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Lu J, He R, Liu Y, Zhang J, Xu H, Zhang T, Chen L, Yang G, Zhang J, Liu J, Chi H. Exploiting cell death and tumor immunity in cancer therapy: challenges and future directions. Front Cell Dev Biol 2024; 12:1416115. [PMID: 38887519 PMCID: PMC11180757 DOI: 10.3389/fcell.2024.1416115] [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: 04/26/2024] [Accepted: 05/20/2024] [Indexed: 06/20/2024] Open
Abstract
Cancer remains a significant global challenge, with escalating incidence rates and a substantial burden on healthcare systems worldwide. Herein, we present an in-depth exploration of the intricate interplay between cancer cell death pathways and tumor immunity within the tumor microenvironment (TME). We begin by elucidating the epidemiological landscape of cancer, highlighting its pervasive impact on premature mortality and the pronounced burden in regions such as Asia and Africa. Our analysis centers on the pivotal concept of immunogenic cell death (ICD), whereby cancer cells succumbing to specific stimuli undergo a transformation that elicits robust anti-tumor immune responses. We scrutinize the mechanisms underpinning ICD induction, emphasizing the release of damage-associated molecular patterns (DAMPs) and tumor-associated antigens (TAAs) as key triggers for dendritic cell (DC) activation and subsequent T cell priming. Moreover, we explore the contributions of non-apoptotic RCD pathways, including necroptosis, ferroptosis, and pyroptosis, to tumor immunity within the TME. Emerging evidence suggests that these alternative cell death modalities possess immunogenic properties and can synergize with conventional treatments to bolster anti-tumor immune responses. Furthermore, we discuss the therapeutic implications of targeting the TME for cancer treatment, highlighting strategies to harness immunogenic cell death and manipulate non-apoptotic cell death pathways for therapeutic benefit. By elucidating the intricate crosstalk between cancer cell death and immune modulation within the TME, this review aims to pave the way for the development of novel cancer therapies that exploit the interplay between cell death mechanisms and tumor immunity and overcome Challenges in the Development and implementation of Novel Therapies.
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Affiliation(s)
- Jiaan Lu
- Clinical Medical College, Southwest Medical University, Luzhou, China
| | - Ru He
- Clinical Medical College, Southwest Medical University, Luzhou, China
| | - Yang Liu
- Clinical Medical College, Southwest Medical University, Luzhou, China
| | - Jinghan Zhang
- Department of Anesthesiology, Southwest Medical University, Luzhou, China
| | - Heng Xu
- Clinical Medical College, Southwest Medical University, Luzhou, China
| | - Tianchi Zhang
- Chengdu University of Traditional Chinese Medicine, Chengdu, China
- Department of General Surgery, Dazhou Central Hospital, Dazhou, China
| | - Li Chen
- Chengdu University of Traditional Chinese Medicine, Chengdu, China
- Department of General Surgery, Dazhou Central Hospital, Dazhou, China
| | - Guanhu Yang
- Department of Specialty Medicine, Ohio University, Athens, OH, United States
| | - Jun Zhang
- Department of General Surgery, Dazhou Central Hospital, Dazhou, China
| | - Jie Liu
- Department of General Surgery, Dazhou Central Hospital, Dazhou, China
| | - Hao Chi
- Clinical Medical College, Southwest Medical University, Luzhou, China
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Xiao Z, Li J, Liang C, Liu Y, Zhang Y, Zhang Y, Liu Q, Yan X. Identification of M5c regulator-medicated methylation modification patterns for prognosis and immune microenvironment in glioma. Aging (Albany NY) 2023; 15:12275-12295. [PMID: 37934565 PMCID: PMC10683591 DOI: 10.18632/aging.205179] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/16/2023] [Accepted: 10/02/2023] [Indexed: 11/08/2023]
Abstract
Glioma is a common intracranial tumor and is generally associated with poor prognosis. Recently, numerous studies illustrated the importance of 5-methylcytosine (m5C) RNA modification to tumorigenesis. However, the prognostic value and immune correlation of m5C in glioma remain unclear. We obtained RNA expression and clinical information from The Cancer Genome Atlas (TCGA) and The Chinese Glioma Genome Atlas (CGGA) datasets to analyze. Nonnegative matrix factorization (NMF) was used to classify patients into two subgroups and compare these patients in survival and clinicopathological characteristics. CIBERSORT and single-sample gene-set algorithm (ssGSEA) methods were used to investigate the relationship between m5C and the immune environment. The Weighted correlation network analysis (WGCNA) and univariate Cox proportional hazard model (CoxPH) were used to construct a m5C-related signature. Most of m5C RNA methylation regulators presented differential expression and prognostic values. There were obvious relationships between immune infiltration cells and m5C regulators, especially NSUN7. In the m5C-related module from WGCNA, we found SEPT3, CHI3L1, PLBD1, PHYHIPL, SAMD8, RAP1B, B3GNT5, RER1, PTPN7, SLC39A1, and MXI1 were prognostic factors for glioma, and they were used to construct the signature. The great significance of m5C-related signature in predicting the survival of patients with glioma was confirmed in the validation sets and CGGA cohort.
