1
|
Yang S, Wang X, Huan R, Deng M, Kong Z, Xiong Y, Luo T, Jin Z, Liu J, Chu L, Han G, Zhang J, Tan Y. Machine learning unveils immune-related signature in multicenter glioma studies. iScience 2024; 27:109317. [PMID: 38500821 PMCID: PMC10946333 DOI: 10.1016/j.isci.2024.109317] [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: 09/16/2023] [Revised: 01/11/2024] [Accepted: 02/17/2024] [Indexed: 03/20/2024] Open
Abstract
In glioma molecular subtyping, existing biomarkers are limited, prompting the development of new ones. We present a multicenter study-derived consensus immune-related and prognostic gene signature (CIPS) using an optimal risk score model and 101 algorithms. CIPS, an independent risk factor, showed stable and powerful predictive performance for overall and progression-free survival, surpassing traditional clinical variables. The risk score correlated significantly with the immune microenvironment, indicating potential sensitivity to immunotherapy. High-risk groups exhibited distinct chemotherapy drug sensitivity. Seven signature genes, including IGFBP2 and TNFRSF12A, were validated by qRT-PCR, with higher expression in tumors and prognostic relevance. TNFRSF12A, upregulated in GBM, demonstrated inhibitory effects on glioma cell proliferation, migration, and invasion. CIPS emerges as a robust tool for enhancing individual glioma patient outcomes, while IGFBP2 and TNFRSF12A pose as promising tumor markers and therapeutic targets.
Collapse
Affiliation(s)
- Sha Yang
- Guizhou University Medical College, Guiyang 550025, Guizhou Province, China
| | - Xiang Wang
- Department of Neurosurgery, the Affiliated Hospital of Guizhou Medical University, Guiyang 550004, China
| | - Renzheng Huan
- Department of Neurosurgery, The Second Affiliated Hospital of Chongqing Medical University, Chongqing 400010, China
| | - Mei Deng
- Department of Neurosurgery, Guizhou Provincial People’s Hospital, Guiyang, China
| | - Zhuo Kong
- Department of Neurosurgery, Guizhou Provincial People’s Hospital, Guiyang, China
| | - Yunbiao Xiong
- Department of Neurosurgery, Guizhou Provincial People’s Hospital, Guiyang, China
| | - Tao Luo
- Department of Neurosurgery, Guizhou Provincial People’s Hospital, Guiyang, China
| | - Zheng Jin
- Department of Neurosurgery, Guizhou Provincial People’s Hospital, Guiyang, China
| | - Jian Liu
- Guizhou University Medical College, Guiyang 550025, Guizhou Province, China
- Department of Neurosurgery, Guizhou Provincial People’s Hospital, Guiyang, China
| | - Liangzhao Chu
- Department of Neurosurgery, the Affiliated Hospital of Guizhou Medical University, Guiyang 550004, China
| | - Guoqiang Han
- Department of Neurosurgery, Guizhou Provincial People’s Hospital, Guiyang, China
| | - Jiqin Zhang
- Department of Anesthesiology, Guizhou Provincial People’s Hospital, Guiyang, China
| | - Ying Tan
- Department of Neurosurgery, Guizhou Provincial People’s Hospital, Guiyang, China
| |
Collapse
|
2
|
Tabnak P, Hasanzade Bashkandi A, Ebrahimnezhad M, Soleimani M. Forkhead box transcription factors (FOXOs and FOXM1) in glioma: from molecular mechanisms to therapeutics. Cancer Cell Int 2023; 23:238. [PMID: 37821870 PMCID: PMC10568859 DOI: 10.1186/s12935-023-03090-7] [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: 09/26/2022] [Accepted: 10/04/2023] [Indexed: 10/13/2023] Open
Abstract
Glioma is the most aggressive and malignant type of primary brain tumor, comprises the majority of central nervous system deaths, and is categorized into different subgroups according to its histological characteristics, including astrocytomas, oligodendrogliomas, glioblastoma multiforme (GBM), and mixed tumors. The forkhead box (FOX) transcription factors comprise a collection of proteins that play various roles in numerous complex molecular cascades and have been discovered to be differentially expressed in distinct glioma subtypes. FOXM1 and FOXOs have been recognized as crucial transcription factors in tumor cells, including glioma cells. Accumulating data indicates that FOXM1 acts as an oncogene in various types of cancers, and a significant part of studies has investigated its function in glioma. Although recent studies considered FOXO subgroups as tumor suppressors, there are pieces of evidence that they may have an oncogenic role. This review will discuss the subtle functions of FOXOs and FOXM1 in gliomas, dissecting their regulatory network with other proteins, microRNAs and their role in glioma progression, including stem cell differentiation and therapy resistance/sensitivity, alongside highlighting recent pharmacological progress for modulating their expression.
Collapse
Affiliation(s)
- Peyman Tabnak
- Faculty of Medicine, Tabriz University of Medical Sciences, Tabriz, Iran.
- Imam Reza Hospital, Tabriz University of Medical Sciences, Tabriz, Iran.
| | | | - Mohammad Ebrahimnezhad
- Faculty of Medicine, Tabriz University of Medical Sciences, Tabriz, Iran
- Imam Reza Hospital, Tabriz University of Medical Sciences, Tabriz, Iran
| | - Mahdieh Soleimani
- Imam Reza Hospital, Tabriz University of Medical Sciences, Tabriz, Iran
| |
Collapse
|
3
|
Li Y, Wu J, Li E, Xiao Z, Lei J, Zhou F, Yin X, Hu D, Mao Y, Wu L, Wenjun L. TP53 mutation detected in circulating exosomal DNA is associated with prognosis of patients with hepatocellular carcinoma. Cancer Biol Ther 2022; 23:439-445. [PMID: 35921289 PMCID: PMC9354767 DOI: 10.1080/15384047.2022.2094666] [Citation(s) in RCA: 13] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/24/2022] Open
Abstract
Exosome DNA (exoDNA) can be used for liquid biopsy. This study was the first to use droplet digital PCR (ddPCR) to detect tumor-specific mutations in exoDNA and to evaluate the prognosis of hepatocellular carcinoma (HCC) patients. 60 HCC patients were enrolled in the study. We used ddPCR to detect c.747 G > T mutation in TP53 gene. We analyzed the correlation between detectable mutation in exoDNA and clinicopathologic characteristics using Multivariate logistics regression analysis. We performed Cox regression to assess the correlation between mutation frequency (mutant droplets/total droplets, MD/TD) and prognostic. We found that 48 of 60 patients had c.747 G > T mutation in TP53 gene in exoDNA (80.0%). We found that detectable mutation in exoDNA and age were associated with microvascular invasion (MVI) (P < .01). The ROC curve analysis revealed that the best cutoff value of mutation frequency to predict MVI was 67% (sensitivity 48.15%, specificity 93.94%,), the corresponding AUC was 0.761 (95%CI, 0.640–0.866; P < .01). Furthermore, we found that patients suffered high-frequency mutation (>67%) had shorted median recurrence-free survival (RFS) with 63 days (range, 53–202 days), compared with 368 days (range, 51–576 days) for patients with low-frequency mutation (<67%) (HR:4.61; 95% CI, 1.70–12.48; P = 0 .003). We also found that high-frequency mutation was associated with poor prognosis though patients had better pathological characteristics, such as AFP (<400 ng/mL), Liver cirrhosis (Negative), Tumor thrombus (Negative), Tumor numbers (Single) and Post-operation TACE (Executed). We provided evidence that the mutations in exoDNA might be used to predict patients with poor RFS. Abbreviations: TP53: Tumor protein p53; ExoDNA: Exosomal DNA; HCC: Hepatocellular carcinoma; ddPCR: Droplet digital Polymerase Chain Reaction (PCR); MD/TD: The ratio of mutant droplets/total droplets; AFP: Alpha-fetoprotein; MVI: Microvascular invasion; RFS: Recurrence-free survival.
