Dataset Information

Development and Validation of a Combined Ferroptosis and Immune Prognostic Classifier for Hepatocellular Carcinoma

ABSTRACT:

Background

Immunotherapy and sorafenib exert anti-tumor effects via ferroptosis, but reliable biomarkers for the individual treatment and prognosis prediction of hepatocellular carcinoma (HCC) based on the ferroptosis and immune status remain lacking.

Methods

Ferroptosis-related genes (FRGs) were identified by downloading data from FerrDb and by searching and reading original articles from PubMed. Immune-related genes (IRGs) were downloaded from ImmPort. Prognostic FRGs and IRGs in the GSE14520 (n = 220) and The Cancer Genome Atlas (TCGA, n = 365) datasets were identified. Least absolute shrinkage and selection operator (LASSO) Cox regression and multivariate Cox regression were used for model construction. Ferroptosis expression profiles, the infiltration of immune cells, and the somatic mutation status were analyzed and compared.

Results

Twenty-seven prognostic ferroptosis- and immune-related signatures were included to construct a comprehensive index of ferroptosis and immune status (CIFI). A subgroup of patients was identified as having a high CIFI value, which was associated with a worse prognosis. This subgroup of patients had significantly up-regulated expressions of many suppressors of ferroptosis and higher fractions of immunosuppressive cells, such as cancer-associated fibroblasts (CAFs) and myeloid-derived suppressor cells (MDSCs). Notably, somatic mutation analysis indicated that high-CIFI patients had higher levels of tumor heterogeneity and higher mutation frequencies of genes like TP53.

Conclusion

In this work, a novel prognostic classifier was developed based on ferroptosis- and IRGs in HCC, and this classifier could be used for prognostic prediction and the selection of patients for immunotherapies and targeted therapies.

SUBMITTER: Liu Y

PROVIDER: S-EPMC7785857 | biostudies-literature | 2020 Jan

REPOSITORIES: biostudies-literature

ACCESS DATA

Similar Datasets

Project description:Background: Ferroptosis, as a unique programmed cell death modality, has been found to be closely related to the occurrence and development of hepatocellular carcinoma (HCC). Hypoxia signaling pathway has been found to be extensively involved in the transformation and growth of HCC and to inhibit anti-tumor therapy through various approaches. However, there is no high-throughput study to explore the potential link between ferroptosis and hypoxia, as well as their combined effect on the prognosis of HCC. Methods: We included 370 patients in The Cancer Genome Atlas (TCGA) database and 231 patients in the International Cancer Genome Consortium (ICGC) database. Univariate COX regression and Least Absolute Shrinkage and Selection Operator approach were used to construct ferroptosis-related genes (FRGs) and hypoxia-related genes (HRGs) prognostic signature (FHPS). Kaplan-Meier method and Receiver Operating Characteristic curves were analyzed to evaluate the predictive capability of FHPS. CIBERSOR and single-sample Gene Set Enrichment Analysis were used to explore the connection between FHPS and tumor immune microenvironment. Immunohistochemical staining was used to compare the protein expression of prognostic FRGs and HRGs between normal liver tissue and HCC tissue. In addition, the nomogram was established to facilitate the clinical application of FHPS. Results: Ten FRGs and HRGs were used to establish the FHPS. We found consistent results in the TCGA training cohort, as well as in the independent ICGC validation cohort, that patients in the high-FHPS subgroup had advanced tumor staging, shorter survival time, and higher mortality. Moreover, patients in the high-FHPS subgroup showed ferroptosis suppressive, high hypoxia, and immunosuppression status. Finally, the nomogram showed a strong prognostic capability to predict overall survival (OS) for HCC patients. Conclusion: We developed a novel prognostic signature combining ferroptosis and hypoxia to predict OS, ferroptosis, hypoxia, and immune status, which provides a new idea for individualized treatment of HCC patients.

Project description:Background Studies have shown that the regulation of ferroptosis could be a new approach to cancer treatment and abnormal ferroptosis is closely associated with a dysregulated immune response. However, a combined signature with ferroptosis-related genes (FRGs) and immune-related genes (IRGs) is necessary to be constructed for predicting prognoses and guiding individualized precision therapy of lung adenocarcinoma (LUAD) patients. Methods In this study, based on the Cancer Genome Atlas (TCGA) cohort, prognosis-related FRGs and IRGs were first identified and incorporated into the Least Absolute Shrinkage and Selection Operator (LASSO)-Cox regression model to generate a combined signature of ferroptosis- and immune-related genes (CSFI) values to predict the overall survivals (OSs) of LUAD patients. And patients with LUAD from the Gene Expression Omnibus (GEO) database were applied for the validation set. Nomogram was constructed based on multivariate Cox regression analysis. Subsequently, ferroptosis, immunity, and gene mutation status of patients between the CSFI-high and -low groups were compared. Additionally, the enrichment pathways in CSFI-high and -low groups were explored by Gene Ontology (GO), Kyoto Gene and Genome Encyclopedia (KEGG) and Gene Set Enrichment Analysis (GSEA) analyses. Results As a result, the CSFI-low group showed a good prognosis instead of the CSFI-high group. CSFI was identified to be an independent prognosis factor for LUAD. In general, there were ferroptosis- and immune-suppressive states in CSFI-high patients. Notably, the mutation frequencies of TP53 were higher in CSFI-high patients. Conclusions In LUAD, CSFI which served as a novel classifier was offered for predicting the prognoses of patients and contributing to guiding personalized targeted therapy of patients. Therefore, based on these findings, it was believed that a synergistic treatment of ferroptosis and immunity would be more effective on LUAD patients with low CSFI values.

