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Tan X, Li G, Deng H, Xiao G, Wang Y, Zhang C, Chen Y. Obesity enhances the response to neoadjuvant anti-PD1 therapy in oral tongue squamous cell carcinoma. Cancer Med 2024; 13:e7346. [PMID: 38923758 PMCID: PMC11194614 DOI: 10.1002/cam4.7346] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/30/2023] [Revised: 03/29/2024] [Accepted: 05/18/2024] [Indexed: 06/28/2024] Open
Abstract
OBJECTIVES Previous studies have demonstrated that obesity may impact the efficacy of anti-PD1 therapy, but the underlying mechanism remains unclear. In this study, our objective was to determine the prognostic value of obesity in patients with oral tongue squamous cell carcinoma (OTSCC) treated with pembrolizumab and establish a subtype based on fatty acid metabolism-related genes (FAMRGs) for immunotherapy. MATERIALS AND METHODS We enrolled a total of 56 patients with OTSCC who underwent neoadjuvant anti-PD1 therapy. Univariate and multivariate Cox regression analyses, Kaplan-Meier survival analysis, and immunohistochemistry staining were performed. Additionally, we acquired the gene expression profiles of pan-cancer samples and conducted GSEA and KEGG pathway analysis. Moreover, data from TCGA, MSigDB, UALCAN, GEPIA and TIMER were utilized to construct the FAMRGs subtype. RESULTS Our findings indicate that high Body Mass Index (BMI) was significantly associated with improved PFS (HR = 0.015; 95% CI, 0.001 to 0.477; p = 0.015), potentially attributed to increased infiltration of PD1 + T cells. A total of 91 differentially expressed FAMRGs were identified between the response and non-response groups in pan-cancer patients treated with immunotherapy. Of these, 6 hub FAMRGs (ACSL5, PLA2G2D, PROCA1, IL4I1, UBE2L6 and PSME1) were found to affect PD-1 expression and T cell infiltration in HNSCC, which may impact the efficacy of anti-PD1 therapy. CONCLUSION This study demonstrates that obesity serves as a robust prognostic predictor for patients with OTSCC undergoing neoadjuvant anti-PD1 therapy. Furthermore, the expression of 6 hub FAMRGs (ACSL5, PLA2G2D, PROCA1, IL4I1, UBE2L6 and PSME1) plays a pivotal role in the context of anti-PD1 therapy and deserves further investigation.
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Affiliation(s)
- Xiyan Tan
- State Key Laboratory of Oncology in South China, Guangdong Provincial Clinical Research Center for CancerSun Yat‐sen University Cancer CenterGuangzhouP.R. China
- Department of Head and Neck SurgerySun Yat‐sen University Cancer CenterGuangzhouP.R. China
| | - Guoli Li
- State Key Laboratory of Oncology in South China, Guangdong Provincial Clinical Research Center for CancerSun Yat‐sen University Cancer CenterGuangzhouP.R. China
- Department of Head and Neck SurgerySun Yat‐sen University Cancer CenterGuangzhouP.R. China
| | - Honghao Deng
- State Key Laboratory of Oncology in South China, Guangdong Provincial Clinical Research Center for CancerSun Yat‐sen University Cancer CenterGuangzhouP.R. China
- Department of Head and Neck SurgerySun Yat‐sen University Cancer CenterGuangzhouP.R. China
| | - Guoming Xiao
- State Key Laboratory of Oncology in South China, Guangdong Provincial Clinical Research Center for CancerSun Yat‐sen University Cancer CenterGuangzhouP.R. China
- Department of Head and Neck SurgerySun Yat‐sen University Cancer CenterGuangzhouP.R. China
| | - Yaqin Wang
- State Key Laboratory of Oncology in South China, Guangdong Provincial Clinical Research Center for CancerSun Yat‐sen University Cancer CenterGuangzhouP.R. China
- Department of Radiation OncologySun Yat‐sen University Cancer CenterGuangzhouP.R. China
| | - Chenzhi Zhang
- State Key Laboratory of Oncology in South China, Guangdong Provincial Clinical Research Center for CancerSun Yat‐sen University Cancer CenterGuangzhouP.R. China
- Department of Colorectal SurgerySun Yat‐sen University Cancer CenterGuangzhouP.R. China
| | - Yanfeng Chen
- State Key Laboratory of Oncology in South China, Guangdong Provincial Clinical Research Center for CancerSun Yat‐sen University Cancer CenterGuangzhouP.R. China
- Department of Head and Neck SurgerySun Yat‐sen University Cancer CenterGuangzhouP.R. China
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刘 鹏, 娄 丽, 刘 霞, 王 建, 姜 颖. [A risk scoring model based on M2 macrophage-related genes for predicting prognosis of HBV-related hepatocellular carcinoma]. NAN FANG YI KE DA XUE XUE BAO = JOURNAL OF SOUTHERN MEDICAL UNIVERSITY 2024; 44:827-840. [PMID: 38862440 PMCID: PMC11166709 DOI: 10.12122/j.issn.1673-4254.2024.05.04] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Subscribe] [Scholar Register] [Received: 03/10/2024] [Indexed: 06/13/2024]
Abstract
OBJECTIVE To investigate the prognostic value of M2 macrophage-related genes (MRG) in hepatitis B virus (HBV)- related hepatocellular carcinoma (HCC). METHODS The transcriptome data of 73 patients with HBV-related HCC were obtained from TCGA database, and the MRG modules were identified by WGCNA. The MRG-based risk scoring model was constructed by LASSO regression analysis and validated using an external dataset. The correlation of the risk score with immune cell infiltration and drug sensitivity of HCC were analyzed with CIBERSORT and R. pRRophetic. The signaling pathways of the differential genes between the high- and low-risk groups were investigated using GSVA and GSEA enrichment analyses, and MRG expressions at the single cell level were validated using R.Seurat. The cell interaction intensity was analyzed by R.Cellchat to identify important cell types related to HCC progression. MRG expression levels were detected by RT-qPCR in THP-1 cells with HCC-conditioned medium-induced M2 polarization and in HBV-positive HCC cells. RESULTS A high M2 macrophage infiltration level was significantly correlated with a poor prognosis of HCC, and 5 hub MRG (VTN, GCLC, PARVB, TRIM27, and GMPR) were identified. The overall survival of HCC patients was significantly lower in the high-risk than in the low-risk group. The high- and the low-risk groups showed significant enrichment of M2 macrophages and na?ve B cells, respectively, and were sensitive to BI. 2536 and to AG. 014699, AKT. inhibitor. Ⅷ, AZD. 0530, AZD7762, and BMS. 708163, respectively. The proliferation-related and metabolism-related pathways were enriched in the high-risk group, where monocytes showed the most active cell interactions during HCC progression. VTN was significantly upregulated in HCC cell lines, while GCLC, PARVB, TRIM27, and GMPR were upregulated in M2 THP-1 cells. CONCLUSION The MRG-based risk scoring model can accurately predict the prognosis of HBV-related HCC and reveal the differences in tumor microenvironment to guide precision treatment of the patients.
