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Wang C, Liu X, Nov P, Li L, Li C, Liao X, Li L, Du K, Li J. A signature based on circadian rhythm-associated genes for the evaluation of prognosis and the tumour microenvironment in HNSCC. Sci Rep 2024; 14:7594. [PMID: 38556542 PMCID: PMC10982303 DOI: 10.1038/s41598-024-57160-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/26/2022] [Accepted: 03/13/2024] [Indexed: 04/02/2024] Open
Abstract
The morbidity and mortality rates of head and neck squamous cell carcinoma (HNSCC) remain high worldwide. Therefore, there is an urgent need to identify a new prognostic biomarker to guide the personalized treatment of HNSCC patients. Increasing evidence suggests that circadian rhythm genes play an important role in the development and progression of cancer. We aimed to explore the value of circadian rhythm genes in predicting prognosis and guiding the treatment of HNSCC. We first obtained a list of circadian rhythm genes from previous research. The sequencing data were retrieved from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. Finally, univariate Cox proportional hazard analysis, least absolute shrinkage and selection operator (LASSO) regression, and multivariate Cox proportional hazard analysis were performed to develop a prognostic signature (Circadian Rhythm-Related Gene Prognostic Index, CRRGPI) consisting of nine circadian rhythm genes. The signature exhibited good performance in predicting overall survival. Patients with low CRRGPI scores had lower metabolic activities and an active antitumour immunity ability. Additionally, a clinical cohort was used to further evaluate the ability of the CRRGPI to predict the efficacy of immune checkpoint inhibitors. In conclusion, the novel circadian rhythm-related gene signature can provide a precise prognostic evaluation with the potential capacity to guide individualized treatment regimens for HNSCC patients.
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Affiliation(s)
- Changqian Wang
- Department of Radiation Oncology, Oncology Center, Zhujiang Hospital of Southern Medical University, Guangzhou, 510282, Guangdong Province, China
- Department of Oncology, Shenzhen Hospital of Southern Medical University, Shenzhen, China
| | - Xiang Liu
- Department of Radiation Oncology, Oncology Center, Zhujiang Hospital of Southern Medical University, Guangzhou, 510282, Guangdong Province, China
| | - Pengkhun Nov
- Department of Radiation Oncology, Oncology Center, Zhujiang Hospital of Southern Medical University, Guangzhou, 510282, Guangdong Province, China
| | - Lilin Li
- Department of Radiation Oncology, Oncology Center, Zhujiang Hospital of Southern Medical University, Guangzhou, 510282, Guangdong Province, China
| | - Chunhui Li
- Department of Radiation Oncology, Oncology Center, Zhujiang Hospital of Southern Medical University, Guangzhou, 510282, Guangdong Province, China
| | - Xuejiao Liao
- Department of Radiation Oncology, Oncology Center, Zhujiang Hospital of Southern Medical University, Guangzhou, 510282, Guangdong Province, China
| | - Luyao Li
- Department of Radiation Oncology, Oncology Center, Zhujiang Hospital of Southern Medical University, Guangzhou, 510282, Guangdong Province, China
| | - Kunpeng Du
- Department of Radiation Oncology, Oncology Center, Zhujiang Hospital of Southern Medical University, Guangzhou, 510282, Guangdong Province, China.
| | - Jiqiang Li
- Department of Radiation Oncology, Oncology Center, Zhujiang Hospital of Southern Medical University, Guangzhou, 510282, Guangdong Province, China.