Project description:BackgroundTP53 mutation is the most common mutation in hepatocellular carcinoma (HCC), and it affects the progression and prognosis of HCC. We investigated how TP53 mutation regulates the HCC immunophenotype and thus affects the prognosis of HCC.MethodsWe investigated TP53 mutation status and RNA expression in different populations and platforms and developed an immune prognostic model (IPM) based on immune-related genes that were differentially expressed between TP53WT and TP53MUT HCC samples. Then, the influence of the IPM on the immune microenvironment in HCC was comprehensively analysed.FindingsTP53 mutation resulted in the downregulation of the immune response in HCC. Thirty-seven of the 312 immune response-related genes were differentially expressed based on TP53 mutation status. An IPM was established and validated based on 865 patients with HCC to differentiate patients with a low or high risk of poor survival. A nomogram was also established for clinical application. Functional enrichment analysis showed that the humoral immune response and immune system diseases pathway represented the major function and pathway, respectively, related to the IPM genes. Moreover, we found that the patients in the high-risk group had higher fractions of T cells follicular helper, T cells regulatory (Tregs) and macrophages M0 and presented higher expression of CTLA-4, PD-1 and TIM-3 than the low-risk group.InterpretationTP53 mutation is strongly related to the immune microenvironment in HCC. Our IPM, which is sensitive to TP53 mutation status, may have important implications for identifying subgroups of HCC patients with low or high risk of unfavourable survival. FUND: This work was supported by the International Science and Technology Cooperation Projects (2016YFE0107100), the Capital Special Research Project for Health Development (2014-2-4012), the Beijing Natural Science Foundation (L172055 and 7192158), the National Ten Thousand Talent Program, the Fundamental Research Funds for the Central Universities (3332018032), and the CAMS Innovation Fund for Medical Science (CIFMS) (2017-I2M-4-003 and 2018-I2M-3-001).

Project description:Background: There is not yet an effective marker in predicting the efficacy of immune checkpoint inhibitors (ICIs) in treating hepatocellular carcinoma (HCC) patients. The Gustave Roussy Immune Score (GRIm-Score) based on three objective variables, namely, neutrophil-to-lymphocyte ratio (NLR), serum albumin level (ALB), and lactate dehydrogenase (LDH), was developed as feasible prognostic indication in lung cancer patients receiving ICIs therapies. Our study aimed to adapt the GRIm-Score (HCC-GRIm-Score) in HCC patients who received ICIs therapies and thus improving the predictive ability. Methods: From January 2018 to September 2020, 261 patients who received ICIs therapy were retrospectively included and divided into training and validation groups. After determining the factors for HCC-GRIm-Score by multivariable analysis from training group, the optimized HCC-GRIm-Score was validated and compared to the original GRIm-Score and the Barcelona clinic liver cancer (BCLC) staging system. Results: One hundred sixty-one and 80 patients were assigned into the training and validation groups, respectively. Two more factors, aspartate transaminase-to-alanine transaminase ratio [hazard ratio (HR), 1.51; 95% confidence interval (CI), 0.94-2.42] and total bilirubin (HR, 1.76; 95% CI, 1.07-2.88), were identified as independent prognostic factors for overall survival (OS) and integrated in the HCC-GRIm-Score system according to the multivariable analysis. A risk score based on the HCC-GRIm-Score indicated that patients presenting high score (>2) suffered from significantly shorter median OS of 10.3 months compared to those with a low score (not reached; HR, 2.99; 95% CI, 1.89-4.75; p < 0.001). In the validation group of 80 patients, the patients presenting a high score showed an inferior OS (HR 5.62, 95% CI, 1.25-25.24; p = 0.024). HCC-GRIm-Score had the highest area under curve of 0.719 (95% CI, 0.661-0.773) compared to original GRIm-Score and BCLC staging system. Conclusion: The present study confirmed that the modified HCC-GRIm-Score system provided superior predictive ability in identifying the HCC patients potentially benefit from ICIs therapies, compared to the original GRIm-Score and the BCLC staging system.