Construction and Validation of a Reliable Six-Gene Prognostic Signature Based on the TP53 Alteration for Hepatocellular Carcinoma

DNA damage repair molecular subtype derived immune signature applicable for the prognosis and immunotherapy response prediction in colon cancer

Background

The DNA damage repair (DDR) pathway is one of the pathways of tumor pathogenesis, but its relationship with the immunophenotype has not been clarified in colon cancer (CC).

Methods

We identified the differentially expressed immune-related genes (DEIRGs) between two DDR molecular subtypes, namely, C1 and C2, and used univariate Cox analysis and least absolute shrinkage and selection operator (LASSO) penalized Cox regression analysis to construct the risk score in the training cohort [n=1,009, a combination of The Cancer Genome Atlas (TCGA) and GSE39582]. Regarding the median risk score as the unified cutoff to classify the patients into high- and low-risk groups. Two independent cohorts (GSE17538, n=232; GSE38832, n=122) were used for external validation of the prognostic value of the risk score. The IMvigor210 cohort (n=348) was used to test the predictive value of the risk score for immunotherapy response. Gene set variation analysis (GSVA) and gene set enrichment analysis (GSEA) were performed to discover the underlying mechanism. Immune cell infiltration was quantified by the single sample gene set enrichment analysis (ssGSEA) algorithm.

Results

The high-risk group showed significantly reduced overall survival (OS), disease-specific survival (DSS), disease-free survival (DFS), progression-free survival (PFS), and relapse-free survival (RFS) compared to the low-risk group, and the two groups differed significantly in lymphatic invasion, American Joint Committee on Cancer (AJCC) TNM stage, preoperative carcinoembryonic antigen (CEA) level, etc. The enrichment levels of pathways related to colorectal cancer, epithelial-mesenchymal transition (EMT), angiogenesis, hypoxia, P53, TGF-β, KRAS signaling, etc., were upregulated in the high-risk group, but DDR-related pathways were defective in the high-risk group. The immunophenotypes of the high-risk group tended to be desert and excluded, and the risk score of patients who responded to immunotherapy was significantly lower than that of patients who did not respond to immunotherapy. The higher the infiltration levels of gamma delta T cells (γδ T cells), immature dendritic cells, and T follicular helper (Tfh) cells, the more significant adverse impact on the prognosis of CC patients was exhibited and an obviously positive correlation with the risk score was showed.

Conclusions

An immune gene risk score associated with the DDR molecular subtype was built and verified herein; that is applicable to the prognosis and immunotherapy response prediction in CC.

Tissue-specific biological aging predicts progression in prostate cancer and acute myeloid leukemia

Introduction

Chronological aging is a well-recognized diagnostic and prognostic factor in multiple cancer types, yet the role of biological aging in manifesting cancer progression has not been fully explored yet.

Methods

Given the central role of chronological aging in prostate cancer and AML incidence, here we investigate a tissue-specific role of biological aging in prostate cancer and AML progression. We have employed Cox proportional hazards modeling to associate biological aging genes with cancer progression for patients from specific chronological aging groups and for patients with differences in initial cancer aggressiveness.

Results

Our prostate cancer-specific investigations nominated four biological aging genes (CD44, GADD45B, STAT3, GFAP) significantly associated with time to disease progression in prostate cancer in Taylor et al. patient cohort. Stratified survival analysis on Taylor dataset and validation on an independent TCGA and DKFZ PRAD patient cohorts demonstrated ability of these genes to predict prostate cancer progression, especially for patients with higher Gleason score and for patients younger than 60 years of age. We have further tested the generalizability of our approach and applied it to acute myeloid leukemia (AML). Our analysis nominated three AML-specific biological aging genes (CDC42EP2, CDC42, ALOX15B) significantly associated with time to AML overall survival, especially for patients with favorable cytogenetic risk score and for patients older than 56 years of age.

Discussion

Comparison of the identified PC and AML markers to genes selected at random and to known markers of progression demonstrated robustness of our results and nominated the identified biological aging genes as valuable markers of prostate cancer and AML progression, opening new avenues for personalized therapeutic management and potential novel treatment investigations.

