Development and Verification of the Hypoxia-Related and Immune-Associated Prognosis Signature for Hepatocellular Carcinoma

Identification of two heterogeneous subtypes of hepatocellular carcinoma with distinct pathway activities and clinical outcomes based on gene set variation analysis

Background

High heterogeneity is an essential feature of malignant tumors. This study aims to reveal the drivers of hepatocellular carcinoma heterogeneity for prognostic stratification and to guide individualized treatment.

Methods

Omics data and clinical data for two HCC cohorts were derived from the Cancer Genome Atlas (TCGA) and the International Cancer Genome Atlas (ICGC), respectively. CNV data and methylation data were downloaded from the GSCA database. GSVA was used to estimate the transcriptional activity of KEGG pathways, and consensus clustering was used to categorize the HCC samples. The pRRophetic package was used to predict the sensitivity of samples to anticancer drugs. TIMER, MCPcounter, quanTIseq, and TIDE algorithms were used to assess the components of TME. LASSO and COX analyses were used to establish a prognostic gene signature. The biological role played by genes in HCC cells was confirmed by in vitro experiments.

Results

We classified HCC tissues into two categories based on the activity of prognostic pathways. Among them, the transcriptional profile of cluster A HCC is similar to that of normal tissue, dominated by cancer-suppressive metabolic pathways, and has a better prognosis. In contrast, cluster B HCC is dominated by high proliferative activity and has significant genetic heterogeneity. Meanwhile, cluster B HCC is often poorly differentiated, has a high rate of serum AFP positivity, is prone to microvascular invasion, and has shorter overall survival. In addition, we found that mutations, copy number variations, and aberrant methylation were also crucial drivers of the differences in heterogeneity between the two HCC subtypes. Meanwhile, the TME of the two HCC subtypes is also significantly different, which offers the possibility of precision immunotherapy for HCC patients. Finally, based on the prognostic value of molecular subtypes, we developed a gene signature that could accurately predict patients' OS. The riskscore quantified by the signature could evaluate the heterogeneity of HCC and guide clinical treatment. Finally, we confirmed through in vitro experiments that RFPL4B could promote the progression of Huh7 cells.

Conclusion

The molecular subtypes we identified effectively exposed the heterogeneity of HCC, which is important for discovering new effective therapeutic targets.

A hypoxia-glycolysis-lactate-related gene signature for prognosis prediction in hepatocellular carcinoma

BACKGROUND

Liver cancer ranks sixth in incidence and third in mortality globally and hepatocellular carcinoma (HCC) accounts for 90% of it. Hypoxia, glycolysis, and lactate metabolism have been found to regulate the progression of HCC separately. However, there is a lack of studies linking the above three to predict the prognosis of HCC. The present study aimed to identify a hypoxia-glycolysis-lactate-related gene signature for assessing the prognosis of HCC.

METHODS

This study collected 510 hypoxia-glycolysis-lactate genes from Molecular Signatures Database (MSigDB) and then classified HCC patients from TCGA-LIHC by analyzing their hypoxia-glycolysis-lactate genes expression. Differentially expressed genes (DEGs) were screened out to construct a gene signature by LASSO-Cox analysis. Univariate and multivariate regression analyses were used to evaluate the independent prognostic value of the gene signature. Analyses of immune infiltration, somatic cell mutations, and correlation heatmap were conducted by "GSVA" R package. Single-cell analysis conducted by "SingleR", "celldex", "Seurat", and "CellCha" R packages revealed how signature genes participated in hypoxia/glycolysis/lactate metabolism and PPI network identified hub genes.

RESULTS

We classified HCC patients from TCGA-LIHC into two clusters and screened out DEGs. An 18-genes prognostic signature including CDCA8, CBX2, PDE6A, MED8, DYNC1LI1, PSMD1, EIF5B, GNL2, SEPHS1, CCNJL, SOCS2, LDHA, G6PD, YBX1, RTN3, ADAMTS5, CLEC3B, and UCK2 was built to stratify the risk of HCC. The risk score of the hypoxia-glycolysis-lactate gene signature was further identified as a valuable independent factor for estimating the prognosis of HCC. Then we found that the features of clinical characteristics, immune infiltration, somatic cell mutations, and correlation analysis differed between the high-risk and low-risk groups. Furthermore, single-cell analysis indicated that the signature genes could interact with the ligand-receptors of hepatocytes/fibroblasts/plasma cells to participate in hypoxia/glycolysis/lactate metabolism and PPI network identified potential hub genes in this process: CDCA8, LDHA, YBX1.

CONCLUSION

The hypoxia-glycolysis-lactate-related gene signature we built could provide prognostic value for HCC and suggest several hub genes for future HCC studies.

Identification of hub genes within the CCL18 signaling pathway in hepatocellular carcinoma through bioinformatics analysis

Introduction

Hepatocellular carcinoma (HCC) is an aggressive malignancy, and CCL18, a marker of M2 macrophage activation, is often associated with tumor immune suppression. However, the role of CCL18 and its signaling pathway in HCC is still limited. Our study focuses on investigating the prognostic impact of CCL18 and its signaling pathway in HCC patients and biological functions in vitro.

