Project description:BackgroundDue to the phenotypic and molecular diversity of hepatocellular carcinomas (HCC), it is still a challenge to determine patients' prognosis. We aim to identify new prognostic markers for resected HCC patients.Methods274 patients were retrospectively identified and samples collected from Zhongshan hospital, Fudan University. We analyzed the gene expression patterns of tumors and compared expression patterns with patient survival times. We identified a "9-gene signature" associated with survival by using the coefficient and regression formula of multivariate Cox model. This molecular signature was then validated in three patients cohorts from internal cohort (n = 69), TCGA (n = 369) and GEO dataset (n = 80).ResultsWe identified 9-gene signature consisting of ZC2HC1A, MARCKSL1, PTGS1, CDKN2B, CLEC10A, PRDX3, PRKCH, MPEG1 and LMO2. The 9-gene signature was used, combined with clinical parameters, to fit a multivariable Cox model to the training cohort (concordance index, ci = 0.85), which was successfully validated (ci = 0.86 for internal cohort; ci = 0.78 for in silico cohort). The signature showed improved performance compared with clinical parameters alone (ci = 0.70). Furthermore, the signature predicted patient prognosis than previous gene signatures more accurately. It was also used to stratify early-stage, HBV or HCV-infected patients into low and high-risk groups, leading to significant differences in survival in training and validation (P < 0.001).ConclusionsThe 9-gene signature, in which four were upregulated (ZC2HC1A, MARCKSL1, PTGS1, CDKN2B) and five (CLEC10A, PRDX3, PRKCH, MPEG1, LMO2) were downregulated in HCC with poor prognosis, stratified HCC patients into low and high risk group significantly in different clinical settings, including receiving adjuvant transarterial chemoembolization and especially in early stage disease. This new signature should be validated in prospective studies to stratify patients in clinical decisions.

Project description:Background: IL-33, a cytokine with pleiotropic functions, is elevated in serum of patients with hepatocellular carcinoma (HCC). This study investigated effects of local IL-33 expression in resected HCC on patient survival and on immunological and molecular tumor microenvironment. Methods: Tissue of resected HCCs was stained for H&E, masson trichrome, alpha smooth muscle actin, IL-33, CD8 and IL-13 and analysed by flow cytometry. Besides histomorphologic evaluation, the immunohistochemical stainings were analysed for the respective cell numbers separately for tumor area, infiltrative margin and distant liver stroma. These findings were correlated with clinical data and patient outcome. Further, gene expression of different HCC risk groups was compared using Micro Arrays. Results: In multivariable analysis, infiltration of HCCs by IL-33+ cells (P=0.032) and CD8+ cells (P=0.014) both independently were associated with prolonged patient survival. Flow cytometry demonstrated that cytotoxically active CD8+CD62L-KLRG1+CD107a+ effectory-memory cells are the main producers of IL-33 in these HCC patients. Using infiltration by IL-33+ and CD8+ cells as two separate factors, a HCC immune score (HCCIS) was designed and evaluated that stratified patient survival (P=0.0004). This HCCIS identified high and low risk patients who differ in gene expression profiles (P<0.001). Conclusion: Infiltration of HCCs by IL-33+ and CD8+ cells is independently associated with prolonged patient survival. We suggest that this is due to an induction of highly effective cytotoxically active CD8+CD62L-KLRG1+CD107a+ effector-memory cells producing IL-33. Based on these two independent factors we established a HCC immune score that provides risk stratification for HCC patients and can be used in the clinical setting. To investigate if HCCIS 0 high risk and HCCIS 2 low risk tumors exhibit a distinct molecular environment and gene expression pattern, RNA from fresh tumor tissue was isolated and analyzed by whole genome Microarray 4 patients with low risk tumors (HCCIS 2) were compared to 4 patients with high risk tumors (HCCIS 0).

Project description:Background: IL-33, a cytokine with pleiotropic functions, is elevated in serum of patients with hepatocellular carcinoma (HCC). This study investigated effects of local IL-33 expression in resected HCC on patient survival and on immunological and molecular tumor microenvironment. Methods: Tissue of resected HCCs was stained for H&E, masson trichrome, alpha smooth muscle actin, IL-33, CD8 and IL-13 and analysed by flow cytometry. Besides histomorphologic evaluation, the immunohistochemical stainings were analysed for the respective cell numbers separately for tumor area, infiltrative margin and distant liver stroma. These findings were correlated with clinical data and patient outcome. Further, gene expression of different HCC risk groups was compared using Micro Arrays. Results: In multivariable analysis, infiltration of HCCs by IL-33+ cells (P=0.032) and CD8+ cells (P=0.014) both independently were associated with prolonged patient survival. Flow cytometry demonstrated that cytotoxically active CD8+CD62L-KLRG1+CD107a+ effectory-memory cells are the main producers of IL-33 in these HCC patients. Using infiltration by IL-33+ and CD8+ cells as two separate factors, a HCC immune score (HCCIS) was designed and evaluated that stratified patient survival (P=0.0004). This HCCIS identified high and low risk patients who differ in gene expression profiles (P<0.001). Conclusion: Infiltration of HCCs by IL-33+ and CD8+ cells is independently associated with prolonged patient survival. We suggest that this is due to an induction of highly effective cytotoxically active CD8+CD62L-KLRG1+CD107a+ effector-memory cells producing IL-33. Based on these two independent factors we established a HCC immune score that provides risk stratification for HCC patients and can be used in the clinical setting. To investigate if HCCIS 0 high risk and HCCIS 2 low risk tumors exhibit a distinct molecular environment and gene expression pattern, RNA from fresh tumor tissue was isolated and analyzed by whole genome Microarray