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Leahy C, Osborne N, Shirota L, Rote P, Lee YK, Song BJ, Yin L, Zhang Y, Garcia V, Hardwick JP. The fatty acid omega hydroxylase genes (CYP4 family) in the progression of metabolic dysfunction-associated steatotic liver disease (MASLD): An RNA sequence database analysis and review. Biochem Pharmacol 2024:116241. [PMID: 38697309 DOI: 10.1016/j.bcp.2024.116241] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/14/2024] [Revised: 04/21/2024] [Accepted: 04/25/2024] [Indexed: 05/04/2024]
Abstract
Fatty acid omega hydroxylase P450s consist of enzymes that hydroxylate various chain-length saturated and unsaturated fatty acids (FAs) and bioactive eicosanoid lipids. The human cytochrome P450 gene 4 family (CYP4) consists of 12 members that are associated with several human diseases. However, their role in the progression of metabolic dysfunction-associated fatty liver disease (MASLD) remains largely unknown. It has long been thought that the induction of CYP4 family P450 during fasting and starvation prevents FA-related lipotoxicity through FA metabolism to dicarboxylic acids that are chain-shortened in peroxisomes and then transported to the mitochondria for complete oxidation. Several studies have revealed that peroxisome succinate transported to the mitochondria is used for gluconeogenesis during fasting and starvation, and recent evidence suggests that peroxisome acetate can be utilized for lipogenesis and lipid droplet formation as well as epigenetic modification of gene transcription. In addition, omega hydroxylation of the bioactive eicosanoid arachidonic acid to 20-Hydroxyeicosatetraenoic acid (20-HETE) is essential for activating the GPR75 receptor, leading to vasoconstriction and cell proliferation. Several mouse models of diet-induced MASLD have revealed the induction of selective CYP4A members and the suppression of CYP4F during steatosis and steatohepatitis, suggesting a critical metabolic role in the progression of fatty liver disease. Thus, to further investigate the functional roles of CYP4 genes, we analyzed the differential gene expression of 12 members of CYP4 gene family in datasets from the Gene Expression Omnibus (GEO) from patients with steatosis, steatohepatitis, fibrosis, cirrhosis, and hepatocellular carcinoma. We also observed the differential expression of various CYP4 genes in the progression of MASLD, indicating that different CYP4 members may have unique functional roles in the metabolism of specific FAs and eicosanoids at various stages of fatty liver disease. These results suggest that targeting selective members of the CYP4A family is a viable therapeutic approach for treating and managing MASLD.
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Affiliation(s)
- Charles Leahy
- Department of Integrative Medical Sciences Liver focus group, Northeast Ohio Medical University, 4209 State Route 44, Rootstown, OH 44272, USA
| | - Nicholas Osborne
- Department of Integrative Medical Sciences Liver focus group, Northeast Ohio Medical University, 4209 State Route 44, Rootstown, OH 44272, USA
| | - Leticia Shirota
- Department of Integrative Medical Sciences Liver focus group, Northeast Ohio Medical University, 4209 State Route 44, Rootstown, OH 44272, USA
| | - Paula Rote
- Department of Integrative Medical Sciences Liver focus group, Northeast Ohio Medical University, 4209 State Route 44, Rootstown, OH 44272, USA
| | - Yoon-Kwang Lee
- Department of Integrative Medical Sciences Liver focus group, Northeast Ohio Medical University, 4209 State Route 44, Rootstown, OH 44272, USA
| | - Byoung-Joon Song
- Section of Molecular Pharmacology and Toxicology, National Institute on Alcohol Abuse and Alcoholism, 9000 Rockville Pike, Bethesda, MD 20892, USA
| | - Liya Yin
- Department of Integrative Medical Sciences Liver focus group, Northeast Ohio Medical University, 4209 State Route 44, Rootstown, OH 44272, USA
| | - Yanqiao Zhang
- Department of Integrative Medical Sciences Liver focus group, Northeast Ohio Medical University, 4209 State Route 44, Rootstown, OH 44272, USA
| | - Victor Garcia
- Department of Pharmacology, New York Medical College, 15 Dana Road Science Building, Rm. 530, Valhalla, NY 10595, USA
| | - James P Hardwick
- Department of Integrative Medical Sciences Liver focus group, Northeast Ohio Medical University, 4209 State Route 44, Rootstown, OH 44272, USA.
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Li J, Wei Y, Liu J, Cheng S, Zhang X, Qiu H, Li J, He C. Integrative analysis of metabolism subtypes and identification of prognostic metabolism-related genes for glioblastoma. Biosci Rep 2024; 44:BSR20231400. [PMID: 38419527 DOI: 10.1042/bsr20231400] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/16/2023] [Revised: 02/01/2024] [Accepted: 02/28/2024] [Indexed: 03/02/2024] Open
Abstract
Increasing evidence has demonstrated that cancer cell metabolism is a critical factor in tumor development and progression; however, its role in glioblastoma (GBM) remains limited. In the present study, we classified GBM into three metabolism subtypes (MC1, MC2, and MC3) through cluster analysis of 153 GBM samples from the RNA-sequencing data of The Cancer Genome Atlas (TCGA) based on 2752 metabolism-related genes (MRGs). We further explored the prognostic value, metabolic signatures, immune infiltration, and immunotherapy sensitivity of the three metabolism subtypes. Moreover, the metabolism scoring model was established to quantify the different metabolic characteristics of the patients. Results showed that MC3, which is associated with a favorable survival outcome, had higher proportions of isocitrate dehydrogenase (IDH) mutations and lower tumor purity and proliferation. The MC1 subtype, which is associated with the worst prognosis, shows a higher number of segments and homologous recombination defects and significantly lower mRNA expression-based stemness index (mRNAsi) and epigenetic-regulation-based mRNAsi. The MC2 subtype has the highest T-cell exclusion score, indicating a high likelihood of immune escape. The results were validated using an independent dataset. Five MRGs (ACSL1, NDUFA2, CYP1B1, SLC11A1, and COX6B1) correlated with survival outcomes were identified based on metabolism-related co-expression module analysis. Laboratory-based validation tests further showed the expression of these MRGs in GBM tissues and how their expression influences cell function. The results provide a reference for developing clinical management approaches and treatments for GBM.
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Affiliation(s)
- Jiahui Li
- Department of Rehabilitation Medicine, The Affiliated Jiangsu Shengze Hospital of Nanjing Medical University, Suzhou, Jiangsu Province 215228, China
- Center of Rehabilitation Medicine, The First Affiliated Hospital of Nanjing Medical University, Nanjing, Jiangsu Province 210029, China
| | - Yutian Wei
- Neurovascular Center, Changhai Hospital, Naval Medical University, Shanghai, 200433, China
| | - Jiali Liu
- Center of Rehabilitation Medicine, The First Affiliated Hospital of Nanjing Medical University, Nanjing, Jiangsu Province 210029, China
| | - Shupeng Cheng
- Center of Rehabilitation Medicine, The First Affiliated Hospital of Nanjing Medical University, Nanjing, Jiangsu Province 210029, China
| | - Xia Zhang
- Center of Rehabilitation Medicine, Honghui Hospital, Xi'an Jiaotong University, Xi'an, Shanxi Province 710054, China
| | - Huaide Qiu
- Faculty of Rehabilitation Science, Nanjing Normal University of Special Education, Nanjing, Jiangsu Province 210038, China
| | - Jianan Li
- Center of Rehabilitation Medicine, The First Affiliated Hospital of Nanjing Medical University, Nanjing, Jiangsu Province 210029, China
| | - Chuan He
- Department of Rehabilitation Medicine, The Affiliated Jiangsu Shengze Hospital of Nanjing Medical University, Suzhou, Jiangsu Province 215228, China
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Zhang Z, Zhao C, Yang S, Lu W, Shi J. A novel lipid metabolism-based risk model associated with immunosuppressive mechanisms in diffuse large B-cell lymphoma. Lipids Health Dis 2024; 23:20. [PMID: 38254162 PMCID: PMC10801940 DOI: 10.1186/s12944-024-02017-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/08/2023] [Accepted: 01/12/2024] [Indexed: 01/24/2024] Open
Abstract
BACKGROUND The molecular diversity exhibited by diffuse large B-cell lymphoma (DLBCL) is a significant obstacle facing current precision therapies. However, scoring using the International Prognostic Index (IPI) is inadequate when fully predicting the development of DLBCL. Reprogramming lipid metabolism is crucial for DLBCL carcinogenesis and expansion, while a predictive approach derived from lipid metabolism-associated genes (LMAGs) has not yet been recognized for DLBCL. METHODS Gene expression profiles of DLBCL were generated using the Gene Expression Omnibus (GEO) and The Cancer Genome Atlas (TCGA) databases. The LASSO Cox regression was used to construct an effective predictive risk-scoring model for DLBCL patients. The Kaplan-Meier survival assessment was employed to compare a given risk score with the IPI score and its impact on the survival of DLBCL patients. Functional enrichment examination was performed utilizing the KEGG pathway. After identifying hub genes via single-sample GSEA (ssGSEA), immunohistochemical staining and immunofluorescence were performed on lymph node samples from control and DLBCL patients to confirm these identified genes. RESULTS Sixteen lipid metabolism- and survival-associated genes were identified to construct a prognostic risk-scoring approach. This model demonstrated robust performance over various datasets and emerged as an autonomous risk factor for predicting the development of DLBCL patients. The risk score could significantly distinguish the development of DLBCL patients from the low-risk and elevated-risk IPI classes. Results from the inhibitory immune-related pathways and lower immune scores suggested an immunosuppressive phenotype within the elevated-risk group. Three hub genes, MECR, ARSK, and RAN, were identified to be negatively correlated with activated CD8 T cells and natural killer T cells in the elevated-risk score class. Ultimately, it was determined that these three genes were expressed by lymphoma cells but not by T cells in clinical samples from DLBCL patients. CONCLUSION The risk level model derived from 16 lipid metabolism-associated genes represents a prognostic biomarker for DLBCL that is novel, robust, and may have an immunosuppressive role. It can compensate for the limitations of the IPI score in predicting overall survival and has potential clinical application value.
