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Immune Subtyping and NK Cell Targeting: Optimizing Immune Checkpoint Inhibitor Therapy in Hepatocellular Carcinoma

(A) Number of principal components versus standard deviation under PCA analysis. (B) Visualization of cell clustering under the UMAP algorithm. (C) Distribution of annotated cells. (D) Average expression of marker genes on each cell. (E) Distribution of i

(A) Unsupervised consistent clustering of the two subtypes of TCGA-HCC patients. (B) Comparison of overall survival (OS) between the two subtypes of TCGA-HCC patients. (C) Comparison of MIAS scores between the two subtypes of TCGA-HCC patients. (D) Compar

(A) Volcano plot of NK_scissor_C1-associated drug priorities. (B) NK_scissor_C1-associated drug usage status. (C) The Veen diagram showing intersections of NK_scissor_C1-associated drug targets with HCC-associated genes. (D) Interaction network of top 10

- New Study Unveils Novel Classification Approach for Predicting ICI Response in HCC Patients

CHINA, March 18, 2025 /EINPresswire.com/ -- Hepatocellular carcinoma (HCC), the most common type of primary liver cancer, accounts for about 75–85% of all liver cancer cases. Immune checkpoint inhibitors (ICIs), despite yielding a superior therapeutic impact, have substantial drawbacks, including therapy-resistant patients and absence of biomarkers for predicting the response to ICIs. Hence, there is an urgent need to investigate dependable biomarkers to enhance patient prognosis while minimizing the adverse effects of ICIs.

This research, published in the Genes & Diseases journal by a team from Chongqing Medical University, explores the heterogeneity of immune subtypes at the single-cell level using bulk and single-cell sequencing to identify potential ICI response-associated cells and therapeutic agents in HCC.

The researchers employed seven predictive scores related to ICI response to measure the effectiveness of an immune gene set in categorizing HCC patients. The results confirmed the ability of immune signature scores to distinguish two immune subtypes, subtype 1 and subtype 2, with significant differences in immune response. Patients in both subtypes showed varying overall survival, immunity levels, biological activities, and TP53 mutation rates. Furthermore, the study revealed that patients with subtype 1 demonstrated significantly improved overall survival rates and higher immune response scores compared to those with subtype 2.

Interestingly, this study noted that only subtype 1-associated natural killer (NK) cells showed a positive correlation with immune-promoting scores, highlighting their potential role in enhancing ICI treatment efficacy. In addition, the researchers screened 2494 potential drugs using multiple databases and network approaches to identify potential therapeutic agents targeting subtype 1-associated NK cells. Among the candidates, docetaxel and thalidomide emerged as promising options for enhancing ICI response. Notably, sensitivity analysis revealed that docetaxel sensitivity in HCC patients rose as the levels of subtype 1-related NK cells increased, suggesting that increased sensitivity to docetaxel may enhance immune responses in HCC patients.

Although this research provides a framework for immune-based classification in HCC, the correlation between NK cell subsets and docetaxel sensitivity requires further validation through clinical trials. Nevertheless, the combination of subtype 1-associated NK cells and docetaxel may offer new hope for ICI treatment in HCC. In conclusion, this study has revealed the cell types that potentially affect ICIs and identified potential drugs by combining bulk sequencing and single-cell sequencing, which will provide a scientific reference for future studies of ICIs in HCC treatment.

Reference

Title of Original Paper - Comprehensive analysis of immune subtype characterization on identification of potential cells and drugs to predict response to immune checkpoint inhibitors for hepatocellular carcinoma

DOI: https://doi.org/10.1016/j.gendis.2024.101471

Journal: Genes & Diseases
Genes & Diseases is a journal for molecular and translational medicine. The journal primarily focuses on publishing investigations on the molecular bases and experimental therapeutics of human diseases. Publication formats include full length research article, review article, short communication, correspondence, perspectives, commentary, views on news, and research watch.

Funding Information:

Science and Technology Research Programme Project of Chongqing Municipal Education Commission of China (No. KJQN202300423)
National Youth Science Foundation Project (China) (No. 82204159)
Science and Technology Project of Sichuan Provincial Administration of Traditional Chinese Medicine (China) (No. 2023MS047)
Program for Youth Innovation in Future Medicine, Chongqing Medical University (No.W0150)
Intelligent Medicine Research Project of Chongqing Medical University (No. ZHYX202223)

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Genes & Diseases publishes rigorously peer-reviewed and high quality original articles and authoritative reviews that focus on the molecular bases of human diseases. Emphasis is placed on hypothesis-driven, mechanistic studies relevant to pathogenesis and/or experimental therapeutics of human diseases. The journal has worldwide authorship, and a broad scope in basic and translational biomedical research of molecular biology, molecular genetics, and cell biology, including but not limited to cell proliferation and apoptosis, signal transduction, stem cell biology, developmental biology, gene regulation and epigenetics, cancer biology, immunity and infection, neuroscience, disease-specific animal models, gene and cell-based therapies, and regenerative medicine.

Scopus CiteScore: 7.3 | Impact Factor: 6.9

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(A) Unsupervised consistent clustering of the two subtypes of TCGA-HCC patients. (B) Comparison of overall survival (OS) between the two subtypes of TCGA-HCC patients. (C) Comparison of MIAS scores between the two subtypes of TCGA-HCC patients. (D) Compar

(A) Volcano plot of NK_scissor_C1-associated drug priorities. (B) NK_scissor_C1-associated drug usage status. (C) The Veen diagram showing intersections of NK_scissor_C1-associated drug targets with HCC-associated genes. (D) Interaction network of top 10

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