Methods

HCC-related RNA-seq data were obtained from TCGA, ICGC, and GEO. The 6 hub genes with the highest correlation to prognosis were identified using univariate Cox and LASSO regression analysis. Multivariate Cox regression analysis was performed to assess their independent prognostic potential and a nomogram was constructed. In vitro experiments, including CCK8, EdU, RT-qPCR, western blot, and transwell assays, were conducted to investigate the biological effects of exogenous CCL18 and 6 hub genes. A core network of highly expressed proteins in the high-risk group of tumors was constructed. Immune cell infiltration was evaluated using the ESTIMATE and CIBERSORT packages. Finally, potential treatments were explored using the OncoPredict package and CAMP database.

Results

We identified 6 survival-related genes (BMI1, CCR3, CDC25C, CFL1, LDHA, RAC1) within the CCL18 signaling pathway in HCC patients. A nomogram was constructed using the TCGA_LIHC cohort to predict patient survival probability. Exogenous CCL18, as well as overexpression of BMI1, CCR3, CDC25C, CFL1, LDHA, and RAC1, can promote proliferation, migration, invasion, stemness, and increased expression of PD-L1 protein in LM3 and MHCC-97H cell lines. In the high-risk group of patients from the TCGA_LIHC cohort, immune suppression was observed, with a strong correlation to 21 immune-related genes and suppressive immune cells.

Conclusion

Exogenous CCL18 promotes LM3 and MHCC-97H cells proliferation, migration, invasion, stemness, and immune evasion. The high expression of BMI1, CCR3, CDC25C, CFL1, LDHA, and RAC1 can serve as a biomarkers for immune evasion in HCC.

Identification of potential prognostic biomarkers among gene models for coiled-coil domain-containing family members in hepatocellular carcinoma elucidates their influence on the hypoxia pathway and immune microenvironment

Background

The family of coiled-coil domain-containing (CCDC) proteins participates in a wide range of physiological functions and plays a pivotal role in governing the invasion and metastasis of malignant tumor cells. Nonetheless, the precise mechanism governing the interaction among the immune microenvironment, hypoxia pathway, and proliferation in hepatocellular carcinoma (HCC) remains elusive. In this study, our objective was to identify the prognostic significance of CCDC family genes in HCC.

Methods

We conducted an analysis of RNA-seq data from HCC patients sourced from The Cancer Genome Atlas (TCGA) database. Our analysis involved comparing the expression profiles of 168 CCDC family genes between tumor and normal tissues to identify differentially expressed genes (DEGs). The prognostic value of these genes was verified using overall survival (OS) data from TCGA-LIHC patients, employing Univariate and multivariate Cox proportional hazards regression models and Kaplan-Meier plots. Subsequently, we constructed a prognostic signature known as the CCDC score and validated it using additional datasets (ICGC-LIRI-JP and GSE14520). Additionally, we performed functional enrichment analysis and conducted an assessment of the tumor immune microenvironment (TIME).

Results

We identified 34 DEGs of the CCDC family. Among them, six DEGs (CCDC6/22/51/59/132/134) were upregulated and associated with poor prognosis. Higher CCDC score was an independent predictor of poor OS in TCGA-HCC patients (P<0.001, HR =2.37), which was validated in the ICGC-LIRI-JP (P=0.021, HR =2.15) and GSE14520 (P=0.002, HR =2.23) datasets. Functional enrichment analysis showed that hypoxia pathway genes were enriched in the high CCDC score group. Furthermore, immune microenvironment analysis demonstrated that high CCDC score was associated with a suppressed TIME caused by the extrinsic immune escape.

Conclusions

The CCDC score, derived from six CCDC genes, exhibits remarkable expression levels in liver cancer and holds promise as an independent prognostic indicator. Our bioinformatics analysis revealed a high CCDC score is strongly associated with activation of the hypoxia pathway and an immunosuppressive tumor microenvironment in HCC. This profound finding may serve as a cornerstone for innovative targeted drug therapies and pave the way for further investigations into the underlying mechanisms of CCDC-related carcinogenesis in liver cancer.

Cellular senescence throws new insights into patient classification and pharmacological interventions for clinical management of hepatocellular carcinoma

BACKGROUND

Cellular senescence, a state of stable growth arrest, is intertwined with human cancers. However, characterization of cellular senescence-associated phenotypes in hepatocellular carcinoma (HCC) remains unexplored.

AIM

To address this issue, we delineated cellular senescence landscape across HCC.

METHODS

We enrolled two HCC datasets, TCGA-LIHC and International Cancer Genome Consortium (ICGC). Unsupervised clustering was executed to probe tumor heterogeneity based upon cellular senescence genes. Least absolute shrinkage and selection operator algorithm were utilized to define a cellular senescence-relevant scoring system. TRNP1 expression was measured in HCCs and normal tissues through immunohistochemistry, immunoblotting and quantitative real-time polymerase chain reaction. The influence of TMF-regulated nuclear protein (TRNP)1 on HCC senescence and growth was proven via a series of experiments.

RESULTS

TCGA-LIHC patients were classified as three cellular senescence subtypes, named C1-3. The robustness and reproducibility of these subtypes were proven in the ICGC cohort. C2 had the worst overall survival, C1 the next, and C3 the best. C2 presented the highest levels of immune checkpoints, abundance of immune cells, and immunogenetic indicators. Thus, C2 might possibly respond to immunotherapy. C2 had the lowest somatic mutation rate, while C1 presented the highest copy number variations. A cellular senescence-relevant gene signature was generated, which can predict patient survival, and chemo- or immunotherapeutic response. Experimentally, it was proven that TRNP1 presented the remarkable upregulation in HCCs. TRNP1 knockdown induced apoptosis and senescence of HCC cells and attenuated tumor growth.

