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Leng W, Ye J, Wen Z, Wang H, Zhu Z, Song X, Liu K. GABRD Accelerates Tumour Progression via Regulating CCND1 Signalling Pathway in Gastric Cancer. J Cell Mol Med 2025; 29:e70485. [PMID: 40145254 PMCID: PMC11947670 DOI: 10.1111/jcmm.70485] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/11/2024] [Revised: 02/10/2025] [Accepted: 02/27/2025] [Indexed: 03/28/2025] Open
Abstract
Neurotransmitters and their receptors were reported to be involved in tumour initiation and progression. However, little is known about their roles in gastric cancer (GC). Here, we first identified gamma-aminobutyric acid type A receptor subunit delta (GABRD) as a novel oncogene in GC. GABRD was preferentially upregulated in GC tissues compared with adjacent normal tissues. High GABRD expression was significantly associated with poor survival prognosis. Knockdown of GABRD could markedly induce cell apoptosis and cell cycle arrest while repressing proliferation and migration in vitro, and suppress tumour growth in vivo. The results of transcriptomic analysis and Ingenuity pathway analysis (IPA) highlighted that cyclin D1(CCND1) was a potential downstream target. Immunohistochemistry results also indicated that CCND1 expression was associated with GABRD in GC. Functional experiments also confirmed that the role of GABRD in regulating proliferation, migration, invasion, and apoptosis was dependent on CCND1. Mechanically, further research confirmed that GABRD knockdown could induce p53-dependent apoptosis through CCND1, and GABRD upregulated CCDN1 through inhibiting its ubiquitin-mediated degradation. Overall, these findings uncover a role for the neurotransmitter receptor GABRD in regulating the proliferation and apoptosis of gastric cancer cells. Our present study provides novel insights into the mechanism of tumourigenesis in gastric cancer.
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Affiliation(s)
- Weibing Leng
- Colorectal Cancer CenterSichuan University West China HospitalChengduSichuanChina
- Department of Medical OncologySichuan University West China HospitalChengduSichuanChina
| | - Jun Ye
- Department of ProctologyTraditional Chinese Medicine Hospital of LongquanyiChengduSichuanChina
| | - Zhenpeng Wen
- Department of Medical OncologySichuan University West China HospitalChengduSichuanChina
| | - Han Wang
- West China School of MedicineSichuan UniversityChengduSichuanChina
| | - Zhenyu Zhu
- Department of Gastrointestinal SurgeryShandong Cancer Hospital and Institute, Shandong First Medical University and Shandong Academy of Medical SciencesJinanShandongChina
| | - Xilin Song
- Department of Gastrointestinal SurgeryShandong Cancer Hospital and Institute, Shandong First Medical University and Shandong Academy of Medical SciencesJinanShandongChina
| | - Kai Liu
- Department of Gastrointestinal SurgeryShandong Cancer Hospital and Institute, Shandong First Medical University and Shandong Academy of Medical SciencesJinanShandongChina
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Wu H, Zhang W, Chang J, Wu J, Zhang X, Jia F, Li L, Liu M, Zhu J. Comprehensive analysis of mitochondrial-related gene signature for prognosis, tumor immune microenvironment evaluation, and candidate drug development in colon cancer. Sci Rep 2025; 15:6173. [PMID: 39979377 PMCID: PMC11842742 DOI: 10.1038/s41598-024-85035-2] [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: 12/29/2023] [Accepted: 12/30/2024] [Indexed: 02/22/2025] Open
Abstract
Colon adenocarcinoma (COAD), a common digestive system malignancy, involves crucial alterations in mitochondria-related genes influencing tumor growth, metastasis, and immune evasion. Despite limited studies on prognostic models for these genes in COAD, we established a mitochondrial-related risk prognostic model, including nine genes based on available TCGA and MitoCarta 3.0 databases, and validated its predictive power. We investigated the tumor microenvironment (TME), immune cell infiltration, complex cell communication, tumor mutation burden, and drug sensitivity of COAD patients using R language, CellChat, and additional bioinformatic tools from single-cell and bulk-tissue sequencing data. The risk model revealed significant differences in immune cell infiltration between high-risk and low-risk groups, with the strongest correlation found between tissue stem cells and macrophages in COAD. The risk score exhibited a robust correlation with TME signature genes and immune checkpoint molecules. Integrating the risk score with the immune score, microsatellite status, or TMB through TIDE analysis enhanced the accuracy of predicting immunotherapy benefits. Predicted drug efficacy offered options for both high- and low-risk group patients. Our study established a novel mitochondrial-related nine-gene prognostic signature, providing insights for prognostic assessment and clinical decision-making in COAD patients.
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Affiliation(s)
- Hao Wu
- Department of Medical Cell Biology and Genetics, School of Basic Medical Science, Shanxi Medical University, Taiyuan, 030001, China
| | - Wentao Zhang
- Department of Medical Cell Biology and Genetics, School of Basic Medical Science, Shanxi Medical University, Taiyuan, 030001, China
| | - Jingjia Chang
- Department of Medical Cell Biology and Genetics, School of Basic Medical Science, Shanxi Medical University, Taiyuan, 030001, China
| | - Jin Wu
- Department of Molecular & Cellular Biology, Roswell Park Comprehensive Cancer Center, Elm and Carlton Streets, Buffalo, NY, 14263, USA
| | - Xintong Zhang
- Department of Medical Cell Biology and Genetics, School of Basic Medical Science, Shanxi Medical University, Taiyuan, 030001, China
| | - Fengfeng Jia
- Taiyuan Technology Transfer Promotion Center, Taiyuan, 030006, China
| | - Li Li
- Department of Medical Cell Biology and Genetics, School of Basic Medical Science, Shanxi Medical University, Taiyuan, 030001, China
| | - Ming Liu
- Department of Medical Cell Biology and Genetics, School of Basic Medical Science, Shanxi Medical University, Taiyuan, 030001, China.
| | - Jianjun Zhu
- Department of Medical Cell Biology and Genetics, School of Basic Medical Science, Shanxi Medical University, Taiyuan, 030001, China.
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Xu L, Li B, Liu Y, Hu Z, Dan Q, Xu B, Xiang H, Chen Y, Zheng T, Sun D, Liu L. Unveiling KLHL23 as a key immune regulator in hepatocellular carcinoma through integrated analysis. Aging (Albany NY) 2024; 16:13608-13626. [PMID: 39636292 PMCID: PMC11723656 DOI: 10.18632/aging.206167] [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: 02/10/2024] [Accepted: 10/22/2024] [Indexed: 12/07/2024]
Abstract
Age-related cancers are characterized by impaired protein homeostasis, where Kelch protein superfamily members have showed accumulating clues as critical regulators. In this paper, the cancerous role of Kelch-like family member 23 (KLHL23) was comprehensively analyzed with TCGA and single cell GEO database across overall 33 cancer types. By multi-omics analysis upon the transcriptomic, genomic, and methylation data, the current study explored the association of KLHL23 with patient survival, gene ontology, tumor-infiltrating lymphocytes, and drug responses. The correlation of copy number variations and methylation with dysregulated expression of KLHL23 were also addressed. Notably, KLHL23 levels correlated with survival in cancers such as hepatocellular carcinoma and low-grade glioma. The study also highlighted how reduced KLHL23 expression is linked to increased immune activity and sensitivity to chemotherapy, suggesting its potential as a biomarker for cancer prognosis and treatment responsiveness.
