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4. Insights into the historical trajectory and research trends of immune checkpoint blockade in colorectal cancer: visualization and bibliometric analysis.

Author

Chang, Yonglong, Zhou, Xuhui, Nie, Kechao, Liu, Jinhui, and Zhang, Sifang

Abstract

Background: Colorectal cancer (CRC) is a malignant tumor that poses a significant threat to human health due to rising incidence and mortality rates. In recent years, immune checkpoint blockade (ICB) therapy, represented by Programmed death receptor 1 (PD-1), T-lymphocyte-associated protein 4 (CTLA-4), and others, has been widely applied in CRC and has achieved encouraging results in some patients and has become a hot topic in both clinical and basic research. Objective: This study undertakes a comprehensive bibliometric analysis of ICB research in CRC, aiming to evaluate the current status, identify future trends, and provide scientific insights for researchers and decision-makers. Methods: Utilizing the Web of Science Core Collection (WoSCC), articles focusing on ICB in CRC from 2000 to 2022 were retrieved. Knowledge mapping and bibliometric analysis were conducted using tools such as CiteSpace, VOSviewer, SCImago Graphicay, and the R package bibliometrix. Results: 6,718 publications were analyzed from 24,846 institutions across 639 regions. Temporally, ICB research in CRC is rapidly advancing, led by the USA and China with extensive global collaborations. Sun Yat-sen University from China stands out as the institution with the highest number of publications. Professor Thierry Andre from Sorbonne University in France is identified as a prolific author in this field, engaging in extensive collaboration for clinical trials on a global scale. Publications related to this research topic were published in 1,142 academic journals, demonstrating a positive co-citation relationship. Key clustering and burst terms analysis indicate that current research on ICB in CRC has shifted from basic experiments to clinical trials and from universal healthcare to precision medicine. Conclusion: ICB therapies have shown substantial progress in CRC, highlighting their therapeutic potential. Research trends emphasize deeper drug mechanisms, treatment efficacy prediction, managing immune-related adverse events, and exploring novel drug delivery methods. Collaboration across borders remains crucial for further advancements. [ABSTRACT FROM AUTHOR]

Published
2024
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15. CXCR4 is a Novel Biomarker Correlated With Malignant Transformation and Immune Infiltrates in Gastric Precancerous Lesions

Author

Jiang, Xiaotao, primary, Zheng, Junhui, additional, Liu, Lanxing, additional, Jiang, Kailin, additional, Wen, Yi, additional, Yan, Yanhua, additional, Liu, Yufeng, additional, Zhong, Limei, additional, Huang, Yuancheng, additional, Yao, Zhengyang, additional, Nie, Kechao, additional, Zheng, Zhihua, additional, Pan, Jinglin, additional, Liu, Peng, additional, Zhuang, Kunhai, additional, Liu, Fengbin, additional, Xu, Shijie, additional, and Li, Peiwu, additional

Published
2021
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16. Ferroptosis Patterns Correlate with Immune Microenvironment Characterization in Gastric Cancer

Author

Jiang, Xiaotao, primary, Liu, Fan, additional, Liu, Peng, additional, Yan, Yanhua, additional, Lan, Shaoyang, additional, Zhuang, Kunhai, additional, Liu, Yufeng, additional, Jiang, Kailin, additional, Huang, Yuancheng, additional, Nie, Kechao, additional, Zheng, Zhihua, additional, Pan, Jinglin, additional, Zheng, Junhui, additional, Liu, Fengbin, additional, Xu, Shijie, additional, Li, Peiwu, additional, and Wen, Yi, additional

Published
2021
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19. Additional file 1 of TBX5-AS1, an enhancer RNA, is a potential novel prognostic biomarker for lung adenocarcinoma

Author

Cheng, Lin, Han, Tong, Chen, Bolin, Nie, Kechao, and Peng, Weijun

Abstract

Additional file 1: Table S1. List of 174 survival-related eRNAs in lung adenocarcinoma. Table S2. List of the 76 eRNAs with a significant correlation with their target gene in lung adenocarcinoma. Table S3. List of the 26 types of tumours associated with TBX5-AS1 and TBX5.