CONCLUSION

These findings provide a systematic framework for assessing cellular senescence in HCC, which decode the tumor heterogeneity and tailor the pharmacological interventions to improve clinical management.

Development and validation of a copper-related gene prognostic signature in hepatocellular carcinoma

Introduction: Reliable biomarkers are in need to predict the prognosis of hepatocellular carcinoma (HCC). Whilst recent evidence has established the critical role of copper homeostasis in tumor growth and progression, no previous studies have dealt with the copper-related genes (CRGs) signature with prognostic potential in HCC. Methods: To develop and validate a CRGs prognostic signature for HCC, we retrospectively included 353 and 142 patients as the development and validation cohort, respectively. Copper-related Prognostic Signature (Copper-PSHC) was developed using differentially expressed CRGs with prognostic value. The hazard ratio (HR) and the area under the time-dependent receiver operating characteristic curve (AUC) during 3-year follow-up were utilized to evaluate the performance. Additionally, the Copper-PSHC was combined with age, sex, and cancer stage to construct a Copper-clinical-related Prognostic Signature (Copper-CPSHC), by multivariate Cox regression. We further explored the underlying mechanism of Copper-PSHC by analyzing the somatic mutation, functional enrichment, and tumor microenvironment. Potential drugs for the high-risk group were screened. Results: The Copper-PSHC was constructed with nine CRGs. Patients in the high-risk group demonstrated a significantly reduced overall survival (OS) (adjusted HR, 2.65 [95% CI, 1.83-3.84] and 3.30, [95% CI, 1.27-8.60] in the development and validation cohort, respectively). The Copper-PSHC achieved a 3-year AUC of 0.74 [95% CI, 0.67-0.82] and 0.71 [95% CI, 0.56-0.86] for OS in the development and validation cohort, respectively. Copper-CPSHC yield a 3-year AUC of 0.73 [95% CI, 0.66-0.80] and 0.72 [95% CI, 0.56-0.87] for OS in the development and validation cohort, respectively. Higher tumor mutation burden, downregulated metabolic processes, hypoxia status and infiltrated stroma cells were found for the high-risk group. Six small molecular drugs were screened for the treatment of the high-risk group. Conclusion: Copper-PSHC services as a promising tool to identify HCC with poor prognosis and to improve disease outcomes by providing potential clinical decision support in treatment.

Novel roles of karyopherin subunit alpha 2 in hepatocellular carcinoma

Hepatocellular carcinoma is the most common type of liver cancer and associated with a high fatality rate. This disease poses a major threat to human health worldwide. A considerable number of genetic and epigenetic factors are involved in the development of hepatocellular carcinoma. However, the molecular mechanism underlying the progression of hepatocellular carcinoma remains unclear. Karyopherin subunit alpha 2 (KPNA2), also termed importin α1, is a member of the nuclear transporter family. In recent years, KPNA2 has been gradually linked to the nuclear transport pathway for a variety of tumor-associated proteins. Furthermore, it promotes tumor development by participating in various pathophysiological processes such as cell proliferation, apoptosis, immune response, and viral infection. In hepatocellular carcinoma, it has been found that KPNA2 expression is significantly higher in liver cancer tissues versus paracancerous tissues. Moreover, it has been identified as a marker of poor prognosis and early recurrence in patients with hepatocellular carcinoma. Nevertheless, the role of KPNA2 in the development of hepatocellular carcinoma remains to be determined. This review summarizes the current knowledge on the pathogenesis and role of KPNA2 in hepatocellular carcinoma, and provides new directions and strategies for the diagnosis, treatment, and prediction of prognosis of this disease.

Biological function analysis of ARHGAP39 as an independent prognostic biomarker in hepatocellular carcinoma

Hepatocellular carcinoma (HCC) is the most common subtype of liver cancer, with a high morbidity and low survival rate. Rho GTPase activating protein 39 (ARHGAP39) is a crucial activating protein of Rho GTPases, a novel target in cancer therapy, and it was identified as a hub gene for gastric cancer. However, the expression and role of ARHGAP39 in hepatocellular carcinoma remain unclear. Accordingly, the cancer genome atlas (TCGA) data were used to analyze the expression and clinical value of ARHGAP39 in hepatocellular carcinoma. Further, the LinkedOmics tool suggested functional enrichment pathways for ARHGAP39. To investigate in depth the possible role of ARHGAP39 on immune infiltration, we analyzed the relationship between ARHGAP39 and chemokines in HCCLM3 cells. Finally, the GSCA website was used to explore drug resistance in patients with high ARHGAP39 expression. Studies have shown that ARHGAP39 is highly expressed in hepatocellular carcinoma and relevant to clinicopathological features. In addition, the overexpression of ARHGAP39 leads to a poor prognosis. Besides, co-expressed genes and enrichment analysis showed a correlation with the cell cycle. Notably, ARHGAP39 may worsen the survival of hepatocellular carcinoma patients by increasing the level of immune infiltration through chemokines. Moreover, N6-methyladenosine (m6A) modification-related factors and drug sensitivity were also found to be associated with ARHGAP39. In brief, ARHGAP39 is a promising prognostic factor for hepatocellular carcinoma patients that is closely related to cell cycle, immune infiltration, m6A modification, and drug resistance.