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MESH Headings
- Humans
- Carcinoma, Hepatocellular/genetics
- Carcinoma, Hepatocellular/metabolism
- Carcinoma, Hepatocellular/immunology
- Carcinoma, Hepatocellular/pathology
- Liver Neoplasms/genetics
- Liver Neoplasms/pathology
- Liver Neoplasms/metabolism
- Liver Neoplasms/immunology
- DNA Copy Number Variations
- Gene Expression Regulation, Neoplastic
- Biomarkers, Tumor/genetics
- Biomarkers, Tumor/metabolism
- Prognosis
- DNA Methylation
- Lymphocytes, Tumor-Infiltrating/immunology
- Lymphocytes, Tumor-Infiltrating/metabolism
- Databases, Genetic
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Affiliation(s)
- Liangliang Xu
- Shenzhen Key Laboratory for Drug Addiction and Medication Safety, Department of Ultrasound, Institute of Ultrasonic Medicine, Peking University Shenzhen Hospital, Shenzhen Peking University-The Hong Kong University of Science and Technology Medical Center, Shenzhen 518036, China China
- Department of Clinical Oncology, The University of Hong Kong-Shenzhen Hospital, Shenzhen 518053, China
| | - Bo Li
- Guangdong-Hong Kong-Macau University Joint Laboratory of Digestive Cancer Research, Scientific Research Center, The Seventh Affiliated Hospital, Sun Yat-Sen University, Shenzhen 518107, China
| | - Yuchen Liu
- Guangdong Provincial Key Laboratory of Digestive Cancer Research, Scientific Research Center, The Seventh Affiliated Hospital of Sun Yat-Sen University, Shenzhen 518107, China
| | - Zhengming Hu
- Shenzhen Key Laboratory for Drug Addiction and Medication Safety, Department of Ultrasound, Institute of Ultrasonic Medicine, Peking University Shenzhen Hospital, Shenzhen Peking University-The Hong Kong University of Science and Technology Medical Center, Shenzhen 518036, China China
| | - Qing Dan
- Shenzhen Key Laboratory for Drug Addiction and Medication Safety, Department of Ultrasound, Institute of Ultrasonic Medicine, Peking University Shenzhen Hospital, Shenzhen Peking University-The Hong Kong University of Science and Technology Medical Center, Shenzhen 518036, China China
| | - Bingxuan Xu
- Shenzhen Key Laboratory for Drug Addiction and Medication Safety, Department of Ultrasound, Institute of Ultrasonic Medicine, Peking University Shenzhen Hospital, Shenzhen Peking University-The Hong Kong University of Science and Technology Medical Center, Shenzhen 518036, China China
| | - Hongjin Xiang
- Shenzhen Key Laboratory for Drug Addiction and Medication Safety, Department of Ultrasound, Institute of Ultrasonic Medicine, Peking University Shenzhen Hospital, Shenzhen Peking University-The Hong Kong University of Science and Technology Medical Center, Shenzhen 518036, China China
| | - Yun Chen
- Shenzhen Key Laboratory for Drug Addiction and Medication Safety, Department of Ultrasound, Institute of Ultrasonic Medicine, Peking University Shenzhen Hospital, Shenzhen Peking University-The Hong Kong University of Science and Technology Medical Center, Shenzhen 518036, China China
| | - Tingting Zheng
- Shenzhen Key Laboratory for Drug Addiction and Medication Safety, Department of Ultrasound, Institute of Ultrasonic Medicine, Peking University Shenzhen Hospital, Shenzhen Peking University-The Hong Kong University of Science and Technology Medical Center, Shenzhen 518036, China China
| | - Desheng Sun
- Shenzhen Key Laboratory for Drug Addiction and Medication Safety, Department of Ultrasound, Institute of Ultrasonic Medicine, Peking University Shenzhen Hospital, Shenzhen Peking University-The Hong Kong University of Science and Technology Medical Center, Shenzhen 518036, China China
| | - Li Liu
- Shenzhen Key Laboratory for Drug Addiction and Medication Safety, Department of Ultrasound, Institute of Ultrasonic Medicine, Peking University Shenzhen Hospital, Shenzhen Peking University-The Hong Kong University of Science and Technology Medical Center, Shenzhen 518036, China China
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Hu ZX, Li Y, Yang X, Li YX, He YY, Niu XH, Nie TT, Guo XF, Yuan ZL. Constructing a nomogram to predict overall survival of colon cancer based on computed tomography characteristics and clinicopathological factors. World J Gastrointest Oncol 2024; 16:4104-4114. [DOI: 10.4251/wjgo.v16.i10.4104] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/18/2024] [Revised: 08/18/2024] [Accepted: 09/06/2024] [Indexed: 09/26/2024] Open
Abstract
BACKGROUND The colon cancer prognosis is influenced by multiple factors, including clinical, pathological, and non-biological factors. However, only a few studies have focused on computed tomography (CT) imaging features. Therefore, this study aims to predict the prognosis of patients with colon cancer by combining CT imaging features with clinical and pathological characteristics, and establishes a nomogram to provide critical guidance for the individualized treatment.
AIM To establish and validate a nomogram to predict the overall survival (OS) of patients with colon cancer.
METHODS A retrospective analysis was conducted on the survival data of 249 patients with colon cancer confirmed by surgical pathology between January 2017 and December 2021. The patients were randomly divided into training and testing groups at a 1:1 ratio. Univariate and multivariate logistic regression analyses were performed to identify the independent risk factors associated with OS, and a nomogram model was constructed for the training group. Survival curves were calculated using the Kaplan–Meier method. The concordance index (C-index) and calibration curve were used to evaluate the nomogram model in the training and testing groups.
RESULTS Multivariate logistic regression analysis revealed that lymph node metastasis on CT, perineural invasion, and tumor classification were independent prognostic factors. A nomogram incorporating these variables was constructed, and the C-index of the training and testing groups was 0.804 and 0.692, respectively. The calibration curves demonstrated good consistency between the actual values and predicted probabilities of OS.
CONCLUSION A nomogram combining CT imaging characteristics and clinicopathological factors exhibited good discrimination and reliability. It can aid clinicians in risk stratification and postoperative monitoring and provide important guidance for the individualized treatment of patients with colon cancer.
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Affiliation(s)
- Zhe-Xing Hu
- Department of Radiology, Hubei Cancer Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430079, Hubei Province, China
| | - Yin Li
- Department of Radiology, Hubei Cancer Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430079, Hubei Province, China
| | - Xuan Yang
- Department of Radiology, Wuhan Children’s Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430014, Hubei Province, China
| | - Yu-Xia Li
- College of Informatics, Huazhong Agriculture University, Wuhan 430070, Hubei Province, China
| | - Yao-Yao He
- Department of Radiology, Hubei Cancer Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430079, Hubei Province, China
| | - Xiao-Hui Niu
- College of Informatics, Huazhong Agriculture University, Wuhan 430070, Hubei Province, China
| | - Ting-Ting Nie
- Department of Radiology, Hubei Cancer Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430079, Hubei Province, China
| | - Xiao-Fang Guo
- Department of Radiology, Hubei Cancer Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430079, Hubei Province, China
| | - Zi-Long Yuan
- Department of Radiology, Hubei Cancer Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430079, Hubei Province, China
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Liu H, Shi H, Sun Y. Identification of a novel lymphangiogenesis signature associated with immune cell infiltration in colorectal cancer based on bioinformatics analysis. BMC Med Genomics 2024; 17:2. [PMID: 38167072 PMCID: PMC10763205 DOI: 10.1186/s12920-023-01781-8] [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: 08/07/2023] [Accepted: 12/16/2023] [Indexed: 01/05/2024] Open
Abstract
BACKGROUND Lymphangiogenesis plays an important role in tumor progression and is significantly associated with tumor immune infiltration. However, the role and mechanisms of lymphangiogenesis in colorectal cancer (CRC) are still unknown. Thus, the objective is to identify the lymphangiogenesis-related genes associated with immune infiltration and investigation of their prognosis value. METHODS mRNA expression profiles and corresponding clinical information of CRC samples were obtained from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. The lymphangiogenesis-related genes (LymRGs) were collected from the Molecular Signatures database (MSigDB). Lymphangiogenesis score (LymScore) and immune cell infiltrating levels were quantified using ssGSEA. LymScore) and immune cell infiltrating levels-related hub genes were identified using weighted gene co-expression network analysis (WGCNA). Univariate Cox and LASSO regression analyses were performed to identify the prognostic gene signature and construct a risk model. Furthermore, a predictive nomogram was constructed based on the independent risk factor generated from a multivariate Cox model. RESULTS A total of 1076 LymScore and immune cell infiltrating levels-related hub genes from three key modules were identified by WGCNA. Lymscore is positively associated with natural killer cells as well as regulator T cells infiltrating. These modular genes were enriched in extracellular matrix and structure, collagen fibril organization, cell-substrate adhesion, etc. NUMBL, TSPAN11, PHF21A, PDGFRA, ZNF385A, and RIMKLB were eventually identified as the prognostic gene signature in CRC. And patients were divided into high-risk and low-risk groups based on the median risk score, the patients in the high-risk group indicated poor survival and were predisposed to metastasis and advanced stages. NUMBL and PHF21A were upregulated but PDGFRA was downregulated in tumor samples compared with normal samples in the Human Protein Atlas (HPA) database. CONCLUSION Our finding highlights the critical role of lymphangiogenesis in CRC progression and metastasis and provides a novel gene signature for CRC and novel therapeutic strategies for anti-lymphangiogenic therapies in CRC.
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Affiliation(s)
- Hong Liu
- Department of General Surgery, Wuxi Fifth People's Hospital Affiliated to Jiangnan University, Wuxi, Jiangsu, China
| | - Huiwen Shi
- Department of General Surgery, No.971 Hospital of PLA Navy, Qingdao, China
| | - Yinggang Sun
- Department of General Surgery, The 960th Hospital of Joint Logistics Support Force of Chinese People's Liberation Army, Jinan, China.
