ArticleScientific reports2023
Lymphocyte subsets and inflammatory factors as predictors of immunotherapy efficacy in patients with hepatocellular carcinoma.
Article in Scientific reports, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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1 citing paper in PubMed.
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3 authors.
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Abstract
We aimed to investigate the correlation between lymphocyte subpopulations expressing inhibitor receptors, IL-6 levels, and the efficacy of immunotherapy in patients with hepatocellular carcinoma. Blood samples were prospectively collected before and after immunotherapy from patients with intermediate and advanced hepatocellular carcinoma who were treated with immunotherapy at the Fifth Medical Center of the PLA General Hospital from August 2022 to October 2023. According to the efficacy of the patients, patients were divided into effective and ineffective groups, with 40 in the effective group and 44 in the ineffective group. We compared changes in lymphocyte subsets and IL-6 levels between the two groups. Optimal cut-off value was determined using ROC curves. Then, patients were categorized into high and low groups based on cut-off value, and the disease control rates and progression free survival were compared. Before immunotherapy, there were no significant differences in the baseline levels of lymphocyte subsets (PD1 + TIM3 + T/T, TIGIT + T/T, TIM3 + T/T, CTLA4 + T/T, LAG3 + T/T, PD1 + T/T) and IL-6 between the two groups (P > 0.05). After immunotherapy, the levels of PD1 + TIM3 + T/T, TIGIT + T/T, and IL-6 in the effective group were lower than those in the ineffective group and these differences were statistically significant (P = 0.001, P = 0.008, P = 0.000). However, the levels of other lymphocyte subsets showed no significant difference. Using the ROC curve to assess efficacy prediction, PD1 + TIM3 + T/T, TIGIT + T/T and IL-6 demonstrated high predictive ability (AUC = 0.79, AUC = 0.81, AUC = 0.78). The predictive value of efficacy was further improved when all three factors were combined (AUC = 0.92, P = 0.000). Based on the ROC curve, we identified optimal cut-off value for three factors. Notably, patients with values below the optimal cut-off value had higher disease control rate and progression free survival. The levels of PD1 + TIM3 + T/T, TIGIT + T/T, and IL-6 after 2 cycles of immunotherapy may serve as predictors of treatment efficacy in patients with hepatocellular carcinoma.
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