1
|
Chen H, Zhang W, Shi J, Tang Y, Chen X, Li J, Yao X. Study on the mechanism of S100A4-mediated cancer oncogenesis in uveal melanoma cells through the integration of bioinformatics and in vitro experiments. Gene 2024; 911:148333. [PMID: 38431233 DOI: 10.1016/j.gene.2024.148333] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/14/2023] [Revised: 02/13/2024] [Accepted: 02/28/2024] [Indexed: 03/05/2024]
Abstract
BACKGROUND The elevated metastasis rate of uveal melanoma (UM) is intricately correlated with patient prognosis, significantly affecting the quality of life. S100 calcium-binding protein A4 (S100A4) has tumorigenic properties; therefore, the present study investigated the impact of S100A4 on UM cell proliferation, apoptosis, migration, and invasion using bioinformatics and in vitro experiments. METHODS Bioinformatic analysis was used to screen S100A4 as a hub gene and predict its possible mechanism in UM cells, and the S100A4 silencing cell line was constructed. The impact of S100A4 silencing on the proliferative ability of UM cells was detected using the Cell Counting Kit-8 and colony formation assays. Annexin V-FITC/PI double fluorescence and Hoechst 33342 staining were used to observe the effects of apoptosis on UM cells. The effect of S100A4 silencing on the migratory and invasive capabilities of UM cells was assessed using wound healing and Transwell assays. Western blotting was used to detect the expression of related proteins. RESULTS The present study found that S100A4 is a biomarker of UM, and its high expression is related to poor prognosis. After constructing the S100A4 silencing cell line, cell viability, clone number, proliferating cell nuclear antigen, X-linked inhibitor of apoptosis protein, and survivin expression were decreased in UM cells. The cell apoptosis rate and relative fluorescence intensity increased, accompanied by increased levels of Bax and caspase-3 and decreased levels of Bcl-2. Additionally, a decrease in the cell migration index and relative invasion rate was observed with increased E-cadherin expression and decreased N-cadherin and vimentin protein expression. CONCLUSION S100A4 silencing can inhibit the proliferation, migration, and invasion and synchronously induces apoptosis in UM cells.
Collapse
Affiliation(s)
- Huimei Chen
- The First Clinical College of Chinese Medicine, The First Affiliated Hospital of Hunan University of Chinese Medicine, Changsha, Hunan 410208, China; Hunan University of Chinese Medicine, Changsha, Hunan 410208, China; Hunan Provincial Key Laboratory for the Prevention and Treatment of Ophthalmology and Otolaryngology Diseases with Traditional Chinese Medicine, Changsha, Hunan 410208, China
| | - Wenqing Zhang
- The First Clinical College of Chinese Medicine, The First Affiliated Hospital of Hunan University of Chinese Medicine, Changsha, Hunan 410208, China; Hunan University of Chinese Medicine, Changsha, Hunan 410208, China; Hunan Provincial Key Laboratory for the Prevention and Treatment of Ophthalmology and Otolaryngology Diseases with Traditional Chinese Medicine, Changsha, Hunan 410208, China
| | - Jian Shi
- The First Clinical College of Chinese Medicine, The First Affiliated Hospital of Hunan University of Chinese Medicine, Changsha, Hunan 410208, China; Hunan University of Chinese Medicine, Changsha, Hunan 410208, China; Hunan Provincial Key Laboratory for the Prevention and Treatment of Ophthalmology and Otolaryngology Diseases with Traditional Chinese Medicine, Changsha, Hunan 410208, China
| | - Yu Tang
- The First Clinical College of Chinese Medicine, The First Affiliated Hospital of Hunan University of Chinese Medicine, Changsha, Hunan 410208, China; Hunan University of Chinese Medicine, Changsha, Hunan 410208, China; Hunan Provincial Key Laboratory for the Prevention and Treatment of Ophthalmology and Otolaryngology Diseases with Traditional Chinese Medicine, Changsha, Hunan 410208, China
| | - Xiong Chen
- The First Clinical College of Chinese Medicine, The First Affiliated Hospital of Hunan University of Chinese Medicine, Changsha, Hunan 410208, China; Hunan University of Chinese Medicine, Changsha, Hunan 410208, China; Hunan Provincial Key Laboratory for the Prevention and Treatment of Ophthalmology and Otolaryngology Diseases with Traditional Chinese Medicine, Changsha, Hunan 410208, China
| | - Jiangwei Li
- The First Clinical College of Chinese Medicine, The First Affiliated Hospital of Hunan University of Chinese Medicine, Changsha, Hunan 410208, China; Hunan University of Chinese Medicine, Changsha, Hunan 410208, China; Hunan Provincial Key Laboratory for the Prevention and Treatment of Ophthalmology and Otolaryngology Diseases with Traditional Chinese Medicine, Changsha, Hunan 410208, China
| | - Xiaolei Yao
- The First Clinical College of Chinese Medicine, The First Affiliated Hospital of Hunan University of Chinese Medicine, Changsha, Hunan 410208, China; Hunan University of Chinese Medicine, Changsha, Hunan 410208, China; Hunan Provincial Key Laboratory for the Prevention and Treatment of Ophthalmology and Otolaryngology Diseases with Traditional Chinese Medicine, Changsha, Hunan 410208, China.
| |
Collapse
|
2
|
Yong X, Kang T, Li T, Li S, Hu X, Yan X, Zhang F, Zheng J, Yang Q. Identification of multiomics map and key biomarkers in uveal melanoma with chromosome 3 loss. Ann Med Surg (Lond) 2024; 86:831-841. [PMID: 38333293 PMCID: PMC10849387 DOI: 10.1097/ms9.0000000000001585] [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: 11/06/2023] [Accepted: 11/24/2023] [Indexed: 02/10/2024] Open
Abstract
Purpose Chromosome 3 loss is an independent risk factor for uveal melanoma (UM), but its exact molecular mechanisms remain unclear. This study was designed to investigate the relationship between chromosome 3 loss and molecular alterations at multiple levels to construct a prognostic model. Methods Forty-four UM cases with chromosome 3 loss (chr3 del group) and 36 UM cases without copy number variation on chromosome 3 (chr3 wt group) were collected from the Cancer Genome Atlas (TCGA). The TCGA dataset was subjected to a univariate Cox regression analysis to identify different expressed genes, and a subsequent random forest algorithm analysis revealed significant changes in different expressed genes, which were used to develop key biomarkers for UM. Following that, the immune cell infiltration analysis and drug sensitivity analyses were carried out. The UM cell line was then utilized to investigate the potential functions of the key biomarker via cell apoptosis, proliferation, cycle assays, WB, and RT-qPCR. Results By analyzing the 80 cases data in TCGA, the authors unveiled molecular changes relevant to loss of chromosome 3 in UM as well as their poor survival. In addition, machine learning analysis identified three hub genes (GRIN2A, ACAN, and MMP9) as potential therapeutic targets. The differentially enriched pathways between the two groups were mainly about immune-system activity, and hub genes expression was also highly correlated with immune infiltration levels. Conclusion Chromosome 3 loss has considerable clinical significance for UM, and GRIN2A may be useful in diagnosing, treating, and prognosticating the condition.
Collapse
Affiliation(s)
- Xi Yong
- Vascular Surgery Department of Affiliated Hospital of North Sichuan Medical College
- Hepatobiliary, Pancreatic and Intestinal Research Institute of North Sichuan Medical College
| | - Tengyao Kang
- Vascular Surgery Department of Affiliated Hospital of North Sichuan Medical College
- Department of Clinical Medicine, North Sichuan Medical College
| | - Tingting Li
- Department of Pharmacy, The Second Affiliated Hospital of North Sichuan Medical College
- Department of Pharmacology, School of Pharmacy, Guangxi Medical University, Nanning, Guangxi, People’s Republic of China
| | - Sixuan Li
- Vascular Surgery Department of Affiliated Hospital of North Sichuan Medical College
| | - Xuerui Hu
- Endocrine Department of Affiliated Hospital of North Sichuan Medical College, Nanchong, Sichuan
| | - Xiang Yan
- Vascular Surgery Department of Affiliated Hospital of North Sichuan Medical College
| | - Fuzhao Zhang
- Vascular Surgery Department of Affiliated Hospital of North Sichuan Medical College
| | - Jianghua Zheng
- Vascular Surgery Department of Affiliated Hospital of North Sichuan Medical College
| | - Qin Yang
- Infectious Diseases D of Affiliated Hospital of North Sichuan Medical College
| |
Collapse
|
3
|
Wang J, Liu M, Sun J, Zhang Z. Immunogenic profiling of metastatic uveal melanoma discerns a potential signature related to prognosis. J Cancer Res Clin Oncol 2024; 150:23. [PMID: 38246894 PMCID: PMC10800307 DOI: 10.1007/s00432-023-05542-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: 10/03/2023] [Accepted: 11/27/2023] [Indexed: 01/23/2024]
Abstract
BACKGROUND Uveal melanoma (UM) is an aggressive intraocular malignant tumor. The present study aimed to identify the key genes associated with UM metastasis and established a gene signature to analyze the relationship between the signature and prognosis and immune cell infiltration. Later, a predictive model combined with clinical variables was developed and validated. METHODS Two UM gene expression profile chip datasets were downloaded from TCGA and GEO databases. Immune-related genes (IRGs) were obtained from IMPORT database. First, these mRNAs were intersected with IRGs, and weighted gene co-expression network analysis (WGCNA) was used to identify the co-expression of genes primarily associated with metastasis of UM. Univariate Cox regression analysis screened the genes related to prognosis. LASSO-Cox established a risk score to distinguish high-risk group and low-risk group. Then the GSEA enrichment pathway and immune cell infiltration of the two groups were compared. And combined with clinical variables, a predictive model was constructed. The time-dependent receiver operating characteristic (ROC) curve, calibration curve, and decision curve analysis (DCA) curve were used to verify the stability and accuracy of the final predictive model, and a nomogram was then drawn. RESULTS The MEblack, MEpurple, and MEblue modules were significantly associated with the metastasis of UM patients (P value < 0.001, = 0.001, = 0.022, respectively). Four genes (UBXN2B, OTUD3, KAT8, LAMTOR2) were obtained by Pearson correlation analysis, weighted gene correlation network analysis (WGCNA), univariate Cox, and LASSO-Cox. And a novel prognostic risk score was established. Immune-related prognostic signature can well classify UM patients into high-risk and low-risk groups. Kaplan-Meier curve showed that the OS of high-risk patients was worse than that of low-risk patients. In addition, the risk score played an important role in evaluating the signaling pathway and immune cell infiltration of UM patients in high-risk and low-risk groups. Both the training set and validation set of the model showed good predictive accuracy in the degree of differentiation and calibration (e.g., 1-year overall survival: AUC = 0.930 (0.857-1.003)). Finally, a nomogram was established to serve in clinical practice. SIGNIFICANCE UM key gene signature and prognosis predictive model might provide insights for further investigation of the pathogenesis and development of UM at the molecular level, and provide theoretical basis for determining new prognostic markers of UM and immunotherapy.