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Liu Z, Xu Y, Jin S, Liu X, Wang B. Construction of a Prognostic Model Based on Methylation-Related Genes in Patients with Colon Adenocarcinoma. Cancer Manag Res 2023; 15:1097-1110. [PMID: 37818334 PMCID: PMC10561619 DOI: 10.2147/cmar.s417897] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/19/2023] [Accepted: 09/22/2023] [Indexed: 10/12/2023] Open
Abstract
Purpose Colon adenocarcinoma (COAD) is the second leading cause of death in the world, and the new incidence rate ranks third among all cancers. Abnormal DNA methylation is related to the occurrence and development of tumors. In this study, we aimed to identify genes associated with abnormal methylation in COAD. Methods COAD transcriptome data, methylation data and clinical information were downloaded from the TCGA database and GEO database. The differentially expressed genes (DEGs) and methylated genes (DMGs) were analyzed and identified in COAD. PCA analysis was applied to divide COAD into subtypes, and the survival and immune cell infiltration of each subtype were evaluated. Cox and LASSO analyses were performed to construct COAD risk model. GSEA was used to evaluate the enrichment pathways. The Kaplan-Meier was used to analyze the difference in survival. ROC curve was plotted to evaluate the accuracy of the model, and GSE17536 was used to verify the accuracy of the risk model. The risk model is combined with the clinicopathological characteristics of COAD patients to perform multivariate Cox regression analysis to obtain independent risk factors and draw nomograms. Results In total, 4564 DEGs and 1093 DMGs were screened, among which 298 were found to be overlapping genes. For 220 of these overlapping genes, the methylation was significantly negatively correlated to expression levels. An optimal signature from 4 methylated biomarkers was identified to construct the prognostic model. Conclusion Our study identified 4 methylated biomarkers in the COAD. Then, we constructed the risk model to provide a theoretical basis and reference value for the research and treatment of COAD.
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Affiliation(s)
- ZhenDong Liu
- Department of General Surgery, Hainan General Hospital, Hainan Affiliated Hospital of Hainan Medical University, Haikou, Hainan Province, People’s Republic of China
| | - YuYang Xu
- Department of General Surgery, Hainan General Hospital, Hainan Affiliated Hospital of Hainan Medical University, Haikou, Hainan Province, People’s Republic of China
| | - Shan Jin
- Department of Anesthesiology, Second Affiliated Hospital of Hainan Medical University, Haikou, Hainan Province, People’s Republic of China
| | - Xin Liu
- Department of General Surgery, Hainan General Hospital, Hainan Affiliated Hospital of Hainan Medical University, Haikou, Hainan Province, People’s Republic of China
| | - BaoChun Wang
- Department of General Surgery, Hainan General Hospital, Hainan Affiliated Hospital of Hainan Medical University, Haikou, Hainan Province, People’s Republic of China
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Pillai M, Hojel E, Jolly MK, Goyal Y. Unraveling non-genetic heterogeneity in cancer with dynamical models and computational tools. NATURE COMPUTATIONAL SCIENCE 2023; 3:301-313. [PMID: 38177938 DOI: 10.1038/s43588-023-00427-0] [Citation(s) in RCA: 16] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/30/2022] [Accepted: 03/03/2023] [Indexed: 01/06/2024]
Abstract
Individual cells within an otherwise genetically homogenous population constantly undergo fluctuations in their molecular state, giving rise to non-genetic heterogeneity. Such diversity is being increasingly implicated in cancer therapy resistance and metastasis. Identifying the origins of non-genetic heterogeneity is therefore crucial for making clinical breakthroughs. We discuss with examples how dynamical models and computational tools have provided critical multiscale insights into the nature and consequences of non-genetic heterogeneity in cancer. We demonstrate how mechanistic modeling has been pivotal in establishing key concepts underlying non-genetic diversity at various biological scales, from population dynamics to gene regulatory networks. We discuss advances in single-cell longitudinal profiling techniques to reveal patterns of non-genetic heterogeneity, highlighting the ongoing efforts and challenges in statistical frameworks to robustly interpret such multimodal datasets. Moving forward, we stress the need for data-driven statistical and mechanistically motivated dynamical frameworks to come together to develop predictive cancer models and inform therapeutic strategies.
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Affiliation(s)
- Maalavika Pillai
- Department of Cell and Developmental Biology, Feinberg School of Medicine, Northwestern University, Chicago, IL, USA
- Center for Synthetic Biology, Northwestern University, Chicago, IL, USA
- Robert H. Lurie Comprehensive Cancer Center, Northwestern University Feinberg School of Medicine, Chicago, IL, USA
- Centre for BioSystems Science and Engineering, Indian Institute of Science, Bangalore, India
| | - Emilia Hojel
- Department of Cell and Developmental Biology, Feinberg School of Medicine, Northwestern University, Chicago, IL, USA
- Center for Synthetic Biology, Northwestern University, Chicago, IL, USA
- Department of Biomedical Engineering, Northwestern University McCormick School of Engineering, Evanston, IL, USA
| | - Mohit Kumar Jolly
- Centre for BioSystems Science and Engineering, Indian Institute of Science, Bangalore, India.
| | - Yogesh Goyal
- Department of Cell and Developmental Biology, Feinberg School of Medicine, Northwestern University, Chicago, IL, USA.
- Center for Synthetic Biology, Northwestern University, Chicago, IL, USA.
- Robert H. Lurie Comprehensive Cancer Center, Northwestern University Feinberg School of Medicine, Chicago, IL, USA.
- Department of Biomedical Engineering, Northwestern University McCormick School of Engineering, Evanston, IL, USA.
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Sawaki K, Kanda M, Baba H, Inokawa Y, Hattori N, Hayashi M, Tanaka C, Kodera Y. Gamma-aminobutyric Acid Type A Receptor Subunit Delta as a Potential Therapeutic Target in Gastric Cancer. Ann Surg Oncol 2023; 30:628-636. [PMID: 36127526 DOI: 10.1245/s10434-022-12573-2] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/08/2022] [Accepted: 08/28/2022] [Indexed: 12/13/2022]
Abstract
BACKGROUND Novel therapeutic targets are needed to improve the poor prognosis of patients with advanced gastric cancer. The aim of this study was to identify a novel therapeutic target for the treatment of GC and to investigate the potential therapeutic value of an antibody raised against the target. METHODS We identified gamma-aminobutyric acid type A receptor subunit delta as a candidate therapeutic target by differential transcriptome analysis of metastatic GC tissue and adjacent nontumor tissues. GABRD mRNA levels were analyzed in 230 pairs of gastric tissue by quantitative reverse-transcription polymerase chain reaction. GABRD function was assessed in proliferation, invasion, and apoptosis assays in human GC cell lines expressing control or GABRD-targeting small interfering RNA (siRNA). Mouse anti-human polyclonal GABRD antibodies were generated and assessed for inhibition of GC cell growth in vitro and in a mouse xenograft model of peritoneal GC dissemination. RESULTS High GABRD mRNA expression level in primary human GC tissue was associated with poor prognosis. Expression of siGABRD in GC cell lines significantly decreased cell proliferation and invasion and increased apoptosis compared with control siRNA expression. Anti-GABRD polyclonal antibodies inhibited GC cell proliferation in vitro and decreased peritoneal tumor nodule size in the mouse xenograft model. CONCLUSION We identified GABRD as novel regulator of GC cell growth and function. GABRD is upregulated in GC tissue and is associated with poor prognosis, suggesting that it may be a potential therapeutic target for GC.
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Affiliation(s)
- Koichi Sawaki
- Department of Gastroenterological Surgery, Nagoya University Graduate School of Medicine, Nagoya, Japan
| | - Mitsuro Kanda
- Department of Gastroenterological Surgery, Nagoya University Graduate School of Medicine, Nagoya, Japan.
| | - Hayato Baba
- Department of Surgery and Science, Graduate School of Medicine and Pharmaceutical Sciences, University of Toyama, Toyama, Japan
| | - Yoshikuni Inokawa
- Department of Gastroenterological Surgery, Nagoya University Graduate School of Medicine, Nagoya, Japan
| | - Norifumi Hattori
- Department of Gastroenterological Surgery, Nagoya University Graduate School of Medicine, Nagoya, Japan
| | - Masamichi Hayashi
- Department of Gastroenterological Surgery, Nagoya University Graduate School of Medicine, Nagoya, Japan
| | - Chie Tanaka
- Department of Gastroenterological Surgery, Nagoya University Graduate School of Medicine, Nagoya, Japan
| | - Yasuhiro Kodera
- Department of Gastroenterological Surgery, Nagoya University Graduate School of Medicine, Nagoya, Japan
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Calderillo Ruiz G, Lopez Basave H, Vazquez Renteria RS, Castillo Morales A, Guijosa A, Castillo Morales C, Herrera M, Diaz C, Vazquez Cortes E, Ruiz-Garcia E, Munoz Montano WR. The Prognostic Significance of HALP Index for Colon Cancer Patients in a Hispanic-Based Population. JOURNAL OF ONCOLOGY 2022; 2022:4324635. [PMID: 36467502 PMCID: PMC9711950 DOI: 10.1155/2022/4324635] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/16/2022] [Revised: 10/11/2022] [Accepted: 10/17/2022] [Indexed: 10/04/2023]
Abstract
Background Survival and recurrence rates following locoregional colon cancer surgical resection are highly variable. Currently used tools to assess patient risk are still imperfect. In the present work, we evaluate, for the first time, the prognostic value of the recently developed HALP (hemoglobin, albumin, lymphocyte, and platelet) index in Hispanic colon cancer patients. Patients and Methods. We conducted a retrospective cohort study in Mexican patients with a nonmetastatic colon cancer diagnosis who underwent surgical resection. We determined the preoperative HALP score optimal cut-off value by using the X-tile software. We plotted survival curves using the Kaplan-Meier method and performed a multivariate Cox regression analysis to explore the association of preoperative HALP score with two primary endpoints: overall survival (OS) and disease-free survival (DFS). Results We included 640 patients (49.8% female). The optimal HALP cut-off value was 15.0. A low HALP index was statistically significantly associated with a higher TNM stage. Low HALP score was statistically significantly associated with shorter median OS in the Kaplan-Meier analysis (73.5 vs. 84.8 months) and in the multivariate Cox regression analysis (HR = 1.942, 95% CI = 1.647-2.875). There was no significant association between the HALP score and DFS. Conclusions Our findings show that the HALP index is an independent factor associated with survival in Hispanic patients, despite recurrence. It seems to reflect both the anatomical extent of the disease and traditionally unaccounted nutritional and inflammatory factors that are significant for prognosis.