Published
2021
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20. Ferroptosis Patterns Correlate with Immune Microenvironment Characterization in Gastric Cancer

Author

Jiang,Xiaotao, Liu,Fan, Liu,Peng, Yan,Yanhua, Lan,Shaoyang, Zhuang,Kunhai, Liu,Yufeng, Jiang,Kailin, Huang,Yuancheng, Nie,Kechao, Zheng,Zhihua, Pan,Jinglin, Zheng,Junhui, Liu,Fengbin, Xu,Shijie, Li,Peiwu, Wen,Yi, Jiang,Xiaotao, Liu,Fan, Liu,Peng, Yan,Yanhua, Lan,Shaoyang, Zhuang,Kunhai, Liu,Yufeng, Jiang,Kailin, Huang,Yuancheng, Nie,Kechao, Zheng,Zhihua, Pan,Jinglin, Zheng,Junhui, Liu,Fengbin, Xu,Shijie, Li,Peiwu, and Wen,Yi

Abstract

Xiaotao Jiang,1,2 Fan Liu,2,3 Peng Liu,1,2 Yanhua Yan,1,2 Shaoyang Lan,1 Kunhai Zhuang,1,4 Yufeng Liu,5 Kailin Jiang,1,2 Yuancheng Huang,1,2 Kechao Nie,1,2 Zhihua Zheng,1,2 Jinglin Pan,6 Junhui Zheng,1,2 Fengbin Liu,1,4 Shijie Xu,5 Peiwu Li,1 Yi Wen1 1Department of Gastroenterology, The First Affiliated Hospital of Guangzhou University of Chinese Medicine, Guangzhou, Guangdong, People’s Republic of China; 2First Clinical Medical College, Guangzhou University of Chinese Medicine, Guangzhou, Guangdong, People’s Republic of China; 3Zhaoqing Hospital of Chinese Medicine Affiliated to Southern Medical University, Zhaoqing, Guangdong, People’s Republic of China; 4Baiyun Hospital of the First Affiliated Hospital of Guangzhou University of Chinese Medicine, Guangzhou, Guangdong, People’s Republic of China; 5Guangzhou University of Chinese Medicine, Guangzhou, Guangdong, People’s Republic of China; 6Department of Gastroenterology, Hainan Provincial Hospital of Traditional Chinese Medicine, Haikou, Hainan, People’s Republic of ChinaCorrespondence: Peiwu Li; Yi Wen Email doctorlipw2@163.com; 421491922@qq.comObjective: We aimed to build a ferroptosis-based classifier to characterize the molecular features of gastric cancers (GC) and investigate the relationship between different ferroptosis patterns and GC tumor microenvironment (TME).Methods: Based on the genomic and clinical information from TCGA portal and GEO database, non-negative matrix factorization (NMF) was used to identify ferroptosis subtypes in GC patients. In order to estimate the ferroptosis levels, we established ferroptosis subtype score (FSS) to quantify ferroptosis patterns and ferroptosis potential index (FPI) by principal component analysis (PCA). The correlations of different ferroptosis patterns with TME cell-infiltrating characteristics (including immune cell infiltration, immune checkpoints expression levels, tumor mutational burden (TMB) and immunotherapy response) were systematically analyz

Published
2021

21. Corrigendum: Current Evidence and Future Perspective of Accuracy of Artificial Intelligence Application for Early Gastric Cancer Diagnosis With Endoscopy: A Systematic and Meta-Analysis

Author

Jiang, Kailin, primary, Jiang, Xiaotao, additional, Pan, Jinglin, additional, Wen, Yi, additional, Huang, Yuanchen, additional, Weng, Senhui, additional, Lan, Shaoyang, additional, Nie, Kechao, additional, Zheng, Zhihua, additional, Ji, Shuling, additional, Liu, Peng, additional, Li, Peiwu, additional, and Liu, Fengbin, additional

