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Azimi P, Yazdanian T, Ahmadiani A. mRNA markers for survival prediction in glioblastoma multiforme patients: a systematic review with bioinformatic analyses. BMC Cancer 2024; 24:612. [PMID: 38773447 PMCID: PMC11106946 DOI: 10.1186/s12885-024-12345-z] [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: 01/14/2024] [Accepted: 05/06/2024] [Indexed: 05/23/2024] Open
Abstract
BACKGROUND Glioblastoma multiforme (GBM) is a type of fast-growing brain glioma associated with a very poor prognosis. This study aims to identify key genes whose expression is associated with the overall survival (OS) in patients with GBM. METHODS A systematic review was performed using PubMed, Scopus, Cochrane, and Web of Science up to Journey 2024. Two researchers independently extracted the data and assessed the study quality according to the New Castle Ottawa scale (NOS). The genes whose expression was found to be associated with survival were identified and considered in a subsequent bioinformatic study. The products of these genes were also analyzed considering protein-protein interaction (PPI) relationship analysis using STRING. Additionally, the most important genes associated with GBM patients' survival were also identified using the Cytoscape 3.9.0 software. For final validation, GEPIA and CGGA (mRNAseq_325 and mRNAseq_693) databases were used to conduct OS analyses. Gene set enrichment analysis was performed with GO Biological Process 2023. RESULTS From an initial search of 4104 articles, 255 studies were included from 24 countries. Studies described 613 unique genes whose mRNAs were significantly associated with OS in GBM patients, of which 107 were described in 2 or more studies. Based on the NOS, 131 studies were of high quality, while 124 were considered as low-quality studies. According to the PPI network, 31 key target genes were identified. Pathway analysis revealed five hub genes (IL6, NOTCH1, TGFB1, EGFR, and KDR). However, in the validation study, only, the FN1 gene was significant in three cohorts. CONCLUSION We successfully identified the most important 31 genes whose products may be considered as potential prognosis biomarkers as well as candidate target genes for innovative therapy of GBM tumors.
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Affiliation(s)
- Parisa Azimi
- Neurosurgeon, Neuroscience Research Center, Shahid Beheshti University of Medical Sciences, Arabi Ave, Daneshjoo Blvd, Velenjak, Tehran, 19839- 63113, Iran.
| | | | - Abolhassan Ahmadiani
- Neurosurgeon, Neuroscience Research Center, Shahid Beheshti University of Medical Sciences, Arabi Ave, Daneshjoo Blvd, Velenjak, Tehran, 19839- 63113, Iran.
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Yang S, Wang X, Huan R, Deng M, Kong Z, Xiong Y, Luo T, Jin Z, Liu J, Chu L, Han G, Zhang J, Tan Y. Machine learning unveils immune-related signature in multicenter glioma studies. iScience 2024; 27:109317. [PMID: 38500821 PMCID: PMC10946333 DOI: 10.1016/j.isci.2024.109317] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/16/2023] [Revised: 01/11/2024] [Accepted: 02/17/2024] [Indexed: 03/20/2024] Open
Abstract
In glioma molecular subtyping, existing biomarkers are limited, prompting the development of new ones. We present a multicenter study-derived consensus immune-related and prognostic gene signature (CIPS) using an optimal risk score model and 101 algorithms. CIPS, an independent risk factor, showed stable and powerful predictive performance for overall and progression-free survival, surpassing traditional clinical variables. The risk score correlated significantly with the immune microenvironment, indicating potential sensitivity to immunotherapy. High-risk groups exhibited distinct chemotherapy drug sensitivity. Seven signature genes, including IGFBP2 and TNFRSF12A, were validated by qRT-PCR, with higher expression in tumors and prognostic relevance. TNFRSF12A, upregulated in GBM, demonstrated inhibitory effects on glioma cell proliferation, migration, and invasion. CIPS emerges as a robust tool for enhancing individual glioma patient outcomes, while IGFBP2 and TNFRSF12A pose as promising tumor markers and therapeutic targets.
