ArticleFrontiers in immunology2023
Prognostic signatures of sphingolipids: Understanding the immune landscape and predictive role in immunotherapy response and outcomes of hepatocellular carcinoma.
Article in Frontiers in immunology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 53 papers, 1 of them a synthesis that pooled it.
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Who cites it
53 citing papers in PubMed, 1 synthesis or guideline pooled it, 54 citations in OpenAlex.
- Exploring the Role of HtrA Family Genes in Cancer: A Systematic Review.Molecular diagnosis & therapy · 2024Pooled it
- Integrative Phosphoproteomic and Metabolomic Analysis of Disruption of Metabolic Homeostasis in Breast Cancer: A Pilot Study.Biochemical genetics · 2026Article
- Advances in adoptive cell therapy for ovarian cancer.Frontiers in immunology · 2026Review
- Decoding the Sphingolipid Landscape of Clear Cell Renal Cell Carcinoma: A Single-Cell-Guided Prognostic Model Built With 101 Machine Learning.Human mutation · 2026Article
- Single-cell and multi-omics analyses identify CAMP-associated neutrophil remodeling during radiochemotherapy in cervical cancer.Frontiers in cell and developmental biology · 2026Article
- Artificial neural network-based immune biomarker signature predicts pathological complete response to neoadjuvant chemotherapy in HER2-negative breast cancer.Frontiers in oncology · 2026Article
- Sphingolipid Metabolism in the Pathogenesis of Hashimoto's Thyroiditis.International journal of molecular sciences · 2025Review
- Development and validation of a nomogram model of lung metastasis in breast cancer based on machine learning algorithm and cytokines.BMC cancer · 2025Article
- Immunosuppressive tumor microenvironment in pancreatic cancer: mechanisms and therapeutic targets.Frontiers in immunology · 2025Review
- Metabolic reprogramming and immune microenvironment characteristics in laryngeal carcinoma: advances in immunotherapy.Frontiers in immunology · 2025Review
- Metabolic reprogramming in hepatocellular carcinoma: mechanisms of immune evasion and therapeutic implications.Frontiers in immunology · 2025Review
- The role of Treg cells in colorectal cancer and the immunotherapy targeting Treg cells.Frontiers in immunology · 2025Review
- Acute aerobic exercise alters serum protein distribution in colorectal cancer patients.Frontiers in oncology · 2025Article
- Immune microenvironment and immunotherapy in hepatocellular carcinoma: mechanisms and advances.Frontiers in immunology · 2025Review
- Targeting tumor-associated macrophages in colon cancer: mechanisms and therapeutic strategies.Frontiers in immunology · 2025Review
- Uncovering the heterogeneity of NK cells on the prognosis of HCC by integrating bulk and single-cell RNA-seq data.Frontiers in oncology · 2025Article
- Sesquiterpene lactones and cancer: new insight into antitumor and anti-inflammatory effects of parthenolide-derived Dimethylaminomicheliolide and Micheliolide.Frontiers in pharmacology · 2025Review
- Mechanisms of tumor-associated macrophages in breast cancer and treatment strategy.Frontiers in immunology · 2025Review
- Circulating cell-free DNA methylation analysis of pancreatic cancer patients for early noninvasive diagnosis.Frontiers in oncology · 2025Article
- New progress in imaging diagnosis and immunotherapy of breast cancer.Frontiers in immunology · 2025Review
Corrections and comments
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Authors and funding
13 authors at 7 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: Hepatocellular carcinoma (HCC) is a complex disease with a poor outlook for patients in advanced stages. Immune cells play an important role in the progression of HCC. The metabolism of sphingolipids functions in both tumor growth and immune infiltration. However, little research has focused on using sphingolipid factors to predict HCC prognosis. This study aimed to identify the key sphingolipids genes (SPGs) in HCC and develop a reliable prognostic model based on these genes. Methods: The TCGA, GEO, and ICGC datasets were grouped using SPGs obtained from the InnateDB portal. A prognostic gene signature was created by applying LASSO-Cox analysis and evaluating it with Cox regression. The validity of the signature was verified using ICGC and GEO datasets. The tumor microenvironment (TME) was examined using ESTIMATE and CIBERSORT, and potential therapeutic targets were identified through machine learning. Single-cell sequencing was used to examine the distribution of signature genes in cells within the TME. Cell viability and migration were tested to confirm the role of the key SPGs. Results: We identified 28 SPGs that have an impact on survival. Using clinicopathological features and 6 genes, we developed a nomogram for HCC. The high- and low-risk groups were found to have distinct immune characteristics and response to drugs. Unlike CD8 T cells, M0 and M2 macrophages were found to be highly infiltrated in the TME of the high-risk subgroup. High levels of SPGs were found to be a good indicator of response to immunotherapy. In cell function experiments, SMPD2 and CSTA were found to enhance survival and migration of Huh7 cells, while silencing these genes increased the sensitivity of Huh7 cells to lapatinib. Conclusion: The study presents a six-gene signature and a nomogram that can aid clinicians in choosing personalized treatments for HCC patients. Furthermore, it uncovers the connection between sphingolipid-related genes and the immune microenvironment, offering a novel approach for immunotherapy. By focusing on crucial sphingolipid genes like SMPD2 and CSTA, the efficacy of anti-tumor therapy can be increased in HCC cells.
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