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Affiliation(s)
- Zhaoli Zhang
- Department of Hematology, Shanghai Ninth People's Hospital, Shanghai Jiaotong University School of Medicine, Shanghai, China
| | - Chong Zhao
- Department of Hematology, Shanghai Ninth People's Hospital, Shanghai Jiaotong University School of Medicine, Shanghai, China
| | - Shaoxin Yang
- Department of Hematology, Shanghai Ninth People's Hospital, Shanghai Jiaotong University School of Medicine, Shanghai, China
| | - Wei Lu
- Department of Hematology, Shanghai Ninth People's Hospital, Shanghai Jiaotong University School of Medicine, Shanghai, China.
| | - Jun Shi
- Department of Hematology, Shanghai Ninth People's Hospital, Shanghai Jiaotong University School of Medicine, Shanghai, China.
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Yu X, Xu C, Zou Y, Liu W, Xie Y, Wu C. A prognostic metabolism-related gene signature associated with the tumor immune microenvironment in neuroblastoma. Am J Cancer Res 2024; 14:253-273. [PMID: 38323276 PMCID: PMC10839309] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/21/2023] [Accepted: 01/15/2024] [Indexed: 02/08/2024] Open
Abstract
Neuroblastoma (NB) is the most prevalent malignant solid tumor in children. Tumor metabolism, including lipid, amino acid, and glucose metabolism, is intricately linked to the genesis and progression of tumors. This study aimed to establish a prognostic gene signature for NB patients, based on metabolism-related genes, and to investigate a treatment approach that could enhance the survival rate of high-risk NB patients. From the NB dataset GSE49710, we identified metabolism-related gene markers utilizing the "limma" R package and univariate Cox analysis combined with least absolute shrinkage and selection operator (LASSO) regression analysis. We explored the correlation between these gene markers and the overall survival of NB patients. Gene set enrichment analysis (GSEA) and single-sample GSEA algorithms were used to assess the differences in metabolism and immune status. Furthermore, we examined the association between metabolic subgroups and drug responsiveness. Concurrently, data downloaded from TARGET and MTAB were used for external verification. Using multicolor immunofluorescence and immunohistochemistry, we investigated the relationship between the lipid metabolism-related gene ELOVL6 with both the International Neuroblastoma Staging System classification of NB and survival rate. Finally, we explored the effect of high ELOVL6 expression on the immune microenvironment in NB using flow cytometry. We identified an eight-gene signature comprising metabolism-related genes in NB: ELOVL6, OSBPL9, RPL27A, HSD17B3, ACHE, AKR1C1, PIK3R1, and EPHX2. This panel effectively predicted disease-free survival, and was validated using an internal dataset from GSE49710 and two external datasets from the TARGET and MTAB databases. Moreover, our findings confirmed that ELOVL6 fosters an immunosuppressive microenvironment and contributes to the malignant progression in NB. The eight-gene signature is significant in predicting the prognosis of NB, effectively classifying patients into high- and low-risk groups. This classification may guide the development of innovative treatment strategies for these patients. Notably, the signature gene ELOVL6 markedly encourages an immunosuppressive microenvironment and malignant progression in NB.
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Affiliation(s)
- Xin Yu
- Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center for CancerTianjin, China
- Tianjin’s Clinical Research Center for CancerTianjin, China
- Key Laboratory of Cancer Immunology and BiotherapyTianjin, China
| | - Chao Xu
- Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center for CancerTianjin, China
- Tianjin’s Clinical Research Center for CancerTianjin, China
- Key Laboratory of Cancer Immunology and BiotherapyTianjin, China
- National Clinical Research Center for Cancer, Tianjin Cancer Hospital Airport HospitalTianjin, China
| | - Yiping Zou
- Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center for CancerTianjin, China
- Tianjin’s Clinical Research Center for CancerTianjin, China
- Key Laboratory of Cancer Immunology and BiotherapyTianjin, China
| | - Weishuai Liu
- Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center for CancerTianjin, China
- Tianjin’s Clinical Research Center for CancerTianjin, China
- Key Laboratory of Cancer Immunology and BiotherapyTianjin, China
| | - Yongjie Xie
- Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center for CancerTianjin, China
- Tianjin’s Clinical Research Center for CancerTianjin, China
- Key Laboratory of Cancer Immunology and BiotherapyTianjin, China
| | - Chao Wu
- Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center for CancerTianjin, China
- Tianjin’s Clinical Research Center for CancerTianjin, China
- Key Laboratory of Cancer Immunology and BiotherapyTianjin, China
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Liu Y, Liu S, Yan L, Zhang Q, Liu W, Huang X, Liu S. Contribution of m5C RNA Modification-Related Genes to Prognosis and Immunotherapy Prediction in Patients with Ovarian Cancer. Mediators Inflamm 2023; 2023:1400267. [PMID: 38022687 PMCID: PMC10661868 DOI: 10.1155/2023/1400267] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/12/2023] [Revised: 09/03/2023] [Accepted: 10/16/2023] [Indexed: 12/01/2023] Open
Abstract
Background 5-Methylcytosine (m5C) RNA modification is closely implicated in the occurrence of a variety of cancers. Here, we established a novel prognostic signature for ovarian cancer (OC) patients based on m5C RNA modification-related genes and explored the correlation between these genes with the tumor immune microenvironment. Methods Methylated-RNA immunoprecipitation sequencing helped us to identify candidate genes related to m5C RNA modification at first. Based on TCGA database, we screened the differentially expressed candidate genes related to the prognosis and constructed a prognostic model using LASSO Cox regression analyses. Notably, the accuracy of the model was evaluated by Kaplan-Meier analysis and receiver operator characteristic curves. Independent prognostic risk factors were investigated by Cox proportional hazard model. Furthermore, we also analyzed the biological functions and pathways involved in the signature. Finally, the immune response of the model was visualized in great detail. Results Totally, 2,493 candidate genes proved to be involved in m5C modification of RNA for OC. We developed a signature with prognostic value consisting of six m5C RNA modification-related genes. Specially, samples have been split into two cohorts with low- and high-risk scores according to the model, in which the low-risk OC patients exhibited dramatically better overall survival time than those with high-risk scores. Besides, not only was this model a prognostic factor independent of other clinical characteristics but it predicted the intensity of the immune response in OC. Significantly, the accuracy and availability of the signature were verified by ICGC database. Conclusions Our study bridged the gap between m5C RNA modification and the prognosis of OC and was expected to provide an effective breakthrough for immunotherapy in OC patients.
