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Search Results (11)
  • Open Access

    ARTICLE

    A novel oxaliplatin-resistant gene signatures predicting survival of patients in colorectal cancer

    QIOU GU1, CHUILIN LAI1, XIAO GUAN1, JING ZHU2, TIAN ZHAN1, JIANPING ZHANG1,*

    BIOCELL, Vol.48, No.2, pp. 253-269, 2024, DOI:10.32604/biocell.2023.028336

    Abstract Objectives: Colorectal cancer (CRC) is a serious threat to human health worldwide. Oxaliplatin is a platinum analog and is widely used to treat CRC. However, resistance to oxaliplatin restricts its effectiveness and application while its target recognition and mechanism of action also remain unclear. Therefore, we aimed to develop an oxaliplatin-resistant prognostic model to clarify these aspects. Methods: We first obtained oxaliplatin-resistant and parental cell lines, and identified oxaliplatin-resistant genes using RNA sequencing (RNA-seq) and differential gene analysis. We then acquired relevant data from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. Cox regression and Least Absolute… More > Graphic Abstract

    A novel oxaliplatin-resistant gene signatures predicting survival of patients in colorectal cancer

  • Open Access

    ARTICLE

    M2 macrophages predicted the prognosis of breast cancer by combing a novel immune cell signature and promoted cell migration and invasion of cancer cells in vitro

    QI XIA1, XING CHEN2, QINGHUA MA3, XIANXIU WEN2,*

    BIOCELL, Vol.48, No.2, pp. 217-228, 2024, DOI:10.32604/biocell.2023.027414

    Abstract Background: Breast cancer (BC) is the most common cancer and the leading cause of cancer death in women. Immune features play an important role in improving the prognosis prediction of BC. However, while previous immune signatures consisted mainly of immune genes, immune cell-based signatures have been rarely reported. Methods: In this study, we report that a novel immune cell signature is effective in improving prognostic prediction by combining M2 macrophages. We identified 17 differentially infiltrating immune cells between cancer and normal groups. Prognostic features of the four immune cells identified by LASSO COX analysis showed good performance for survival risk… More >

  • Open Access

    ARTICLE

    Comprehensive bioinformatics analysis and experimental validation: An anoikis-related gene prognostic model for targeted drug development in head and neck squamous cell carcinoma

    LIN QIU1,#, ANQI TAO1,#, XIAOQIAN SUN4,5, FEI LIU1, XIANPENG GE2,3,*, CUIYING LI1,*

    Oncology Research, Vol.31, No.5, pp. 715-752, 2023, DOI:10.32604/or.2023.029443

    Abstract We analyzed RNA-sequencing (RNA-seq) and clinical data from head and neck squamous cell carcinoma (HNSCC) patients in The Cancer Genome Atlas (TCGA) Genomic Data Commons (GDC) portal to investigate the prognostic value of anoikis-related genes (ARGs) in HNSCC and develop new targeted drugs. Differentially expressed ARGs were screened using bioinformatics methods; subsequently, a prognostic model including three ARGs (CDKN2A, BIRC5, and PLAU) was constructed. Our results showed that the model-based risk score was a good prognostic indicator, and the potential of the three ARGs in HNSCC prognosis was validated by the TISCH database, the model’s accuracy was validated in two… More >

  • Open Access

    ARTICLE

    Immunogenic cell death-related long noncoding RNA influences immunotherapy against lung adenocarcinoma

    DONGJIE SUN1,2, CHI ZHANG3,*

    Oncology Research, Vol.31, No.5, pp. 753-767, 2023, DOI:10.32604/or.2023.029287

    Abstract Lung adenocarcinoma (LUAD) is the leading cause of cancer-related deaths, accounting for over a million deaths worldwide annually. Immunogenic cell death (ICD) elicits an adaptive immune response. However, the role of ICD-related long noncoding RNAs (lncRNAs) in LUAD is unknown. In this study, we investigated the characteristics of the tumor microenvironment in LUAD, the prognostic significance of ICD-related lncRNAs, and the half-maximal inhibitory concentration (IC50) of possible chemotherapeutic drugs. We sorted prognostic lncRNAs using univariate Cox regression and constructed a risk signature based on them. We then confirmed the model’s accuracy and generated a nomogram. Additionally, we performed immune microenvironment… More > Graphic Abstract