Collapse
Affiliation(s)
- Jian Wang
- Department of Neurosurgery, Tangdu Hospital, Fourth Military Medical University, Xi'an, China
| | - Miaomiao Liu
- Department of Respiratory, Tangdu Hospital, Fourth Military Medical University, Xi'an, China
| | - Jiaxing Sun
- Department of Ophthalmology, Eye Institute of Chinese PLA, Xijing Hospital, Fourth Military Medical University, Xi'an, 710032, China
| | - Zifeng Zhang
- Department of Ophthalmology, Eye Institute of Chinese PLA, Xijing Hospital, Fourth Military Medical University, Xi'an, 710032, China.
| |
Collapse
|
4
|
Le VH, Minh TNT, Kha QH, Le NQK. A transfer learning approach on MRI-based radiomics signature for overall survival prediction of low-grade and high-grade gliomas. Med Biol Eng Comput 2023; 61:2699-2712. [PMID: 37432527 DOI: 10.1007/s11517-023-02875-2] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/21/2023] [Accepted: 06/20/2023] [Indexed: 07/12/2023]
Abstract
Lower-grade gliomas (LGG) can eventually progress to glioblastoma (GBM) and death. In the context of the transfer learning approach, we aimed to train and test an MRI-based radiomics model for predicting survival in GBM patients and validate it in LGG patients. From each patient's 704 MRI-based radiomics features, we chose seventeen optimal radiomics signatures in the GBM training set (n = 71) and used these features in both the GBM testing set (n = 31) and LGG validation set (n = 107) for further analysis. Each patient's risk score, calculated based on those optimal radiomics signatures, was chosen to represent the radiomics model. We compared the radiomics model with clinical, gene status models, and combined model integrating radiomics, clinical, and gene status in predicting survival. The average iAUCs of combined models in training, testing, and validation sets were respectively 0.804, 0.878, and 0.802, and those of radiomics models were 0.798, 0.867, and 0.717. The average iAUCs of gene status and clinical models ranged from 0.522 to 0.735 in all three sets. The radiomics model trained in GBM patients can effectively predict the overall survival of GBM and LGG patients, and the combined model improved this ability.
Collapse
Affiliation(s)
- Viet Huan Le
- International Ph.D. Program in Medicine, College of Medicine, Taipei Medical University, Taipei, 110, Taiwan
- Department of Thoracic Surgery, Khanh Hoa General Hospital, Nha Trang City, 65000, Vietnam
| | - Tran Nguyen Tuan Minh
- International Ph.D. Program in Medicine, College of Medicine, Taipei Medical University, Taipei, 110, Taiwan
| | - Quang Hien Kha
- International Ph.D. Program in Medicine, College of Medicine, Taipei Medical University, Taipei, 110, Taiwan
| | - Nguyen Quoc Khanh Le
- Professional Master Program in Artificial Intelligence in Medicine, College of Medicine, Taipei Medical University, Taipei, 110, Taiwan.
- Research Center for Artificial Intelligence in Medicine, Taipei Medical University, Taipei, 110, Taiwan.
- AIBioMed Research Group, Taipei Medical University, Taipei, 110, Taiwan.
- Translational Imaging Research Center, Taipei Medical University Hospital, Taipei, 110, Taiwan.
| |
Collapse
|
5
|
Li Y, Xiong C, Wu LL, Zhang BY, Wu S, Chen YF, Xu QH, Liao HF. Tumor subtypes and signature model construction based on chromatin regulators for better prediction of prognosis in uveal melanoma. Pathol Oncol Res 2023; 29:1610980. [PMID: 37362244 PMCID: PMC10287976 DOI: 10.3389/pore.2023.1610980] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/29/2022] [Accepted: 05/26/2023] [Indexed: 06/28/2023]
Abstract
Background: Uveal Melanoma (UM) is the most prevalent primary intraocular malignancy in adults. This study assessed the importance of chromatin regulators (CRs) in UM and developed a model to predict UM prognosis. Methods: Gene expression data and clinical information for UM were obtained from public databases. Samples were typed according to the gene expression of CRs associated with UM prognosis. The prognostic key genes were further screened by the protein interaction network, and the risk model was to predict UM prognosis using the least absolute shrinkage and selection operator (LASSO) regression analysis and performed a test of the risk mode. In addition, we performed gene set variation analysis, tumor microenvironment, and tumor immune analysis between subtypes and risk groups to explore the mechanisms influencing the development of UM. Results: We constructed a signature model consisting of three CRs (RUVBL1, SIRT3, and SMARCD3), which was shown to be accurate, and valid for predicting prognostic outcomes in UM. Higher immune cell infiltration in poor prognostic subtypes and risk groups. The Tumor immune analysis and Tumor Immune Dysfunction and Exclusion (TIDE) score provided a basis for clinical immunotherapy in UM. Conclusion: The risk model has prognostic value for UM survival and provides new insights into the treatment of UM.