Collapse
Affiliation(s)
- Yong Li
- Department of Hepatobiliary and Pancreatic Surgery, The Second Affiliated Hospital of Nanchang University, Nanchang, China
| | - Junjun Wu
- Department of Hepatobiliary and Pancreatic Surgery, Jiangxi Provincial People's Hospital, Nanchang, China
| | - Enliang Li
- Department of Hepatobiliary and Pancreatic Surgery, The Second Affiliated Hospital of Nanchang University, Nanchang, China
| | - Zhouqing Xiao
- Department of Hepatobiliary and Pancreatic Surgery, The Second Affiliated Hospital of Nanchang University, Nanchang, China
| | - Jun Lei
- Department of Hepatobiliary and Pancreatic Surgery, The Second Affiliated Hospital of Nanchang University, Nanchang, China
| | - Fan Zhou
- Department of Hepatobiliary and Pancreatic Surgery, The Second Affiliated Hospital of Nanchang University, Nanchang, China
| | - Xiangbao Yin
- Department of Hepatobiliary and Pancreatic Surgery, The Second Affiliated Hospital of Nanchang University, Nanchang, China
| | - Dandan Hu
- Department of Hepatobiliary Surgery, Sun Yat-sen University Cancer Center, Guangzhou, China
| | - Yilei Mao
- Department of Hepatobiliary Surgery, Peking Union Medical College, Beijing, China
| | - Linquan Wu
- Department of Hepatobiliary and Pancreatic Surgery, The Second Affiliated Hospital of Nanchang University, Nanchang, China
| | - Liao Wenjun
- Department of Hepatobiliary and Pancreatic Surgery, The Second Affiliated Hospital of Nanchang University, Nanchang, China
| |
Collapse
|
4
|
Liu P, Yan X, Ma C, Gu J, Tian F, Qu J. Prognostic value of m6A regulators and the nomogram construction in glioma patients. Medicine (Baltimore) 2022; 101:e30643. [PMID: 36123877 PMCID: PMC9478228 DOI: 10.1097/md.0000000000030643] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/02/2022] Open
Abstract
Although N6-methyladenosine (m6A) has been implicated in various biological functions in human cancers, its role in predicting the prognosis of glioma remains unclear. In this study, the transcriptome expression profiles and the clinical data of 961 patients were derived from the Chinese Glioma Genome Atlas (CGGA). We comprehensively evaluated the association between the expression of m6A regulators and the prognosis of glioma and established a 3-gene (YTHDF2, FTO, and ALKBH5) risk signature using least absolute shrinkage and selection operator (LASSO) analysis. Patients with a high-risk signature had significantly adverse prognoses. Gene set enrichment analysis (GSEA) analysis revealed that the G2M checkpoint, MTORC1 signaling, epithelial mesenchymal transition, and PI3K-AKT-mTOR signaling were significantly enriched in the high-risk group. Univariate and multivariate Cox regression analyses confirmed the independent prognostic value of this risk signature. We then constructed a nomogram for individualized prediction of overall survival (OS) by integrating clinicopathological features (age, World Health Organization [WHO] grade), treatment information (radiotherapy, temozolomide therapy), and m6A risk signature. The calibration curves showed excellent agreement between the predicted and actual probabilities for the 1-, 3-, and 5-year OS, with a C-index of 0.780 in the training cohort and 0.717 in the validation cohort. Altogether, our study elucidated the important role of m6A regulators in glioma prognosis, which is valuable for the selection of therapeutic methods and clinical management of patients with glioma.
Collapse
Affiliation(s)
- Pengdi Liu
- Department of Neurosurgery, The Second Affiliated Hospital of Xi’an Jiaotong University, Shaanxi Province, China
| | - Xianxia Yan
- Department of Neurosurgery, The Second Affiliated Hospital of Xi’an Jiaotong University, Shaanxi Province, China
| | - Chengwen Ma
- Department of Neurosurgery, The Second Affiliated Hospital of Xi’an Jiaotong University, Shaanxi Province, China
| | - Junxiang Gu
- Department of Neurosurgery, The Second Affiliated Hospital of Xi’an Jiaotong University, Shaanxi Province, China
| | - Fuyu Tian
- Department of Neurosurgery, The Second Affiliated Hospital of Xi’an Jiaotong University, Shaanxi Province, China
| | - Jianqiang Qu
- Department of Neurosurgery, The Second Affiliated Hospital of Xi’an Jiaotong University, Shaanxi Province, China
- *Correspondence: Jianqiang Qu, Department of Neurosurgery, The Second Affiliated Hospital of Xi’an Jiaotong University, No. 157 Xiwu road, Xi’an 710004, shaanxi Province, China (e-mail: )
| |
Collapse
|
5
|
Peng Y, Wu G, Qiu X, Luo Y, Zou Y, Wei X, Li A. Construction and validation of a necroptosis-related lncRNAs prognosis signature of hepatocellular carcinoma. Front Genet 2022; 13:916024. [PMID: 36110223 PMCID: PMC9468751 DOI: 10.3389/fgene.2022.916024] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/08/2022] [Accepted: 06/28/2022] [Indexed: 11/13/2022] Open
Abstract
Background: Immunotherapy has achieved remarkable success in treating advanced liver cancer. Current evidence shows that most of the available immune checkpoint inhibitor (ICB) treatments are suboptimal, and specific markers are needed for patients regarded as good candidates for immunotherapy. Necroptosis, a type of programmed cell death, plays an important role in hepatocellular carcinoma (HCC) progression and outcome. However, studies on the necroptosis-related lncRNA in HCC are scarce. In this view, the present study investigates the link among necroptosis-related lncRNA, prognosis, immune microenvironment, and immunotherapy response.Methods: Gene transcriptome and clinical data were retrieved from The Cancer Genome Atlas database. Pearson correlation analysis of necroptosis-related genes was performed to identify necroptosis-related lncRNAs. The Wilcoxon method was used to detect differentially expressed genes, and prognostic relevant lncRNAs were obtained by univariate Cox regression analysis. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes analysis were utilized to perform functional enrichment analysis. Lasso–Cox stepwise regression analysis was employed to calculate risk score, which was involved in analyzing immune cells infiltration, immune checkpoints expression, and predicting immunotherapeutic efficacy. Quantitative RT-PCR (qRT-PCR) was performed to detect the expression pattern of lncRNA in cell lines.Results: The 10 lncRNAs generated in this study were used to create a prognostic risk model for HCC and group patients into groups based on risk. High-risk patients with HCC have a significantly lower OS rate than low-risk patients. Multivariate Cox regression analysis showed that risk score is an independent risk factor for HCC with high accuracy. Patients in the high-risk group exhibited a weaker immune surveillance and higher expression level of immune checkpoint molecules. In terms of drug resistance, patients in the low-risk group were more sensitive to sorafenib. The OS-related nomogram was constructed to verify the accuracy of our model. Finally, quantitative RT-PCR experiments were used to verify the expression patterns of candidate genes.Conclusion: The lncRNA signature established herein, encompassing 10 necroptosis-related lncRNAs, is valuable for survival prediction and holds promise as prognostic markers for HCC.
