Exploring the role of methylation-driven gene IFFO1 in pancreatic adenocarcinoma diagnosis, prognosis and cellular functions by XU Ziqi, HU Ruizhi, LI Junjian, WANG Hongxia, SANG Youzhou

“…Methods: mRNA expression data (TCGA-PAAD-mRNA), DNA methylation data (TCGA-PAAD-meth, GSE53051, PACA-AU) of PAAD and adjacent normal tissues, as well as DNA methylation data of healthy individuals’ blood (GSE69270), were obtained from the The Cancer Genome Atlas (TCGA), International Cancer Genome Consortium (ICGC) and Gene Expression Omnibus (GEO) databases. …”
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Non‐Invasive Tumor‐Naïve Minimal Residual Disease Detection of Liver Cancer by Incorporating Circulating Tumor DNA Features and Alpha‐Fetoprotein: A Prospective Study by Qingqi Ren, Shiyong Li, Guolin Zhong, Yunfei Li, Dao‐Ling Huang, Liangliang Zhang, Yumin Feng, Guanghui Long, Mao Mao

“…This process integrated protein tumor marker alpha‐fetoprotein (AFP) and cancer genomic hallmarks, copy number aberration (CNA) and fragment size (FS). …”
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Chemokine family significance and prognostic value in colorectal cancer by Yi Ding, Yi Ding, Yi Ding, Yinnan Chen, Yinnan Chen, Yinnan Chen, Siyun Xie, Quanpeng Qiu, Quanpeng Qiu, Xiaolong Guo, Yun Feng, Yun Feng, Hongxia Li, Hongxia Li, Fang Zhu, Yaping Liu, Yaping Liu, Yaping Liu

“…This study was rigorously augmented using comprehensive datasets from The Cancer Genome Atlas (TCGA), ensuring a robust analysis of gene expression patterns associated with clinical outcomes.ResultsThrough data analysis, we identified key genes from the chemokine family thought pertinent to CRC outcomes. …”
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Immunoinfiltration Analysis of Mitochondrial Damage‐Related Genes in Lung Adenocarcinoma and Construction of a Classification and Prognostic Model Integrated With WGCNA and Machine... by Jirong Zhang, Lin Lin

“…Materials & Methods Using GeneCards and The Cancer Genome Atlas (TCGA) databases, we screened differentially expressed mitochondrial damage‐related genes in LUAD. …”
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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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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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Mitochondrial dysfunction-driven AMPK-p53 axis activation underpins the anti-hepatocellular carcinoma effects of sulfane sulfur by Xue Zheng, Yuhua Luo, Rui Huo, Yiwen Wang, Youbang Chen, Mianrong Chen, Qi Zhao, Kexin Li, Hanyi Zhang, Xiaotong Li, Xiang Li, Hui Zhang, Zaopeng He, Li Huang, Chun-tao Yang

“…We utilized bioinformatics algorithms for clustering, function enrichment, feature screening and survival analysis on proteomic data from the Cancer Proteome Atlas (CPTAC) and transcriptomic data from the Cancer Genome Atlas (TCGA). The impact of PSCP on HCC was assessed in vitro and in vivo, focusing on the expression and activity of p53 and AMP-activated protein kinase (AMPK), as well as mitochondrial function. …”
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Association of tumour mutation burden with prognosis and its clinical significance in stage III gastric cancer by Ya-Lin Han, Li Chen, Xu-Ning Wang, Mao-Lin Xu, Rui Qin, Fang-Ming Gong, Peng Sun, Hong-Yi Liu, Zhi-Peng Teng, Zhao-Xia Li, Guang-Hai Dai

“…Methods: Patients with stage III GC were divided into a high TMB and low TMB group in both a study cohort of 38 patients and the Cancer Genome Atlas (TCGA) cohort of 173 patients. In the study cohort, next-generation sequencing was used to detect mutated GC genes and obtain TMB data. …”
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Mutation in CDC42 Gene Set as a Response Biomarker for Immune Checkpoint Inhibitor Therapy by Kun Wang, Yingying Zhang, Zhaoming Su, Bei Wang, Yuanyang Zhou, Xiaochu Tong, Chengying Xie, Xiaomin Luo, Sulin Zhang, Mingyue Zheng

“…We explored the mechanism based on The Cancer Genome Atlas database. We also examined whether combining a CDC42 inhibitor with ICI could enhance ICI's efficacy. …”
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Predicting hepatocellular carcinoma outcomes and immune therapy response with ATP-dependent chromatin remodeling-related genes, highlighting MORF4L1 as a promising target by Chao Xu, Litao Liang, Guoqing Liu, Yanzhi Feng, Bin Xu, Deming Zhu, Wenbo Jia, Jinyi Wang, Wenhu Zhao, Xiangyu Ling, Yongping Zhou, Wenzhou Ding, Lianbao Kong

