Screening of a novel autophagy-related prognostic signature and therapeutic targets in hepatocellular carcinoma

ICD-related risk model predicts the prognosis and immunotherapy response of patients with liver cancer

Immunogenic cell death (ICD) is a novel cell death mechanism that activates and regulates the immune system against cancer. However, its prognostic value in liver cancer remains unclear. Here, several algorithms such as correlation analysis, Cox regression analysis, and Lasso regression analysis were carried out to evaluate the prognostic value of ICD-related genes in patients with liver cancer. Three ICD-related prognostic genes, the prion protein gene (PRNP), dynamin 1-like gene (DNM1L), and caspase-8 (CASP8), were identified and used to construct a risk signature. Patients with liver cancer were categorized into high- and low-risk groups using the ICD-related signature. Subsequently, a multivariate regression analysis revealed that the signature was an independent risk factor in liver cancer [hazard ratio (HR) = 6.839; 95% confidence interval (CI) = 1.625-78.785]. Patient survival was also predicted using the risk model, with area under the curve values of 0.75, 0.70, and 0.69 for 1-, 3-, and 5-year survival, respectively. Finally, a prognostic nomogram containing the clinical characteristics and risk scores of patients was constructed. The constructed ICD-related signature could serve as a prognostic and immunotherapeutic biomarker in liver cancer.

Expression and Function of BMP and Activin Membrane-Bound Inhibitor (BAMBI) in Chronic Liver Diseases and Hepatocellular Carcinoma

BAMBI (bone morphogenetic protein and activin membrane-bound inhibitor) is a transmembrane pseudoreceptor structurally related to transforming growth factor (TGF)-β type 1 receptors (TGF-β1Rs). BAMBI lacks a kinase domain and functions as a TGF-β1R antagonist. Essential processes such as cell differentiation and proliferation are regulated by TGF-β1R signaling. TGF-β is the best-studied ligand of TGF-βRs and has an eminent role in inflammation and fibrogenesis. Liver fibrosis is the end stage of almost all chronic liver diseases, such as non-alcoholic fatty liver disease, and at the moment, there is no effective anti-fibrotic therapy available. Hepatic BAMBI is downregulated in rodent models of liver injury and in the fibrotic liver of patients, suggesting that low BAMBI has a role in liver fibrosis. Experimental evidence convincingly demonstrated that BAMBI overexpression is able to protect against liver fibrosis. Chronic liver diseases have a high risk of hepatocellular carcinoma (HCC), and BAMBI was shown to exert tumor-promoting as well as tumor-protective functions. This review article aims to summarize relevant studies on hepatic BAMBI expression and its role in chronic liver diseases and HCC.

A novel senescence-related lncRNA signature that predicts prognosis and the tumor microenvironment in patients with lung adenocarcinoma

Background: Cellular senescence has recently been considered a new cancer hallmark. However, the factors regulating cellular senescence have not been well characterized. The aim of this study is to identify long non-coding RNAs (lncRNAs) associated with senescence and prognosis in patients with lung adenocarcinoma (LUAD). Methods: Using RNA sequence data from the Cancer Genome Atlas Lung Adenocarcinoma (TCGA-LUAD) and senescence genes from the CellAge database, a subset of senescence-related lncRNAs was first identified. Then, using univariate and multivariate Cox regression analyses, a senescence lncRNA signature (LUADSenLncSig) associated with LUAD prognosis was developed. Based on the median LUADSenLncSig risk score, LUAD patients were divided into high-risk and low-risk groups. Kaplan-Meier analysis was used to compare the overall survival (OS) in the high- and low-risk score subgroups. Differences in Gene Set Enrichment Analysis (GSEA), immune infiltration, tumor mutation burden (TMB), tumor immune dysfunction and exclusion (TIDE) module score, chemotherapy, and targeted therapy selection were also compared between the high-risk and low-risk groups. Results: A prognostic risk model was obtained consisting of the following nine senescence-related lncRNAs: LINC01116, AC005838.2, SH3PXD2A-AS1, VIMS-AS1, SH3BP5-AS1, AC092279.1, AC026355.1, AC027020.2, and LINC00996. The LUADSenLncSig high-risk group was associated with poor OS (hazard ratio = 1.17, 95% confidence interval = 1.102-1.242; p < 0.001). The accuracy of the model was further supported based on receiver operating characteristic (ROC), principal component analysis (PCA), and internal validation cohorts. In addition, a nomogram was developed consisting of LUADSenLncSig for LUAD prognosis, which is consistent with the actual probability of OS. Furthermore, immune infiltration analysis showed the low-risk group had a stronger anti-tumor immune response in the tumor microenvironment. Notably, the levels of immune checkpoint genes such as CTLA-4, PDCD-1, and CD274, and the TIDE scores were significantly higher in the low-risk subgroups than in high-risk subgroups (p < 0.001). This finding indicates the LUADSenLncSig can potentially predict immunotherapy efficacy. Conclusion: In this study, a lncRNA signature, LUADSenLncSig, that has dual functions of senescence phenotype identification and prognostic prediction as well as the potential to predict the LUAD response to immunotherapy was developed.

