Current and novel approaches in the pharmacological treatment of hepatocellular carcinoma

Villarruel-Melquiades, Fernanda; Mendoza-Garrido, M. Eugenia; García-Cuéllar, Claudia M.; Sánchez-Pérez, Yesennia; Pérez‐Carreón, Julio Isael; Camacho, Javier

doi:10.3748/wjg.v29.i17.2571

Cited by 11 publications

(7 citation statements)

References 233 publications

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“…Liver cancer, a malignant tumor with consistently high global incidence and mortality rates, has long been a focal point of medical research and clinical intervention[ 1 , 2 ]. In particular, within the rapidly advancing field of immunotherapy, immune checkpoint blockade (ICB) treatment has emerged as an innovative therapeutic approach, offering renewed hope for patients with liver cancer[ 3 ]. This strategy has achieved significant clinical efficacy by preventing tumor cells from suppressing the immune system and stimulating the body’s own immune response[ 3 - 5 ].…”

Section: Introductionmentioning

confidence: 99%

“…In particular, within the rapidly advancing field of immunotherapy, immune checkpoint blockade (ICB) treatment has emerged as an innovative therapeutic approach, offering renewed hope for patients with liver cancer[ 3 ]. This strategy has achieved significant clinical efficacy by preventing tumor cells from suppressing the immune system and stimulating the body’s own immune response[ 3 - 5 ]. However, only a small fraction of liver cancer patients benefit from this treatment, and the molecular basis underlying the control of immune responses and evasion has not been determined[ 6 , 7 ].…”

Section: Introductionmentioning

confidence: 99%

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Identification of an immune-related gene signature for predicting prognosis and immunotherapy efficacy in liver cancer via cell-cell communication

Li,

Zhang,

Wang

et al. 2024

World J Gastroenterol

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BACKGROUND Liver cancer is one of the deadliest malignant tumors worldwide. Immunotherapy has provided hope to patients with advanced liver cancer, but only a small fraction of patients benefit from this treatment due to individual differences. Identifying immune-related gene signatures in liver cancer patients not only aids physicians in cancer diagnosis but also offers personalized treatment strategies, thereby improving patient survival rates. Although several methods have been developed to predict the prognosis and immunotherapeutic efficacy in patients with liver cancer, the impact of cell-cell interactions in the tumor microenvironment has not been adequately considered. AIM To identify immune-related gene signals for predicting liver cancer prognosis and immunotherapy efficacy. METHODS Cell grouping and cell-cell communication analysis were performed on single-cell RNA-sequencing data to identify highly active cell groups in immune-related pathways. Highly active immune cells were identified by intersecting the highly active cell groups with B cells and T cells. The significantly differentially expressed genes between highly active immune cells and other cells were subsequently selected as features, and a least absolute shrinkage and selection operator (LASSO) regression model was constructed to screen for diagnostic-related features. Fourteen genes that were selected more than 5 times in 10 LASSO regression experiments were included in a multivariable Cox regression model. Finally, 3 genes (stathmin 1, cofilin 1, and C-C chemokine ligand 5) significantly associated with survival were identified and used to construct an immune-related gene signature. RESULTS The immune-related gene signature composed of stathmin 1, cofilin 1, and C-C chemokine ligand 5 was identified through cell-cell communication. The effectiveness of the identified gene signature was validated based on experimental results of predictive immunotherapy response, tumor mutation burden analysis, immune cell infiltration analysis, survival analysis, and expression analysis. CONCLUSION The findings suggest that the identified gene signature may contribute to a deeper understanding of the activity patterns of immune cells in the liver tumor microenvironment, providing insights for personalized treatment strategies.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Identification of an immune-related gene signature for predicting prognosis and immunotherapy efficacy in liver cancer via cell-cell communication

Li,

Zhang,

Wang

et al. 2024

World J Gastroenterol

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“…HCC is characterized by asymptomatic progression at the early stage and metastatic potential at the advanced stage, which leads to diagnosis at terminal stage and poor prognosis 3 . In recent decades, although therapy strategies for HCC, such as chemotherapy 4 and immunotherapy 5 , have made great progress, overall survival has not improved 6 . Therefore, molecular and cellular events in HCC should be further understood to explore more effective therapeutic targets against HCC.…”

Section: Introductionmentioning

confidence: 99%

Integrated analysis of histone lysine lactylation (Kla)-specific genes suggests that NR6A1, OSBP2 and UNC119B are novel therapeutic targets for hepatocellular carcinoma