Expression of Selected miRNAs in Normal and Cancer-Associated Fibroblasts and in BxPc3 and MIA PaCa-2 Cell Lines of Pancreatic Ductal Adenocarcinoma

Therapy for pancreatic ductal adenocarcinoma remains challenging, and the chances of a complete cure are very limited. As in other types of cancer, the expression and role of miRNAs in controlling the biological properties of this type of tumor have been extensively studied. A better insight into miRNA biology seems critical to refining diagnostics and improving their therapeutic potential. In this study, we focused on the expression of miR-21, -96, -196a, -210, and -217 in normal fibroblasts, cancer-associated fibroblasts prepared from a ductal adenocarcinoma of the pancreas, and pancreatic carcinoma cell lines. We compared these data with miRNAs in homogenates of paraffin-embedded sections from normal pancreatic tissues. In cancer-associated fibroblasts and cancer cell lines, miRNAs differed significantly from the normal tissue. In detail, miR-21 and -210 were significantly upregulated, while miR-217 was downregulated. Similar transcription profiles were earlier reported in cancer-associated fibroblasts exposed to hypoxia. However, the cells in our study were cultured under normoxic conditions. We also noted a relation to IL-6 production. In conclusion, cultured cancer-associated fibroblasts and carcinoma cells reflect miR-21 and -210 expression similarly to the cancer tissue samples harvested from the patients.

Enhancer RNA-based modeling of adverse events and objective responses of cancer immunotherapy reveals associated key enhancers and target genes

Immune checkpoint inhibitors (ICI) targeting PD-1/PD-L1 or CTLA-4 are emerging and effective immunotherapy strategies. However, ICI-treated patients present heterogeneous responses and adverse events, thus demanding effective ways to assess benefit over risk before treatment. Here, by integrating pan-cancer clinical and molecular data, we tried to predict immune-related adverse events (irAEs, risk) and objective response rates (ORRs, benefit) based on enhancer RNAs (eRNAs) expression among patients receiving anti-PD-1/PD-L1 therapies. We built two tri-variate (eRNAs) regression models, one (with ENSR00000326714, ENSR00000148786, and ENSR00000005553) explaining 71% variance (R=0.84) of irAEs and the other (with ENSR00000164478, ENSR00000035913, and ENSR00000167231) explaining 79% (R=0.89) of ORRs. Interestingly, target genes of irAE-related enhancers, including upstream regulators of MYC, were involved in metabolism, inflammation, and immune activation, while ORR-related enhancers target PAK2 and DLG1 which participate in T cell activation. More importantly, we found that ENSR00000148786 probably enhanced TMEM43/LUMA expression mainly in B cells to induce irAEs in ICI-treated patients. Our study provides references for the identification of immunotherapy-related biomarkers and potential therapeutic targets during immunotherapy.

General Characteristics and Promotion Properties of Circular PLOD2 in Patients with Glioma

BACKGROUND

Circular RNAs are closed endogenous RNAs that are involved in the progression of diverse tumors. Even with the most advanced combined treatments, patients with glioblastoma multiforme have a median survival time of <15 months. This study aimed to investigate the roles of circular PLOD2 (circPLOD2) in glioma tumorigenesis and tumor development and to clarify its tumor-promoting effects by bioinformatics analysis and molecular experiments.

METHODS

To determine the characteristics of circPLOD2 expression, quantitative real-time polymerase chain reaction was conducted. Stable knockdown of circPLOD2 was implemented for functional assays. Cell Counting Kit-8 and colony formation assays were used to measure cell proliferation. Transwell assays and tube formation assays were used to evaluate cell invasion and angiogenesis abilities, respectively. An intracranial xenograft model was established to determine the function of circPLOD2 in vivo. Further biochemical and Western blot analyses were conducted to evaluate proteins associated with circPLOD2.

RESULTS

circPLOD2 was upregulated in glioma tissues and cells. High expression of circPLOD2 was significantly associated with tumor size, World Health Organization grade, and molecular characteristics of glioma. circPLOD2 deregulation affected glioblastoma multiforme cell proliferation, invasion, and angiogenesis. Knockdown of circPLOD2 inhibited tumorigenesis in vivo. Further biochemical analysis showed that circPLOD2 was involved in oncogenic pathways and correlated with the expression of proteins related to proliferation, invasion, and angiogenesis.

CONCLUSIONS

Our data indicate that circPLOD2 promotes glioma tumorigenesis and tumor development in vitro and in vivo and that suppressing circPLOD2 could be a novel therapeutic strategy for glioma.

Systems Pharmacology-Based Strategy to Investigate the Mechanism of Ruangan Lidan Decoction for Treatment of Hepatocellular Carcinoma

epatocellular carcinoma (HCC) is one of the leading contributors to cancer mortality worldwide. Currently, the prevention and treatment of HCC remains a major challenge. As a traditional Chinese medicine (TCM) formula, Ruangan Lidan decoction (RGLD) has been proved to own the effect of relieving HCC symptoms. However, due to its biological effects and complex compositions, its underlying mechanism of actions (MOAs) have not been fully clarified yet. In this study, we proposed a pharmacological framework to systematically explore the MOAs of RGLD against HCC. We firstly integrated the active ingredients and potential targets of RGLD. We next highlighted 25 key targets that played vital roles in both RGLD and HCC disease via a protein-protein interaction (PPI) network and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses. Furthermore, an ingredient-target network of RGLD consisting of 216 ingredients with 306 targets was constructed, and multilevel systems pharmacology analyses indicated that RGLD could act on multiple biological processes related to the pathogenesis of HCC, such as cellular response to hypoxia and cell proliferation. Additionally, integrated pathway analysis of RGLD uncovered that RGLD might treat HCC through regulating various pathways, including MAPK signaling pathway, PI3K/Akt signaling pathway, TNF signaling pathway, and ERBB signaling pathway. Survival analysis results showed that HCC patients with low expression of VEGFA, HIF1A, CASP8, and TOP2A were related with a higher survival rate than those with high expression, indicating the potential clinical significance for HCC. Finally, molecular docking results of core ingredients and targets further proved the feasibility of RGLD in the treatment of HCC. Overall, this study indicates that RGLD may treat HCC through multiple mechanisms, which also provides a potential paradigm to investigate the MOAs of TCM prescription.

