Prognostic signature for hepatocellular carcinoma based on 4 pyroptosis-related genes

Perforin 1 in Cancer: Mechanisms, Therapy, and Outlook

PRF1 (perforin 1) is a key cytotoxic molecule that plays a crucial role in the killing function of natural killer (NK) cells and cytotoxic T lymphocytes (CTLs). Recent studies have focused on PRF1's role in cancer development, progression, and prognosis. Studies have shown that aberrant PRF1 expression has a significant role to play in cancer development and progression. In some cancers, high expression of the PRF1 gene is associated with a better prognosis for patients, possibly because it helps enhance the body's immune response to tumors. However, some studies have also shown that the absence of PRF1 may make it easier for tumors to evade the body's immune surveillance, thus affecting patient survival. Furthermore, recent studies have explored therapeutic strategies based on PRF1, such as enhancing the ability of immune cells to kill cancer cells by boosting PRF1 activity. In addition, they have improved the efficacy of immunotherapy by modulating its expression to enhance the effectiveness of the treatment. Based on these findings, PRF1 may be a valuable biomarker both for the treatment of cancer and for its prognosis in the future. To conclude, PRF1 has an important biological function and has clinical potential for the treatment of cancer, which indicates that it deserves more research and development in the future.

Identification and validation of a novel predictive signature based on hepatocyte-specific genes in hepatocellular carcinoma by integrated analysis of single-cell and bulk RNA sequencing

BACKGROUND

Hepatocellular carcinoma represents a significant global burden in terms of cancer-related mortality, posing a substantial risk to human health. Despite the availability of various treatment modalities, the overall survival rates for patients with hepatocellular carcinoma remain suboptimal. The objective of this study was to explore the potential of novel biomarkers and to establish a novel predictive signature utilizing multiple transcriptome profiles.

METHODS

The GSE115469 and CNP0000650 cohorts were utilized for single cell analysis and gene identification. The Cancer Genome Atlas (TCGA) and International Cancer Genome Consortium (ICGC) datasets were utilized in the development and evaluation of a predictive signature. The expressions of hepatocyte-specific genes were further validated using the GSE135631 cohort. Furthermore, immune infiltration results, immunotherapy response prediction, somatic mutation frequency, tumor mutation burden, and anticancer drug sensitivity were analyzed based on various risk scores. Subsequently, functional enrichment analysis was performed on the differential genes identified in the risk model. Moreover, we investigated the expression of particular genes in chronic liver diseases utilizing datasets GSE135251 and GSE142530.

RESULTS

Our findings revealed hepatocyte-specific genes (ADH4, LCAT) with notable alterations during cell maturation and differentiation, leading to the development of a novel predictive signature. The analysis demonstrated the efficacy of the model in predicting outcomes, as evidenced by higher risk scores and poorer prognoses in the high-risk group. Additionally, a nomogram was devised to forecast the survival rates of patients at 1, 3, and 5 years. Our study demonstrated that the predictive model may play a role in modulating the immune microenvironment and impacting the anti-tumor immune response in hepatocellular carcinoma. The high-risk group exhibited a higher frequency of mutations and was more likely to benefit from immunotherapy as a treatment option. Additionally, we confirmed that the downregulation of hepatocyte-specific genes may indicate the progression of hepatocellular carcinoma and aid in the early diagnosis of the disease.

CONCLUSION

Our research findings indicate that ADH4 and LCAT are genes that undergo significant changes during the differentiation of hepatocytes into cancer cells. Additionally, we have created a unique predictive signature based on genes specific to hepatocytes.

The Pyroptosis-Related Signature Composed of GSDMC Predicts Prognosis and Contributes to Growth and Metastasis of Hepatocellular Carcinoma

BACKGROUND

Pyroptosis-related genes (PRG) are closely associated with the progression and metastasis of hepatocellular carcinoma (HCC). The predictive power of PRGs could be used to assess the clinical outcomes of HCC.