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Affiliation(s)
- Zhenyong Xiao
- Department of Neurosurgery, The Fourth Affiliated Hospital of Guangxi Medical University, Liuzhou 545000, Guangxi, China
| | - Jinwei Li
- Department of Neurosurgery, The Fourth Affiliated Hospital of Guangxi Medical University, Liuzhou 545000, Guangxi, China
- Department of Neurosurgery, West China Hospital, Sichuan University, Chengdu 610000, Sichuan, China
| | - Cong Liang
- Department of Pharmacy, The Fourth Affiliated Hospital of Guangxi Medical University, Liuzhou 545000, Guangxi, China
| | - Yamei Liu
- Department of Neurosurgery, The Fourth Affiliated Hospital of Guangxi Medical University, Liuzhou 545000, Guangxi, China
| | - Yuxiu Zhang
- Department of Neurosurgery, The Fourth Affiliated Hospital of Guangxi Medical University, Liuzhou 545000, Guangxi, China
| | - Yuxia Zhang
- Department of Neurosurgery, The Fourth Affiliated Hospital of Guangxi Medical University, Liuzhou 545000, Guangxi, China
| | - Quan Liu
- Department of Neurosurgery, The Fourth Affiliated Hospital of Guangxi Medical University, Liuzhou 545000, Guangxi, China
| | - Xianlei Yan
- Department of Neurosurgery, The Fourth Affiliated Hospital of Guangxi Medical University, Liuzhou 545000, Guangxi, China
- Department of Neurosurgery, West China Hospital, Sichuan University, Chengdu 610000, Sichuan, China
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Shi T, Li M, Yu Y. Machine learning-enhanced insights into sphingolipid-based prognostication: revealing the immunological landscape and predictive proficiency for immunomotherapy and chemotherapy responses in pancreatic carcinoma. Front Mol Biosci 2023; 10:1284623. [PMID: 38028544 PMCID: PMC10643633 DOI: 10.3389/fmolb.2023.1284623] [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: 08/28/2023] [Accepted: 10/17/2023] [Indexed: 12/01/2023] Open
Abstract
Background: With a poor prognosis for affected individuals, pancreatic adenocarcinoma (PAAD) is known as a complicated and diverse illness. Immunocytes have become essential elements in the development of PAAD. Notably, sphingolipid metabolism has a dual function in the development of tumors and the invasion of the immune system. Despite these implications, research on the predictive ability of sphingolipid variables for PAAD prognosis is strikingly lacking, and it is yet unclear how they can affect PAAD immunotherapy and targeted pharmacotherapy. Methods: The investigation process included SPG detection while also being pertinent to the prognosis for PAAD. Both the analytical capability of CIBERSORT and the prognostic capability of the pRRophetic R package were used to evaluate the immunological environments of the various HCC subtypes. In addition, CCK-8 experiments on PAAD cell lines were carried out to confirm the accuracy of drug sensitivity estimates. The results of these trials, which also evaluated cell survival and migratory patterns, confirmed the usefulness of sphingolipid-associated genes (SPGs). Results: As a result of this thorough investigation, 32 SPGs were identified, each of which had a measurable influence on the dynamics of overall survival. This collection of genes served as the conceptual framework for the development of a prognostic model, which was carefully assembled from 10 chosen genes. It should be noted that this grouping of patients into cohorts with high and low risk was a sign of different immune profiles and therapy responses. The increased abundance of SPGs was identified as a possible sign of inadequate responses to immune-based treatment approaches. The careful CCK-8 testing carried out on PAAD cell lines was of the highest importance for providing clear confirmation of drug sensitivity estimates. Conclusion: The significance of Sphingolipid metabolism in the complex web of PAAD development is brought home by this study. The novel risk model, built on the complexity of sphingolipid-associated genes, advances our understanding of PAAD and offers doctors a powerful tool for developing personalised treatment plans that are specifically suited to the unique characteristics of each patient.
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Affiliation(s)
| | | | - Yabin Yu
- Department of Hepatobiliary Surgery, The Affiliated Huaian No 1 People’s Hospital of Nanjing Medical University, Huaian, China
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Ding W, Zhang M, Zhang P, Zhang X, Sun J, Lin B. Identification of anoikis-related subtypes and immune landscape in kidney renal clear cell carcinoma. Sci Rep 2023; 13:18069. [PMID: 37872217 PMCID: PMC10593771 DOI: 10.1038/s41598-023-45069-4] [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: 06/20/2023] [Accepted: 10/15/2023] [Indexed: 10/25/2023] Open
Abstract
Anoikis is a specific form of programmed cell death induced by the loss of cell contact with the extracellular matrix and other cells, and plays an important role in organism development, tissue homeostasis, disease development and tumor metastasis. We comprehensively investigated the expression patterns of anoikis-related genes (ARGs) in kidney renal clear cell carcinoma (KIRC) from public databases. Anoikis-related prognostic signatures were established based on four ARGs expression, in which KIRC patients were assigned different risk scores and divided into two different risk groups. In addition, four ARGs expression was validated by qRT-PCR. A better prognosis was observed in the low-risk group, but with lower immune activity (including immune cells and immune-related functions) in the tumor microenvironment. Combined with the relevant clinical characteristics, a nomogram for clinical application was established. Receiver operating characteristics (ROC) and calibration curves were constructed to demonstrate the predictive power of this risk signature. In addition, higher risk scores were significantly and positively correlated with higher gene expression of tumor mutation load (TMB), immune checkpoints (ICPs) and mismatch repair (MMR)-related proteins in general. The results also suggested that the high-risk group was more sensitive to immunotherapy and certain chemotherapeutic agents. Anoikis-related prognostic signatures may provide a better understanding of the roles of ARGs and offer new perspectives for clinical prognosis and individualized treatment.
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Affiliation(s)
- Wencong Ding
- The Department of Nephrology and Hemopurification Center, Affiliated Guangdong Hospital of Integrated Traditional Chinese and Western Medicine of Guangzhou University of Chinese Medicine, Foshan, 528000, Guangdong, China
| | - Min Zhang
- The Department of Nephrology and Hemopurification Center, Affiliated Guangdong Hospital of Integrated Traditional Chinese and Western Medicine of Guangzhou University of Chinese Medicine, Foshan, 528000, Guangdong, China
| | - Ping Zhang
- The Department of Nephrology and Hemopurification Center, Affiliated Guangdong Hospital of Integrated Traditional Chinese and Western Medicine of Guangzhou University of Chinese Medicine, Foshan, 528000, Guangdong, China
| | - Xianghong Zhang
- The Department of Nephrology and Hemopurification Center, Affiliated Guangdong Hospital of Integrated Traditional Chinese and Western Medicine of Guangzhou University of Chinese Medicine, Foshan, 528000, Guangdong, China
| | - Junwei Sun
- The Department of Nephrology and Hemopurification Center, Affiliated Guangdong Hospital of Integrated Traditional Chinese and Western Medicine of Guangzhou University of Chinese Medicine, Foshan, 528000, Guangdong, China
| | - Biying Lin
- The Department of Nephrology and Hemopurification Center, Affiliated Guangdong Hospital of Integrated Traditional Chinese and Western Medicine of Guangzhou University of Chinese Medicine, Foshan, 528000, Guangdong, China.
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Zhang P, Zhang H, Tang J, Ren Q, Zhang J, Chi H, Xiong J, Gong X, Wang W, Lin H, Li J, Huang C. The integrated single-cell analysis developed an immunogenic cell death signature to predict lung adenocarcinoma prognosis and immunotherapy. Aging (Albany NY) 2023; 15:10305-10329. [PMID: 37796202 PMCID: PMC10599752 DOI: 10.18632/aging.205077] [Citation(s) in RCA: 7] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/30/2023] [Accepted: 09/06/2023] [Indexed: 10/06/2023]
Abstract
BACKGROUND Research on immunogenic cell death (ICD) in lung adenocarcinoma (LUAD) has been relatively limited. This study aims to create ICD-related signatures for accurate survival prognosis prediction in LUAD patients, addressing the challenge of lacking reliable early prognostic indicators for this type of cancer. METHODS Using single-cell RNA sequencing (scRNA-seq) analysis, ICD activity in cells was calculated by AUCell algorithm, divided into high- and low-ICD groups according to median values, and key ICD regulatory genes were identified through differential analysis, and these genes were integrated into TCGA data to construct prognostic signatures using LASSO and COX regression analysis, and multi-dimensional analysis of ICD-related signatures in terms of prognosis, immunotherapy, tumor microenvironment (TME), and mutational landscape. RESULTS The constructed signature reveals a pronounced disparity in prognosis between the high- and low-risk groups of LUAD patients. The statistical discrepancies in survival times among LUAD patients from both the TCGA and GEO databases further corroborate this observation. Additionally, heightened levels of immune cell infiltration expression are evidenced in the low-risk group, suggesting a potential benefit from immunotherapeutic interventions for these patients. The expression levels of pivotal risk-associated genes in tissue samples were assessed utilizing qRT-PCR, thereby unveiling PITX3 as a plausible therapeutic target in the context of LUAD. CONCLUSIONS Our constructed ICD-related signatures provide help in predicting the prognosis and immunotherapy of LUAD patients, and to some extent guide the clinical treatment of LUAD patients.
