DGAT1 Expression Promotes Ovarian Cancer Progression and Is Associated with Poor Prognosis by Leilei Xia, Ye Wang, Shengyun Cai, Mingjuan Xu

“…We analyzed the correlation between DGAT1 and ovarian cancer staging, grading, vascular invasion, and prognosis by collating the information of ovarian cancer specimens from The Cancer Genome Atlas (TCGA) database. Furthermore, the effects of DGAT1 expression on proliferation, migration, invasion, and tumor growth were studied using ovarian cancer cell lines. …”
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RNA modification writer-based immunological profile and genomic landscape of tumor microenvironment in lung adenocarcinoma by Qiang Xu, Lingyu Kong, Zhezhu Han, Xiuying Jin, Mingyan Ding, Zhengri Piao, Songnan Zhang

“…Methods We assessed the expression properties and genetic alterations of 26 RNA modification writers, including adenosine-to-inosine RNA editing, alternative polyadenylation, m1A, and m6A in 502 lung adenocarcinoma (LUAD) samples from the Cancer Genome Atlas (TCGA) datasets. Then, we used differentially expressed gene (DEGs) to develop a signature for predicting patient outcomes, which was dubbed the “writer score” for RNA-modified writers. …”
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Spatial transcriptome reveals histology-correlated immune signature learnt by deep learning attention mechanism on H&E-stained images for ovarian cancer prognosis by Chun Wai Ng, Kwong-Kwok Wong, Barrett C. Lawson, Sammy Ferri-Borgogno, Samuel C. Mok

“…Methods In this study, 773 WSIs of H&E-stained tumor sections from 335 patients with treatment naïve high-grade serous ovarian cancer who were included in The Cancer Genome Atlas (TCGA) Pan-Cancer study were used to train, and validate, and to test a ResNet101 CNN model modified with attention mechanism. …”
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The Prognostic Significance of TRs in Hepatocellular Carcinoma: Insights from TCGA and GEO Databases by Hao Zhou, Weijie Wang, Ruopeng Liang, Rongtao Zhu, Jiahui Cao, Chenguang Sun, Yuling Sun

“…Methods: This study utilized Kaplan-Meier analysis of TR expression profiles from The Cancer Genome Atlas (TCGA). Expression levels of TRs in HCC and immune single cells were assessed using datasets from the Gene Expression Omnibus (GEO) and TCGA, analyzed with R software. …”
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Development of a 3-MicroRNA Signature and Nomogram for Predicting the Survival of Patients with Uveal Melanoma Based on TCGA and GEO Databases by Jun Zuo, Hongquan Ye, Jing Tang, Jianqun Lu, Qi Wan

“…Methods. miRNA and mRNA sequencing data for 80 UM patients were obtained from The Cancer Genome Atlas (TCGA) database. The patients were further randomly assigned to a training set (n = 40, used to identify key miRNAs) and a testing set (n = 40, used to internally verify the signature). …”
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Machine learning-random forest model was used to construct gene signature associated with cuproptosis to predict the prognosis of gastric cancer by Xiaolong Liu, Pengxian Tao, He Su, Yulan Li

“…Transcriptome and clinical data of patients with GC were collected from The Cancer Genome Atlas and Gene Expression Omnibus datasets. …”
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NEIL3 Mediates Lung Cancer Progression and Modulates PI3K/AKT/mTOR Signaling: A Potential Therapeutic Target by Hongbo Huang, Qingwang Hua

“…The public data used in this study were downloaded from The Cancer Genome Atlas (TCGA) database. “Limma” in R was used for the analysis of differentially expressed genes. …”
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Multi‐omics graph convolutional networks for digestive system tumour classification and early‐late stage diagnosis by Lin Zhou, Zhengzhi Zhu, Hongbo Gao, Chunyu Wang, Muhammad Attique Khan, Mati Ullah, Siffat Ullah Khan

“…A rigorous experimental evaluation was undertaken on the DST dataset from The Cancer Genome Atlas to scrutinise the efficacy of the MGTCN model. …”
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A Novel Insight into Paraptosis-Related Classification and Signature in Lower-Grade Gliomas by Xi-Feng Qian, Jia-Hao Zhang, Yue-Xue Mai, Xin Yin, Yu-Bin Zheng, Zi-Yuan Yu, Guo-Dong Zhu, Xu-Guang Guo

“…The relevant data of LGG patients were acquired from The Cancer Genome Atlas database, and we found that LGG patients could be divided into three different clusters based on paraptosis via consensus cluster analysis. …”
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The role of MRO as an M2 macrophage-associated gene in non-small cell lung cancer: insights into immune infiltration, prognostic significance, and therapeutic implications by Yue Gu, Miaosen Zheng, Jing Xie

“…Methods NSCLC samples from The Cancer Genome Atlas (TCGA) were analyzed using the CIBERSORT algorithm to quantify immune cell compositions. …”
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Lipid Metabolism-Related Gene Signature Predicts Prognosis and Indicates Immune Microenvironment Infiltration in Advanced Gastric Cancer by Lijian He, Qiange Ye, Yanmei Zhu, Wenqi Zhong, Guifang Xu, Lei Wang, Zhangding Wang, Xiaoping Zou