Collapse
Affiliation(s)
- YunZhen Peng
- Cancer Center, Integrated Hospital of Traditional Chinese Medicine, Southern Medical University, Guangzhou, China
| | - GuoJing Wu
- Cancer Center, Integrated Hospital of Traditional Chinese Medicine, Southern Medical University, Guangzhou, China
| | - Xin Qiu
- Department of Urology, The Third Affiliated Hospital, Southern Medical University, Guangzhou, China
| | - Yue Luo
- Cancer Center, Integrated Hospital of Traditional Chinese Medicine, Southern Medical University, Guangzhou, China
| | - YiShu Zou
- Cancer Center, Integrated Hospital of Traditional Chinese Medicine, Southern Medical University, Guangzhou, China
| | - XueYan Wei
- Cancer Center, Integrated Hospital of Traditional Chinese Medicine, Southern Medical University, Guangzhou, China
| | - Aimin Li
- Cancer Center, Integrated Hospital of Traditional Chinese Medicine, Southern Medical University, Guangzhou, China
- *Correspondence: Aimin Li, mailto:
| |
Collapse
|
6
|
Li L, Wei Y, Shi G, Yang H, Li Z, Fang R, Cao H, Cui Y. Multi-omics data integration for subtype identification of Chinese lower-grade gliomas: a joint similarity network fusion approach. Comput Struct Biotechnol J 2022; 20:3482-3492. [PMID: 35860412 PMCID: PMC9284445 DOI: 10.1016/j.csbj.2022.06.065] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/19/2022] [Revised: 06/30/2022] [Accepted: 06/30/2022] [Indexed: 12/28/2022] Open
Abstract
Lower-grade gliomas (LGG), characterized by heterogeneity and invasiveness, originate from the central nervous system. Although studies focusing on molecular subtyping and molecular characteristics have provided novel insights into improving the diagnosis and therapy of LGG, there is an urgent need to identify new molecular subtypes and biomarkers that are promising to improve patient survival outcomes. Here, we proposed a joint similarity network fusion (Joint-SNF) method to integrate different omics data types to construct a fused network using the Joint and Individual Variation Explained (JIVE) technique under the SNF framework. Focusing on the joint network structure, a spectral clustering method was employed to obtain subtypes of patients. Simulation studies show that the proposed Joint-SNF method outperforms the original SNF approach under various simulation scenarios. We further applied the method to a Chinese LGG data set including mRNA expression, DNA methylation and microRNA (miRNA). Three molecular subtypes were identified and showed statistically significant differences in patient survival outcomes. The five-year mortality rates of the three subtypes are 80.8%, 32.1%, and 34.4%, respectively. After adjusting for clinically relevant covariates, the death risk of patients in Cluster 1 was 5.06 times higher than patients in other clusters. The fused network attained by the proposed Joint-SNF method enhances strong similarities, thus greatly improves subtyping performance compared to the original SNF method. The findings in the real application may provide important clues for improving patient survival outcomes and for precision treatment for Chinese LGG patients. An R package to implement the method can be accessed in Github at https://github.com/Sameerer/Joint-SNF.
Collapse
Affiliation(s)
- Lingmei Li
- Division of Health Statistics, School of Public Health, Shanxi Medical University, Taiyuan, Shanxi 030001, PR China
| | - Yifang Wei
- Division of Health Statistics, School of Public Health, Shanxi Medical University, Taiyuan, Shanxi 030001, PR China
| | - Guojing Shi
- Division of Health Statistics, School of Public Health, Shanxi Medical University, Taiyuan, Shanxi 030001, PR China
| | - Haitao Yang
- Division of Health Statistics, School of Public Health, Hebei Medical University, Shijiazhuang, Hebei 050017, PR China
| | - Zhi Li
- Department of Hematology, Taiyuan Central Hospital of Shanxi Medical University, Taiyuan, Shanxi 030001, PR China
| | - Ruiling Fang
- Division of Health Statistics, School of Public Health, Shanxi Medical University, Taiyuan, Shanxi 030001, PR China
| | - Hongyan Cao
- Division of Health Statistics, School of Public Health, Shanxi Medical University, Taiyuan, Shanxi 030001, PR China
- Shanxi Medical University-Yidu Cloud Institute of Medical Data Science, Taiyuan, Shanxi 030001, PR China
- Corresponding authors at: Division of Health Statistics, School of Public Health, Shanxi Medical University, Taiyuan, Shanxi, PR China.
| | - Yuehua Cui
- Department of Statistics and Probability, Michigan State University, East Lansing, MI 48824, USA
- Corresponding authors at: Division of Health Statistics, School of Public Health, Shanxi Medical University, Taiyuan, Shanxi, PR China.
| |
Collapse
|
7
|
Peng X, Xu Z, Guo Y, Zhu Y. Necroptosis-Related Genes Associated With Immune Activity and Prognosis of Colorectal Cancer. Front Genet 2022; 13:909245. [PMID: 35783272 PMCID: PMC9243386 DOI: 10.3389/fgene.2022.909245] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/31/2022] [Accepted: 05/10/2022] [Indexed: 12/24/2022] Open
Abstract
This study aims at screening out the key necroptosis-related genes in colorectal cancer and elucidating the role of necroptosis-related genes in the immune activity and prognosis of colorectal cancer (CRC). The CRC patients’ data were downloaded from The Cancer Genome Atlas (TCGA). The non-negative matrix factorization method was applied to identify new molecular subgroups. Survival analysis and single sample Gene Set Enrichment Analysis were performed to determinate the differences in the overall survival time and immune status of the subgroups. Prognostic model was constructed on the basis of univariate Cox regression and LASSO analysis. Functional analyses were used to explore the potential mechanisms. Based on prognostic related necroptosis genes, we identify two molecular subgroups with significantly different survival. The better prognosis was associated with more active immune infiltration and upregulated expression of immune checkpoints. We screened nine necroptosis related genes as key prognostic genes and established a risk model, which showed a good potential for survival prediction in colorectal cancer. Nomogram assessment showed that the model had high reliability for predicting the prognosis of colorectal cancer patients. The high-risk and low-risk group also has different sensitivity to immunotherapy and commonly used drugs for colorectal cancer. Overall, necroptosis related genes were involved in the immune microenvironment of colorectal cancer patient, could be utilized to predict the prognosis of colorectal cancer and develop more individualized treatment.
Collapse
Affiliation(s)
- Xinyi Peng
- The First Clinical College of Zhejiang Chinese Medical University, Hangzhou, China
- Zhejiang Provincial Hospital of Traditional Chinese Medicine, Hangzhou, China
| | - Zhili Xu
- The First Clinical College of Zhejiang Chinese Medical University, Hangzhou, China
- Zhejiang Provincial Hospital of Traditional Chinese Medicine, Hangzhou, China
| | - Yong Guo
- The First Clinical College of Zhejiang Chinese Medical University, Hangzhou, China
- Zhejiang Provincial Hospital of Traditional Chinese Medicine, Hangzhou, China
- *Correspondence: Yong Guo, ; Ying Zhu,
| | - Ying Zhu
- The First Clinical College of Zhejiang Chinese Medical University, Hangzhou, China
- Zhejiang Provincial Hospital of Traditional Chinese Medicine, Hangzhou, China
- *Correspondence: Yong Guo, ; Ying Zhu,
| |
Collapse
|
8
|
Chen J, Shen S, Li Y, Fan J, Xiong S, Xu J, Zhu C, Lin L, Dong X, Duan W, Zhao Y, Qian X, Liu Z, Wei Y, Christiani DC, Zhang R, Chen F. APOLLO: An accurate and independently validated prediction model of lower-grade gliomas overall survival and a comparative study of model performance. EBioMedicine 2022; 79:104007. [PMID: 35436725 PMCID: PMC9035655 DOI: 10.1016/j.ebiom.2022.104007] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/15/2022] [Revised: 03/29/2022] [Accepted: 03/30/2022] [Indexed: 11/25/2022] Open
Abstract
BACKGROUND Virtually few accurate and robust prediction models of lower-grade gliomas (LGG) survival exist that may aid physicians in making clinical decisions. We aimed to develop a prognostic prediction model of LGG by incorporating demographic, clinical and transcriptional biomarkers with either main effects or gene-gene interactions. METHODS Based on gene expression profiles of 1,420 LGG patients from six independent cohorts comprising both European and Asian populations, we proposed a 3-D analysis strategy to develop and validate an Accurate Prediction mOdel of Lower-grade gLiomas Overall survival (APOLLO). We further conducted decision curve analysis to assess the net benefit (NB) of identifying true positives and the net reduction (NR) of unnecessary interventions. Finally, we compared the performance of APOLLO and the existing prediction models by the first systematic review. FINDINGS APOLLO possessed an excellent discriminative ability to identify patients at high mortality risk. Compared to those with less than the 20th percentile of APOLLO risk score, patients with more than the 90th percentile of APOLLO risk score had significantly worse overall survival (HR=54·18, 95% CI: 34·73-84·52, P=2·66 × 10-69). Further, APOLLO can accurately predict both 36- and 60-month survival in six independent cohorts with a pooled AUC36-month=0·901 (95% CI: 0·879-0·923), AUC60-month=0·843 (95% CI: 0·815-0·871) and C-index=0·818 (95% CI: 0·800-0·835). Moreover, APOLLO offered an effective screening strategy for detecting LGG patients susceptible to death (NB36-month=0·166, NR36-month=40·1% and NB60-month=0·258, NR60-month=19·2%). The systematic comparisons revealed APOLLO outperformed the existing models in accuracy and robustness. INTERPRETATION APOLLO has the demonstrated feasibility and utility of predicting LGG survival (http://bigdata.njmu.edu.cn/APOLLO). FUNDING National Key Research and Development Program of China (2016YFE0204900); Natural Science Foundation of Jiangsu Province (BK20191354); National Natural Science Foundation of China (81973142 and 82103946); China Postdoctoral Science Foundation (2020M681671); National Institutes of Health (CA209414, CA249096, CA092824 and ES000002).
