Comprehensive prognostic and immune analysis of a glycosylation related risk model in pancreatic cancer
Abstract Background Pancreatic cancer (PC) is a malignant tumor with extremely poor prognosis, exhibiting resistance to chemotherapy and immunotherapy. Nowadays, it is ranked as the third leading cause of cancer-related mortality. Glycation is a common epigenetic modification that occurs during the...
| Main Authors: | , , , , , , , , , |
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| Format: | Article |
| Language: | English |
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BMC
2023-12-01
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| Series: | BMC Cancer |
| Subjects: | |
| Online Access: | https://doi.org/10.1186/s12885-023-11725-1 |
| _version_ | 1797388279695278080 |
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| author | XueAng Liu Jian Shi Lei Tian Bin Xiao Kai Zhang Yan Zhu YuFeng Zhang KuiRong Jiang Yi Zhu Hao Yuan |
| author_facet | XueAng Liu Jian Shi Lei Tian Bin Xiao Kai Zhang Yan Zhu YuFeng Zhang KuiRong Jiang Yi Zhu Hao Yuan |
| author_sort | XueAng Liu |
| collection | DOAJ |
| description | Abstract Background Pancreatic cancer (PC) is a malignant tumor with extremely poor prognosis, exhibiting resistance to chemotherapy and immunotherapy. Nowadays, it is ranked as the third leading cause of cancer-related mortality. Glycation is a common epigenetic modification that occurs during the tumor transformation. Many studies have demonstrated a strong correlation between glycation modification and tumor progression. However, the expression status of glycosylation-related genes (GRGs) in PC and their potential roles in PC microenvironment have not been extensively investigated. Method We systematically integrated RNA sequencing data and clinicopathological parameters of PC patients from TCGA and GTEx databases. A GRGs risk model based on glycosylation related genes was constructed and validated in 60 patients from Pancreatic biobank via RT-PCR. R packages were used to analyze the relationships between GRGs risk scores and overall survival (OS), tumor microenvironment, immune checkpoint, chemotherapy drug sensitivity and tumor mutational load in PC patients. Panoramic analysis was performed on PC tissues. The function of B3GNT8 in PC was detected via in vitro experiments. Results In this study, we found close correlations between GRGs risk model and PC patients’ overall survival and tumor microenvironment. Multifaceted predictions demonstrated the low-risk cohort exhibits superior OS compared to high-risk counterparts. Meanwhile, the low-risk group was characterized by high immune infiltration and may be more sensitive to immunotherapy or chemotherapy. Panoramic analysis was further confirmed a significant relationship between the GRGs risk score and both the distribution of PC tumor cells as well as CD8 + T cell infiltration. In addition, we also identified a unique glycosylation gene B3GNT8, which could suppress PC progression in vitro and in vivo. Conclusion We established a GRGs risk model, which could predict prognosis and immune infiltration in PC patients. This risk model may provide a new tool for PC precision treatment. |
| first_indexed | 2024-03-08T22:38:32Z |
| format | Article |
| id | doaj.art-9222b951da4341ebac6925d9b4044e02 |
| institution | Directory Open Access Journal |
| issn | 1471-2407 |
| language | English |
| last_indexed | 2024-03-08T22:38:32Z |
| publishDate | 2023-12-01 |
| publisher | BMC |
| record_format | Article |
| series | BMC Cancer |