Metabolism-related signatures is correlated with poor prognosis and immune infiltration in hepatocellular carcinoma via multi-omics analysis and basic experiments

Background

Metabolism is an ordered series of biological processes that occur in an organism. Altered cellular metabolism is often closely associated with the development of cancer. The aim of this research was to construct a model by multiple metabolism-related molecules to diagnose and assess the prognosis of patients.

Method

WGCNA analysis was used to screen out differential genes. GO, KEGG are used to explore potential pathways and mechanisms. The lasso regression model was used to filter out the best indicators to construct the model. Single-sample GSEA (ssGSEA) assess immune cells abundance, immune terms in different Metabolism Index (MBI) groups. Human tissues and cells were used to verify the expression of key genes.

Result

WGCNA clustering grouped genes into 5 modules, of which 90 genes from the MEbrown module were selected for subsequent analysis. GO analysis was found that BP mainly has mitotic nuclear division, while KEGG pathway is enriched to Cell cycle, Cellular senescence. Mutation analysis revealed that the frequency of TP53 mutations was much higher in samples from the high MBI group than in the low MBI group. Immunoassay revealed that patients with higher MBI have higher macrophage and Regulatory T cells (Treg) abundance, while NK cells were lowly expressed in the high MBI group. RT-qPCR and immunohistochemistry (IHC) revealed that the hub genes expression is higher in cancer tissues. The expression in hepatocellular carcinoma cells was also much higher than that in normal hepatocytes.

Conclusion

In conclusion, a metabolism-related model was constructed that can be used to estimate the prognosis of hepatocellular carcinoma, and the clinical treatment of different hepatocellular carcinoma patients with medications was guided.

CD5L-associated gene analyses highlight the dysregulations, prognostic effects, immune associations, and drug-sensitivity predicative potentials of LCAT and CDC20 in hepatocellular carcinoma

BACKGROUND

The dysregulation of CD5L has been reported in hepatocellular carcinoma (HCC). However, its functions in HCC were controversial. In this study, we aimed to identify CD5L-associated pathways and markers and explore their values in HCC diagnosis, prognosis and treatment.

METHODS

HCC datasets with gene expression profiles and clinical data in TCGA and ICGC were downloaded. The immune/stroma cell infiltrations were estimated with xCell. CD5L-associated pathways and CD5L-associated genes (CD5L-AGs) were identified with gene expression comparisons and gene set enrichment analysis (GSEA). Cox regression, Kaplan-Meier survival analysis, and least absolute shrinkage and selection operator (LASSO) regression analysis were performed. The correlations of the key genes with immune/stroma infiltrations, immunoregulators, and anti-cancer drug sensitivities in HCC were investigated. At protein level, the key genes dysregulations, their correlations and prognostic values were validated in clinical proteomic tumor analysis consortium (CPTAC) database. Serum CD5L and LCAT activity in 50 HCC and 30 normal samples were evaluated and compared. The correlations of serum LCAT activity with alpha-fetoprotein (AFP), albumin (ALB) and high-density lipoprotein (HDL) in HCC were also investigated.

RESULTS

Through systemic analyses, 14 CD5L-associated biological pathways, 256 CD5L-AGs and 28 CD5L-associated prognostic and diagnostic genes (CD5L-APDGs) were identified. A risk model consisting of LCAT and CDC20 was constructed for HCC overall survival (OS), which could discriminate HCC OS status effectively in both the training and the validation sets. CD5L, LCAT and CDC20 were shown to be significantly correlated with immune/stroma cell infiltrations, immunoregulators and 31 anti-cancer drug sensitivities in HCC. At protein level, the dysregulations of CD5L, LCAT and CDC20 were confirmed. LCAT and CDC20 were shown to be significantly correlated with proliferation marker MKI67. In serum, no significance of CD5L was shown. However, the lower activity of LCAT in HCC serum was obvious, as well as its significant positive correlations ALB and HDL concentrations.

CONCLUSIONS

CD5L, LCAT and CDC20 were dysregulated in HCC both at mRNA and protein levels. The LCAT-CDC20 signature might be new predicator for HCC OS. The associations of the three genes with HCC microenvironment and anti-cancer drug sensitivities would provide new clues for HCC immunotherapy and chemotherapy.

