A Prognostic Gene Signature for Hepatocellular Carcinoma

Construction of a Lung Adenocarcinoma Prognostic Model Utilizing Serine and Glycine Metabolism-Related Genes

The objective of this study was to construct a prognostic model by utilizing serine/glycine metabolism-related genes (SGMGs), thus establishing a risk score for lung adenocarcinoma (LUAD). Based on the TCGA-LUAD and SGMG data set, two subtypes with different SGMG expression levels were identified by clustering analysis. Thirteen differential expression genes were used to construct RiskScore by Cox regression. GSE72094 data set was used for validation. The survival characteristics, immune features, and potential benefits of chemotherapy drugs were analyzed for two risk groups. RiskScore was constructed based on the genes ABCC12, RIC3, CYP4B1, SFTPB, CACNA2D2, IGF2BP1, NTSR1, DKK1, CREG2, PITX3, RGS20, FETUB, and IGFBP1. Patients in the low-risk (LR) group exhibited a superior overall survival. In addition, aDCs, iDSs, mast cells, neutrophils, HLA, and type II IFN were more abundant in the LR group with higher IPS scores and lower TIDE scores. In contrast, NK cells, APC coinhibition, and MHC-I were more common in the high-risk (HR) group, which may be more sensitive to chemotherapy drugs such as cisplatin, oxaliplatin, and nilotinib. RiskScore was a promising biomarker that can be used to distinguish LUAD prognosis, immune features, and sensitivity to chemotherapy drugs.

Unleashing the potential of gene signatures as prognostic and predictive tools: A step closer to personalized medicine in hepatocellular carcinoma (HCC)

Hepatocellular carcinoma (HCC) is one of the growing malignancies globally, affecting a myriad of people and causing numerous cancer-related deaths. Despite therapeutic improvements in treatment strategies over the past decades, HCC still remains one of the leading causes of person-years of life lost. Numerous studies have been conducted to assess the characteristics of HCC with the aim of predicting its prognosis and responsiveness to treatment. However, the identified biomarkers have shown limited sensitivity, and the translation of these findings into clinical practice has faced challenges. The development of sequencing techniques has facilitated the exploration of a wide range of genes, leading to the emergence of gene signatures. Although several studies assessed differentially expressed genes in normal and HCC tissues to find the unique gene signature with prognostic value, to date, no study has reviewed the task, and to the best of our knowledge, this review represents the first comprehensive analysis of relevant studies in HCC. Most gene signatures focused on immune-related genes, while others investigated genes related to metabolism, autophagy, and apoptosis. Even though no identical gene signatures were found, NDRG1, SPP1, BIRC5, and NR0B1 were the most extensively studied genes with prognostic value. Finally, despite challenges such as the lack of consistent patterns in gene signatures, we believe that comprehensive analysis of pertinent gene signatures will bring us a step closer to personalized medicine in HCC, where treatment strategies can be tailored to individual patients based on their unique molecular profiles.

A prognostic signature based on seven T-cell-related cell clustering genes in bladder urothelial carcinoma

Bladder urothelial carcinoma (BLCA) is one of the most common cancer-related deaths in the world, along with high mortality. Due to the difficult detection of early symptoms, the treatment for this disease is still dissatisfactory. Thus, the current research hotspot is beginning to focus on the immune microenvironment in this disease, aiming to provide guidance for diagnosis and treatment. In this study, the single-cell RNA sequencing data downloaded from the gene expression omnibus database was used to classify the immune cells of BLCA. And the final seven T-cell-related cell clustering genes associated with BLCA prognosis (HSPA2, A2M, JUN, PDGFRB, GBP2, LGALS1, and GAS6) were screened out, and then used for constructing the prognostic model against BLCA based on the Cox and LASSO regression analysis. Satisfactorily, the model could efficiently evaluate the overall survival of BLCA and had the potential to be applied for the clinic treatment. Moreover, we also revealed that the difference in immune infiltration levels and gene mutation might account for the diverse prognosis in BLCA patients. In a word, our findings provided a novel insight for designing efficient immunotherapies for BLCA.

