A novel mitochondrial unfolded protein response-related risk signature to predict prognosis, immunotherapy and sorafenib sensitivity in hepatocellular carcinoma.

Zhang S ，Guo H ，Wang H ，Liu X ，Wang M ，Liu X ，Fan Y ，Tan K ... -  《-》

Immunogenic landscape and risk score prediction based on unfolded protein response (UPR)-related molecular subtypes in hepatocellular carcinoma.

Hepatocellular carcinoma (HCC) is the most common type of cancer and causes a significant number of cancer-related deaths worldwide. The molecular mechanisms underlying the development of HCC are complex, and the heterogeneity of HCC has led to a lack of effective prognostic indicators and drug targets for clinical treatment of HCC. Previous studies have indicated that the unfolded protein response (UPR), a fundamental pathway for maintaining endoplasmic reticulum homeostasis, is involved in the formation of malignant characteristics such as tumor cell invasiveness and treatment resistance. The aims of our study are to identify new prognostic indicators and provide drug treatment targets for HCC in clinical treatment based on UPR-related genes (URGs). Gene expression profiles and clinical information were downloaded from the TCGA, ICGC and GEO databases. Consensus cluster analysis was performed to classify the molecular subtypes of URGs in HCC patients. Univariate Cox regression and machine learning LASSO algorithm were used to establish a risk prognosis model. Kaplan-Meier and ROC analyses were used to evaluate the clinical prognosis of URGs. TIMER and XCell algorithms were applied to analyze the relationships between URGs and immune cell infiltration. Real time-PCR was performed to analyze the effect of sorafenib on the expression levels of four URGs. Most URGs were upregulated in HCC samples. According to the expression pattern of URGs, HCC patients were divided into two independent clusters. Cluster 1 had a higher expression level, worse prognosis, and higher expression of immunosuppressive factors than cluster 2. Patients in cluster 1 were more prone to immune escape during immunotherapy, and were more sensitive to chemotherapeutic drugs. Four key UPR genes (ATF4, GOSR2, PDIA6 and SRPRB) were established in the prognostic model and HCC patients with high risk score had a worse clinical prognosis. Additionally, patients with high expression of four URGs are more sensitive to sorafenib. Moreover, ATF4 was upregulated, while GOSR2, PDIA6 and SRPRB were downregulated in sorafenib-treated HCC cells. The UPR-related prognostic signature containing four URGs exhibits high potential application value and performs well in the evaluation of effects of chemotherapy/immunotherapy and clinical prognosis.

Guo H ，Zhang S ，Zhang B ，Shang Y ，Liu X ，Wang M ，Wang H ，Fan Y ，Tan K ... -  《Frontiers in Immunology》

Identification of an m6A-Related Signature as Biomarker for Hepatocellular Carcinoma Prognosis and Correlates with Sorafenib and Anti-PD-1 Immunotherapy Treatment Response.

N6-methyladenosine (m6A) modification plays an essential role in diverse key biological processes and may take part in the development and progression of hepatocellular carcinoma (HCC). Here, we systematically analyzed the expression profiles and prognostic values of 13 widely reported m6A modification-related genes in HCC. The mRNA expression of 13 m6A modification-related genes and clinical parameters of HCC patients were downloaded from TCGA, ICGC, GSE109211, and GSE78220. Univariate and LASSO analyses were used to develop risk signature. Time-dependent ROC was performed to assess the predictive accuracy and sensitivity of risk signature. FTO, YTHDC1, YTHDC2, ALKBH5, KIAA1429, HNRNPC, METTL3, RBM15, YTHDF2, YTHDF1, and WTAP were significantly overexpressed in HCC patients. YTHDF1, HNRNPC, RBM15, METTL3, and YTHDF2 were independent prognostic factors for OS and DFS in HCC patients. Next, a risk signature was also developed and validated with five m6A modification-related genes in TCGA and ICGC HCC cohort. It could effectively stratify HCC patients into high-risk patients with shorter OS and DFS and low-risk patients with longer OS and DFS and showed good predictive efficiency in predicting OS and DFS. Moreover, significantly higher proportions of macrophages M0 cells, neutrophils, and Tregs were found to be enriched in HCC patients with high risk scores, while significantly higher proportions of memory CD4 T cells, gamma delta T cells, and naive B cells were found to be enriched in HCC patients with low scores. Finally, significantly lower risk scores were found at sorafenib treatment responders and anti-PD-1 immunotherapy responders compared to that in nonresponders, and anti-PD-1 immunotherapy-treated patients with lower risk scores had better OS than patients with higher risk scores. A risk signature developed with the expression of 5 m6A-related genes could improve the prediction of prognosis of HCC and correlated with sorafenib treatment and anti-PD-1 immunotherapy response.