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Wang Q, Zhao Y, Wang F, Tan G. Clustering and machine learning-based integration identify cancer associated fibroblasts genes’ signature in head and neck squamous cell carcinoma. Front Genet 2023; 14:1111816. [PMID: 37065499 PMCID: PMC10098459 DOI: 10.3389/fgene.2023.1111816] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/30/2022] [Accepted: 03/16/2023] [Indexed: 04/03/2023] Open
Abstract
Background: A hallmark signature of the tumor microenvironment in head and neck squamous cell carcinoma (HNSCC) is abundantly infiltration of cancer-associated fibroblasts (CAFs), which facilitate HNSCC progression. However, some clinical trials showed targeted CAFs ended in failure, even accelerated cancer progression. Therefore, comprehensive exploration of CAFs should solve the shortcoming and facilitate the CAFs targeted therapies for HNSCC.Methods: In this study, we identified two CAFs gene expression patterns and performed the single‐sample gene set enrichment analysis (ssGSEA) to quantify the expression and construct score system. We used multi-methods to reveal the potential mechanisms of CAFs carcinogenesis progression. Finally, we integrated 10 machine learning algorithms and 107 algorithm combinations to construct most accurate and stable risk model. The machine learning algorithms contained random survival forest (RSF), elastic network (Enet), Lasso, Ridge, stepwise Cox, CoxBoost, partial least squares regression for Cox (plsRcox), supervised principal components (SuperPC), generalised boosted regression modelling (GBM), and survival support vector machine (survival-SVM).Results: There are two clusters present with distinct CAFs genes pattern. Compared to the low CafS group, the high CafS group was associated with significant immunosuppression, poor prognosis, and increased prospect of HPV negative. Patients with high CafS also underwent the abundant enrichment of carcinogenic signaling pathways such as angiogenesis, epithelial mesenchymal transition, and coagulation. The MDK and NAMPT ligand–receptor cellular crosstalk between the cancer associated fibroblasts and other cell clusters may mechanistically cause immune escape. Moreover, the random survival forest prognostic model that was developed from 107 machine learning algorithm combinations could most accurately classify HNSCC patients.Conclusion: We revealed that CAFs would cause the activation of some carcinogenesis pathways such as angiogenesis, epithelial mesenchymal transition, and coagulation and revealed unique possibilities to target glycolysis pathways to enhance CAFs targeted therapy. We developed an unprecedentedly stable and powerful risk score for assessing the prognosis. Our study contributes to the understanding of the CAFs microenvironment complexity in patients with head and neck squamous cell carcinoma and serves as a basis for future in-depth CAFs gene clinical exploration.
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Affiliation(s)
- Qiwei Wang
- Department of Otolaryngology Head and Neck Surgery, Third Xiangya Hospital, Central South University, Changsha, Hunan, China
| | - Yinan Zhao
- Xiangya School of Nursing, Central South University, Changsha, Hunan, China
| | - Fang Wang
- Department of Otorhinolaryngology/Head and Neck Surgery, University Hospital Rechts der Isar, Technical University of Munich, Munich, Bavaria, Germany
| | - Guolin Tan
- Third Xiangya Hospital, Central South University, Changsha, China
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He L, Liang M, Guo W, Liu J, Yu Y. HOXA1 is a radioresistance marker in multiple cancer types. Front Oncol 2022; 12:965427. [PMID: 36119466 PMCID: PMC9478604 DOI: 10.3389/fonc.2022.965427] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/09/2022] [Accepted: 08/15/2022] [Indexed: 11/13/2022] Open
Abstract
Radiotherapy is an important therapeutic method for patients with cancer. However, radioresistance can cause treatment failure. Thus, there is an urgent need to investigate mechanisms of radioresistance and identity markers that could be used to predict radioresistance and prognosis of post-radiotherapy cancer patients. In the present study, we propose HOXA1 as a candidate biomarker of intrinsic radioresistance in multiple cancer types. By analyzing data from The Cancer Genome Atlas (TCGA), we found that HOXA1 was aberrantly upregulated in multiple cancers, and that elevated HOXA1 was significantly associated with poor prognosis of post-radiotherapy head and neck squamous cell carcinoma (HNSCC) and low-grade glioma (LGG) patients. Correlation analysis showed that HOXA1 expression was positively correlated with expression of EGFR, CDK6, and CAV1, which have been reported to enhance radioresistance. In addition, gene set enrichment analysis (GSEA) showed that the oxidative phosphorylation gene set was negatively enriched in HOXA1 high-expression samples in both HNSCC and LGG. Moreover, immunohistochemical assays indicated that high HOXA1 expression was significantly correlated with a high recurrence rate of nasopharyngeal carcinoma (NPC) after radiotherapy. Further in vitro experiments demonstrated that HOXA1 knockdown markedly attenuated the DNA repair capacity of NPC cells and sensibilized NPC cells to irradiation. Taken together, the results of this study demonstrate that HOXA1 has potential to be a predictive marker for radioresistance and post-radiotherapy prognosis that could help to guide individualized treatment in multiple cancer types.
