DNASE1L3 as a Prognostic Biomarker Associated with Immune Cell Infiltration in Cancer

Fourteen years of cellular deconvolution: methodology, applications, technical evaluation and outstanding challenges

Single-cell RNA sequencing (scRNA-Seq) is a recent technology that allows for the measurement of the expression of all genes in each individual cell contained in a sample. Information at the single-cell level has been shown to be extremely useful in many areas. However, performing single-cell experiments is expensive. Although cellular deconvolution cannot provide the same comprehensive information as single-cell experiments, it can extract cell-type information from bulk RNA data, and therefore it allows researchers to conduct studies at cell-type resolution from existing bulk datasets. For these reasons, a great effort has been made to develop such methods for cellular deconvolution. The large number of methods available, the requirement of coding skills, inadequate documentation, and lack of performance assessment all make it extremely difficult for life scientists to choose a suitable method for their experiment. This paper aims to fill this gap by providing a comprehensive review of 53 deconvolution methods regarding their methodology, applications, performance, and outstanding challenges. More importantly, the article presents a benchmarking of all these 53 methods using 283 cell types from 30 tissues of 63 individuals. We also provide an R package named DeconBenchmark that allows readers to execute and benchmark the reviewed methods (https://github.com/tinnlab/DeconBenchmark).

Nine-Gene Prognostic Signature Related to Gut Microflora for Predicting the Survival in Gastric Cancer Patients

BACKGROUND/AIMS

The purpose of this study is to screen the feature genes related to gut microflora and explore the role of the genes in predicting the prognosis of patients with gastric cancer.

MATERIALS AND METHODS

We downloaded the gene profile of gastric cancer from the University of California Santa Cruz, the gut microflora related to gastric cancer from The Cancer Microbiome Atlas. The GSE62254 dataset was downloaded from National Center for Biotechnology Information Gene Expression Omnibus as a validation dataset. A correlation network between differentially expressed genes and gut microflora was constructed using Cytoscape. The optimized prognostic differentially expressed genes were identified through least absolute shrinkage and selection operator (LASSO) algorithm and univariate Cox regression analysis. The risk score model was established and then measured via Kaplan-Meier and area under the curve. Finally, the nomogram model was constructed according to the independent clinical factors, which was evaluated using C-index.

RESULTS

A total of 754 differentially expressed genes and 8 gut microflora were screened, based on which we successfully constructed the correlation network. We obtained 9 optimized prognostic differentially expressed genes, including HSD17B3, GNG7, CHAD, ARHGAP8, NOX1, YY2, GOLGA8A, DNASE1L3, and ABCA8. Moreover, Kaplan-Meier curves indicated the risk score model correctly predicted the prognosis of gastric cancer in both University of California Santa Cruz and GSE62254 dataset (area under the curve >0.8; area under the curve >0.7). Finally, we constructed the nomogram, in which the C index of 1, 3, and 5 years was 0.824, 0.772, and 0.735 representing that the nomogram was consistent with the actual situation.

CONCLUSIONS

These results indicate the 9 differentially expressed genes related to gut microflora might predict the survival time of patients with gastric cancer. Both risk signature and nomogram could effectively predict the prognosis for patients with gastric cancer.

Distinct Hodgkin lymphoma subtypes defined by noninvasive genomic profiling

The scarcity of malignant Hodgkin and Reed-Sternberg cells hampers tissue-based comprehensive genomic profiling of classic Hodgkin lymphoma (cHL). By contrast, liquid biopsies show promise for molecular profiling of cHL due to relatively high circulating tumour DNA (ctDNA) levels1-4. Here we show that the plasma representation of mutations exceeds the bulk tumour representation in most cases, making cHL particularly amenable to noninvasive profiling. Leveraging single-cell transcriptional profiles of cHL tumours, we demonstrate Hodgkin and Reed-Sternberg ctDNA shedding to be shaped by DNASE1L3, whose increased tumour microenvironment-derived expression drives high ctDNA concentrations. Using this insight, we comprehensively profile 366 patients, revealing two distinct cHL genomic subtypes with characteristic clinical and prognostic correlates, as well as distinct transcriptional and immunological profiles. Furthermore, we identify a novel class of truncating IL4R mutations that are dependent on IL-13 signalling and therapeutically targetable with IL-4Rα-blocking antibodies. Finally, using PhasED-seq5, we demonstrate the clinical value of pretreatment and on-treatment ctDNA levels for longitudinally refining cHL risk prediction and for detection of radiographically occult minimal residual disease. Collectively, these results support the utility of noninvasive strategies for genotyping and dynamic monitoring of cHL, as well as capturing molecularly distinct subtypes with diagnostic, prognostic and therapeutic potential.