Collapse
Affiliation(s)
- Yue Li
- School of Ophthalmology and Optometry, Nanchang University, Nanchang, Jiangxi, China
- Affiliated Eye Hospital of Nanchang University, Nanchang, Jiangxi, China
- National Clinical Research Center for Ocular Diseases Jiangxi Province Division, Nanchang, Jiangxi, China
- Jiangxi Clinical Research Center for Ophthalmic Disease, Nanchang, Jiangxi, China
| | - Chao Xiong
- School of Ophthalmology and Optometry, Nanchang University, Nanchang, Jiangxi, China
- Affiliated Eye Hospital of Nanchang University, Nanchang, Jiangxi, China
- National Clinical Research Center for Ocular Diseases Jiangxi Province Division, Nanchang, Jiangxi, China
- Jiangxi Clinical Research Center for Ophthalmic Disease, Nanchang, Jiangxi, China
| | - Li Li Wu
- School of Ophthalmology and Optometry, Nanchang University, Nanchang, Jiangxi, China
- Affiliated Eye Hospital of Nanchang University, Nanchang, Jiangxi, China
- National Clinical Research Center for Ocular Diseases Jiangxi Province Division, Nanchang, Jiangxi, China
- Jiangxi Clinical Research Center for Ophthalmic Disease, Nanchang, Jiangxi, China
| | - Bo Yuan Zhang
- School of Ophthalmology and Optometry, Nanchang University, Nanchang, Jiangxi, China
- Affiliated Eye Hospital of Nanchang University, Nanchang, Jiangxi, China
- National Clinical Research Center for Ocular Diseases Jiangxi Province Division, Nanchang, Jiangxi, China
- Jiangxi Clinical Research Center for Ophthalmic Disease, Nanchang, Jiangxi, China
| | - Sha Wu
- School of Ophthalmology and Optometry, Nanchang University, Nanchang, Jiangxi, China
- Affiliated Eye Hospital of Nanchang University, Nanchang, Jiangxi, China
- National Clinical Research Center for Ocular Diseases Jiangxi Province Division, Nanchang, Jiangxi, China
- Jiangxi Clinical Research Center for Ophthalmic Disease, Nanchang, Jiangxi, China
| | - Yu Fen Chen
- School of Ophthalmology and Optometry, Nanchang University, Nanchang, Jiangxi, China
- Affiliated Eye Hospital of Nanchang University, Nanchang, Jiangxi, China
- National Clinical Research Center for Ocular Diseases Jiangxi Province Division, Nanchang, Jiangxi, China
- Jiangxi Clinical Research Center for Ophthalmic Disease, Nanchang, Jiangxi, China
| | - Qi Hua Xu
- School of Ophthalmology and Optometry, Nanchang University, Nanchang, Jiangxi, China
- Affiliated Eye Hospital of Nanchang University, Nanchang, Jiangxi, China
- National Clinical Research Center for Ocular Diseases Jiangxi Province Division, Nanchang, Jiangxi, China
- Jiangxi Clinical Research Center for Ophthalmic Disease, Nanchang, Jiangxi, China
| | - Hong Fei Liao
- School of Ophthalmology and Optometry, Nanchang University, Nanchang, Jiangxi, China
- Affiliated Eye Hospital of Nanchang University, Nanchang, Jiangxi, China
- National Clinical Research Center for Ocular Diseases Jiangxi Province Division, Nanchang, Jiangxi, China
- Jiangxi Clinical Research Center for Ophthalmic Disease, Nanchang, Jiangxi, China
| |
Collapse
|
6
|
Tabatabai MA, Bahri N, Matthews-Juarez P, Alcendor D, Cooper R, Juarez P, Ramesh A, Tabatabai N, Singh KP, Wilus D. The role of histological subtypes in the survival of patients diagnosed with cutaneous or mucosal melanoma in the United States of America. PLoS One 2023; 18:e0286538. [PMID: 37276224 PMCID: PMC10241359 DOI: 10.1371/journal.pone.0286538] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/09/2022] [Accepted: 05/18/2023] [Indexed: 06/07/2023] Open
Abstract
BACKGROUND Literature presents limited information on histological subtypes and their association with other factors influencing the survival of melanoma patients. To explore the risk of death due to melanoma associated with histological subtypes, this retrospective study used the Surveillance, Epidemiology, and End Results program (SEER) data from 1998 to 2019. METHODS A total of 27,532 patients consisting of 15,527 males and 12,005 females. The Hypertabastic Accelerated Failure Time model was used to analyze the impact of histology on the survival of patients with cutaneous or mucosal melanoma. RESULTS The median survival time (MST) for cutaneous patients was 149 months, whereas those diagnosed with mucosal melanoma was 34 months. Nodular melanoma had a hazard ratio of 3.40 [95% CI: (2.94, 3.94)] compared to lentigo maligna melanoma. Across all histological subtypes, females had a longer MST, when compared to males. The hazard ratio (HR) of distant to localized melanoma was 9.56 [95% CI: (7.58, 12.07)]. CONCLUSIONS Knowledge of patients' histological subtypes and their hazard assessment would enable clinicians and healthcare providers to perform personalized treatment, resulting in a lower risk of complication and higher survivability of melanoma patients. Significant factors were stage of the disease, age, histology, sex, and income. Focus should be placed on high-risk populations with severe and aggressive histological subtypes. Programs that emphasize preventive measures such as awareness, education, and early screening could reduce risk.
Collapse
Affiliation(s)
| | - Nader Bahri
- Meharry Medical College, Nashville, TN, United States of America
| | | | - Donald Alcendor
- Meharry Medical College, Nashville, TN, United States of America
| | - Robert Cooper
- Meharry Medical College, Nashville, TN, United States of America
| | - Paul Juarez
- Meharry Medical College, Nashville, TN, United States of America
| | - Aramandla Ramesh
- Meharry Medical College, Nashville, TN, United States of America
| | - Niki Tabatabai
- University of California Los Angeles, Los Angeles, CA, United States of America
| | - Karan P. Singh
- University of Texas Health Sciences Center at Tyler, Tyler, TX, United States of America
| | - Derek Wilus
- Meharry Medical College, Nashville, TN, United States of America
| |
Collapse
|
7
|
Li X, Kang J, Yue J, Xu D, Liao C, Zhang H, Zhao J, Liu Q, Jiao J, Wang L, Li G. Identification and validation of immunogenic cell death-related score in uveal melanoma to improve prediction of prognosis and response to immunotherapy. Aging (Albany NY) 2023; 15:3442-3464. [PMID: 37142279 PMCID: PMC10449274 DOI: 10.18632/aging.204680] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/13/2023] [Accepted: 04/17/2023] [Indexed: 05/06/2023]
Abstract
BACKGROUND Immunogenic cell death (ICD) could activate innate and adaptive immune response. In this work, we aimed to develop an ICD-related signature in uveal melanoma (UVM) patients and facilitate assessment of their prognosis and immunotherapy. METHODS A set of machine learning methods, including non-negative matrix factorization (NMF) method and least absolute shrinkage and selection operator (LASSO) logistic regression model, and bioinformatics analytic tools were integrated to construct an ICD-related risk score (ICDscore). CIBERSORT and ESTIMATE algorithms were used to evaluate the infiltration of immune cells. The Genomics of Drug Sensitivity in Cancer (GDSC), cellMiner and tumor immune dysfunction and exclusion (TIDE) databases were used for therapy sensitivity analyses. The predictive performance between ICDscore with other mRNA signatures was also compared. RESULTS The ICDscore could predict the prognosis of UVM patients in both the training and four validating cohorts. The ICDscore outperformed 19 previously published signatures. Patients with high ICDscore exhibited a substantial increase in immune cell infiltration and expression of immune checkpoint inhibitor-related genes, leading to a higher response rate to immunotherapy. Furthermore, the downregulation of poly (ADP-ribose) polymerase family member 8 (PARP8), a critical gene involved in the development of the ICDscore, resulted in decreased cell proliferation and slower migration of UVM cells. CONCLUSION In conclusion, we developed a robust and powerful ICD-related signature for evaluating the prognosis and benefits of immunotherapy that could serve as a promising tool to guide decision-making and surveillance for UVM patients.
Collapse
Affiliation(s)
- Xiaoyan Li
- Department of Central Laboratory, Shanxi Provincial People’s Hospital, Taiyuan, Shanxi, China
- Department of Blood Transfusion, Shanxi Provincial People’s Hospital, Taiyuan, Shanxi, China
| | - Jing Kang
- Department of Clinical Laboratory, Shanxi Bethune Hospital, Shanxi Academy of Medical Sciences, Tongji Shanxi Hospital, Third Hospital of Shanxi Medical University, Taiyuan, Shanxi, China
| | - Jing Yue
- Department of Clinical Laboratory, Shanxi Bethune Hospital, Shanxi Academy of Medical Sciences, Tongji Shanxi Hospital, Third Hospital of Shanxi Medical University, Taiyuan, Shanxi, China
| | - Dawei Xu
- Department of Blood Transfusion, Shanxi Provincial People’s Hospital, Taiyuan, Shanxi, China
| | - Chunhua Liao
- Department of Physiotherapy and Rehabilitation, The Second Affiliated Hospital of Air Force Military Medical University, Xi'an, Shaanxi, China
| | - Huina Zhang
- College of Life Science and Agronomy, Zhoukou Normal University, Zhoukou, Henan, China
| | - Jin Zhao
- College of Life Science and Agronomy, Zhoukou Normal University, Zhoukou, Henan, China
| | - Qiongwen Liu
- College of Life Science and Agronomy, Zhoukou Normal University, Zhoukou, Henan, China
| | - Jinke Jiao
- College of Life Science and Agronomy, Zhoukou Normal University, Zhoukou, Henan, China
| | - Lin Wang
- Department of Geriatrics, Xijing Hospital, The Air Force Military Medical University, Xi'an, Shaanxi, China
| | - Guoyin Li
- College of Life Science and Agronomy, Zhoukou Normal University, Zhoukou, Henan, China
- Key Laboratory of Modern Teaching Technology, Ministry of Education, Shaanxi Normal University, Xi’an, Shaanxi, China
- Academy of Medical Science, Zhengzhou University, Zhengzhou, Henan, China
| |
Collapse
|
8
|
Meng S, Zhu T, Fan Z, Cheng Y, Dong Y, Wang F, Wang X, Dong D, Yuan S, Zhao X. Integrated single-cell and transcriptome sequencing analyses develops a metastasis-based risk score system for prognosis and immunotherapy response in uveal melanoma. Front Pharmacol 2023; 14:1138452. [PMID: 36843929 PMCID: PMC9947539 DOI: 10.3389/fphar.2023.1138452] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/05/2023] [Accepted: 01/30/2023] [Indexed: 02/11/2023] Open
Abstract
Background: Uveal melanoma (UM) is the most frequent ocular neoplasm with a strong metastatic ability. The prognostic value of metastasis-associated genes (MAGs) of UM remains unclear. It is urgent to develop a prognostic score system according to the MAGs of UM. Methods: Unsupervised clustering was used to identify MAGs-based molecular subtypes. Cox methods were utilized to generate a prognostic score system. The prognostic ability of the score system was detected by plotting ROC and survival curves. The immune activity and underlying function were depicted by CIBERSORT GSEA algorithms. Results: Gene cluster analysis determined two MAGs-based subclusters in UM, which were remarkably different in clinical outcomes. A risk score system containing six MAGs (COL11A1, AREG, TIMP3, ADAM12, PRRX1 and GAS1) was set up. We employed ssGSEA to compare immune activity and immunocyte infiltration between the two risk groups. Notch, JAK/STAT and mTOR pathways were greatly enriched in the high-risk group. Furthermore, we observed that knockdown of AREG could inhibit UM proliferation and metastasis by in vitro assays. Conclusion: The MAGs-based subtype and score system in UM can enhance prognosis assessment, and the core system provides valuable reference for clinical decision-making.