Collapse
Affiliation(s)
- Jiajin Chen
- Department of Biostatistics, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, Jiangsu, China, 211166
| | - Sipeng Shen
- Department of Biostatistics, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, Jiangsu, China, 211166; China International Cooperation Center for Environment and Human Health, Nanjing Medical University, Nanjing, China, 211166
| | - Yi Li
- Department of Biostatistics, University of Michigan, Ann Arbor, MI, USA, 48109
| | - Juanjuan Fan
- Department of Biostatistics, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, Jiangsu, China, 211166
| | - Shiyu Xiong
- Department of Clinical Medicine, The First Clinical Medical College, Nanjing Medical University, Nanjing, Jiangsu, China, 211166
| | - Jingtong Xu
- Department of Clinical Medicine, The First Clinical Medical College, Nanjing Medical University, Nanjing, Jiangsu, China, 211166
| | - Chenxu Zhu
- Department of Biostatistics, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, Jiangsu, China, 211166
| | - Lijuan Lin
- Department of Biostatistics, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, Jiangsu, China, 211166
| | - Xuesi Dong
- Office of Cancer Screening, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China, 100021
| | - Weiwei Duan
- Department of Bioinformatics, School of Biomedical Engineering and Informatics, Nanjing Medical University, Nanjing, Jiangsu, China 211166
| | - Yang Zhao
- Department of Biostatistics, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, Jiangsu, China, 211166
| | - Xu Qian
- Department of Nutrition and Food Hygiene, Institute for Brain Tumors, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, China, 211166
| | - Zhonghua Liu
- Department of Statistics and Actuarial Science, the University of Hong Kong, Hong Kong, China, 999077
| | - Yongyue Wei
- Department of Biostatistics, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, Jiangsu, China, 211166; China International Cooperation Center for Environment and Human Health, Nanjing Medical University, Nanjing, China, 211166
| | - David C Christiani
- Pulmonary and Critical Care Division, Department of Medicine, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA, 02114.
| | - Ruyang Zhang
- Department of Biostatistics, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, Jiangsu, China, 211166; China International Cooperation Center for Environment and Human Health, Nanjing Medical University, Nanjing, China, 211166.
| | - Feng Chen
- Department of Biostatistics, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, Jiangsu, China, 211166; China International Cooperation Center for Environment and Human Health, Nanjing Medical University, Nanjing, China, 211166; Jiangsu Key Lab of Cancer Biomarkers, Prevention and Treatment, Cancer Center, Collaborative Innovation Center for Cancer Personalized Medicine, Nanjing Medical University, Nanjing, Jiangsu, China, 211166.
| |
Collapse
|
9
|
Screening and Validation of Significant Genes with Poor Prognosis in Pathologic Stage-I Lung Adenocarcinoma. JOURNAL OF ONCOLOGY 2022; 2022:3794021. [PMID: 35444699 PMCID: PMC9015852 DOI: 10.1155/2022/3794021] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 11/19/2021] [Accepted: 02/05/2022] [Indexed: 11/17/2022]
Abstract
Background Although more pathologic stage-I lung adenocarcinoma (LUAD) was diagnosed recently, some relapsed or distantly metastasized shortly after radical resection. The study aimed to identify biomarkers predicting prognosis in the pathologic stage-I LUAD and improve the understanding of the mechanisms involved in tumorigenesis. Methods We obtained the expression profiling data for non-small cell lung cancer (NSCLC) patients from the NCBI-GEO database. Differentially expressed genes (DEGs) between early-stage NSCLC and normal lung tissue were determined. After function enrichment analyses on DEGs, the protein-protein interaction (PPI) network was built and analyzed with the Search Tool for the Retrieval of Interacting Genes (STRING) and Cytoscape. Overall survival (OS) and mRNA levels of genes were performed with Kaplan–Meier analysis and Gene Expression Profiling Interactive Analysis (GEPIA). qPCR and western blot analysis of hub genes in stage-I LUAD patients validated the significant genes with poor prognosis. Results A total of 172 DEGs were identified, which were mainly enriched in terms related to management of extracellular matrix (ECM), receptor signaling pathway, cell adhesion, activity of endopeptidase, and receptor. The PPI network identified 11 upregulated hub genes that were significantly associated with OS in NSCLC and highly expressed in NSCLC tissues compared with normal tissues by GEPIA. Elevated expression of ANLN, EXO1, KIAA0101, RRM2, TOP2A, and UBE2T were identified as potential risk factors in pathologic stage-I LUAD. Except for ANLN and KIAA0101, the hub genes mRNA levels were higher in tumors compared with adjacent non-cancerous samples in the qPCR analysis. The hub genes protein levels were also overexpressed in tumors. In vitro experiments showed that knockdown of UBE2T in LUAD cell lines could inhibit cell proliferation and cycle progression. Conclusions The DEGs can probably be used as potential predictors for stage-I LUAD worse prognosis and UBE2T may be a potential tumor promoter and target for treatment.
Collapse
|
10
|
Zhou H, Meng M, Wang Z, Zhang H, Yang L, Li C, Zhang L. The Role of m5C-Related lncRNAs in Predicting Overall Prognosis and Regulating the Lower Grade Glioma Microenvironment. Front Oncol 2022; 12:814742. [PMID: 35372082 PMCID: PMC8971304 DOI: 10.3389/fonc.2022.814742] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/14/2021] [Accepted: 02/17/2022] [Indexed: 12/26/2022] Open
Abstract
Glioma is the most lethal primary brain tumor with a poor prognosis and high recurrence rate. Enormous efforts have been made to find therapeutic targets for gliomas. In the current study, we identified m5C-related lncRNAs through Pearson correlation analysis by the criteria |R|>0.5 and p<0.001 in TCGA LGG and CGGA325 datasets. We then established an eight-lncRNA m5C-related prognostic signature (m5C LPS) through lasso cox regression analysis and multivariate analysis. The performance of the signature was confirmed in the CGGA325 dataset and evaluated in differential subgroups divided by relevant clinicopathological characteristics. Patients were then divided into high and low risk groups using risk scores calculated with the signature. Next, we performed GO, KEGG and gene set enrichment analysis (GSEA) and identified the m5C LPS to be related with glioma microenvironment, immune response, EMT, cell cycle, and hypoxia. Correlation of the risk groups with immune cell infiltration, somatic mutation, and CNVs was then explored. Responses to immuno- and chemotherapies in different risk groups were evaluated using submap and pRRophetic R packages respectively. The high-risk group was more sensitive to anti-CTLA4 therapy and to compounds including Temozolomide, Bleomycin, Cisplatin, Cyclopamine, A.443654 (Akt inhibitor), AZD6482 (PI3K inhibitor), GDC0941(PI3K inhibitor), and metformin. We present for the first time a m5C-related lncRNA signature for lower grade glioma patient prognosis and therapy response prediction with validated performance, providing a promising target for future research.