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Affiliation(s)
- Sha Yang
- Guizhou University Medical College, Guiyang 550025, Guizhou Province, China
| | - Xiang Wang
- Department of Neurosurgery, the Affiliated Hospital of Guizhou Medical University, Guiyang 550004, China
| | - Renzheng Huan
- Department of Neurosurgery, The Second Affiliated Hospital of Chongqing Medical University, Chongqing 400010, China
| | - Mei Deng
- Department of Neurosurgery, Guizhou Provincial People’s Hospital, Guiyang, China
| | - Zhuo Kong
- Department of Neurosurgery, Guizhou Provincial People’s Hospital, Guiyang, China
| | - Yunbiao Xiong
- Department of Neurosurgery, Guizhou Provincial People’s Hospital, Guiyang, China
| | - Tao Luo
- Department of Neurosurgery, Guizhou Provincial People’s Hospital, Guiyang, China
| | - Zheng Jin
- Department of Neurosurgery, Guizhou Provincial People’s Hospital, Guiyang, China
| | - Jian Liu
- Guizhou University Medical College, Guiyang 550025, Guizhou Province, China
- Department of Neurosurgery, Guizhou Provincial People’s Hospital, Guiyang, China
| | - Liangzhao Chu
- Department of Neurosurgery, the Affiliated Hospital of Guizhou Medical University, Guiyang 550004, China
| | - Guoqiang Han
- Department of Neurosurgery, Guizhou Provincial People’s Hospital, Guiyang, China
| | - Jiqin Zhang
- Department of Anesthesiology, Guizhou Provincial People’s Hospital, Guiyang, China
| | - Ying Tan
- Department of Neurosurgery, Guizhou Provincial People’s Hospital, Guiyang, China
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Saghapour E, Yue Z, Sharma R, Kumar S, Sembay Z, Willey CD, Chen JY. Explorative Discovery of Gene Signatures and Clinotypes in Glioblastoma Cancer Through GeneTerrain Knowledge Map Representation. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.04.01.587278. [PMID: 38617348 PMCID: PMC11014492 DOI: 10.1101/2024.04.01.587278] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 04/16/2024]
Abstract
This study introduces the GeneTerrain Knowledge Map Representation (GTKM), a novel method for visualizing gene expression data in cancer research. GTKM leverages protein-protein interactions to graphically display differentially expressed genes (DEGs) on a 2-dimensional contour plot, offering a more nuanced understanding of gene interactions and expression patterns compared to traditional heatmap methods. The research demonstrates GTKM's utility through four case studies on glioblastoma (GBM) datasets, focusing on survival analysis, subtype identification, IDH1 mutation analysis, and drug sensitivities of different tumor cell lines. Additionally, a prototype website has been developed to showcase these findings, indicating the method's adaptability for various cancer types. The study reveals that GTKM effectively identifies gene patterns associated with different clinical outcomes in GBM, and its profiles enable the identification of sub-gene signature patterns crucial for predicting survival. The methodology promises significant advancements in precision medicine, providing a powerful tool for understanding complex gene interactions and identifying potential therapeutic targets in cancer treatment.