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Affiliation(s)
| | - Horacio Lopez Basave
- Gastrointestinal Oncology Unit, Instituto Nacional de Cancerologia, Mexico, Mexico
| | | | | | - Alberto Guijosa
- School of Medicine, Universidad Panamericana, Mexico, Mexico
| | | | - Marytere Herrera
- Gastrointestinal Oncology Unit, Instituto Nacional de Cancerologia, Mexico, Mexico
| | - Consuelo Diaz
- Gastrointestinal Oncology Unit, Instituto Nacional de Cancerologia, Mexico, Mexico
| | | | - Erika Ruiz-Garcia
- Gastrointestinal Oncology Unit, Instituto Nacional de Cancerologia, Mexico, Mexico
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Niu M, Chen C, Gao X, Guo Y, Zhang B, Wang X, Chen S, Niu X, Zhang C, Li L, Li Z, Zhao Z, Jiang X. Comprehensive analysis of the differences between left- and right-side colorectal cancer and respective prognostic prediction. BMC Gastroenterol 2022; 22:482. [PMID: 36419007 DOI: 10.1186/s12876-022-02585-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/12/2022] [Accepted: 11/16/2022] [Indexed: 11/25/2022] Open
Abstract
Abstract
Background
Previous studies have reported that the tumor heterogeneity and complex oncogenic mechanisms of proximal and distal colon cancer (CRC) are divergent. Therefore, we aim to analyze the differences between left-sided CRC (L_cancer) and right-sided CRC (R_cancer), as well as constructing respective nomograms.
Methods
We enrolled 335 colon cancer patients (146 L_cancer patients and 189 R_cancer patients) from The Cancer Genome Atlas (TCGA) data sets, and 102 pairs of color cancer tissue and adjacent normal tissue (51 L_cancer patients and 51 R_cancer patients) from our hospital. Firstly, we analyzed the differences between the L_cancer patients and R_cancer patients, and then established the L_cancer and R_cancer prognostic models using LASSO Cox.
Results
R_cancer patients had lower survival than L_cancer patients. R_cancer patients had higher ESTIMATE and immune scores and lower tumor purity. These patterns of expression of immune checkpoint-related genes and TMB level were higher in R_cancer than in L_cancer patients. Finally, we using Lasso Cox regression analyses established a prognostic model for L_cancer patients and a prognostic model for R_cancer patients. The AUC values of the risk score for OS in L_cancer were 0.862 in the training set and 0.914 in the testing set, while those in R_cancer were 0.835 in the training set and 0.857 in the testing set. The AUC values in fivefold cross-validation were between 0.727 and 0.978, proving that the two prognostic models have great stability. The nomogram of L_cancer included prognostic genes, age, pathological M, pathological stage, and gender, the AUC values of which were 0.800 in the training set and 0.905 in the testing set. Meanwhile, the nomogram of R_cancer comprised prognostic genes, pathological N, pathological T, and age, the AUC values of which were 0.836 in the training set and 0.850 in the testing set. In the R_cancer patients, high-risk patients had a lower proportion of ‘B cells memory’, ‘Dendritic cells resting’, immune score, ESTIMATE score, immune checkpoint-related genes, and HLA-family genes, and a higher proportion of ‘T cells follicular helper’, ‘Dendritic cells activated’, and ‘Mast cells activated’.
Conclusions
We found significant differences between L_cancer and R_cancer patients and established a clinical predictive nomogram for L_cancer patients and a nomogram for R_cancer patients. Additionally, R_cancer patients in low-risk groups may be more beneficial from immunotherapy.
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11
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Li Z, Zhou J, Gu L, Zhang B. Pseudogenes and the associated ceRNA network as potential prognostic biomarkers for colorectal cancer. Sci Rep 2022; 12:17787. [PMID: 36272991 PMCID: PMC9588006 DOI: 10.1038/s41598-022-22768-y] [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: 11/11/2021] [Accepted: 10/19/2022] [Indexed: 01/19/2023] Open
Abstract
Colorectal cancer (CRC) is one of the most common and malignant carcinomas. Many long noncoding RNAs (lncRNAs) have been reported to play important roles in the tumorigenesis of CRC by influencing the expression of some mRNAs via competing endogenous RNA (ceRNA) networks and interacting with miRNAs. Pseudogene is one kind of lncRNA and can act as RNA sponges for miRNAs and regulate gene expression via ceRNA networks. However, there are few studies about pseudogenes in CRC. In this study, 31 differentially expressed (DE) pseudogenes, 17 DE miRNAs and 152 DE mRNAs were identified by analyzing the expression profiles of colon adenocarcinoma obtained from The Cancer Genome Atlas. A ceRNA network was constructed based on these RNAs. Kaplan-Meier analysis showed that 7 pseudogenes, 4 miRNAs and 30 mRNAs were significantly associated with overall survival. Then multivariate Cox regression analysis of the ceRNA-related DE pseudogenes was performed and a 5-pseudogene signature with the greatest prognostic value for CRC was identified. Moreover, the results were validated by the Gene Expression Omnibus database, and quantitative real-time PCR in 113 pairs of CRC tissues and colon cancer cell lines. This study provides a pseudogene-associated ceRNA network, 7 prognostic pseudogene biomarkers, and a 5-pseudogene prognostic risk signature that may be useful for predicting the survival of CRC patients.
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Affiliation(s)
- Zhuoqi Li
- grid.412474.00000 0001 0027 0586Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education/Beijing), Division of Etiology, Peking University Cancer Hospital and Institute, Beijing, China
| | - Jing Zhou
- grid.412474.00000 0001 0027 0586Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education/Beijing), Division of Etiology, Peking University Cancer Hospital and Institute, Beijing, China
| | - Liankun Gu
- grid.412474.00000 0001 0027 0586Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education/Beijing), Division of Etiology, Peking University Cancer Hospital and Institute, Beijing, China
| | - Baozhen Zhang
- grid.412474.00000 0001 0027 0586Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education/Beijing), Division of Etiology, Peking University Cancer Hospital and Institute, Beijing, China
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12
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Wu G, Yang Y, Ye R, Yue H, Zhang H, Huang T, Liu M, Zheng Y, Wang Y, Zhou Y, Guo Q. Development and validation of an ECM-related prognostic signature to predict the immune landscape of human hepatocellular carcinoma. BMC Cancer 2022; 22:1036. [PMID: 36195857 PMCID: PMC9531523 DOI: 10.1186/s12885-022-10049-w] [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: 04/01/2022] [Accepted: 08/31/2022] [Indexed: 12/24/2022] Open
Abstract
Background The global burden of hepatocellular carcinoma (HCC) is increasing, negatively impacting social health and economies. The discovery of novel and valuable biomarkers for the early diagnosis and therapeutic guidance of HCC is urgently needed. Methods Extracellular matrix (ECM)-related gene sets, transcriptome data and mutation profiles were downloaded from the Matrisome Project and The Cancer Genome Atlas (TCGA)-LIHC datasets. Coexpression analysis was initially performed with the aim of identifying ECM-related lncRNAs (r > 0.4, p < 0.001). The screened lncRNAs were subjected to univariate analysis to obtain a series of prognosis-related lncRNA sets, which were incorporated into least absolute selection and shrinkage operator (LASSO) regression for signature establishment. Following the grouping of LIHC samples according to risk score, the correlations between the signature and clinicopathological, tumour immune infiltration, and mutational characteristics as well as therapeutic response were also analysed. lncRNA expression levels used for modelling were finally examined at the cellular and tissue levels by real-time PCR. All analyses were based on R software. Results AL031985.3 and MKLN1-AS were ultimately identified as signature-related lncRNAs, and both were significantly upregulated in HCC tissue samples and cell lines. The prognostic value of the signature reflected by the AUC value was superior to that of age, sex, grade and stage. Correlation analysis results demonstrated that high-risk groups exhibited significant enrichment of immune cells (DCs, macrophages and Tregs) and increased expression levels of all immune checkpoint genes. Prominent differences in clinicopathological profiles, immune functions, tumour mutation burden (TMB) and drug sensitivity were noted between the two risk groups. Conclusions Our signature represents a valuable predictive tool in the prognostic management of HCC patients. Further validation of the mechanisms involved is needed. Supplementary Information The online version contains supplementary material available at 10.1186/s12885-022-10049-w.