Wu,

Li,

Long

et al. 2023

Sci Rep

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Histone lysine lactylation (Kla) plays a vital role in the tumorigenesis of hepatocellular carcinoma (HCC). Hence, we focused on Kla-specific genes to select novel therapeutic targets. Differentially expressed Kla-specific genes (DEKlaGs) were identified from TCGA with the cut-off criteria |log2(FlodChange (FC))| > 2, p-value < 0.05, following investigating the prognostic value. The correlation between lactate accumulation and prognostic DEKlaGs expression was further investigated. On the other hand, we explored the roles of Kla activation in the immune microenvironment, immunotherapy, and drug resistance. We conducted gene set enrichment analysis (GSEA) to predict the pathways influenced by Kla. The predictive power of Cox model was further identified in ICGC and GEO databases. A total of 129 DEKlaGs were identified, and 32 molecules might be potential prognostic biomarkers. A Cox model including ARHGEF37, MTFR2, NR6A1, NT5DC2, OSBP2, RNASEH2A, SFN, and UNC119B was constructed, which suggested unfavorable overall survival in high-risk score group, and risk score could serve as an indicator for large tumor size, poor pathological grade and advanced stage. NR6A1, OSBP2 and UNC119B could inhibit NK cell as well as TIL cell infiltration, and impair Type-I and II IFN responses in HCC, thereby contributing to unsatisfactory prognosis and immunotherapy resistance. OSBP2 and UNC119B were identified to be related to chemotherapy resistance. GSEA showed that WNT, MTOR, MAPK and NOTCH signaling pathways were activated, indicating that these pathways might play a crucial role during the Kla process. On the other hand, we showed that NR6A1 and OSBP2 were overexpressed in GEO. OSBP2 and UNC119B contributed to poor survival and advanced stage in ICGC. In summary, histone Kla was related to HCC prognosis and might serve as an independent biomarker. NR6A1, OSBP2 and UNC119B were associated with the prognosis, immunotherapy, and chemotherapy resistance, suggesting that NR6A1, OSBP2 and UNC119B might be novel candidate therapeutic targets for HCC.

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“…Hepatocellular carcinoma (HCC) is a critical global healthcare issue with a mortality-to-morbidity ratio as high as 91.6% ( Villarruel-Melquiades et al, 2023 ). Patients with HBV/HCV infection, cirrhosis of any cause, alcoholism, non-alcoholic steatohepatitis, or family history of HCC are considered high-risk groups for HCC, especially among men aged over 40 years old ( Xie et al, 2023 ).…”

Section: Introductionmentioning

confidence: 99%

Heterogeneity characterization of hepatocellular carcinoma based on the sensitivity to 5-fluorouracil and development of a prognostic regression model

Gu,

Li,

et al. 2023

Front. Pharmacol.

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Background: 5-Fluorouracil (5-FU) is a widely used chemotherapeutic drug in clinical cancer treatment, including hepatocellular carcinoma (HCC). A correct understanding of the mechanisms leading to a low or lack of sensitivity of HCC to 5-FU-based treatment is a key element in the current personalized medical treatment.Methods: Weighted gene co-expression network analysis (WGCNA) was used to analyze the expression profiles of the cancer cell line from GDSC2 to identify 5-FU-related modules and hub genes. According to hub genes, HCC was classified and the machine learning model was developed by ConsensusClusterPlus and five different machine learning algorithms. Furthermore, we performed quantitative reverse transcription-polymerase chain reaction (qRT-PCR) analysis on the genes in our model.Results: A total of 19 modules of the cancer cell line were divided by WGCNA, and the most negative correlation with 5-FU was the midnight blue module, from which 45 hub genes were identified. HCC was divided into three subgroups (C1, C2, and C3) with significant overall survival (OS) differences. OS of C1 was the shortest, which was characterized by a high clinical grade and later T stage and stage. OS of C3 was the longest. OS of C2 was between the two subtypes, and its immune infiltration was the lowest. Five out of 45 hub genes, namely, TOMM40L, SNRPA, ILF3, CPSF6, and NUP205, were filtered to develop a risk regression model as an independent prognostic indicator for HCC. The qRT-PCR results showed that TOMM40L, SNRPA, ILF3, CPSF6, and NUP205 were remarkably highly expressed in hepatocellular carcinoma.Conclusion: The HCC classification based on the sensitivity to 5-FU was in line with the prognostic differences observed in HCC and most of the genomic variation, immune infiltration, and heterogeneity of pathological pathways. The regression model related to 5-FU sensitivity may be of significance in individualized prognostic monitoring of HCC.

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Current and novel approaches in the pharmacological treatment of hepatocellular carcinoma

Cited by 11 publications

References 233 publications

Identification of an immune-related gene signature for predicting prognosis and immunotherapy efficacy in liver cancer via cell-cell communication

Identification of an immune-related gene signature for predicting prognosis and immunotherapy efficacy in liver cancer via cell-cell communication

Integrated analysis of histone lysine lactylation (Kla)-specific genes suggests that NR6A1, OSBP2 and UNC119B are novel therapeutic targets for hepatocellular carcinoma

Heterogeneity characterization of hepatocellular carcinoma based on the sensitivity to 5-fluorouracil and development of a prognostic regression model

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