Published
2021
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24. Current Evidence and Future Perspective of Accuracy of Artificial Intelligence Application for Early Gastric Cancer Diagnosis With Endoscopy: A Systematic and Meta-Analysis

Author

Jiang, Kailin, primary, Jiang, Xiaotao, additional, Pan, Jinglin, additional, Wen, Yi, additional, Huang, Yuanchen, additional, Weng, Senhui, additional, Lan, Shaoyang, additional, Nie, Kechao, additional, Zheng, Zhihua, additional, Ji, Shuling, additional, Liu, Peng, additional, Li, Peiwu, additional, and Liu, Fengbin, additional

Published
2021
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25. Construction and Validation of a Ferroptosis-Related Prognostic Model for Gastric Cancer

Author

Jiang, Xiaotao, primary, Yan, Qiaofeng, additional, Xie, Linling, additional, Xu, Shijie, additional, Jiang, Kailin, additional, Huang, Jiahua, additional, Wen, Yi, additional, Yan, Yanhua, additional, Zheng, Junhui, additional, Tang, Shuting, additional, Nie, Kechao, additional, Zheng, Zhihua, additional, Pan, Jinglin, additional, Liu, Peng, additional, Huang, Yuancheng, additional, Yan, Xingrui, additional, Zou, Yushan, additional, Chen, Xuan, additional, Liu, Fengbin, additional, Li, Peiwu, additional, and Zhuang, Kunhai, additional

Published
2021
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27. Construction and validation of a TP53-associated immune prognostic model for gastric cancer

Author

Nie, Kechao, primary, Zheng, Zhihua, additional, Wen, Yi, additional, Shi, Laner, additional, Xu, Shjie, additional, Wang, Xueqi, additional, Zhou, Yingsheng, additional, Fu, Bin, additional, Li, Xiushen, additional, Deng, Zhitong, additional, Pan, Jinglin, additional, Jiang, Xiaotao, additional, Jiang, Kailin, additional, Yan, Yanhua, additional, Zhuang, Kunhai, additional, Huang, Wei, additional, Liu, Fengbin, additional, and Li, Peiwu, additional

Published
2020
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28. CXCR4 Negatively Correlates with NKT Cell Infiltration During Gastric Precancerous Lesions Progression to Early Gastric Cancer

Author

Jiang, Xiaotao, primary, Zhuang, Kunhai, additional, Jiang, Kailin, additional, Wen, Yi, additional, Xie, Linling, additional, Weng, Senhui, additional, Chen, Xu, additional, Nie, Kechao, additional, Zheng, Zhihua, additional, Pan, Jinglin, additional, Yan, Yanhua, additional, Liu, Peng, additional, Zheng, Junhui, additional, Huang, Yuancheng, additional, Liu, Yufeng, additional, Li, Peiwu, additional, and Liu, Fengbin, additional

Published
2020
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32. Construction of a 13‐microRNA‐based signature and prognostic nomogram for predicting overall survival in patients with hepatocellular carcinoma

Author

Zheng, Zhihua, primary, Wen, Yi, additional, Nie, Kechao, additional, Tang, Shuting, additional, Chen, Xu, additional, Lan, Shaoyang, additional, Pan, Jinglin, additional, Jiang, Kailin, additional, Jiang, Xiaotao, additional, Liu, Peng, additional, Yan, Yanhua, additional, Liu, Fengbin, additional, Liu, Yufeng, additional, and Li, Peiwu, additional

Published
2020
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35. LYZ and SST Prevent the Progression of Chronic Inflammation into Adenocarcinoma in the Stomach

