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Hepatocellular carcinoma cell differentiation trajectory predicts immunotherapy, potential therapeutic drugs, and prognosis of patients.

ABSTRACT: The aim of this study is to explore a novel classification and investigate the clinical significance of hepatocellular carcinoma (HCC) cells. We analyzed integrated single-cell RNA sequencing and bulk RNA-seq data obtained from HCC samples. Cell trajectory analysis divided HCC cells into three subgroups with different differentiation states: state 1 was closely related to phosphoric ester hydrolase activity, state 2 was involved in eukaryotic initiation factor 4E binding, translation regulator activity and ribosome, and state 3 was associated with oxidoreductase activity and metabolism. Three molecular classes based on HCC differentiation-related genes (HDRGs) from HCC samples were identified, which revealed immune checkpoint gene expression and overall survival (OS) of HCC patients. Moreover, a prognostic risk scoring (RS) model was generated based on eight HDRGs, and the results showed that the OS of the high-risk group was worse than that of the low-risk group. Further, potential therapeutic drugs were screened out based on eight prognostic RS-HDRGs. This study highlights the importance of HCC cell differentiation in immunotherapy, clinical prognosis, and potential molecular-targeted drugs for HCC patients, and proposes a direction for the development of individualized treatments for HCC.

SUBMITTER: Qiu J

PROVIDER: S-EPMC10426728 | biostudies-literature | 2023

REPOSITORIES: biostudies-literature

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Hepatocellular carcinoma cell differentiation trajectory predicts immunotherapy, potential therapeutic drugs, and prognosis of patients.

Qiu Jun J Wang Haoyun H Lv Xin X Mao Lipeng L Huang Junyan J Hao Tao T Li Junliang J Qi Shuo S Chen Guodong G Jiang Haiping H

Open life sciences 20230808 1

The aim of this study is to explore a novel classification and investigate the clinical significance of hepatocellular carcinoma (HCC) cells. We analyzed integrated single-cell RNA sequencing and bulk RNA-seq data obtained from HCC samples. Cell trajectory analysis divided HCC cells into three subgroups with different differentiation states: state 1 was closely related to phosphoric ester hydrolase activity, state 2 was involved in eukaryotic initiation factor 4E binding, translation regulator a ...[more]

PMID: 37589009

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Project description:ObjectivesThis study aimed to investigate the differentiation state and clinical significance of colorectal cancer cells, as well as to predict the immune response and prognosis of patients based on differentiation-related genes of colorectal cancer.IntroductionColorectal cancer cells exhibit different differentiation states under the influence of the tumor microenvironment, which determines the cell fates.MethodsWe combined single-cell sequencing (scRNA-seq) data from The Cancer Genome Atlas source with extensive transcriptome data from the Gene Expression Omnibus database. We obtained colorectal cancer differentiation-related genes using cell trajectory analysis and developed a colorectal cancer differentiation-related gene based molecular typing and prognostic model to predict the immune response and prognosis of patients with colorectal cancer.ResultsWe identified 5 distinct cell differentiation subsets and 620 colorectal cancer differentiation-related genes. Colorectal cancer differentiation-related genes were significantly associated with metabolism, angiogenesis, and immunity. We separated patients into 3 subtypes based on colorectal cancer differentiation-related gene expression in the tumor and found differences among the different subtypes in immune infiltration status, immune checkpoint gene expression, clinicopathological features, and overall survival. Immunotherapeutic interventions involving a highly expressed immune checkpoint blockade may be selectively effective in the corresponding cancer subtypes. We built a risk score prediction model (5-year AUC: .729) consisting of the 4 most important predictors of survival (TIMP1, MMP1, LGALS4, and ITLN1). Finally, we generated and validated a nomogram consisting of the risk score and clinicopathological variables.ConclusionThis study highlights the significance of genes involved in cell differentiation for clinical prognosis and immunotherapy in patients and provides prospective therapeutic targets for colorectal cancer.

Project description:Immune checkpoint inhibitors(ICIs) that activate tumor-specific immune responses bring new hope for the treatment of hepatocellular carcinoma(HCC). However, there are still some problems, such as uncertain curative effects and low objective response rates, which limit the curative effect of immunotherapy. Therefore, it is an urgent problem to guide the use of ICIs in HCC based on molecular typing. We downloaded the The Cancer Genome Atlas-Liver hepatocellular carcinoma(TCGA-LIHC) and Mongolian-LIHC cohort. Unsupervised clustering was applied to the highly variable data regarding expression of DNA damage repair(DDR). The CIBERSORT was used to evaluate the proportions of immune cells. The connectivity map(CMap) and pRRophetic algorithms were used to predict the drug sensitivity. There were significant differences in DDR molecular subclasses in HCC(DDR1 and DDR2), and DDR1 patients had low expression of DDR-related genes, while DDR2 patients had high expression of DDR-related genes. Of the patients who received traditional treatment, DDR2 patients had significantly worse overall survival(OS) than DDR1 patients. In contrast, of the patients who received ICIs, DDR2 patients had significantly prolonged OS compared with DDR1 patients. Of the patients who received traditional treatment, patients with high DDR scores had worse OS than those with low DDR scores. However, the survival of patients with high DDR scores after receiving ICIs was significantly higher than that of patients with low DDR scores. The DDR scores of patients in the DDR2 group were significantly higher than those of patients in the DDR1 group. The tumor microenvironment(TME) of DDR2 patients was highly infiltrated by activated immune cells, immune checkpoint molecules and proinflammatory molecules and antigen presentation-related molecules. In this study, HCC patients were divided into the DDR1 and DDR2 group. Moreover, DDR status may serve as a potential biomarker to predict opposite clinical prognosis immunotherapy and non-immunotherapy in HCC.