Comprehensive analysis of metabolic pathway activity subtypes derived prognostic signature in hepatocellular carcinoma

OBJECTIVE

Metabolic reprogramming is one of the hallmarks of cancer, but metabolic pathway activity-related subtypes of hepatocellular carcinoma (HCC) have not been identified.

METHODS

Based on the quantification results of 41 metabolic pathway activities by gene set variation analysis, the training cohort (n = 609, merged by TCGA and GSE14520) was clustered into three subtypes (C1, C2, and C3) with the nonnegative matrix factorization method. Totally 1371 differentially expressed genes among C1, C2, and C3 were identified, and an 8-gene risk score was established by univariable Cox regression analysis, least absolute shrinkage and selection operator method, and multivariable Cox regression analysis.

RESULTS

C1 had the strongest metabolic activity, good prognosis, the highest CTNNB1 mutation rate, with massive infiltration of eosinophils and natural killer cells. C2 had the weakest metabolic activity, poor prognosis, was younger, was inclined to vascular invasion and advanced stage, had the highest TP53 mutation rate, exhibited a higher expression level of immune checkpoints, accompanied by massive infiltration of regulatory T cells. C3 had moderate metabolic activity and prognosis, the highest LRP1B mutation rate, and a higher infiltration level of neutrophils and macrophages. Internal cohorts (TCGA, n = 370; GSE14520, n = 239), external cohorts (ICGC, n = 231; GSE116174, n = 64), and clinical subgroup validation showed that the risk score was applicable for patients with diverse clinical features and was effective in predicting the prognosis and malignant progression of patients with HCC. Compared with the low-risk group, the high-risk group had a poor prognosis, enhanced cancer stem cell characteristics, activated DNA damage repair, weakened metabolic activity, cytolytic activity, and interferon response.

CONCLUSION

We identified HCC subtypes from the perspective of metabolism-related pathway activity and proposed a robust prognostic signature for HCC.

A Five-Gene Signature Associated With DNA Damage Repair Molecular Subtype Predict Overall Survival for Hepatocellular Carcinoma

Background: DNA damage repair (DDR) is an important mechanism for the occurrence and development of hepatocellular carcinoma (HCC), but its impact on prognosis has not been fully understood.

Materials and methods: A total of 904 HCC patients were included in our study, TCGA (n = 370) and GSE14520 (n = 239) were merged into a large-sample training cohort (n = 609). The training cohort was clustered into C1 and C2 based on prognostic DDR-related genes, the differentially expressed genes (DEGs) between C1 and C2 were identified by the Wilcoxon signed-rank test referred to criteria (|log2FC|≥1 and FDR< 0.05). The univariate Cox analysis was used to screen the prognostic-related DEGs, and Lasso penalized Cox regression analysis was used to construct the risk score. The patients were clarified into high- and low-risk groups based on the median risk score. ICGC (n = 231) and GSE116174 (n = 64) cohorts were used for external validation of the risk score’s prognostic value.

Results: The Kaplan–Meier survival analysis showed that the high-risk group had a significantly reduced overall survival (OS) compared to the low-risk group in the three independent cohorts, and the time-dependent ROC curve showed that the five-gene (STMN1, PON1, PLOD2, MARCKSL1, and SPP1) risk score with a high accuracy in predicting OS. The patients with AFP >300 ng/ml, tumor poor differentiation (grade 3–4), micro and macro vascular tumor invasion, advanced stage (AJCC III-IV, BCLC stage B-C, and CLIP score >2) exhibited a higher risk score. Subgroup survival analysis found that the risk score was applicable to patients with different clinical characteristics. GO and KEGG functional enrichment analysis revealed that cell cycle, p53 signaling, TNF signaling-related pathways were upregulated in the high-risk group. The higher infiltration level of activated CD4 T cell, CD56 bright natural killer cell, plasmacytoid dendritic cell, and type 2 T helper cells were found to lead an unfavorable impact on the OS of HCC patients, and these four kinds of immune cells exhibited a higher infiltration level in the high-risk group.

