ZHEN WANG¹, JUN FU¹, SAISAI ZHU¹, HAODONG TANG², KUI SHI¹, JIHUA YANG³, MENG WANG³, MENGGE WU¹, DUNFENG QI^1,*

Oncology Research, Vol.32, No.12, pp. 1851-1866, 2024, DOI:10.32604/or.2024.055286 - 13 November 2024

Abstract Background: Pancreatic ductal adenocarcinoma (PDAC) has a rich and complex tumor immune microenvironment (TIME). M2 macrophages are among the most extensively infiltrated immune cells in the TIME and are necessary for the growth and migration of cancers. However, the mechanisms and targets mediating M2 macrophage infiltration in pancreatic cancer remain elusive. Methods: The M2 macrophage infiltration score of patients was assessed using the xCell algorithm. Using weighted gene co-expression network analysis (WGCNA), module genes associated with M2 macrophages were identified, and a predictive model was designed. The variations in immunological cell patterns, cancer mutations, and… More > Graphic Abstract

Kaiyue Hong, Yasmina Radani, Teja Manda, Jinhui Chen, Liming Yang^*

Phyton-International Journal of Experimental Botany, Vol.93, No.3, pp. 413-425, 2024, DOI:10.32604/phyton.2024.047739 - 28 March 2024

Abstract This study explores CAMTA genes in the rare and endangered Chinese plant species, Liriodendron chinense. Despite the completion of whole-genome sequencing, the roles of CAMTA genes in calcium regulation and stress responses in this species remain largely unexplored. Within the L. chinense genome, we identified two CAMTA genes, Lchi09764 and Lchi222536, characterized by four functional domains: CG-1, TIG, ANK repeats, and IQ motifs. Our analyses, including phylogenetic investigations, cis-regulatory element analyses, and chromosomal location studies, aim to elucidate the defining features of CAMTA genes in L. chinense. Applying Weighted Gene Co-Expression Network Analysis (WGCNA), we explored the impact of CAMTA genes on More >

HENG LI^1,#, YOUMING LEI^3,#, GAOFENG LI¹, YUNCHAO HUANG^2,*

Oncology Research, Vol.32, No.1, pp. 187-197, 2024, DOI:10.32604/or.2023.030656 - 15 November 2023

Abstract Lung cancer is a prevalent malignancy, and fatalities of the disease exceed 400,000 cases worldwide. Lung squamous cell carcinoma (LUSC) has been recognized as the most common pathological form of lung cancer. The comprehensive understanding of molecular features related to LUSC progression has great significance in LUSC prognosis assessment and clinical management. In this study, we aim to identify a panel of signature genes closely associated with LUSC, which can provide novel insights into the progression of LUSC. Gene expression profiles were retrieved from public resources including gene expression omnibus (GEO) and the cancer genome… More >

JINFANG HU^1,#, JIANGEN AO^2,#, LONGSHENG FU^1,#, YAOQI WU¹, FENG SHAO³, TIANTIAN XU¹, MINGJIN JIANG⁴, SHAOFENG XIONG¹, YANNI LV^1,*

BIOCELL, Vol.47, No.7, pp. 1611-1622, 2023, DOI:10.32604/biocell.2023.028684 - 21 June 2023

Abstract Background: The attenuation function of Dalbergia odorifera leaves on cerebral ischemia-reperfusion (I/R) is little known. The candidate targets for the Chinese herb were extracted from brain tissues through the high-affinity chromatography. The molecular mechanism of D. odorifera leaves on cerebral I/R was investigated. Methods: Serial affinity chromatography based on D. odorifera leaves extract (DLE) affinity matrices were applied to find specific binding proteins in the brain tissues implemented on C57BL/6 mice by intraluminal middle cerebral artery occlusion for 1 h and reperfusion for 24 h. Specific binding proteins were subjected to mass-spectrometry to search for the differentially expressed… More >

JUNXIA LIU¹, KE PANG², FEI HE^2,*

BIOCELL, Vol.46, No.7, pp. 1661-1673, 2022, DOI:10.32604/biocell.2022.018023 - 17 March 2022

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 More >

HAN ZHAO¹, JING GUO¹, QINGJIA CHI², MENG FANG^1,*

BIOCELL, Vol.46, No.5, pp. 1245-1259, 2022, DOI:10.32604/biocell.2022.018117 - 06 January 2022