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Affiliation(s)
- Lu He
- Department of Radiotherapy, Affiliated Cancer Hospital and Institute of Guangzhou Medical University, Guangzhou, China
| | - Min Liang
- Department of Oncology, The Fifth Affiliated Hospital of Guangzhou Medical University, Guangzhou Medical University, Guangzhou, China
- Key Laboratory of Biological Targeting Diagnosis, Therapy and Rehabilitation of Guangdong Higher Education Institutes, The Fifth Affiliated Hospital of Guangzhou Medical University, Guangzhou, China
| | - Weisheng Guo
- Department of Radiotherapy, Affiliated Cancer Hospital and Institute of Guangzhou Medical University, Guangzhou, China
| | - Jinquan Liu
- Department of Radiotherapy, Affiliated Cancer Hospital and Institute of Guangzhou Medical University, Guangzhou, China
- *Correspondence: Yi Yu, ; Jinquan Liu,
| | - Yi Yu
- Department of Radiotherapy, Affiliated Cancer Hospital and Institute of Guangzhou Medical University, Guangzhou, China
- *Correspondence: Yi Yu, ; Jinquan Liu,
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Shen Y, Huang Q, Zhang Y, Hsueh CY, Zhou L. A novel signature derived from metabolism-related genes GPT and SMS to predict prognosis of laryngeal squamous cell carcinoma. Cancer Cell Int 2022; 22:226. [PMID: 35804447 PMCID: PMC9270735 DOI: 10.1186/s12935-022-02647-2] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/30/2022] [Accepted: 06/28/2022] [Indexed: 12/30/2022] Open
Abstract
Background A growing body of evidence has suggested the involvement of metabolism in the occurrence and development of tumors. But the link between metabolism and laryngeal squamous cell carcinoma (LSCC) has rarely been reported. This study seeks to understand and explain the role of metabolic biomarkers in predicting the prognosis of LSCC. Methods We identified the differentially expressed metabolism-related genes (MRGs) through RNA-seq data of The Cancer Genome Atlas (TCGA) and Gene set enrichment analysis (GSEA). After the screening of protein–protein interaction (PPI), hub MRGs were analyzed by least absolute shrinkage and selection operator (LASSO) and Cox regression analyses to construct a prognostic signature. Kaplan–Meier survival analysis and the receiver operating characteristic (ROC) was applied to verify the effectiveness of the prognostic signature in four cohorts (TCGA cohort, GSE27020 cohort, TCGA-sub1 cohort and TCGA-sub2 cohort). The expressions of the hub MRGs in LSCC cell lines and clinical samples were verified by quantitative reverse transcriptase PCR (qRT-PCR). The immunofluorescence staining of the tissue microarray (TMA) was carried out to further verify the reliability and validity of the prognostic signature. Cox regression analysis was then used to screen for independent prognostic factors of LSCC and a nomogram was constructed based on the results. Results Among the 180 differentially expressed MRGs, 14 prognostic MRGs were identified. A prognostic signature based on two MRGs (GPT and SMS) was then constructed and verified via internal and external validation cohorts. Compared to the adjacent normal tissues, SMS expression was higher while GPT expression was lower in LSCC tissues, indicating poorer outcomes. The prognostic signature was proven as an independent risk factor for LSCC in both internal and external validation cohorts. A nomogram based on these results was developed for clinical application. Conclusions Differentially expressed MRGs were found and proven to be related to the prognosis of LSCC. We constructed a novel prognostic signature based on MRGs in LSCC for the first time and verified it via different cohorts from both databases and clinical samples. A nomogram based on this prognostic signature was developed. Supplementary Information The online version contains supplementary material available at 10.1186/s12935-022-02647-2.