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Affiliation(s)
- Ehsan Saghapour
- Department of Biomedical Informatics and Data Science, University of Alabama at Birmingham, Birmingham, AL, US
| | - Zongliang Yue
- Health Outcome Research and Policy Department, Harrison College of Pharmacy, Auburn University, AL, US
| | - Rahul Sharma
- Department of Biomedical Informatics and Data Science, University of Alabama at Birmingham, Birmingham, AL, US
| | - Sidharth Kumar
- Department of Radiation Oncology, The University of Alabama at Birmingham, Birmingham, AL, US
| | - Zhandos Sembay
- Department of Biomedical Informatics and Data Science, University of Alabama at Birmingham, Birmingham, AL, US
| | - Christopher D Willey
- Department of Radiation Oncology, The University of Alabama at Birmingham, Birmingham, AL, US
| | - Jake Y Chen
- Department of Biomedical Informatics and Data Science, University of Alabama at Birmingham, Birmingham, AL, US
- Systems Pharmacology AI Research Center, University of Alabama at Birmingham, AL, US
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Sanchez-Niño MD, Ceballos MI, Carriazo S, Pintor-Chocano A, Sanz AB, Saleem MA, Ortiz A. Interaction of Fabry Disease and Diabetes Mellitus: Suboptimal Recruitment of Kidney Protective Factors. Int J Mol Sci 2023; 24:15853. [PMID: 37958836 PMCID: PMC10650640 DOI: 10.3390/ijms242115853] [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: 09/27/2023] [Revised: 10/27/2023] [Accepted: 10/29/2023] [Indexed: 11/15/2023] Open
Abstract
Fabry disease is a lysosomal disease characterized by globotriaosylceramide (Gb3) accumulation. It may coexist with diabetes mellitus and both cause potentially lethal kidney end-organ damage. However, there is little information on their interaction with kidney disease. We have addressed the interaction between Fabry disease and diabetes in data mining of human kidney transcriptomics databases and in Fabry (Gla-/-) and wild type mice with or without streptozotocin-induced diabetes. Data mining was consistent with differential expression of genes encoding enzymes from the Gb3 metabolic pathway in human diabetic kidney disease, including upregulation of UGCG, the gene encoding the upstream and rate-limiting enzyme glucosyl ceramide synthase. Diabetic Fabry mice displayed the most severe kidney infiltration by F4/80+ macrophages, and a lower kidney expression of kidney protective genes (Pgc1α and Tfeb) than diabetic wild type mice, without a further increase in kidney fibrosis. Moreover, only diabetic Fabry mice developed kidney insufficiency and these mice with kidney insufficiency had a high expression of Ugcg. In conclusion, we found evidence of interaction between diabetes and Fabry disease that may increase the severity of the kidney phenotype through modulation of the Gb3 synthesis pathway and downregulation of kidney protective genes.
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Affiliation(s)
- Maria D. Sanchez-Niño
- Department of Nephrology and Hypertension, IIS-Fundacion Jimenez Diaz UAM, 28040 Madrid, Spain; (M.I.C.); (S.C.); (A.P.-C.); (A.B.S.)
- RICORS2040, 28040 Madrid, Spain
- Department of Pharmacology, School of Medicine, Universidad Autonoma de Madrid, 28029 Madrid, Spain
| | - Maria I. Ceballos
- Department of Nephrology and Hypertension, IIS-Fundacion Jimenez Diaz UAM, 28040 Madrid, Spain; (M.I.C.); (S.C.); (A.P.-C.); (A.B.S.)
- RICORS2040, 28040 Madrid, Spain
| | - Sol Carriazo
- Department of Nephrology and Hypertension, IIS-Fundacion Jimenez Diaz UAM, 28040 Madrid, Spain; (M.I.C.); (S.C.); (A.P.-C.); (A.B.S.)
- RICORS2040, 28040 Madrid, Spain
| | - Aranzazu Pintor-Chocano
- Department of Nephrology and Hypertension, IIS-Fundacion Jimenez Diaz UAM, 28040 Madrid, Spain; (M.I.C.); (S.C.); (A.P.-C.); (A.B.S.)
- RICORS2040, 28040 Madrid, Spain
| | - Ana B. Sanz
- Department of Nephrology and Hypertension, IIS-Fundacion Jimenez Diaz UAM, 28040 Madrid, Spain; (M.I.C.); (S.C.); (A.P.-C.); (A.B.S.)
- RICORS2040, 28040 Madrid, Spain
| | - Moin A. Saleem
- Translational Health Sciences, Bristol Medical School, University of Bristol, Bristol BS8 1UD, UK;
| | - Alberto Ortiz
- Department of Nephrology and Hypertension, IIS-Fundacion Jimenez Diaz UAM, 28040 Madrid, Spain; (M.I.C.); (S.C.); (A.P.-C.); (A.B.S.)
