DNASE1L3 as an indicator of favorable survival in hepatocellular carcinoma patients following resection

Constructing a prognostic model for hepatocellular carcinoma based on bioinformatics analysis of inflammation-related genes

Background

This study aims to screen inflammation-related genes closely associated with the prognosis of hepatocellular carcinoma (HCC) to accurately forecast the prognosis of HCC patients.

Methods

Gene expression matrices and clinical information for liver cancer samples were obtained from the Cancer Genome Atlas (TCGA) and the International Cancer Genome Consortium (ICGC). An intersection of differentially expressed genes of HCC and normal and GeneCards yielded inflammation-related genes associated with HCC. Cox regression and the minor absolute shrinkage and selection operator (LASSO) regression analysis to filter genes associated with HCC prognosis. The prognostic value of the model was confirmed by drawing Kaplan-Meier and ROC curves. Select differentially expressed genes between the high-risk and low-risk groups and perform GO and KEGG pathways analyses. CIBERSORT analysis was conducted to assess associations of risk models with immune cells and verified using real-time qPCR.

Results

A total of six hub genes (C3, CTNNB1, CYBC1, DNASE1L3, IRAK1, and SERPINE1) were selected using multivariate Cox regression to construct a prognostic model. The validation evaluation of the prognostic model showed that it has an excellent ability to predict prognosis. A line plot was drawn to indicate the HCC patients' survival, and the calibration curve revealed satisfactory predictability. Among the six hub genes, C3 and DNASE1L3 are relatively low expressed in HCCLM3 and 97H liver cancer cell lines, while CTNNB1, CYBC1, IRAK1, and SERPINE1 are relatively overexpressed in liver cancer cell lines.

Conclusion

One new inflammatory factor-associated prognostic model was constructed in this study. The risk score can be an independent predictor for judging the prognosis of HCC patients' survival.

Deoxyribonuclease 1-like 3 inhibits colorectal malignancy through antagonizing NEDD4-triggered CDKN1A ubiquitination

Deoxyribonuclease 1-like 3 (DNASE1L3) has been shown to play nonnegligible roles in several types of carcinomas. Nevertheless, the biological function, clinical relevance, and influence of DNASE1L3 in colorectal cancer (CRC) remain obscure. Immunohistochemistry was adopted to examine DNASE1L3 and CDKN1A expression in CRC tissue, and the clinical significance of DNASE1L3 was assessed. Cell counting kit-8, colony formation, and transwell assays were employed for assessing tumor proliferation and migration. The mechanisms underlying the impact of DNASE1L3 were explored via western blot analysis, co-immunoprecipitation, and ubiquitination assay. It was observed that DNASE1L3 was downregulated in CRC tissues and was tightly associated with patient prognosis. DNASE1L3 impaired CRC cell proliferation and migration through elevating CDKN1A via suppressing CDKN1A ubiquitination. Meanwhile, DNASE1L3 was positively related to CDKN1A. In mechanism, DNASE1L3 and CDKN1A interacted with the E3 ubiquitin ligase NEDD4. Moreover, DNASE1L3 was competitively bound to NEDD4, thus repressing NEDD4-mediated CDKN1A ubiquitination and degradation. These discoveries implied the potential mechanisms of DNASE1L3 during tumorigenesis, suggesting that DNASE1L3 may serve as a new potential therapeutic agent for CRC.

A novel prognostic signature based on immunogenic cell death score predicts outcomes and response to transcatheter arterial chemoembolization and immunotherapy in hepatocellular carcinoma

PURPOSE

The phenomenon of immunogenic cell death (ICD) is intricately linked to numerous antitumor treatments and exerts a profound regulatory function in the tumor immune microenvironment (TIME). We aimed to establish a prognostic signature from the ICD-related biomarkers to differentiate the TIME in hepatocellular carcinoma and predict diverse outcomes for patients with liver cancer.

METHODS

ICD score-related genes (ICDSGs) were identified using the weighted gene co-expression network analysis (WGCNA). The ICD score-related signature (ICDSsig) was established by applying LASSO and Cox regression. Model precision was verified using the external datasets. We used independent prognostic variables in clinicopathologic factors to develop a nomogram. Further, clinical characteristics, immune and molecular landscapes, the responses of transcatheter arterial chemoembolization (TACE) and immunotherapy, and chemotherapy sensitivity were analyzed for high- and low-risk patients.

