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Sökning: WFRF:(Huang WK)

  • Resultat 11-20 av 39
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11.
  • Kanai, M, et al. (författare)
  • 2023
  • swepub:Mat__t
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  • Chang, PH, et al. (författare)
  • The Prognostic Roles of Pretreatment Circulating Tumor Cells, Circulating Cancer Stem-Like Cells, and Programmed Cell Death-1 Expression on Peripheral Lymphocytes in Patients with Initially Unresectable, Recurrent or Metastatic Head and Neck Cancer: An Exploratory Study of Three Biomarkers in One-time Blood Drawing
  • 2019
  • Ingår i: Cancers. - : MDPI AG. - 2072-6694. ; 11:4
  • Tidskriftsartikel (refereegranskat)abstract
    • Circulating tumor cells (CTCs) and immune status are strongly related to cancer prognosis, although few studies have examined both factors. This prospective observational study (ClinicalTrials.gov: NCT02420600) evaluated whether CTCs, circulating cancer stem-like cells (cCSCs), and peripheral lymphocytes with/without Programmed cell death protein 1 (PD-1) expression were associated with prognosis among patients receiving palliative chemotherapy for initially unresectable, recurrent/metastatic head and neck squamous cell carcinoma (rmHNSCC). Thirty-four patients were enrolled between January 2015 and June 2016. Overall survival (OS) was associated with a higher CTC number (hazard ratio [HR]: 1.01, p = 0.0004) and cCSC ratio (HR: 29.903, p < 0.0001). Progression-free survival (PFS) was also associated with CTC number (HR: 1.013, p = 0.002) and cCSC ratio (HR: 10.92, p = 0.003). A CD8+ proportion of ≥ 17% was associated with improved OS (HR: 0.242, p = 0.004). A CD4: CD8 ratio of >1.2 was associated with poorer trend of PFS (HR: 2.12, p = 0.064). PD-1 expression was not associated with survival outcomes. Baseline CTCs, cCSC ratio, and CD8+ ratio may predict prognosis in rmHNSCC.
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  • Chen, Y, et al. (författare)
  • Follicular Helper T-Cell-Based Classification of Endometrial Cancer Promotes Precise Checkpoint Immunotherapy and Provides Prognostic Stratification
  • 2022
  • Ingår i: Frontiers in immunology. - : Frontiers Media SA. - 1664-3224. ; 12, s. 788959-
  • Tidskriftsartikel (refereegranskat)abstract
    • Despite the fact that management of EC is moving towards four TCGA-based molecular classifications, a pronounced variation in immune response among these molecular subtypes limits its clinical use. We aimed to investigate the determinant biomarker of ICI response in endometrial cancer (EC). We characterized transcriptome signatures associated with tumor immune microenvironment in EC. Two immune infiltration signatures were identified from the TCGA database (n = 520). The high- and low-infiltration clusters were compared for differences in patient clinical characteristics, genomic features, and immune cell transcription signatures for ICI prediction. A Lasso Cox regression model was applied to construct a prognostic gene signature. Time-dependent receiver operating characteristic curve, Kaplan–Meier curve, nomogram, and decision curve analyses were used to assess the prediction capacity. The efficacy of potential biomarker was validated by the Karolinska endometrial cancer cohort (n = 260). Immune signature profiling suggested that T follicular helper–like cells (Tfh) may be an important and favorable factor for EC; high Tfh infiltration showed potential for clinical use in the anti-PD-1 treatment. A Tfh Infiltration Risk Model (TIRM) established using eight genes was validated, and it outperformed the Immune Infiltration Risk Model. The TIRM had a stable prognostic value in combination with clinical risk factors and could be considered as a valuable tool in a clinical prediction model. We identified CRABP1 as an individual poor prognostic factor in EC. The Tfh-based classification distinguishes immune characteristics and predicts ICI efficacy. A nomogram based on Tfh-related risk score accurately predicted the prognosis of patients with EC, demonstrating superior performance to TCGA-based classification.
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  • Dareng, EO, et al. (författare)
  • Polygenic risk modeling for prediction of epithelial ovarian cancer risk
  • 2022
  • Ingår i: European journal of human genetics : EJHG. - : Springer Science and Business Media LLC. - 1476-5438 .- 1018-4813. ; 30:3, s. 349-362
  • Tidskriftsartikel (refereegranskat)abstract
    • Polygenic risk scores (PRS) for epithelial ovarian cancer (EOC) have the potential to improve risk stratification. Joint estimation of Single Nucleotide Polymorphism (SNP) effects in models could improve predictive performance over standard approaches of PRS construction. Here, we implemented computationally efficient, penalized, logistic regression models (lasso, elastic net, stepwise) to individual level genotype data and a Bayesian framework with continuous shrinkage, “select and shrink for summary statistics” (S4), to summary level data for epithelial non-mucinous ovarian cancer risk prediction. We developed the models in a dataset consisting of 23,564 non-mucinous EOC cases and 40,138 controls participating in the Ovarian Cancer Association Consortium (OCAC) and validated the best models in three populations of different ancestries: prospective data from 198,101 women of European ancestries; 7,669 women of East Asian ancestries; 1,072 women of African ancestries, and in 18,915 BRCA1 and 12,337 BRCA2 pathogenic variant carriers of European ancestries. In the external validation data, the model with the strongest association for non-mucinous EOC risk derived from the OCAC model development data was the S4 model (27,240 SNPs) with odds ratios (OR) of 1.38 (95% CI: 1.28–1.48, AUC: 0.588) per unit standard deviation, in women of European ancestries; 1.14 (95% CI: 1.08–1.19, AUC: 0.538) in women of East Asian ancestries; 1.38 (95% CI: 1.21–1.58, AUC: 0.593) in women of African ancestries; hazard ratios of 1.36 (95% CI: 1.29–1.43, AUC: 0.592) in BRCA1 pathogenic variant carriers and 1.49 (95% CI: 1.35–1.64, AUC: 0.624) in BRCA2 pathogenic variant carriers. Incorporation of the S4 PRS in risk prediction models for ovarian cancer may have clinical utility in ovarian cancer prevention programs.
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  • Resultat 11-20 av 39

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