Collapse
Affiliation(s)
| | - Tianye Zhu
- Department of Ophthalmology, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China
| | - Zhiwei Fan
- School of Medicine, Nantong University, Nantong, China
| | - Yulan Cheng
- Nantong Key Laboratory of Environmental Toxicology, Department of Occupational Medicine and Environmental Toxicology, School of Public Health, Nantong University, Nantong, China
| | | | - Fengxu Wang
- Nantong Key Laboratory of Environmental Toxicology, Department of Occupational Medicine and Environmental Toxicology, School of Public Health, Nantong University, Nantong, China
| | - Xuehai Wang
- Nantong Key Laboratory of Environmental Toxicology, Department of Occupational Medicine and Environmental Toxicology, School of Public Health, Nantong University, Nantong, China
| | - Deping Dong
- Hai an People’s Hospital, Nantong, China,*Correspondence: Deping Dong, ; Songtao Yuan, ; Xinyuan Zhao,
| | - Songtao Yuan
- Department of Ophthalmology, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China,*Correspondence: Deping Dong, ; Songtao Yuan, ; Xinyuan Zhao,
| | - Xinyuan Zhao
- Nantong Key Laboratory of Environmental Toxicology, Department of Occupational Medicine and Environmental Toxicology, School of Public Health, Nantong University, Nantong, China,*Correspondence: Deping Dong, ; Songtao Yuan, ; Xinyuan Zhao,
| |
Collapse
|
9
|
Lactate Rewrites the Metabolic Reprogramming of Uveal Melanoma Cells and Induces Quiescence Phenotype. Int J Mol Sci 2022; 24:ijms24010024. [PMID: 36613471 PMCID: PMC9820521 DOI: 10.3390/ijms24010024] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/10/2022] [Revised: 12/15/2022] [Accepted: 12/15/2022] [Indexed: 12/24/2022] Open
Abstract
Uveal melanoma (UM), the most common primary intraocular cancer in adults, is among the tumors with poorer prognosis. Recently, the role of the oncometabolite lactate has become attractive due to its role as hydroxycarboxylic acid receptor 1 (HCAR1) activator, as an epigenetic modulator inducing lysine residues lactylation and, of course, as a glycolysis end-product, bridging the gap between glycolysis and oxidative phosphorylation. The aim of the present study was to dissect in UM cell line (92.1) the role of lactate as either a metabolite or a signaling molecule, using the known modulators of HCAR1 and of lactate transporters. Our results show that lactate (20 mM) resulted in a significant decrease in cell proliferation and migration, acting and switching cell metabolism toward oxidative phosphorylation. These results were coupled with increased euchromatin content and quiescence in UM cells. We further showed, in a clinical setting, that an increase in lactate transporters MCT4 and HCAR1 is associated with a spindle-shape histological type in UM. In conclusion, our results suggest that lactate metabolism may serve as a prognostic marker of UM progression and may be exploited as a potential therapeutic target.
Collapse
|
10
|
Machine Learning-Based Integration Develops a Pyroptosis-Related lncRNA Model to Enhance the Predicted Value of Low-Grade Glioma Patients. JOURNAL OF ONCOLOGY 2022; 2022:8164756. [PMID: 35646114 PMCID: PMC9135526 DOI: 10.1155/2022/8164756] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 02/24/2022] [Accepted: 04/26/2022] [Indexed: 12/22/2022]
Abstract
Background Molecular features have been included in the categorization of gliomas because they may be excellent predictors of tumor prognosis. Lower-grade glioma (LGGs, which comprise grade 2 and grade 3 gliomas) patients have a wide variety of outcomes. The goal of this research is to investigate a pyroptosis-based long noncoding RNA (lncRNA) profile and see whether it can be used to predict LGG prognosis. Methods The Genotype-Tissue Expression (GTEx) and Cancer Genome Atlas (TCGA) datasets were utilized to get RNA data and clinical information for this research. Six considerably related lncRNAs (AL355574.1, AL355974.2, Z97989.1, SNAI3-AS1, LINC02593, and CYTOR) were selected using Cox regression (univariate and multivariate) and LASSO Cox regression. A variety of statistical techniques, including ROC curves, nomogram, and Kaplan-Meier curves, were utilized to verify the risk score's accuracy. Following that, bioinformatics studies were carried out to investigate the possible molecular processes that influence LGG prognosis. The variations in pathway enrichment were investigated using GSEA. The immune microenvironment inconsistencies were investigated using CIBERSORT, ESTIMATE, MCPcounter, TIMER algorithms, and ssGSEA. Results We discovered six lncRNAs with distinct expression patterns that are linked to LGG prognosis. Kaplan-Meier studies showed a signature of high-risk lncRNAs associated with a poor prognosis for LGG. Furthermore, the AUC of the lncRNA signature was 0.763, indicating that they may be used to predict LGG prognosis. In predicting LGG prognosis, our risk assessment approach outperformed conventional clinicopathological characteristics. In the high-risk group of people, GSEA identified tumor-related pathways and immune-related pathways. Furthermore, T cell-related activities such as T cell coinhibition and costimulation, check point, APC coinhibition and costimulation, CCR, and inflammatory promoting were shown to be substantially different between the two groups in TCGA analysis. Immune checkpoints including PD-1, CTLA4, and PD-L1 were expressed differentially in the two groups as well. Conclusion This study found that pyroptosis-based lncRNAs were useful in predicting LGG patients' survival, suggesting that they may be used as a therapeutic target in the future.
Collapse
|
11
|
Shi K, Li X, Zhang J, Sun X. Development and Validation of a Novel Metabolic Signature-Based Prognostic Model for Uveal Melanoma. Transl Vis Sci Technol 2022; 11:9. [PMID: 35536719 PMCID: PMC9100464 DOI: 10.1167/tvst.11.5.9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/24/2022] Open
Abstract
Purpose Uveal melanoma (UM) is the most common primary malignant tumor with poor prognosis. The role of metabolism-related genes in the prognosis of UM remains unrevealed. This study aimed to establish and validate a prognostic prediction model for UM based on metabolism-related genes. Methods Gene expression profiles and clinicopathological information were downloaded from The Cancer Genome Atlas, and the Gene Expression Omnibus database. Univariable Cox regression, least absolute shrinkage and selection operator Cox regression, and stepwise regression were performed to establish the model. Kaplan-Meier survival analysis, receiver operating characteristic (ROC) curve analysis, and calibration and discrimination analyses were used to evaluate the prognostic model. Results Three metabolism-related genes, carbonic anhydrase 12, acyl-CoA synthetase long-chain family member 3, and synaptojanin 2, and three clinicopathological parameters (i.e., age, gender, and metastasis staging) were identified to establish the model. The risk score was found to be an independent prognostic factor for UM survival. High-risk patients demonstrated significantly poorer prognosis than low-risk patients. ROC analysis suggested the promising prognostic efficiency of the model. The calibration curve manifested satisfactory agreement between the predicted and observed risk. A nomogram and online survival calculator were developed to predict the survival probability. Conclusions The novel metabolism-based prognostic model could accurately predict the prognosis of UM patients, which facilitates the prediction of the survival probability by both ophthalmologists and patients with the online dynamic nomogram. Translational Relevance The dynamic nomogram links gene expression profiles to clinical prognosis of UM and is useful to evaluate the survival probability.
Collapse
Affiliation(s)
- Ke Shi
- Department of Ophthalmology, Shanghai General Hospital, Shanghai Jiao Tong University, School of Medicine, Shanghai, China.,National Clinical Research Center for Eye Diseases, Shanghai, China.,Shanghai Key Laboratory of Fundus Diseases, Shanghai, China.,Shanghai Engineering Center for Visual Science and Photomedicine, Shanghai, China
| | - Xinxin Li
- Department of Ophthalmology, Shanghai General Hospital, Shanghai Jiao Tong University, School of Medicine, Shanghai, China.,National Clinical Research Center for Eye Diseases, Shanghai, China.,Shanghai Key Laboratory of Fundus Diseases, Shanghai, China.,Shanghai Engineering Center for Visual Science and Photomedicine, Shanghai, China
| | - Jingfa Zhang
- Department of Ophthalmology, Shanghai General Hospital, Shanghai Jiao Tong University, School of Medicine, Shanghai, China.,National Clinical Research Center for Eye Diseases, Shanghai, China.,Shanghai Key Laboratory of Fundus Diseases, Shanghai, China.,Shanghai Engineering Center for Visual Science and Photomedicine, Shanghai, China
| | - Xiaodong Sun
- Department of Ophthalmology, Shanghai General Hospital, Shanghai Jiao Tong University, School of Medicine, Shanghai, China.,National Clinical Research Center for Eye Diseases, Shanghai, China.,Shanghai Key Laboratory of Fundus Diseases, Shanghai, China.,Shanghai Engineering Center for Visual Science and Photomedicine, Shanghai, China
| |
Collapse
|
12
|
Caban M, Owczarek K, Lewandowska U. The Role of Metalloproteinases and Their Tissue Inhibitors on Ocular Diseases: Focusing on Potential Mechanisms. Int J Mol Sci 2022; 23:ijms23084256. [PMID: 35457074 PMCID: PMC9026850 DOI: 10.3390/ijms23084256] [Citation(s) in RCA: 13] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/01/2022] [Revised: 04/04/2022] [Accepted: 04/09/2022] [Indexed: 02/01/2023] Open
Abstract
Eye diseases are associated with visual impairment, reduced quality of life, and may even lead to vision loss. The efficacy of available treatment of eye diseases is not satisfactory. The unique environment of the eye related to anatomical and physiological barriers and constraints limits the bioavailability of existing agents. In turn, complex ethiopathogenesis of ocular disorders that used drugs generally are non-disease specific and do not act causally. Therefore, there is a need for the development of a new therapeutic and preventive approach. It seems that matrix metalloproteinases (MMPs) and tissue inhibitors of metalloproteinases (TIMPs) have a significant role in the development and progression of eye diseases and could be used in the therapy of these disorders as pharmacological targets. MMPs and TIMPs play an important role in the angiogenesis, epithelial-mesenchymal transition, cell invasion, and migration, which occur in ocular diseases. In this review, we aim to describe the participation of MMPs and TIMPs in the eye diseases, such as age-related macular degeneration, cataract, diabetic retinopathy, dry eye syndrome, glaucoma, and ocular cancers, posterior capsule opacification focusing on potential mechanisms.