RESULTS

ICD score-calculated using the single-sample gene set enrichment analysis (ssGSEA)-displayed strong associations with the TIME in HCC. We identified 34 ICDSGs after integrating the TCGA and GSE104580 datasets. Then, three novel ICDSGs (DNASE1L3, KLRB1, and LILRB1) were screened out to construct the ICDSsig; the prognostic signature performed well in the external databases. The high-risk patients had worse outcomes owing to their advanced pathological state, non-response of TACE, and immune-cold phenotype in the immune landscapes. The immune checkpoint genes, N6-methyladenosine-relevant genes, and microsatellite instability score were increased in the high-risk subgroup, thereby indicating a favorable sensitivity to immunotherapy. Common chemotherapy drugs were more effective in high-risk patients due to low half-maximal inhibitory concentration values.

CONCLUSION

The ICDSsig can potentially predict outcomes and therapeutic responses for patients with liver cancer and may assist clinicians in designing individualized treatment strategies.

Integrative analysis of deoxyribonuclease 1-like 3 as a potential biomarker in renal cell carcinoma

Background

Clear cell renal cell carcinoma (ccRCC), the most common subtype of renal cell carcinoma (RCC), is insensitive to radiotherapy and chemotherapy after surgery. Deoxyribonuclease 1-like 3 (DNASE1L3), an endonuclease that cleaves both membrane-encapsulated single- and double-stranded DNA, suppresses cell cycle progression, proliferation and metabolism in hepatocellular carcinoma cells. There is currently no established link between DNASE1L3 and RCC inhibition. We are gonging to explored the mechanism underlying the relationship between DNASEL1L3 and RCC.

Methods

RNA sequencing data for RCC tissue and peritumoral tissue were downloaded from The Cancer Genome Atlas database and analyzed. The expression levels of DNASE1L3 in RCC and normal samples were verified using the Gene Expression Omnibus (GEO) database, Human Protein Atlas database and western blotting. The role and potential mechanism of DNASE1L3 were investigated by analysis of immune-related databases and wound healing, invasion, cell counting kit 8 and immunofluorescence assays.

Results

We revealed that DNASE1L3 expression was downregulated in RCC group compared with control group [The Cancer Genome Atlas (TCGA): 7.98 vs. 10.87, P<0.001]. Meanwhile, DNASE1L3 expression correlated with the clinical characteristics of patients. Patients with low DNASE1L3 expression had worse survival (P<0.001) and larger (r=-0.32, P<0.001) and heavier tumors (r=-0.17, P<0.001). DNASE1L3 overexpression inhibited the proliferation (786-O: 0.135±0.014 vs. 0.322±0.027, P<0.001) and invasion (786-O: 1,479±134 vs. 832±67, P<0.05) of RCC cells. The expression of DNASE1L3 was significantly correlated with the tumor immune microenvironment and drug sensitivity in ccRCC. Moreover, the level of the key phosphoinositide 3-kinase (PI3K)/protein kinase B (AKT) signaling pathway protein P-AKT was decreased in the group of cells transfected with DNASE1L3.

Conclusions

This study strongly suggest that DNASE1L3 may be a promising potential biomarker for the diagnosis and treatment of ccRCC patients.

Inflammation-Based Prognostic Scores in Pancreatic Cancer Patients-A Single-Center Analysis of 1294 Patients within the Last Decade

Inflammatory properties are known to promote tumor progression leading to an impaired median overall survival (mOS). Various small studies have focused on a wide range of inflammation-based prognostic indicators. By using sufficient data from 1294 out of 2323 patients diagnosed with pancreatic cancer between 2009 and 2021 at our cancer center, inflammatory markers such as the neutrophil to lymphocyte ratio (NRL), the platelet to lymphocyte ratio (PLR), the lymphocyte to monocyte ratio (LMR) and the CRP to albumin ratio (CAR) were evaluated. We identified a new combined score, termed the inflammatory benchmark index (IBI). We performed univariate and multivariate overall survival analyses and identified optimal prognostic cut-off values for each parameter. In univariate analyses, advanced age (p < 0.001), gender (p < 0.001), tumor stage (p < 0.001), CA19-9 (p = 0.001), NLR (p = 0.001), LMR (p = 0.004), PLR (p = 0.004), CAR (p = 0.001) and IBI (p = 0.001) were identified as prognostic markers. In multivariate analyses advanced age (p < 0.001), gender (p = 0.001), tumor stage (p < 0.001), CA19-9 (p < 0.001), NLR (p = 0.001), LMR (p = 0.038), CAR (p < 0.001) and IBI (p < 0.001) were independent prognostic markers. These findings emphasize the impact of inflammation in pancreatic cancer, provide easily accessible prognostic values for the clinician, and may be useful as stratification parameters for trials aimed at patient inflammation or immune response.