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Affiliation(s)
- Yibin Liu
- Department of Gynecology, The Second Hospital of Hebei Medical University, 215 Heping West Road, Shijiazhuang, Hebei 050011, China
| | - Shouze Liu
- Department of Gynecology, The Second Hospital of Hebei Medical University, 215 Heping West Road, Shijiazhuang, Hebei 050011, China
- Department of Gynecology III, Cangzhou Central Hospital, Cangzhou, Hebei 061000, China
| | - Lu Yan
- Department of Gynecology, The Second Hospital of Hebei Medical University, 215 Heping West Road, Shijiazhuang, Hebei 050011, China
| | - Qianqian Zhang
- Department of Gynecology and Obstetrics, Beijing Tsinghua Changgung Hospital, Beijing 102218, China
| | - Wenhua Liu
- Department of Pain, Cangzhou Hospital of Integrated TCM-WM Hebei, Cangzhou, Hebei 061001, China
| | - Xianghua Huang
- Department of Gynecology, The Second Hospital of Hebei Medical University, 215 Heping West Road, Shijiazhuang, Hebei 050011, China
| | - Shikai Liu
- Department of Gynecology III, Cangzhou Central Hospital, Cangzhou, Hebei 061000, China
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Wang Z, Tao P, Fan P, Wang J, Rong T, Hou Y, Zhou Y, Lu W, Hong L, Ma L, Zhang Y, Tong H. Insight of a lipid metabolism prognostic model to identify immune landscape and potential target for retroperitoneal liposarcoma. Front Immunol 2023; 14:1209396. [PMID: 37483592 PMCID: PMC10359070 DOI: 10.3389/fimmu.2023.1209396] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/20/2023] [Accepted: 06/20/2023] [Indexed: 07/25/2023] Open
Abstract
Introduction The exploration of lipid metabolism dysregulation may provide novel perspectives for retroperitoneal liposarcoma (RPLS). In our study, we aimed to investigate potential targets and facilitate further understanding of immune landscape in RPLS, through lipid metabolism-associated genes (LMAGs) based prognostic model. Methods Gene expression profiles and corresponding clinical information of 234 cases were enrolled from two public databases and the largest retroperitoneal tumor research center of East China, including cohort-TCGA (n=58), cohort-GSE30929 (n=92), cohort-FD (n=50), cohort-scRNA-seq (n=4) and cohort-validation (n=30). Consensus clustering analysis was performed to identify lipid metabolism-associated molecular subtypes (LMSs). A prognostic risk model containing 13 LMAGs was established using LASSO algorithm and multivariate Cox analysis in cohort-TCGA. ESTIMATE, CIBERSORT, XCELL and MCP analyses were performed to visualize the immune landscape. WGCNA was used to identify three hub genes among the 13 model LMAGs, and preliminarily validated in both cohort-GSE30929 and cohort-FD. Moreover, TIMER was used to visualize the correlation between antigen-presenting cells and potential targets. Finally, single-cell RNA-sequencing (scRNA-seq) analysis of four RPLS and multiplexed immunohistochemistry (mIHC) were performed in cohort-validation to validate the discoveries of bioinformatics analysis. Results LMS1 and LMS2 were characterized as immune-infiltrated and -excluded tumors, with significant differences in molecular features and clinical prognosis, respectively. Elongation of very long chain fatty acids protein 2 (ELOVL2), the enzyme that catalyzed the elongation of long chain fatty acids, involved in the maintenance of lipid metabolism and cellular homeostasis in normal cells, was identified and negatively correlated with antigen-presenting cells and identified as a potential target in RPLS. Furthermore, ELOVL2 was enriched in LMS2 with significantly lower immunoscore and unfavorable prognosis. Finally, a high-resolution dissection through scRNA-seq was performed in four RPLS, revealing the entire tumor ecosystem and validated previous findings. Discussion The LMS subgroups and risk model based on LMAGs proposed in our study were both promising prognostic classifications for RPLS. ELOVL2 is a potential target linking lipid metabolism to immune regulations against RPLS, specifically for patients with LMS2 tumors.
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Affiliation(s)
- Zhenyu Wang
- First Affiliated Hospital, Anhui University of Science and Technology, Huainan, China
| | - Ping Tao
- Department of Laboratory Medicine, Shanghai Traditional Chinese Medicine-Integrated Hospital, Shanghai University of Traditional Chinese Medicine, Shanghai, China
| | - Peidang Fan
- First Affiliated Hospital, Anhui University of Science and Technology, Huainan, China
| | - Jiongyuan Wang
- Department of General Surgery, Zhongshan Hospital, Fudan University, Shanghai, China
| | - Tao Rong
- First Affiliated Hospital, Anhui University of Science and Technology, Huainan, China
| | - Yingyong Hou
- Department of Pathology, Zhongshan Hospital, Fudan University, Shanghai, China
| | - Yuhong Zhou
- Department of Medical Oncology, Zhongshan Hospital, Fudan University, Shanghai, China
| | - Weiqi Lu
- Department of General Surgery, Zhongshan Hospital, Fudan University, Shanghai, China
| | - Liang Hong
- Department of General Surgery, Shanghai Fifth People’s Hospital, Fudan University, Shanghai, China
| | - Lijie Ma
- Department of General Surgery, Shanghai Fifth People’s Hospital, Fudan University, Shanghai, China
- Department of Liver Surgery, Renji Hospital, School of Medicine, Shanghai Jiaotong University, Shanghai, China
| | - Yong Zhang
- Department of General Surgery, Zhongshan Hospital, Fudan University, Shanghai, China
| | - Hanxing Tong
- Department of General Surgery, Zhongshan Hospital, Fudan University, Shanghai, China
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Fan X, Yang L, Qin W, Zou B, Fan B, Wang S, Wang L. Prophylactic cranial irradiation-related lymphopenia affects survival in patients with limited-stage small cell lung cancer. Heliyon 2023; 9:e16483. [PMID: 37251477 PMCID: PMC10220366 DOI: 10.1016/j.heliyon.2023.e16483] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/25/2022] [Revised: 05/15/2023] [Accepted: 05/17/2023] [Indexed: 05/31/2023] Open
Abstract
Background The study aimed to identify the relations of the absolute lymphocyte count (ALC) nadir during prophylactic cranial irradiation (PCI) and patient outcomes in limited-stage small cell lung cancer (LS-SCLC). Methods We analyzed 268 L S-SCLC patients who underwent PCI from 2012 to 2019. ALC values were collected prior, during, and 3 months post PCI. Kaplan-Meier and Cox regression analyses were performed to assess the relation of ALC to patient prognosis. Two nomograms were developed on the basis of clinical variables for survival prediction. Results Compared with the ALC before PCI (1.13 × 109 cells/L), the ALC nadir during PCI was significantly reduced by 0.68 × 109 cells/L (P < 0.001) and raised to 1.02 × 109 cells/L 3 months post PCI. Patients with a low ALC nadir during PCI (<0.68 × 109 cells/L) had inferior progression free survival (PFS) (median PFS: 17.2 m vs. 43.7 m, P = 0.019) and overall survival (OS) (median OS: 29.0 m vs 39.1 m, P = 0.012). Multivariate Cox analysis revealed that age, smoking history, clinical stage, and ALC nadir were independent OS (P = 0.006, P = 0.005, P < 0.001 and P = 0.027, respectively), as well as independent PFS predictors (P = 0.032, P = 0.012, P = 0.012 and P = 0.018, respectively). After internal cross-validation, the corrected concordance indices of the predictive nomograms for PFS and OS were 0.637 and 0.663, respectively. Conclusion LS-SCLC patients with a low ALC nadir during PCI likely have worse survival outcomes. Dynamic evaluation of the ALC during PCI is recommended for LS-SCLC patients.