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Affiliation(s)
- Yujie Shen
- Department of Otorhinolaryngology, Eye & ENT Hospital, Fudan University, Shanghai, 200031, China
| | - Qiang Huang
- Department of Otorhinolaryngology, Eye & ENT Hospital, Fudan University, Shanghai, 200031, China
| | - Yifan Zhang
- Department of Otorhinolaryngology, Eye & ENT Hospital, Fudan University, Shanghai, 200031, China
| | - Chi-Yao Hsueh
- Department of Otorhinolaryngology, Eye & ENT Hospital, Fudan University, Shanghai, 200031, China.
| | - Liang Zhou
- Department of Otorhinolaryngology, Eye & ENT Hospital, Fudan University, Shanghai, 200031, China.
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Xu S, Zhou Y, Luo J, Chen S, Xie J, Liu H, Wang Y, Li Z. Integrated Analysis of a Ferroptosis-Related LncRNA Signature for Evaluating the Prognosis of Patients with Colorectal Cancer. Genes (Basel) 2022; 13:1094. [PMID: 35741856 PMCID: PMC9223081 DOI: 10.3390/genes13061094] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/02/2022] [Revised: 06/15/2022] [Accepted: 06/15/2022] [Indexed: 12/18/2022] Open
Abstract
LncRNAs have been well known for their multiple functions in the tumorigenesis, development, and relapse of colorectal cancer (CRC). Accumulating studies demonstrated that the expression of lncRNAs can be regulated by ferroptosis, a biological process that has been revealed to suppress CRC progression. However, the functions and clinical implications of ferroptosis-associated lncRNAs in CRC remain largely unknown. We, herein, aim to construct a prognostic signature with ferroptosis-related lncRNAs for the prognostic estimation of CRC patients. Firstly, we identified the lncRNAs related to ferroptosis based on the RNA-Seq data of CRC from the TCGA database. The univariate and multivariate Cox analyses were then performed to establish a prognostic signature composed of eight ferroptosis-related lncRNAs (AL161729.4, AC010973.2, CCDC144NL-AS1, AC009549.1, LINC01857, AP003555.1, AC099850.3, and AC008494.3). Furthermore, we divided the CRC patients into high- and low-risk groups based on the signature and found the overall survival (OS) of patients in the high-risk group was significantly shorter than that in the low-risk group (p = 3.31 × 10-11). Moreover, the patients in the high-risk groups had shorter recurrence-free survival (RFS) (p = 6.5 × 10-3) and disease-free survival (DFS) (p = 4.27 × 10-4), as well as higher tumor recurrence rate. Additionally, we found that the oncogenic pathways were enriched in the high-risk group, whereas the ferroptosis pathway that probably repressed CRC development was enriched in the low-risk group. In summary, our signature may provide a theoretical foundation for not only accurate judgment for prognosis but also evaluation for recurrence and metastasis in CRC patients.
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Affiliation(s)
- Shaohua Xu
- Research Institute of Hunan University in Chongqing, Chongqing 401120, China; (S.X.); (Y.Z.)
- Hunan Provincial Key Laboratory of Medical Virology, Institute of Pathogen Biology and Immunology of College of Biology, Hunan University, Changsha 410082, China; (J.L.); (S.C.); (J.X.); (H.L.)
| | - Yanjie Zhou
- Research Institute of Hunan University in Chongqing, Chongqing 401120, China; (S.X.); (Y.Z.)
- Hunan Provincial Key Laboratory of Medical Virology, Institute of Pathogen Biology and Immunology of College of Biology, Hunan University, Changsha 410082, China; (J.L.); (S.C.); (J.X.); (H.L.)
| | - Junyun Luo
- Hunan Provincial Key Laboratory of Medical Virology, Institute of Pathogen Biology and Immunology of College of Biology, Hunan University, Changsha 410082, China; (J.L.); (S.C.); (J.X.); (H.L.)
| | - Su Chen
- Hunan Provincial Key Laboratory of Medical Virology, Institute of Pathogen Biology and Immunology of College of Biology, Hunan University, Changsha 410082, China; (J.L.); (S.C.); (J.X.); (H.L.)
| | - Jiahui Xie
- Hunan Provincial Key Laboratory of Medical Virology, Institute of Pathogen Biology and Immunology of College of Biology, Hunan University, Changsha 410082, China; (J.L.); (S.C.); (J.X.); (H.L.)
| | - Hui Liu
- Hunan Provincial Key Laboratory of Medical Virology, Institute of Pathogen Biology and Immunology of College of Biology, Hunan University, Changsha 410082, China; (J.L.); (S.C.); (J.X.); (H.L.)
| | - Yirong Wang
- Bioinformatics Center, College of Biology, Hunan University, Changsha 410082, China
| | - Zhaoyong Li
- Research Institute of Hunan University in Chongqing, Chongqing 401120, China; (S.X.); (Y.Z.)
