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Search Results (13)
  • Open Access

    REVIEW

    Identification of a three-gene signature in the triple-negative breast cancer

    LIPING WANG1,2, ZHOU LUO1, MINMIN SUN3, QIUYUE YUAN4, YINGGANG ZOU5, DEYUAN FU1,*

    BIOCELL, Vol.46, No.3, pp. 595-606, 2022, DOI:10.32604/biocell.2022.017337 - 18 November 2021

    Abstract This work aimed to improve current prognostic signatures based on clinical stages in identifying high-risk patients of triple-negative breast cancer (TNBC), to allow patients with a high-risk score for specific treatment decisions. In this study, 396 TNBC samples from TCGA and GEO databases were included in genome-wide transcriptome analysis. The relationship between normalized gene expression values and survival data of patients was determined by Cox proportional hazards models in each dataset. The overlapped genes among all datasets were considered as a potential prognostic signature. The risk score was constructed based on individual genes and validated… More >

  • Open Access

    ARTICLE

    WGCNA and LASSO algorithm constructed an immune infiltration-related 5-gene signature and nomogram to improve prognosis prediction of hepatocellular carcinoma

    MENG FANG1, JING GUO1, HAIPING WANG1, ZICHANG YANG2, HAN ZHAO1,*, 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 >

  • Open Access

    ARTICLE

    A novel nine gene signature integrates stemness characteristics associated with prognosis in hepatocellular carcinoma

    XINGHONG YAO1,2,#, CHENGQUAN LU3,#, JUNYI SHEN1, WENLI JIANG1, YAN QIU1, YE ZENG1,*, LIANG LI1,*

    BIOCELL, Vol.45, No.6, pp. 1425-1448, 2021, DOI:10.32604/biocell.2021.017289 - 01 September 2021

    Abstract Cancer stem cells (CSCs) are heterogeneous with self-renewal and differentiation ability. The mRNA expression-based stemness index (mRNAsi) described the similarity between tumor cells and CSCs, which is positively associated with the poor prognosis of cancer patients. However, the key prognostic genes related to mRNAsi in hepatocellular carcinoma (HCC) remains unclear. A 9-gene signature related to mRNAsi and HCC prognosis including PSMG3, SNRPD1, DTYMK, PIGU, NME1, TXNL4A, IPO4, PES1, and REXO4 was obtained. High expression of this signature indicates poor prognosis of HCC. PIGU was an independent prognostic factor of HCC, which was significantly associated with progression of… More >

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