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Affiliation(s)
- Xinyu Fan
- Department of Radiation Oncology, Shandong Cancer Hospital and Institute, Shandong First Medical University and Shandong Academy of Medical Science, Jinan, 250000, China
| | - Linlin Yang
- Department of Radiation Oncology, Shandong Cancer Hospital and Institute, Shandong First Medical University and Shandong Academy of Medical Science, Jinan, 250000, China
| | - Wenru Qin
- Department of Radiation Oncology, Shandong Cancer Hospital and Institute, Shandong First Medical University and Shandong Academy of Medical Science, Jinan, 250000, China
| | - Bing Zou
- Department of Radiation Oncology, Shandong Cancer Hospital and Institute, Shandong First Medical University and Shandong Academy of Medical Science, Jinan, 250000, China
| | - Bingjie Fan
- Department of Radiation Oncology, Shandong Cancer Hospital and Institute, Shandong First Medical University and Shandong Academy of Medical Science, Jinan, 250000, China
| | - Shijiang Wang
- Department of Radiation Oncology, Shandong Cancer Hospital and Institute, Shandong First Medical University and Shandong Academy of Medical Science, Jinan, 250000, China
- Cheeloo College of Medicine, Shandong University, Jinan, 250000, China
| | - Linlin Wang
- Department of Radiation Oncology, Shandong Cancer Hospital and Institute, Shandong First Medical University and Shandong Academy of Medical Science, Jinan, 250000, China
- Cheeloo College of Medicine, Shandong University, Jinan, 250000, China
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10
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Lin X, Yang Q, Zheng D, Tian H, Chen L, Wu J, Ji Z, Chen Y, Li Z. Scientometric analysis of lipid metabolism in breast neoplasm: 2012-2021. Front Physiol 2023; 14:1042603. [PMID: 37179822 PMCID: PMC10168182 DOI: 10.3389/fphys.2023.1042603] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/04/2022] [Accepted: 04/10/2023] [Indexed: 05/15/2023] Open
Abstract
Introduction: In recent years, more and more studies have proved that lipid metabolism plays an essential role in breast cancer's proliferation and metastasisand also has a specific significance in predicting survival. Methods: This paper collected data from 725 publications related to lipid metabolism in breast neoplasm from 2012 to 2021 through the Web of Science Core Collection database. Bibliometrix, VOSviewer, and CiteSpace were used for the scientometrics analysis of countries, institutions, journals, authors, keywords, etc. Results: The number of documents published showed an increasing trend, with an average annual growth rate of 14.49%. The United States was the most productive country (n = 223, 30.76%). The journals with the largest number of publications are mostly from developed countries. Except for the retrieved topics, "lipid metabolism" (n = 272) and "breast cancer" (n = 175), the keywords that appeared most frequently were "expression" (n = 151), "fatty-acid synthase" (n = 78), "growth" (n = 72), "metabolism" (n = 67) and "cells" (n = 66). Discussion: These findings and summaries help reveal the current research status and clarify the hot spots in this field.
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Affiliation(s)
| | | | | | | | | | | | | | - Yexi Chen
- Department of Thyroid, Breast and Hernia Surgery, General Surgery, The Second Affiliated Hospital of Shantou University Medical College, Shantou, Guangdong, China
| | - Zhiyang Li
- Department of Thyroid, Breast and Hernia Surgery, General Surgery, The Second Affiliated Hospital of Shantou University Medical College, Shantou, Guangdong, China
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11
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Liu L, Mo M, Chen X, Chao D, Zhang Y, Chen X, Wang Y, Zhang N, He N, Yuan X, Chen H, Yang J. Targeting inhibition of prognosis-related lipid metabolism genes including CYP19A1 enhances immunotherapeutic response in colon cancer. J Exp Clin Cancer Res 2023; 42:85. [PMID: 37055842 PMCID: PMC10100168 DOI: 10.1186/s13046-023-02647-8] [Citation(s) in RCA: 11] [Impact Index Per Article: 11.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/29/2022] [Accepted: 03/14/2023] [Indexed: 04/15/2023] Open
Abstract
BACKGROUND Lipid metabolic reprogramming in colon cancer shows a potential impact on tumor immune microenvironment and is associated with response to immunotherapy. Therefore, this study aimed to develop a lipid metabolism-related prognostic risk score (LMrisk) to provide new biomarkers and combination therapy strategies for colon cancer immunotherapy. METHODS Differentially expressed lipid metabolism-related genes (LMGs) including cytochrome P450 (CYP) 19A1 were screened to construct LMrisk in TCGA colon cancer cohort. The LMrisk was then validated in three GEO datasets. The differences of immune cell infiltration and immunotherapy response between LMrisk subgroups were investigated via bioinformatic analysis. These results were comfirmed by in vitro coculture of colon cancer cells with peripheral blood mononuclear cells, human colon cancer tissue microarray analysis, multiplex immunofluorescence staining and mouse xenograft models of colon cancer. RESULTS Six LMGs including CYP19A1, ALOXE3, FABP4, LRP2, SLCO1A2 and PPARGC1A were selected to establish the LMrisk. The LMrisk was positively correlated with the abundance of macrophages, carcinoma-associated fibroblasts (CAFs), endothelial cells and the levels of biomarkers for immunotherapeutic response including programmed cell death ligand 1 (PD-L1) expression, tumor mutation burden and microsatellite instability, but negatively correlated with CD8+ T cell infiltration levels. CYP19A1 protein expression was an independent prognostic factor, and positively correlated with PD-L1 expression in human colon cancer tissues. Multiplex immunofluorescence analyses revealed that CYP19A1 protein expression was negatively correlated with CD8+ T cell infiltration, but positively correlated with the levels of tumor-associated macrophages, CAFs and endothelial cells. Importantly, CYP19A1 inhibition downregulated PD-L1, IL-6 and TGF-β levels through GPR30-AKT signaling, thereby enhancing CD8+ T cell-mediated antitumor immune response in vitro co-culture studies. CYP19A1 inhibition by letrozole or siRNA strengthened the anti-tumor immune response of CD8+ T cells, induced normalization of tumor blood vessels, and enhanced the efficacy of anti-PD-1 therapy in orthotopic and subcutaneous mouse colon cancer models. CONCLUSION A risk model based on lipid metabolism-related genes may predict prognosis and immunotherapeutic response in colon cancer. CYP19A1-catalyzed estrogen biosynthesis promotes vascular abnormality and inhibits CD8+ T cell function through the upregulation of PD-L1, IL-6 and TGF-β via GPR30-AKT signaling. CYP19A1 inhibition combined with PD-1 blockade represents a promising therapeutic strategy for colon cancer immunotherapy.
