Prognostic value and immune relevancy of a combined autophagy-, apoptosis- and necrosis-related gene signature in glioblastoma.

BACKGROUND: Glioblastoma (GBM) is considered the most malignant and devastating intracranial tumor without effective treatment. Autophagy, apoptosis, and necrosis, three classically known cell death pathways, can provide novel clinical and immunological insights, which may assist in designing personalized therapeutics. In this study, we developed and validated an effective signature based on autophagy-, apoptosis- and necrosis-related genes for prognostic implications in GBM patients. METHODS: Variations in the expression of genes involved in autophagy, apoptosis and necrosis were explored in 518 GBM patients from The Cancer Genome Atlas (TCGA) database. Univariate Cox analysis, least absolute shrinkage and selection operator (LASSO) analysis, and multivariate Cox analysis were performed to construct a combined prognostic signature. Kaplan-Meier survival, receiver-operating characteristic (ROC) curves and Cox regression analyses based on overall survival (OS) and progression-free survival (PFS) were conducted to estimate the independent prognostic performance of the gene signature. The Chinese Glioma Genome Atlas (CGGA) dataset was used for external validation. Finally, we investigated the differences in the immune microenvironment between different prognostic groups and predicted potential compounds targeting each group. RESULTS: A 16-gene cell death index (CDI) was established. Patients were clustered into either the high risk or the low risk groups according to the CDI score, and those in the low risk group presented significantly longer OS and PFS than the high CDI group. ROC curves demonstrated outstanding performance of the gene signature in both the training and validation groups. Furthermore, immune cell analysis identified higher infiltration of neutrophils, macrophages, Treg, T helper cells, and aDCs, and lower infiltration of B cells in the high CDI group. Interestingly, this group also showed lower expression levels of immune checkpoint molecules PDCD1 and CD200, and higher expression levels of PDCD1LG2, CD86, CD48 and IDO1. CONCLUSION: Our study proposes that the CDI signature can be utilized as a prognostic predictor and may guide patients' selection for preferential use of immunotherapy in GBM.

The impact of particulate matter 2.5 on the risk of hepatocellular carcinoma: a meta-analysis.

OBJECTIVE: The convoluted element of PM2.5 may cause various biological reactions. Nowadays, few studies have indicated the long-term health effects of PM2.5 on HCC. Therefore, this meta-analysis first aims to obtain more precise estimates of the effects of PM2.5 exposure on HCC to assess the strength of the evidence. METHODS: A combination of computer and manual retrieval was used to search in Medline through PubMed, EMBASE and Web of Science. Review Manager 5.3 software was used to examine the heterogeneity among the studies. RESULTS: Finally, 8 qualified articles meet the inclusion criteria. The results were I2 = 0%, P > 0.1 indicating that there was no heterogeneity. The results showed that the concentration of PM2.5 increased by 10 µg/m3 was significantly correlated with liver cancer, and HR was 1.22 (95% CI 1.14-1.30, P < 0.05), indicating that maternal exposure to PM2.5 was positively correlated with liver cancer. CONCLUSIONS: Our meta-analysis showed that the patients with HCC significance related to PM2.5 exposure. However, more studies investigating the combined effects of different air pollutants on HCC incidence are warranted to provide more comprehensive evidence for assessing the different levels impacts of PM2.5 exposure on HCC incidence.

miRNA biomarkers for predicting overall survival outcomes for head and neck squamous cell carcinoma.

Head and neck squamous cell carcinoma (HNSCC) is a malignant tumor of the upper aerodigestive tract. The loss and gain of miRNA function promote cancer development through various mechanisms. RNA sequencing (RNA-seq) and miRNAs sequencing data from the Cancer Genome Atlas (TCGA) was used to show the dysfunctional miRNAs microenvironment and to provide useful biomarkers for miRNAs therapy. Seven miRNAs were found to be independent prognostic factors of HNSCC patients in the training cohort. A total of 60 target genes for these miRNAs were predicted. Nine target genes (CDCA4, CXCL14, FLNC, KLF7, NBEAL2, P4HA1, PFKM, PFN2 and SEPPINE1) were correlated with patient's overall survival (OS) outcomes. We identified novel miRNAs markers for the prognosis of head and neck squamous cell carcinoma.