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Affiliation(s)
- Pengpeng Zhang
- Department of Thoracic Surgery, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China
- Department of Lung Cancer Surgery, Tianjin Medical University Cancer Institute and Hospital, Tianjin, China
| | - Haotian Zhang
- Department of Thoracic Surgery, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China
| | - Junjie Tang
- Department of Thoracic Surgery, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China
| | - Qianhe Ren
- Department of Thoracic Surgery, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China
| | - Jieying Zhang
- First Teaching Hospital of Tianjin University of Traditional Chinese Medicine, Tianjin, China
| | - Hao Chi
- Clinical Medical College, Southwest Medical University, Luzhou, China
| | - Jingwen Xiong
- Department of Sports Rehabilitation, Southwest Medical University, Luzhou, China
| | - Xiangjin Gong
- Department of Sports Rehabilitation, Southwest Medical University, Luzhou, China
| | - Wei Wang
- Department of Thoracic Surgery, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China
| | - Haoran Lin
- Department of Thoracic Surgery, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China
| | - Jun Li
- Department of Thoracic Surgery, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China
| | - Chenjun Huang
- Department of Thoracic Surgery, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China
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Zou L, Meng L, Xu Y, Wang K, Zhang J. Revealing the diagnostic value and immune infiltration of senescence-related genes in endometriosis: a combined single-cell and machine learning analysis. Front Pharmacol 2023; 14:1259467. [PMID: 37860112 PMCID: PMC10583561 DOI: 10.3389/fphar.2023.1259467] [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: 07/16/2023] [Accepted: 09/05/2023] [Indexed: 10/21/2023] Open
Abstract
Introduction: Endometriosis is a prevalent and recurrent medical condition associated with symptoms such as pelvic discomfort, dysmenorrhea, and reproductive challenges. Furthermore, it has the potential to progress into a malignant state, significantly impacting the quality of life for affected individuals. Despite its significance, there is currently a lack of precise and non-invasive diagnostic techniques for this condition. Methods: In this study, we leveraged microarray datasets and employed a multifaceted approach. We conducted differential gene analysis, implemented weighted gene co-expression network analysis (WGCNA), and utilized machine learning algorithms, including random forest, support vector machine, and LASSO analysis, to comprehensively explore senescence-related genes (SRGs) associated with endometriosis. Discussion: Our comprehensive analysis, which also encompassed profiling of immune cell infiltration and single-cell analysis, highlights the therapeutic potential of this gene assemblage as promising targets for alleviating endometriosis. Furthermore, the integration of these biomarkers into diagnostic protocols promises to enhance diagnostic precision, offering a more effective diagnostic journey for future endometriosis patients in clinical settings. Results: Our meticulous investigation led to the identification of a cluster of genes, namely BAK1, LMNA, and FLT1, which emerged as potential discerning biomarkers for endometriosis. These biomarkers were subsequently utilized to construct an artificial neural network classifier model and were graphically represented in the form of a Nomogram.
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Affiliation(s)
- Lian Zou
- Chongqing Emergency Medical Center, Department of Obstetrics and Gynecology in Chongging University Central Hospital, Chongqing, China
| | - Lou Meng
- Chongqing Emergency Medical Center, Department of Obstetrics and Gynecology in Chongging University Central Hospital, Chongqing, China
| | - Yan Xu
- Chongqing Emergency Medical Center, Department of Obstetrics and Gynecology in Chongging University Central Hospital, Chongqing, China
| | - Kana Wang
- Department of Gynecology, West China Second Hospital of Sichuan University, Chengdu, China
| | - Jiawen Zhang
- Department of Gynecology, West China Second Hospital of Sichuan University, Chengdu, China
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Li Y, Cai H, Yang J, Xie X, Pei S, Wu Y, Zhang J, Song G, Zhang J, Zhang Q, Chi H, Yang G. Decoding tumor heterogeneity in uveal melanoma: basement membrane genes as novel biomarkers and therapeutic targets revealed by multi-omics approaches for cancer immunotherapy. Front Pharmacol 2023; 14:1264345. [PMID: 37822877 PMCID: PMC10562578 DOI: 10.3389/fphar.2023.1264345] [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: 07/20/2023] [Accepted: 09/15/2023] [Indexed: 10/13/2023] Open
Abstract
Background: Uveal melanoma (UVM) is a primary intraocular malignancy that poses a significant threat to patients' visual function and life. The basement membrane (BM) is critical for establishing and maintaining cell polarity, adult function, embryonic and organ morphogenesis, and many other biological processes. Some basement membrane protein genes have been proven to be prognostic biomarkers for various cancers. This research aimed to develop a novel risk assessment system based on BMRGs that would serve as a theoretical foundation for tailored and accurate treatment. Methods: We used gene expression profiles and clinical data from the TCGA-UVM cohort of 80 UVM patients as a training set. 56 UVM patients from the combined cohort of GSE84976 and GSE22138 were employed as an external validation dataset. Prognostic characteristics of basement membrane protein-related genes (BMRGs) were characterized by Lasso, stepwise multifactorial Cox. Multivariate analysis revealed BMRGs to be independent predictors of UVM. The TISCH database probes the crosstalk of BMEGs in the tumor microenvironment at the single-cell level. Finally, we investigated the function of ITGA5 in UVM using multiple experimental techniques, including CCK8, transwell, wound healing assay, and colony formation assay. Results: There are three genes in the prognostic risk model (ADAMTS10, ADAMTS14, and ITGA5). After validation, we determined that the model is quite reliable and accurately forecasts the prognosis of UVM patients. Immunotherapy is more likely to be beneficial for UVM patients in the high-risk group, whereas the survival advantage may be greater for UVM patients in the low-risk group. Knockdown of ITGA5 expression was shown to inhibit the proliferation, migration, and invasive ability of UVM cells in vitro experiments. Conclusion: The 3-BMRGs feature model we constructed has excellent predictive performance which plays a key role in the prognosis, informing the individualized treatment of UVM patients. It also provides a new perspective for assessing pre-immune efficacy.
