CHENG-GONG LUO^1,2,#, JIAO ZHANG^1,#, YUN-ZHAO AN¹, XUAN LIU¹, SHUAI-JIE LI¹, WEI ZHANG¹, KAI LI¹, XU ZHAO¹, DONG-BO YUAN¹, LING-YUE AN¹, WEI CHEN², YE TIAN^1,*, BIN XU^1,*

BIOCELL, Vol.48, No.5, pp. 771-792, 2024, DOI:10.32604/biocell.2024.048878

Abstract Background: Ferroptosis, a lipid peroxidation-mediated programmed cell death, is closely linked to tumor development, including prostate cancer (PCa). Despite established connections between ferroptosis and PCa, a comprehensive investigation is essential for understanding its impact on patient prognosis. Methods: A risk model incorporating four ferroptosis-related genes was developed and validated. Elevated risk scores correlated with an increased likelihood of biochemical recurrence (BCR), diminished immune infiltration, and adverse clinicopathological characteristics. To corroborate these results, we performed validation analyses utilizing datasets from both the Cancer Genome Atlas Cohort (TCGA) and the Gene Expression Synthesis Cohort (GEO). Moreover, we conducted further investigations into the… More >

ZHENHUA LI¹, HUILAI LV¹, FAN ZHANG¹, ZIMING ZHU², QIANG GUO³, MINGBO WANG¹, CHAO HUANG¹, LIJUAN CHEN⁴, WENPAN ZHANG⁴, YUN LI^5,*, ZIQIANG TIAN^1,*

BIOCELL, Vol.48, No.1, pp. 123-138, 2024, DOI:10.32604/biocell.2023.031568

Abstract Introduction: DNA polymerases are crucial for maintaining genome stability and influencing tumorigenesis. However, the clinical implications of DNA polymerases in tumorigenesis and their potential as anti-cancer therapy targets are not well understood. Methods: We conducted a systematic analysis using TCGA Pan-Cancer Atlas data and Gene Set Cancer Analysis results to examine the expression profiles of 15 DNA polymerases (POLYs) and their clinical correlations. We also evaluated the prognostic value of POLYs by analyzing their expression levels in relation to overall survival time (OS) using Kaplan-Meier survival curves. Additionally, we investigated the correlations between POLY expression and immune cells, DNA damage… More >

JINGYUE FU, RUI CHEN, ZHIZHENG ZHANG, JIANYI ZHAO, TIANSONG XIA^*

Oncology Research, Vol.31, No.2, pp. 157-167, 2023, DOI:10.32604/or.2023.027972

Abstract Background: Breast cancer has become the most common malignant tumor in the world. It is vital to discover novel prognostic biomarkers despite the fact that the majority of breast cancer patients have a good prognosis because of the high heterogeneity of breast cancer, which causes the disparity in prognosis. Recently, inflammatory-related genes have been proven to play an important role in the development and progression of breast cancer, so we set out to investigate the predictive usefulness of inflammatory-related genes in breast malignancies. Methods: We assessed the connection between Inflammatory-Related Genes (IRGs) and breast cancer by studying the TCGA database.… More > Graphic Abstract

HAOTONG SUN^1,2, HEYING WANG^1,3, XIN LI^1,2, YANJIE HAO^1,2, JUN LING^1,2, HUAN WANG^1,2, FEIMIAO WANG^1,2, FANG XU^1,2,*

BIOCELL, Vol.47, No.3, pp. 607-618, 2023, DOI:10.32604/biocell.2023.026445

Abstract Background: Colon adenocarcinoma (COAD) is the second leading cause of cancer death worldwide thus, identification of COAD biomarkers is critical. Mitotic Arrest Deficient 2 Like 2 (MAD2L2) is a key factor in mammalian DNA damage repair and is highly expressed in many malignant tumors. This is a comprehensive study of MAD2L2 expression, its diagnostic value, prognostic analysis, potential biological function, and impact on the immune system of patients with COAD. Methods: Gene expression, clinical relevance, prognostic analysis, diagnostic value, GO/KEGG cluster analysis, data obtained from TCGA, and bioinformatics statistical analysis were performed using the R package. Immune responses to MAD2L2… More >

Hua Yang^*

Oncologie, Vol.24, No.4, pp. 835-863, 2022, DOI:10.32604/oncologie.2022.026447

Abstract Background: Epithelial ovarian cancer (EOC) is the deadliest malignancy among the gynecologic tumors, and ovarian serous cystadenocarcinoma (OV) is the dominant histological type. Ferroptosis is a novel iron-dependent, programmed form of cell death, and agents that trigger ferroptosis may constitute potential anti-cancer therapies. Materials and Methods: We herein extracted the genes that participate in the process of ferroptosis from the online FerrDb database to create a ferroptosis-related genome (FRG), and then comprehensively analyzed the relationship between the mRNA expression of each gene and the clinicopathologic features of The Cancer Genome Atlas (TCGA)-OV cohort. Results: We found that most of the… More >