PRAME Expression: A Target for Cancer Immunotherapy and a Prognostic Factor in Uveal Melanoma

Purpose

Uveal melanoma (UM) is a rare disease with a high mortality, and new therapeutic options are being investigated. Preferentially Expressed Antigen in Melanoma (PRAME) is a cancer testis antigen, expressed in the testis, but also in cancers, including uveal melanoma. PRAME is considered a target for immune therapy in several cancers, and PRAME-specific T cell clones have been shown to kill UM cells.

Methods

We studied the literature on PRAME expression in hematological and solid malignancies, including UM, and its role as a target for immunotherapy. The distribution of tumor features was compared between PRAME-high and PRAME-low UM in a 64-patient cohort from the Leiden University Medical Center (LUMC) and in the Cancer Genome Atlas (TCGA) cohort of 80 cases and differential gene expression analysis was performed in the LUMC cohort.

Results

PRAME is expressed in many malignancies, it is frequently associated with a negative prognosis, and can be the target of T cell receptor (TCR)-transduced T cells, a promising treatment option with high avidity and safety. In UM, PRAME is expressed in 26% to 45% of cases and is correlated with a worse prognosis. In the LUMC and the TCGA cohorts, high PRAME expression was associated with larger diameter, higher Tumor-Node-Metastasis (TNM) stage, more frequent gain of chromosome 8q, and an inflammatory phenotype.

Conclusions

We confirm that PRAME is associated with poor prognosis in UM and has a strong connection with extra copies of 8q. We show that PRAME-specific immunotherapy in an adjuvant setting is promising in treatment of malignancies, including UM.

Circulating cell-free DNA fragmentation is a stepwise and conserved process linked to apoptosis

BACKGROUND

Circulating cell-free DNA (cfDNA) is a pool of short DNA fragments mainly released from apoptotic hematopoietic cells. Nevertheless, the precise physiological process governing the DNA fragmentation and molecular profile of cfDNA remains obscure. To dissect the DNA fragmentation process, we use a human leukemia cell line HL60 undergoing apoptosis to analyze the size distribution of DNA fragments by shallow whole-genome sequencing (sWGS). Meanwhile, we also scrutinize the size profile of plasma cfDNA in 901 healthy human subjects and 38 dogs, as well as 438 patients with six common cancer types by sWGS.

RESULTS

Distinct size distribution profiles were observed in the HL60 cell pellet and supernatant, suggesting fragmentation is a stepwise process. Meanwhile, C-end preference was seen in both intracellular and extracellular cfDNA fragments. Moreover, the cfDNA profiles are characteristic and conserved across mammals. Compared with healthy subjects, distinct cfDNA profiles with a higher proportion of short fragments and lower C-end preference were found in cancer patients.

CONCLUSIONS

Our study provides new insight into fragmentomics of circulating cfDNA processing, which will be useful for early diagnosis of cancer and surveillance during cancer progression.

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.