Investigation of the Potential Correlation Between RNA-Binding Proteins in the Evolutionarily Conserved MEX3 Family and Non-small-Cell Lung Cancer

Members of the MEX3 (muscle excess 3) family, uniquely characterised as mRNA binding proteins, play emerging roles in the post-transcriptional regulation of programmed biological processes, including tumour cell death and immune mechanisms, and have been shown to be involved in a variety of diseases. However, the role of MEX3 in non-small cell lung cancer (NSCLC) has not been fully elucidated. In this study, we found no significant changes in the sequence and copy number of the MEX3 gene through analysis using the COSMIC database, revealing its stability during malignancy development. Its expression in NSCLC was examined using the Oncomine™ database, and the prognosis of each member gene was analysed by Kaplan–Meier. The results showed that overexpression of MEX3A, MEX3B, MEX3C and MEX3D was associated with significantly worse OS in patients with LUAD, while overexpression of MEX3D was also associated with significantly worse OS in patients with LUSC. Afterwards, we applied the Tumour Immunology Estimation Resource (TIMER) tool to assess the correlation between different MEX3 and infiltrative immune cell infiltration. Ultimately, we found that most MEX3 members were highly expressed in NSCLC, with high expression suggesting poor prognosis and correlating with immune cell infiltration. The complexity and heterogeneity of NSCLC was understood through MEX3, setting the framework for the prognostic impact of MEX3 in NSCLC patients and the development of new targeted therapeutic strategies in the future.

Hypoxia-immune-related microenvironment prognostic signature for osteosarcoma

Introduction: Increasing evidences have shown that hypoxia and the immune microenvironment play vital roles in the development of osteosarcoma. However, reliable gene signatures based on the combination of hypoxia and the immune status for prognostic prediction of osteosarcoma have so far not been identified. Methods: The individual hypoxia and immune status of osteosarcoma patients were identified with transcriptomic profiles of a training cohort from the TARGET database using ssGSEA and ESTIMATE algorithms, respectively. Lasso regression and stepwise Cox regression were performed to develop a hypoxia-immune-based gene signature. An independent cohort from the GEO database was used for external validation. Finally, a nomogram was constructed based on the gene signature and clinical features to improve the risk stratification and to quantify the risk assessment for individual patients. Results: Hypoxia and the immune status were significantly associated with the prognosis of osteosarcoma patients. Seven hypoxia- and immune-related genes (BNIP3, SLC38A5, SLC5A3, CKMT2, S100A3, CXCL11 and PGM1) were identified to be involved in our prognostic signature. In the training cohort, the prognostic signature discriminated high-risk patients with osteosarcoma. The hypoxia-immune-based gene signature proved to be a stable and predictive method as determined in different datasets and subgroups of patients. Furthermore, a nomogram based on the prognostic signature was generated to optimize the risk stratification and to quantify the risk assessment. Similar results were validated in an independent GEO cohort, confirming the stability and reliability of the prognostic signature. Conclusion: The hypoxia-immune-based prognostic signature might contribute to the optimization of risk stratification for survival and personalized management of osteosarcoma patients.

Construction and validation of prognostic signature for hepatocellular carcinoma basing on hepatitis B virus related specific genes

BACKGROUND

Hepatocellular carcinoma (HCC) is a frequent primary liver cancer, and it is one of the leading cause of cancer-related deaths. Hepatitis B virus (HBV) infection is a crucial risk factor for HCC. Thus, this study aimed to explore the prognostic role of HBV-positive HCC related specific genes in HCC.

METHODS

The HCC related data were downloaded from three databases, including The Cancer Genome Atlas (TCGA), International Cancer Genome Consortium (ICGC), and Gene Expression Omnibus (GEO). Univariate Cox regression analysis and LASSO Cox regression analysis were conducted to build the Risk score. Multivariate Cox regression analysis and survival analysis determined the independent prognostic indicators.

RESULTS

After cross analysis of differentially expressed genes (DEGs), we have identified 106 overlapped DEGs, which were probably HBV-positive HCC related specific genes. These 106 DEGs were significantly enriched in 213 GO terms and 8 KEGG pathways. Among that, 11 optimal genes were selected to build a Risk score, and Risk score was an independent prognostic factor for HCC. High risk HCC patients had worse OS. Moreover, five kinds of immune cells were differentially infiltrated between high and low risk HCC patients.

CONCLUSION

The prognostic signature, based on HMMR, MCM6, TPX2, KIF20A, CCL20, RGS2, NUSAP1, FABP5, FZD6, PBK, and STK39, is conducive to distinguish different prognosis of HCC patients.