Lei Hu^1,2,#, Meng Chen^2,3,#, Haiming Dai^2,3,4, Hongzhi Wang^2,3,4,*, Wulin Yang^2,3,4,*

Oncologie, Vol.24, No.4, pp. 803-822, 2022, DOI:10.32604/oncologie.2022.026419

Abstract Background and Aim: Hundreds of consistently altered metabolic genes have been identified in breast cancer (BC), but their prognostic value remains to be explored. Therefore, we aimed to build a prediction model based on metabolism-related genes (MRGs) to guide BC prognosis. Methods: Current work focuses on constructing a novel MRGs signature to predict the prognosis of BC patients using MRGs derived from the Virtual Metabolic Human (VMH) database, and expression profiles and clinicopathological data from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. Results: The 3-MRGs-signature constructed by SERPINA1, QPRT and PXDNL was found to be an… More >

Dayu Tian¹, Yang Shi¹, Li Lei¹, Xiangmin Qiu¹, Tao Song^2,*, Qianyin Li^1,*

Oncologie, Vol.24, No.2, pp. 261-282, 2022, DOI:10.32604/oncologie.2022.022838

Abstract Background: Six2, a transcription factor, exerts an oncogenic role in clear cell renal cell carcinoma (ccRCC). Increased Six2 expression could enhance cancer metastasis. However, the regulatory mechanism of Six2 in promoting metastasis remains unclear. The purpose of this study is to analyze the regulatory pattern of Six2 and the potential role of Six2 in the tumor immune microenvironment. Materials and Methods: Firstly, transcriptional data in TCGA-KIRC cohorts was used to analyze the relationship between Six2 expression and clinical information. Secondly, we detect the association between Six2 and the tumor immune microenvironment in ccRCC. Then, we analyzed Six2-related differentially expressed genes… More >

Bo Ling, Zuliang Huang, Suoyi Huang, Li Qian, Genliang Li, Qianli Tang

Oncology Research, Vol.28, No.6, pp. 561-578, 2020, DOI:10.3727/096504020X15907428281601

Abstract There is growing evidence on the clinical significance of tumor microenvironment (TME) cells in predicting prognosis and therapeutic effects. However, cell interactions in tumor microenvironments have not been thoroughly studied or systematically analyzed so far. In this study, 22 immune cell components in the lung adenocarcinoma (LUAD) TME were analyzed using gene expression profile from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO). The TME-based molecular subtypes of LUAD were defined to evaluate further the relationship between molecular subtypes, prognosis, and clinical characteristics. A TME risk score model was constructed by using the differentially expressed genes (DEGs) of… More >

Dong Yan^1,#, Chunxiao Li^2,#, Yantong Zhou², Xue Yan¹, Weihua Zhi¹, Haili Qian^2,*, Yue Han^1,*

Oncologie, Vol.24, No.1, pp. 101-111, 2022, DOI:10.32604/oncologie.2022.020357

Abstract Hepatocellular carcinoma (HCC) is one of the most deadly types of cancer. Sorafenib is currently the only available first-line molecular targeted drug approved by the FDA for HCC. However, primary and secondary resistance is often encountered with treatment with sorafenib. Genomic alterations found in HCC represent potential targets to develop new drugs or new combinational strategies against this type of cancer. Here we analyzed genomic alterations from the TCGA database of HCC samples and the corresponding targeted drugs available to the clinic to identify candidate drugs that might hold promise when used in combination with sorafenib. Our results revealed that… More >

Beifen Dai^1,#, Zhihao Xu^2,#, Hongjue Li³, Bo Wang³, Jinsong Cai¹, Xiaomo Liu^4,*

Oncologie, Vol.24, No.1, pp. 113-130, 2022, DOI:10.32604/oncologie.2022.020259

Abstract Large-scale genomic studies are important ways to comprehensively decode the human genomics, and provide valuable insights to human disease causalities and phenotype developments. Genomic studies are in need of high throughput bioinformatics analyses to harness and integrate such big data. It is in this overarching context that artificial intelligence (AI) offers enormous potentials to advance genomic studies. However, racial bias is always an important issue in the data. It is usually due to the accumulation process of the dataset that inevitability involved diverse subjects with different races. How can race bias affect the outcomes of AI methods? In this work,… More >