DNASE1L3 enhances antitumor immunity and suppresses tumor progression in colon cancer

DNASE1L3, an enzyme highly expressed in DCs, is functionally important for regulating autoimmune responses to self-DNA and chromatin. Deficiency of DNASE1L3 leads to development of autoimmune diseases in both humans and mice. However, despite the well-established causal relationship between DNASE1L3 and immunity, little is known about the involvement of DNASE1L3 in regulation of antitumor immunity, the foundation of modern antitumor immunotherapy. In this study, we identify DNASE1L3 as a potentially new regulator of antitumor immunity and a tumor suppressor in colon cancer. In humans, DNASE1L3 is downregulated in tumor-infiltrating DCs, and this downregulation is associated with poor patient prognosis and reduced tumor immune cell infiltration in many cancer types. In mice, Dnase1l3 deficiency in the tumor microenvironment enhances tumor formation and growth in several colon cancer models. Notably, the increased tumor formation and growth in Dnase1l3-deficient mice are associated with impaired antitumor immunity, as evidenced by a substantial reduction of cytotoxic T cells and a unique subset of DCs. Consistently, Dnase1l3-deficient DCs directly modulate cytotoxic T cells in vitro. To our knowledge, our study unveils a previously unknown link between DNASE1L3 and antitumor immunity and further suggests that restoration of DNASE1L3 activity may represent a potential therapeutic approach for anticancer therapy.

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.

Pan‑cancer analysis of the deoxyribonuclease gene family

Deoxyribonuclease (DNase) is an enzyme that catalyzes the cleavage of phosphodiester bonds in the main chain of DNA to degrade DNA. DNase serves a vital role in several immune-related diseases. The present study linked the expression of DNase with overall survival (OS), performed pan-cancer co-expression analysis, and assessed the association between DNase and immune infiltration subtypes, tumor microenvironment and drug sensitivity through pan-cancer studies. Furthermore, gene expression data and clinical data were downloaded from The Cancer Genome Atlas. Next, through a series of bioinformatics analyses, DNase expression and survival, immune subtypes, tumor microenvironment and drug sensitivity in 33 tumor types were systematically studied. The expression of the DNase gene family was shown to have an apparent intratumoral heterogeneity. The expression of DNase 2, lysosomal (DNASE2) was the highest in tumors, whereas that of DNASE2 β was the lowest. DNase 1-like 3 (DNASE1L3) was mainly downregulated in tumors, whereas the rest of the DNases were mainly upregulated in tumors. The expression of DNase family members was also found to be associated with the OS rate of patients. DNase family genes may serve an essential role in the tumor microenvironment. DNase family gene expression was related to the content of cytotoxic cells, Immunescore, Stromalscore, Estimatescore and Tumorpurity. The present study also revealed that the DNase genes may be involved in the drug resistance of cancer cells. Finally, the correlation between DNase, and clinical stage and tumor microenvironment in hepatocellular carcinoma (HCC) was studied. In addition, the difference in DNASE1L3 expression between HCC and adjacent normal tissues, and the relationship between DNASE1L3 expression and clinical stage was verified by analyzing three groups in a Gene Expression Omnibus dataset and by performing immunohistochemistry. In conclusion, the present study assessed DNase gene expression, analyzed its relationship with patient OS, performed pan-cancer co-expression analysis, and assessed the association between DNase and immune infiltration subtypes, tumor microenvironment and drug sensitivity. The present study also confirmed the value of further laboratory research on DNases and their prospects in clinical cancer treatment.

DNASE1L3 regulation by transcription factor FOXP2 affects the proliferation, migration, invasion and tube formation of lung adenocarcinoma

Lung adenocarcinoma (LUAD) is prone to bone metastasis, resulting in poor prognosis. The present study aimed to detect the expression of deoxyribonuclease 1-like 3 (DNASE1L3) and forkhead-box P2 (FOXP2) in LUAD cells to investigate the role of DNASE1L3 in the regulation of proliferation, migration, invasion and tube formation of LUAD cells and how FOXP2 affects DNASE1L3 expression. The expression of DNASE1L3 and FOXP2 in LUAD cells was analyzed by reverse transcription-quantitative PCR (RT-qPCR) and western blotting. The transfection efficiency of DNASE1L3 overexpression plasmids, FOXP2 overexpression or interference plasmids into A549 cells was also confirmed by RT-qPCR and western blotting. The viability, proliferation, migration and invasion and tube formation of LUAD cells following transfection was in turn detected by MTT, EdU staining, wound healing, Transwell and tube formation assay. The expression of proteins associated with epithelial-mesenchymal transformation and tube formation was detected by western blotting. Binding between DNASE1L3 and FOXP2 was confirmed by dual-luciferase reporter assay and chromatin immunoprecipitation. Gene Expression Profiling Interactive Analysis database predicted that underexpression of DNASE1L3 in LUAD was associated with poor prognosis. DNASE1L3 expression was decreased in LUAD cells and overexpression of DNASE1L3 inhibited the proliferation, migration, invasion and tube formation of LUAD cells. Transcription factor FOXP2 positively regulated DNASE1L3 transcription in LUAD cells. FOXP2 was also underexpressed in LUAD cells and downregulation of FOXP2 promoted proliferation, migration, invasion and tube formation of LUAD cells, which was reversed by overexpression of DNASE1L3. In conclusion, DNASE1L3 was positively regulated by transcription factor FOXP2 and overexpression inhibited proliferation, migration, invasion and tube formation of LUAD cells.