Collapse
|
13
|
Lei S, Zhang Y. Integrative analysis identifies key genes related to metastasis and a robust gene-based prognostic signature in uveal melanoma. BMC Med Genomics 2022; 15:61. [PMID: 35300699 PMCID: PMC8932077 DOI: 10.1186/s12920-022-01211-1] [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: 08/20/2021] [Accepted: 03/10/2022] [Indexed: 11/10/2022] Open
Abstract
PURPOSE Uveal melanoma (UM) is an aggressive intraocular malignancy, leading to systemic metastasis in half of the patients. However, the mechanism of the high metastatic rate remains unclear. This study aimed to identify key genes related to metastasis and construct a gene-based signature for better prognosis prediction of UM patients. METHODS Weighted gene co-expression network analysis (WGCNA) was used to identify the co-expression of genes primarily associated with metastasis of UM. Univariate, Lasso-penalized and multivariate Cox regression analyses were performed to establish a prognostic signature for UM patients. RESULTS The tan and greenyellow modules were significantly associated with the metastasis of UM patients. Significant genes related to the overall survival (OS) in these two modules were then identified. Additionally, an OS-predicting signature was established. The UM patients were divided into a low- or high-risk group. The Kaplan-Meier curve indicated that high-risk patients had poorer OS than low-risk patients. The receiver operating curve (ROC) was used to validate the stability and accuracy of the final five-gene signature. Based on the signature and clinical traits of UM patients, a nomogram was established to serve in clinical practice. CONCLUSIONS We identified key genes involved in the metastasis of UM. A robust five-gene-based prognostic signature was constructed and validated. In addition, the gene signature-based nomogram was created that can optimize the prognosis prediction and identify possible factors causing the poor prognosis of high-risk UM patients.
Collapse
Affiliation(s)
- Shizhen Lei
- Department of Ophthalmology, The Fourth Affiliated Hospital of China Medical University, Shenyang, 110032, China
| | - Yi Zhang
- Department of Gerontology and Geriatrics, Shengjing Hospital of China Medical University, 36 Sanhao Road, Shenyang, 110004, China.
| |
Collapse
|
14
|
Prognostic Biomarkers in Uveal Melanoma: The Status Quo, Recent Advances and Future Directions. Cancers (Basel) 2021; 14:cancers14010096. [PMID: 35008260 PMCID: PMC8749988 DOI: 10.3390/cancers14010096] [Citation(s) in RCA: 21] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/23/2021] [Revised: 12/15/2021] [Accepted: 12/23/2021] [Indexed: 01/18/2023] Open
Abstract
Simple Summary Although rare, uveal melanoma (UM) is the most common cancer that develops inside adult eyes. The prognosis is poor, since 50% of patients will develop lethal metastases in the first decade, especially to the liver. Once metastases are detected, life expectancy is limited, given that the available treatments are mostly unsuccessful. Thus, there is a need to find methods that can accurately predict UM prognosis and also effective therapeutic strategies to treat this cancer. In this manuscript, we initially compile the current knowledge on epidemiological, clinical, pathological and molecular features of UM. Then, we cover the most relevant prognostic factors currently used for the evaluation and follow-up of UM patients. Afterwards, we highlight emerging molecular markers in UM published over the last three years. Finally, we discuss the problems preventing meaningful advances in the treatment and prognostication of UM patients, as well as forecast new roadblocks and paths of UM-related research. Abstract Uveal melanoma (UM) is the most common malignant intraocular tumour in the adult population. It is a rare cancer with an incidence of nearly five cases per million inhabitants per year, which develops from the uncontrolled proliferation of melanocytes in the choroid (≈90%), ciliary body (≈6%) or iris (≈4%). Patients initially present either with symptoms like blurred vision or photopsia, or without symptoms, with the tumour being detected in routine eye exams. Over the course of the disease, metastases, which are initially dormant, develop in nearly 50% of patients, preferentially in the liver. Despite decades of intensive research, the only approach proven to mildly control disease spread are early treatments directed to ablate liver metastases, such as surgical excision or chemoembolization. However, most patients have a limited life expectancy once metastases are detected, since there are limited therapeutic approaches for the metastatic disease, including immunotherapy, which unlike in cutaneous melanoma, has been mostly ineffective for UM patients. Therefore, in order to offer the best care possible to these patients, there is an urgent need to find robust models that can accurately predict the prognosis of UM, as well as therapeutic strategies that effectively block and/or limit the spread of the metastatic disease. Here, we initially summarized the current knowledge about UM by compiling the most relevant epidemiological, clinical, pathological and molecular data. Then, we revisited the most important prognostic factors currently used for the evaluation and follow-up of primary UM cases. Afterwards, we addressed emerging prognostic biomarkers in UM, by comprehensively reviewing gene signatures, immunohistochemistry-based markers and proteomic markers resulting from research studies conducted over the past three years. Finally, we discussed the current hurdles in the field and anticipated the future challenges and novel avenues of research in UM.
Collapse
|
15
|
Ozhan A, Tombaz M, Konu O. Discovery of Cancer-Specific and Independent Prognostic Gene Subsets of the Slit-Robo Family Using TCGA-PANCAN Datasets. OMICS-A JOURNAL OF INTEGRATIVE BIOLOGY 2021; 25:782-795. [PMID: 34757814 DOI: 10.1089/omi.2021.0097] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/12/2022]
Abstract
The Slit-Robo family of axon guidance molecules works in concert, playing important roles in organ development and cancer. Expressions of individual Slit-Robo genes have been used in calculating univariable hazard ratios (HRuni) for predicting cancer prognosis in the literature. However, Slit-Robo members do not act independently; hence, hazard ratios from multivariable Cox regression (HRmulti) on the whole gene set can further lead to identification of cancer-specific, novel, and independent prognostic gene pairs or modules. Herein, we obtained mRNA expressions of the Slit-Robo family consisting of four Robos (ROBO1/2/3/4) and three Slits (SLIT1/2/3), along with four types of survival outcome across cancers found in the Cancer Genome Atlas (TCGA). We used cluster heat maps to visualize closely associated pairs/modules of prognostic genes across 33 different cancers. We found a smaller number of significant genes in HRmulti than in HRuni, suggesting that the former analysis was less redundant. High ROBO4 expression emerged as relatively protective within the family, in both types of HR analyses. Multivariable Cox regression, on the other hand, revealed significantly more HR signatures containing Slit-Robo pairs acting in opposing directions than those containing Slit-Slit or Robo-Robo pairs for disease-specific survival. Furthermore, we discovered, through the online app SmulTCan's lasso regression, Slit-Robo gene subsets that significantly differentiated between high- versus low-risk prognosis patient groups, particularly for renal cancers and low-grade glioma. The statistical pipeline reported herein can help test independent and significant pairs/modules within a codependent gene family for cancer prognostication, and thus should also prove useful in personalized/precision medicine research.