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Affiliation(s)
- Guozhi Wu
- The First Clinical Medical College, Lanzhou University, Lanzhou, 730000, Gansu, China.,Department of Gastroenterology, The First Hospital of Lanzhou University, No.1 West Donggang Road, Lanzhou, 730000, Gansu, China.,Gansu Key Laboratory of Gastroenterology, Lanzhou University, Lanzhou, 730000, Gansu, China
| | - Yuan Yang
- The First Clinical Medical College, Lanzhou University, Lanzhou, 730000, Gansu, China.,Department of Gastroenterology, The First Hospital of Lanzhou University, No.1 West Donggang Road, Lanzhou, 730000, Gansu, China.,Gansu Key Laboratory of Gastroenterology, Lanzhou University, Lanzhou, 730000, Gansu, China
| | - Rong Ye
- Department of Radiology, the First Hospital of Lanzhou University, Lanzhou, 730000, Gansu, China
| | - Hanxun Yue
- The First Clinical Medical College, Lanzhou University, Lanzhou, 730000, Gansu, China.,Department of Gastroenterology, The First Hospital of Lanzhou University, No.1 West Donggang Road, Lanzhou, 730000, Gansu, China.,Gansu Key Laboratory of Gastroenterology, Lanzhou University, Lanzhou, 730000, Gansu, China
| | - Huiyun Zhang
- The First Clinical Medical College, Lanzhou University, Lanzhou, 730000, Gansu, China.,Department of Gastroenterology, The First Hospital of Lanzhou University, No.1 West Donggang Road, Lanzhou, 730000, Gansu, China.,Gansu Key Laboratory of Gastroenterology, Lanzhou University, Lanzhou, 730000, Gansu, China
| | - Taobi Huang
- The First Clinical Medical College, Lanzhou University, Lanzhou, 730000, Gansu, China.,Department of Gastroenterology, The First Hospital of Lanzhou University, No.1 West Donggang Road, Lanzhou, 730000, Gansu, China.,Gansu Key Laboratory of Gastroenterology, Lanzhou University, Lanzhou, 730000, Gansu, China
| | - Min Liu
- Department of Gastroenterology, The First Hospital of Lanzhou University, No.1 West Donggang Road, Lanzhou, 730000, Gansu, China.,Gansu Key Laboratory of Gastroenterology, Lanzhou University, Lanzhou, 730000, Gansu, China
| | - Ya Zheng
- Department of Gastroenterology, The First Hospital of Lanzhou University, No.1 West Donggang Road, Lanzhou, 730000, Gansu, China.,Gansu Key Laboratory of Gastroenterology, Lanzhou University, Lanzhou, 730000, Gansu, China
| | - Yuping Wang
- Department of Gastroenterology, The First Hospital of Lanzhou University, No.1 West Donggang Road, Lanzhou, 730000, Gansu, China.,Gansu Key Laboratory of Gastroenterology, Lanzhou University, Lanzhou, 730000, Gansu, China
| | - Yongning Zhou
- Department of Gastroenterology, The First Hospital of Lanzhou University, No.1 West Donggang Road, Lanzhou, 730000, Gansu, China. .,Gansu Key Laboratory of Gastroenterology, Lanzhou University, Lanzhou, 730000, Gansu, China.
| | - Qinghong Guo
- Department of Gastroenterology, The First Hospital of Lanzhou University, No.1 West Donggang Road, Lanzhou, 730000, Gansu, China. .,Gansu Key Laboratory of Gastroenterology, Lanzhou University, Lanzhou, 730000, Gansu, China.
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13
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Di Z, Zhou S, Xu G, Ren L, Li C, Ding Z, Huang K, Liang L, Yuan Y. Single-cell and WGCNA uncover a prognostic model and potential oncogenes in colorectal cancer. Biol Proced Online 2022; 24:13. [PMID: 36117173 PMCID: PMC9484253 DOI: 10.1186/s12575-022-00175-x] [Citation(s) in RCA: 23] [Impact Index Per Article: 7.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/22/2022] [Accepted: 08/30/2022] [Indexed: 11/19/2022] Open
Abstract
BACKGROUND Colorectal cancer (CRC) is one of the leading causes of cancer-related death worldwide. Single-cell transcriptome sequencing (scRNA-seq) can provide accurate gene expression data for individual cells. In this study, a new prognostic model was constructed by scRNA-seq and bulk transcriptome sequencing (bulk RNA-seq) data of CRC samples to develop a new understanding of CRC. METHODS CRC scRNA-seq data were downloaded from the GSE161277 database, and CRC bulk RNA-seq data were downloaded from the TCGA and GSE17537 databases. The cells were clustered by the FindNeighbors and FindClusters functions in scRNA-seq data. CIBERSORTx was applied to detect the abundance of cell clusters in the bulk RNA-seq expression matrix. WGCNA was performed with the expression profiles to construct the gene coexpression networks of TCGA-CRC. Next, we used a tenfold cross test to construct the model and a nomogram to assess the independence of the model for clinical application. Finally, we examined the expression of the unreported model genes by qPCR and immunohistochemistry. A clone formation assay and orthotopic colorectal tumour model were applied to detect the regulatory roles of unreported model genes. RESULTS A total of 43,851 cells were included after quality control, and 20 cell clusters were classified by the FindCluster () function. We found that the abundances of C1, C2, C4, C5, C15, C16 and C19 were high and the abundances of C7, C10, C11, C13, C14 and C17 were low in CRC tumour tissues. Meanwhile, the results of survival analysis showed that high abundances of C4, C11 and C13 and low abundances of C5 and C14 were associated with better survival. The WGCNA results showed that the red module was most related to the tumour and the C14 cluster, which contains 615 genes. Lasso Cox regression analysis revealed 8 genes (PBXIP1, MPMZ, SCARA3, INA, ILK, MPP2, L1CAM and FLNA), which were chosen to construct a risk model. In the model, the risk score features had the greatest impact on survival prediction, indicating that the 8-gene risk model can better predict prognosis. qPCR and immunohistochemistry analysis showed that the expression levels of MPZ, SCARA3, MPP2 and PBXIP1 were high in CRC tissues. The functional experiment results indicated that MPZ, SCARA3, MPP2 and PBXIP1 could promote the colony formation ability of CRC cells in vitro and tumorigenicity in vivo. CONCLUSIONS We constructed a risk model to predict the prognosis of CRC patients based on scRNA-seq and bulk RNA-seq data, which could be used for clinical application. We also identified 4 previously unreported model genes (MPZ, SCARA3, MPP2 and PBXIP1) as novel oncogenes in CRC. These results suggest that this model could potentially be used to evaluate the prognostic risk and provide potential therapeutic targets for CRC patients.
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Affiliation(s)
- Ziyang Di
- Zhongnan Hospital of Wuhan University, Wuhan, China
| | - Sicheng Zhou
- National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Gaoran Xu
- Zhongnan Hospital of Wuhan University, Wuhan, China
| | - Lian Ren
- Zhongnan Hospital of Wuhan University, Wuhan, China
| | - Chengxin Li
- Zhongnan Hospital of Wuhan University, Wuhan, China
| | - Zheyu Ding
- Zhongnan Hospital of Wuhan University, Wuhan, China
| | - Kaixin Huang
- Zhongnan Hospital of Wuhan University, Wuhan, China
| | - Leilei Liang
- National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Yihang Yuan
- Department of General Surgery, Tongren Hospital, Shanghai Jiao Tong University School of Medicine, 1111 XianXia Road, Shanghai, 200336 China
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14
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Li B, Ge N, Pan Z, Hou C, Xie K, Wang D, Liu J, Wan J, Deng F, Li M, Luo S. KCNJ14 knockdown significantly inhibited the proliferation and migration of colorectal cells. BMC Med Genomics 2022; 15:194. [PMID: 36100894 PMCID: PMC9472386 DOI: 10.1186/s12920-022-01351-4] [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] [Received: 09/30/2021] [Accepted: 07/25/2022] [Indexed: 12/24/2022] Open
Abstract
Abstract
Background
This study attempted to verify the potential of KCNJ14 as a biomarker in colorectal cancer (CRC).