Collapse
Affiliation(s)
- Hongshu Zhou
- Department of Neurosurgery, Xiangya Hospital, Central South University, Changsha, China
| | - Ming Meng
- Department of Neurosurgery, Xiangya Hospital, Central South University, Changsha, China
| | - Zeyu Wang
- Department of Neurosurgery, Xiangya Hospital, Central South University, Changsha, China
| | - Hao Zhang
- Department of Neurosurgery, Xiangya Hospital, Central South University, Changsha, China
| | - Liting Yang
- Department of Neurosurgery, Xiangya Hospital, Central South University, Changsha, China
- Hypothalamic Pituitary Research Center, Xiangya Hospital, Central South University, Changsha, China
- Brain Tumor Center, Xiangya Hospital, Central South University, Changsha, China
- National Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Central South University, Changsha, China
| | - Chuntao Li
- Department of Neurosurgery, Xiangya Hospital, Central South University, Changsha, China
- Hypothalamic Pituitary Research Center, Xiangya Hospital, Central South University, Changsha, China
- Brain Tumor Center, Xiangya Hospital, Central South University, Changsha, China
- National Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Central South University, Changsha, China
- *Correspondence: Liyang Zhang, ; Chuntao Li,
| | - Liyang Zhang
- Department of Neurosurgery, Xiangya Hospital, Central South University, Changsha, China
- Hypothalamic Pituitary Research Center, Xiangya Hospital, Central South University, Changsha, China
- Brain Tumor Center, Xiangya Hospital, Central South University, Changsha, China
- National Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Central South University, Changsha, China
- *Correspondence: Liyang Zhang, ; Chuntao Li,
| |
Collapse
|
11
|
Identification and validation of a cigarette smoke-related five-gene signature as a prognostic biomarker in kidney renal clear cell carcinoma. Sci Rep 2022; 12:2189. [PMID: 35140327 PMCID: PMC8828851 DOI: 10.1038/s41598-022-06352-y] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/05/2021] [Accepted: 01/27/2022] [Indexed: 11/08/2022] Open
Abstract
Cigarette smoking greatly promotes the progression of kidney renal clear cell carcinoma (KIRC), however, the underlying molecular events has not been fully established. In this study, RCC cells were exposed to the tobacco specific nitrosamine 4-(methylnitrosamino)-1-(3-pyridyl)-1-butanone (NNK, nicotine-derived nitrosamine) for 120 days (40 passages), and then the soft agar colony formation, wound healing and transwell assays were used to explore characteristics of RCC cells. RNA-seq was used to explore differentially expressed genes. We found that NNK promoted RCC cell growth and migration in a dose-dependent manner, and RNA-seq explored 14 differentially expressed genes. In TCGA-KIRC cohort, Lasso regression and multivariate COX regression models screened and constructed a five-gene signature containing ANKRD1, CYB5A, ECHDC3, MT1E, and AKT1S1. This novel gene signature significantly associated with TNM stage, invasion depth, metastasis, and tumor grade. Moreover, when compared with individual genes, the gene signature contained a higher hazard ratio and therefore had a more powerful value for the prognosis of KIRC. A nomogram was also developed based on clinical features and the gene signature, which showed good application. Finally, AKT1S1, the most crucial component of the gene signature, was significantly induced after NNK exposure and its related AKT/mTOR signaling pathway was dramatically activated. Our findings supported that NNK exposure would promote the KIRC progression, and the novel cigarette smoke-related five-gene signature might serve as a highly efficient biomarker to identify progression of KIRC patients, AKT1S1 might play an important role in cigarette smoke exposure-induced KIRC progression.
Collapse
|
12
|
Wu S, Zhang X, Rui W, Sheng Y, Yu Y, Zhang Y, Yao Z, Qiu T, Ren Y. A nomogram strategy for identifying the subclassification of IDH mutation and ATRX expression loss in lower-grade gliomas. Eur Radiol 2022; 32:3187-3198. [PMID: 35133485 DOI: 10.1007/s00330-021-08444-1] [Citation(s) in RCA: 11] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/11/2021] [Revised: 09/22/2021] [Accepted: 10/25/2021] [Indexed: 12/29/2022]
Abstract
OBJECTIVES To construct a radiomics nomogram based on multiparametric MRI data for predicting isocitrate dehydrogenase 1 mutation (IDH +) and loss of nuclear alpha thalassemia/mental retardation syndrome X-linked expression (ATRX -) in patients with lower-grade gliomas (LrGG; World Health Organization [WHO] 2016 grades II and III). METHODS A total of 111 LrGG patients (76 mutated IDH and 35 wild-type IDH) were enrolled, divided into a training set (n = 78) and a validation set (n = 33) for predicting IDH mutation. IDH + LrGG patients were further stratified into the ATRX - (n = 38) and ATRX + (n = 38) subtypes. A total of 250 radiomics features were extracted from the region of interest of each tumor, including that from T2 fluid-attenuated inversion recovery (T2 FLAIR), contrast-enhanced T1 WI, ASL-derived cerebral blood flow (CBF), DWI-derived ADC, and exponential ADC (eADC). A radiomics signature was selected using the Elastic Net regression model, and a radiomics nomogram was finally constructed using the age, gender information, and above features. RESULTS The radiomics nomogram identified LrGG patients for IDH mutation (C-index: training sets = 0.881, validation sets = 0.900) and ATRX loss (C-index: training sets = 0.863, validation sets = 0.840) with good calibration. Decision curve analysis further confirmed the clinical usefulness of the two nomograms for predicting IDH and ATRX status. CONCLUSIONS The nomogram incorporating age, gender, and the radiomics signature provided a clinically useful approach in noninvasively predicting IDH and ATRX mutation status for LrGG patients. The proposed method could facilitate MRI-based clinical decision-making for the LrGG patients. KEY POINTS • Non-invasive determination of IDH and ATRX gene status of LrGG patients can be obtained with a radiomics nomogram. • The proposed nomogram is constructed by radiomics signature selected from 250 radiomics features, combined with age and gender. • The proposed radiomics nomogram exhibited good calibration and discrimination for IDH and ATRX gene mutation stratification of LrGG patients in both training and validation sets.
Collapse
Affiliation(s)
- Shiman Wu
- Department of Radiology, Huashan Hospital, Fudan University, Jing'an District, 12 Middle Urumqi Road, Shanghai, 200040, People's Republic of China
| | - Xi Zhang
- Department of Biomedical Engineering, Fourth Military Medical University, Xi'an, Shaanxi, People's Republic of China
| | - Wenting Rui
- Department of Radiology, Huashan Hospital, Fudan University, Jing'an District, 12 Middle Urumqi Road, Shanghai, 200040, People's Republic of China
| | - Yaru Sheng
- Department of Radiology, Huashan Hospital, Fudan University, Jing'an District, 12 Middle Urumqi Road, Shanghai, 200040, People's Republic of China
| | - Yang Yu
- Department of Radiology, Huashan Hospital, Fudan University, Jing'an District, 12 Middle Urumqi Road, Shanghai, 200040, People's Republic of China
| | - Yong Zhang
- GE Healthcare, Shanghai, People's Republic of China
| | - Zhenwei Yao
- Department of Radiology, Huashan Hospital, Fudan University, Jing'an District, 12 Middle Urumqi Road, Shanghai, 200040, People's Republic of China
| | - Tianming Qiu
- Department of Neurosurgery, Huashan Hospital, Fudan University, Jing'an District, 12 Middle Urumqi Road, Shanghai, 200040, People's Republic of China.
| | - Yan Ren
- Department of Radiology, Huashan Hospital, Fudan University, Jing'an District, 12 Middle Urumqi Road, Shanghai, 200040, People's Republic of China.
| |
Collapse
|
13
|
Shi H, Zhong F, Yi X, Shi Z, Ou F, Zuo Y, Xu Z. The Construction of a Prognostic Model Based on a Peptidyl Prolyl Cis-Trans Isomerase Gene Signature in Hepatocellular Carcinoma. Front Genet 2021; 12:730141. [PMID: 34887898 PMCID: PMC8650315 DOI: 10.3389/fgene.2021.730141] [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: 06/24/2021] [Accepted: 10/25/2021] [Indexed: 11/16/2022] Open
Abstract
Objective: The aim of the present study was to construct a prognostic model based on the peptidyl prolyl cis–trans isomerase gene signature and explore the prognostic value of this model in patients with hepatocellular carcinoma. Methods: The transcriptome and clinical data of hepatocellular carcinoma patients were downloaded from The Cancer Genome Atlas and the International Cancer Genome Consortium database as the training set and validation set, respectively. Peptidyl prolyl cis–trans isomerase gene sets were obtained from the Molecular Signatures Database. The differential expression of peptidyl prolyl cis–trans isomerase genes was analyzed by R software. A prognostic model based on the peptidyl prolyl cis–trans isomerase signature was established by Cox, Lasso, and stepwise regression methods. Kaplan–Meier survival analysis was used to evaluate the prognostic value of the model and validate it with an independent external data. Finally, nomogram and calibration curves were developed in combination with clinical staging and risk score. Results: Differential gene expression analysis of hepatocellular carcinoma and adjacent tissues showed that there were 16 upregulated genes. A prognostic model of hepatocellular carcinoma was constructed based on three gene signatures by Cox, Lasso, and stepwise regression analysis. The Kaplan–Meier curve showed that hepatocellular carcinoma patients in high-risk score group had a worse prognosis (p < 0.05). The receiver operating characteristic curve revealed that the area under curve values of predicting the survival rate at 1, 2, 3, 4, and 5 years were 0.725, 0.680, 0.644, 0.630, and 0.639, respectively. In addition, the evaluation results of the model by the validation set were basically consistent with those of the training set. A nomogram incorporating clinical stage and risk score was established, and the calibration curve matched well with the diagonal. Conclusion: A prognostic model based on 3 peptidyl prolyl cis–trans isomerase gene signatures is expected to provide reference for prognostic risk stratification in patients with hepatocellular carcinoma.