Comparative transcriptomics of high-altitude Vulpes and their low-altitude relatives

The harsh environment of Qinghai-Tibet Plateau (QTP) imposes strong selective stresses (e.g., hypoxia, high UV-radiation, and extreme temperature) to the native species, which have driven striking phenotypic and genetic adaptations. Although the mechanisms of high-altitude adaptation have been explored for many plateau species, how the phylogenetic background contributes to genetic adaption to high-altitude of Vulpes is largely unknown. In this study, we sequenced transcriptomic data across multiple tissues of two high-altitude Vulpes (Vulpes vulpes montana and Vulpes ferrilata) and their low-altitude relatives (Vulpes corsac and Vulpes lagopus) to search the genetic and gene expression changes caused by high-altitude environment. The results indicated that the positive selection genes (PSGs) identified by both high-altitude Vulpes are related to angiogenesis, suggesting that angiogenesis may be the result of convergent evolution of Vulpes in the face of hypoxic selection pressure. In addition, more PSGs were detected in V. ferrilata than in V. v. montana, which may be related to the longer adaptation time of V. ferrilata to plateau environment and thus more genetic changes. Besides, more PSGs associated with high-altitude adaptation were identified in V. ferrilata compared with V. v. montana, indicating that the longer the adaptation time to the high-altitude environment, the more genetic alterations of the species. Furthermore, the result of expression profiles revealed a tissue-specific pattern between Vulpes. We also observed that differential expressed genes in the high-altitude group exhibited species-specific expression patterns, revealed a convergent expression pattern of Vulpes in high-altitude environment. In general, our research provides a valuable transcriptomic resource for further studies, and expands our understanding of high-altitude adaptation within a phylogenetic context.

Hallmark-guided subtypes of hepatocellular carcinoma for the identification of immune-related gene classifiers in the prediction of prognosis, treatment efficacy, and drug candidates

Hepatocellular carcinoma (HCC), accounting for ~90% of all primary liver cancer, is a prevalent malignancy worldwide. The intratumor heterogeneity of its causative etiology, histology, molecular landscape, and immune phenotype makes it difficult to precisely recognize individuals with high mortality risk or tumor-intrinsic treatment resistance, especially immunotherapy. Herein, we comprehensively evaluated the activities of cancer hallmark gene sets and their correlations with the prognosis of HCC patients using gene set variation analysis (GSVA) and identified two HCC subtypes with distinct prognostic outcomes. Based on these subtypes, seven immune-related genes (TMPRSS6, SPP1, S100A9, EPO, BIRC5, PLXNA1, and CDK4) were used to construct a novel prognostic gene signature [hallmark-guided subtypes-based immunologic signature (HGSIS)] via multiple statistical approaches. The HGSIS-integrated nomogram suggested an enhanced predictive performance. Interestingly, oncogenic hallmark pathways were significantly enriched in the high-risk group and positively associated with the risk score. Distinct mutational landscapes and immune profiles were observed between different risk groups. Moreover, immunophenoscore (IPS) and tumor immune dysfunction and exclusion (TIDE) analysis showed different sensitivities of HGSIS risk groups for immune therapy efficacy, and the pRRophetic algorithm indicated distinguishable responses for targeted/chemotherapies in different groups. KIF2C was picked out as the key target concerning HGSIS, and the top 10 small molecules were predicted to bind to the active site of KIF2C via molecular docking, which might be further used for candidate drug discovery of HCC. Taken together, our study offers novel insights for clinically significant subtype recognition, and the proposed signature may be a helpful guide for clinicians to improve the treatment regimens.

A novel HCC prognosis predictor PDSS1 affects the cell cycle through the STAT3 signaling pathway in HCC

Decaprenyl diphosphate synthase subunit 1 (PDSS1) is closely related to a variety of human diseases, but its expression pattern and biological function in HCC have not been studied to date.

Methods

The expression level of PDSS1 was analyzed using the TCGA and GEO databases. The relationships between PDSS1 and patient clinicopathological characteristics were verified based on TCGA clinical data. Additionally, the co-expressed genes of PDSS1were investigated and Gene Set Enrichment Analysis (GSEA) was conducted using LinkedOmics. Next, the association between PDSS1 and immune infiltration was determined using version 1.34.0 of the GSVA package. EdU assay, colony-formation assay, transwell assay, wound-healing assay, and flow cytometry analysis were used to assess the effect of PDSS1 on the cell phenotype.

Results

PDSS1 was upregulated in HCC compared with adjacent tissues. High PDSS1 in HCC was associated with poor overall survival, disease-specific survival, and progress-free interval. Results suggested that PDSS1 may activate multiple oncogenic pathways in HCC, especially those involved in the cell cycle. The expression of PDSS1 was significantly related to Th2 cells, TFH, T helper cells, NK CD56bright cells, cytotoxic cells, DC, CD8 T cells, and neutrophils. PDSS1 knockdown inhibited cell proliferation, cell cycle, migration and invasion. Furthermore, PDSS1 acted as an oncogene through the STAT3 signaling pathway.

Conclusion

Our study reveals that a high level of PDSS1 is significantly correlated with poor patient prognosis and immune cell infiltration in HCC. PDSS1 may be a novel biomarker and potential therapeutic target for HCC.

