis of LRP2 mutations to immunotherapy efficacy in pan-cancer cohort |
title_sort | integrated in silico analysis of lrp2 mutations to immunotherapy efficacy in pan-cancer cohort |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9283634/ https://www.ncbi.nlm.nih.gov/pubmed/35834061 http://dx.doi.org/10.1007/s12672-022-00528-8 |
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