Author

Pan, Jinglin, primary, Su, Zeqi, additional, Gao, Shujing, additional, Wen, Yi, additional, Chen, Xinlin, additional, Ke, Zunfu, additional, Fu, Bin, additional, Wang, Xueqi, additional, Li, Haiwen, additional, Zhuang, Kunhai, additional, Liu, Hong, additional, Xu, Zhiheng, additional, Li, Jian, additional, Wei, Honghuai, additional, Jian, Yanting, additional, Ji, Yichun, additional, Huang, Yuancheng, additional, Jiang, Xiaotao, additional, Jiang, Kailin, additional, Nie, Kechao, additional, Zheng, Zhihua, additional, Wei, Wei, additional, Liu, Yufeng, additional, Liu, Fengbin, additional, and Li, Peiwu, additional

Published
2020
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36. Identification of potential crucial genes associated with the pathogenesis and prognosis of liver hepatocellular carcinoma

Author

Shi, Laner, Shang, Xin, Nie, Kechao, Lin, Zhiqin, Zheng, Meisi, Wang, Miao, Yuan, Haoyu, and Zhu, Zhangzhi

Abstract

AimsLiver hepatocellular carcinoma (LIHC) is the main manifestation of primary liver cancer, with low survival rate and poor prognosis. Medical decision-making process of LIHC is so complex that new biomarkers for diagnosis and prognosis have yet to be explored, this study aimed to identify the genes involved in the pathophysiology of LIHC and biomarkers that can be used to predict the prognosis of LIHC.MethodsSix Gene Expression Omnibus (GEO) datasets selected from GEO were screened and integrated to find out the differential expression genes (DEGs) obtained from LIHC and normal hepatic tissues. The Gene Ontology and Kyoto Encyclopaedia of Genes and Genomes pathway enrichment analysis of DEGs was implemented by DAVID. The Protein–protein interaction network was performed via STRING. In addition, Cox regression model was used to construct a gene prognostic signature.ResultsWe ascertained 10 hub genes, nine of them (CDK1, CDC20, CCNB1, Thymidylate synthetase, Nuclear division cycle80, NUF2, MAD2L1, CCNA2 and BIRC5) as biomarkers of progression in LIHC patients. We also build a six gene prognosis signature (SOCS2, GAS2L3, NLRP5, TAF3, UTP11 and GAGE2A), which can be implemented to predict over survival effectively.ConclusionsWe revealed promising genes that may participate in the pathophysiology of LIHC, and found available biomarkers for LIHC prognosis prediction, which were significant for researchers to further understand the molecular basis of LIHC and direct the synthesis medicine of LIHC.

Published
2021
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38. Coffee intake and risk of pancreatic cancer: an updated meta-analysis of prospective studies.

Author

Nie K, Xing Z, Huang W, Wang W, and Liu W

Subjects
Humans, Prospective Studies, Risk Factors, Coffee adverse effects, Pancreatic Neoplasms etiology
Abstract

Introduction: Inconsistent results on the relationship between coffee consumption and pancreatic cancer risk has been reported in both epidemiological studies and previous meta-analyses. This updated meta-analysis was conducted to assess the association of coffee intake with pancreatic cancer risk., Evidence Acquisition: We evaluated the relationship of coffee ingestion and pancreatic cancer risk by performing a meta-analysis of prospective cohort studies and made an explicit document search in the PubMed database before November 2015. We also obtained prospective cohort studies of previous meta-analyses. A random-effects model was used for pooling overall relative risk. Twenty articles of coffee ingestion and pancreatic cancer were contained in our meta-analysis., Evidence Synthesis: The summary relative risk (RR) of pancreatic cancer and coffee intake of the highest compared with lowest category was 0.99 (95% CI=0.81-1.21), with statistically moderate heterogeneity (I2=47.9%, P=0.008). The heterogeneity reduced to I2=38.5% after excluding one study, and the RR was 1.06 (95% CI=0.94-1.20). The relationships of coffee intake and pancreatic risk did not modified by geographic areas, sex of participants, number of cases, follow-up years, and the number of adjusted confounders., Conclusions: Dose-response analysis indicated that every one-cup increase in coffee consumption was associated with an 1% increase in pancreatic cancer risk. No statistically significant publication biases existed. Coffee consumption may weakly increase the risk of pancreatic cancer.

Published
2016

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