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Affiliation(s)
- Lilong Liu
- Department of Pharmacology and Hubei Province Key Laboratory of Allergy and Immune-related Diseases, School of Basic Medical Sciences, Wuhan University, 185 Donghu Road, Wuhan, 430071, China
| | - Min Mo
- Department of Pharmacology and Hubei Province Key Laboratory of Allergy and Immune-related Diseases, School of Basic Medical Sciences, Wuhan University, 185 Donghu Road, Wuhan, 430071, China
| | - Xuehan Chen
- Department of Pharmacology and Hubei Province Key Laboratory of Allergy and Immune-related Diseases, School of Basic Medical Sciences, Wuhan University, 185 Donghu Road, Wuhan, 430071, China
| | - Dongchen Chao
- Department of Pharmacology and Hubei Province Key Laboratory of Allergy and Immune-related Diseases, School of Basic Medical Sciences, Wuhan University, 185 Donghu Road, Wuhan, 430071, China
| | - Yufan Zhang
- Department of Pharmacology and Hubei Province Key Laboratory of Allergy and Immune-related Diseases, School of Basic Medical Sciences, Wuhan University, 185 Donghu Road, Wuhan, 430071, China
| | - Xuewei Chen
- Department of Laboratory Medicine, Zhongnan Hospital of Wuhan University, Wuhan, 430071, China
| | - Yang Wang
- Department of Pharmacology and Hubei Province Key Laboratory of Allergy and Immune-related Diseases, School of Basic Medical Sciences, Wuhan University, 185 Donghu Road, Wuhan, 430071, China
| | - Nan Zhang
- Department of Pharmacology and Hubei Province Key Laboratory of Allergy and Immune-related Diseases, School of Basic Medical Sciences, Wuhan University, 185 Donghu Road, Wuhan, 430071, China
| | - Nan He
- Department of Pharmacology and Hubei Province Key Laboratory of Allergy and Immune-related Diseases, School of Basic Medical Sciences, Wuhan University, 185 Donghu Road, Wuhan, 430071, China
| | - Xi Yuan
- Department of Pharmacology and Hubei Province Key Laboratory of Allergy and Immune-related Diseases, School of Basic Medical Sciences, Wuhan University, 185 Donghu Road, Wuhan, 430071, China
| | - Honglei Chen
- Department of Pathology, School of Basic Medical Sciences, Wuhan University, Wuhan, 430071, China.
| | - Jing Yang
- Department of Pharmacology and Hubei Province Key Laboratory of Allergy and Immune-related Diseases, School of Basic Medical Sciences, Wuhan University, 185 Donghu Road, Wuhan, 430071, China.
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12
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Li C, Tao Y, Chen Y, Wu Y, He Y, Yin S, Xu S, Yu Y. Development of a metabolism-related signature for predicting prognosis, immune infiltration and immunotherapy response in breast cancer. Am J Cancer Res 2022; 12:5440-5461. [PMID: 36628282 PMCID: PMC9827085] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/23/2022] [Accepted: 11/27/2022] [Indexed: 01/12/2023] Open
Abstract
Breast cancer (BRCA) is the most commonly diagnosed cancer and among the top causes of cancer deaths globally. The abnormality of the metabolic process is an important characteristic that distinguishes cancer cells from normal cells. Currently, there are few metabolic molecular models to evaluate the prognosis and treatment response of BRCA patients. By analyzing RNA-seq data of BRCA samples from public databases via bioinformatic approaches, we developed a prognostic signature based on seven metabolic genes (PLA2G2D, GNPNAT1, QPRT, SHMT2, PAICS, NT5E and PLPP2). Low-risk patients showed better overall survival in all five cohorts (TCGA cohort, two external validation cohorts and two internal validation cohorts). There was a higher proportion of tumor-infiltrating CD8+ T cells, CD4+ memory resting T cells, gamma delta T cells and resting dendritic cells and a lower proportion of M0 and M2 macrophages in the low-risk group. Low-risk patients also showed higher ESTIMATE scores, higher immune function scores, higher Immunophenoscores (IPS) and checkpoint expression, lower stemness scores, lower TIDE (Tumor Immune Dysfunction and Exclusion) scores and IC50 values for several chemotherapeutic agents, suggesting that low-risk patients could respond more favorably to immunotherapy and chemotherapy. Two real-world patient cohorts receiving anti-PD-1 therapy were applied for validating the predictive results. Molecular subtypes identified based on these seven genes also showed different immune characteristics. Immunohistochemical data obtained from the human protein atlas database demonstrated the protein expression of signature genes. This research may contribute to the identification of metabolic targets for BRCA and the optimization of risk stratification and personalized treatment for BRCA patients.
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Affiliation(s)
- Chunzhen Li
- National Key Laboratory of Medical Immunology and Institute of Immunology, Naval Medical UniversityShanghai 200433, China
| | - Yijie Tao
- National Key Laboratory of Medical Immunology and Institute of Immunology, Naval Medical UniversityShanghai 200433, China
| | - Yining Chen
- Faculty of Health Sciences and Engineering, University of Shanghai for Science and TechnologyShanghai 200433, China
| | - Yunyang Wu
- National Key Laboratory of Medical Immunology and Institute of Immunology, Naval Medical UniversityShanghai 200433, China
| | - Yixian He
- National Key Laboratory of Medical Immunology and Institute of Immunology, Naval Medical UniversityShanghai 200433, China
| | - Shulei Yin
- National Key Laboratory of Medical Immunology and Institute of Immunology, Naval Medical UniversityShanghai 200433, China
| | - Sheng Xu
- National Key Laboratory of Medical Immunology and Institute of Immunology, Naval Medical UniversityShanghai 200433, China
| | - Yizhi Yu
- National Key Laboratory of Medical Immunology and Institute of Immunology, Naval Medical UniversityShanghai 200433, China
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13
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D MO, C TZ, R SP. Human orphan cytochromes P450: An update. Curr Drug Metab 2022; 23:CDM-EPUB-128186. [PMID: 36503398 DOI: 10.2174/1389200224666221209153032] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/05/2022] [Revised: 10/25/2022] [Accepted: 11/11/2022] [Indexed: 12/14/2022]
Abstract
Orphan cytochromes P450 (CYP) are enzymes whose biological functions and substrates are unknown. However, the use of new experimental strategies has allowed obtaining more information about their relevance in the metabolism of endogenous and exogenous compounds. Likewise, the modulation of their expression and activity has been associated with pathogenesis and prognosis in different diseases. In this work, we review the regulatory pathways and the possible role of orphan CYP to provide evidence that allow us to stop considering some of them as orphan enzymes and to propose them as possible therapeutic targets in the design of new strategies for the treatment of diseases associated with CYP-mediated metabolism.
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Affiliation(s)
- Molina-Ortiz D
- Laboratorio de Toxicología Genética, Instituto Nacional de Pediatría, Coyoacán, Mexico City, México, 04530
| | - Torres-Zárate C
- Laboratorio de Toxicología Genética, Instituto Nacional de Pediatría, Coyoacán, Mexico City, México, 04530
| | - Santes-Palacios R
- Laboratorio de Toxicología Genética, Instituto Nacional de Pediatría, Coyoacán, Mexico City, México, 04530
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14
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Zhu J, Kong W, Huang L, Wang S, Bi S, Wang Y, Shan P, Zhu S. MLSP: A Bioinformatics Tool for Predicting Molecular Subtypes and Prognosis in Patients with Breast Cancer. Comput Struct Biotechnol J 2022; 20:6412-6426. [DOI: 10.1016/j.csbj.2022.11.017] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/30/2022] [Revised: 10/18/2022] [Accepted: 11/07/2022] [Indexed: 11/13/2022] Open
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15
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Zhang L, She R, Zhu J, Lu J, Gao Y, Song W, Cai S, Wang L. Novel lipometabolism biomarker for chemotherapy and immunotherapy response in breast cancer. BMC Cancer 2022; 22:1030. [PMID: 36182903 PMCID: PMC9526348 DOI: 10.1186/s12885-022-10110-8] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/16/2022] [Accepted: 09/15/2022] [Indexed: 11/15/2022] Open
Abstract
Emerging proof shows that abnormal lipometabolism affects invasion, metastasis, stemness and tumor microenvironment in carcinoma cells. However, molecular markers related to lipometabolism have not been further established in breast cancer. In addition, numerous studies have been conducted to screen for prognostic features of breast cancer only with RNA sequencing profiles. Currently, there is no comprehensive analysis of multiomics data to extract better biomarkers. Therefore, we have downloaded the transcriptome, single nucleotide mutation and copy number variation dataset for breast cancer from the TCGA database, and constructed a riskScore of twelve genes by LASSO regression analysis. Patients with breast cancer were categorized into high and low risk groups based on the median riskScore. The high-risk group had a worse prognosis than the low-risk group. Next, we have observed the mutated frequencies and the copy number variation frequencies of twelve lipid metabolism related genes LMRGs and analyzed the association of copy number variation and riskScore with OS. Meanwhile, the ESTIMATE and CIBERSORT algorithms assessed tumor immune fraction and degree of immune cell infiltration. In immunotherapy, it is found that high-risk patients have better efficacy in TCIA analysis and the TIDE algorithm. Furthermore, the effectiveness of six common chemotherapy drugs was estimated. At last, high-risk patients were estimated to be sensitive to six chemotherapeutic agents and six small molecule drug candidates. Together, LMRGs could be utilized as a de novo tumor biomarker to anticipate better the prognosis of breast cancer patients and the therapeutic efficacy of immunotherapy and chemotherapy.