Collapse
Affiliation(s)
- Huadi Shi
- Cancer Center, Affiliated Hospital of Guangdong Medical University, Zhanjiang, China
| | - Fulan Zhong
- Cancer Center, Affiliated Hospital of Guangdong Medical University, Zhanjiang, China
| | - Xiaoqiong Yi
- Cancer Center, Affiliated Hospital of Guangdong Medical University, Zhanjiang, China
| | - Zhenyi Shi
- Cancer Center, Affiliated Hospital of Guangdong Medical University, Zhanjiang, China
| | - Feiyan Ou
- Cancer Center, Affiliated Hospital of Guangdong Medical University, Zhanjiang, China
| | - Yufang Zuo
- Cancer Center, Affiliated Hospital of Guangdong Medical University, Zhanjiang, China
| | - Zumin Xu
- Cancer Center, Affiliated Hospital of Guangdong Medical University, Zhanjiang, China
| |
Collapse
|
14
|
Identification of Autophagy-Related Prognostic Signature and Analysis of Immune Cell Infiltration in Low-Grade Gliomas. BIOMED RESEARCH INTERNATIONAL 2021; 2021:7918693. [PMID: 34790823 PMCID: PMC8592714 DOI: 10.1155/2021/7918693] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 07/09/2021] [Revised: 10/15/2021] [Accepted: 10/21/2021] [Indexed: 12/21/2022]
Abstract
Autophagy plays an important role in cancer. Many studies have demonstrated that autophagy-related genes (ARGs) can act as a prognostic signature for some cancers, but little has been known in low-grade gliomas (LGG). In our study, we aimed to establish a prognostical model based on ARGs and find prognostic risk-related key genes in LGG. In the present study, a prognostic signature was constructed based on a total of 8 ARGs (MAPK8IP1, EEF2, GRID2, BIRC5, DLC1, NAMPT, GRID1, and TP73). It was revealed that the higher the risk score, the worse was the prognosis. Time-dependent ROC analysis showed that the risk score could precisely predict the prognosis of LGG patients. Additionally, four key genes (TGFβ2, SERPING1, SERPINE1, and TIMP1) were identified and found significantly associated with OS of LGG patients. Besides, they were also discovered to be strongly related to six types of immune cells which infiltrated in LGG tumor. Taken together, the present study demonstrated the promising potential of the ARG risk score formula as an independent factor for LGG prediction. It also provided the autophagy-related signature of prognosis and potential therapeutic targets for the treatment of LGG.
Collapse
|
15
|
Lin T, Cheng H, Liu D, Wen L, Kang J, Xu L, Shan C, Chen Z, Li H, Lai M, Zhou Z, Hong W, Hu Q, Li S, Zhou C, Geng J, Jin X. A Novel Six Autophagy-Related Genes Signature Associated With Outcomes and Immune Microenvironment in Lower-Grade Glioma. Front Genet 2021; 12:698284. [PMID: 34721517 PMCID: PMC8548643 DOI: 10.3389/fgene.2021.698284] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/21/2021] [Accepted: 09/22/2021] [Indexed: 11/13/2022] Open
Abstract
Since autophagy and the immune microenvironment are deeply involved in the tumor development and progression of Lower-grade gliomas (LGG), our study aimed to construct an autophagy-related risk model for prognosis prediction and investigate the relationship between the immune microenvironment and risk signature in LGG. Therefore, we identified six autophagy-related genes (BAG1, PTK6, EEF2, PEA15, ITGA6, and MAP1LC3C) to build in the training cohort (n = 305 patients) and verify the prognostic model in the validation cohort (n = 128) and the whole cohort (n = 433), based on the data from The Cancer Genome Atlas (TCGA). The six-gene risk signature could divide LGG patients into high- and low-risk groups with distinct overall survival in multiple cohorts (all p < 0.001). The prognostic effect was assessed by area under the time-dependent ROC (t-ROC) analysis in the training, validation, and whole cohorts, in which the AUC value at the survival time of 5 years was 0.837, 0.755, and 0.803, respectively. Cox regression analysis demonstrated that the risk model was an independent risk predictor of OS (HR > 1, p < 0.05). A nomogram including the traditional clinical parameters and risk signature was constructed, and t-ROC, C-index, and calibration curves confirmed its robust predictive capacity. KM analysis revealed a significant difference in the subgroup analyses' survival. Functional enrichment analysis revealed that these autophagy-related signatures were mainly involved in the phagosome and immune-related pathways. Besides, we also found significant differences in immune cell infiltration and immunotherapy targets between risk groups. In conclusion, we built a powerful predictive signature and explored immune components (including immune cells and emerging immunotherapy targets) in LGG.