Collapse
Affiliation(s)
- Ayse Ozhan
- UNAM-National Nanotechnology Research Center, Institute of Material Science and Nanotechnology, Bilkent University, Ankara, Turkey
| | - Melike Tombaz
- Department of Molecular Biology and Genetics, Faculty of Science, Bilkent University, Ankara, Turkey
| | - Ozlen Konu
- UNAM-National Nanotechnology Research Center, Institute of Material Science and Nanotechnology, Bilkent University, Ankara, Turkey.,Department of Molecular Biology and Genetics, Faculty of Science, Bilkent University, Ankara, Turkey.,Interdisciplinary Graduate Program in Neuroscience, Aysel Sabuncu Brain Research Center, Bilkent University, Ankara, Turkey
| |
Collapse
|
16
|
SmulTCan: A Shiny application for multivariable survival analysis of TCGA data with gene sets. Comput Biol Med 2021; 137:104793. [PMID: 34488031 DOI: 10.1016/j.compbiomed.2021.104793] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/13/2021] [Revised: 08/20/2021] [Accepted: 08/21/2021] [Indexed: 12/13/2022]
Abstract
BACKGROUND Survival analysis is widely used in cancer research, and although several methods exist in R, there is the need for a more interactive, flexible, yet comprehensive online tool to analyze gene sets using Cox proportional hazards (CPH) models. The web-based Shiny application (app) SmulTCan extends existing tools to multivariable CPH models of gene sets-as exemplified using the netrins and their receptors (netrins-receptors). It can be used to identify survival gene signatures (GSs) and select the best subsets of input gene, microRNA, methylation level, and copy number variation sets from the Cancer Genome Atlas (TCGA). OBJECTIVES To create a tool for CPH model building and best subset selection, using survival data from TCGA with input gene expression files from UCSC Xena. Furthermore, we aim to analyze the input TSV file of netrins-receptors in SmulTCan and discuss our findings. METHODS SmulTCan uses Shiny's reactivity with built-in R functions from packages for CPH model analysis and best subset selection including "survminer", "riskRegression", "rms", "glmnet", and "BeSS". RESULTS Results from the SmulTCan app with the netrins-receptors gene set indicated unique hazard ratio GSs in certain renal and neural cancers, while the best subsets for this gene set, obtained via the app, could differentiate between prognostic outcomes in these cancers. AVAILABILITY SmulTCan is available at http://konulabapps.bilkent.edu.tr:3838/SmulTCan/. The input file for netrins-receptors is available in the online version of this paper. TCGA dataset folders containing survival files are available through https://github.com/aozh7/SmulTCan/. SUPPLEMENTARY INFORMATION The supplementary information (SI) accompanies the online version of this article.
Collapse
|
17
|
A Novel 8-Gene Prognostic Signature for Survival Prediction of Uveal Melanoma. ACTA ACUST UNITED AC 2021; 2021:6693219. [PMID: 34434692 PMCID: PMC8382551 DOI: 10.1155/2021/6693219] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/11/2020] [Revised: 07/11/2021] [Accepted: 07/28/2021] [Indexed: 02/03/2023]
Abstract
Background Uveal melanoma (UM) has favorable local tumor control, but once metastasis develops, the prognosis is rather poor. Thus, it is urgent to develop metastasis predicting markers. Objective Our study investigated a novel gene expression-based signature in predicting metastasis for patients with UM. Methods In the discovery phase, 63 patients with UM from GEO data set GSE22138 were analyzed using the Weighted Correlation Network Analysis (WGCNA) to identify metastasis-related hub genes. The Least Absolute Shrinkage and Selection Operator (Lasso) Cox regression was used to select candidate genes and build a gene expression signature. In the validation phase, the signature was validated in The Cancer Genome Atlas database. Results Forty-one genes were identified as hub genes of metastasis by WGCNA. After the Lasso Cox regression analysis, eight genes including RPL10A, EIF1B, TIPARP, RPL15, SLC25A38, PHLDA1, TFDP2, and MEGF10 were highlighted as candidate predictors. The gene expression signature for UM (UMPS) could independently predict MFS by univariate and multivariate Cox regression analysis. Incorporating UMPS increased the AUC of the traditional clinical model. In the validation cohort, UMPS performed well in predicting the MFS of UM patients. Conclusions UMPS, an eight-gene-based signature, is useful in predicting prognosis for patients with UM.
Collapse
|
18
|
Le VH, Kha QH, Hung TNK, Le NQK. Risk Score Generated from CT-Based Radiomics Signatures for Overall Survival Prediction in Non-Small Cell Lung Cancer. Cancers (Basel) 2021; 13:cancers13143616. [PMID: 34298828 PMCID: PMC8304936 DOI: 10.3390/cancers13143616] [Citation(s) in RCA: 25] [Impact Index Per Article: 8.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/15/2021] [Revised: 07/14/2021] [Accepted: 07/16/2021] [Indexed: 12/17/2022] Open
Abstract
Simple Summary Despite recent advancements in lung cancer treatment, individuals with lung cancer have a dismal 5-year survival rate of only 15%. In patients with non-small cell lung cancer (NSCLC), medical images have lately been employed as a valuable marker for predicting overall survival. The primary goal of this study was to develop a risk score based on computed tomography (CT) based radiomics feature signatures that may be used to predict survival in NSCLC patients. After analyzing 577 NSCLC patients from two data sets, we discovered that the risk score model’s prediction ability as a prognostic indicator was superior to other clinical indicators (age, stage, and gender), and the possibility of patient risk stratification with survival was evaluated using a risk score representation of 10 radiomics signatures. According to this study, the risk score generated using CT-based radiomics signatures promises to predict overall survival in NSCLC patients. Abstract This study aimed to create a risk score generated from CT-based radiomics signatures that could be used to predict overall survival in patients with non-small cell lung cancer (NSCLC). We retrospectively enrolled three sets of NSCLC patients (including 336, 84, and 157 patients for training, testing, and validation set, respectively). A total of 851 radiomics features for each patient from CT images were extracted for further analyses. The most important features (strongly linked with overall survival) were chosen by pairwise correlation analysis, Least Absolute Shrinkage and Selection Operator (LASSO) regression model, and univariate Cox proportional hazard regression. Multivariate Cox proportional hazard model survival analysis was used to create risk scores for each patient, and Kaplan–Meier was used to separate patients into two groups: high-risk and low-risk, respectively. ROC curve assessed the prediction ability of the risk score model for overall survival compared to clinical parameters. The risk score, which developed from ten radiomics signatures model, was found to be independent of age, gender, and stage for predicting overall survival in NSCLC patients (HR, 2.99; 95% CI, 2.27–3.93; p < 0.001) and overall survival prediction ability was 0.696 (95% CI, 0.635–0.758), 0.705 (95% CI, 0.649–0.762), 0.657 (95% CI, 0.589–0.726) (AUC) for 1, 3, and 5 years, respectively, in the training set. The risk score is more likely to have a better accuracy in predicting survival at 1, 3, and 5 years than clinical parameters, such as age 0.57 (95% CI, 0.499–0.64), 0.552 (95% CI, 0.489–0.616), 0.621 (95% CI, 0.544–0.689) (AUC); gender 0.554, 0.546, 0.566 (AUC); stage 0.527, 0.501, 0.459 (AUC), respectively, in 1, 3 and 5 years in the training set. In the training set, the Kaplan–Meier curve revealed that NSCLC patients in the high-risk group had a lower overall survival time than the low-risk group (p < 0.001). We also had similar results that were statistically significant in the testing and validation set. In conclusion, risk scores developed from ten radiomics signatures models have great potential to predict overall survival in NSCLC patients compared to the clinical parameters. This model was able to stratify NSCLC patients into high-risk and low-risk groups regarding the overall survival prediction.
Collapse
Affiliation(s)
- Viet-Huan Le
- International Master/Ph.D. Program in Medicine, College of Medicine, Taipei Medical University, Taipei 110, Taiwan; (V.-H.L.); (Q.-H.K.); (T.N.K.H.)
- Department of Thoracic Surgery, Khanh Hoa General Hospital, Nha Trang City 65000, Vietnam
| | - Quang-Hien Kha
- International Master/Ph.D. Program in Medicine, College of Medicine, Taipei Medical University, Taipei 110, Taiwan; (V.-H.L.); (Q.-H.K.); (T.N.K.H.)
| | - Truong Nguyen Khanh Hung
- International Master/Ph.D. Program in Medicine, College of Medicine, Taipei Medical University, Taipei 110, Taiwan; (V.-H.L.); (Q.-H.K.); (T.N.K.H.)
- Department of Orthopedic and Trauma, Cho Ray Hospital, Ho Chi Minh City 70000, Vietnam
| | - Nguyen Quoc Khanh Le
- International Master/Ph.D. Program in Medicine, College of Medicine, Taipei Medical University, Taipei 110, Taiwan; (V.-H.L.); (Q.-H.K.); (T.N.K.H.)
- Professional Master Program in Artificial Intelligence in Medicine, College of Medicine, Taipei Medical University, Taipei 106, Taiwan
- Research Center for Artificial Intelligence in Medicine, Taipei Medical University, Taipei 106, Taiwan
- Translational Imaging Research Center, Taipei Medical University Hospital, Taipei 110, Taiwan
- Correspondence: ; Tel.: +886-2-66382736 (ext. 1992); Fax: +886-02-27321956
| |
Collapse
|
19
|
Cao H, Tong H, Zhu J, Xie C, Qin Z, Li T, Liu X, He W. A Glycolysis-Based Long Non-coding RNA Signature Accurately Predicts Prognosis in Renal Carcinoma Patients. Front Genet 2021; 12:638980. [PMID: 33868376 PMCID: PMC8047215 DOI: 10.3389/fgene.2021.638980] [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: 12/08/2020] [Accepted: 03/16/2021] [Indexed: 12/18/2022] Open
Abstract
Background The prognosis of renal cell carcinoma (RCC) varies greatly among different risk groups, and the traditional indicators have limited effect in the identification of risk grade in patients with RCC. The purpose of our study is to explore a glycolysis-based long non-coding RNAs (lncRNAs) signature and verify its potential clinical significance in prognostic prediction of RCC patients. Methods In this study, RNA data and clinical information were downloaded from The Cancer Genome Atlas (TCGA) database. Univariate and multivariate cox regression displayed six significantly related lncRNAs (AC124854.1, AC078778.1, EMX2OS, DLGAP1-AS2, AC084876.1, and AC026401.3) which were utilized in construction of risk score by a formula. The accuracy of risk score was verified by a series of statistical methods such as receiver operating characteristic (ROC) curves, nomogram and Kaplan-Meier curves. Its potential clinical significance was excavated by gene enrichment analysis. Results Kaplan-Meier curves and ROC curves showed reliability of the risk score to predict the prognosis of RCC patients. Stratification analysis indicated that the risk score was independent predictor compare to other traditional clinical parameters. The clinical nomogram showed highly rigorous with index of 0.73 and precisely predicted 1-, 3-, and 5-year survival time of RCC patients. Kyoto Encyclopedia of Genes and Genomes (KEGG) and Gene set enrichment analysis (GSEA) depicted the top ten correlated pathways in both high-risk group and low-risk group. There are 6 lncRNAs and 25 related mRNAs including 36 lncRNA-mRNA links in lncRNA-mRNA co-expression network. Conclusion This research demonstrated that glycolysis-based lncRNAs possessed an important value in survival prediction of RCC patients, which would be a potential target for future treatment.