Identifying a Novel Endoplasmic Reticulum-Related Prognostic Model for Hepatocellular Carcinomas

From the standpoint of the ER (endoplasmic reticulum), we were interested in identifying hub genes that impact clinical prognosis for HCC (hepatocellular carcinoma) patients and developing an ER-related prognostic model. Using TCGA-LIHC (The Cancer Genome Atlas-Liver Hepatocellular Carcinoma) and GSE14520 datasets, we conducted a series of analyses, which included differential gene screening, clinical prognostic analysis, Lasso regression, nomogram prediction, tumour clustering, gene functional enrichment, and tumour infiltration of immune cells. Following our screening for ER-related genes ( $n=1975$ ), we conducted a Lasso regression model to obtain five hub genes, KPNA2, FMO3, SPP1, KIF2C, and LPCAT1, using TCGA-LIHC as a training set. According to risk scores, HCC samples within either the TCGG-LIHC or GSE14520 cohort were categorized into high- and low-risk groups. Compared to the high-risk group of HCC patients, patients in the low-risk group had a better prognosis of OS (overall survival) or RFS (relapse-free survival). For TCGA-LIHC training set, with the factors of risk score, stage, age, and sex, we plotted a nomogram for 1-, 3-, and 5-year survival predictions. Our model demonstrated better clinical validity in both TCGA-LIHC and GSE14520 cohorts. Additionally, events related to biological enzyme activity, biological metabolic processes, or the cell cycle were associated with the prognostic risk of ER. Furthermore, two HCC prognosis-associated tumour clusters were identified by ER hub gene-based consensus clustering. Our findings indicated a link between ER prognostic signature-related high/low risk and tumour infiltration levels of several immune cells, such as “macrophages M2/M0” and “regulatory T cells (Tregs).” Overall, we developed a novel ER-related clinical prognostic model for HCC patients.

A Novel and Robust Prognostic Model for Hepatocellular Carcinoma Based on Enhancer RNAs-Regulated Genes

Evidence has demonstrated that enhancer RNAs (eRNAs) play a vital role in the progression and prognosis of cancers, but few studies have focused on the prognostic ability of eRNA-regulated genes (eRGs) for hepatocellular carcinoma (HCC). Using gene expression profiles of HCC patients from the TCGA-LIHC and eRNA expression profiles from the enhancer RNA in cancers (eRic) data portal, we developed a novel and robust prognostic signature composed of 10 eRGs based on Lasso-penalized Cox regression analysis. According to the signature, HCC patients were stratified into high- and low-risk groups, which have been shown to have significant differences in tumor immune microenvironment, immune checkpoints, HLA-related genes, DNA damage repair-related genes, Gene-set variation analysis (GSVA), and the lower half-maximal inhibitory concentration (IC50) of Sorafenib. The prognostic nomogram combining the signature, age, and TNM stage had good predictive ability in the training set (TCGA-LIHC) with the concordance index (C-index) of 0.73 and the AUCs for 1-, 3-, and 5-year OS of 0.82, 0.77, 0.74, respectively. In external validation set (GSE14520), the nomogram also performed well with the C-index of 0.71 and the AUCs for 1-, 3-, and 5-year OS of 0.74, 0.77, 0.74, respectively. In addition, an important eRG (AKR1C3) was validated using two HCC cell lines (Huh7 and MHCC-LM3) in vitro, and the results demonstrated the overexpression of AKR1C3 is related to cell proliferation, migration, and invasion in HCC. Altogether, our eRGs signature and nomogram can predict prognosis accurately and conveniently, facilitate individualized treatment, and improve prognosis for HCC patients.

A novel hypoxia-driven gene signature that can predict the prognosis of hepatocellular carcinoma

Hypoxia environment exists in already started hepatocellular carcinoma (HCC) and promotes its progression by driving changes in the gene expression profiles of cells. However, the status of hypoxia-driven genes in HCC is largely unknown. In the present study, 368 HCC tissues from The Cancer Genome Atlas were divided into high and low hypoxia groups according to their hypoxia signatures. A total of 1,142 differentially expressed genes (DEGs) were identified between the two groups, and 34 of these DEGs were highly expressed in HCC tissues compared with adjacent tissues, especially in HCC tissues from patients with stage III-IV HCC. After constructing a protein-protein interaction network and applying the least absolute shrinkage and selection operator Cox regression method for 34 DEGs, a three-gene signature (complement factor H related 3 [CFHR3], egl-9 family hypoxia inducible factor 3 [EGLN3], and chromogranin A [CHGA]) was constructed and had prognostic value to predicted outcome of patients with HCC. This three-gene signature was suitable for classifying patients with HCC in the International Cancer Genome Consortium. CFHR3 shows remarkable diagnostic value in HCC. Hypoxia decreased CFHR3 expression, but increased HCC cell proliferation and motility. Overexpression of CFHR3 in HCC cells under hypoxia reversed the stimulatory effects of hypoxia and suppressed cell proliferation and metastasis in vivo. In conclusion, we identified a novel hypoxia-driven gene signature (CFHR3, EGLN3, and CHGA) for reliable prognostic prediction of HCC, and demonstrated that overexpression of CFHR3 may be a potential strategy to overcome hypoxia and treat HCC.

DNTTIP2 Expression is Associated with Macrophage Infiltration and Malignant Characteristics in Low-Grade Glioma

Purpose

Methods

Results

Conclusion

8DEstablishment and validation of a hypoxia-related signature predicting prognosis in hepatocellular carcinoma

Background

Hypoxia plays a crucial role in immunotherapy of hepatocellular carcinoma (HCC) by changing the tumor microenvironment. Until now the association between hypoxia genes and prognosis of HCC remains obscure. We attempt to construct a hypoxia model to predict the prognosis in HCC.