Conclusion: The five-gene risk score proposed in the research may provide new insights into the individualized evaluation of HCC prognosis.

A Ferroptosis and Pyroptosis Molecular Subtype-Related Signature Applicable for Prognosis and Immune Microenvironment Estimation in Hepatocellular Carcinoma

Background: Due to the heterogeneity of tumors and the complexity of the immune microenvironment, the specific role of ferroptosis and pyroptosis in hepatocellular carcinoma (HCC) is not fully understood, especially its impact on prognosis.

Methods: The training set (n = 609, merged by TCGA and GSE14520) was clustered into three subtypes (C1, C2, and C3) based on the prognosis-related genes associated with ferroptosis and pyroptosis. The intersecting differentially expressed genes (DEGs) among C1, C2, and C3 were used in univariate Cox and LASSO penalized Cox regression analysis for the construction of the risk score. The median risk score served as the unified cutoff to divide patients into high- and low-risk groups.

Results: Internal (TCGA, n = 370; GSE14520, n = 239) and external validation (ICGC, n = 231) suggested that the 12-gene risk score had high accuracy in predicting the OS, DSS, DFS, PFS, and RFS of HCC. As an independent prognostic indicator, the risk score could be applicable for patients with different clinical features tested by subgroup (n = 26) survival analysis. In the high-risk patients with a lower infiltration abundance of activated B cells, activated CD8 T cells, eosinophils, and type I T helper cells and a higher infiltration abundance of immature dendritic cells, the cytolytic activity, HLA, inflammation promotion, and type I IFN response in the high-risk group were weaker. The TP53 mutation rate, TMB, and CSC characteristics in the high-risk group were significantly higher than those in the low-risk group. Low-risk patients have active metabolic activity and a more robust immune response. The high- and low-risk groups differed significantly in histology grade, vascular tumor cell type, AFP, new tumor event after initial treatment, main tumor size, cirrhosis, TNM stage, BCLC stage, and CLIP score.

Conclusion: The ferroptosis and pyroptosis molecular subtype-related signature identified and validated in this work is applicable for prognosis prediction, immune microenvironment estimation, stem cell characteristics, and clinical feature assessment in HCC.

Identification and validation of a novel immune-related signature associated with macrophages and CD8 T cell infiltration predicting overall survival for hepatocellular carcinoma

BACKGROUND

Although the effects of macrophages and CD8 T cell infiltration on clinical outcome have been widely reported, the association between immunity-associated gene with them for hepatocellular carcinoma (HCC) remains unclear.

MATERIALS AND METHODS

The ssGSEA served for quantifying the macrophages as well as CD8 T cell infiltration in the HCC samples obtained from TCGA database. Kaplan-Meier (KM) survival assay was used to determine the associations between macrophages and CD8 T cell infiltration with OS. LASSO Cox regressive method assisted in developing an immune gene signature as well as building a risk score. The performance was evaluated by the time-dependent ROC together with the KM survival analysis. The ICGC database were adopted for external verification. CIBERSORT was applied to the correlation analysis on the immune-related signature and the immunocyte infiltration. GSEA were employed exploring the underlying molecular mechanisms.

RESULTS

Increased CD8+ T cell infiltration was associated with longer OS, whereas a greater infiltration of macrophages was related to shorter OS. There were 398 differential expression genes (DEGs) between the high- and low infiltration groups with the "edgeR" package. An prognostic signature consisted of 10 immune genes was built in TCGA and examined in ICGC. The uniform cutoff (0.927) was adopted for separating sufferers into the high-risk (HR) and low-risk (LR) groups. The ROC curves revealed that the AUC data for this signature predicting 1, 2, 3, 4 and 5 year were all above 0.7 in both TCGA and ICGC cohort and patients in the HR group exhibited an evidently weaker prognostic results compared with the LR group. The HR group presented evidently greater Tregs and Macrophage M0 relative to the LR group, whereas the LR group saw the enrichment of CD8 T cells.

CONCLUSION

The immune signature associated with macrophages as well as CD8 T cell infiltration has reliable prognostic and predictive value for HCC patients.