KYNU as a Biomarker of Tumor-Associated Macrophages and Correlates with Immunosuppressive Microenvironment and Poor Prognosis in Gastric Cancer by Kaiyu Shen, Binyu Chen, Liu Yang, Wencang Gao

“…GC-associated single-cell RNA sequencing and bulk RNA sequencing (bulk-seq) data were obtained from the Gene Expression Omnibus and The Cancer Genome Atlas databases, respectively. The differential expression of KYNU between GC and normal gastric tissues was first analyzed based on the bulk-seq data, followed by an exploration of the relationship between KYNU and various clinicopathological features. …”
Get full text

The Potential Dual Role of H2.0-like Homeobox in the Tumorgenesis and Development of Colorectal Cancer and Its Prognostic Value by Shuo Chen, Lin Zhang, Kai Wang, Jizhen Huo, Siqi Zhang, Xipeng Zhang

“…In this study, the data were collected from The Cancer Genome Atlas and Gene Expression Omnibus databases. …”
Get full text

Transmembrane and Ubiquitin-Like Domain-Containing 1 Promotes Glioma Growth and Indicates Unfavorable Prognosis by Yinggang Liu, Changcheng Cai, Ke Wu, Libo Hu

“…We conducted a comprehensive analysis using two cohorts: a retrospective glioma cohort from our hospital and The Cancer Genome Atlas (TCGA) cohort. The mRNA levels of TMUB1 were assessed through reverse transcription-quantitative polymerase chain reaction (RT-qPCR). …”
Get full text

Correcting scale distortion in RNA sequencing data by Christopher Thron, Farhad Jafari

“…We examined several RNA-seq datasets from the Cancer Genome Atlas (TCGA), Stand Up 2 Cancer (SU2C), and GTEx databases with various types of preprocessing. …”
Get full text

Impact of Extracellular Matrix-Related Genes on the Tumor Microenvironment and Prognostic Indicators in Esophageal Cancer: A Comprehensive Analytical Study by Yinghong Wu, Wenjie Hu, Zhihong Jia, Qiying Zhu, Jinghui Xu, Liang Peng, Renjie Wang

“…Our study utilized next-generation sequencing and clinical data from esophageal cancer patients provided by The Cancer Genome Atlas, employing the R package in RStudio for computational analysis. …”
Get full text

Construction of a 12-gene prognostic model for colorectal cancer based on heat shock protein-related genes by Qin Tong, Junchao Zhou

“…Transcriptional data and clinical information of CRC patients were obtained from The Cancer Genome Atlas (TCGA) database, and a literature search was conducted to identify HSP-related genes. …”
Get full text

Identification and Validation of a Potential Stemness-Associated Biomarker in Hepatocellular Carcinoma by Yangyang Zhang, Ruike Zhang, Lingxiu Zeng, Haizhou Wang, Ruyi Peng, Meng Zhang, Hailin Zhang, Zhenwei Yang, Liping Gao, Meng Wang, Jing Liu

“…The data of HCC patients from The Cancer Genome Atlas (TCGA) were collected and divided based on the mRNA expression-based stemness index (mRNAsi) in this study. …”
Get full text

Identification of a Novel PPAR Signature for Predicting Prognosis, Immune Microenvironment, and Chemotherapy Response in Bladder Cancer by Ke Zhu, Wen Deng, Hui Deng, Xiaoqiang Liu, Gongxian Wang, Bin Fu

“…The RNA sequencing data and clinical information of BLCA patients were acquired from The Cancer Genome Atlas (TCGA). The differentially expressed PPAR-targeted genes were investigated. …”
Get full text

A Systematic Pan-Cancer Analysis of YY1 Aberrations and their Relationship with Clinical Outcome, Tumor Microenvironment, and Therapeutic Targets by Xinghao Fu, Feihong Ji, Qi He, Xinguang Qiu

“…We first explored the potential carcinogenic effect of YY1 in 33 cancers using the cancer genome atlas (TCGA) project and gene expression omnibus (GEO) datasets in this research. …”
Get full text

Landscape of Alternative Splicing Events Related to Prognosis and Immune Infiltration in Glioma: A Data Analysis and Basic Verification by Hong-xin Su, Gang Yang, Fei Su, Chen-xiao Hu, Tao Zhang, Jun-tao Ran, Quan-lin Guan

“…RNA splicing patterns were collected from The Cancer Genome Atlas SpliceSeq database, followed by calculating the percentage of splicing index. …”
Get full text

Intratumor heterogeneity: models of malignancy emergence and evolution by R. A. Ivanov, S. A. Lashin