Regulative Roles of Metabolic Plasticity Caused by Mitochondrial Oxidative Phosphorylation and Glycolysis on the Initiation and Progression of Tumorigenesis

One important feature of tumour development is the regulatory role of metabolic plasticity in maintaining the balance of mitochondrial oxidative phosphorylation and glycolysis in cancer cells. In recent years, the transition and/or function of metabolic phenotypes between mitochondrial oxidative phosphorylation and glycolysis in tumour cells have been extensively studied. In this review, we aimed to elucidate the characteristics of metabolic plasticity (emphasizing their effects, such as immune escape, angiogenesis migration, invasiveness, heterogeneity, adhesion, and phenotypic properties of cancers, among others) on tumour progression, including the initiation and progression phases. Thus, this article provides an overall understanding of the influence of abnormal metabolic remodeling on malignant proliferation and pathophysiological changes in carcinoma.

Molecular Mechanisms of Neutrophil Extracellular Trap (NETs) Degradation

Although many studies have been exploring the mechanisms driving NETs formation, much less attention has been paid to the degradation and elimination of these structures. The NETs clearance and the effective removal of extracellular DNA, enzymatic proteins (neutrophil elastase, proteinase 3, myeloperoxidase) or histones are necessary to maintain tissue homeostasis, to prevent inflammation and to avoid the presentation of self-antigens. The persistence and overabundance of DNA fibers in the circulation and tissues may have dramatic consequences for a host leading to the development of various systemic and local damage. NETs are cleaved by a concerted action of extracellular and secreted deoxyribonucleases (DNases) followed by intracellular degradation by macrophages. NETs accumulation depends on the ability of DNase I and DNAse II to hydrolyze DNA. Furthermore, the macrophages actively engulf NETs and this event is facilitated by the preprocessing of NETs by DNase I. The purpose of this review is to present and discuss the current knowledge about the mechanisms of NETs degradation and its role in the pathogenesis of thrombosis, autoimmune diseases, cancer and severe infections, as well as to discuss the possibilities for potential therapeutic interventions. Several anti-NETs approaches had therapeutic effects in animal models of cancer and autoimmune diseases; nevertheless, the development of new drugs for patients needs further study for an effective development of clinical compounds that are able to target NETs.

MARCKS is a New Prognostic Biomarker in Hepatocellular Carcinoma

Background

Hepatocellular carcinoma (HCC) is one of the most common type of cancers, but there is still a lack of known biomarkers for the effective diagnosis or prognosis of HCC. Myristoylated alanine-rich C-kinase substrate (MARCKS) is a substrate of protein kinase C, which was located in the cell plasma membrane. The purpose of our study was to evaluate the role of MARCKS in HCC.

Methods

The role of MARCKS in HCC was explored by bioinformatics and experiment.

Results

We demonstrated that MARCKS expression was significantly elevated in HCC datasets of TCGA. MARCKS was up-regulated in tumor sample in HCC. Functional enrichment indicated that MARCKS-related differentially expressed genes (DEGs) were mainly enriched in cell junction tissue, response to growth factors and cell population proliferation. Tumor and ECM-receptor interactions related pathways were enriched by the KEGG. MARCKS expression in HCC patients was higher in females, younger individuals, and those at worse clinical stages. Cox regression analysis showed that MARCKS expression was a risk factor for overall survival and disease-specific survival of patients.

Conclusion

MARCKS was up-regulated in HCC, may play a crucial role in HCCs, and has prognostic value for clinical outcomes.

Development and Validation of Prognostic Nomograms for Hepatocellular Carcinoma After Hepatectomy Based on Inflammatory Markers

Background

The value of lactate dehydrogenase (LDH) compared with other inflammation-based scores in predicting the outcomes of hepatitis B virus (HBV)-related hepatocellular carcinoma (HCC) patients after curative resection remains unknown. This study aims to evaluate the predictive value of LDH and develop novel nomograms to predict postoperative recurrence and survival in these patients.