Can MRI features predict clinically relevant hepatocellular carcinoma genetic subtypes?

PURPOSE

Recent studies in cancer genomics have revealed core drivers for hepatocellular carcinoma (HCC) pathogenesis. We aim to study whether MRI features can serve as non-invasive markers for the prediction of common genetic subtypes of HCC.

METHODS

Sequencing of 447 cancer-implicated genes was performed on 43 pathology proven HCC from 42 patients, who underwent contrast-enhanced MRI followed by biopsy or resection. MRI features were retrospectively evaluated including tumor size, infiltrative tumor margin, diffusion restriction, arterial phase hyperenhancement, non-peripheral washout, enhancing capsule, peritumoral enhancement, tumor in vein, fat in mass, blood products in mass, cirrhosis and tumor heterogeneity. Fisher's exact test was used to correlate genetic subtypes with imaging features. Prediction performance using correlated MRI features for genetic subtype and inter-reader agreement were assessed.

RESULTS

The two most prevalent genetic mutations were TP53 (13/43, 30%) and CTNNB1 (17/43, 40%). Tumors with TP53 mutation more often demonstrated an infiltrative tumor margin on MRI (p = 0.01); inter-reader agreement was almost perfect (kappa = 0.95). The CTNNB1 mutation was associated with peritumoral enhancement on MRI (p = 0.04), inter-reader agreement was substantial (kappa = 0.74). The MRI feature of an infiltrative tumor margin correlated with the TP53 mutation with accuracy, sensitivity, and specificity of 74.4%, 61.5% and 80.0%, respectively. Peritumoral enhancement correlated with the CTNNB1 mutation with accuracy, sensitivity, and specificity of 69.8%, 47.0% and 84.6%, respectively.

CONCLUSION

An infiltrative tumor margin on MRI correlated with TP53 mutation and peritumoral enhancement correlated with CTNNB1 mutation in HCC. Absence of these MRI features are potential negative predictors of the respective HCC genetic subtypes that have implications for prognosis and treatment response.

Identification and Characterization of an Ageing-Associated 13-lncRNA Signature That Predicts Prognosis and Immunotherapy in Hepatocellular Carcinoma

Background

In cancer pathology, cell senescence not only alters cell function but also reshapes the immune microenvironments in tumours. However, the association between cell senescence, tumour microenvironment, and disease progression of hepatocellular carcinoma (HCC) is yet to be fully understood. Therefore, the role of cell senescence-related genes and long noncoding RNAs (lncRNAs) in evaluating the clinical prognosis and immune cell infiltration (ICI) of HCC patients requires further investigation.

Methods

The limma R package was utilised to investigate differentially expressed genes according to the multiomics data. The CIBERSORT R package was utilised to assess ICI, and unsupervised cluster analysis was conducted using the R software's ConsensusClusterPlus package. A polygenic prognostic model of lncRNAs was constructed by conducting univariate and least absolute shrinkage and selection operator (Lasso) cox proportional-hazards regression analyses. The time-dependent receiver operating characteristic (ROC) curves were used for validation. We utilised the survminer R package to evaluate the tumour mutational burden (TMB). Moreover, the gene set enrichment analysis (GSEA) helped in pathway enrichment analysis, and the immune infiltration level of the model was evaluated using the IMvigor210 cohort.

