A Metabolic Gene Signature to Predict Overall Survival in Head and Neck Squamous Cell Carcinoma by Zeng-Hong Wu, Yun Tang, Yue Zhou

“…In this study, we used RNA sequencing (RNA-seq) data from the cancer genome atlas (TCGA), with validation in the GEO dataset to profile the metabolic microenvironment and define potential biomarkers for metabolic therapy. …”
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Integrating bioinformatics and machine learning to identify AhR-related gene signatures for prognosis and tumor microenvironment modulation in melanoma by Qianru Li, Qianru Li, Heli Li

“…However, the specific downstream targets and mechanisms by which AhR influences melanoma remain insufficiently understood.MethodsMelanoma samples from The Cancer Genome Atlas (TCGA) and normal skin tissues from the Genotype-Tissue Expression (GTEx) database were analyzed to identify differentially expressed genes, which were intersected with a curated list of AhR-related pathway genes. …”
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Integrating RNA-seq and scRNA-seq to explore the prognostic features and immune landscape of exosome-related genes in breast cancer metastasis by Guanyou Huang, Yong Yu, Heng Su, Hongchuan Gan, Liangzhao Chu

“…Objective This study aims to explore the role of exosome-related genes in breast cancer (BRCA) metastasis by integrating RNA-seq and single-cell RNA-seq (scRNA-seq) data from BRCA samples and to develop a reliable prognostic model.Methods Initially, a comprehensive analysis was conducted on exosome-related genes from the BRCA cohort in The Cancer Genome Atlas (TCGA) database. Three prognostic genes (JUP, CAPZA1 and ARVCF) were identified through univariate Cox regression and Lasso-Cox regression analyses, and a metastasis-related risk score model was established based on these genes. …”
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The heterogeneity of NOTCH1 to tumor immune infiltration in pan-cancer by XiaoJun Duan, Rihan Wu, Mingyang Zhang, Kexin Li, Lei Yu, Huirong Sun, Xingxia Hao, Changshan Wang

“…In this study, the data originated from the Genotype-Tissue Expression (GTEx) and the Cancer Genome Atlas (TCGA) databases were input into multiple online bioinformatic tools to study the characteristics of NOTCH1 in pan-cancer. …”
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The Use of Machine Learning to Create a Risk Score to Predict Survival in Patients with Hepatocellular Carcinoma: A TCGA Cohort Analysis by Samer Tohme, Hamza O Yazdani, Amaan Rahman, Sanah Handu, Sidrah Khan, Tanner Wilson, David A Geller, Richard L Simmons, Michele Molinari, Christof Kaltenmeier

“…The current study uses Artificial Neural Network (ANN) and Classification Tree Analysis (CTA) to create a gene signature score that can help predict survival in patients with HCC. Methods. The Cancer Genome Atlas (TCGA-LIHC) was analyzed for differentially expressed genes. …”
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Promising markers of CIMP+ colon tumors identified on the basis of TCGA data analysis by G. S. Krasnov, A. D. Beniaminov, R. A. Tychko, G. A. Puzanov, R. O. Novakovskiy, A. V. Kudryavtseva, A. A. Dmitriev

“…For the identification of CpG sites, the methylation level of which could be used to detect CIMP+ tumors, an analysis of expression and methylation profiles of 297 primary colon tumors and 38 histologically normal tissues paired to them, which are presented in the TCGA (The Cancer Genome Atlas) project database, was performed by us using the CrossHub tool created previously. …”
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Comprehensive Analysis of the Mechanism of Anoikis in Hepatocellular Carcinoma by Dongqian Li, Qian Bao, Shiqi Ren, Haoxiang Ding, Chengfeng Guo, Kai Gao, Jian Wan, Yao Wang, MingYan Zhu, Yicheng Xiong