Abstract Hepatocellular carcinoma (HCC) is a worldwide malignant tumor that caused irreversible consequences. Tanshinone IIA has been shown to play a notable role in HCC treatment. However, the potential targets and associating mechanism of Tanshinone IIA against HCC remain unknown. We first screened out 105 overlapping genes by integrating the predicted targets of Tanshinone IIA from multiple databases and the differentially expressed genes of HCC from the Cancer Genome Atlas (TCGA) database. Then, we performed weighted gene co-expression network analysis (WGCNA) using the RNA-seq profiles of overlapping genes and HCC-related clinical information. 23 genes related to… More >

MENG FANG¹, JING GUO¹, HAIPING WANG¹, ZICHANG YANG², HAN ZHAO^1,*, QINGJIA CHI²

BIOCELL, Vol.46, No.2, pp. 401-415, 2022, DOI:10.32604/biocell.2022.016989 - 20 October 2021

Abstract Hepatocellular carcinoma (HCC) is a common immunogenic malignant tumor. Although the new strategies of immunotherapy and targeted therapy have made considerable progress in the treatment of HCC, the 5-year survival rate of patients is still very low. The identification of new prognostic signatures and the exploration of the immune microenvironment are crucial to the optimization and improvement of molecular therapy strategies. We studied the potential clinical benefits of the inflammation regulator miR-93-3p and mined its target genes. Weighted gene co-expression network analysis (WGCNA), univariate and multivariate COX regression and the LASSO COX algorithm are employed… More >

MENGYI TANG^1,2,3,4,#, BOWEN YANG^1,2,3,4,#, CHUANG ZHANG^1,2,3,4, CHAOXU ZHANG^1,2,3,4, DAN ZANG^1,2,3,4, LIBAO GONG^1,2,3,4, YUNPENG LIU^1,2,3,4, ZHI LI^1,2,3,4,*, XIUJUAN QU^1,2,3,4,*

BIOCELL, Vol.45, No.4, pp. 911-921, 2021, DOI:10.32604/biocell.2021.010119 - 22 April 2021

Abstract Distal gastric cancer (DGC) is a subgroup of gastric cancer (GC), which has different molecular characteristics from proximal gastric cancer (PGC). These differences result in different overall survival (OS) rates; however, data pertaining to the survival rate in PGC or DGC are contradictory. This suggests that the location of GC is not the unique cause of the different survival rates, while the molecular characteristics might be more important factors determining the prognosis of DGC. Therefore, the aim of this study was to discover key prognostic factors in DGC using bioinformatic methods and to explore the… More >

Xingliang Feng^*1, Meng Zhang^*†1, Jialin Meng^*, Yongqiang Wang^†, Yi Liu^*, Chaozhao Liang^*, Song Fan^*

Oncology Research, Vol.28, No.3, pp. 285-297, 2020, DOI:10.3727/096504020X15791676105394

Abstract We aimed to investigate the potential mechanisms of progression and identify novel prognosis-related biomarkers for papillary renal cell carcinoma (PRCC) patients. The related data were derived from The Cancer Genome Atlas (TCGA) and then analyzed by weighted gene coexpression network analysis (WGCNA). The correlation between each module and the clinical traits were analyzed by Pearson’s correlation analysis. Pathway analysis was conducted to reveal potential mechanisms. Hub genes within each module were screened by intramodule analysis, and visualized by Cytoscape software. Furthermore, important hub genes were validated in an external dataset and clinical samples. A total… More >

Pihua Han^*†1, Haiming Yang^‡1, Xiang Li^*1, Jie Wu^*, Peili Wang^§, Dapeng Liu^*, Guodong Xiao^¶, Xin Sun^*, Hong Ren^*

Oncology Research, Vol.28, No.7-8, pp. 715-729, 2020, DOI:10.3727/096504020X16037124605559

Abstract The aim of this study was to identify a novel cancer stemness-related ceRNA regulatory axis in lung adenocarcinoma (LUAD) via weighted gene coexpression network analysis of a stemness index. The RNA sequencing expression profiles of 513 cancer samples and 60 normal samples were obtained from the TCGA database. Differentially expressed mRNAs (DEmRNAs), lncRNAs (DElncRNAs), and miRNAs (DEmiRNAs) were identified with R software. Functional enrichment analysis was conducted using DAVID 6.8. The ceRNA network was constructed via multiple bioinformatics analyses, and the correlations between possible ceRNAs and prognosis were analyzed using Kaplan–Meier plots. WGCNA was then… More >