Project description:BackgroundMAPK-RAP1A signaling, which is involved in cancer progression, remains to be defined. Upregulation of MAPK-RAP1A signaling accounts for most cancers that harbor high incident rate, such as non-small cell lung cancer (NSCLC) and pancreatic cancer, especially in hepatocellular carcinoma (HCC). MAPK-RAP1A signaling plays an important function as clinical diagnosis and prognostic value in cancers, and the role of MAPK-RAP1A signaling related with immune infiltration for HCC should be elucidated.MethodsMicroarray data and patient cohort information from The Cancer Genome Atlas (TCGA; n = 425) and International Cancer Genome Consortium (ICGC; n = 405) were selected for validation. The Cox regression and least absolute shrinkage and selection operator (LASSO) were used to construct a clinical prognostic model in this analysis and validation study. We also tested the area under the curve (AUC) of the risk signature that could reflect the status of predictive power by determining model. MAPK-RAP1A signaling is also associated with tumor-infiltrating immune cells (TICs) as well as clinical parameters in HCC. The GSEA and CIBERSORT were used to calculate the proportion of TICs, which should be beneficial for the clinical characteristics (clinical stage, distant metastasis) and positively correlated with the survival of HCC patients.ResultsHCC patients with enrichment of MAPK-RAP1A signaling were associated with clinical characteristics and favorable T cell gamma delta (Vδ T cells), and STMN1, RAP1A, FLT3, HSPA8, ANGPT2, and PGF were used as candidate biomarkers for risk scores of HCC. To determine the molecular mechanism of this signature gene association, Gene Set Enrichment Analysis (GSEA) was proposed. Cytokine-cytokine receptor interaction, TGF-β signaling pathway, and Intestinal immune network for IgA production gene sets were closely related in MAPK-RAP1A gene sets. Thus, we established a novel prognostic prediction of HCC to deepen learning of MAPK-RAP1A signaling pathways.ConclusionOur findings demonstrated that HCC patients with enrichment of MAPK-RAP1A signaling were associated with clinical characteristics and favorable T cell gamma delta (Vδ T cells), which may be a novel prognostic prediction of HCC.

Project description:Tumor-infiltrating leukocytes (TILs) are immune cells surrounding tumor cells, and several studies have shown that TILs are potential survival predictors in different cancers. However, few studies have dissected the differences between hepatitis B- and hepatitis C-related hepatocellular carcinoma (HBV-HCC and HCV-HCC). Therefore, we aimed to determine whether the abundance and composition of TILs are potential predictors for survival outcomes in HCC and which TILs are the most significant predictors. Two bioinformatics algorithms, ESTIMATE and CIBERSORT, were utilized to analyze the gene expression profiles from 6 datasets, from which the abundance of corresponding TILs was inferred. The ESTIMATE algorithm examined the overall abundance of TILs, whereas the CIBERSORT algorithm reported the relative abundance of 22 different TILs. Both HBV-HCC and HCV-HCC were analyzed. The results indicated that the total abundance of TILs was higher in non-tumor tissue regardless of the HCC type. Alternatively, the specific TILs associated with overall survival (OS) and recurrence-free survival (RFS) varied between subtypes. For example, in HBV-HCC, plasma cells (hazard ratio [HR] = 1.05; 95% CI 1.00-1.10; p = 0.034) and activated dendritic cells (HR = 1.08; 95% CI 1.01-1.17; p = 0.03) were significantly associated with OS, whereas in HCV-HCC, monocytes (HR = 1.21) were significantly associated with OS. Furthermore, for RFS, CD8+ T cells (HR = 0.98) and M0 macrophages (HR = 1.02) were potential biomarkers in HBV-HCC, whereas neutrophils (HR = 1.01) were an independent predictor in HCV-HCC. Lastly, in both HBV-HCC and HCV-HCC, CD8+ T cells (HR = 0.97) and activated dendritic cells (HR = 1.09) had a significant association with OS, while γ delta T cells (HR = 1.04), monocytes (HR = 1.05), M0 macrophages (HR = 1.04), M1 macrophages (HR = 1.02), and activated dendritic cells (HR = 1.15) were highly associated with RFS. Conclusions: These findings demonstrated that TILs are potential survival predictors in HCC and different kinds of TILs are observed according to the virus type. Therefore, further investigations are warranted to elucidate the role of TILs in HCC, which may improve immunotherapy outcomes.

Dataset Information

Perivascular Tumor-Infiltrating Leukocyte Scoring for Prognosis of Resected Hepatocellular Carcinoma Patients.

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Perivascular Tumor-Infiltrating Leukocyte Scoring for Prognosis of Resected Hepatocellular Carcinoma Patients.

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