Methods
Data on transcriptomics and DNA methylation and the clinical information of CRC patients were downloaded from The Cancer Genome Atlas and Gene Expression Omnibus databases. Biological information analysis methods were conducted to determine the role of KCNJ14 in the prognosis, diagnosis, immune cell infiltration, and regulation mechanism of CRC patients. The effect of KCNJ14 on the proliferation and migration of HCT116 and SW480 CRC cell lines was verified by in vitro experiments (MTT, colony-forming, wound healing, and transwell assays). Western blotting was performed to detect the effect of KCNJ14 on the levels of mTOR signalling pathway-related proteins.
Results
KCNJ14 expression was remarkably increased in CRC tissues and cell lines, which reduced the overall survival time of patients. KCNJ14 mRNA was negatively regulated by its methylation site cg17660703, which can also endanger the prognosis of patients with CRC. Functional enrichment analysis suggested that KCNJ14 is involved in the mTOR, NOD-like receptor, and VEGF signalling pathways. KCNJ14 expression was positively correlated with the number of CD4 + T cells and negatively correlated with that of CD8 + T cells in the immune microenvironment. KCNJ14 knockdown significantly reduced not only the proliferation and migration of CRC cell lines but also the levels of mTOR signalling pathway-related proteins.
Conclusions
This study not only increases the molecular understanding of KCNJ14 but also provides a potentially valuable biological target for the treatment of colorectal cancer.
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15
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The Prediction of Survival Outcome and Prognosis Factor in Association with Comorbidity Status in Patients with Colorectal Cancer: A Research-Based Study. Healthcare (Basel) 2022; 10:healthcare10091693. [PMID: 36141305 PMCID: PMC9498868 DOI: 10.3390/healthcare10091693] [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: 08/04/2022] [Revised: 08/29/2022] [Accepted: 08/29/2022] [Indexed: 11/16/2022] Open
Abstract
Colorectal carcinoma (CRC) is rising exponentially in Asia, representing 11% of cancer worldwide. This study analysed the influence of CRC on patients’ life expectancy (survival and prognosis factors) via clinicopathology data and comorbidity status of CRC patients. Methodology: A retrospective study performed in HUSM using clinical data from the Surgery unit from 2015 to 2020. The demographic and pertinent clinical data were retrieved for preliminary analyses (data cleansing and exploration). Demographics and pathological characteristics were illustrated using descriptive analysis; 5-year survival rates were calculated using Kaplan−Meier methods; potential prognostic variables were analysed using simple and multivariate logistic regression analysis conducted via the Cox proportional hazards model, while the Charlson Comorbidity Scale was used to categorize patients’ disease status. Results: Of a total of 114 CRC patients, two-thirds (89.5%) were from Malay tribes, while Indian and Chinese had 5.3% each. The 50−69.9 years were the most affected group (45.6%). Overall, 40.4% were smokers (majorly male (95.7%)), 14.0% ex-smokers, and 45.6% non-smokers (p-value = 0.001). The Kaplan−Meier overall 5-year median survival time was 62.5%. From the outcomes, patients who were male and >70 years had metastasis present, who presented with per rectal bleeding and were classified as Duke C; and who has tumour in the rectum had the lowest survival rate. Regarding the prognosis factors investigated, “Gender” (adjusted hazard ratio (HR): 2.62; 95% CI: 1.56−7.81, p-value = 0.040), “Presence of metastases” (HR: 3.76; 95% CI: 1.89−7.32, p-value = 0.010), “Metastasis site: Liver” (HR: 5.04; 95% CI: 1.71−19.05, p-value = 0.039), “Lymphovascular permeation” (HR: 2.94; 95% CI: 1.99−5.92, p-value = 0.021), and “CEA-level” (HR: 2.43; 95% CI: 1.49−5.80, p-value = 0.001) remained significant in the final model for multiple Cox proportional hazard regression analyses. There was a significant mean association between tumour grades and the patient’s comorbidity status. Conclusions: Histopathological factors (gender, metastases presence, site of metastases, CEA level, and lymphovascular permeation) showed the best prognosis-predicting factors in CRC.
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16
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Cao Y, Deng S, Yan L, Gu J, Mao F, Xue Y, Qin L, Jiang Z, Cai W, Zheng C, Nie X, Liu H, Sun Z, Shang F, Tao K, Wang J, Wu K, Zhu B, Cai K. The Prognostic Significance of RIMKLB and Related Immune Infiltrates in Colorectal Cancers. Front Genet 2022; 13:818994. [PMID: 35444692 PMCID: PMC9015428 DOI: 10.3389/fgene.2022.818994] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/20/2021] [Accepted: 03/14/2022] [Indexed: 12/24/2022] Open
Abstract
RimK-like family member B (RIMKLB) is an enzyme that post-translationally modulates ribosomal protein S6, which can affect the development of immune cells. Some studies have suggested its role in tumor progression. However, the relationships among RIMKLB expression, survival outcomes, and tumor-infiltrating immune cells (TIICs) in colorectal cancer (CRC) are still unknown. Therefore, we analyzed RIMKLB expression levels in CRC and normal tissues and investigated the correlations between RIMKLB and TIICs as well as the impact of RIMKLB expression on clinical prognosis in CRC using multiple databases, including the Tumor Immune Estimation Resource (TIMER), Gene Expression Profiling Interactive Analysis (GEPIA), PrognoScan, and UALCAN databases. Enrichment analysis was conducted with the cluster Profiler package in R software to explore the RIMKLB-related biological processes involved in CRC. The RIMKLB expression was significantly decreased in CRC compared to normal tissues, and correlated with histology, stage, lymphatic metastasis, and tumor status (p < 0.05). Patients with CRC with high expression of RIMKLB showed poorer overall survival (OS) (HR = 2.5,p = 0.00,042), and inferior disease-free survival (DFS) (HR = 1.9,p = 0.19) than those with low expression of RIMKLB. TIMER analysis indicated that RIMKLB transcription was closely related with several TIICs, including CD4+ and CD8+ T cells, B cells, tumor-associated macrophages (TAMs), monocytes, neutrophils, natural killer cells, dendritic cells, and subsets of T cells. Moreover, the expression of RIMKLB showed significant positive correlations with infiltrating levels of PD1 (r = 0.223, p = 1.31e-06; r = 0.249, p = 1.25e-03), PDL1 (r = 0.223, p = 6.03e-07; r = 0.41, p = 5.45e-08), and CTLA4 (r = 0.325, p = 9.68e-13; r = 0.41, p = 5.45e-08) in colon and rectum cancer, respectively. Enrichment analysis showed that the RIMKLB expression was positively related to extracellular matrix and immune inflammation-related pathways. In conclusion, RIMKLB expression is associated with survival outcomes and TIICs levels in patients with CRC, and therefore, might be a potential novel prognostic biomarker that reflects the immune infiltration status.
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Affiliation(s)
- Yinghao Cao
- Department of Gastrointestinal Surgery, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Shenghe Deng
- Department of Gastrointestinal Surgery, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Lizhao Yan
- Department of Hand Surgery, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Junnan Gu
- Department of Gastrointestinal Surgery, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Fuwei Mao
- Department of Gastrointestinal Surgery, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Yifan Xue
- Department of Gastrointestinal Surgery, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Le Qin
- Department of Gastrointestinal Surgery, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Zhengxing Jiang
- Department of Gastrointestinal Surgery, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Wentai Cai
- College of Life Science and Technology, Huazhong University of Science and Technology, Wuhan, China
| | - Changmin Zheng
- School of Optical and Electronic Information, Huazhong University of Science and Technology, Wuhan, China
| | - Xiu Nie
- Department of Pathology, Union Hospital, Tongji Medical, Huazhong University of Science and Technology, Wuhan, China
| | - Hongli Liu
- Cancer Center, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Zhuolun Sun
- Department of Urology, Third Affiliated Hospital of Sun Yat-sen University, Guangzhou0, China
| | - Fumei Shang
- Department of Medical Oncology, Nanyang Central Hospital, Nanyang, China
| | - Kaixiong Tao
- Department of Gastrointestinal Surgery, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Jiliang Wang
- Department of Gastrointestinal Surgery, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Ke Wu
- Department of Gastrointestinal Surgery, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Bin Zhu
- Department of Infectious Diseases, Union Hospital, Tongji Medcial College, Huazhong University of Science and Technology, Wuhan, China
| | - Kailin Cai
- Department of Gastrointestinal Surgery, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
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17
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Qi C, Lei L, Hu J, Wang G, Liu J, Ou S. Identification of a five-gene signature deriving from the vacuolar ATPase (V-ATPase) sub-classifies gliomas and decides prognoses and immune microenvironment alterations. Cell Cycle 2022; 21:1294-1315. [PMID: 35266851 PMCID: PMC9132400 DOI: 10.1080/15384101.2022.2049157] [Citation(s) in RCA: 13] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/07/2023] Open
Abstract
Aberrant expression of coding genes of the V-ATPase subunits has been reported in glioma patients that can activate oncogenic pathways and result in worse prognosis. However, the predictive effect of a single gene is not specific or sensitive enough. In this study, by using a series of bioinformatics analyses, we identified five coding genes (ATP6V1C2, ATP6V1G2, TCIRG1, ATP6AP1 and ATP6AP2) of the V-ATPase that were related to glioma patient prognosis. Based on the expression of these genes, glioma patients were sub-classified into different prognosis clusters, of which C1 cluster performed better prognosis; however, C2 cluster showed more malignant phenotypes with oncogenic and immune-related pathway activation. The single-cell RNA-seq data revealed that ATP6AP1, ATP6AP2, ATP6V1G2 and TCIRG1 might be cell-type potential markers. Copy number variation and DNA promoter methylation potentially regulate these five gene expressions. A risk score model consisted of these five genes effectively predicted glioma prognosis and was fully validated by six independent datasets. The risk scores also showed a positive correlation with immune checkpoint expression. Importantly, glioma patients with high-risk scores presented resistance to traditional treatment. We also revealed that more inhibitory immune cells infiltration and higher rates of “non-response” to immune checkpoint blockade (ICB) treatment in the high-risk score group. In conclusion, our study identified a five-gene signature from the V-ATPase that could sub-classify gliomas into different phenotypes and their abnormal expression was regulated by distinct mechanisms and accompanied with immune microenvironment alterations potentially act as a biomarker for ICB treatment.