Collapse
Affiliation(s)
- Honghao Cao
- Department of Urology, The First Affiliated Hospital of Chongqing Medical University, Chongqing, China.,Department of Urology, Rongchang Traditional Chinese Medicine Hospital, Chongqing, China
| | - Hang Tong
- Department of Urology, The First Affiliated Hospital of Chongqing Medical University, Chongqing, China.,Central Laboratory, The First Affiliated Hospital of Chongqing Medical University, Chongqing, China
| | - Junlong Zhu
- Department of Urology, The First Affiliated Hospital of Chongqing Medical University, Chongqing, China.,Central Laboratory, The First Affiliated Hospital of Chongqing Medical University, Chongqing, China
| | - Chenchen Xie
- Central Laboratory, The First Affiliated Hospital of Chongqing Medical University, Chongqing, China
| | - Zijia Qin
- Department of Urology, The First Affiliated Hospital of Chongqing Medical University, Chongqing, China.,Central Laboratory, The First Affiliated Hospital of Chongqing Medical University, Chongqing, China
| | - Tinghao Li
- Department of Urology, The First Affiliated Hospital of Chongqing Medical University, Chongqing, China.,Central Laboratory, The First Affiliated Hospital of Chongqing Medical University, Chongqing, China
| | - Xudong Liu
- Department of Urology, The First Affiliated Hospital of Chongqing Medical University, Chongqing, China
| | - Weiyang He
- Department of Urology, The First Affiliated Hospital of Chongqing Medical University, Chongqing, China
| |
Collapse
|
20
|
Singh L, Singh MK, Kenney MC, Jager MJ, Rizvi MA, Meel R, Lomi N, Bakhshi S, Sen S, Kashyap S. Prognostic significance of PD-1/PD-L1 expression in uveal melanoma: correlation with tumor-infiltrating lymphocytes and clinicopathological parameters. Cancer Immunol Immunother 2020; 70:1291-1303. [PMID: 33136179 DOI: 10.1007/s00262-020-02773-8] [Citation(s) in RCA: 17] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/08/2020] [Accepted: 10/19/2020] [Indexed: 12/25/2022]
Abstract
BACKGROUND To understand how to improve the effect of immune checkpoint inhibitors in uveal melanoma (UM), we need a better understanding of the expression of PD-1 and PD-L1, their relation with the presence of tumor-infiltrating lymphocytes (TILs), and their prognostic relevance in UM patients. MATERIALS AND METHODS Expression of PD-1 and PD-L1 was assessed in 71 UM tissue samples by immunohistochemistry and quantitative real-time PCR (qRT-PCR), and further validated by western blotting. The effect of interferon gamma (IFN-γ) on PD-1/PD-L1 expression was determined on four UM cell lines. RESULTS Immunoreactivity of PD-1 was found in 30/71 cases and of PD-L1 in 44/71 UM samples. Tumor-infiltrating lymphocytes were found in 46% of UM tissues. PD-1 was expressed on TILs while tumor cells expressed PD-L1. UM with and without TILs showed expression of PD-1 in 69% and 18% cases, respectively (p = 0.001). Similarly, PD-L1 was found in 75% of UM with TILs and in 50% of cases without TILs, respectively (p = 0.03). DFS rate were lower in patients with TILs with expression of PD-1 and PD-L1, but the rate of DFS was higher with expression of PD-L1 in patients without TILs. After treatment of UM cell lines with IFN-γ, PD-1 expression was induced in all UM cell lines whereas PD-L1 expression was found at a lower level in untreated cells, while expression also increased following treatment with IFN-γ. CONCLUSION Our study suggests that increased infiltration with TILs promotes the aggressive behavior and suppresses the immune response of UM cells, thereby inhibiting immunotherapy.
Collapse
Affiliation(s)
- Lata Singh
- Department of Ocular Pathology, Dr. R P. Centre for Ophthalmic Sciences, All India Institute of Medical Sciences, New Delhi, India.,Department of Ophthalmology, Gavin Herbert Eye Institute, University of California, Irvine, USA.,Biosciences, Jamia Millia Islamia, New Delhi, India
| | - Mithalesh Kumar Singh
- Department of Ocular Pathology, Dr. R P. Centre for Ophthalmic Sciences, All India Institute of Medical Sciences, New Delhi, India
| | - Maria Cristina Kenney
- Department of Ophthalmology, Gavin Herbert Eye Institute, University of California, Irvine, USA
| | - Martine J Jager
- Department of Ophthalmology, Leiden University Medical Center, Leiden, The Netherlands
| | | | - Rachna Meel
- Department of Ophthalmology, Dr. R. Centre for Ophthalmic Sciences, All India Institute of Medical Sciences, New Delhi, India
| | - Neiwete Lomi
- Department of Ophthalmology, Dr. R. Centre for Ophthalmic Sciences, All India Institute of Medical Sciences, New Delhi, India
| | - Sameer Bakhshi
- Department of Medical Oncology, All India Institute of Medical Sciences, IRCH, New Delhi, India
| | - Seema Sen
- Department of Ocular Pathology, Dr. R P. Centre for Ophthalmic Sciences, All India Institute of Medical Sciences, New Delhi, India
| | - Seema Kashyap
- Department of Ocular Pathology, Dr. R P. Centre for Ophthalmic Sciences, All India Institute of Medical Sciences, New Delhi, India.
| |
Collapse
|
21
|
Luo H, Ma C, Shao J, Cao J. Prognostic Implications of Novel Ten-Gene Signature in Uveal Melanoma. Front Oncol 2020; 10:567512. [PMID: 33194647 PMCID: PMC7661968 DOI: 10.3389/fonc.2020.567512] [Citation(s) in RCA: 22] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/23/2020] [Accepted: 09/15/2020] [Indexed: 12/18/2022] Open
Abstract
Background: Uveal melanoma (UM) is the most common primary intraocular cancer in adults. Genomic studies have provided insights into molecular subgroups and oncogenic drivers of UM that may lead to novel therapeutic strategies. Methods: Dataset TCGA-UVM, download from TCGA portal, were taken as the training cohort, and dataset GSE22138, obtained from GEO database, was set as the validation cohort. In training cohort, Kaplan-Meier analysis and univariate Cox regression model were applied to preliminary screen prognostic genes. Besides, the Cox regression model with LASSO was implemented to build a multi-gene signature, which was then validated in the validation cohorts through Kaplan-Meier, Cox, and ROC analyses. In addition, the correlation between copy number aberrations and risk score was evaluated by Spearman test. GSEA and immune infiltrating analyses were conducted for understanding function annotation and the role of the signature in the tumor microenvironment. Results: A ten-gene signature was built, and it was examined by Kaplan-Meier analysis revealing that significantly overall survival, progression-free survival, and metastasis-free survival difference was seen. The ten-gene signature was further proven to be an independent risk factor compared to other clinic-pathological parameters via the Cox regression analysis. Moreover, the receiver operating characteristic curve (ROC) analysis results demonstrated a better predictive power of the UM prognosis that our signature owned. The ten-gene signature was significantly correlated with copy numbers of chromosome 3, 8q, 6q, and 6p. Furthermore, GSEA and immune infiltrating analyses showed that the signature had close interactions with immune-related pathways and the tumor environment. Conclusions: Identifying the ten-gene signature (SIRT3, HMCES, SLC44A3, TCTN1, STPG1, POMGNT2, RNF208, ANXA2P2, ULBP1, and CA12) could accurately identify patients' prognosis and had close interactions with the immunodominant tumor environment, which may provide UM patients with personalized prognosis prediction and new treatment insights.