- RICORS2040, 28040 Madrid, Spain
- Department of Medicine, School of Medicine, Universidad Autonoma de Madrid, 28029 Madrid, Spain
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Röbeck P, Franzén B, Cantera-Ahlman R, Dragomir A, Auer G, Jorulf H, Jacobsson SP, Viktorsson K, Lewensohn R, Häggman M, Ladjevardi S. Multiplex protein analysis and ensemble machine learning methods of fine needle aspirates from prostate cancer patients reveal potential diagnostic signatures associated with tumour grade. Cytopathology 2023; 34:286-294. [PMID: 36840380 DOI: 10.1111/cyt.13226] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/01/2022] [Revised: 02/06/2023] [Accepted: 02/16/2023] [Indexed: 02/26/2023]
Abstract
BACKGROUND Improved molecular diagnosis is needed in prostate cancer (PC). Fine needle aspiration (FNA) is a minimally invasive biopsy technique, less traumatic compared to core needle biopsy, and could be useful for diagnosis of PC. Molecular biomarkers (BMs) in FNA-samples can be assessed for prediction, eg of immunotherapy efficacy before treatment as well as at treatment decision time points during disease progression. METHODS In the present pilot study, the expression levels of 151 BM proteins were analysed by proximity extension assay in FNA-samples from 16 patients, including benign prostate lesions (n = 3) and cancers (n = 13). An ensemble data analysis strategy was applied using several machine learning models. RESULTS Twelve potentially predictive BM proteins correlating with International Society of Urological Pathology grade groups were identified, among them vimentin, tissue factor pathway inhibitor 2, and integrin beta-5. The validity of the results was supported by network analysis that showed functional associations between most of the identified putative BMs. We also showed that multiple immune checkpoint targets can be assessed (eg PD-L1, CD137, and Galectin-9), which may support the selection of immunotherapy in advanced PC. Results are promising but need further validation in a larger cohort. CONCLUSIONS Our pilot study represents a "proof of concept" and shows that multiplex profiling of potential diagnostic and predictive BM proteins is feasible on tumour material obtained by FNA sampling of prostate cancer. Moreover, our results demonstrate that an ensemble data analysis strategy may facilitate the identification of BM signatures in pilot studies when the patient cohort is limited.
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Affiliation(s)
- Pontus Röbeck
- Department of Urology, Uppsala University, Uppsala, Sweden
- Department of Surgical Sciences, Uppsala University, Uppsala, Sweden
| | - Bo Franzén
- Department of Oncology and Pathology, Karolinska Institutet, Stockholm, Sweden
| | - Rafaele Cantera-Ahlman
- Department of Urology, Uppsala University, Uppsala, Sweden
- Department of Surgical Sciences, Uppsala University, Uppsala, Sweden
| | - Anca Dragomir
- Department of Immunology, Genetics and Pathology, Uppsala University, Uppsala, Sweden
| | - Gert Auer
- Department of Oncology and Pathology, Karolinska Institutet, Stockholm, Sweden
| | - Håkan Jorulf
- Department of Urology, Uppsala University, Uppsala, Sweden
- Department of Surgical Sciences, Uppsala University, Uppsala, Sweden
| | - Sven P Jacobsson
- Department of Analytical Chemistry, Stockholm University, Stockholm, Sweden
| | - Kristina Viktorsson
- Department of Oncology and Pathology, Karolinska Institutet, Stockholm, Sweden
| | - Rolf Lewensohn
- Department of Oncology and Pathology, Karolinska Institutet, Stockholm, Sweden
- Theme Cancer, Medical Unit Head and Neck, Lung, and Skin Tumors, Thoracic Oncology Center, Karolinska University Hospital, Solna, Sweden
| | - Michael Häggman
- Department of Urology, Uppsala University, Uppsala, Sweden
- Department of Surgical Sciences, Uppsala University, Uppsala, Sweden
| | - Sam Ladjevardi
- Department of Urology, Uppsala University, Uppsala, Sweden
- Department of Surgical Sciences, Uppsala University, Uppsala, Sweden
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HAUS Augmin-Like Complex Subunit 1 Influences Tumour Microenvironment and Prognostic Outcomes in Glioma. JOURNAL OF ONCOLOGY 2022; 2022:8027686. [PMID: 35865089 PMCID: PMC9296284 DOI: 10.1155/2022/8027686] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 12/28/2021] [Revised: 05/09/2022] [Accepted: 05/17/2022] [Indexed: 11/18/2022]
