XINRUI SHI¹, XIA GAO¹, WENCONG LIU², XUEJIAO TANG¹, JIAYI LIU¹, DONGCHEN PAN¹, XUEQING DUAN¹, YUQING JIN¹, WEIYAN REN¹, LEI YANG^1,*, WENXUAN LIU^1,*

Oncology Research, Vol.31, No.4, pp. 569-590, 2023, DOI:10.32604/or.2023.028964

Abstract Hepatocellular carcinoma (HCC) is the most common fatal cancer worldwide, patients with HCC have a high mortality rate and poor prognosis. PANoptosis is a novel discovery of programmed cell death associated with cancer development. However, the role of PANoptosis in HCC remains obscure. In this study, we enrolled 274 PANoptosisrelated genes (PANRGs) and screened 8 genes to set up a prognostic model. A previous scoring system calculated PANscore was utilized to quantify the individual risk level of each HCC patient, and the reliability of the prognostic model has been validated in an external cohort. Nomogram constructed with PANscore and clinical… More >

YANGQING HUANG^1,2, XINLAN ZHOU¹, XIUFEN LI¹, DAN HUANG¹, ZHONG FANG^3,*, RONGRONG DING^1,*

Oncology Research, Vol.31, No.2, pp. 193-205, 2023, DOI:10.32604/or.2023.027112

Abstract Sterol o-acyltransferase1 (SOAT1) is an enzyme that regulates lipid metabolism. Nevertheless, the predictive value of SOAT1 regarding immune responses in cancer is not fully understood. Herein, we aimed to expound the predictive value and the potential biological functions of SOAT1 in pan-cancer. Raw data related to SOAT1 expression in 33 different types of cancer were acquired from The Cancer Genome Atlas (TCGA) and Genotype-Tissue Expression (GTEx) databases. SOAT1 expression was significantly increased in most cancers and showed a distinct correlation with prognosis. This enhanced expression of the SOAT1 gene was confirmed by evaluating SOAT1 protein expression using tissue microarrays. In… More >

XI YANG^1,5,#, HUIXIAN WU^2,3,#, CHAO XIONG^4,#, BO ZHAO¹, MEILIAN LIU¹, JIE QIN⁶, MEI DENG^1,2,3,*

BIOCELL, Vol.47, No.5, pp. 1021-1037, 2023, DOI:10.32604/biocell.2023.027103

Abstract Background: Cytochrome b561 (CYB561) plays a critical role in neuroendocrine function, cardiovascular regulation, and tumor growth; however, the prognostic value of CYB561 in patients with breast cancer and the relationship between CYB561 expression and immune infiltration in breast cancer remain unclear. Methods: The mRNA expression and clinical data of patients with breast cancer were obtained from The Cancer Genome Atlas database. Functional enrichment analysis was used to explore underlying biological functions associated with CYB561. The methylation status of CYB561 was analyzed using the MethSurv database. The enrichment score of immune cell infiltration for CYB561 in breast cancer was calculated using… More >

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 >

Xuelian Du^1,#, Hao Shi^2,#, Haiyan Liu¹, Linghua Zhou¹, Anqun Xie¹, Jufang Guo^1,*

Oncologie, Vol.24, No.4, pp. 769-787, 2022, DOI:10.32604/oncologie.2022.026248

Abstract Background: Gestational diabetes mellitus (GDM) affects the health of numerous women around the world. A recent study has shown that GDM is associated with an increased incidence of cancer. In this study, we aimed to explore the possible shared mechanisms and potential common therapeutic targets between GDM and cancer. Methods: The limma package was used to identify differentially expressed genes (DEGs) in GDM. The Cytoscape plugin cytoHubba was used to screen hub genes. The CIBERSORT algorithm was used to explore the correlation between hub genes and immunity. Cox regression analysis was used to assess the relationship between protein tyrosine kinase… More >