Collapse
Affiliation(s)
- Tao Lin
- Department of Neurosurgery, Guangdong Sanjiu Brain Hospital, Guangzhou, China
| | - Hao Cheng
- Department of Nasopharyngeal Carcinoma, The First People's Hospital of Chenzhou, Southern Medical University, Chenzhou, China
| | - Da Liu
- Department of Neurosurgery, Guangdong Sanjiu Brain Hospital, Guangzhou, China
| | - Lei Wen
- Department of Oncology, Guangdong Sanjiu Brain Hospital, Guangzhou, China
| | - Junlin Kang
- Department of Neurosurgery, Lanzhou University First Hospital, Lanzhou, China
| | - Longwen Xu
- Department of Medical Oncology, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, China
| | - Changguo Shan
- Department of Oncology, Guangdong Sanjiu Brain Hospital, Guangzhou, China
| | - Zhijie Chen
- Department of Neurosurgery, Guangdong Sanjiu Brain Hospital, Guangzhou, China
| | - Hainan Li
- Department of Pathology, Guangdong Sanjiu Brain Hospital, Guangzhou, China
| | - Mingyao Lai
- Department of Oncology, Guangdong Sanjiu Brain Hospital, Guangzhou, China
| | - Zhaoming Zhou
- Department of Oncology, Guangdong Sanjiu Brain Hospital, Guangzhou, China
| | - Weiping Hong
- Department of Oncology, Guangdong Sanjiu Brain Hospital, Guangzhou, China
| | - Qingjun Hu
- Department of Oncology, Guangdong Sanjiu Brain Hospital, Guangzhou, China
| | - Shaoqun Li
- Department of Oncology, Guangdong Sanjiu Brain Hospital, Guangzhou, China
| | - Cheng Zhou
- Department of Radiation Oncology, Nanfang Hospital, Southern Medical University, Guangzhou, China
| | - Jiwu Geng
- Guangdong Key Laboratory of Occupational Disease Prevention and Treatment/Guangdong Province Hospital for Occupational Disease Prevention and Treatment, Guangzhou, China
| | - Xin Jin
- Department of Neurosurgery, Guangdong Sanjiu Brain Hospital, Guangzhou, China
| |
Collapse
|
16
|
Su W, Liao M, Tan H, Chen Y, Zhao R, Jin W, Zhu S, Zhang Y, He L, Liu B. Identification of autophagic target RAB13 with small-molecule inhibitor in low-grade glioma via integrated multi-omics approaches coupled with virtual screening of traditional Chinese medicine databases. Cell Prolif 2021; 54:e13135. [PMID: 34632655 PMCID: PMC8666277 DOI: 10.1111/cpr.13135] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/02/2021] [Revised: 09/08/2021] [Accepted: 09/20/2021] [Indexed: 02/05/2023] Open
Abstract
Objectives Autophagy, a highly conserved lysosomal degradation process in eukaryotic cells, has been widely reported closely related to the progression of many types of human cancers, including LGG; however, the intricate relationship between autophagy and LGG remains to be clarified. Materials and methods Multi‐omics methods were used to integrate omics data to determine potential autophagy regulators in LGG. The expression of ZFP36L2 and RAB13 in SW1088 cells was experimentally manipulated using cDNAs and small interfering RNAs (siRNA). RT‐qPCR detects RNAi gene knockout and cDNA overexpression efficiency. The expression levels of proteins in SW1088 cells were evaluated using Western blot analysis and immunofluorescence analysis. Homology modelling and molecular docking were used to identify compounds from Multi‐Traditional Chinese Medicine (TCM) Databases. The apoptosis ratios were determined by flow cytometry analysis of Annexin‐V/PI double staining. We detect the number of autophagosomes by GFP‐MRFP‐LC3 plasmid transfection to verify the process of autophagy flow. Results We integrated various omics data from LGG, including EXP, MET and CNA data, with the SNF method and the LASSO algorithm, and identified ZFP36L2 and RAB13 as positive regulators of autophagy, which are closely related to the core autophagy regulators. Both transcription level and protein expression level of the four autophagy regulators, including ULK1, FIP200, ATG16L1 and ATG2B, and LC3 puncta were increased by ZFP36L2 and RAB13 overexpression. In addition, RAB13 participates in autophagy through ATG2B, FIP200, ULK1, ATG16L1 and Beclin‐1. Finally, we screened multi‐TCM databases and identified gallic acid as a novel potential RAB13 inhibitor, which was confirmed to negatively regulate autophagy as well as to induce cell death in SW1088 cells. Conclusion Our study identified the key autophagic regulators ZFP36L2 and Rab13 in LGG progression, and demonstrated that gallic acid is a small molecular inhibitor of RAB13, which negatively regulates autophagy and provides a possible small molecular medicine for the subsequent treatment of LGG.
Collapse
Affiliation(s)
- Wei Su
- Department of Neurology and State Key Laboratory of Biotherapy and Cancer Center, West China Hospital, Sichuan University, Chengdu, China
| | - Minru Liao
- State Key Laboratory of Biotherapy and Cancer Center, West China Hospital, Sichuan University, Collaborative Innovation Center of Biotherapy, Chengdu, China
| | - Huidan Tan
- State Key Laboratory of Biotherapy and Cancer Center, West China Hospital, Sichuan University, Collaborative Innovation Center of Biotherapy, Chengdu, China
| | - Yanmei Chen
- State Key Laboratory of Biotherapy and Cancer Center, West China Hospital, Sichuan University, Collaborative Innovation Center of Biotherapy, Chengdu, China
| | - Rongyan Zhao
- State Key Laboratory of Biotherapy and Cancer Center, West China Hospital, Sichuan University, Collaborative Innovation Center of Biotherapy, Chengdu, China
| | - Wenke Jin
- State Key Laboratory of Biotherapy and Cancer Center, West China Hospital, Sichuan University, Collaborative Innovation Center of Biotherapy, Chengdu, China
| | - Shiou Zhu
- State Key Laboratory of Biotherapy and Cancer Center, West China Hospital, Sichuan University, Collaborative Innovation Center of Biotherapy, Chengdu, China
| | - Yiwen Zhang
- State Key Laboratory of Biotherapy and Cancer Center, West China Hospital, Sichuan University, Collaborative Innovation Center of Biotherapy, Chengdu, China
| | - Li He
- Department of Neurology and State Key Laboratory of Biotherapy and Cancer Center, West China Hospital, Sichuan University, Chengdu, China
| | - Bo Liu
- State Key Laboratory of Biotherapy and Cancer Center, West China Hospital, Sichuan University, Collaborative Innovation Center of Biotherapy, Chengdu, China
| |
Collapse
|
17
|
Establishment of an Immune-Related Gene Signature for Risk Stratification for Patients with Glioma. COMPUTATIONAL AND MATHEMATICAL METHODS IN MEDICINE 2021; 2021:2191709. [PMID: 34497663 PMCID: PMC8420975 DOI: 10.1155/2021/2191709] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 04/30/2021] [Revised: 07/14/2021] [Accepted: 08/11/2021] [Indexed: 12/14/2022]
Abstract
Glioma is a frequently seen primary malignant intracranial tumor, characterized by poor prognosis. The study is aimed at constructing a prognostic model for risk stratification in patients suffering from glioma. Weighted gene coexpression network analysis (WGCNA), integrated transcriptome analysis, and combining immune-related genes (IRGs) were used to identify core differentially expressed IRGs (DE IRGs). Subsequently, univariate and multivariate Cox regression analyses were utilized to establish an immune-related risk score (IRRS) model for risk stratification for glioma patients. Furthermore, a nomogram was developed for predicting glioma patients' overall survival (OS). The turquoise module (cor = 0.67; P < 0.001) and its genes (n = 1092) were significantly pertinent to glioma progression. Ultimately, multivariate Cox regression analysis constructed an IRRS model based on VEGFA, SOCS3, SPP1, and TGFB2 core DE IRGs, with a C-index of 0.811 (95% CI: 0.786-0.836). Then, Kaplan-Meier (KM) survival curves revealed that patients presenting high risk had a dismal outcome (P < 0.0001). Also, this IRRS model was found to be an independent prognostic indicator of gliomas' survival prediction, with HR of 1.89 (95% CI: 1.252-2.85) and 2.17 (95% CI: 1.493-3.14) in the Cancer Genome Atlas (TCGA) and Chinese Glioma Genome Atlas (CGGA) datasets, respectively. We established the IRRS prognostic model, capable of effectively stratifying glioma population, convenient for decision-making in clinical practice.
Collapse
|
18
|
Chen Y, Wang Y, He Q, Wang W, Zhang T, Wang Z, Dong J, Lan Q, Zhao J. Integrative analysis of TP73 profile prognostic significance in WHO grade II/III glioma. Cancer Med 2021; 10:4644-4657. [PMID: 34121368 PMCID: PMC8267133 DOI: 10.1002/cam4.4016] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/28/2021] [Revised: 04/24/2021] [Accepted: 04/26/2021] [Indexed: 12/17/2022] Open
Abstract
Due to the extremely intrinsic heterogeneity among glioma patients, the outcomes of these patients are tremendously different. Therefore, the exploitation of novel biomarker classification of glioma is vitally important for deep insight into the essence and predicting the prognosis of glioma. We aim to analyze the correlation between TP73 mRNA expression, DNA methylated alteration and the prognosis of WHO grade II/III glioma, utilizing bioinformatics to evaluate its significance as a risk‐factor in predicting the prognosis of these glioma patients. The analysis found that TP73 expression was positively correlated with the grade of glioma, and showed a strong correlation with glioma molecular classification, which revealed significantly higher TP73 expression in IDH‐wildtype than in IDH‐mutant subtype of WHO grade II/III glioma. Cox regression analysis indicated that high expression of TP73 shared an independent high‐risk factor impacting the prognosis of WHO grade II/III glioma. We discovered 8 DNA promoter methylation sites with prognostic significance, which were negatively associated with TP73 expression, and positively associated with beneficial overall survival (OS) and progression‐free survival (PFS). Integrating with four independent glioma datasets, subsequent Meta‐analysis verified that low expression of TP73 was closely related to favorable OS, especially in IDH‐mutant subtype. Moreover, we found that 1p/19qCodel/TP73low subgroup shared the most favorable OS, 1p/19qNon−codel/TP73high subgroup suffered the worst OS. Meanwhile, the enrichment analysis of TP73‐related differential mRNAs demonstrated that TP73 aberration in WHO grade II/III glioma might be closely related to cell cycle and P53 signaling pathways. Finally, TP73 expression of 53 glioma specimens was measured by qRT‐PCR, which was consistent with the previous analytical result, and TP73 high‐expression subgroup suffered worse PFS than TP73 low‐expression subgroup. In summary, our funding supports that TP73 gene can perform as a reliable biomarker to evaluate the survival outcome of patients diagnosed with WHO grade II/III glioma.