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Affiliation(s)
- Yunyue Li
- Queen Mary College, Medical School of Nanchang University, Nanchang, China
| | - Huabao Cai
- Department of Neurosurgery, First Affiliated Hospital of Anhui Medical University, Hefei, China
| | - Jinyan Yang
- School of Stomatology, Southwest Medical University, Luzhou, China
| | - Xixi Xie
- School of Stomatology, Southwest Medical University, Luzhou, China
| | - Shengbin Pei
- Department of Breast Surgery, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China
| | - Yifan Wu
- Department of Breast Surgery, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China
| | - Jinhao Zhang
- School of Stomatology, Southwest Medical University, Luzhou, China
| | - Guobin Song
- School of Stomatology, Southwest Medical University, Luzhou, China
| | - Jieying Zhang
- First Teaching Hospital of Tianjin University of Traditional Chinese Medicine, Tianjin, China
| | - Qinhong Zhang
- Heilongjiang University of Chinese Medicine, Harbin, China
| | - Hao Chi
- Clinical Medical College, Southwest Medical University, Luzhou, China
| | - Guanhu Yang
- Department of Specialty Medicine, Ohio University, Athens, OH, United States
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Zhang S, Jiang C, Jiang L, Chen H, Huang J, Zhang J, Wang R, Chi H, Yang G, Tian G. Uncovering the immune microenvironment and molecular subtypes of hepatitis B-related liver cirrhosis and developing stable a diagnostic differential model by machine learning and artificial neural networks. Front Mol Biosci 2023; 10:1275897. [PMID: 37808522 PMCID: PMC10556489 DOI: 10.3389/fmolb.2023.1275897] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/10/2023] [Accepted: 09/14/2023] [Indexed: 10/10/2023] Open
Abstract
Background: Hepatitis B-related liver cirrhosis (HBV-LC) is a common clinical disease that evolves from chronic hepatitis B (CHB). The development of cirrhosis can be suppressed by pharmacological treatment. When CHB progresses to HBV-LC, the patient's quality of life decreases dramatically and drug therapy is ineffective. Liver transplantation is the most effective treatment, but the lack of donor required for transplantation, the high cost of the procedure and post-transplant rejection make this method unsuitable for most patients. Methods: The aim of this study was to find potential diagnostic biomarkers associated with HBV-LC by bioinformatics analysis and to classify HBV-LC into specific subtypes by consensus clustering. This will provide a new perspective for early diagnosis, clinical treatment and prevention of HCC in HBV-LC patients. Two study-relevant datasets, GSE114783 and GSE84044, were retrieved from the GEO database. We screened HBV-LC for feature genes using differential analysis, weighted gene co-expression network analysis (WGCNA), and three machine learning algorithms including least absolute shrinkage and selection operator (LASSO), support vector machine recursive feature elimination (SVM-RFE), and random forest (RF) for a total of five methods. After that, we constructed an artificial neural network (ANN) model. A cohort consisting of GSE123932, GSE121248 and GSE119322 was used for external validation. To better predict the risk of HBV-LC development, we also built a nomogram model. And multiple enrichment analyses of genes and samples were performed to understand the biological processes in which they were significantly enriched. And the different subtypes of HBV-LC were analyzed using the Immune infiltration approach. Results: Using the data downloaded from GEO, we developed an ANN model and nomogram based on six feature genes. And consensus clustering of HBV-LC classified them into two subtypes, C1 and C2, and it was hypothesized that patients with subtype C2 might have milder clinical symptoms by immune infiltration analysis. Conclusion: The ANN model and column line graphs constructed with six feature genes showed excellent predictive power, providing a new perspective for early diagnosis and possible treatment of HBV-LC. The delineation of HBV-LC subtypes will facilitate the development of future clinical treatment of HBV-LC.
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Affiliation(s)
- Shengke Zhang
- Department of Clinical Medicine, School of Clinical Medicine, Affiliated Hospital of Southwest Medical University, Luzhou, China
| | - Chenglu Jiang
- Department of Clinical Medicine, School of Clinical Medicine, Affiliated Hospital of Southwest Medical University, Luzhou, China
| | - Lai Jiang
- Department of Clinical Medicine, School of Clinical Medicine, Affiliated Hospital of Southwest Medical University, Luzhou, China
| | - Haiqing Chen
- Department of Clinical Medicine, School of Clinical Medicine, Affiliated Hospital of Southwest Medical University, Luzhou, China
| | - Jinbang Huang
- Department of Clinical Medicine, School of Clinical Medicine, Affiliated Hospital of Southwest Medical University, Luzhou, China
| | - Jieying Zhang
- First Teaching Hospital of Tianjin University of Traditional Chinese Medicine, Tianjin, China
- National Clinical Research Center for Chinese Medicine Acupuncture and Moxibustion, Tianjin, China
| | - Rui Wang
- Department of General Surgery (Hepatobiliary Surgery), The Affiliated Hospital of Southwest Medical University, Luzhou, China
- Nuclear Medicine and Molecular Imaging Key Laboratory of Sichuan Province, Luzhou, China
- Academician (Expert) Workstation of Sichuan Province, Luzhou, China
| | - Hao Chi
- Department of Clinical Medicine, School of Clinical Medicine, Affiliated Hospital of Southwest Medical University, Luzhou, China
| | - Guanhu Yang
- Department of Specialty Medicine, Ohio University, Athens, United States
| | - Gang Tian
- Department of Laboratory Medicine, The Affiliated Hospital of Southwest Medical University, Luzhou, China
- Molecular Diagnosis of Clinical Diseases Key Laboratory of Luzhou, Luzhou, China
- Sichuan Province Engineering Technology Research Center of Molecular Diagnosis of Clinical Diseases, Luzhou, China
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Xu W, Jiang T, Shen K, Zhao D, Zhang M, Zhu W, Liu Y, Xu C. GADD45B regulates the carcinogenesis process of chronic atrophic gastritis and the metabolic pathways of gastric cancer. Front Endocrinol (Lausanne) 2023; 14:1224832. [PMID: 37608794 PMCID: PMC10441793 DOI: 10.3389/fendo.2023.1224832] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/18/2023] [Accepted: 07/18/2023] [Indexed: 08/24/2023] Open
Abstract