“…This paper’s data (TCGA-HCC) were retrieved from the database of the Cancer Genome Atlas (TCGA). Differential gene expression with prognostic implications for anoikis was identified by performing both the univariate Cox and differential expression analyses. …”
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The frequency of mutations in advanced thyroid cancer in Japan: a single-center study by Soji Toda, Hiroyuki Iwasaki, Yoichiro Okubo, Hiroyuki Hayashi, Mei Kadoya, Hiroyuki Takahashi, Tomoyuki Yokose, Yukihiko Hiroshima, Katsuhiko Masudo

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Identification of Survival Risk and Immune-Related Characteristics of Kidney Renal Clear Cell Carcinoma by Xiaobin Wu, Yonghui Liang, Xian Chen, Xiangyang Long, Wujun Xu, Li Liu, Binhui Wang, Xiong Zou

“…A series of information such as RNA sequence, clinical data, and tumor mutation burden (TMB) of KIRC patients were downloaded through The Cancer Genome Atlas (TCGA). Next, combining the survival information and gene expression data of TCGA and Gene Expression Omnibus (GEO), we established an immune gene-related prognosis model (IGRPM) and analyzed it. …”
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Apoptosis antagonizing transcription factor expression and its validation as a potential diagnostic and prognostic biomarker in oral squamous cell carcinoma by Ainiwaerjiang Abudourousuli, Zumulaiti Aierken, Hasiyati Mamuti, Tuxunayi Yimamu, Chengli Da

“…This study aimed to investigate the expression of apoptosis antagonizing transcription factor (AATF) in OSCC, examine its correlation with clinicopathological features, assess its prognostic implications, and explore its potential role in OSCC progression.MethodsExpression profiles and clinical data of OSCC patients were obtained from The Cancer Genome Atlas (TCGA). Immunohistochemical analysis on tissue microarrays was performed to assess AATF expression in OSCC. …”
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Novel protein-based prognostic signature linked to immunotherapeutic efficiency in ovarian cancer by Shuo-Fu Chen, Liang-Yun Wang, Yi-Sian Lin, Cho-Yi Chen

“…Methods The workflow was demonstrated based on the Reverse Phase Protein Array (RPPA) and RNA-sequencing profiles of ovarian cancer patients from The Cancer Genome Atlas (TCGA). The algorithm began by clustering patients using immune-related gene sets, which allowed us to identify immune-related proteins of interest. …”
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Immune gene features and prognosis in colorectal cancer: insights from ssGSEA typing by Anwen Huang, Jinxiu Wu, Jiakuan Wang, Chengwen Jiao, Yunfei Yang, Huaiwen Xiao, Li Yao

“…Methods We obtained and merged RNA-Seq data along with clinical details for colorectal cancer (CRC) from The Cancer Genome Atlas (TCGA) repository, and then performed immunocluster typing on all CRC specimens. …”
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MKRN1 promotes colorectal cancer metastasis by activating the TGF-β signalling pathway through SNIP1 protein degradation by Yi Zhang, Qin-shan Li, Hong-lin Liu, Hong-ting Tang, Han-lin Yang, Dao-qiu Wu, Yu-ying Huang, Li-cheng Li, Li-hong Liu, Meng-xing Li

“…Methods MKRN1 expression in CRC was analysed using the Cancer Cell Line Encyclopaedia and the Cancer Genome Atlas (TCGA) databases. Rectal tumour tissues were frozen to explore the MKRN1 expression in CRC and its clinical significance. …”
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The role of long non-coding RNA LINC00839 in oral squamous cell carcinoma based on bioinformatics and experimental research by Ashkan Kalantary-Charvadeh, Saman Morovat, Somayeh Aslani, Nasrin Ziamajidi, Amirnader Emami Razavi, Roghayeh Abbasalipourkabir

“…Abstract This study explores the role of LINC00839 and its potential interaction with the miR-195-5p/cyclin E1 (CCNE1) axis in oral squamous cell carcinoma (OSCC). Using The Cancer Genome Atlas, we analyzed lncRNA, miRNA, and mRNA sequencing data for OSCC. …”
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Comprehensive Analysis of Competing Endogenous RNA Network Focusing on Long Noncoding RNA Involved in Cirrhotic Hepatocellular Carcinoma by Yuli Zhang, Dinggui Chen, Miaomiao Yang, Xianfeng Qian, Chunmei Long, Zhongwei Zheng

