CST2 promotes cell proliferation and regulates cell cycle by activating Wnt-β-catenin signalling pathway in serous ovarian cancer by Xiaohua Wang, Sufen Zhao, Yanwei Guo, Chunhui Wang, Shuyu Han, Xingcha Wang

“…Therefore, we aimed to investigate the expression levels, survival outcomes, immune cell infiltration, proliferation, cell cycle, and underlying molecular mechanisms associated with the CST2 signature in SOC.Methods The Cancer Genome Atlas database was used to acquire clinical information and CST2 expression profiles from patients with SOC. …”
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Identification of SETD4 as an Onco‐Immunological Biomarker Encompassing the Tumor Microenvironment, Prognoses, and Therapeutic Responses in Various Human Cancers by Yuyun Zhong, Ruiqi Wang, Zijie Huang, Zhaoting Hu, Bin Peng, Bin Chen, Liyue Sun

“…Methods Utilizing The Cancer Genome Atlas database, and other publicly accessible platforms, we comprehensively analyzed SETD4 gene expression, methylation patterns, and prognostic significance. …”
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SHP2 promotes the epithelial-mesenchymal transition in triple negative breast cancer cells by regulating β-catenin by Shihan Qian, Jingjing Zhu, Qing Han, Huang Cheng, Huaibin Zhou

“…Methods In this study, we conducted bioinformatics analysis of the Gene Expression Omnibus (GEO) and The Cancer Genome Atlas (TCGA) databases to examine PTPN11 (encoding SHP2) expression levels and perform survival analysis in TNBC. …”
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UBE2J1 is identified as a novel plasma cell-related gene involved in the prognosis of high-grade serous ovarian cancer by Yunjie Tian, Ruoyu Dong, Yingxia Guan, Ying Wang, Wei Zhao, Jun Zhang, Shan Kang

“…The effects of immune cell markers on prognosis were analyzed via univariate Cox regression, least absolute shrinkage and selection operator (LASSO) and gene set variation analysis (GSVA) of bulk sequencing data from The Cancer Genome Atlas (TCGA)-HGSOC cohort. Finally, the effects of key markers on HGSOC cells were evaluated via Cell Counting Kit-8 (CCK-8), Transwell, colony formation, wound healing, immunofluorescence and in vivo tumor growth assays. …”
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Screening and validation of tsRNAs associated with lung adenocarcinoma by LU Chunli, SHAN Yifan, XIE Weijia

“…The effects of tsRNAs expression levels on the prognosis of lung adenocarcinoma patients were analyzed based on the Cancer Genome Atlas （TCGA） database （TCGA-LUAD）. The target genes were predicted based on TRFtarget2.0 and tRFTar databases. …”
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Analysing DNA methylation and transcriptomic signatures to predict prostate cancer recurrence risk by Fahad M. Aldakheel, Hadeel Alnajran, Shatha A. Alduraywish, Ayesha Mateen, Mohammed S. Alqahtani, Rabbani Syed

“…This study employs a machine learning approach to identify DNA methylation and RNA expression biomarkers predictive of PCa recurrence using datasets from The Cancer Genome Atlas (TCGA). We analyzed 49,133 genes, identifying 684 differentially methylated genes (DMGs) and 691 differentially expressed genes (DEGs) between recurrence and non-recurrence groups. …”
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Exploration of the Immune-Related Signatures and Immune Infiltration Analysis in Melanoma by Ai-lan Li, Yong-mei Zhu, Lai-qiang Gao, Shu-yue Wei, Ming-tao Wang, Qiang Ma, You-you Zheng, Jian-hua Li, Qing-feng Wang

“…The transcriptome profiling and clinical data of melanoma were downloaded from The Cancer Genome Atlas database, and their matched normal samples were obtained from the Genotype-Tissue Expression database. …”
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RETRACTED ARTICLE: NR3C2 affects the proliferation and invasiveness of colon cancer cells through the Wnt/β-Catenin signaling pathway by Ke Nie, Zhong-Jiang He, Ling-Jun Kong

“…Method mRNA (messenger RNA) data and clinical records pertaining to colon cancer were retrieved from The Cancer Genome Atlas (TCGA) database. The analysis of NR3C2 expression discrepancies between normal colon and tumor tissues was conducted using R software. …”
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Identification and Verification of Novel Biomarkers Involving Rheumatoid Arthritis with Multimachine Learning Algorithms: An In Silicon and In Vivo Study by Fucun Liu, Juelan Ye, Shouli Wang, Yang Li, Yuhang Yang, Jianru Xiao, Aimin Jiang, Xuhua Lu, Yunli Zhu

“…We retrieved RA-related and pan-cancer information datasets from the Gene Expression Omnibus and The Cancer Genome Atlas databases, respectively. Six gene expression profiles and corresponding clinical information of GSE12021, GSE29746, GSE55235, GSE55457, GSE77298, and GSE89408 were adopted to perform differential expression gene analysis, enrichment, and immune component difference analyses of RA. …”
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Interleukin-6 as a Pan-Cancer Prognostic Inflammatory Biomarker: A Population-Based Study and Comprehensive Bioinformatics Analysis by Xie H, Wei L, Ruan G, Zhang H, Shi H

“…The SangerBox database was used to analyze the correlation between IL-6 expression and immune checkpoint (ICP), tumor mutation burden (TMB), and microsatellite instability (MSI) in cancer. Genomic changes in the IL-6 levels were studied using the c-BioPortal database. …”
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Identification of Five m6A-Related lncRNA Genes as Prognostic Markers for Endometrial Cancer Based on TCGA Database by Li Shan, Ye Lu, Cheng-Cheng Xiang, Xiaoli Zhu, Er-Dong Zuo, Xu Cheng