Background Gastric cancer continues to be a significant global healthcare challenge, and its burden remains substantial. The development of gastric cancer (GC) is closely linked to chronic atrophic gastritis (CAG), yet there is a scarcity of research exploring the underlying mechanisms of CAG-induced carcinogenesis. Methods In this study, we conducted a comprehensive investigation into the oncogenes involved in CAG using both bulk transcriptome and single-cell transcriptome data. Our approach employed hdWGCNA to identify pathogenic genes specific to CAG, with non-atrophic gastritis (NAG) serving as the control group. Additionally, we compared CAG with GC, using normal gastric tissue as the control group in the single-cell transcriptome analysis. By intersecting the identified pathogenic genes, we pinpointed key network molecules through protein interaction network analysis. To further refine the gene selection, we applied LASSO, SVM-RFE, and RF techniques, which resulted in a set of cancer-related genes (CRGs) associated with CAG. To identify CRGs potentially linked to gastric cancer progression, we performed a univariate COX regression analysis on the gene set. Subsequently, we explored the relationship between CRGs and immune infiltration, drug sensitivity, and clinical characteristics in gastric cancer patients. We employed GSVA to investigate how CRGs regulated signaling pathways in gastric cancer cells, while an analysis of cell communication shed light on the impact of CRGs on signal transmission within the gastric cancer tumor microenvironment. Lastly, we analyzed changes in metabolic pathways throughout the progression of gastric cancer. Results Using hdWGCNA, we have identified a total of 143 pathogenic genes that were shared by CAG and GC. To further investigate the underlying mechanisms, we conducted protein interaction network analysis and employed machine learning screening techniques. As a result, we have identified 15 oncogenes that are specifically associated with chronic atrophic gastritis. By performing ROC reanalysis and prognostic analysis, we have determined that GADD45B is the most significant gene involved in the carcinogenesis of CAG. Immunohistochemical staining and differential analysis have revealed that GADD45B expression was low in GC tissues while high in normal gastric tissues. Moreover, based on prognostic analysis, high expression of GADD45B has been correlated with poor prognosis in GC patients. Additionally, an analysis of immune infiltration has shown a relationship between GADD45B and the infiltration of various immune cells. By correlating GADD45B with clinical characteristics, we have found that it primarily affects the depth of invasion in GC. Through cell communication analysis, we have discovered that the CD99 signaling pathway network and the CDH signaling pathway network are the main communication pathways that significantly alter the microenvironment of gastric tissue during the development of chronic atrophic gastritis. Specifically, GADD45B-low GC cells were predominantly involved in the network communication of the CDH signaling pathway, while GADD45B-high GC cells played a crucial role in both signaling pathways. Furthermore, we have identified several metabolic pathways, including D-Glutamine and D-glutamate metabolism and N-Glycan biosynthesis, among others, that played important roles in the occurrence and progression of GC, in addition to the six other metabolic pathways. In summary, our study highlighted the discovery of 143 pathogenic genes shared by CAG and GC, with a specific focus on 15 oncogenes associated with CAG. We have identified GADD45B as the most important gene in the carcinogenesis of CAG, which exhibited differential expression in GC tissues compared to normal gastric tissues. Moreover, GADD45B expression was correlated with patient prognosis and is associated with immune cell infiltration. Our findings also emphasized the impact of the CD99 and CDH signaling pathway networks on the microenvironment of gastric tissue during the development of CAG. Additionally, we have identified key metabolic pathways involved in GC progression. Conclusion GADD45B, an oncogene implicated in chronic atrophic gastritis, played a critical role in GC development. Decreased expression of GADD45B was associated with the onset of GC. Moreover, GADD45B expression levels were closely tied to poor prognosis in GC patients, influencing the infiltration patterns of various cells within the tumor microenvironment, as well as impacting the metabolic pathways involved in GC progression.
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Affiliation(s)
- Wei Xu
- Department of Gastroenterology, The First Affiliated Hospital of Soochow University, Suzhou, Jiangsu, China
| | - Tianxiao Jiang
- Department of General, Visceral, and Transplant Surgery, Ludwig-Maximilians-University Munich, Munich, Germany
| | - Kanger Shen
- Department of Gastroenterology, The First Affiliated Hospital of Soochow University, Suzhou, Jiangsu, China
| | - Dongxu Zhao
- Department of Interventional Radiology, The First Affiliated Hospital of Soochow University, Suzhou, Jiangsu, China
| | - Man Zhang
- Department of Emergency Medicine, The Affiliated Hospital of Xuzhou Medical University, Xuzhou, Jiangsu, China
| | - Wenxin Zhu
- Department of Gastroenterology, Kunshan Third People’s Hospital, Suzhou, Jiangsu, China
| | - Yunfei Liu
- Department of General, Visceral, and Transplant Surgery, Ludwig-Maximilians-University Munich, Munich, Germany
| | - Chunfang Xu
- Department of Gastroenterology, The First Affiliated Hospital of Soochow University, Suzhou, Jiangsu, China
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10
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Ren Q, Zhang P, Lin H, Feng Y, Chi H, Zhang X, Xia Z, Cai H, Yu Y. A novel signature predicts prognosis and immunotherapy in lung adenocarcinoma based on cancer-associated fibroblasts. Front Immunol 2023; 14:1201573. [PMID: 37325647 PMCID: PMC10264584 DOI: 10.3389/fimmu.2023.1201573] [Citation(s) in RCA: 26] [Impact Index Per Article: 26.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/06/2023] [Accepted: 05/17/2023] [Indexed: 06/17/2023] Open
Abstract
Background Extensive research has established the significant correlations between cancer-associated fibroblasts (CAFs) and various stages of cancer development, including initiation, angiogenesis, progression, and resistance to therapy. In this study, we aimed to investigate the characteristics of CAFs in lung adenocarcinoma (LUAD) and develop a risk signature to predict the prognosis of patients with LUAD. Methods We obtained single-cell RNA sequencing (scRNA-seq) and bulk RNA-seq data from the public database. The Seurat R package was used to process the scRNA-seq data and identify CAF clusters based on several biomarkers. CAF-related prognostic genes were further identified using univariate Cox regression analysis. To reduce the number of genes, Lasso regression was performed, and a risk signature was established. A novel nomogram that incorporated the risk signature and clinicopathological features was developed to predict the clinical applicability of the model. Additionally, we conducted immune landscape and immunotherapy responsiveness analyses. Finally, we performed in vitro experiments to verify the functions of EXO1 in LUAD. Results We identified 5 CAF clusters in LUAD using scRNA-seq data, of which 3 clusters were significantly associated with prognosis in LUAD. A total of 492 genes were found to be significantly linked to CAF clusters from 1731 DEGs and were used to construct a risk signature. Moreover, our immune landscape exploration revealed that the risk signature was significantly related to immune scores, and its ability to predict responsiveness to immunotherapy was confirmed. Furthermore, a novel nomogram incorporating the risk signature and clinicopathological features showed excellent clinical applicability. Finally, we verified the functions of EXP1 in LUAD through in vitro experiments. Conclusions The risk signature has proven to be an excellent predictor of LUAD prognosis, stratifying patients more appropriately and precisely predicting immunotherapy responsiveness. The comprehensive characterization of LUAD based on the CAF signature can predict the response of LUAD to immunotherapy, thus offering fresh perspectives into the management of LUAD patients. Our study ultimately confirms the role of EXP1 in facilitating the invasion and growth of tumor cells in LUAD. Nevertheless, further validation can be achieved by conducting in vivo experiments.