DNA Methylation Based Molecular Subtypes Predict Prognosis in Breast Cancer Patients.

BACKGROUND: Epigenetic changes are tightly linked to tumorigenesis development and malignant transformation' However, DNA methylation occurs earlier and is constant during tumorigenesis. It plays an important role in controlling gene expression in cancer cells. METHODS: In this study, we determining the prognostic value of molecular subtypes based on DNA methylation status in breast cancer samples obtained from The Cancer Genome Atlas database (TCGA). RESULTS: Seven clusters and 204 corresponding promoter genes were identified based on consensus clustering using 166 CpG sites that significantly influenced survival outcomes. The overall survival (OS) analysis showed a significant prognostic difference among the 7 groups (p<0.05). Finally, a prognostic model was used to estimate the results of patients on the testing set based on the classification findings of a training dataset DNA methylation subgroups. CONCLUSIONS: The model was found to be important in the identification of novel biomarkers and could be of help to patients with different breast cancer subtypes when predicting prognosis, clinical diagnosis and management.

Integrated analysis of the functions and prognostic values of RNA binding proteins in hepatocellular carcinoma.

BACKGROUND: Hepatocellular carcinoma (HCC), one of the most common malignant tumors worldwide, ranks as the fifth most common cancer and has been the second most frequent cause of cancer-related death. RNA binding proteins (RBPs) are proteins that interact with different classes of RNA and are commonly detected in cells. METHODS: We used RNA sequencing data from TCGA to display dysfunctional RBPs microenvironments and provide potential useful biomarkers for HCC diagnosis and prognosis. RESULTS: 330 differently expressed RBPs (208 upregulated and 122 downregulated) were identified. KEGG were mainly enriched in RNA degradation, Influenza A, Hepatitis C, RIG-I-like receptor signaling pathway, Herpes simplex virus 1 infection and RNA transport. CBioPortal results demonstrated that these genes were altered in 50 samples out of 357 HCC patients (14%) and the amplification of BRCA1 was the largest frequent copy-number alteration. CONCLUSION: Based on the online database, we identified novel RBPs markers for the prognosis of hepatocellular carcinoma.

Effect of continuous positive airway pressure on gastroesophageal reflux in patients with obstructive sleep apnea: a meta-analysis.

PURPOSE: Gastroesophageal reflux disease (GERD) often occurs in patients with obstructive sleep apnea (OSA). Although continuous positive airway pressure (CPAP) is considered to be the preferred treatment for OSA, the effect of CPAP therapy on reflux events remains controversial. In this study, we utilized meta-analysis to investigate whether or not CPAP treatment reduces the incidence of reflux. METHODS: Two independent reviewers obtained the data sources from the database of PubMed, Elsevier, Cochrane library, and CNKI using search terms, and then filtered the target articles based on the inclusion and exclusion criteria. RevMan (version 5.3) and STATA (version 12.0) were used for data synthesis. The effect of CPAP treatment on GERD was studied by calculating the weighted mean difference (WMD) and standard deviation (SD) before and after CPAP treatment. RESULTS: Ten studies involving a total of 272 participants were included in this study. The results showed that the total of WMD before and after CPAP was - 17.68 (95% CI - 30.67 to - 4.69) for percentage time pH < 4, - 24.66 (95% CI - 36.15 to - 13.18) for the longest reflux duration, - 27.53 (95% CI - 49.53 to - 5.52) for number of reflux events, - 49.76 (95% CI - 60.18 to - 39.35) for DeMeester score, - 1.85 (95% CI - 3.00 to - 0.71) for reflux diseases questionnaire (RDQ) score, and - 8.95 (95% CI - 16.00 to - 1.89) for reflux symptom index (RSI). The subgroup analysis demonstrated that the improvement of reflux symptoms was more obvious with the extension of treatment time. CONCLUSIONS: This meta-analysis showed that CPAP treatment significantly reduces the incidence of reflux events in patients with OSA.