Methods

This study retrospectively collected 1560 patients with HBV-related HCC who underwent curative resection from four institutions in China. In total, 924 patients were recruited from our center and randomly divided into the training cohort (n = 616) and internal validation (n = 308) cohorts. Additionally, 636 patients were selected from three other centers as the external validation cohort. The C index of inflammation-based scores was calculated and compared in the training cohort. Novel models were developed according to multivariable Cox regression analysis in the training cohort and validated in the internal and external validation cohorts.

Results

LDH showed a higher C-index than other inflammation-based scores for recurrence survival (RFS, 0.60, 95% CI, 0.58-0.61) and overall survival (OS, 0.65, 95% CI, 0.63-0.68). The nomograms of RFS and OS were developed based on tumor diameter, macrovascular invasion, AFP, operative hemorrhage, tumor differentiation, tumor number and LDH and achieved a high C-index (0.78, 95% CI, 0.76-0.79 and 0.81, 95% CI, 0.79-0.83), which were remarkably higher than the C-indexes of the five conventional HCC staging systems (0.52-0.62 for RFS and 0.53-0.67 for OS). The nomograms were validated in the internal validation cohort (0.77 for RFS, 0.78 for OS) and external validation cohort (0.80 for RFS, 0.81 for OS) and performed well-fitted calibration curves.

Conclusion

The two nomograms based on inflammatory markers achieved optimal prediction for RFS and OS of patients with HBV-related HCC after hepatectomy.

DNASE1L3 inhibits hepatocellular carcinoma by delaying cell cycle progression through CDK2

PURPOSE

Dysregulated cell cycle targeting is a well-established therapeutic strategy against hepatocellular carcinoma (HCC). Dissecting the underlying mechanism may improve the efficacy of HCC therapy.

METHODS

HCC data from TCGA and new clinical samples were used for DNASE1L3 expression analysis and for assessing its correlation with HCC development. The in vitro function of DNASE1L3 in HCC cell proliferation, colony formation, migration and invasion was assessed using RTCA, CCK-8 and transwell assays and the in vivo function in subcutaneous tumor formation in a xenograft nude mouse model. The role of DNASE1L3 in HCC tumorigenesis was further verified in AKT/NRASV12-induced and DEN/CCl₄-induced primary liver cancers in wildtype and Dnase1l3^-/- mice. Finally, RNA-Seq analysis followed by biochemical methods including cell cycle, immunofluorescence, co-immunoprecipitation and Western blotting assays were employed to reveal the underlying mechanism.

RESULTS

We found that DNASE1L3 was significantly downregulated and served as a favorable prognostic factor in HCC. DNASE1L3 dramatically attenuated HCC cell proliferation, colony formation, migration and invasion in vitro and reduced subcutaneous tumor formation in nude mice in vivo. Furthermore, DNASE1L3 overexpression dampened AKT/NRASV12-induced mouse liver cancer in wildtype mice and DNASE1L3 deficiency worsened DEN/CCl₄-induced liver cancer in Dnase1l3^-/- mice. Systemic analysis revealed that DNASE1L3 impaired HCC cell cycle progression by interacting with CDK2 and inhibiting CDK2-stimulated E2F1 activity. C-terminal deletion (DNASE1L3^ΔCT) diminished the interaction with CDK2 and abrogated the inhibitory function against HCC.

CONCLUSION

Our study unveils DNASE1L3 as a novel HCC cell cycle regulator and tumor suppressor. DNASE1L3 impairs HCC tumorigenesis by delaying cell cycle progression possibly through disrupting the positive E2F1-CDK2 regulatory loop. DNASE1L3 may serve as a target for the development of novel therapeutic strategies against HCC.

A universal co-expression gene network and prognostic model for hepatic-biliary-pancreatic cancers identified by integrative analyses

Hepatic, biliary and pancreatic cancers are a diverse set of malignancies with poor prognoses. It is possible that common molecular mechanisms are involved in the carcinogenesis of these cancers. Here, we identified LINC01537 and seven protein-coding genes by integrative analysis of transcriptomes of mRNAs, microRNAs and long non-coding RNAs from cholangiocarcinoma, hepatocellular carcinoma and pancreatic adenocarcinoma cohorts in TCGA. A predictive model constructed from seven biomarkers was established to successfully predict the survival rate of patients, which was then further verified in external cohorts. Additionally, patients with high-risk scores in our model were prone to epithelial-mesenchymal transition. Finally, activation of the biomarker PDE2A significantly attenuated migration and epithelial-mesenchymal transition in the HepG2 liver cancer cell line.