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Affiliation(s)
- Qianhe Ren
- Department of Thoracic Surgery, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China
| | - Pengpeng Zhang
- Department of Thoracic Surgery, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China
| | - Haoran Lin
- Department of Thoracic Surgery, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China
| | - Yanlong Feng
- Department of Thoracic Surgery, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China
| | - Hao Chi
- Clinical Medical College, Southwest Medical University, Luzhou, China
| | - Xiao Zhang
- Department of Thoracic Surgery, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China
| | - Zhijia Xia
- Department of General, Visceral, and Transplant Surgery, Ludwig-Maximilians-University, Munich, Germany
| | - Huabao Cai
- Department of Neurosurgery, First Affiliated Hospital of Anhui Medical University, Hefei, China
| | - Yue Yu
- Department of Thoracic Surgery, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China
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11
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Chi H, Gao X, Xia Z, Yu W, Yin X, Pan Y, Peng G, Mao X, Teichmann AT, Zhang J, Tran LJ, Jiang T, Liu Y, Yang G, Wang Q. FAM family gene prediction model reveals heterogeneity, stemness and immune microenvironment of UCEC. Front Mol Biosci 2023; 10:1200335. [PMID: 37275958 PMCID: PMC10235772 DOI: 10.3389/fmolb.2023.1200335] [Citation(s) in RCA: 25] [Impact Index Per Article: 25.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/04/2023] [Accepted: 05/09/2023] [Indexed: 06/07/2023] Open
Abstract
Background: Endometrial cancer (UCEC) is a highly heterogeneous gynecologic malignancy that exhibits variable prognostic outcomes and responses to immunotherapy. The Familial sequence similarity (FAM) gene family is known to contribute to the pathogenesis of various malignancies, but the extent of their involvement in UCEC has not been systematically studied. This investigation aimed to develop a robust risk profile based on FAM family genes (FFGs) to predict the prognosis and suitability for immunotherapy in UCEC patients. Methods: Using the TCGA-UCEC cohort from The Cancer Genome Atlas (TCGA) database, we obtained expression profiles of FFGs from 552 UCEC and 35 normal samples, and analyzed the expression patterns and prognostic relevance of 363 FAM family genes. The UCEC samples were randomly divided into training and test sets (1:1), and univariate Cox regression analysis and Lasso Cox regression analysis were conducted to identify the differentially expressed genes (FAM13C, FAM110B, and FAM72A) that were significantly associated with prognosis. A prognostic risk scoring system was constructed based on these three gene characteristics using multivariate Cox proportional risk regression. The clinical potential and immune status of FFGs were analyzed using CiberSort, SSGSEA, and tumor immune dysfunction and rejection (TIDE) algorithms. qRT-PCR and IHC for detecting the expression levels of 3-FFGs. Results: Three FFGs, namely, FAM13C, FAM110B, and FAM72A, were identified as strongly associated with the prognosis of UCEC and effective predictors of UCEC prognosis. Multivariate analysis demonstrated that the developed model was an independent predictor of UCEC, and that patients in the low-risk group had better overall survival than those in the high-risk group. The nomogram constructed from clinical characteristics and risk scores exhibited good prognostic power. Patients in the low-risk group exhibited a higher tumor mutational load (TMB) and were more likely to benefit from immunotherapy. Conclusion: This study successfully developed and validated novel biomarkers based on FFGs for predicting the prognosis and immune status of UCEC patients. The identified FFGs can accurately assess the prognosis of UCEC patients and facilitate the identification of specific subgroups of patients who may benefit from personalized treatment with immunotherapy and chemotherapy.
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Affiliation(s)
- Hao Chi
- Clinical Medical College, Southwest Medical University, Luzhou, China
| | - Xinrui Gao
- Clinical Medical College, Southwest Medical University, Luzhou, China
| | - Zhijia Xia
- Department of General, Visceral, and Transplant Surgery, Ludwig-Maximilians-University Munich, Munich, Germany
| | - Wanying Yu
- Clinical Medical College, Southwest Medical University, Luzhou, China
| | - Xisheng Yin
- Clinical Medical College, Southwest Medical University, Luzhou, China
| | - Yifan Pan
- Clinical Medical College, Southwest Medical University, Luzhou, China
| | - Gaoge Peng
- Clinical Medical College, Southwest Medical University, Luzhou, China
| | - Xinrui Mao
- Clinical Medical College, Southwest Medical University, Luzhou, China
| | - Alexander Tobias Teichmann
- Sichuan Provincial Center for Gynecology and Breast Diseases (Gynecology), Affiliated Hospital of Southwest Medical University, Luzhou, China
| | - Jing Zhang
- Division of Basic Biomedical Sciences, The University of South Dakota Sanford School of Medicine, Vermillion, SD, United States
| | - Lisa Jia Tran
- Department of General, Visceral, and Transplant Surgery, Ludwig-Maximilians-University Munich, Munich, Germany
| | - Tianxiao Jiang
- Department of General, Visceral, and Transplant Surgery, Ludwig-Maximilians-University Munich, Munich, Germany
| | - Yunfei Liu
- Department of General, Visceral, and Transplant Surgery, Ludwig-Maximilians-University Munich, Munich, Germany
| | - Guanhu Yang
- Department of Specialty Medicine, Ohio University, Athens, OH, United States
| | - Qin Wang
- Sichuan Provincial Center for Gynecology and Breast Diseases (Gynecology), Affiliated Hospital of Southwest Medical University, Luzhou, China
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12
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Wang Y, Huang X, Fan H, Xu Y, Qi Z, Zhang Y, Huang Y. Identification of fatty acid-related subtypes, the establishment of a prognostic signature, and immune infiltration characteristics in lung adenocarcinoma. Aging (Albany NY) 2023; 15:204725. [PMID: 37199651 DOI: 10.18632/aging.204725] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/15/2023] [Accepted: 05/03/2023] [Indexed: 05/19/2023]
Abstract
Abnormal fatty acid (FA) metabolism can change the inflammatory microenvironment and promote tumor progression and metastasis, however, the potential association between FA-related genes (FARGs) and lung adenocarcinoma (LUAD) is still unclear. In this study, we described the genetic and transcriptomic changes of FARGs in LUAD patients and identified two different FA subtypes, which were significantly correlated with overall survival and tumor microenvironment infiltrating cells in LUAD patients. In addition, the FA score was also constructed through the LASSO Cox to evaluate the FA dysfunction of each patient. Multivariate Cox analysis proved that the FA score was an independent predictor and created the FA score integrated nomogram, which offered a quantitative tool for clinical practice. The performance of the FA score has been substantiated in numerous datasets for its commendable accuracy in estimating overall survival in LUAD patients. The groups with high and low FA scores exhibited different mutation spectrums, copy number variations, enrichment pathways, and immune status. Noteworthy differences between the two groups in terms of immunophenoscore and Tumor Immune Dysfunction and Exclusion were observed, suggesting that the group with a low FA score was more responsive to immunotherapy, and similar results were also confirmed in the immunotherapy cohort. In addition, seven potential chemotherapeutic drugs related to FA score targeting were predicted. Ultimately, we ascertained that the attenuation of KRT6A expression impeded the proliferation, migration, and invasion of LUAD cell lines. In summary, this research offers novel biomarkers to facilitate prognostic forecasting and clinical supervision for individuals afflicted with LUAD.