Abstract
Background. The expression of HAUS Augmin-like complex subunit 1 (HAUS1), a protein-coding gene, is low in normal samples among various cancers with pan-cancer analysis. The depletion of HAUS1 in cells decreases the G2/M cell compartment and induces apoptosis. However, the detailed expression pattern of HAUS1 and its correlation with immune infiltration in glioma (LGG and GBM) (LGG: low-grade glioma; GBM: glioblastoma) remain unknown. Therefore, in this study, we examined the role and prognostic value of HAUS1 in glioma. Methods. Transcriptional expression data of HAUS1 were collected from the CGGA and TCGA databases. The Kaplan–Meier analysis, univariate and multivariate Cox analyses, and receiver operating characteristic (ROC) curves were used to analyse the clinical significance of HAUS1 in glioma. The STRING database was used to analyse protein-protein interactions (PPI), and the “ClusterProfiler” package was used for functional enrichment analysis to examine the possible biological roles of HAUS1. In addition, the HAUS1 promoter methylation modification was analysed using MEXPRESS, and the association between HAUS1 expression and tumour-infiltrating immune cells was investigated using CIBERSORT. Results. Based on the data retrieved from TCGA (703 samples) and CGGA (1018 samples), an elevated expression of HAUS1 was observed in glioma samples, which was associated with poorer survival of patients, unfavourable clinical characteristics, 1p/19q codeletion status, WHO grade, and IDH mutation status. Furthermore, multivariate and univariate Cox analyses revealed that HAUS1 was an independent predictor of glioma. HAUS1 expression level was associated with several tumour-infiltrating immune cells, such as Th2 cells, macrophages, and activated dendritic cells. The outcomes of ROC curve analysis showed that HAUS1 was good to prognosticate immune infiltrating levels in glioma with a higher area under the curve (AUC) value (AUC = 0.974). Conclusions. HAUS1 was upregulated and served as a biomarker for poor prognosis in patients with glioma. High HAUS1 expression was associated with several tumour-infiltrating immune cells such as Th2 cells, macrophages, and activated dendritic cells, which had high infiltration levels. Therefore, these findings suggest that HAUS1 is a potential biomarker for predicting the prognosis of patients with glioma and plays a pivotal role in immune infiltration in glioma.
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Circulating Protein Biomarkers for Prognostic Use in Patients with Advanced Pancreatic Ductal Adenocarcinoma Undergoing Chemotherapy. Cancers (Basel) 2022; 14:cancers14133250. [PMID: 35805022 PMCID: PMC9264968 DOI: 10.3390/cancers14133250] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/23/2022] [Revised: 06/25/2022] [Accepted: 06/28/2022] [Indexed: 02/06/2023] Open
Abstract
Patients with advanced pancreatic ductal adenocarcinoma (PDAC) have a dismal prognosis. We aimed to find a prognostic protein signature for overall survival (OS) in patients with advanced PDAC, and to explore whether early changes in circulating-protein levels could predict survival. We investigated 92 proteins using the Olink Immuno-Oncology panel in serum samples from 363 patients with advanced PDAC. Protein panels for several survival cut-offs were developed independently by two bioinformaticians using LASSO and Ridge regression models. Two panels of proteins discriminated patients with OS < 90 days from those with OS > 2 years. Index I (CSF-1, IL-6, PDCD1, TNFRSF12A, TRAIL, TWEAK, and CA19-9) had AUCs of 0.99 (95% CI: 0.98−1) (discovery cohort) and 0.89 (0.74−1) (replication cohort). For Index II (CXCL13, IL-6, PDCD1, and TNFRSF12A), the corresponding AUCs were 0.97 (0.93−1) and 0.82 (0.68−0.96). Four proteins (ANGPT2, IL-6, IL-10, and TNFRSF12A) were associated with survival across all treatment groups. Longitudinal samples revealed several changes, including four proteins that were also part of the prognostic signatures (CSF-1, CXCL13, IL-6, TNFRSF12A). This study identified two circulating-protein indices with the potential to identify patients with advanced PDAC with very short OS and with long OS.
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