Collapse
Affiliation(s)
- Huan Luo
- Department of Anatomy, College of Basic Medicine, Zhengzhou University, Zhengzhou, China.,Charité-Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Berlin, Germany.,Klinik für Augenheilkunde, Charité-Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Berlin, Germany
| | - Chao Ma
- Charité-Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Berlin, Germany.,Charité-Universitätsmedizin Berlin, BCRT-Berlin Institute of Health Center for Regenerative Therapies, Berlin, Germany
| | - Jinping Shao
- Department of Anatomy, College of Basic Medicine, Zhengzhou University, Zhengzhou, China
| | - Jing Cao
- Department of Anatomy, College of Basic Medicine, Zhengzhou University, Zhengzhou, China
| |
Collapse
|
22
|
Yang J, Shi W, Zhu S, Yang C. Construction of a 6-gene prognostic signature to assess prognosis of patients with pancreatic cancer. Medicine (Baltimore) 2020; 99:e22092. [PMID: 32925750 PMCID: PMC7489722 DOI: 10.1097/md.0000000000022092] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/18/2023] Open
Abstract
Pancreatic cancer (PaCa) is one of the most fatal cancers in the world. Although great efforts have made to explore the mechanisms of PaCa oncogenesis, the prognosis of PaCa patients is still unsatisfactory. Thus, it is imperative to further understand the potential carcinogenesis of PaCa and reliable prognostic models.The gene expression profile and clinical information of GSE21501 were downloaded from the Gene Expression Omnibus (GEO) database. Weighted gene co-expression network analysis (WGCNA) was applied to explore the potent genes associated with the overall survival (OS) events of PaCa patients. Cox regression model was applied to selecting prognostic genes and establish prognostic model. The prognostic values of six-gene signature were validated in TCGA-PAAD cohort.According to the WGCNA analysis, a total of 19 modules were identified and 115 hub genes in the mostly associated module were reserved for next analysis. According to the univariate and multivariate Cox regression analysis, we established a six-gene signature (FTSJ3, STAT1, STX2, CDX2, RASSF4, MACF1) which could effectively evaluate the overall survival (OS) of PaCa patients. In validated patients' cohorts, the six-gene signature exhibited excellent prognostic value in TCGA-PAAD cohort as well.We developed a six-gene signature to exactly predict OS of PaCa patients and provide a novel personalized strategy for evaluating prognosis. The findings may be contributed to medical customization and therapeutic decision in clinical practice.
Collapse
Affiliation(s)
| | | | | | - Cheng Yang
- Department of Gastroenterology, Wuxi People's Hospital Affiliated to Nanjing Medical University, Wuxi 214023, China
| |
Collapse
|
23
|
Tian M, Yang J, Han J, He J, Liao W. A novel immune checkpoint-related seven-gene signature for predicting prognosis and immunotherapy response in melanoma. Int Immunopharmacol 2020; 87:106821. [PMID: 32731180 DOI: 10.1016/j.intimp.2020.106821] [Citation(s) in RCA: 23] [Impact Index Per Article: 5.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/05/2020] [Revised: 07/09/2020] [Accepted: 07/17/2020] [Indexed: 02/05/2023]
Abstract
BACKGROUND New emergence of immunotherapy has significantly improved clinical outcome of melanoma patients with advanced and metastatic diseases. We aimed to develop a gene signature based on the expression of PD-1/PD-L1 signaling pathway genes to predict prognosis and immunotherapy response in melanoma patients. METHODS Melanoma samples from The Cancer Genome Atlas (TCGA) database and Gene Expression Omnibus (GEO) were used as the training set and external validation sets respectively. Prognostic genes for overall survival (OS) were identified by univariate Cox regression analysis. Then a multi-gene risk signature was established with the Least Absolute Shrinkage and Selector Operation (LASSO) regression and multivariate Cox regression. The predictive and prognostic value of gene signature was evaluated by Kaplan Meier curve, Time-dependent receiver operating characteristic (ROC) curve, and area under curve (AUC). Gene set enrichment analysis (GSEA) was performed to investigate the discrepantly enriched biological processes between low-risk and high-risk group of melanoma patients. RESULTS A seven-gene risk signature (BATF2, CTLA4, EGFR, HLA-DQB1, IKBKG, PIK3R2, PPP3CA) was constructed. The signature was an independent risk factor for OS (hazard ratio = 1.544, p < 0.001) and it could robustly predict OS in both training and validation sets. Besides, high risk scores indicated advanced clinical stage and no response to immunotherapy for melanoma patients. GSEA demonstrated that high risk score was intimately associated with immune response and immune regulation. In conclusion, the novel seven-gene signature could serve as a robust biomarker for prognosis and a potential indicator of immunotherapy response in melanoma.
Collapse
Affiliation(s)
- Maolang Tian
- Department of Head and Neck Oncology and Department of Radiation Oncology, Cancer Center and State Key Laboratory of Biotherapy, West China Hospital, Sichuan University, Chengdu, Sichuan 610041, China
| | - Jiangping Yang
- Department of Head and Neck Oncology and Department of Radiation Oncology, Cancer Center and State Key Laboratory of Biotherapy, West China Hospital, Sichuan University, Chengdu, Sichuan 610041, China
| | - Jiaqi Han
- Department of Head and Neck Oncology and Department of Radiation Oncology, Cancer Center and State Key Laboratory of Biotherapy, West China Hospital, Sichuan University, Chengdu, Sichuan 610041, China
| | - Jinlan He
- Department of Head and Neck Oncology and Department of Radiation Oncology, Cancer Center and State Key Laboratory of Biotherapy, West China Hospital, Sichuan University, Chengdu, Sichuan 610041, China
| | - Wenjun Liao
- Department of Head and Neck Oncology and Department of Radiation Oncology, Cancer Center and State Key Laboratory of Biotherapy, West China Hospital, Sichuan University, Chengdu, Sichuan 610041, China.
| |
Collapse
|
24
|
Zhao X, Cui L. A robust six-miRNA prognostic signature for head and neck squamous cell carcinoma. J Cell Physiol 2020; 235:8799-8811. [PMID: 32342519 DOI: 10.1002/jcp.29723] [Citation(s) in RCA: 20] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/05/2019] [Revised: 04/03/2020] [Accepted: 04/07/2020] [Indexed: 02/06/2023]
Abstract
Head and neck squamous cell carcinoma (HNSCC) remains a major health problem worldwide. We aimed to identify a robust microRNA (miRNA)-based signature for predicting HNSCC prognosis. The miRNA expression profiles of HNSCC were obtained from The Cancer Genome Atlas (TCGA) database. The TCGA HNSCC cohort was randomly divided into the discovery and validation cohort. A miRNA-based prognostic signature was built up based on TGCA discovery cohort, and then further validated. The downstream targets of prognostic miRNAs were subjected to functional enrichment analyses. The role of miR-1229-3p, a prognosis-related miRNA, in tumorigenesis of HNSCC was further evaluated. A total of 305 significantly differentially expressed miRNAs were found between HNSCC samples and normal tissues. A six-miRNA prognostic signature was constructed, which exhibited a strong association with overall survival (OS) in the TCGA discovery cohort. In addition, these findings were successfully confirmed in TCGA validation cohort and our own independent cohort. The miRNA-based signature was demonstrated as an independent prognostic indicator for HNSCC. A risk signature-based nomogram model was constructed and showed good performance for predicting the OS for HNSCC. The functional analyses revealed that the downstream targets of these prognostic miRNAs were closely linked to cancer progression. Mechanistically, in vitro analysis revealed that miR-1229-3p played a tumor promoting role in HNSCC. In conclusion, our study has developed a robust miRNA-based signature for predicting the prognosis of HNSCC with high accuracy, which will contribute to improve the therapeutic outcome.
Collapse
Affiliation(s)
- Xinyuan Zhao
- Department of Endodontics, Stomatological Hospital, Southern Medical University, Guangzhou, China
| | - Li Cui
- Division of Oral Biology and Medicine, School of Dentistry, UCLA, Los Angeles, California
| |
Collapse
|
25
|
Gulfidan G, Turanli B, Beklen H, Sinha R, Arga KY. Pan-cancer mapping of differential protein-protein interactions. Sci Rep 2020; 10:3272. [PMID: 32094374 PMCID: PMC7039988 DOI: 10.1038/s41598-020-60127-x] [Citation(s) in RCA: 22] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/17/2019] [Accepted: 02/04/2020] [Indexed: 01/02/2023] Open
Abstract
Deciphering the variations in the protein interactome is required to reach a systems-level understanding of tumorigenesis. To accomplish this task, we have considered the clinical and transcriptome data on >6000 samples from The Cancer Genome Atlas for 12 different cancers. Utilizing the gene expression levels as a proxy, we have identified the differential protein-protein interactions in each cancer type and presented a differential view of human protein interactome among the cancers. We clearly demonstrate that a certain fraction of proteins differentially interacts in the cancers, but there was no general protein interactome profile that applied to all cancers. The analysis also provided the characterization of differentially interacting proteins (DIPs) representing significant changes in their interaction patterns during tumorigenesis. In addition, DIP-centered protein modules with high diagnostic and prognostic performances were generated, which might potentially be valuable in not only understanding tumorigenesis, but also developing effective diagnosis, prognosis, and treatment strategies.
Collapse
Affiliation(s)
- Gizem Gulfidan
- Department of Bioengineering, Marmara University, 34722, Istanbul, Turkey
| | - Beste Turanli
- Department of Bioengineering, Marmara University, 34722, Istanbul, Turkey
- Department of Bioengineering, Istanbul Medeniyet University, 34720, Istanbul, Turkey
| | - Hande Beklen
- Department of Bioengineering, Marmara University, 34722, Istanbul, Turkey
| | - Raghu Sinha
- Department of Biochemistry and Molecular Biology, Penn State College of Medicine, Hershey, 17033, Pennsylvania, United States
| | - Kazim Yalcin Arga
- Department of Bioengineering, Marmara University, 34722, Istanbul, Turkey.
| |
Collapse
|