JIAMING ZHAN, WEIHUA WANG, YANLEI TANG, NING ZHOU, DAOWEN JIANG^*

BIOCELL, Vol.46, No.12, pp. 2601-2613, 2022, DOI:10.32604/biocell.2022.021300

Abstract Esophageal cancer (EC) was an aggressive malignant neoplasm characterized by high morbidity and poor prognosis. Identifying the changes in DNA damage repair genes helps to better understand the mechanisms of carcinoma progression. In this study, by comparing EC samples and normal samples, we found a total of 132 DDR expression with a significant difference. Moreover, we revealed higher expression of POLN, PALB2, ATM, PER1, TOP3B and lower expression of HMGB1, UBE2B were correlated to longer OS in EC. In addition, a prognostic risk score based on 7 DDR gene expression (POLN, HMGB1, TOP3B, PER1, UBE2B, ATM, PALB2) was constructed for… More >

WEI LIANG^1,2,*, QIANG LUO^1,2,#, ZONGWEI ZHANG^1,2,#, KEJU YANG^1,2,3, ANKANG YANG^1,2, QINGJIA CHI⁴, HUAN HU⁵

BIOCELL, Vol.46, No.8, pp. 1989-2002, 2022, DOI:10.32604/biocell.2022.019300

Abstract Diabetic nephropathy (DN) is a common microvascular complication that easily leads to end-stage renal disease. It is important to explore the key biomarkers and molecular mechanisms relevant to diabetic nephropathy (DN). We used highthroughput RNA sequencing to obtain the genes related to DN glomerular tissues and healthy glomerular tissues of mice. Then we used LIMMA to analyze differentially expressed genes (DEGs) between DN and non-diabetic glomerular samples. And we performed KEGG, gene ontology functional (GO) enrichment, and gene set enrichment analysis to reveal the signaling pathway of the disease. The CIBERSORT algorithm based on support vector machine was used to… More >

JUNXIA LIU¹, KE PANG², FEI HE^2,*

BIOCELL, Vol.46, No.7, pp. 1661-1673, 2022, DOI:10.32604/biocell.2022.018023

Abstract Breast cancer is one of the most common cancers in the world and seriously threatens the health of women worldwide. Prognostic models based on immune-related genes help to improve the prognosis prediction and clinical treatment of breast cancer patients. In the study, we used weighted gene co-expression network analysis to construct a co-expression network to screen out highly prognostic immune-related genes. Subsequently, the prognostic immune-related gene signature was successfully constructed from highly immune-related genes through COX regression and LASSO COX analysis. Survival analysis and time receiver operating characteristic curves indicate that the prognostic signature has strong predictive performance. And we… More >

LU YANG^1,#, YUN LIU^1,#, BOKE ZHANG², MENGSI YU³, FEN HUANG¹, YANG WEN¹, JIANGZHENG ZENG¹, YANDA LU¹, CHANGCHENG YANG¹

BIOCELL, Vol.46, No.5, pp. 1215-1243, 2022, DOI:10.32604/biocell.2022.018221

Abstract The aim of this study was to reveal genes associated with breast cancer metastasis, to investigate their intrinsic relationship with immune cell infiltration in the tumor microenvironment, and to screen for prognostic biomarkers. Gene expression data of breast cancer patients and their metastases were downloaded from the GEO, TCGA database. R language package was used to screen for differentially expressed genes, enrichment analysis of genes, PPI network construction, and also to elucidate key genes for diagnostic and prognostic survival. Spearman’s r correlation was used to analyze the correlation between key genes and infiltrating immune cells. We screened 25 hub genes,… More >

YONGHUI YU^1,#, SONGHUI XU^2,#, ERYONG ZHAO^3,#, YONGSHUN DONG¹, JINBIN CHEN¹, BOQI RAO¹, JIE ZENG⁴, LEI YANG¹, JIACHUN LU¹, FUMAN QIU^1,4,*

BIOCELL, Vol.46, No.4, pp. 999-1011, 2022, DOI:10.32604/biocell.2022.017004

Abstract The outcomes of ovarian cancer are complicated and usually unfavorable due to their diagnoses at a late stage. Identifying the efficient prognostic biomarkers to improve the survival of ovarian cancer is urgently warranted. The survival-related pseudogenes retrieved from the Cancer Genome Atlas database were screened by univariate Cox regression analysis and further assessed by least absolute shrinkage and selection operator (LASSO) method. A risk score model based on the prognostic pseudogenes was also constructed. The pseudogene-mRNA regulatory networks were established using correlation analysis, and their potent roles in the ovarian cancer progression were uncovered by functional enrichment analysis. Lastly, ssGSEA… More >