“…Gene expression and clinical data were extracted from The Cancer Genome Atlas. Coexpression analysis was performed to identify m6A-related lncRNAs, which were entered into univariate Cox regression models for evaluating the prognosis of UCEC. …”
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Identification of HOXA9 methylation as an epigenetic biomarker predicting prognosis and guiding treatment choice in acute myeloid leukemia by Fei Xie, Ting-juan Zhang, Xin-long Zhang, Zi-jun Xu, Liang Qiao, Yun Wang, Yang-jing Zhao, Jun Qian, Jing-dong Zhou

“…Methods We systematically first screened the prognostic value of HOXA cluster genes methylation in AML from The Cancer Genome Atlas (TCGA) datasets. Afterwards, the candidate prognosis-related gene HOXA9 were selected for clinical relevance analysis and were further validated in another independent cohort from our research center. …”
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SUMO modified ETV1 promotes M2-polarized tumor-associated macrophage infiltration and cancer progression by facilitating CCL2 transcription in esophageal squamous cell carcinoma ce... by Tianci Han, Xiaoqi Guo, Junwei Xie, Wei Tong, Liang Zhang

“…Methods Gene expression and immune infiltration in ESCC samples from the Cancer Genome Atlas (TCGA) were analyzed. The expression of ETV1 in clinical samples was detected by real-time PCR, western blot and immunohistochemistry staining. …”
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Genomic characterization of Escherichia coli with a polyketide synthase (pks) island isolated from ulcerative colitis patients by Chao Lv, Mohd Abdullah, Chun-Li Su, Weiye Chen, Nan Zhou, Zile Cheng, Yiwen Chen, Min Li, Kenneth W. Simpson, Ahmed Elsaadi, Yongzhang Zhu, Steven M. Lipkin, Yung-Fu Chang

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Construction and validation of prognosis and treatment outcome models based on plasma membrane tension characteristics in bladder cancer by Zhipeng Wang, Sheng Li, Fuchun Zheng, Situ Xiong, Lei Zhang, Liangwei Wan, Chen Wang, Xiaoqiang Liu, Jun Deng

“…Methods Transcriptomic, clinical and mutation data from BLCA patients were collected from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. …”
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Immune regulatory genes impact the hot/cold tumor microenvironment, affecting cancer treatment and patient outcomes by Mengmeng Sang, Jia Ge, Juan Ge, Juan Ge, Gu Tang, Qiwen Wang, Jiarun Wu, Liming Mao, Liming Mao, Xiaoling Ding, Xiaorong Zhou

“…Nevertheless, as yet there is no consensus regarding the clinically relevant definition of hot/cold tumors, and the influence of immune genes on the formation of hot/cold tumors remains poorly understood.MethodsData for 33 different types of cancer were obtained from The Cancer Genome Atlas database, and their immune composition was assessed using the CIBERSORT algorithm. …”
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A Novel Immune-Related lncRNA-Based Model for Survival Prediction in Clear Cell Renal Cell Carcinoma by Zedan Zhang, Yanlin Tang, Yanjun Liu, Hongkai Zhuang, Enyu Lin, Lu Xie, Xiaoqiang Feng, Kaiwen Tian, Jiayi Zeng, Jiumin Liu, Yuming Yu

“…The transcription profile and clinical information were obtained from The Cancer Genome Atlas (TCGA). Immune-related gene sets and transcription factor genes were downloaded from GSEA website and Cistrome database, respectively. …”
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Unveiling the role of ASPP1 in cancer progression: pan-cancer bioinformatics and experimental validation in colorectal cancer by Keyuan Xiao, Xiang Li, Ihsan Ullah, Wenqing Hu, Kaiqiang Wang, Fan Yang, Chengyu Yang, Chunqi Feng, Liang Zong, Xinghua Li

“…Data were extracted from public resources, including The Cancer Genome Atlas (TCGA), GTEx, and the Human Protein Atlas, and analyzed via tools such as cBioPortal, GEPIA, and TIMER2. …”
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CT45A1‐mediated MLC2 (MYL9) phosphorylation promotes natural killer cell resistance and outer cell fate in a cell‐in‐cell structure, potentiating the progression of microsatellite... by Hao‐Wei Teng, Hsiang‐Yueh Huang, Chun‐Chi Lin, Yuh‐Ching Twu, Wen‐Hao Yang, Wen‐Chun Lin, Hsin‐Yi Lan, Yen‐Yu Lin, Wei‐Lun Hwang

“…We aimed to identify the tumor‐autonomous regulators determining these heterogeneous clinical outcomes. The Cancer Genome Atlas (TCGA) dataset was used to identify regulators in MSI‐H CRC patients with unfavorable outcomes. …”
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Integrating single-cell RNA-seq and bulk RNA-seq to explore prognostic value and immune landscapes of methionine metabolism-related signature in breast cancer by Yanxian Gao, Ziyu Feng, Hailong Zhao, Xinghai Liu, Muyu Zhu, Xiafei Yu, Xiaoan Liu, Xian Wu, Jing Tao

“…Breast cancer cell lines have been identified as methionine-dependent, and methionine restriction has been proposed as a potential cancer treatment strategy.MethodsWe integrated transcriptomic and single-cell RNA sequencing (ScRNA-seq) analyses based on The Cancer Genome Atlas (TCGA) database and Gene Expression Omnibus (GEO) datasets. …”
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