“…We utilized data from The Cancer Genome Atlas (TCGA) and the Gene Expression Omnibus (GEO), applying machine learning algorithms to develop a prognostic model based on ACRRGs’ expression. …”
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The Identification and Validation of a Robust Immune-Associated Gene Signature in Cutaneous Melanoma by Le-Bin Song, Jiao-Chen Luan, Qi-Jie Zhang, Lin Chen, Hao-Yang Wang, Xue-Chen Cao, Ning-Hong Song, Yan Lu

“…Methods. 434 melanoma patients were extracted from The Cancer Genome Atlas (TCGA) database, and 1811 IAGs were downloaded from the ImmPort database in our retrospective study. …”
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Diagnosis of invasive encapsulated follicular variant papillary thyroid carcinoma by protein-based machine learning by Truong Phan-Xuan Nguyen, Minh-Khang Le, Sittiruk Roytrakul, Shanop Shuangshoti, Nakarin Kitkumthorn, Somboon Keelawat

“…Additionally, we analyzed the performance of single-protein/gene receiver operating characteristic in differentiating the invasive encapsulated follicular variant of papillary thyroid carcinoma from others within The Cancer Genome Atlas projects, which yielded an AUC >0.5. …”
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A Narrative Review of Prognostic Gene Signatures in Oral Squamous Cell Carcinoma Using LASSO Cox Regression by Nur Fatinazwa Mohd Faizal, Saptarsi Shai, Bansi P. Savaliya, Lee Peng Karen-Ng, Rupa Kumari, Rahul Kumar, Vui King Vincent-Chong

“…It is essential to distinguish between cancers arising in the head and neck regions due to significant differences in their etiologies, treatment approaches, and prognoses. As the Cancer Genome Atlas (TCGA) dataset is available in HNSCC, the survival analysis prognosis of OSCC patients based on the TCGA dataset for discovering gene expression-based prognostic biomarkers is limited. …”
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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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The lysosome-related characteristics affects the prognosis and tumor microenvironment of lung adenocarcinoma by Wuguang Chang, Wuyou Gao, Yawei Wu, Bin Luo, Lekai Zhong, Leqi Zhong, Wenqian Lin, Zhesheng Wen, Youfang Chen

“…However, there are few studies on lysosome-associated genes (LAGs) in lung adenocarcinoma (LUAD).MethodsBulk RNA-seq of LUAD was downloaded from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO). …”
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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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DOCK4 Is a Platinum-Chemosensitive and Prognostic-Related Biomarker in Ovarian Cancer by Qianqian Zhao, Jie Zhong, Ping Lu, Xiao Feng, Ying Han, Chenqi Ling, Wenke Guo, Weijin Zhou, Fudong Yu

“…The gene expression profiles were obtained from Gene Expression Omnibus (GEO) and The Cancer Genome Atlas (TCGA) database. A total of 4 genes (AP2A2, DOCK4, HSDL2, and PDK4) were the candidate differentially expressed genes (DEGs) of PPAR-TRGs with platinum chemosensitivity. …”
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Development of a Novel Prognostic Model for Lung Adenocarcinoma Utilizing Pyroptosis-Associated LncRNAs by Hong-Yan Bai, Tian-Tian Li, Li-Na Sun, Jing-Hong Zhang, Xiu-He Kang, Yi-Qing Qu

“…This study used genotype-tissue expression (GTEx) and the cancer genome atlas (TCGA) databases to obtain 477 lung adenocarcinoma (LUAD) and 347 healthy individuals’ samples as research subjects and divided LUAD patients into low-risk and high-risk groups based on prognostic risk scores. …”
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Identification of a Robust Five-Gene Risk Model in Prostate Cancer: A Robust Likelihood-Based Survival Analysis by Yutao Wang, Jiaxing Lin, Kexin Yan, Jianfeng Wang

“…We considered 723 samples obtained from TCGA (the Cancer Genome Atlas), GSE46602, and GSE21032. Prostate cancer prognosis-related genes with P<0.05 were selected using Univariable Cox regression analysis. …”
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MAIP1-Related Tumor Immune Infiltration: As a Potential Prognostic Biomarker for Esophageal Cancer by Xiaoyu He, Fu Gan, Yongjian Lin, Guoqing Liu, Yunhua Lin, Dongxu Chen

“…We obtained RNA-seq datasets and corresponding clinical data for EC patients from the Cancer Genome Atlas (TCGA) database via the UCSC Xena browser to extract MAIP1 expression and plot survival curves to determine their prognosis. …”
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