Dataset Information

RECK expression is associated with angiogenesis and immunogenic Tumor Microenvironment in Hepatocellular Carcinoma, and is a prognostic factor for better survival.

ABSTRACT: Angiogenesis and immunosuppression have been described as closely related processes that can occur in parallel. As an inhibitor of matrix metalloproteinase, whether the level of reversion-inducing cysteine-rich protein with Kazal motifs (RECK) in hepatocellular carcinoma (HCC) reflects a link between angiogenesis and immunosuppression is still unknown. We analyzed RNA expression, immune infiltration and survival of HCC from The Cancer Genome Atlas databases. Immune scores and stromal scores were calculated based on the ESTIMATE algorithm to quantify the immune and stromal components in HCC. The association between RECK and clinicopathological features was further investigated by immunohistochemistry on tissue microarray. We found that the prognosis of patients with high RECK expression was significantly better than that of patients with low RECK expression. High RECK expression was associated with high ESTIMATE Score, recruitment of more tumor-infiltrating lymphocytes, low tumor purity, and high PD-L1 expression. In addition, positive RECK expression was associated with a lower incidence of vascular invasion and recurrence, a lower level of alpha fetoprotein (AFP) and microvessel density and a better tumor differentiation. Multivariate analyses revealed that reduced RECK expression was an independent prognostic factor for recurrence and poor prognosis. In conclusion, high RECK expression reflects an immunogenic and hypovascularity status in HCC. RECK is a promising prognostic marker for survival of HCC and may act as a complementary indicator for patients to receive anti-angiogenic therapy or immunotherapy.

SUBMITTER: Dong ZR

PROVIDER: S-EPMC8176247 | biostudies-literature | 2021

REPOSITORIES: biostudies-literature

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RECK expression is associated with angiogenesis and immunogenic Tumor Microenvironment in Hepatocellular Carcinoma, and is a prognostic factor for better survival.

Dong Zhao-Ru ZR Chen Zhi-Qiang ZQ Yang Xiao-Yun XY Ding Zi-Niu ZN Liu Kai-Xuan KX Yan Lun-Jie LJ Meng Guang-Xiao GX Yang Ya-Fei YF Yan Yu-Chuan YC Yao Sheng-Yu SY Yang Chun-Cheng CC Zhi Xu-Ting XT Li Tao T

Journal of Cancer 20210505 13

Angiogenesis and immunosuppression have been described as closely related processes that can occur in parallel. As an inhibitor of matrix metalloproteinase, whether the level of reversion-inducing cysteine-rich protein with Kazal motifs (RECK) in hepatocellular carcinoma (HCC) reflects a link between angiogenesis and immunosuppression is still unknown. We analyzed RNA expression, immune infiltration and survival of HCC from The Cancer Genome Atlas databases. Immune scores and stromal scores were ...[more]

PMID: 34093791

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Project description:Background: Hepatocellular carcinoma (HCC) is one of the most common malignant tumors in the world. The efficacy of immunotherapy usually depends on the interaction of immunomodulation in the tumor microenvironment (TME). This study aimed to explore the potential stromal-immune score-based prognostic genes related to immunotherapy in HCC through bioinformatics analysis. Methods: ESTIMATE algorithm was applied to calculate the immune/stromal/Estimate scores and tumor purity of HCC using the Cancer Genome Atlas (TCGA) transcriptome data. Functional enrichment analysis of differentially expressed genes (DEGs) was analyzed by the Database for Annotation, Visualization, and Integrated Discovery database (DAVID). Univariate and multivariate Cox regression analysis and least absolute shrinkage and selection operator (LASSO) regression analysis were performed for prognostic gene screening. The expression and prognostic value of these genes were further verified by KM-plotter database and the Human Protein Atlas (HPA) database. The correlation of the selected genes and the immune cell infiltration were analyzed by single sample gene set enrichment analysis (ssGSEA) algorithm and Tumor Immune Estimation Resource (TIMER). Results: Data analysis revealed that higher immune/stromal/Estimate scores were significantly associated with better survival benefits in HCC within 7 years, while the tumor purity showed a reverse trend. DEGs based on both immune and stromal scores primarily affected the cytokine-cytokine receptor interaction signaling pathway. Among the DEGs, three genes (CASKIN1, EMR3, and GBP5) were found most significantly associated with survival. Moreover, the expression levels of CASKIN1, EMR3, and GBP5 genes were significantly correlated with immune/stromal/Estimate scores or tumor purity and multiple immune cell infiltration. Among them, GBP5 genes were highly related to immune infiltration. Conclusion: This study identified three key genes which were related to the TME and had prognostic significance in HCC, which may be promising markers for predicting immunotherapy outcomes.

Project description:PurposeHepatocellular carcinoma (HCC) is characterized by a poor prognosis and a high recurrence rate. The tumor immune microenvironment in HCC has been characterized as shifted toward immunosuppression. We conducted a genomic data-driven classification of immune microenvironment HCC subtypes. In addition, we demonstrated their prognostic value and suggested a potential therapeutic targeting strategy.MethodsRNA sequencing data from The Cancer Genome Atlas-Liver Hepatocellular Carcinoma was used (n = 366). Abundance of immune cells was imputed using CIBERSORT and visualized using unsupervised hierarchic clustering. Overall survival (OS) was analyzed using Kaplan-Meier estimates and Cox regression. Differential expression and gene set enrichment analyses were conducted on immune clusters with poor OS and high programmed death-1 (PD-1)/programmed death-ligand 1 (PD-L1) coexpression. A scoring metric combining differentially expressed genes and immune cell content was created, and its prognostic value and immune checkpoint blockade response prediction was evaluated.ResultsTwo clusters were characterized by macrophage enrichment, with distinct M0Hi and M2Hi subtypes. M2Hi (P = .038) and M0Hi (P = .018) were independently prognostic for OS on multivariable analysis. Kaplan-Meier estimates demonstrated that patients in M0Hi and M2Hi treated with sorafenib had decreased OS (P = .041), and angiogenesis hallmark genes were enriched in the M0Hi group. CXCL6 and POSTN were overexpressed in both the M0Hi and the PD-1Hi/PD-L1Hi groups. A score consisting of CXCL6 and POSTN expression and absolute M0 macrophage content was discriminatory for OS (intermediate: hazard ratio [HR], 1.59; P ≤ .001; unfavorable: HR, 2.08; P = .04).ConclusionDistinct immune cell clusters with macrophage predominance characterize an aggressive HCC phenotype, defined molecularly by angiogenic gene enrichment and clinically by poor prognosis and sorafenib response. This novel immunogenomic signature may aid in stratification of unresectable patients to receive checkpoint inhibitor and antiangiogenic therapy combinations.

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

RECK expression is associated with angiogenesis and immunogenic Tumor Microenvironment in Hepatocellular Carcinoma, and is a prognostic factor for better survival.

Publications

RECK expression is associated with angiogenesis and immunogenic Tumor Microenvironment in Hepatocellular Carcinoma, and is a prognostic factor for better survival.

Similar Datasets

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