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Affiliation(s)
- Chunxiao Qi
- Department of Neurosurgery, The First Hospital of China Medical University, Shenyang, Liaoning, China.,Department of Neurosurgery, The Second Hospital of Dalian Medical University, Dalian, Liaoning, China
| | - Lei Lei
- Department of Rheumatology and Immunology, Dalian Municipal Central Hospital Affiliated of Dalian Medical University, Dalian, Liaoning, China
| | - Jinqu Hu
- Department of Neurosurgery, The First Hospital of China Medical University, Shenyang, Liaoning, China
| | - Gang Wang
- Department of Neurosurgery, The First Hospital of China Medical University, Shenyang, Liaoning, China
| | - Jiyuan Liu
- Department of Neurosurgery, The First Hospital of China Medical University, Shenyang, Liaoning, China
| | - Shaowu Ou
- Department of Neurosurgery, The First Hospital of China Medical University, Shenyang, Liaoning, China
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18
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Granata V, Faggioni L, Grassi R, Fusco R, Reginelli A, Rega D, Maggialetti N, Buccicardi D, Frittoli B, Rengo M, Bortolotto C, Prost R, Lacasella GV, Montella M, Ciaghi E, Bellifemine F, De Muzio F, Grazzini G, De Filippo M, Cappabianca S, Laghi A, Grassi R, Brunese L, Neri E, Miele V, Coppola F. Structured reporting of computed tomography in the staging of colon cancer: a Delphi consensus proposal. LA RADIOLOGIA MEDICA 2022; 127:21-29. [PMID: 34741722 PMCID: PMC8795004 DOI: 10.1007/s11547-021-01418-9] [Citation(s) in RCA: 37] [Impact Index Per Article: 12.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Subscribe] [Scholar Register] [Received: 07/14/2021] [Accepted: 09/28/2021] [Indexed: 12/11/2022]
Abstract
BACKGROUND Structured reporting (SR) in radiology is becoming increasingly necessary and has been recognized recently by major scientific societies. This study aims to build structured CT-based reports in colon cancer during the staging phase in order to improve communication between the radiologist, members of multidisciplinary teams and patients. MATERIALS AND METHODS A panel of expert radiologists, members of the Italian Society of Medical and Interventional Radiology, was established. A modified Delphi process was used to develop the SR and to assess a level of agreement for all report sections. Cronbach's alpha (Cα) correlation coefficient was used to assess internal consistency for each section and to measure quality analysis according to the average inter-item correlation. RESULTS The final SR version was built by including n = 18 items in the "Patient Clinical Data" section, n = 7 items in the "Clinical Evaluation" section, n = 9 items in the "Imaging Protocol" section and n = 29 items in the "Report" section. Overall, 63 items were included in the final version of the SR. Both in the first and second round, all sections received a higher than good rating: a mean value of 4.6 and range 3.6-4.9 in the first round; a mean value of 5.0 and range 4.9-5 in the second round. In the first round, Cronbach's alpha (Cα) correlation coefficient was a questionable 0.61. In the first round, the overall mean score of the experts and the sum of scores for the structured report were 4.6 (range 1-5) and 1111 (mean value 74.07, STD 4.85), respectively. In the second round, Cronbach's alpha (Cα) correlation coefficient was an acceptable 0.70. In the second round, the overall mean score of the experts and the sum of score for structured report were 4.9 (range 4-5) and 1108 (mean value 79.14, STD 1.83), respectively. The overall mean score obtained by the experts in the second round was higher than the overall mean score of the first round, with a lower standard deviation value to underline greater agreement among the experts for the structured report reached in this round. CONCLUSIONS A wide implementation of SR is of critical importance in order to offer referring physicians and patients optimum quality of service and to provide researchers with the best quality data in the context of big data exploitation of available clinical data. Implementation is a complex procedure, requiring mature technology to successfully address the multiple challenges of user-friendliness, organization and interoperability.
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Affiliation(s)
- Vincenza Granata
- Division of Radiology, “Istituto Nazionale Tumori IRCCS Fondazione Pascale – IRCCS di Napoli”, Naples, Italy
| | - Lorenzo Faggioni
- Department of Translational Research, University of Pisa, Pisa, Italy
| | - Roberta Grassi
- Italian Society of Medical and Interventional Radiology (SIRM), SIRM Foundation, via della Signora 2, 20122 Milan, Italy
- Division of Radiology, “Università Degli Studi Della Campania Luigi Vanvitelli”, Naples, Italy
| | | | - Alfonso Reginelli
- Division of Radiology, “Università Degli Studi Della Campania Luigi Vanvitelli”, Naples, Italy
| | - Daniela Rega
- Division of Colorectal Surgery, Istituto Nazionale Tumori IRCCS Fondazione Pascale-IRCCS Di Napoli, 80131 Naples, Italy
| | - Nicola Maggialetti
- Section of Radiodiagnostic, DSMBNOS, “Aldo Moro” University, Bari, Italy
| | | | - Barbara Frittoli
- Department of Radiology, Spedali Civili Hospital of Brescia, University of Brescia, Brescia, Italy
| | - Marco Rengo
- Department of Radiological Sciences, Oncology and Pathology, Sapienza University of Rome - I.C.O.T. Hospital, Via Franco Faggiana, 1668, 04100 Latina, Italy
| | - Chandra Bortolotto
- Department of Radiology, I.R.C.C.S. Policlinico San Matteo Foundation, Pavia, Italy
| | - Roberto Prost
- Radiology Unit, Azienda Ospedaliera Brotzu, Cagliari, Italy
| | - Giorgia Viola Lacasella
- Division of Radiology, “Università Degli Studi Della Campania Luigi Vanvitelli”, Naples, Italy
| | - Marco Montella
- Division of Radiology, “Università Degli Studi Della Campania Luigi Vanvitelli”, Naples, Italy
| | | | | | - Federica De Muzio
- Department of Medicine and Health Sciences “V. Tiberio”, University of Molise, Via Francesco De Sanctis 1, 86100 Campobasso, Italy
| | - Giulia Grazzini
- Division of Radiology, “Azienda Ospedaliera Universitaria Careggi”, Florence, Italy
| | - Massimo De Filippo
- Department of Medicine and Surgery, Unit of Radiologic Science, University of Parma, Maggiore Hospital, Parma, Italy
| | - Salvatore Cappabianca
- Division of Radiology, “Università Degli Studi Della Campania Luigi Vanvitelli”, Naples, Italy
| | - Andrea Laghi
- Department of Surgical and Medical Sciences and Translational Medicine, Sapienza University of Rome-Sant’Andrea University Hospital, Via di Grottarossa, 1035-1039, 00189 Rome, Italy
| | - Roberto Grassi
- Italian Society of Medical and Interventional Radiology (SIRM), SIRM Foundation, via della Signora 2, 20122 Milan, Italy
- Division of Radiology, “Università Degli Studi Della Campania Luigi Vanvitelli”, Naples, Italy
| | - Luca Brunese
- Department of Medicine and Health Sciences “V. Tiberio”, University of Molise, Via Francesco De Sanctis 1, 86100 Campobasso, Italy
| | - Emanuele Neri
- Department of Translational Research, University of Pisa, Pisa, Italy
- Italian Society of Medical and Interventional Radiology (SIRM), SIRM Foundation, via della Signora 2, 20122 Milan, Italy
| | - Vittorio Miele
- Italian Society of Medical and Interventional Radiology (SIRM), SIRM Foundation, via della Signora 2, 20122 Milan, Italy
- Division of Radiology, “Azienda Ospedaliera Universitaria Careggi”, Florence, Italy
| | - Francesca Coppola
- Department of Radiology, IRCCS Azienda Ospedaliero-Universitaria Di Bologna, Bologna, Italy
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Tao S, Ye X, Pan L, Fu M, Huang P, Peng Z, Yang S. Construction and Clinical Translation of Causal Pan-Cancer Gene Score Across Cancer Types. Front Genet 2021; 12:784775. [PMID: 35003220 PMCID: PMC8733729 DOI: 10.3389/fgene.2021.784775] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/28/2021] [Accepted: 11/24/2021] [Indexed: 12/17/2022] Open
Abstract
Pan-cancer strategy, an integrative analysis of different cancer types, can be used to explain oncogenesis and identify biomarkers using a larger statistical power and robustness. Fine-mapping defines the casual loci, whereas genome-wide association studies (GWASs) typically identify thousands of cancer-related loci and not necessarily have a fine-mapping component. In this study, we develop a novel strategy to identify the causal loci using a pan-cancer and fine-mapping assumption, constructing the CAusal Pan-cancER gene (CAPER) score and validating its performance using internal and external validation on 1,287 individuals and 985 cell lines. Summary statistics of 15 cancer types were used to define 54 causal loci in 15 potential genes. Using the Cancer Genome Atlas (TCGA) training set, we constructed the CAPER score and divided cancer patients into two groups. Using the three validation sets, we found that 19 cancer-related variables were statistically significant between the two CAPER score groups and that 81 drugs had significantly different drug sensitivity between the two CAPER score groups. We hope that our strategies for selecting causal genes and for constructing CAPER score would provide valuable clues for guiding the management of different types of cancers.