DNASE1L3 inhibits proliferation, invasion and metastasis of hepatocellular carcinoma by interacting with β-catenin to promote its ubiquitin degradation pathway

As a member of the deoxyribonuclease 1 family, DNASE1L3 plays a significant role both inside and outside the cell. However, the role of DNASE1L3 in hepatocellular carcinoma (HCC) and its molecular basis remains to be further investigated. In this study, we report that DNASE1L3 is downregulated in clinical HCC samples and evaluate the relationship between its expression and HCC clinical features. In vivo and in vitro experiments showed that DNASE1L3 negatively regulates the proliferation, invasion and metastasis of HCC cells. Mechanistic studies showed that DNASE1L3 recruits components of the cytoplasmic β‐catenin destruction complex (GSK‐3β and Axin), promotes the ubiquitination degradation of β‐catenin, and inhibits its nuclear transfer, thus, decreasing c‐Myc, P21 and P27 level. Ultimately, cell cycle and EMT signals are restrained. In general, this study provides new insight into the mechanism for HCC and suggests that DNASE1L3 can become a considerable target for HCC.

Deficient DNASE1L3 facilitates neutrophil extracellular traps-induced invasion via cyclic GMP-AMP synthase and the non-canonical NF-κB pathway in diabetic hepatocellular carcinoma

Objective

Diabetic hepatocellular carcinoma (HCC) patients have high mortality and metastasis rates. Diabetic conditions promote neutrophil extracellular traps (NETs) generation, which mediates HCC metastasis and invasion. However, whether and how diabetes-induced NETs trigger HCC invasion is largely unknown. Here, we aimed to observe the effects of diabetes-induced NETs on HCC invasion and investigate mechanisms relevant to a DNA sensor cyclic GMP-AMP synthase (cGAS).

Methods

Serum from diabetic patients and healthy individuals was collected. Human neutrophil-derived NETs were isolated for stimulating HCC cell invasion. Data from the SEER and TCGA databases were used for bioinformatics analysis. In HCC cells and allograft models, NETs-triggered invasion was observed.

Results

Diabetic HCC patients had poorer survival than non-diabetic ones. Either diabetic serum or extracted NETs caused HCC invasion. Induction of diabetes or NETosis elicited HCC allograft invasion in nude mice. HCC cell invasion was attenuated by the treatment with DNase1. In TCGA_LIHC, an extracellular DNase DNASE1L3 was downregulated in tumor tissues, while function terms (the endocytic vesicle membrane, the NF-κB pathway and extracellular matrix disassembly) were enriched. DNASE1L3 knockdown in LO2 hepatocytes or H22 cell-derived allografts facilitated HCC invasion in NETotic or diabetic nude mice. Moreover, exposure of HCC cells to NETs upregulated cGAS and the non-canonical NF-κB pathway and induced expression of metastasis genes (MMP9 and SPP1). Both cGAS inhibitor and NF-κB RELB knockdown diminished HCC invasion caused by NETs DNA. Also, cGAS inhibitor was able to retard translocation of NF-κB RELB.

Conclusion

Defective DNASE1L3 aggravates NETs DNA-triggered HCC invasion on diabetic conditions via cGAS and the non-canonical NF-κB pathway.

Prediction of Hepatocellular Carcinoma Prognosis and Immune Cell Infiltration Using Gene Signature Associated with Inflammatory Response

