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Pomella S, Melaiu O, Cifaldi L, Bei R, Gargari M, Campanella V, Barillari G. Biomarkers Identification in the Microenvironment of Oral Squamous Cell Carcinoma: A Systematic Review of Proteomic Studies. Int J Mol Sci 2024; 25:8929. [PMID: 39201614 PMCID: PMC11354375 DOI: 10.3390/ijms25168929] [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: 06/28/2024] [Revised: 07/30/2024] [Accepted: 08/05/2024] [Indexed: 09/02/2024] Open
Abstract
An important determinant for oral squamous cell carcinoma (OSCC) onset and outcome is the composition of the tumor microenvironment (TME). Thus, the study of the interactions occurring among cancer cells, immune cells, and cancer-associated fibroblasts within the TME could facilitate the understanding of the mechanisms underlying OSCC development and progression, as well as of its sensitivity or resistance to the therapy. In this context, it must be highlighted that the characterization of TME proteins is enabled by proteomic methodologies, particularly mass spectrometry (MS). Aiming to identify TME protein markers employable for diagnosing and prognosticating OSCC, we have retrieved a total of 119 articles spanning 2001 to 2023, of which 17 have passed the selection process, satisfying all its criteria. We have found a total of 570 proteins detected by MS-based proteomics in the TME of OSCC; among them, 542 are identified by a single study, while 28 are cited by two or more studies. These 28 proteins participate in extracellular matrix remodeling and/or energy metabolism. Here, we propose them as markers that could be used to characterize the TME of OSCC for diagnostic/prognostic purposes. Noteworthy, most of the 28 individuated proteins share one feature: being modulated by the hypoxia that is present in the proliferating OSCC mass.
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Affiliation(s)
| | | | | | | | | | | | - Giovanni Barillari
- Department of Clinical Sciences and Translational Medicine, University of Rome Tor Vergata, Via Montpellier, 00133 Rome, Italy; (S.P.); (O.M.); (L.C.); (R.B.); (M.G.); (V.C.)
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Xiao W, Tang P, Sui Z, Han Y, Zhao G, Wu X, Yang Y, Zhu N, Gong L, Yu Z, Zhang H. Establishment of a risk model by integrating hypoxia genes in predicting prognosis of esophageal squamous cell carcinoma. Cancer Med 2022; 12:2117-2133. [PMID: 35789548 PMCID: PMC9883439 DOI: 10.1002/cam4.5002] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/07/2022] [Revised: 06/03/2022] [Accepted: 06/11/2022] [Indexed: 02/02/2023] Open
Abstract
BACKGROUND Esophageal squamous cell carcinoma (ESCC) has a dismal prognosis, and hypoxia plays a key role in metastasis and proliferation of ESCC. Thus, we aimed to develop a hypoxia-based gene signature to assist in the treatment decisions and prognosis. METHODS We performed consensus clustering analysis on samples from GSE53625 dataset from the Gene Expression Omnibus (GEO) database and used weighted gene co-expression network analysis to filter out candidate modules, which were then intersected with differentially expressed genes from clustered subgroups to obtain hypoxia-related genes (HRGs). After that, the aforementioned genes were used to construct risk score models and validated in The Cancer Genome Atlas (TCGA) database and Cox regression analysis were used to construct a nomogram. Immunohistochemical was used to detect protein expression levels of relevant genes. Moreover, the relationship between risk scores and tumor microenvironment was explored. RESULTS A hypoxia risk model containing six genes (PNPLA1, CARD18, IL-18, SLC37A2, ADAMTS18, and FAM83C) was constructed by screening key HRGs. Poorer prognosis in the high-risk group than in the low-risk group. And Cox regression analysis showed that risk score was an independent prognostic factor. The nomogram based on risk scores could well predict 1-, 3-, and 5-year survival. P53, Wnt, and hypoxia signaling pathways may be some regulatory mechanisms of hypoxia associated with the tumor microenvironment. In addition, we confirmed the high expression of BGN and low expression of IL-18 in ESCC tissues. CONCLUSIONS Our study determined the prognostic value of a 6-hypoxia gene signature and a prognostic model, providing potential prognostic predictors and therapeutic targets for ESCC.