Jiang H ，Ning G ，Wang Y ，Lv W ... -  《-》

Comprehensive scRNA-seq Analysis and Identification of CD8_+T Cell Related Gene Markers for Predicting Prognosis and Drug Resistance of Hepatocellular Carcinoma.

Tumor heterogeneity of immune infiltration of cells plays a decisive role in hepatocellular carcinoma (HCC) therapy response and prognosis. This study investigated the effect of different subtypes of CD8+T cells on the HCC tumor microenvironment about its prognosis. Single-cell RNA sequencing, transcriptome, and single-nucleotide variant data from LUAD patients were obtained based on the GEO, TCGA, and HCCD18 databases. CD8+ T cells-associated subtypes were identified by consensus clustering analysis, and genes with the highest correlation with prognostic CD8+ T cell subtypes were identified using WGCNA. The ssGSEA and ESTIMATE algorithms were used to calculate pathway enrichment scores and immune cell infiltration levels between different subtypes. Finally, the TIDE algorithm, CYT score, and tumor responsiveness score were utilized to predict patient response to immunotherapy. We defined 3 CD8+T cell clusters (CD8_0, CD8_1, CD8_2) based on the scRNA- seq dataset (GSE149614). Among, CD8_2 was prognosis-related risk factor with HCC. We screened 30 prognosis genes from CD8_2, and identified 3 molecular subtypes (clust1, clust2, clust3). Clust1 had better survival outcomes, higher gene mutation, and enhanced immune infiltration. Furthermore, we identified a 12 genes signature (including CYP7A1, SPP1, MSC, CXCL8, CXCL1, GCNT3, TMEM45A, SPP2, ME1, TSPAN13, S100A9, and NQO1) with excellent prediction performance for HCC prognosis. In addition, High-score patients with higher immune infiltration benefited less from immunotherapy. The sensitivity of low-score patients to multiple drugs including Parthenolide and Shikonin was significantly higher than that of high-score patients. Moreover, high-score patients had increased oxidative stress pathways scores, and the RiskScore was closely associated with oxidative stress pathways scores. And the nomogram had good clinical utility. To predict the survival outcome and immunotherapy response for HCC, we developed a 12-gene signature based on the heterogeneity of the CD8+ T cells.

Cao L ，Liu M ，Ma X ，Rong P ，Zhang J ，Wang W ... -  《-》

An Unfolded Protein Response-Related mRNA Signature Predicting the Survival and Therapeutic Effect of Hepatocellular Carcinoma.

Tumorigenesis, metastasis, and treatment response of hepatocellular carcinoma (HCC) are regulated by unfolded protein responses (UPR) signaling pathways, including IRE1a, PERK, and ATF6, but little is known about UPR related genes with HCC prognosis and therapeutic indicators. We aimed to identify a UPR related prognostic signature (UPRRPS) for HCC and explore the potential effect of the current signature on the existing molecular targeted agents and immune checkpoint inhibitors (ICIs). We used The Cancer Genome Atlas (TCGA) database to screen candidate UPR genes (UPRGs), which are expressed differentially between hepatocellular carcinoma and normal liver tissue and associated with prognosis. A gene risk score for overall survival prediction was established using the least absolute shrinkage and selection operator (LASSO) regression analysis, which was validated using data from the International Cancer Genome Consortium (ICGC) database and evaluated by the C-index. Then immune and molecular characteristics stratified by the current UPRRPS were analyzed, and the corresponding drug sensitivity was conducted. Initially, 42 UPRGs from the TCGA database were screened as differentially expressed genes, which were also associated with HCC prognosis. Using the LASSO regression analysis, nine UPRGs (EXTL3, PPP2R5B, ZBTB17, EIF2S2, EIF2S3, HDGF, SRPRB, EXTL2, and TPP1) were used to develop a UPRRPS to predict the OS of HCC patients in the TCGA set with the Cindex of 0.763. The current UPRRPS was also well-validated in the ICGC set with the C-index of 0.700. Multivariate Cox regression analyses also confirmed that the risk score was an independent risk factor for HCC in both the TCGA and ICGC sets (both P<0.05). Functional analyses showed that low-risk score was associated with increased natural killer cells, T helpers, tumor immune dysfunction and exclusion score, microsatellite instability expression, and more benefit from ICIs; the high-risk score was associated with increased active dendritic cells, Tregs, T-cell exclusion score, and less benefit from ICIs. Gene set enrichment analyses showed that the signaling pathways of VEGF, MAPK, and mTOR were enriched in high UPRRPS, and the drug sensitivities of the corresponding inhibitors were all significantly higher in the high UPRRPS subgroup (all P<0.001). With the current findings, UPRRPS was a promising biomarker for predicting the prognosis of HCC patients. UPRRPS might also be taken as a potential indicator to guide the management of immune checkpoint inhibitors and molecular targeted agents.

Su Z ，Wang L ，Chen X ，Zhong X ，Wang D ，Wang J ，Shao L ，Chen G ，Wu J ... -  《-》