It has been demonstrated that the inflammatory response influences cancer development and can be used as a prognostic biomarker in various tumors. However, the relevance of genes associated with inflammatory responses in hepatocellular carcinoma (HCC) remains unknown. The Cancer Genome Atlas (TCGA) database was analyzed using weighted gene coexpression network analysis (WGCNA) and differential analysis to discover essential inflammatory response-related genes (IFRGs). Cox regression studies, both univariate and multivariate, were employed to develop a prognostic IFRGs signature. Additionally, Gene Set Enrichment Analysis (GSEA) was used to deduce the biological function of the IFRGs signature. Finally, we estimated immune cell infiltration using a single sample GSEA (ssGSEA) and x-cell. Our results revealed that, among the major HCC IFRGs, two (DNASE1L3 and KLKB1) were employed to create a predictive IFRG signature. The IFRG signature could correctly predict overall survival (O.S) as per Kaplan-Meier time-dependent roc curves analysis. It was also linked to pathological tumor stage and T stage and might be used as a prognostic predictor in HCC. GSEA analysis concluded that the IFRG signature might influence the immune response in HCC. Immunological cell infiltration and immune checkpoint molecule expression differed in the high-risk and low-risk groups. As a result of our findings, DNASILE may play a role in the tumor microenvironment. However, more research is necessary to confirm the role of DNASE1L3 and KLKB1.

Deoxyribonuclease 1-like 3 Inhibits Hepatocellular Carcinoma Progression by Inducing Apoptosis and Reprogramming Glucose Metabolism

HCC has remained one of the challenging cancers to treat, owing to the paucity of drugs targeting the critical survival pathways. Considering the cancer cells are deficient in DNase activity, the increase of an autonomous apoptisis endonuclease should be a reasonable choice for cancer treatment. In this study, we investigated whether DNASE1L3, an endonuclease implicated in apoptosis, could inhibit the progress of HCC. We found DNASE1L3 was down-regulated in HCC tissues, whereas its high expression was positively associated with the favorable prognosis of patients with HCC. Besides, serum DNASE1L3 levels were lower in HCC patients than in healthy individuals. Functionally, we found that DNASE1L3 inhibited the proliferation of tumor cells by inducing G0/G1 cell cycle arrest and cell apoptosis in vitro. Additionally, DNASE1L3 overexpression suppressed tumor growth in vivo. Furthermore, we found that DNASE1L3 overexpression weakened glycolysis in HCC cells and tissues via inactivating the rate-limiting enzymes involved in PTPN2-HK2 and CEBPβ-p53-PFK1 pathways. Finally, we identified the HBx to inhibit DNASE1L3 expression by up-regulating the expression of ZNF384. Collectively, our findings demonstrated that DNASE1L3 could inhibit the HCC progression through inducing cell apoptosis and weakening glycolysis. We believe DNASE1L3 could be considered as a promising prognostic biomarker and therapeutic target for HCC.

DNASE1L3 as a Novel Diagnostic and Prognostic Biomarker for Lung Adenocarcinoma Based on Data Mining

Previous researches have highlighted that low-expressing deoxyribonuclease1-like 3 (DNASE1L3) may play a role as a potential prognostic biomarker in several cancers. However, the diagnosis and prognosis roles of DNASE1L3 gene in lung adenocarcinoma (LUAD) remain largely unknown. This research aimed to explore the diagnosis value, prognostic value, and potential oncogenic roles of DNASE1L3 in LUAD. We performed bioinformatics analysis on LUAD datasets downloaded from TCGA (The Cancer Genome Atlas) and GEO (Gene Expression Omnibus), and jointly analyzed with various online databases. We found that both the mRNA and protein levels of DNASE1L3 in patients with LUAD were noticeably lower than that in normal tissues. Low DNASE1L3 expression was significantly associated with higher pathological stages, T stages, and poor prognosis in LUAD cohorts. Multivariate analysis revealed that DNASE1L3 was an independent factor affecting overall survival (HR = 0.680, p = 0.027). Moreover, decreased DNASE1L3 showed strong diagnostic efficiency for LUAD. Results indicated that the mRNA level of DNASE1L3 was positively correlated with the infiltration of various immune cells, immune checkpoints in LUAD, especially with some m6A methylation regulators. In addition, enrichment function analysis revealed that the co-expressed genes may participate in the process of intercellular signal transduction and transmission. GSEA indicated that DNASE1L3 was positively related to G protein-coupled receptor ligand biding (NES = 1.738; P adjust = 0.044; FDR = 0.033) and G alpha (i) signaling events (NES = 1.635; P adjust = 0.044; FDR = 0.033). Our results demonstrated that decreased DNASE1L3 may serve as a novel diagnostic and prognostic biomarker associating with immune infiltrates in lung adenocarcinoma.