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Affiliation(s)
- Shiyue Tao
- Department of Biostatistics, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, China
| | - Xiangyu Ye
- Department of Epidemiology, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, China
| | - Lulu Pan
- Department of Biostatistics, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, China
| | - Minghan Fu
- Department of Biostatistics, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, China
| | - Peng Huang
- Department of Epidemiology, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, China
| | - Zhihang Peng
- Department of Biostatistics, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, China
| | - Sheng Yang
- Department of Biostatistics, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, China
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20
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Tao Z, Zhang E, Li L, Zheng J, Zhao Y, Chen X. A united risk model of 11 immune‑related gene pairs and clinical stage for prediction of overall survival in clear cell renal cell carcinoma patients. Bioengineered 2021; 12:4259-4277. [PMID: 34304692 PMCID: PMC8806637 DOI: 10.1080/21655979.2021.1955558] [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] [Indexed: 12/24/2022] Open
Abstract
Clear cell renal cell carcinoma (ccRCC) is the most common subtype of renal cancer. Currently, we lack effective risk models for the prognosis of ccRCC patients. Given the significant role of cancer immunity in ccRCC, we aimed to establish a novel united risk model including clinical stage and immune-related gene pairs (IRGPs) to assess the prognosis. The gene expression profile and clinical data of ccRCC patients from The Cancer Genome Atlas and Arrayexpress were divided into training cohort (n = 381), validation cohort 1 (n = 156), and validation cohort 2 (n = 101). Through univariate Cox regression analysis and Least Absolute Shrinkage and Selection Operator analysis, 11 IRGPs were obtained. After further analysis, it was found that clinical stage could be an independent prognostic factor; hence, we used it to construct a united prognostic model with 11 IRGPs. Based on this model, patients were divided into high-risk and low-risk groups. In Kaplan–Meier analysis, a significant difference was observed in overall survival (OS) among all three cohorts (p < 0.001). The calibration curve revealed that the signature model is in high accordance with the observed values of each data cohort. The 1-year, 3-year, and 5-year receiver operating characteristic curves of each data cohort showed better performance than only IRGP signatures. The results of immune infiltration analysis revealed significantly (p < 0.05) higher abundance of macrophages M0, T follicular helper cells, and other tumor infiltrating cells. In summary, we successfully established a united prognostic risk model, which can effectively assess the OS of ccRCC patients.
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Affiliation(s)
- Zijia Tao
- Department of Urology, Shengjing Hospital of China Medical University, Shenyang, Liaoning, People's Republic of China
| | - Enchong Zhang
- Department of Urology, Shengjing Hospital of China Medical University, Shenyang, Liaoning, People's Republic of China
| | - Lei Li
- Department of Urology, Shengjing Hospital of China Medical University, Shenyang, Liaoning, People's Republic of China
| | - Jianyi Zheng
- Department of Urology, Shengjing Hospital of China Medical University, Shenyang, Liaoning, People's Republic of China
| | - Yiqiao Zhao
- Department of Urology, Shengjing Hospital of China Medical University, Shenyang, Liaoning, People's Republic of China
| | - Xiaonan Chen
- Department of Urology, Shengjing Hospital of China Medical University, Shenyang, Liaoning, People's Republic of China
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21
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Lee J, Hwang JH, Chun H, Woo W, Oh S, Choi J, Kim LK. PLEKHA8P1 Promotes Tumor Progression and Indicates Poor Prognosis of Liver Cancer. Int J Mol Sci 2021; 22:7614. [PMID: 34299245 PMCID: PMC8304620 DOI: 10.3390/ijms22147614] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/22/2021] [Revised: 07/11/2021] [Accepted: 07/14/2021] [Indexed: 02/08/2023] Open
Abstract
Hepatocellular carcinoma (HCC) records the second-lowest 5-year survival rate despite the avalanche of research into diagnosis and therapy. One of the major obstacles in treatment is chemoresistance to drugs such as 5-fluorouracil (5-FU), making identification and elucidation of chemoresistance regulators highly valuable. As the regulatory landscape grows to encompass non-coding genes such as long non-coding RNAs (lncRNAs), a relatively new class of lncRNA has emerged in the form of pseudogene-derived lncRNAs. Through bioinformatics analyses of the TCGA LIHC dataset, we have systematically identified pseudogenes of prognostic value. Initial experimental validation of selected pseudogene-derived lncRNA (PLEKHA8P1) and its parental gene (PLEKHA8), a well-studied transport protein in Golgi complex recently implicated as an oncogene in both colorectal and liver cancer, indicates that the pseudogene/parental gene pair promotes tumor progression and that their dysregulated expression levels affect 5-FU-induced chemoresistance in human HCC cell line FT3-7. Our study has thus confirmed cancer-related functions of PLEKHA8, and laid the groundwork for identification and validation of oncogenic pseudogene-derived lncRNA that shows potential as a novel therapeutic target in circumventing chemoresistance induced by 5-FU.
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MESH Headings
- Adaptor Proteins, Signal Transducing/genetics
- Adaptor Proteins, Signal Transducing/metabolism
- Biomarkers, Tumor/metabolism
- Carcinoma, Hepatocellular/genetics
- Carcinoma, Hepatocellular/metabolism
- Cell Line, Tumor
- Computational Biology/methods
- Databases, Genetic
- Disease Progression
- Drug Resistance, Neoplasm/genetics
- Fluorouracil/pharmacology
- Gene Expression Profiling/methods
- Gene Expression Regulation, Neoplastic/genetics
- Humans
- Kaplan-Meier Estimate
- Liver Neoplasms/genetics
- Liver Neoplasms/metabolism
- MicroRNAs/genetics
- Prognosis
- Pseudogenes
- RNA, Long Noncoding/genetics
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Affiliation(s)
- Jiyeon Lee
- Severance Biomedical Science Institute, Graduate School of Medical Science, Brain Korea 21 Project, Gangnam Severance Hospital, Yonsei University College of Medicine, Seoul 06273, Korea; (J.L.); (W.W.)
| | - Ji-Hyun Hwang
- Interdisciplinary Program of Integrated OMICS for Biomedical Science, The Graduate School, Yonsei University, Seoul 03722, Korea;
| | - Harim Chun
- Department of Biomedical Sciences, Korea University College of Medicine, Seoul 02841, Korea;
| | - Wonjin Woo
- Severance Biomedical Science Institute, Graduate School of Medical Science, Brain Korea 21 Project, Gangnam Severance Hospital, Yonsei University College of Medicine, Seoul 06273, Korea; (J.L.); (W.W.)
| | - Sekyung Oh
- Department of Medical Science, Catholic Kwandong University College of Medicine, Incheon 22711, Korea;
| | - Jungmin Choi
- Department of Biomedical Sciences, Korea University College of Medicine, Seoul 02841, Korea;
| | - Lark Kyun Kim
- Severance Biomedical Science Institute, Graduate School of Medical Science, Brain Korea 21 Project, Gangnam Severance Hospital, Yonsei University College of Medicine, Seoul 06273, Korea; (J.L.); (W.W.)
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