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.

Construction of a competing endogenous RNA network to analyse glucose-6-phosphate dehydrogenase dysregulation in hepatocellular carcinoma

Hepatocellular carcinoma (HCC) is a common malignant tumour with high rates of morbidity and mortality worldwide. Therefore, it is of great significance to find new molecular markers for HCC diagnosis and treatment. G6PD is known to be dysregulated in a variety of tumours. In addition, the ceRNA network plays a crucial role in the occurrence and development of HCC. However, the mechanism by which the ceRNA network regulates G6PD in HCC remains unclear. We used TCGA-LIHC data to analyse the possibility of using G6PD as an independent prognostic marker. Univariate Cox proportional hazards regression, multivariate Cox proportional hazards regression, and receiver operating characteristic curve analysis were used to analyse the influence of G6PD overexpression on the prognosis of HCC patients. We also analysed the biological function of G6PD, its effect on the immune microenvironment, and drug sensitivity. Finally, we constructed a ceRNA network of lncRNAs/miR-122-5p/G6PD to explore the regulatory mechanism of G6PD. G6PD was highly expressed in HCC, was related to pathological stage and poor prognosis, and could be used as an independent prognostic indicator of HCC. The expression of G6PD was closely related to the immune microenvironment of HCC. In addition, the expression of G6PD in HCC could be regulated by the ceRNA network. Therefore, G6PD can be used as an immunotherapy target to improve the survival and prognosis of HCC patients, and the ceRNA regulatory network of G6PD has potential diagnostic and therapeutic value for HCC.

Comprehensive Analysis of RELL2 as a Potential Biomarker Associated with Tumor Immune Infiltrating Cells in a Pan-Cancer Analysis

Background

Receptor expressed in lymphoid tissues-like 2 (RELL2), which is a member of RELT family, is closely associated with the plasma membrane and acts as a modulator for RELT signaling. Overexpression of RELL2 induces the activation of MAPK14/p38 cascade and apoptosis. However, whether RELL2 contributes to cancers remains unclear. Here, we examined its role in cancer patient prognosis and various tumors.

Methods

We used several bioinformatics methods, specifically gene set enrichment analysis (GSEA), ScanNeo, and ESTIMATE, to analyze the CCLE dataset, GTEx dataset, and TCGA dataset. We investigated the possible association of RELL2 with the microsatellite instability (MSI) of various tumors, tumor mutational burden (TMB), immune checkpoint, immune neoantigens, immune microenvironment, and patient prognosis.

Result

RELL2 is highly expressed in cancer compared with normal tissues. RELL2 expression is linked with worse progression-free interval and overall survival in numerous cancers. In most cancers, high RELL2 expression was related to a poor prognosis. RELL2 expression was significantly associated with the tumor microenvironment, MSI, and TMB. RELL2 expression is strongly associated with phenotypes that are of major clinical significance, particularly those associated with immune neoantigens and the expression profiles of immune checkpoint genes in pan-cancer. RELL2 expression strongly linked with the expressions of methyltransferases and DNA repair genes. It also significantly correlated with multiple signaling pathways through gene set enrichment analysis.

Conclusion

RELL2 may be a prognostic biomarker in pan-cancer and may have an important function in tumorigenesis and progression.

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.

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.