Prognostic evaluation and immune infiltration analysis of five bioinformatic selected genes in hepatocellular carcinoma

Despite the development in hepatocellular carcinoma (HCC) treatment in recent years, the therapeutic outcome of HCC remains unfavourable. This study examines the prognosis of HCC from a genetic level using clinical databases and single‐cell data to identify genes with a high prognostic value. Three up‐regulated genes (UBE2S, PTTG1, and CDC20) and two down‐regulated genes (SOCS2 and DNASE1L3) in HCC tissues were identified. Various analyses confirmed its correlation with tumour stage (p < 0.01) and patient survival time (log‐rank p < 0.001). Immune analysis, single‐cell analysis, and gene set enrichment analysis (GSEA) were employed to provide insight on how they affect cancer progression, and we observed a close relation between these genes and tumour immune infiltration. Eventually, we constructed a risk score system that risk score = (0.0465) × UBE2S + (0.1851) × CDC20 + (−0.0461) × DNASE1L3 + (−0.2279) × SOCS2 (5‐year area under curve = 0.706). The risk score system may serve as an effective novel prognostic system for HCC patients. This study might provide novel ideas for prognostic or therapeutic biomarkers for HCC.

Transcriptional and epigenetic landscape of Ca2+-signaling genes in hepatocellular carcinoma

Calcium (Ca2+) signaling has a major role in regulating a wide range of cellular mechanisms, including gene expression, proliferation, metabolism, cell death, muscle contraction, among others. Recent evidence suggests that ~ 1600 genes are related to the Ca2+ signaling. Some of these genes' expression is altered in several pathological conditions, including different cancer types, and epigenetic mechanisms are involved. However, their expression and regulation in hepatocellular carcinoma (HCC) and the liver are barely known. Here, we aimed to explore the expression of genes involved in the Ca2+-signaling in HCC, liver regeneration, and hepatocyte differentiation, and whether their expression is regulated by epigenetic mechanisms such as DNA methylation and histone posttranslational modifications (HPM). Results show that several Ca2+-signaling genes' expression is altered in HCC samples; among these, a subset of twenty-two correlate with patients' survival. DNA methylation correlates with eight of these genes' expression, and Guadecitabine, a hypomethylating agent, regulates the expression of seven down-regulated and three up-regulated genes in HepG2 cells. The down-regulated genes displayed a marked decrease of euchromatin histone marks, whereas up-regulated genes displayed gain in these marks. Additionally, the expression of these genes is modulated during liver regeneration and showed similar profiles between in vitro differentiated hepatocytes and liver-derived hepatocytes. In conclusion, some components of the Ca2+-signaling are altered in HCC and displayed a correlation with patients' survival. DNA methylation and HMP are an attractive target for future investigations to regulate their expression. Ca2+-signaling could be an important regulator of cell proliferation and differentiation in the liver.

METTL3-mediated m6A methylation of ASPM drives hepatocellular carcinoma cells growth and metastasis

Background

Abnormal spindle‐like microcephaly (ASPM) has been proved to participate in tumor progression. However, the underlying mechanism of ASPM in liver hepatocellular carcinoma (LIHC) remains elusive.

Methods

The mRNA and protein expression were determined using Western blot and qRT‐PCR, and the capacities of cells proliferation, migration, and invasion were evaluated by CCK‐8, colony formation, wound healing, and transwell. MeRIP was performed to validate the interaction between ASPM and methyltransferase‐like 3 (METTL3).

Results

Herein, we found that ASPM was significantly upregulated in LIHC, and the high expression of ASPM was associated with poor LIHC prognosis. Furthermore, ASPM knockdown could suppress LIHC cells proliferation, migration, and invasion, while ASPM overexpression exerted reverse effect. Mechanistically, we revealed that the N6‐methyladenosine (m6A) modification of ASPM mRNA mediated by METTL3 promoted its expression in LIHC. More importantly, silencing METTL3 suppressed LIHC cells proliferation, migration, and invasion, which could be retained by ASPM overexpression.

Conclusion

Collectively, our findings suggested that METTL3/ASPM axis could serve as a novel promising therapeutic candidate for LIHC.