“…These techniques enable the identification of somatic mutations, copy number alterations, and structural rearrangements within cancer genomes. Furthermore, single­cell sequencing methods have emerged as powerful tools for dissecting intratumoral heterogeneity and tracing clonal evolution. …”
Get full text

CTSK and PLAU as Prognostic Biomarker and Related to Immune Infiltration in Pancreatic Cancer: Evidence from Bioinformatics Analysis and qPCR by Yuntao Ding, Zhangzuo Li, Huizhi Wang, Qi Wang, Han Jiang, Zhengyue Yu, Min Xu

“…Expression profiles and clinical data from the Cancer Genome Atlas (TCGA) were then used to compare the expression levels of CTSK and PLAU in pancreatic cancer and healthy pancreatic tissues via the Wilcoxon rank-sum test, with further validation using qPCR. …”
Get full text

Multiomic machine learning on lactylation for molecular typing and prognosis of lung adenocarcinoma by Mengmeng Hua, Tao Li

“…LRG mRNA and long non-coding RNA transcriptomes, epigenetic methylation data, and somatic mutation data from The Cancer Genome Atlas LUAD cohort were analyzed to identify lactylation cancer subtypes (CSs) using 10 multiomics ensemble clustering techniques. …”
Get full text

Exploring Unique Extracellular Vesicles Associated Signatures: Prognostic Insights, Immune Microenvironment Dynamics, and Therapeutic Responses in Pancreatic Adenocarcinoma by Kai Nan, Ming Zhang, Zilong Geng, Yuankai Zhang, Lin Liu, Zhi Yang, Peng Xu

“…Initially, we identified differentially expressed lncRNAs (DELs) from The Cancer Genome Atlas (TCGA) and Genotype-Tissue Expression (GTEx) project datasets. …”
Get full text

Comprehensive genomic profiling of primary bladder mucinous adenocarcinoma, a rare genitourinary cancer: A case report by Shinkuro Yamamoto, Shingo Ashida, Tomoya Nao, Kaho Murakami, Ryohei Iga, Tsutomu Shimamoto, Hideo Fukuhara, Nobutaka Shimizu, Satoshi Fukata, Atsushi Kurabayashi, Takashi Karashima, Keiji Inoue

Get full text

AMEND 2.0: module identification and multi-omic data integration with multiplex-heterogeneous graphs by Samuel S. Boyd, Chad Slawson, Jeffrey A. Thompson

“…AMEND was applied to two real-world multi-omic datasets: renal cell carcinoma data from The cancer genome atlas and an O-GlcNAc Transferase knockout study. …”
Get full text

Identification of the circRNA-miRNA-mRNA Regulatory Network in Bladder Cancer by Bioinformatics Analysis by Jiancheng Lv, Ping-an Chang, Xin Li, Xiao Yang, Jie Han, Hao Yu, Zijian Zhou, Haiwei Yang, Pengchao Li, Jiexiu Zhang, Qiang Lu

“…We obtained four datasets of circRNA, microRNA (miRNA), and messenger (mRNA) expression profiles from the Gene Expression Omnibus and The Cancer Genome Atlas microarray databases and identified 434, 367, and 4799/4841 differentially expressed circRNAs, miRNAs, and mRNAs, respectively. …”
Get full text

The Underlying Mechanism Involved in Gefitinib Resistance and Corresponding Experiment Validation in Lung Cancer by Puwei Song, Jianghui Zhou, Kaiqin Wu, Wenli Wang, Shaorui Gu

“…Open-accessed data of lung cancer patients were downloaded from The Cancer Genome Atlas Program and Gene Expression Omnibus databases. …”
Get full text

Exploration of the Long Noncoding RNAs Involved in the Crosstalk between M2 Macrophages and Tumor Metabolism in Lung Cancer by Fang Fang, Yuanshan Yao, Zhe Ma

“…This study aimed to identify the lncRNAs involved in the crosstalk between tumor metabolism and M2 macrophages. Methods. The Cancer Genome Atlas was responsible for the public data. …”
Get full text

NIPAL1 as a prognostic biomarker associated with pancreatic adenocarcinoma progression and immune infiltration by Youlong Zhu, Zongze Qi, Shaoqi Zu, Fangchao Yang, Yanming Wang, Lei Zhu, Xintong Li, Ruixue Li, Hong Zhu

“…Primitive RNA sequencing (RNA-seq) data of PAAD from The Cancer Genome Atlas (TCGA) was utilized for bioinformatics analysis to characterize the expression levels of NIPAL1 in tumor and normal tissues. …”
Get full text