METHODS

The Cancer Genome Atlas (TCGA) RNA-seq data and clinical information from patients with liver hepatocellular carcinoma (LIHC) were used to identify PRG with differentially expressed between HCC and normal samples. Univariate Cox regression, least absolute shrinkage and selection operator (LASSO) Cox method, and multivariate Cox regression analysis were used to develop a prognostic model that included three PRGs. Gene set enrichment analysis (GSEA) was performed to identify differential immune cells and their associated pathways. The expression of Gasdermin C (GSDMC) in the HCC samples was detected by western blotting, and the function of GSDMC in HCC proliferation and metastasis was detected by the Cell Counting Kit-8 (CCK-8), colony formation, cell invasion, and wound healing assays.

RESULTS

Of 52 PRGs, GSDMC, Bcl-2 homologusantagonist/ killer 1 (BAK1), and NOD-like receptor thermal protein domain associated protein 6 (NLRP6) were selected to establish a prognostic model. The model successfully differentiated HCC patients with varied survival in the TCGA training and test cohorts, as well as the International Cancer Genome Consortium (ICGC) validation cohorts. The risk score was proven to be an independent prognostic factor. In addition, we also reported a marked upregulation of GSDMC in HCC tissues, which could be induced by CD274 (PD-L1). Overexpression of GSDMC contributes to HCC cells invasion, proliferation, and migration.

CONCLUSIONS

The three PRGs signatures containing GSDMC independently predicted HCC prognosis. As a new driver molecule, GSDMC could play a tumor-promoting role by facilitating HCC growth and metastasis.

RNA-Seq and Immune Repertoire Analysis of Normal and Hepatocellular Carcinoma Relapse After Liver Transplantation

Background

Hepatocellular carcinoma (HCC) relapse is the main reason for the poor prognosis of HCC after Liver transplantation (LT). This study aimed to explore the molecular mechanisms and immune repertoire profiles of HCC relapse.

Material and Methods

RNA-seq of blood samples from patients with normal (n=12) and HCC relapse (n=6) after LT was performed to identify differentially expressed genes (DEGs) and key signalling pathways. The DEGs and immune genes were further analyzed by bioinformatics. TRUST4 was used to analyze the differences in the immune repertoire between the two groups. Another 11 blood samples from patients with HCC who had received LT were collected for RT-qPCR verification of key genes.

Results

A total of 131 upregulated and 157 downregulated genes were identified using RNA-seq, and GO enrichment analysis revealed that the top 15 pathways were immune-related. The PPI network identified 10 key genes. Immune infiltration analysis revealed a significant difference in the five immune cell types between the two groups. A total of 83 intersecting genes were obtained by intersecting DEGs and immune genes. 6 key genes, including MX1, ISG15, OAS1, PRF1, SPP1, and THBS1 were obtained according to the intersection of DEGs, PPI network top 10 genes and immune intersecting genes. Immune repertoire analysis showed that the usage frequency of variable (V) and joining (J) genes in the normal group was higher than that in the relapse group. RT-qPCR validation showed that the expression levels of key genes were consistent with the RNA-seq results.

Conclusion

Our study identified key pathways and genes that could help determine whether transplant recipients are more prone to HCC relapse. Immune repertoire analysis revealed a difference in the usage frequency of VJ genes between the normal and relapse groups, providing a research direction for immunotherapy in patients with HCC relapse after liver transplantation.

Performance of non-invasive tests and histology for the prediction of clinical outcomes in patients with non-alcoholic fatty liver disease: an individual participant data meta-analysis

BACKGROUND

Histologically assessed liver fibrosis stage has prognostic significance in patients with non-alcoholic fatty liver disease (NAFLD) and is accepted as a surrogate endpoint in clinical trials for non-cirrhotic NAFLD. Our aim was to compare the prognostic performance of non-invasive tests with liver histology in patients with NAFLD.