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Affiliation(s)
- Lei Zhang
- Department of Gastrointestinal Surgery, the First Affiliated Hospital of Jinan University, Guangzhou, 510632, China.,Institute of Precision Cancer Medicine and Pathology, School of Medicine, Jinan University, Guangzhou, 510632, China.,Department of Oncology Surgery, the Second Affiliated Hospital of Bengbu Medical College, Bengbu, 233080, Anhui Province, China
| | - Risheng She
- Department of Emergency, Dongguan People's Hospital, Dongguan, 523000, China
| | - Jianlin Zhu
- Department of Gastrointestinal Surgery, the First Affiliated Hospital of Jinan University, Guangzhou, 510632, China.,Institute of Precision Cancer Medicine and Pathology, School of Medicine, Jinan University, Guangzhou, 510632, China
| | - Jin Lu
- Laboratory of Computational Medicine and Intelligent Health, Bengbu Medical College, Bengbu, 233030, Anhui Province, China
| | - Yuan Gao
- Department of Medical Ultrasound, the Second Affiliated Hospital of Bengbu Medical College, Bengbu, 233080, Anhui Province, China
| | - Wenhua Song
- Department of Oncology Surgery, the Second Affiliated Hospital of Bengbu Medical College, Bengbu, 233080, Anhui Province, China.
| | - Songwang Cai
- Department of Thoracic Surgery, The First Affiliated Hospital of Jinan University, Guangzhou, Guangdong, 510630, P. R. China.
| | - Lu Wang
- Department of Gastrointestinal Surgery, the First Affiliated Hospital of Jinan University, Guangzhou, 510632, China. .,Institute of Precision Cancer Medicine and Pathology, School of Medicine, Jinan University, Guangzhou, 510632, China.
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Du K, Zou J, Wang B, Liu C, Khan M, Xie T, Huang X, Shen P, Tian Y, Yuan Y. A Metabolism-Related Gene Prognostic Index Bridging Metabolic Signatures and Antitumor Immune Cycling in Head and Neck Squamous Cell Carcinoma. Front Immunol 2022; 13:857934. [PMID: 35844514 PMCID: PMC9282908 DOI: 10.3389/fimmu.2022.857934] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/19/2022] [Accepted: 05/18/2022] [Indexed: 12/26/2022] Open
Abstract
Background In the era of immunotherapy, predictive or prognostic biomarkers for head and neck squamous cell carcinoma (HNSCC) are urgently needed. Metabolic reprogramming in the tumor microenvironment (TME) is a non-negligible reason for the low therapeutic response to immune checkpoint inhibitor (ICI) therapy. We aimed to construct a metabolism-related gene prognostic index (MRGPI) for HNSCC bridging metabolic characteristics and antitumor immune cycling and identified the immunophenotype, genetic alternations, potential targeted inhibitors, and the benefit of immunotherapy in MRGPI-defined subgroups of HNSCC. Methods Based on The Cancer Genome Atlas (TCGA) HNSCC dataset (n = 502), metabolism-related hub genes were identified by the weighted gene co-expression network analysis (WGCNA). Seven genes were identified to construct the MRGPI by using the Cox regression method and validated with an HNSCC dataset (n = 270) from the Gene Expression Omnibus (GEO) database. Afterward, the prognostic value, metabolic activities, genetic alternations, gene set enrichment analysis (GSEA), immunophenotype, Connectivity map (cMAP), and benefit of immunotherapy in MRGPI-defined subgroups were analyzed. Results The MRGPI was constructed based on HPRT1, AGPAT4, AMY2B, ACADL, CKM, PLA2G2D, and ADA. Patients in the low-MRGPI group had better overall survival than those in the high-MRGPI group, consistent with the results in the GEO cohort (cutoff value = 1.01). Patients with a low MRGPI score display lower metabolic activities and an active antitumor immunity status and more benefit from immunotherapy. In contrast, a higher MRGPI score was correlated with higher metabolic activities, more TP53 mutation rate, lower antitumor immunity ability, an immunosuppressive TME, and less benefit from immunotherapy. Conclusion The MRGPI is a promising indicator to distinguish the prognosis, the metabolic, molecular, and immune phenotype, and the benefit from immunotherapy in HNSCC.
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Affiliation(s)
- Kunpeng Du
- Department of Radiation Oncology, Affiliated Cancer Hospital & Institute of Guangzhou Medical University, Guangzhou, China
| | - Jingwen Zou
- Department of Liver Surgery of the Sun Yat-sen University Cancer Center, Guangzhou, China
| | - Baiyao Wang
- Department of Radiation Oncology, Affiliated Cancer Hospital & Institute of Guangzhou Medical University, Guangzhou, China
| | - Chunshan Liu
- Department of Radiation Oncology, Affiliated Cancer Hospital & Institute of Guangzhou Medical University, Guangzhou, China
| | - Muhammad Khan
- Department of Radiation Oncology, Affiliated Cancer Hospital & Institute of Guangzhou Medical University, Guangzhou, China
| | - Tao Xie
- Department of Radiation Oncology, Affiliated Cancer Hospital & Institute of Guangzhou Medical University, Guangzhou, China
| | - Xiaoting Huang
- Department of Radiation Oncology, Affiliated Cancer Hospital & Institute of Guangzhou Medical University, Guangzhou, China
| | - Piao Shen
- Department of Radiation Oncology, Affiliated Cancer Hospital & Institute of Guangzhou Medical University, Guangzhou, China
| | - Yunhong Tian
- Department of Radiation Oncology, Affiliated Cancer Hospital & Institute of Guangzhou Medical University, Guangzhou, China
- *Correspondence: Yunhong Tian, ; Yawei Yuan,
| | - Yawei Yuan
- Department of Radiation Oncology, Affiliated Cancer Hospital & Institute of Guangzhou Medical University, Guangzhou, China
- *Correspondence: Yunhong Tian, ; Yawei Yuan,
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17
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Identification of molecular subtypes and a novel prognostic model of diffuse large B-cell lymphoma based on a metabolism-associated gene signature. J Transl Med 2022; 20:186. [PMID: 35468826 PMCID: PMC9036805 DOI: 10.1186/s12967-022-03393-9] [Citation(s) in RCA: 27] [Impact Index Per Article: 13.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/07/2022] [Accepted: 04/11/2022] [Indexed: 12/13/2022] Open
Abstract
Background Diffuse large B cell lymphoma (DLBCL) is the most common lymphoma in adults. Metabolic reprogramming in tumors is closely related to the immune microenvironment. This study aimed to explore the interactions between metabolism-associated genes (MAGs) and DLBCL prognosis and their potential associations with the immune microenvironment. Methods Gene expression and clinical data on DLBCL patients were obtained from the GEO database. Metabolism-associated molecular subtypes were identified by consensus clustering. A prognostic risk model containing 14 MAGs was established using Lasso-Cox regression in the GEO training cohort. It was then validated in the GEO internal testing cohort and TCGA external validation cohort. GO, KEGG and GSVA were used to explore the differences in enriched pathways between high- and low-risk groups. ESTIMATE, CIBERSORT, and ssGSEA analyses were used to assess the immune microenvironment. Finally, WGCNA analysis was used to identify two hub genes among the 14 model MAGs, and they were preliminarily verified in our tissue microarray (TMA) using multiple fluorescence immunohistochemistry (mIHC). Results Consensus clustering divided DLBCL patients into two metabolic subtypes with significant differences in prognosis and the immune microenvironment. Poor prognosis was associated with an immunosuppressive microenvironment. A prognostic risk model was constructed based on 14 MAGs and it was used to classify the patients into two risk groups; the high-risk group had poorer prognosis and an immunosuppressive microenvironment characterized by low immune score, low immune status, high abundance of immunosuppressive cells, and high expression of immune checkpoints. Cox regression, ROC curve analysis, and a nomogram indicated that the risk model was an independent prognostic factor and had a better prognostic value than the International Prognostic Index (IPI) score. The risk model underwent multiple validations and the verification of the two hub genes in TMA indicated consistent results with the bioinformatics analyses. Conclusions The molecular subtypes and a risk model based on MAGs proposed in our study are both promising prognostic classifications in DLBCL, which may provide novel insights for developing accurate targeted cancer therapies. Supplementary Information The online version contains supplementary material available at 10.1186/s12967-022-03393-9.