The development and validation of a novel senescence-related long-chain non-coding RNA (lncRNA) signature that predicts prognosis and the tumor microenvironment of patients with hepatocellular carcinoma

Background

The epigenetic regulators of cellular senescence, especially long non-coding RNAs (lncRNAs), remain unclear. The expression levels of lncRNA were previously known to be prognostic indicators for tumors. We hypothesized that lncRNAs regulating cellular senescence could also predict prognosis in patients with hepatocellular carcinoma (HCC) and developed a novel lncRNA predictive signature.

Methods

Using RNA sequencing data from The Cancer Genome Atlas Liver Hepatocellular Carcinoma (TCGA-LIHC) database, a co-expression network of senescence-related messenger RNAs (mRNAs) and lncRNAs was constructed. Using univariate Cox regression analysis and a stepwise multiple Cox regression analysis, we constructed a prognostic HCC senescence-related lncRNA signature (HCCSenLncSig). Kaplan-Meier analysis was used to compare the overall survival (OS) of high- and low-risk groups stratified by the HCCSenLncSig. Furthermore, the HCCSenLncSig risk score and other clinical characteristics were included to develop an HCC prognostic nomogram. The accuracy of the model was evaluated by the time dependent receiver operating characteristic (ROC) and calibration curves, respectively.

Results

We obtained a prognostic risk model consisting of 8 senescence-related lncRNAs: AL117336.3, AC103760.1, FOXD2-AS1, AC009283.1, AC026401.3, AC021491.4, AC124067.4, and RHPN1-AS1. The HCCSenLncSig high-risk group was associated with poor OS [hazard ratio (HR) =1.125, 95% confidence interval (CI): 1.082-1.169; P<0.001]. The accuracy of the model was further supported by ROC curves (the area under the curve is 0.783, sensitivity of 0.600, and specificity of 0.896 at the cut-off value of 1.447). The HCCSenLncSig was found to be an independent prognostic factor from other clinical factors in both univariate and multivariate Cox regression analyses. The prognostic nomogram shows HCCSenLncSig has a good prognostic effect for survival risk stratification. Finally, we found that a higher number of immunosuppressed Treg cells infiltrate in high-risk patients (P<0.001 compared to low-risk patients), possibly explaining why these patients have a poor prognosis. On the other hand, the expression of immunotherapy markers, such as CD276, PDCD1, and CTLA4, was also up-regulated in the high-risk patients, indicating potential immunotherapy response in these patients.

Conclusions

The development of HCCSenLncSig allows us to better predict HCC patients' survival outcomes and disease risk, as well as contribute to the development of novel HCC anti-cancer therapeutic strategies.

Identification of autophagy related genes in predicting the prognosis and aiding 5- fluorouracil therapy of colorectal cancer

The emergence of 5-Fluorouracil (5-FU) resistance is the barrier to effective clinical outcomes for colorectal cancer (CRC) patients. Autophagy was found to be involved in protecting tumor cells from 5-FU. However, the specific role of autophagy-related genes in CRC 5-FU resistance remains unclear. In this study, HSPB8 among 34 differentially expressed ARGs in CRC was identified to be the hub ARGs in 5-FU resistant which was down-regulated in CRC samples when compared with normal samples but up-regulated in CRC samples with relatively higher lymphatic invasion, later stages and poor prognosis of CRC. Mechanistic analysis demonstrated that due to the recruitment of CAFs, HSPB8 expression was enhanced in CRC cells so that HSPB8 could act together with its co-chaperone BAG3 in autophagy drived 5-FU resistance. Furthermore, the augmented expression level of HSPB8 was found to be significantly correlated to the immune cell infiltration such as Treg cells, macrophages, monocyte and dendritic cells and so on. Our results suggested CAFs driving HSPB8 induced CRC 5-FU resistance by promoting tumor autophagy would provide a new strategy in seeking potential CRC therapeutic target.