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Affiliation(s)
- Yuzhi Wang
- Department of Laboratory Medicine, Deyang People’s Hospital, Deyang 618000, Sichuan, People’s Republic of China
| | - Xiaoxiao Huang
- Department of Laboratory Medicine, Liuzhou Hospital of Guangzhou Women and Children’s Medical Center, Liuzhou 545000, Guangxi, People’s Republic of China
- Guangxi Clinical Research Center for Obstetrics and Gynecology, Liuzhou 545000, Guangxi, People’s Republic of China
| | - Hong Fan
- Department of Pathology, Shanghai Jianding District Anting Hospital, Shanghai 200000, People’s Republic of China
| | - Yunfei Xu
- Department of Laboratory Medicine, Chengdu Women’s and Children’s Central Hospital, Chengdu 610031, Sichuan, People’s Republic of China
| | - Zelin Qi
- Department of Laboratory Medicine, Deyang People’s Hospital, Deyang 618000, Sichuan, People’s Republic of China
| | - Yi Zhang
- Shengli Clinical Medical College of Fujian Medical University, Fujian Medical University, Fuzhou 350001, Fujian, People’s Republic of China
- Department of Clinical Laboratory, Fujian Provincial Hospital, Fuzhou 350001, Fujian, People’s Republic of China
| | - Yi Huang
- Shengli Clinical Medical College of Fujian Medical University, Fujian Medical University, Fuzhou 350001, Fujian, People’s Republic of China
- Department of Clinical Laboratory, Fujian Provincial Hospital, Fuzhou 350001, Fujian, People’s Republic of China
- Central Laboratory, Center for Experimental Research in Clinical Medicine, Fujian Provincial Hospital, Fuzhou 350001, Fujian, People’s Republic of China
- Fujian Provincial Key Laboratory of Critical Care Medicine, Fujian Provincial Key Laboratory of Cardiovascular Disease, Fuzhou 350001, Fujian, People’s Republic of China
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13
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Dong J, Wang F, Gao X, Zhao H, Zhang J, Wang N, Liu Z, Yan X, Jin J, Ba Y, Ma S, Du J, Ji H, Hu S. Integrated analysis of genome-wide DNA methylation and cancer-associated fibroblasts identified prognostic biomarkers and immune checkpoint blockade in lower grade gliomas. Front Oncol 2023; 12:977251. [PMID: 36727078 PMCID: PMC9885112 DOI: 10.3389/fonc.2022.977251] [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: 06/24/2022] [Accepted: 12/28/2022] [Indexed: 01/18/2023] Open
Abstract
Background Cancer-associated fibroblasts (CAFs) are vital components of prominent cellular components in lower-grade gliomas (LGGs) that contribute to LGGs' progression, treatment resistance, and immunosuppression. Epigenetic modification and immunity have significant implications for tumorigenesis and development. Methods We combined aberrant methylation and CAFs abundances to build a prognostic model and the impact on the biological properties of LGGs. Grouping based on the median CAFs abundances score of samples in the TCGA-LGGs dataset, differentially expressed genes and aberrantly methylated genes were combined for subsequent analysis. Results We identified five differentially methylated and expressed genes (LAT32, SWAP70, GSAP, EMP3, and SLC2A10) and established a prognostic gene signature validated in the CGGA-LGGs dataset. Immunohistochemistry (IHC) and in vitro tests were performed to verify these expressions. The high-risk group increased in tumor-promoting immune cells and tumor mutational burden. Notably, risk stratification had different ICB sensitivities in LGGs, and there were also significant sensitivity differences for temozolomide and the other three novel chemotherapeutic agents. Conclusion Our study reveals characteristics of CAFs in LGGs, refines the direct link between epigenetics and tumor stroma, and might provide clinical implications for guiding tailored anti-CAFs therapy in combination with immunotherapy for LGGs patients.
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Affiliation(s)
- Jiawei Dong
- Cancer Center, Department of Neurosurgery, Zhejiang Provincial People’s Hospital, Affiliated People’s Hospital, Hangzhou Medical College, Hangzhou, Zhejiang, China,Department of Neurosurgery, The Second Affiliated Hospital of Harbin Medical University, Harbin, China
| | - Fang Wang
- Cancer Center, Department of Neurosurgery, Zhejiang Provincial People’s Hospital, Affiliated People’s Hospital, Hangzhou Medical College, Hangzhou, Zhejiang, China,Department of Neurosurgery, The Second Affiliated Hospital of Harbin Medical University, Harbin, China
| | - Xin Gao
- Cancer Center, Department of Neurosurgery, Zhejiang Provincial People’s Hospital, Affiliated People’s Hospital, Hangzhou Medical College, Hangzhou, Zhejiang, China
| | - Hongtao Zhao
- Cancer Center, Department of Neurosurgery, Zhejiang Provincial People’s Hospital, Affiliated People’s Hospital, Hangzhou Medical College, Hangzhou, Zhejiang, China,Department of Neurosurgery, The Second Affiliated Hospital of Harbin Medical University, Harbin, China
| | - Jiheng Zhang
- Cancer Center, Department of Neurosurgery, Zhejiang Provincial People’s Hospital, Affiliated People’s Hospital, Hangzhou Medical College, Hangzhou, Zhejiang, China,Department of Neurosurgery, The Second Affiliated Hospital of Harbin Medical University, Harbin, China
| | - Nan Wang
- Cancer Center, Department of Neurosurgery, Zhejiang Provincial People’s Hospital, Affiliated People’s Hospital, Hangzhou Medical College, Hangzhou, Zhejiang, China,Department of Neurosurgery, The Second Affiliated Hospital of Harbin Medical University, Harbin, China
| | - Zhihui Liu
- Cancer Center, Department of Neurosurgery, Zhejiang Provincial People’s Hospital, Affiliated People’s Hospital, Hangzhou Medical College, Hangzhou, Zhejiang, China,Department of Neurosurgery, The Second Affiliated Hospital of Harbin Medical University, Harbin, China
| | - Xiuwei Yan
- Cancer Center, Department of Neurosurgery, Zhejiang Provincial People’s Hospital, Affiliated People’s Hospital, Hangzhou Medical College, Hangzhou, Zhejiang, China,Department of Neurosurgery, The Second Affiliated Hospital of Harbin Medical University, Harbin, China
| | - Jiaqi Jin
- Cancer Center, Department of Neurosurgery, Zhejiang Provincial People’s Hospital, Affiliated People’s Hospital, Hangzhou Medical College, Hangzhou, Zhejiang, China,Department of Neurosurgery, The Second Affiliated Hospital of Harbin Medical University, Harbin, China