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Affiliation(s)
- Wanyi Xiao
- Department of Esophageal CancerTianjin Medical University Cancer Institute and Hospital, Key Laboratory of Cancer Prevention and Therapy of Tianjin, Tianjin's Clinical Research Center for Cancer, National Clinical Research Center for CancerTianjinChina
| | - Peng Tang
- Department of Esophageal CancerTianjin Medical University Cancer Institute and Hospital, Key Laboratory of Cancer Prevention and Therapy of Tianjin, Tianjin's Clinical Research Center for Cancer, National Clinical Research Center for CancerTianjinChina
| | - Zhilin Sui
- Department of Esophageal CancerTianjin Medical University Cancer Institute and Hospital, Key Laboratory of Cancer Prevention and Therapy of Tianjin, Tianjin's Clinical Research Center for Cancer, National Clinical Research Center for CancerTianjinChina,Department of Thoracic SurgeryNational Cancer Center, National Clinical Research Center for Cancer, Cancer Hospital & Shenzhen Hospital, Chinese Academy of Medical Sciences and PeKing Union Medical CollegeShenzhenChina
| | - Youming Han
- Department of Respiratory MedicineBinhai Hospital of Tianjin Medical University General HospitalTianjinChina
| | - Gang Zhao
- Department of Gastrointestinal Cancer BiologyTianjin Medical University Cancer Institute and Hospital, Key Laboratory of Cancer Prevention and Therapy of Tianjin, Tianjin's Clinical Research Center for Cancer, National Clinical Research Center for CancerTianjinChina
| | - Xianxian Wu
- Department of Thoracic SurgeryNational Cancer Center, National Clinical Research Center for Cancer, Cancer Hospital & Shenzhen Hospital, Chinese Academy of Medical Sciences and PeKing Union Medical CollegeShenzhenChina
| | - Yueyang Yang
- Department of Esophageal CancerTianjin Medical University Cancer Institute and Hospital, Key Laboratory of Cancer Prevention and Therapy of Tianjin, Tianjin's Clinical Research Center for Cancer, National Clinical Research Center for CancerTianjinChina
| | - Ningning Zhu
- Department of Esophageal CancerTianjin Medical University Cancer Institute and Hospital, Key Laboratory of Cancer Prevention and Therapy of Tianjin, Tianjin's Clinical Research Center for Cancer, National Clinical Research Center for CancerTianjinChina
| | - Lei Gong
- Department of Esophageal CancerTianjin Medical University Cancer Institute and Hospital, Key Laboratory of Cancer Prevention and Therapy of Tianjin, Tianjin's Clinical Research Center for Cancer, National Clinical Research Center for CancerTianjinChina
| | - Zhentao Yu
- Department of Thoracic SurgeryNational Cancer Center, National Clinical Research Center for Cancer, Cancer Hospital & Shenzhen Hospital, Chinese Academy of Medical Sciences and PeKing Union Medical CollegeShenzhenChina
| | - Hongdian Zhang
- Department of Esophageal CancerTianjin Medical University Cancer Institute and Hospital, Key Laboratory of Cancer Prevention and Therapy of Tianjin, Tianjin's Clinical Research Center for Cancer, National Clinical Research Center for CancerTianjinChina
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Hypoxia as a Modulator of Inflammation and Immune Response in Cancer. Cancers (Basel) 2022; 14:cancers14092291. [PMID: 35565420 PMCID: PMC9099524 DOI: 10.3390/cancers14092291] [Citation(s) in RCA: 14] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/22/2022] [Revised: 04/25/2022] [Accepted: 04/25/2022] [Indexed: 02/01/2023] Open
Abstract
A clear association between hypoxia and cancer has heretofore been established; however, it has not been completely developed. In this sense, the understanding of the tumoral microenvironment is critical to dissect the complexity of cancer, including the reduction in oxygen distribution inside the tumoral mass, defined as tumoral hypoxia. Moreover, hypoxia not only influences the tumoral cells but also the surrounding cells, including those related to the inflammatory processes. In this review, we analyze the participation of HIF, NF-κB, and STAT signaling pathways as the main components that interconnect hypoxia and immune response and how they modulate tumoral growth. In addition, we closely examine the participation of the immune cells and how they are affected by hypoxia, the effects of the progression of cancer, and some innovative applications that take advantage of this knowledge, to suggest potential therapies. Therefore, we contribute to the understanding of the complexity of cancer to propose innovative therapeutic strategies in the future.
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Han H, Chen Y, Yang H, Cheng W, Zhang S, Liu Y, Liu Q, Liu D, Yang G, Li K. Identification and Verification of Diagnostic Biomarkers for Glomerular Injury in Diabetic Nephropathy Based on Machine Learning Algorithms. Front Endocrinol (Lausanne) 2022; 13:876960. [PMID: 35663304 PMCID: PMC9162431 DOI: 10.3389/fendo.2022.876960] [Citation(s) in RCA: 15] [Impact Index Per Article: 7.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/16/2022] [Accepted: 04/14/2022] [Indexed: 11/25/2022] Open
Abstract
Diabetic nephropathy (DN) is regarded as the leading cause of end-stage renal disease worldwide and lacks novel therapeutic targets. To screen and verify special biomarkers for glomerular injury in patients with DN, fifteen datasets were retrieved from the Gene Expression Omnibus (GEO) database, correspondingly divided into training and testing cohorts and then merged. Using the limma package, 140 differentially expressed genes (DEGs) were screened out between 81 glomerular DN samples and 41 normal ones from the training cohort. With the help of the ConsensusClusterPlus and WGCNA packages, the 81 glomerular DN samples were distinctly divided into two subclusters, and two highly associated modules were identified. By using machine learning algorithms (LASSO, RF, and SVM-RFE) and the Venn diagram, two overlapping genes (PRKAR2B and TGFBI) were finally determined as potential biomarkers, which were further validated in external testing datasets and the HFD/STZ-induced mouse models. Based on the biomarkers, the diagnostic model was developed with reliable predictive ability for diabetic glomerular injury. Enrichment analyses indicated the apparent abnormal immune status in patients with DN, and the two biomarkers played an important role in the immune microenvironment. The identified biomarkers demonstrated a meaningful correlation between the immune cells' infiltration and renal function. In conclusion, two robust genes were identified as diagnostic biomarkers and may serve as potential targets for therapeutics of DN, which were closely associated with multiple immune cells.