Results

The identification of 36 prognosis-related genes was achieved based on their differential expression between healthy and liver cancer tissues. Liver cancer individuals were categorised into 3 independent senescence subtypes using the gene list, revealing considerable survival differences (variations). We observed that the prognosis of patients in the ARG-ST2 subtype was substantially better as compared to that in the ARG-ST3 subtype. Differences were observed in gene expression profiles among the three subtypes, with the differentially expressed genes predominantly associated with cell cycle control. The enrichment of upregulated genes in the ARG-ST3 subtype was observed in pathways related to biological processes, for instance, organelle fission, nuclear division, and chromosome recombination. ICI in the ARG-ST1 and ARG-ST2 subtypes, with relatively better prognosis, was substantially higher as compared to the ARG-ST3 subtype. Furthermore, a risk-score model, which can be employed as a reliable prognostic factor in an independent manner for individuals suffering from liver cancer, was constructed based on 13 cell senescence-related lncRNAs (MIR99AHG, LINC01224, LINC01138, SLC25A30AS1, AC006369.2, SOCS2AS1, LINC01063, AC006037.2, USP2AS1, FGF14AS2, LINC01116, KIF25AS1, and AC002511.2). The individuals with higher risk scores had noticeably poor prognoses in contrast with those having low-risk scores. Moreover, increased levels of TMB and ICI were observed in individuals with low-risk scores and gaining more benefit from immune checkpoint therapy.

Conclusion

Cell senescence is an essential factor in HCC onset and progression. We identified 13 senescence-related lncRNAs as HCC prognostic markers, which can help understand their function in the onset and progression of HCC and guide clinical diagnosis and treatment.

Six-Transmembrane Epithelial Antigen of Prostate 4: An Indicator of Prognosis and Tumor Immunity in Hepatocellular Carcinoma

Purpose

The six-transmembrane epithelial antigen of prostate 4 (STEAP4) has been linked to tumor progression via its involvement in inflammatory responses, oxidative stress, and metabolism. However, STEAP4 has rarely been studied in hepatocellular carcinoma (HCC). We explored STEAP4 expression associated with tumor prognosis to understand its role in tumor biology in HCC.

Patients and Methods

STEAP4 mRNA and protein expressions were primarily analyzed using bioinformatics tools based on The Cancer Genome Atlas database to understand the expression pattern, molecular mechanism, prognostic impact, and association with immune cell infiltration. We further investigated the association between STEAP4 protein expression and clinicopathological parameters and their predictive value in HCC patients using immunohistochemical staining of tissue microarrays.

Results

The expression of STEAP4 mRNA and protein in HCC tissues was significantly lower than in normal liver tissues. Reduced expression of STEAP4 was linked to advanced HCC stages, poor recurrence-free survival (RFS), and overall survival. Furthermore, reduced STEAP4 expression was a significant predictor of worse RFS in univariate and multivariate analyses in the immunohistochemical cohort. GO, KEGG, and GSEA analyses revealed that STEAP4 is related to numerous biological processes and pathways, including drug metabolism, DNA replication, RNA metabolism, and immune response. In terms of the immune system, the decreased level of STEAP4 was correlated with the immunosuppressive microenvironment.

Conclusion

Our data indicated that reduced STEAP4 expression was significantly associated with tumor aggressiveness and poor prognosis, possibly because of its link to various biological processes and induction of HCC immune evasion. Therefore, STEAP4 expression may serve as a potential prognostic biomarker for cancer progression and immunity, as well as a therapeutic target in HCC.

Comprehensive Analysis of Cellular Senescence-Related Genes in Prognosis, Molecular Characterization and Immunotherapy of Hepatocellular Carcinoma

BACKGROUND

Cellular senescence is a tumor suppressive response in which the cell cycle is in a state of permanent arrest and can inhibit tumor cell proliferation. In recent years, induction of cellular senescence has been shown to be important for antitumor therapy, and the link between cellular senescence and clinical prognosis and immunotherapy of hepatocellular carcinoma is still unknown.

METHODS

We performed enrichment analysis of genes in three cellular senescence gene sets, screened for gene sets significantly enriched in hepatocellular carcinoma and extracted genes from them. Signature were constructed using senescence-related genes, and their expression was verified at the protein and RNA levels. Survival, clinical staging and grading, immune infiltration, immunotherapy, and drug sensitivity were also analyzed between risk groups.

