Dataset Information

Integrative analysis of disulfidptosis and immune microenvironment in hepatocellular carcinoma: a putative model and immunotherapeutic strategies.

ABSTRACT:

Background

Hepatocellular carcinoma (HCC) is a malignant tumor with a high rate of recurrence and m metastasis that does not respond well to current therapies and has a very poor prognosis. Disulfidptosis is a novel mode of cell death that has been analyzed as a novel therapeutic target for HCC cells.

Methods

This study integrated bulk ribonucleic acid (RNA) sequencing datasets, spatial transcriptomics (ST), and single-cell RNA sequencing to explore the landscape of disulfidptosis and the immune microenvironment of HCC cells.

Results

We developed a novel model to predict the prognosis of patients with HCC based on disulfidptosis. The model has good stability, applicability, and prognostic and immune response prediction abilities. N-myc downregulated gene1 (NDRG1) may contribute to poor prognosis by affecting macrophage differentiation, thus allowing HCC cells to evade the immune system.

Conclusion

Our study explores the disulfidptosis of HCC cells through multi-omics and establishes a new putative model that explores possible targets for HCC treatment.

SUBMITTER: Yang T

PROVIDER: S-EPMC10791859 | biostudies-literature | 2023

REPOSITORIES: biostudies-literature

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Publications

Integrative analysis of disulfidptosis and immune microenvironment in hepatocellular carcinoma: a putative model and immunotherapeutic strategies.

Yang Ti T Liu Junhao J Liu Fang F Lei Jiashun J Chen Siliang S Ma Zengxin Z Ke Peifeng P Yang Qiaolan Q Wen Jianfan J He Yifeng Y Duan Juan J Zeng Xiancheng X

Frontiers in immunology 20240103

<h4>Background</h4>Hepatocellular carcinoma (HCC) is a malignant tumor with a high rate of recurrence and m metastasis that does not respond well to current therapies and has a very poor prognosis. Disulfidptosis is a novel mode of cell death that has been analyzed as a novel therapeutic target for HCC cells.<h4>Methods</h4>This study integrated bulk ribonucleic acid (RNA) sequencing datasets, spatial transcriptomics (ST), and single-cell RNA sequencing to explore the landscape of disulfidptosis ...[more]

PMID: 38235128

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Project description:The intricate nature and varied forms of bladder urothelial carcinoma (BLCA) highlight the need for new indicators to define tumor prognosis. Disulfidptosis, a novel form of cell death, is closely linked to BLCA progression, prognosis, and treatment outcomes. Our current goal is to develop a novel disulfidptosis-related immune prognostic model to enhance BLCA treatment strategies. Utilizing RNA-seq data from The Cancer Genome Atlas (TCGA) , which included 419 patients (19 normal, 400 tumor), we performed weighted gene co-expression network analysis (WGCNA) to identify disulfidptosis-associated immune genes. Through multivariate Cox regression, and the least absolute shrinkage and selection operator (LASSO) regularization, we established a disulfidptosis-related immune risk scoring system. A nomogram combining risk score and clinical features predicted prognosis. Model performance was validated through survival curve analysis and independent validation cohort. Immune checkpoints, cell infiltration, and tumor mutation load were assessed. Differential gene enrichment analysis was conducted. Prognostic genes were validated via in vitro experiments. Eight immune genes related to disulfidptosis were identified and verified in BLCA prognosis. A prognostic model outperformed previous ones in predicting overall survival (OS) for high- and low-risk groups. Patients with low-risk scores had higher OS rates and tumor mutation burden (TMB) compared to high-risk score patients. CD4 memory T cells, CD8 T cells, M1 macrophages, and resting NK cells were found to be higher in the low-risk group. Immune checkpoint inhibitor (ICI) treatment may be more effective for the low-risk score group. High-risk score group exhibited stronger correlation with cancer malignant pathways. Knocking out tumor necrosis factor receptor superfamily member 12 A (TNFRSF12A) inhibits BLCA cell proliferation and invasion while overexpressing it has the opposite effect. We constructed a novel risk score model that combines disulfidptosis and immune genes, demonstrating good prognostic prediction performance. We discovered and verified that the TNFRSF12A gene is an oncogene in BLCA, which may help provide personalized guidance for individualized treatment and immunotherapy selection for BLCA patients to a certain extent.

Project description:BackgroundVarious studies highlighted that immune cell-mediated inflammatory processes play crucial roles in the progression and treatment of hepatocellular carcinoma (HCC). However, the immune microenvironment of HCC is still poorly characterized. Exploring the role of immune-related genes (IRGs) and describing the immune landscape in HCC would provide insights into tumor-immune co-evolution along HCC progression.MethodsWe integrated the datasets with complete prognostic information from the Cancer Genome Atlas (TCGA) database and GEO DataSets (GSE14520, GSE76427, and GSE54236) to construct a novel immune landscape based on the Cibersort algorithm and reveal the prognostic signature in HCC patients.ResultsTo describe the tumor microenvironment (TME) in HCC, immune infiltration patterns were defined using the CIBERSORT method, and a prognostic signature contains 5 types of immune cells, including 3 high-risk immune cells (T.cells. CD4. memory. resting, Macrophages.M0, Macrophages.M2) and 2 low-risk immune cells (Plasma. cells, T.cells.CD8), were finally constructed. A novel prognostic index, based on prognostic immune risk score (pIRG), was developed using the univariate Cox regression analyses and LASSO Cox regression algorithm. Furthermore, the ROC curve and KM curve showed that the TME signatures had a stable value in predicting the prognosis of HCC patients in the internal training cohort, internal validation, and external validation cohort. Differential genes analysis and qPCR experiment showed that the expression levels of AKR1B10, LAPTM4B, MMP9, and SPP1 were significantly increased in high-risk patients, while the expression of CD5L was lower. Further analysis found that AKR1B10 and MMP9 were associated with higher M0 macrophage infiltration, while CD5L was associated with higher plasma cell infiltration.ConclusionsTaken together, we performed a comprehensive evaluation of the immune landscape of HCC and constructed a novel and robust prognostic prediction model. AKR1B10, LAPTM4B, MMP9, SPP1, and CD5L were involved in important processes in the HCC tumor microenvironment and were expected to become HCC prediction markers and potential targets of treatment.

Dataset Information

Integrative analysis of disulfidptosis and immune microenvironment in hepatocellular carcinoma: a putative model and immunotherapeutic strategies.

Background

Methods

Results

Conclusion

Publications

Integrative analysis of disulfidptosis and immune microenvironment in hepatocellular carcinoma: a putative model and immunotherapeutic strategies.

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