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18
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Yan J, Yuan W, Zhang J, Li L, Zhang L, Zhang X, Zhang M. Identification and Validation of a Prognostic Prediction Model in Diffuse Large B-Cell Lymphoma. Front Endocrinol (Lausanne) 2022; 13:846357. [PMID: 35498426 PMCID: PMC9048048 DOI: 10.3389/fendo.2022.846357] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/31/2021] [Accepted: 02/25/2022] [Indexed: 11/13/2022] Open
Abstract
BACKGROUND Diffuse large B-cell lymphoma (DLBCL) is a heterogeneous group with varied pathophysiological, genetic, and clinical features, accounting for approximately one-third of all lymphoma cases worldwide. Notwithstanding that unprecedented scientific progress has been achieved over the years, the survival of DLBCL patients remains low, emphasizing the need to develop novel prognostic biomarkers for early risk stratification and treatment optimization. METHOD In this study, we screened genes related to the overall survival (OS) of DLBCL patients in datasets GSE117556, GSE10846, and GSE31312 using univariate Cox analysis. Survival-related genes among the three datasets were screened according to the criteria: hazard ratio (HR) >1 or <1 and p-value <0.01. Least Absolute Shrinkage and Selection Operator (LASSO) and multivariate Cox regression analysis were used to optimize and establish the final gene risk prediction model. The TCGA-NCICCR datasets and our clinical cohort were used to validate the performance of the prediction model. CIBERSORT and ssGSEA algorithms were used to estimate immune scores in the high- and low-risk groups. RESULTS We constructed an eight-gene prognostic signature that could reliably predict the clinical outcome in training, testing, and validation cohorts. Our prognostic signature also performed distinguished areas under the ROC curve in each dataset, respectively. After stratification based on clinical characteristics such as cell-of-origin (COO), age, eastern cooperative oncology group (ECOG) performance status, international prognostic index (IPI), stage, and MYC/BCL2 expression, the difference in OS between the high- and low-risk groups was statistically significant. Next, univariate and multivariate analyses revealed that the risk score model had a significant prediction value. Finally, a nomogram was established to visualize the prediction model. Of note, we found that the low-risk group was enriched with immune cells. CONCLUSION In summary, we identified an eight-gene prognostic prediction model that can effectively predict survival outcomes of patients with DLBCL and built a nomogram to visualize the perdition model. We also explored immune alterations between high- and low-risk groups.
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Affiliation(s)
- Jiaqin Yan
- Department of Oncology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Wei Yuan
- Department of Oncology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
- The Academy of Medical Sciences, Zhengzhou University, Zhengzhou, China
- State Key Laboratory of Esophageal Cancer Prevention and Treatment, Zhengzhou University, Zhengzhou, China
| | - Junhui Zhang
- Otorhinolaryngology, The Third Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Ling Li
- Department of Oncology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Lei Zhang
- Department of Oncology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Xudong Zhang
- Department of Oncology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Mingzhi Zhang
- Department of Oncology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
- *Correspondence: Mingzhi Zhang,
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Liu H, Xu R, Gao C, Zhu T, Liu L, Yang Y, Zeng H, Huang Y, Wang H. Metabolic Molecule PLA2G2D Is a Potential Prognostic Biomarker Correlating With Immune Cell Infiltration and the Expression of Immune Checkpoint Genes in Cervical Squamous Cell Carcinoma. Front Oncol 2021; 11:755668. [PMID: 34733790 PMCID: PMC8558485 DOI: 10.3389/fonc.2021.755668] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/09/2021] [Accepted: 09/24/2021] [Indexed: 12/23/2022] Open
Abstract
Cervical squamous cell carcinoma (CSCC) is the major pathological type of cervical cancer (CC), the second most prevalent reproductive system malignant tumor threatening the health of women worldwide. The prognosis of CSCC patients is largely affected by the tumor immune microenvironment (TIME); however, the biomarker landscape related to the immune microenvironment of CSCC and patient prognosis is less characterized. Here, we analyzed RNA-seq data of CSCC patients from The Cancer Genome Atlas (TCGA) database by dividing it into high- and low-immune infiltration groups with the MCP-counter and ESTIMATE R packages. After combining weighted gene co-expression network analysis (WGCNA) and differentially expressed gene (DEG) analysis, we found that PLA2G2D, a metabolism-associated gene, is the top gene positively associated with immune infiltration and patient survival. This finding was validated using data from The Cancer Genome Characterization Initiative (CGCI) database and further confirmed by quantitative reverse transcription-polymerase chain reaction (qRT-PCR). Finally, multiplex immunohistochemistry (mIHC) was performed to confirm the differential infiltration of immune cells between PLA2G2D-high and PLA2G2D-low tumors at the protein level. Our results demonstrated that PLA2G2D expression was significantly correlated with the infiltration of immune cells, especially T cells and macrophages. More importantly, PLA2G2D-high tumors also exhibited higher infiltration of CD8+ T cells inside the tumor region than PLA2G2D-low tumors. In addition, PLA2G2D expression was found to be positively correlated with the expression of multiple immune checkpoint genes (ICPs). Moreover, based on other immunotherapy cohort data, PLA2G2D high expression is correlated with increased cytotoxicity and favorable response to immune checkpoint blockade (ICB) therapy. Hence, PLA2G2D could be a novel potential biomarker for immune cell infiltration, patient survival, and the response to ICB therapy in CSCC and may represent a promising target for the treatment of CSCC patients.
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Affiliation(s)
- Hong Liu
- Cancer Biology Research Center (Key Laboratory of the Ministry of Education), Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
- Department of Gynecologic Oncology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Ruiyi Xu
- Department of Gynecologic Oncology, Women’s Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Chun Gao
- Cancer Biology Research Center (Key Laboratory of the Ministry of Education), Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
- Department of Gynecologic Oncology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Tong Zhu
- Cancer Biology Research Center (Key Laboratory of the Ministry of Education), Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
- Department of Gynecologic Oncology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Liting Liu
- Cancer Biology Research Center (Key Laboratory of the Ministry of Education), Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
- Department of Gynecologic Oncology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Yifan Yang
- Cancer Biology Research Center (Key Laboratory of the Ministry of Education), Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
- Department of Gynecologic Oncology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Haihong Zeng
- Department of Pathogen Biology, School of Basic Medicine, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Yafei Huang
- Department of Pathogen Biology, School of Basic Medicine, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Hui Wang
- Cancer Biology Research Center (Key Laboratory of the Ministry of Education), Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
- Department of Gynecologic Oncology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
- Department of Gynecologic Oncology, Women’s Hospital, Zhejiang University School of Medicine, Hangzhou, China
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