- Hunan Provincial Key Laboratory of Medical Virology, Institute of Pathogen Biology and Immunology of College of Biology, Hunan University, Changsha 410082, China; (J.L.); (S.C.); (J.X.); (H.L.)
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Liu P, Lin C, Liu Z, Zhu C, Lin Z, Xu D, Chen J, Huang Q, Li CY, Hou L, Pan JA, Liu X. Inhibition of ALG3 stimulates cancer cell immunogenic ferroptosis to potentiate immunotherapy. Cell Mol Life Sci 2022; 79:352. [PMID: 35676564 PMCID: PMC11072400 DOI: 10.1007/s00018-022-04365-4] [Citation(s) in RCA: 14] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/21/2022] [Revised: 04/27/2022] [Accepted: 05/10/2022] [Indexed: 12/21/2022]
Abstract
Immune checkpoint blockade therapy has drastically improved the prognosis of certain advanced-stage cancers. However, low response rates and immune-related adverse events remain important limitations. Here, we report that inhibiting ALG3, an a-1,3-mannosyltransferase involved in protein glycosylation in the endoplasmic reticulum (ER), can boost the response of tumors to immune checkpoint blockade therapy. Deleting N-linked glycosylation gene ALG3 in mouse cancer cells substantially attenuates their growth in mice in a manner depending on cytotoxic T cells. Furthermore, ALG3 inhibition or N-linked glycosylation inhibitor tunicamycin treatment synergizes with anti-PD1 therapy in suppressing tumor growth in mouse models of cancer. Mechanistically, we found that inhibiting ALG3 induced deficiencies of post-translational N-linked glycosylation modification and led to excessive lipid accumulation through sterol-regulated element-binding protein (SREBP1)-dependent lipogenesis in cancer cells. N-linked glycosylation deficiency-mediated lipid hyperperoxidation induced immunogenic ferroptosis of cancer cells and promoted a pro-inflammatory microenvironment, which boosted anti-tumor immune responses. In human subjects with cancer, elevated levels of ALG3 expression in tumor tissues are associated with poor patient survival. Taken together, we reveal an unappreciated role of ALG3 in regulating tumor immunogenicity and propose a potential therapeutic strategy for enhancing cancer immunotherapy.
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Affiliation(s)
- Pei Liu
- The Department of Biochemistry and Molecular Cell Biology, Molecular Cancer Research Center, School of Medicine, Sun Yat-Sen University, No. 66, Gongchang Rd, Shenzhen, 518107, Guangdong, China
| | - Cha Lin
- The Department of Biochemistry and Molecular Cell Biology, Molecular Cancer Research Center, School of Medicine, Sun Yat-Sen University, No. 66, Gongchang Rd, Shenzhen, 518107, Guangdong, China
| | - Zheyu Liu
- The Department of Biochemistry and Molecular Cell Biology, Molecular Cancer Research Center, School of Medicine, Sun Yat-Sen University, No. 66, Gongchang Rd, Shenzhen, 518107, Guangdong, China
| | - Chenchen Zhu
- The Department of Biochemistry and Molecular Cell Biology, Molecular Cancer Research Center, School of Medicine, Sun Yat-Sen University, No. 66, Gongchang Rd, Shenzhen, 518107, Guangdong, China
| | - Zhongda Lin
- The Department of Biochemistry and Molecular Cell Biology, Molecular Cancer Research Center, School of Medicine, Sun Yat-Sen University, No. 66, Gongchang Rd, Shenzhen, 518107, Guangdong, China
| | - Dan Xu
- The Department of Biochemistry and Molecular Cell Biology, Molecular Cancer Research Center, School of Medicine, Sun Yat-Sen University, No. 66, Gongchang Rd, Shenzhen, 518107, Guangdong, China
| | - Jian Chen
- The Department of Biochemistry and Molecular Cell Biology, Molecular Cancer Research Center, School of Medicine, Sun Yat-Sen University, No. 66, Gongchang Rd, Shenzhen, 518107, Guangdong, China
| | - Qian Huang
- Molecular Diagnostic Laboratory of Cancer Center, Shanghai General Hospital, Shanghai Jiaotong University School of Medicine, Shanghai, China
| | - Chuan-Yuan Li
- Department of Dermatology, Duke University Medical Center, Durham, NC, USA
| | - Linlin Hou
- The Department of Biochemistry and Molecular Cell Biology, Molecular Cancer Research Center, School of Medicine, Sun Yat-Sen University, No. 66, Gongchang Rd, Shenzhen, 518107, Guangdong, China
| | - Ji-An Pan
- The Department of Biochemistry and Molecular Cell Biology, Molecular Cancer Research Center, School of Medicine, Sun Yat-Sen University, No. 66, Gongchang Rd, Shenzhen, 518107, Guangdong, China
| | - Xinjian Liu
- The Department of Biochemistry and Molecular Cell Biology, Molecular Cancer Research Center, School of Medicine, Sun Yat-Sen University, No. 66, Gongchang Rd, Shenzhen, 518107, Guangdong, China.