    Immunogenic cell death-related long noncoding RNA influences immunotherapy against lung adenocarcinoma

  • Open Access

    ARTICLE

    System analysis based on the T cell exhaustion‑related genes identifies CD38 as a novel therapy target for ovarian cancer

    TIANMING SHI1,2,#, RONGRONG YAN1,2,#, MI HAN1,2,*

    Oncology Research, Vol.31, No.4, pp. 591-604, 2023, DOI:10.32604/or.2023.029282

    Abstract Ovarian cancer (OV) is highly heterogeneous tumor with a very poor prognosis. Studies increasingly show that T cell exhaustion is prognostically relevant in OV. The aim of this study was to dissect the heterogeneity of T cell subclusters in OV through single cell transcriptomic analysis. The single RNA-sequencing (scRNA-seq) data of five OV patients were analyzed, and six major cell clusters were identified after threshold screening. Further clustering of T cell-associated clusters revealed four subtypes. Pathways related to oxidative phosphorylation, G2M checkpoint, JAK-STAT and MAPK signaling were significantly activated, while the p53 pathway was inhibited in the CD8+ exhausted T… More > Graphic Abstract

    System analysis based on the T cell exhaustion‑related genes identifies CD38 as a novel therapy target for ovarian cancer

  • Open Access

    ARTICLE

    An inflammatory-related genes signature based model for prognosis prediction in breast cancer

    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

    An inflammatory-related genes signature based model for prognosis prediction in breast cancer

  • Open Access

    ARTICLE

    A Metabolism-Related Gene Signature Predicts the Prognosis of Breast Cancer Patients: Combined Analysis of High-Throughput Sequencing and Gene Chip Data Sets

    Lei Hu1,2,#, Meng Chen2,3,#, Haiming Dai2,3,4, Hongzhi Wang2,3,4,*, Wulin Yang2,3,4,*

    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 >

  • Open Access

    ARTICLE

    Prognostic model for prostate cancer based on glycolysis-related genes and non-negative matrix factorization analysis

    ZECHAO LU1,#, FUCAI TANG1,#, HAOBIN ZHOU2,#, ZEGUANG LU3,#, WANYAN CAI4,#, JIAHAO ZHANG5, ZHICHENG TANG6, YONGCHANG LAI1,*, ZHAOHUI HE1,*

    BIOCELL, Vol.47, No.2, pp. 339-350, 2023, DOI:10.32604/biocell.2023.023750

    Abstract Background: Establishing an appropriate prognostic model for PCa is essential for its effective treatment. Glycolysis is a vital energy-harvesting mechanism for tumors. Developing a prognostic model for PCa based on glycolysis-related genes is novel and has great potential. Methods: First, gene expression and clinical data of PCa patients were downloaded from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO), and glycolysis-related genes were obtained from the Molecular Signatures Database (MSigDB). Gene enrichment analysis was performed to verify that glycolysis functions were enriched in the genes we obtained, which were used in non-negative matrix factorization (NMF) to identify clusters.… More >

  • Open Access

    ARTICLE

    Weighted gene co-expression network analysis identifies a novel immune-related gene signature and nomogram to predict the survival and immune infiltration status of breast cancer

    JUNXIA LIU1, KE PANG2, FEI HE2,*

    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 >

  • Open Access

    ARTICLE

    Construction and validation of prognostic model based on autophagy-related lncRNAs in gastric cancer

    MENGQIU CHENG1,2, WEI CAO2, GUODONG CAO1, XIN XU1,2,*, BO CHEN1,*

    BIOCELL, Vol.46, No.1, pp. 97-109, 2022, DOI:10.32604/biocell.2021.015608

    Abstract Gastric cancer (GC) is one of the most common cancer worldwide. Although emerging evidence indicates that autophagy-related long non-coding RNA (lncRNA) plays an important role in the progression of GC, the prognosis of GC based on autophagy is still deficient. The Cancer Genome of Atlas stomach adenocarcinoma (TCGA-STAD) dataset was downloaded and separated into a training set and a testing set randomly. Then, 24 autophagy-related lncRNAs were found strongly associated with the survival of the TCGA-STAD dataset. 11 lncRNAs were selected to build the risk score model through the least absolute shrinkage and selection operator (LASSO) regression. Every patient got… More >

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