“…We obtained gene expression profiles from The Cancer Genome Atlas (TCGA) database for early and advanced gastric cancer samples and performed differential expression analysis to identify specific lipid metabolism-related genes in AGC. …”
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Developing a novel model for predicting overall survival in late-onset colon adenocarcinoma patients based on LODDS: a study based on the SEER database and external validation by Chen Chen, Heng-Bo Xia, Wei-Wei Yuan, Meng-Ci Zhou, Xue Zhang, A.-Man Xu

“…Results A total of 103,291 and 100 patients with late-onset colon adenocarcinoma (50–80 years old) were screened from the Surveillance, Epidemiology, and End Results (SEER) and The Cancer Genome Atlas (TCGA) databases, respectively. Cox regression analysis revealed independent risk factors for OS and CSS, including age, gender, race, size, LODDS stage, PLN stage, LNR stage, and TNM stage. …”
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Comprehensive analysis of the prognostic, immunological, and diagnostic roles of SIRT1 in pan-cancer and its validation in KIRC by Qi Liu, Songxian Sun, Chunxiang Zhou, Houxi Xu, Houxi Xu

“…Our study aimed to analyze the role of SIRT1 in pan-cancer to gain a more comprehensive understanding of its role in multiple malignancies.MethodsWe systematically examined the role of SIRT1 in pan-cancer by analyzing data from The Cancer Genome Atlas (TCGA) and Genotype-Tissue Expression (GTEx) databases. …”
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Kruppel-family zinc finger proteins as emerging epigenetic biomarkers in head and neck squamous cell carcinoma by Patrick Pearson, Kendra Smith, Nilita Sood, Elizabeth Chia, Alicia Follett, Michael B. Prystowsky, Simon Kirby, Thomas J. Belbin

“…Methods We examined prognostic significance of ZNF154 and ZNF132 expression and DNA methylation in independent patient cohort of about 500 head and neck cancer patients in the Cancer Genome Atlas (TCGA). We also overexpressed these genes in HEK-293 cells, as well as the oral cancer cell line UM-SCC-1. …”
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DNA methylation of ACADS promotes immunogenic cell death in hepatocellular carcinoma by Ze Qian, Yifan Jiang, Yacong Wang, Yu Li, Lin Zhang, Xiaofeng Xu, Diyu Chen

“…Methods and results Using RNA sequencing data from different tumours in The Cancer Genome Atlas database, we observed that ACADS was downregulated and hypermethylated in HCC. …”
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RETRACTED ARTICLE: Single-cell omics and machine learning integration to develop a polyamine metabolism-based risk score model in breast cancer patients by Xiliang Zhang, Hanjie Guo, Xiaolong Li, Wei Tao, Xiaoqing Ma, Yuxing Zhang, Weidong Xiao

“…Methods We used a multi-omics approach combining bulk RNA sequencing and single-cell RNA sequencing (scRNA-seq) to study polyamine metabolism. Data from The Cancer Genome Atlas, Gene Expression Omnibus, and Genotype-Tissue Expression identified 286 differentially expressed genes linked to polyamine pathways in breast cancer. …”
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MicroRNA-150-3p enhances the antitumour effects of CGP57380 and is associated with a favourable prognosis in non-small cell lung cancer by Hongmei Zheng, Songqing Fan, Jiadi Luo, Qiuyuan Wen, Hongjing Zang

“…A similar analysis was performed using data from The Cancer Genome Atlas (TCGA). Cell proliferation, colony formation and migration assays were validated in A549 and H157 cells treated with miR-150-3p mimics. …”
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The immune-related gene CD5 is a prognostic biomarker associated with the tumor microenvironment of breast cancer by Yi Zhao, Hengheng Zhang, Wenwen Wang, Guoshuang Shen, Miaozhou Wang, Zhen Liu, Jiuda Zhao, Jinming Li

“…In this study, we obtained the RNA-seq data of 1086 patients from The Cancer Genome Atlas (TCGA) database. We calculated the proportions of tumor-infiltrating immune cells (TICs) and immune and stromal components using the CIBERSORT and ESTIMATE methods, and we screened differentially expressed genes (DEGs). …”
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Exploring the prognostic role of microbial and genetic markers in lung squamous cell carcinoma by Fan Yang, Xiaodong Jia, Zihuan Ma, Siyao Liu, Chunzi Liu, Dan Chen, Xiuju Wang, Niansong Qian, Hui Ma

“…LUSC patient data from The Cancer Genome Atlas (TCGA), including microbial genus level abundance data and RNA sequencing (RNA-Seq) data, were used as a training dataset. …”
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Prognostic value of FCER1G expression and M2 macrophage infiltration in esophageal squamous cell carcinoma by Wei Peng, Yali Zhao, Ningning Yang, Yan Fang, Yintong Wu, Zhenzhong Feng, Qiang Wu, Xian Wang

“…Methods The expression of FCER1G and its prognostic value in ESCC was examined by The Cancer Genome Atlas and Gene Expression Omnibus databases. …”
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