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  • Open Access

    ARTICLE

    A Machine-Learning Prognostic Model for Colorectal Cancer Using a Complement-Related Risk Signature

    Jun Li1, Kangmin Yu1, Zhiyong Chen1, Dan Xing2, Binshan Zha1, Wentao Xie1, Huan Ouyang1, Changjun Yu3,*

    Oncology Research, Vol.33, No.11, pp. 3469-3492, 2025, DOI:10.32604/or.2025.066193 - 22 October 2025

    Abstract Objectives: Colorectal cancer (CRC) remains a major contributor to global cancer mortality, ranking second worldwide for cancer-related deaths in 2022, and is characterized by marked heterogeneity in prognosis and therapeutic response. We sought to construct a machine-learning prognostic model based on a complement-related risk signature (CRRS) and to situate this signature within the CRC immune microenvironment. Methods: Transcriptomic profiles with matched clinical annotations from TCGA and GEO CRC cohorts were analyzed. Prognostic CRRS genes were screened using Cox proportional hazards modeling alongside machine-learning procedures. A random survival forest (RSF) predictor was trained and externally validated.… More >

  • Open Access

    ARTICLE

    Identification of a 10-pseudogenes signature as a novel prognosis biomarker for ovarian cancer

    YONGHUI YU1,#, SONGHUI XU2,#, ERYONG ZHAO3,#, YONGSHUN DONG1, JINBIN CHEN1, BOQI RAO1, JIE ZENG4, LEI YANG1, JIACHUN LU1, FUMAN QIU1,4,*

    BIOCELL, Vol.46, No.4, pp. 999-1011, 2022, DOI:10.32604/biocell.2022.017004 - 15 December 2021

    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… More >

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