METHODS

This was an individual participant data meta-analysis of the prognostic performance of histologically assessed fibrosis stage (F0-4), liver stiffness measured by vibration-controlled transient elastography (LSM-VCTE), fibrosis-4 index (FIB-4), and NAFLD fibrosis score (NFS) in patients with NAFLD. The literature was searched for a previously published systematic review on the diagnostic accuracy of imaging and simple non-invasive tests and updated to Jan 12, 2022 for this study. Studies were identified through PubMed/MEDLINE, EMBASE, and CENTRAL, and authors were contacted for individual participant data, including outcome data, with a minimum of 12 months of follow-up. The primary outcome was a composite endpoint of all-cause mortality, hepatocellular carcinoma, liver transplantation, or cirrhosis complications (ie, ascites, variceal bleeding, hepatic encephalopathy, or progression to a MELD score ≥15). We calculated aggregated survival curves for trichotomised groups and compared them using stratified log-rank tests (histology: F0-2 vs F3 vs F4; LSM: <10 vs 10 to <20 vs ≥20 kPa; FIB-4: <1·3 vs 1·3 to ≤2·67 vs >2·67; NFS: <-1·455 vs -1·455 to ≤0·676 vs >0·676), calculated areas under the time-dependent receiver operating characteristic curves (tAUC), and performed Cox proportional-hazards regression to adjust for confounding. This study was registered with PROSPERO, CRD42022312226.

FINDINGS

Of 65 eligible studies, we included data on 2518 patients with biopsy-proven NAFLD from 25 studies (1126 [44·7%] were female, median age was 54 years [IQR 44-63), and 1161 [46·1%] had type 2 diabetes). After a median follow-up of 57 months [IQR 33-91], the composite endpoint was observed in 145 (5·8%) patients. Stratified log-rank tests showed significant differences between the trichotomised patient groups (p<0·0001 for all comparisons). The tAUC at 5 years were 0·72 (95% CI 0·62-0·81) for histology, 0·76 (0·70-0·83) for LSM-VCTE, 0·74 (0·64-0·82) for FIB-4, and 0·70 (0·63-0·80) for NFS. All index tests were significant predictors of the primary outcome after adjustment for confounders in the Cox regression.

INTERPRETATION

Simple non-invasive tests performed as well as histologically assessed fibrosis in predicting clinical outcomes in patients with NAFLD and could be considered as alternatives to liver biopsy in some cases.

FUNDING

Innovative Medicines Initiative 2.

Identification of novel gene signatures and immune cell infiltration in intervertebral disc degeneration using bioinformatics analysis

Background: Intervertebral disc degeneration (IDD) is the leading cause of lower back pain, and an overall understanding of the molecular mechanisms related to IDD is still lacking. The purpose of this study was to explore gene signatures and immune cell infiltration related to IDD via bioinformatics analysis. Methods: A total of five expression profiles of mRNA and non-coding RNA were downloaded from the Gene Expression Omnibus (GEO) database. The potentially involved lncRNA/circRNA-miRNA-mRNA networks and protein-protein interaction networks were constructed by miRNet, circBank, STRING, and the Cytoscape database. Gene ontology, Kyoto Encyclopaedia of Genes and Genomes Analysis, Gene Set Enrichment Analysis, Gene Set Variation Analysis, Immune Infiltration Analysis, and Drug-Gene Interaction were used to analyse the top 20 hub genes. RT-qPCR was conducted to confirm the 12 differential expressions of genes both in the nucleus pulposus and annulus fibrosus tissues Results: There were 346 differentially expressed mRNAs, 12 differentially expressed miRNAs, 883 differentially expressed lncRNAs, and 916 differentially expressed circRNAs in the GEO database. Functional and enrichment analyses revealed hub genes associated with platelet activation, immune responses, focal adhesion, and PI3K-Akt signalling. The apoptotic pathway, the reactive oxygen species pathway, and oxidative phosphorylation play an essential role in IDD. Immune infiltration analysis demonstrated that the Treg cells had significant infiltration, and three levels of immune cells, including dendritic cells, Th2 cells, and tumour-infiltrating lymphocytes, were inhibited in IDD. Drug-gene interaction analysis showed that COL1A1 and COL1A2 were targeted by collagenase clostridium histolyticum, ocriplasmin, and PDGFRA was targeted by 66 drugs or molecular compounds. Finally, 24 cases of IDD tissues and 12 cases of normal disc tissues were collected, and the results of RT-qPCR were consistent with the bioinformatics results. Conclusion: Our data indicated that the 20 hub genes and immune cell infiltration were involved in the pathological process of IDD. In addition, the PDGFRA and two potential drugs were found to be significant in IDD development.