Results

We screened out 3 hypoxia genes (ENO1, UGP2, TPI1) to make the model, which can predict prognosis in HCC. And this model emerges as an independent prognostic factor for HCC. A Nomogram was drawn to evaluate the overall survival in a more accurate way. Furthermore, immune infiltration state and immunosuppressive microenvironment of the tumor were detected in high-risk patients.

Conclusion

We establish and validate a risk prognostic model developed by 3 hypoxia genes, which could effectively evaluate the prognosis of HCC patients. This prognostic model can be used as a guidance for hypoxia modification in HCC patients undergoing immunotherapy.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12876-021-02057-0.

Establishment of a novel ferroptosis-related lncRNA pair prognostic model in colon adenocarcinoma

Long non-coding RNAs (lncRNAs) have been reported to be prognostic factors for cancer. Ferroptosis is an iron-dependent process of programmed cell death. Here, we established a ferroptosis-related lncRNA (frlncRNA) pair signature and revealed its prognostic value in colon adenocarcinoma (COAD) by analyzing the data from The Cancer Genome Atlas (TCGA). FrlncRNAs were identified based on co-expression analysis using the Pearson correlation. Differentially expressed frlncRNAs (DEfrlncRNAs) were recognized and paired, followed by prognostic assessment using univariate Cox regression analysis. The least absolute shrinkage and selection operator (LASSO) penalized Cox analysis was used to determine and construct a risk score prognostic model, by which the receiver operating characteristic (ROC) curves for predicting the overall survival (OS) were conducted. Following the evaluation of whether it was an independent prognostic factor, correlations between the risk score model and clinicopathological characteristics, hypoxia- and immune-related factors, and somatic variants were investigated. In total, 148 DEfrlncRNA pairs were identified, 25 of which were involved in a risk score prognostic signature. The area under ROC curves (AUCs) representing the predictive effect for 1-, 3-, and 5-year survival rates were 0.860, 0.885, and 0.934, respectively. The risk score model was confirmed as an independent prognostic factor and was significantly superior to the clinicopathological characteristics. Correlation analyses showed disparities in clinicopathological characteristics, hypoxia- and immune-related factors, and somatic variants, as well as specific signaling pathways between high- and low-risk groups. The novel risk score prognostic model constructed by pairing DEfrlncRNAs showed promising clinical prediction value in COAD.

The REASON score: an epigenetic and clinicopathologic score to predict risk of poor survival in patients with early stage oral squamous cell carcinoma

BACKGROUND

Oral squamous cell carcinoma (OSCC) is a capricious cancer with poor survival rates, even for early-stage patients. There is a pressing need to develop more precise risk assessment methods to appropriately tailor clinical treatment. Genome-wide association studies have not produced a viable biomarker. However, these studies are limited by using heterogeneous cohorts, not focusing on methylation although OSCC is a heavily epigenetically-regulated cancer, and not combining molecular data with clinicopathologic data for risk prediction. In this study we focused on early-stage (I/II) OSCC and created a risk score called the REASON score, which combines clinicopathologic characteristics with a 12-gene methylation signature, to predict the risk of 5-year mortality.

METHODS

We combined data from an internal cohort (n = 515) and The Cancer Genome Atlas (TCGA) cohort (n = 58). We collected clinicopathologic data from both cohorts to derive the non-molecular portion of the REASON score. We then analyzed the TCGA cohort DNA methylation data to derive the molecular portion of the risk score.

RESULTS

5-year disease specific survival was 63% for the internal cohort and 86% for the TCGA cohort. The clinicopathologic features with the highest predictive ability among the two the cohorts were age, race, sex, tobacco use, alcohol use, histologic grade, stage, perineural invasion (PNI), lymphovascular invasion (LVI), and margin status. This panel of 10 non-molecular features predicted 5-year mortality risk with a concordance (c)-index = 0.67. Our molecular panel consisted of a 12-gene methylation signature (i.e., HORMAD2, MYLK, GPR133, SOX8, TRPA1, ABCA2, HGFAC, MCPH1, WDR86, CACNA1H, RNF216, CCNJL), which had the most significant differential methylation between patients who survived vs. died by 5 years. All 12 genes have already been linked to survival in other cancers. Of the genes, only SOX8 was previously associated with OSCC; our study was the first to link the remaining 11 genes to OSCC survival. The combined molecular and non-molecular panel formed the REASON score, which predicted risk of death with a c-index = 0.915.

CONCLUSIONS

The REASON score is a promising biomarker to predict risk of mortality in early-stage OSCC patients. Validation of the REASON score in a larger independent cohort is warranted.

Oncogenic Potential of the Dual-Function Protein MEX3A

MEX3A belongs to the MEX3 (Muscle EXcess) protein family consisting of four members (MEX3A-D) in humans. Characteristic for MEX3 proteins is their domain structure with 2 HNRNPK homology (KH) domains mediating RNA binding and a C-terminal really interesting new gene (RING) domain that harbors E3 ligase function. In agreement with their domain composition, MEX3 proteins were reported to modulate both RNA fate and protein ubiquitination. MEX3 paralogs exhibit an oncofetal expression pattern, they are severely downregulated postnatally, and re-expression is observed in various malignancies. Enforced expression of MEX3 proteins in various cancers correlates with poor prognosis, emphasizing their oncogenic potential. The latter is supported by MEX3A's impact on proliferation, self-renewal as well as migration of tumor cells in vitro and tumor growth in xenograft studies.