| | - Yixu Ba
- Cancer Center, Department of Neurosurgery, Zhejiang Provincial People’s Hospital, Affiliated People’s Hospital, Hangzhou Medical College, Hangzhou, Zhejiang, China,Department of Neurosurgery, The Second Affiliated Hospital of Harbin Medical University, Harbin, China
| | - Shuai Ma
- Cancer Center, Department of Neurosurgery, Zhejiang Provincial People’s Hospital, Affiliated People’s Hospital, Hangzhou Medical College, Hangzhou, Zhejiang, China,Department of Neurosurgery, The Second Affiliated Hospital of Harbin Medical University, Harbin, China
| | - Jianyang Du
- Cancer Center, Department of Neurosurgery, Zhejiang Provincial People’s Hospital, Affiliated People’s Hospital, Hangzhou Medical College, Hangzhou, Zhejiang, China
| | - Hang Ji
- Cancer Center, Department of Neurosurgery, Zhejiang Provincial People’s Hospital, Affiliated People’s Hospital, Hangzhou Medical College, Hangzhou, Zhejiang, China,Department of Neurosurgery, The Second Affiliated Hospital of Harbin Medical University, Harbin, China,*Correspondence: Shaoshan Hu, ; Hang Ji,
| | - Shaoshan Hu
- Cancer Center, Department of Neurosurgery, Zhejiang Provincial People’s Hospital, Affiliated People’s Hospital, Hangzhou Medical College, Hangzhou, Zhejiang, China,Department of Neurosurgery, The Second Affiliated Hospital of Harbin Medical University, Harbin, China,*Correspondence: Shaoshan Hu, ; Hang Ji,
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14
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Zhao S, Chi H, Yang Q, Chen S, Wu C, Lai G, Xu K, Su K, Luo H, Peng G, Xia Z, Cheng C, Lu P. Identification and validation of neurotrophic factor-related gene signatures in glioblastoma and Parkinson's disease. Front Immunol 2023; 14:1090040. [PMID: 36825022 PMCID: PMC9941742 DOI: 10.3389/fimmu.2023.1090040] [Citation(s) in RCA: 44] [Impact Index Per Article: 44.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/04/2022] [Accepted: 01/17/2023] [Indexed: 02/10/2023] Open
Abstract
Background Glioblastoma multiforme (GBM) is the most common cancer of the central nervous system, while Parkinson's disease (PD) is a degenerative neurological condition frequently affecting the elderly. Neurotrophic factors are key factors associated with the progression of degenerative neuropathies and gliomas. Methods The 2601 neurotrophic factor-related genes (NFRGs) available in the Genecards portal were analyzed and 12 NFRGs with potential roles in the pathogenesis of Parkinson's disease and the prognosis of GBM were identified. LASSO regression and random forest algorithms were then used to screen the key NFRGs. The correlation of the key NFRGs with immune pathways was verified using GSEA (Gene Set Enrichment Analysis). A prognostic risk scoring system was constructed using LASSO (Least absolute shrinkage and selection operator) and multivariate Cox risk regression based on the expression of the 12 NFRGs in the GBM cohort from The Cancer Genome Atlas (TCGA) database. We also investigated differences in clinical characteristics, mutational landscape, immune cell infiltration, and predicted efficacy of immunotherapy between risk groups. Finally, the accuracy of the model genes was validated using multi-omics mutation analysis, single-cell sequencing, QT-PCR, and HPA. Results We found that 4 NFRGs were more reliable for the diagnosis of Parkinson's disease through the use of machine learning techniques. These results were validated using two external cohorts. We also identified 7 NFRGs that were highly associated with the prognosis and diagnosis of GBM. Patients in the low-risk group had a greater overall survival (OS) than those in the high-risk group. The nomogram generated based on clinical characteristics and risk scores showed strong prognostic prediction ability. The NFRG signature was an independent prognostic predictor for GBM. The low-risk group was more likely to benefit from immunotherapy based on the degree of immune cell infiltration, expression of immune checkpoints (ICs), and predicted response to immunotherapy. In the end, 2 NFRGs (EN1 and LOXL1) were identified as crucial for the development of Parkinson's disease and the outcome of GBM. Conclusions Our study revealed that 4 NFRGs are involved in the progression of PD. The 7-NFRGs risk score model can predict the prognosis of GBM patients and help clinicians to classify the GBM patients into high and low risk groups. EN1, and LOXL1 can be used as therapeutic targets for personalized immunotherapy for patients with PD and GBM.
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Affiliation(s)
- Songyun Zhao
- Department of Neurosurgery, Wuxi People's Hospital Affiliated to Nanjing Medical University, Wuxi, Jiangsu, China
| | - Hao Chi
- Clinical Medical College, Southwest Medical University, Luzhou, China
| | - Qian Yang
- Clinical Molecular Medicine Testing Center, The First Affiliated Hospital of Chongqing Medical University, Chongqing, China
| | - Shi Chen
- Clinical Molecular Medicine Testing Center, The First Affiliated Hospital of Chongqing Medical University, Chongqing, China
| | - Chenxi Wu
- Department of Oncology, Wuxi People's Hospital Affiliated to Nanjing Medical University, Wuxi, Jiangsu, China
| | - Guichuan Lai
- Department of Epidemiology and Health Statistics, School of Public Health, Chongqing Medical University, Chongqing, China
| | - Ke Xu
- Department of Oncology, Chongqing General Hospital, Chongqing, China
| | - Ke Su
- Clinical Medical College, Southwest Medical University, Luzhou, China
| | - Honghao Luo
- Department of Radiology, Xichong People's Hospital, Nanchong, China
| | - Gaoge Peng
- Clinical Medical College, Southwest Medical University, Luzhou, China
| | - Zhijia Xia
- Department of General, Visceral, and Transplant Surgery, Ludwig-Maximilians-University Munich, Munich, Germany
| | - Chao Cheng
- Department of Neurosurgery, Wuxi People's Hospital Affiliated to Nanjing Medical University, Wuxi, Jiangsu, China
| | - Peihua Lu
- Department of Oncology, Wuxi People's Hospital Affiliated to Nanjing Medical University, Wuxi, Jiangsu, China.,Department of Clinical Research Center, Wuxi People's Hospital of Nanjing Medical University, Wuxi, Jiangsu, China
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