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Fig. 3 | Molecular Cytogenetics

Fig. 3

From: Machine learning-based identification of telomere-related gene signatures for prognosis and immunotherapy response in hepatocellular carcinoma

Fig. 3

Building and confirming a risk prediction model utilizing TRGs.(A) LASSO regression plots independent variable coefficients against the log-transformed regularization parameter λ on the x-axis.(B) For each λ, LASSO regression provides confidence intervals for the coefficients, depicted on the y-axis.(C-H) Analysis of KM survival curves for CDC20, TRIP13, EZH2, AKR1B10, and DNAJC6 in the TCGA-LIHC dataset suggested significant differences in overall survival (OS) time.(I-K) Survival profiles and the distribution of TRGs risk scores across the three cohorts are examined. Patients are ordered by their TRGs risk scores, with the vital status of each individual patient categorized by their risk score as illustrated in the central figure(I: TCGA-LIHC cohort; J:GSE14520;K: ICGC cohort). P< 0.05 is statistically different

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