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Xu S, Xie J, Zhou Y, Liu H, Wang Y, Li Z. Integrated Analysis of RNA Binding Protein-Related lncRNA Prognostic Signature for Breast Cancer Patients. Genes (Basel) 2022; 13:genes13020345. [PMID: 35205391 PMCID: PMC8872055 DOI: 10.3390/genes13020345] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/13/2022] [Revised: 02/05/2022] [Accepted: 02/10/2022] [Indexed: 12/19/2022] Open
Abstract
Long non-coding RNAs (lncRNAs) have been well known for their multiple functions in the tumorigenesis, development, and prognosis of breast cancer (BC). Mechanistically, their production, function, or stability can be regulated by RNA binding proteins (RBPs), which were also involved in the carcinogenesis and progression of BC. However, the roles and clinical implications of RBP-related lncRNAs in BC remain largely unknown. Therefore, we herein aim to construct a prognostic signature with RBP-relevant lncRNAs for the prognostic evaluation of BC patients. Firstly, based on the RNA sequencing data of female BC patients from The Cancer Genome Atlas (TCGA) database, we screened out 377 differentially expressed lncRNAs related to RBPs. The univariate, least absolute shrinkage and selection operator (LASSO), and multivariate Cox regression analyses were then performed to establish a prognostic signature composed of 12-RBP-related lncRNAs. Furthermore, we divided the BC patients into high- and low-risk groups by the prognostic signature and found the overall survival (OS) of patients in the high-risk group was significantly shorter than that of the low-risk group. Moreover, the 12-lncRNA signature exhibited independence in evaluating the prognosis of BC patients. Additionally, a functional enrichment analysis revealed that the prognostic signature was associated with some cancer-relevant pathways, including cell cycle and immunity. In summary, our 12-lncRNA signature may provide a theoretical reference for the prognostic evaluation or clinical treatment of BC patients.
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Affiliation(s)
- Shaohua Xu
- Hunan Provincial Key Laboratory of Medical Virology, Institute of Pathogen Biology and Immunology, College of Biology, Hunan University, Changsha 410082, China; (S.X.); (J.X.); (Y.Z.); (H.L.)
| | - Jiahui Xie
- Hunan Provincial Key Laboratory of Medical Virology, Institute of Pathogen Biology and Immunology, College of Biology, Hunan University, Changsha 410082, China; (S.X.); (J.X.); (Y.Z.); (H.L.)
| | - Yanjie Zhou
- Hunan Provincial Key Laboratory of Medical Virology, Institute of Pathogen Biology and Immunology, College of Biology, Hunan University, Changsha 410082, China; (S.X.); (J.X.); (Y.Z.); (H.L.)
| | - Hui Liu
- Hunan Provincial Key Laboratory of Medical Virology, Institute of Pathogen Biology and Immunology, College of Biology, Hunan University, Changsha 410082, China; (S.X.); (J.X.); (Y.Z.); (H.L.)
| | - Yirong Wang
- Bioinformatics Center, College of Biology, Hunan University, Changsha 410082, China
- Correspondence: (Y.W.); (Z.L.)
| | - Zhaoyong Li
- Hunan Provincial Key Laboratory of Medical Virology, Institute of Pathogen Biology and Immunology, College of Biology, Hunan University, Changsha 410082, China; (S.X.); (J.X.); (Y.Z.); (H.L.)