Project description:BackgroundLamin family members play crucial roles in promoting oncogenesis and cancer development. The values of lamin family in predicting prognosis and immunotherapy response remain largely unclarified. Our research is aimed at comprehensively estimating the clinical significance of lamin family in hepatocellular carcinoma and constructing a novel lamin family-based signature to predict prognosis and guide the precise immunotherapy.MethodsThe expression features and prognostic value of LMNA, LMNB1, and LMNB2 were explored in the TCGA and GEO databases. The biological functions of LMNB1 and LMNB2 were validated by in vitro assays. A lamin family-based signature was built using the TCGA training set. The TCGA test set, entire TCGA set, and GSE14520 set were used to validate its predictive power. Univariate and multivariate analyses were performed to evaluate the independence of the lamin family-based signature from other clinicopathological characteristics. A nomogram was constructed using the lamin family-based signature and TNM stage. The associations of this signature with molecular pathways, clinical characteristics, immune cell infiltration, and immunotherapy response were analyzed.ResultsLamin family members were upregulated in HCC. Upregulation of LMNB1 and LMNB2 promoted HCC proliferation, migration, and invasion. The predictive signature was initially established based on LMNB1 and LMNB2 which could effectively identify differences in overall survival, immune cell infiltration, and clinicopathological characteristics of high- and low-risk patients. The nomogram showed high prognostic predictive accuracy. Importantly, the lamin family-based signature was correlated with immune suppression and expression of immune checkpoint molecules.ConclusionsThe lamin family-based signature is a robust biomarker to predict overall survival and immunotherapy response in HCC. High-risk score patients have a poorer overall survival and might be more sensitive to immunotherapy. This signature may contribute to improving individualized prognosis prediction and precision immunotherapy for HCC patients.

Project description:ObjectiveThe aim of this study is to assess the clinical utility of RecQ Like Helicase 4 (RECQL4) as a prognostic marker in hepatocellular carcinoma (HCC) and investigate its associations with various biological processes, angiogenesis-related factors, immune cell infiltration, immune checkpoints, and drug sensitivity.MethodsRECQL4 expression was analyzed across a range of cancer types utilizing data from the TCGA database. Disparities in RECQL4 expression levels between normal and malignant tissues were evaluated, alongside an analysis of progression-free interval (PFI), disease-specific survival (DSS), and overall survival (OS) curves. Exploration of pertinent pathways, immune cell infiltration, single-cell RNA-seq data, and drug sensitivity was conducted employing The Cancer Genome Atlas (TCGA) and Tumor Immune Single-Cell Hub (TISCH) databases. Furthermore, validation of in-silico results was validated through qPCR, Western blotting, CCK-8 assay, EdU assay, clonogenic assay, wound-healing assay, and transwell assay.ResultsIn HCC, RECQL4 was highly expressed and associated with poorer prognosis (p < 0.05). It positively correlated with pathways related to MYC targets, DNA replication, PI3K/AKT/mTOR signaling, DNA repair mechanisms, and the G2/M checkpoint (R > 0.24, p < 0.001). RECQL4 also showed significant correlations with angiogenesis-related genes, including PTK2 (R > 0.4, p < 0.05), suggesting a potential role in angiogenesis regulation. Immune analysis indicated that RECQL4 was associated with immune cell types such as T helper 2 cells, NK CD56bright cells, and follicular helper T cells, suggesting a positive relationship with their infiltration. High RECQL4 expression was also linked to increased sensitivity to drugs including Sorafenib, 5-Fluorouracil, Cisplatin, and Doxorubicin. Cellular experiments showed that RECQL4 expression at the mRNA and protein levels were significantly higher in HCC cell lines Hep3B and Huh7 compared to the normal liver cell line MHA. Moreover, RECQL4 knockdown resulted in reduced proliferation and migration in HCC cell lines (p < 0.05).ConclusionsRECQL4 shows promise as a biomarker for predicting recurrence and survival in HCC and may affect angiogenesis regulation. Its expression also appears to impact sensitivity to drugs such as Sorafenib, 5-Fluorouracil, Cisplatin, and Doxorubicin. Furthermore, silencing RECQL4 significantly inhibits HCC cell line proliferation and migration.

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Hepatocellular carcinoma cell differentiation trajectory predicts immunotherapy, potential therapeutic drugs, and prognosis of patients.

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Hepatocellular carcinoma cell differentiation trajectory predicts immunotherapy, potential therapeutic drugs, and prognosis of patients.

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