| spelling | doaj.art-9222b951da4341ebac6925d9b4044e022023-12-17T12:20:25ZengBMCBMC Cancer1471-24072023-12-0123112010.1186/s12885-023-11725-1Comprehensive prognostic and immune analysis of a glycosylation related risk model in pancreatic cancerXueAng Liu0Jian Shi1Lei Tian2Bin Xiao3Kai Zhang4Yan Zhu5YuFeng Zhang6KuiRong Jiang7Yi Zhu8Hao Yuan9Pancreas Center, The First Affiliated Hospital of Nanjing Medical UniversityPancreas Center, The First Affiliated Hospital of Nanjing Medical UniversityPancreas Center, The First Affiliated Hospital of Nanjing Medical UniversityPancreas Center, The First Affiliated Hospital of Nanjing Medical UniversityPancreas Center, The First Affiliated Hospital of Nanjing Medical UniversityDepartment of Pathology, The First Affiliated Hospital of Nanjing Medical UniversityPancreas Institute of Nanjing Medical UniversityPancreas Center, The First Affiliated Hospital of Nanjing Medical UniversityPancreas Center, The First Affiliated Hospital of Nanjing Medical UniversityPancreas Center, The First Affiliated Hospital of Nanjing Medical UniversityAbstract Background Pancreatic cancer (PC) is a malignant tumor with extremely poor prognosis, exhibiting resistance to chemotherapy and immunotherapy. Nowadays, it is ranked as the third leading cause of cancer-related mortality. Glycation is a common epigenetic modification that occurs during the tumor transformation. Many studies have demonstrated a strong correlation between glycation modification and tumor progression. However, the expression status of glycosylation-related genes (GRGs) in PC and their potential roles in PC microenvironment have not been extensively investigated. Method We systematically integrated RNA sequencing data and clinicopathological parameters of PC patients from TCGA and GTEx databases. A GRGs risk model based on glycosylation related genes was constructed and validated in 60 patients from Pancreatic biobank via RT-PCR. R packages were used to analyze the relationships between GRGs risk scores and overall survival (OS), tumor microenvironment, immune checkpoint, chemotherapy drug sensitivity and tumor mutational load in PC patients. Panoramic analysis was performed on PC tissues. The function of B3GNT8 in PC was detected via in vitro experiments. Results In this study, we found close correlations between GRGs risk model and PC patients’ overall survival and tumor microenvironment. Multifaceted predictions demonstrated the low-risk cohort exhibits superior OS compared to high-risk counterparts. Meanwhile, the low-risk group was characterized by high immune infiltration and may be more sensitive to immunotherapy or chemotherapy. Panoramic analysis was further confirmed a significant relationship between the GRGs risk score and both the distribution of PC tumor cells as well as CD8 + T cell infiltration. In addition, we also identified a unique glycosylation gene B3GNT8, which could suppress PC progression in vitro and in vivo. Conclusion We established a GRGs risk model, which could predict prognosis and immune infiltration in PC patients. This risk model may provide a new tool for PC precision treatment.https://doi.org/10.1186/s12885-023-11725-1Pancreatic cancerCancer glycosylationPrognostic modelBioinformaticsB3GNT8 |
| spellingShingle | XueAng Liu Jian Shi Lei Tian Bin Xiao Kai Zhang Yan Zhu YuFeng Zhang KuiRong Jiang Yi Zhu Hao Yuan Comprehensive prognostic and immune analysis of a glycosylation related risk model in pancreatic cancer BMC Cancer Pancreatic cancer Cancer glycosylation Prognostic model Bioinformatics B3GNT8 |
| title | Comprehensive prognostic and immune analysis of a glycosylation related risk model in pancreatic cancer |
| title_full | Comprehensive prognostic and immune analysis of a glycosylation related risk model in pancreatic cancer |
| title_fullStr | Comprehensive prognostic and immune analysis of a glycosylation related risk model in pancreatic cancer |
| title_full_unstemmed | Comprehensive prognostic and immune analysis of a glycosylation related risk model in pancreatic cancer |
| title_short | Comprehensive prognostic and immune analysis of a glycosylation related risk model in pancreatic cancer |
| title_sort | comprehensive prognostic and immune analysis of a glycosylation related risk model in pancreatic cancer |
| topic | Pancreatic cancer Cancer glycosylation Prognostic model Bioinformatics B3GNT8 |
| url | https://doi.org/10.1186/s12885-023-11725-1 |
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