“…The lncRNA, miRNA, and mRNA expression datasets were obtained from Gene Expression Omnibus and The Cancer Genome Atlas. Based on miRanda and TargetScan, the HCC-specific ceRNA network was constructed to illustrate the coexpression regulatory relationship of lncRNAs, miRNAs, and mRNAs. …”
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Combining single-cell analysis and molecular docking techniques to construct a prognostic model for colon adenocarcinoma and uncovering inhibin subunit βb as a novel therapeutic ta... by Qinqing Wu, Qinqing Wu, Lu Ye, Yuwei Wu, Mengyu Zhao, Mengyu Zhao, Jiaxin Lu, Yanping Yu, Yanping Yu, Yixiao Niu, Yixiao Niu, Luxiao Zhang, Peijun Zuo, Peijun Zuo

“…However, the specific biological link between anoikis and COAD, as well as its mechanisms in tumor progression, remains unclear, making it a potential new direction for therapeutic strategy research.MethodsWe employed transcriptomic data and clinical information from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) to pinpoint differentially expressed anoikis-related genes (ARGs) in COAD. …”
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The expression of BHLHE22 in endometrial carcinoma: Associations with mismatch repair protein expression status, tumor-infiltrating immune cells, programmed death-ligand 1 and clin... by Lin-Yu Chen, Hsing-Yu Chen, Hung-Cheng Lai, Shiou-Fu Lin, Kuo-Chang Wen, Darmawi, Phui-Ly Liew

“…The associations between the clinicopathological characteristics, mismatch repair status, and Kaplan–Meier analyses (including The Cancer Genome Atlas (TCGA) dataset) were analyzed. Results: Twenty-nine of 109 cases (26.6 %) had high BHLHE22 expression, which was associated with higher tumoral CD8, higher stromal CD68 and lower progesterone receptor (PR). …”
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Integrative analysis of cuproptosis-related lncRNAs: Unveiling prognostic significance, immune microenvironment, and copper-induced mechanisms in prostate cancer by Haitao Zhong, Yiming Lai, Wenhao Ouyang, Yunfang Yu, Yongxin Wu, Xinxin He, Lexiang Zeng, Xueen Qiu, Peixian Chen, Lingfeng Li, Jie Zhou, Tianlong Luo, Hai Huang

“…Methods: Sequencing data and copy number variant data were obtained from 492 patients with PCa from The Cancer Genome Atlas (TCGA) Program. Prognostic models of PCa based on cuproptosis-related lncRNAs were constructed using a multi-level attention graph neural network (MLA-GNN) deep learning algorithm. …”
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Downregulated mRNA Expression of ZNF385B Is an Independent Predictor of Breast Cancer by Ning Yan, Cong Liu, Fang Tian, Ling Wang, Yimin Wang, Zhaoying Yang, Yan Jiao, Miao He

“…Furthermore, data of patients with BC were downloaded from The Cancer Genome Atlas (TCGA). The receiver operating characteristic (ROC) curve of ZNF385B expression was established to explore the diagnostic value of ZNF385B and to obtain the cut-off value of high or low ZNF385B expression in BC. …”
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CASC8 activates the pentose phosphate pathway to inhibit disulfidptosis in pancreatic ductal adenocarcinoma though the c-Myc-GLUT1 axis by Hong-Fei Yao, Jieqiong Ge, Jiahao Chen, Xiaoyan Tang, Chunjing Li, Xiao Hu, Abousalam Abdoulkader Ahmed, Yunlong Pu, Guihua Zhou, Tongyi Zhang, Zhiwei Cai, Chongyi Jiang

“…CASC8 expression and its clinical correlations were analyzed using data from The Cancer Genome Atlas (TCGA) and further verified by chromogenic in situ hybridization assay in PDAC tissues. …”
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