Collapse
Affiliation(s)
- Yanming Chen
- Department of Neurosurgery, The Second Affiliated Hospital of Soochow University, Suzhou, China.,China National Clinical Research Center for Neurological Diseases, Beijing, China
| | - Ye Wang
- Heath Management Center, The Second Affiliated Hospital of Soochow University, Suzhou, China
| | - Qiheng He
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - Wen Wang
- China National Clinical Research Center for Neurological Diseases, Beijing, China.,Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - Tan Zhang
- Department of Neurosurgery, The Second Affiliated Hospital of Soochow University, Suzhou, China
| | - Zhongyong Wang
- Department of Neurosurgery, The Second Affiliated Hospital of Soochow University, Suzhou, China
| | - Jun Dong
- Department of Neurosurgery, The Second Affiliated Hospital of Soochow University, Suzhou, China
| | - Qing Lan
- Department of Neurosurgery, The Second Affiliated Hospital of Soochow University, Suzhou, China
| | - Jizong Zhao
- Department of Neurosurgery, The Second Affiliated Hospital of Soochow University, Suzhou, China.,China National Clinical Research Center for Neurological Diseases, Beijing, China.,Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| |
Collapse
|
19
|
Li J, Pan Y, Chen J, Wang Y, Zhou H, Huang X, Liao S. Discoveries of the specific expression of lncRNAs and mRNAs in hippocampus of rats after traumatic brain injury. IBRAIN 2021; 7:95-107. [PMID: 37786908 PMCID: PMC10528755 DOI: 10.1002/j.2769-2795.2021.tb00071.x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/17/2021] [Revised: 05/21/2021] [Accepted: 06/24/2021] [Indexed: 10/04/2023]
Abstract
Objects Explore the relationship between the neural function deficit and the changes of lncRNA and mRNA in hippocampus after traumatic brain injury (TBI) in rats. Methods Twenty male rats weighted 200-240 grams were randomly divided into sham group and TBI group. Neurologic severity score (NSS) was performed after operation, and the hippocampus of rats was collected for long non-coding RNAs (lncRNAs), mRNAs microarray detection, real-time quantitative PCR Detecting System (Q-PCR), western blot (WB) detection, and serum biochemical detection. Results The NSS score of the TBI group was significantly higher than the sham group. Compared with the sham group, 270 lncRNAs changed in the TBI group, of which 224 were up-regulated and 46 were down-regulated. Among up-regulated lncRNAs, mRNAs were distributed in upstream of 22 lncRNAs, downstream of 17 lncRNAs, overlapping regions of 48 lncRNAs, and antisense chains of 21 lncRNAs. Among down-regulated lncRNAs, mRNAs were distributed in upstream of 6 lncRNAs, downstream of 3 lncRNAs, overlapping regions of 10 lncRNAs, and antisense chains of 8 lncRNAs. Compared with the sham group, 1054 mRNA changed in the TBI group, of which 921 mRNA were up-regulated and 133 mRNA were down-regulated. The expression changes of ENSRNOT000063054, ENSRNOT000052790, ENSRNOT00000054410, ENSRNOT000063242, and ENSRNOT000069411 IncRNA regulate the expression of Top2a, RT1-CE11, Papss2, Stk32a, and Grid2 gene. Conclusion The present study detected the differential expression of lncRNAs and mRNAs in hippocampi of rats subjected to TBI, and discussed their relation, primarily.
Collapse
Affiliation(s)
- Juan Li
- Department of AnesthesiologyWest China Hospital, Sichuan UniversityChengduSichuanChina
- Department of AnesthesiologyAffiliated Hospital of Zunyi Medical UniversityZunyiGuizhouChina
| | - Yuan‐Tao Pan
- National Traditional Chinese Medicine Clinical Research Base and Western Medicine Translational Medicine Research Center, Affiliated Traditional Chinese Medicine Hospital, Southwest Medical UniversityLuzhouSichuanChina
| | - Jun‐Jie Chen
- National Traditional Chinese Medicine Clinical Research Base and Western Medicine Translational Medicine Research Center, Affiliated Traditional Chinese Medicine Hospital, Southwest Medical UniversityLuzhouSichuanChina
| | - Yi Wang
- National Traditional Chinese Medicine Clinical Research Base and Western Medicine Translational Medicine Research Center, Affiliated Traditional Chinese Medicine Hospital, Southwest Medical UniversityLuzhouSichuanChina
| | - Hong‐Su Zhou
- Department of AnesthesiologyAffiliated Hospital of Zunyi Medical UniversityZunyiGuizhouChina
| | - Xue‐Yan Huang
- Department of neurologyAffiliated Hospital of Zunyi Medical UniversityZunyiGuizhouChina
| | - Shi‐Xia Liao
- Department of AnesthesiologyWest China Hospital, Sichuan UniversityChengduSichuanChina
| |
Collapse
|
20
|
Guo JC, Wei QS, Dong L, Fang SS, Li F, Zhao Y. Prognostic Value of an Autophagy-Related Five-Gene Signature for Lower-Grade Glioma Patients. Front Oncol 2021; 11:644443. [PMID: 33768004 PMCID: PMC7985555 DOI: 10.3389/fonc.2021.644443] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/21/2020] [Accepted: 02/15/2021] [Indexed: 12/16/2022] Open
Abstract
Background: Molecular characteristics can be good indicators of tumor prognosis and have been introduced into the classification of gliomas. The prognosis of patients with newly classified lower-grade gliomas (LGGs, including grade 2 and grade 3 gliomas) is highly heterogeneous, and new molecular markers are urgently needed. Methods: Autophagy related genes (ATGs) were obtained from Human Autophagy Database (HADb). From the Cancer Genome Atlas (TCGA) and the Chinese Glioma Genome Atlas (CGGA), gene expression profiles including ATG expression information and patient clinical data were downloaded. Cox regression analysis, receiver operating characteristic (ROC) analysis, Kaplan–Meier analysis, random survival forest algorithm (RSFVH) and stratification analysis were performed. Results: Through univariate Cox regression analysis, we found a total of 127 ATGs associated with the prognosis of LGG patients from TCGA dataset and a total of 131 survival-related ATGs from CGGA dataset. Using TCGA dataset as the training group (n = 524), we constructed a five-ATG signature (including BAG1, BID, MAP1LC3C, NRG3, PTK6), which could divide LGG patients into two risk groups with significantly different overall survival (Log Rank P < 0.001). Then we confirmed in the independent CGGA dataset that the five-ATG signature had the ability to predict prognosis (n = 431, Log Rank P < 0.001). We further discovered that the predictive ability of the five-ATG signature was better than the existing clinical indicators and IDH mutation status. In addition, the five-ATG signature could further classify patients after receiving radiotherapy or chemotherapy into groups with different prognosis. Conclusions: We identified a five-ATG signature that could be a reliable prognostic marker and might be therapeutic targets for autophagy therapy for LGG patients.
Collapse
Affiliation(s)
- Jin-Cheng Guo
- School of Traditional Chinese Medicine, Beijing University of Chinese Medicine, Beijing, China
| | - Qing-Shuang Wei
- School of Traditional Chinese Medicine, Beijing University of Chinese Medicine, Beijing, China
| | - Lei Dong
- School of Traditional Chinese Medicine, Beijing University of Chinese Medicine, Beijing, China
| | - Shuang-Sang Fang
- School of Traditional Chinese Medicine, Beijing University of Chinese Medicine, Beijing, China
| | - Feng Li
- School of Traditional Chinese Medicine, Beijing University of Chinese Medicine, Beijing, China
| | - Yi Zhao
- School of Traditional Chinese Medicine, Beijing University of Chinese Medicine, Beijing, China
| |
Collapse
|