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Affiliation(s)
- Hongdong Han
- Department of Endocrinology, the Second Affiliated Hospital, Chongqing Medical University, Chongqing, China
| | - Yanrong Chen
- Department of Endocrinology, the Second Affiliated Hospital, Chongqing Medical University, Chongqing, China
| | - Hao Yang
- Department of Endocrinology and Neurology, Jiulongpo People’s Hospital, Chongqing, China
| | - Wei Cheng
- Department of Endocrinology, the Second Affiliated Hospital, Chongqing Medical University, Chongqing, China
| | - Sijing Zhang
- Department of Endocrinology, the Second Affiliated Hospital, Chongqing Medical University, Chongqing, China
| | - Yunting Liu
- Department of Endocrinology, the Second Affiliated Hospital, Chongqing Medical University, Chongqing, China
| | - Qiuhong Liu
- Department of Endocrinology, the Second Affiliated Hospital, Chongqing Medical University, Chongqing, China
| | - Dongfang Liu
- Department of Endocrinology, the Second Affiliated Hospital, Chongqing Medical University, Chongqing, China
| | - Gangyi Yang
- Department of Endocrinology, the Second Affiliated Hospital, Chongqing Medical University, Chongqing, China
| | - Ke Li
- Department of Endocrinology, the Second Affiliated Hospital, Chongqing Medical University, Chongqing, China
- *Correspondence: Ke Li,
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Chen Y, Zhao H, Feng Y, Ye Q, Hu J, Guo Y, Feng Y. Pan-Cancer Analysis of the Associations of TGFBI Expression With Prognosis and Immune Characteristics. Front Mol Biosci 2021; 8:745649. [PMID: 34671645 PMCID: PMC8521171 DOI: 10.3389/fmolb.2021.745649] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/22/2021] [Accepted: 09/17/2021] [Indexed: 01/25/2023] Open
Abstract
Transforming growth factor-beta-induced (TGFBI) protein has important roles in tumor growth, metastasis, and immunity. However, there is currently no pan-cancer evidence regarding TGFBI. In this study, we conducted a pan-cancer analysis of TGFBI mRNA and protein expression and prognoses of various cancer types using public databases. We also investigated the associations of TGFBI expression with tumor microenvironment (TME) components, immune cell infiltration, tumor mutational burden (TMB), and microsatellite instability (MSI), along with the TGFBI genetic alteration types. The results showed that TGFBI expression varied among different cancer types, and it was positively or negatively related to prognosis in various cancers. TGFBI expression was also significantly correlated with TME components, TMB, MSI, immune cell infiltration, and immunoinhibitory and immunostimulatory gene subsets. These findings indicate that TGFBI participates in various immune responses and it may function as a prognostic marker in various cancers. The findings may be useful for developing immunotherapies that target TGFBI.
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Affiliation(s)
- Yun Chen
- Department of Stomatology, The Second Xiangya Hospital, Central South University, Changsha, China
| | - Han Zhao
- Department of Ophthalmology, Eye, Ear, Nose, and Throat Hospital of Fudan University, Shanghai, China
- Laboratory of Myopia, NHC Key Laboratory of Myopia (Fudan University), Chinese Academy of Medical Sciences, Shanghai, China
- Shanghai Key Laboratory of Visual Impairment and Restoration, Fudan University, Shanghai, China
| | - Yao Feng
- Department of Stomatology, The Second Xiangya Hospital, Central South University, Changsha, China
| | - Qin Ye
- Department of Stomatology, The Second Xiangya Hospital, Central South University, Changsha, China
| | - Jing Hu
- Department of Stomatology, The Second Xiangya Hospital, Central South University, Changsha, China
| | - Yue Guo
- Department of Stomatology, The Second Xiangya Hospital, Central South University, Changsha, China
| | - Yunzhi Feng
- Department of Stomatology, The Second Xiangya Hospital, Central South University, Changsha, China
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