RESULTS

The q-PCR and immunohistochemistry results revealed significant differences in the expression of the signature genes between normal and tumor tissues. Significant differences in clinicopathological features, prognosis and immune infiltration were observed between risk groups. In the low-risk group, better OS and lower TMB scores were demonstrated, while the high-risk group had higher immune checkpoint expression, as well as lower risk of immune escape. In addition, we found that the High-risk group was more sensitive to sorafenib.

CONCLUSION

In summary, the signature constructed using aging-related genes can reliably predict patient prognosis and immunotherapy efficacy, providing a new idea for immune system therapy of hepatocellular carcinoma.

Identification and Characterization of Genes Related to the Prognosis of Hepatocellular Carcinoma Based on Single-Cell Sequencing

The heterogeneity of hepatocellular carcinoma (HCC) highlights the importance of precision therapy. In recent years, single-cell RNA sequencing has been used to reveal the expression of genes at the single-cell level and comprehensively study cell heterogeneity. This study combined big data analytics and single-cell data mining to study the influence of genes on HCC prognosis. The cells and genes closely related to the HCC were screened through single-cell RNA sequencing (71,915 cells, including 34,414 tumor cells) and big data analysis. Comprehensive bioinformatics analysis of the key genes of HCC was conducted for molecular classification and multi-dimensional correlation analyses, and a prognostic model for HCC was established. Finally, the correlation between the prognostic model and clinicopathological features was analyzed. 16,880 specific cells, screened from the single-cell expression profile matrix, were divided into 20 sub-clusters. Cell typing revealed that 97% of these cells corresponded to HCC cell lines, demonstrating the high specificity of cells derived from single-cell sequencing. 2,038 genes with high variability were obtained. The 371 HCC samples were divided into two molecular clusters. Cluster 1 (C1) was associated with tumorigenesis, high immune score, immunotherapy targets (PD-L1 and CYLA-4), high pathological stage, and poor prognosis. Cluster 2 (C2) was related to metabolic and immune function, low immune score, low pathological stage, and good prognosis. Seven differentially expressed genes (CYP3A4, NR1I2, CYP2C9, TTR, APOC3, CYP1A2, and AFP) identified between the two molecular clusters were used to construct a prognostic model. We further validated the correlation between the seven key genes and clinical features, and the established prognostic model could effectively predict HCC prognosis. Our study identified seven key genes related to HCC that were used to construct a prognostic model through single-cell sequencing and big data analytics. This study provides new insights for further research on clinical targets of HCC and new biomarkers for clinical application.

The effect of metformin usage on survival outcomes for hepatocellular carcinoma patients with type 2 diabetes mellitus after curative therapy

OBJECTIVE

Metformin has attracted more attention from researchers for its newly discovered antitumor effects. A meta-analysis was performed to reveal the efficacy of metformin on overall survival (OS) and recurrence-free survival (RFS) for HCC patients with type 2 diabetes mellitus (T2DM) after curative treatment.

METHODS

Databases including PubMed, the Cochrane Library, Web of Science, CNKI, Wangfang, and Weipu Database up until 31 May 2022 were searched for relevant studies. STATA 13.0 was used to perform the meta-analysis.

RESULTS

A total of six studies involving 5,936 patients were included in our study. The results from the current study revealed that metformin usage can significantly prolong the 3-year [odds ratio (OR) = 1.50, 95% confidence interval (CI): 1.22-1.83, p = 0.000] and 5-year (OR = 1.88, 95% CI: 1.47-2.41, p = 0.000) OS and decrease the 1-year (OR = 1.31, 95% CI: 1.08-1.59, p = 0.007), 3-year (OR = 1.88, 95% CI: 1.48-2.37, p = 0.000), and 5-year (OR = 1.83, 95% CI: 1.40-2.40, p = 0.000) recurrence rates.

CONCLUSION

Metformin treatment significantly prolongs the OS and decreases the recurrence rate for HCC patients with T2DM after curative HCC therapy.