- Research Institute of Hunan University in Chongqing, Chongqing 401120, China
- Correspondence: (Y.W.); (Z.L.)
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Chen H, Zu F, Zeng T, Chen Z, Wei J, Liu P, Li Z, Zhou L, Wang H, Tan H, Tan X. Prognostic Value and Correlation With Tumor Immune Infiltration of a Novel Metabolism-Related Gene Signature in Pancreatic Cancer. Front Oncol 2022; 11:757791. [PMID: 35127473 PMCID: PMC8807690 DOI: 10.3389/fonc.2021.757791] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/12/2021] [Accepted: 12/20/2021] [Indexed: 12/13/2022] Open
Abstract
Background Energy metabolism has been considered as one of the novel features of neoplasms. This study aimed to establish the prognostic signature for pancreatic cancer (PC) based on metabolism-related genes (MRGs). Methods We obtained MRGs from the Molecular Signatures Database (MSigDB) and gene sequence data in the Cancer Genome Atlas (TCGA) databases. Then, differentially expressed MRGs (DE-MRGs) were identified utilizing the R software. We built the prognostic model via multivariate Cox regression. Moreover, external validation of the prognostic signature was also performed. Nomogram was created to predict the overall survival (OS). Next, this study analyzed the prognostic value, clinical relationship, and metabolism-related signaling pathways of the prognostic signature. The role in tumor infiltration was further evaluated. Eventually, the expression level of the three MRGs along with the function of NT5E was validated. Results Twenty-two MRGs were chosen, eight of which were identified to be most significantly correlated with the prognosis of PC. Meanwhile, a 3-MRG prognostic signature was established, and we verified this prognostic model in two separate external cohorts. What is more, the nomogram was used to predict 1-/2-/3-year OS of PC patients. In addition, the immune cell infiltration and expression of immune checkpoint were significantly influenced by the risk score. Finally, three MRGs were highly expressed in PC cell lines, and NT5E was associated with the proliferation and migration ability of PC. Conclusion To sum up, the study established and validated a 3-MRG prognostic signature for PC, and the signature could be utilized to predict the prognosis and assist the individualized clinical management of patients with PC.
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Affiliation(s)
- Hui Chen
- General Surgery, Department of Pancreatic and Thyroid Ward, Shengjing Hospital of China Medical University, Shenyang, China
| | - Fuqiang Zu
- General Surgery, Department of Pancreatic and Thyroid Ward, Shengjing Hospital of China Medical University, Shenyang, China
| | - Taofei Zeng
- General Surgery, Department of Hepatobiliary and Splenic Ward, Shengjing Hospital of China Medical University, Shenyang, China
| | - Ziang Chen
- Department of General Surgery, The Second Affiliated Hospital of Harbin Medical University, Harbin, China
| | - Jinhong Wei
- School of Basic Medical Sciences, Southwest Medical University, Luzhou, China
| | - Peng Liu
- General Surgery, Department of Pancreatic and Thyroid Ward, Shengjing Hospital of China Medical University, Shenyang, China
| | - Zeyu Li
- General Surgery, Department of Pancreatic and Thyroid Ward, Shengjing Hospital of China Medical University, Shenyang, China
| | - Lei Zhou
- General Surgery, Department of Pancreatic and Thyroid Ward, Shengjing Hospital of China Medical University, Shenyang, China
| | - Huaitao Wang
- General Surgery, Department of Pancreatic and Thyroid Ward, Shengjing Hospital of China Medical University, Shenyang, China
| | - Hao Tan
- General Surgery, Department of Pancreatic and Endocrine Ward, Shengjing Hospital of China Medical University, Shenyang, China
| | - Xiaodong Tan
- General Surgery, Department of Pancreatic and Thyroid Ward, Shengjing Hospital of China Medical University, Shenyang, China
- *Correspondence: Xiaodong Tan,
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