Deoxyribonuclease 1-like 3 may be a potential prognostic biomarker associated with immune infiltration in colon cancer

Colon adenocarcinoma (COAD) is a common cancer of the digestive system. It’s high morbidity and mortality make it one of the leading causes of cancer deaths. In this study, we studied the microenvironment of colon cancer to find new diagnostic markers and immunotherapy targets for colon cancer. Tumor purity of colon cancer samples in TCGA database were obtained by ESTIMATE algorithm. Then, we analyzed the association of Immune, Stromal, and Estimate scores with tumor prognosis and clinicopathological features. By comparing the gene expression profiles between tumor and normal samples, the high and low immune score groups, 117 intersecting differentially expressed genes (DEGs) were obtained. The function, molecular pathway, and prognostic value of these 117 DEGs pointed toward the importance of deoxyribonuclease 1-like 3 (DNASE1L3). Validation results from multiple databases showed low expression of DNASE1L3 in colon cancer. A single GSEA and correlation analysis of immune cells indicated that DNASE1L3 was closely related to immunity. The low expression of DNASE1L3 in colon cancer samples was measured with qRT-PCR. The scratch and cell proliferation experiments suggested that DNASE1L3 may affect cell migration. Therefore, we concluded that DNASE1L3 might be a biomarker associated with prognosis and immune infiltration in colon cancer.

Comprehensive analyses of competing endogenous RNA networks reveal potential biomarkers for predicting hepatocellular carcinoma recurrence

Background

Hepatocellular carcinoma (HCC) is one of the most common and deadly malignant tumors, with a high rate of recurrence worldwide. This study aimed to investigate the mechanism underlying the progression of HCC and to identify recurrence-related biomarkers.

Methods

We first analyzed 132 HCC patients with paired tumor and adjacent normal tissue samples from the Gene Expression Omnibus (GEO) database to identify differentially expressed genes (DEGs). The expression profiles and clinical information of 372 HCC patients from The Cancer Genome Atlas (TCGA) database were next analyzed to further validate the DEGs, construct competing endogenous RNA (ceRNA) networks and discover the prognostic genes associated with recurrence. Finally, several recurrence-related genes were evaluated in two external cohorts, consisting of fifty-two and forty-nine HCC patients, respectively.

Results

With the comprehensive strategies of data mining, two potential interactive ceRNA networks were constructed based on the competitive relationships of the ceRNA hypothesis. The ‘upregulated’ ceRNA network consists of 6 upregulated lncRNAs, 3 downregulated miRNAs and 5 upregulated mRNAs, and the ‘downregulated’ network includes 4 downregulated lncRNAs, 12 upregulated miRNAs and 67 downregulated mRNAs. Survival analysis of the genes in the ceRNA networks demonstrated that 20 mRNAs were significantly associated with recurrence-free survival (RFS). Based on the prognostic mRNAs, a four-gene signature (ADH4, DNASE1L3, HGFAC and MELK) was established with the least absolute shrinkage and selection operator (LASSO) algorithm to predict the RFS of HCC patients, the performance of which was evaluated by receiver operating characteristic curves. The signature was also validated in two external cohort and displayed effective discrimination and prediction for the RFS of HCC patients.

Conclusions

In conclusion, the present study elucidated the underlying mechanisms of tumorigenesis and progression, provided two visualized ceRNA networks and successfully identified several potential biomarkers for HCC recurrence prediction and targeted therapies.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12885-021-08173-0.

The Role of Nucleases and Nucleic Acid Editing Enzymes in the Regulation of Self-Nucleic Acid Sensing

Detection of microbial nucleic acids by the innate immune system is mediated by numerous intracellular nucleic acids sensors. Upon the detection of nucleic acids these sensors induce the production of inflammatory cytokines, and thus play a crucial role in the activation of anti-microbial immunity. In addition to microbial genetic material, nucleic acid sensors can also recognize self-nucleic acids exposed extracellularly during turn-over of cells, inefficient efferocytosis, or intracellularly upon mislocalization. Safeguard mechanisms have evolved to dispose of such self-nucleic acids to impede the development of autoinflammatory and autoimmune responses. These safeguard mechanisms involve nucleases that are either specific to DNA (DNases) or RNA (RNases) as well as nucleic acid editing enzymes, whose biochemical properties, expression profiles, functions and mechanisms of action will be detailed in this review. Fully elucidating the role of these enzymes in degrading and/or processing of self-nucleic acids to thwart their immunostimulatory potential is of utmost importance to develop novel therapeutic strategies for patients affected by inflammatory and autoimmune diseases.