The role of nitric oxide (NO) levels in patients with obstructive sleep apnea-hypopnea syndrome: a meta-analysis.

PURPOSE: The pathogenesis of cardiovascular disease (CVD) in patients with obstructive sleep apnea (OSA) is unclear. Several studies have suggested that CVD may be caused by oxidative stress from chronic intermittent hypoxia and associated vascular endothelial dysfunction. Oxidative stress in patients with OSA can induce endothelial cell apoptosis, aggravate vascular endothelial damage, and promote the expression of redox-sensitive genes and adhesion molecules. No meta-analysis has explored whether or not OSA is related to nitric oxide (NO). METHOD: To assess the association between serum/plasma NO levels and OSA, we performed a meta-analysis of the literature on the subject to grade the strength of evidence. RESULTS: OSA was significantly related to decreased serum or plasma NO levels (WMD = - 11.66, 95% CI - 17.21 to - 6.11; P < 0.01). Among the studies analyzed, there was high degree of heterogeneity (I2 = 79%, P < 0.01). Sensitivity analysis showed that after omitting any single study or converting a random effects model (REM) to a fixed effects model (FEM), the main results still held. CONCLUSIONS: This meta-analysis suggests a strong correlation between OSA and serum or plasma NO levels which may explain the link between intermittent hypoxia of OSA and risk of CVD. The strength of this finding may spur further basic and clinical research into vascular endothelial dysfunction in patients with OSA.

Association between elevated brain natriuretic peptide levels and weaning failure: A systematic review and meta-analysis.

OBJECTIVE: Cardiovascular dysfunction has been reported as an important mechanism of weaning failure, and recent data suggest that elevated brain natriuretic peptide (BNP) levels is associated with an increased risk of weaning failure. Therefore, we performed this meta-analysis to evaluate the correlation between elevated BNP levels and weaning failure in critically ill patients subject to mechanical ventilation. METHODS: A systematic search in Cochrane Library, Embase, PubMed and Web of Science was performed up to September 25, 2019. Standard mean differences (SMD) and corresponding 95% confidence intervals (CIs) of the BNP levels were calculated for each study. RESULTS: Nine studies with a total number of 589 were included in the final meta-analysis. The results showed that elevated BNP levels were significantly associated with the risk of weaning failure (SMD: 0.76, 95% CI: 0.47 to 1.05, P < .00001). The finding was consistent with the BNP measured before (SMD: 0.68, 95% CI: 0.26 to 1.11, P = .002) or at the end of spontaneous breathing trial (SBT) (SMD: 0.85, 95% CI: 0.52 to 1.18, P < .00001). CONCLUSIONS: This meta-analysis showed that increased plasma BNP concentration was associated with weaning failure in ICU patients.

High CENPM mRNA expression and its prognostic significance in hepatocellular carcinoma: a study based on data mining.

BACKGROUND: Hepatocellular carcinoma (HCC) is a high mortality disease, the fifth most general cancer worldwide, and the second leading to cancer-related deaths, with more than 500,000 new patients diagnosed each year. First, the high expression of centromere M (CENPM) in mammary gland tissue of b-catenin transformed mice was identified. MATERIALS AND METHODS: In our study, we evaluated the expression of CENPM in hepatocellular carcinoma based on data obtained from an online database. Multivariate analysis showed that the expression of CENPM and M classification was an independent prognostic factor for patients with hepatocellular carcinoma. RESULTS: Survival analysis showed that patients with high CENPM had a worse prognosis than patients with low CENPM (P < 0.01). A multivariate Cox regression hazard model showed that B cells, CD8+ T cells, macrophages, and dendritic cells infiltrated by immune cells were statistically significant in liver cancer (P < 0.05). Using the network, the 50 most frequently changed neighbor genes of CENPM were shown, and the most common change was RAD21 (18.3%). CONCLUSION: Our study found that the expression of CENPM was significantly increased in patients with hepatocellular carcinoma, and it was related to a variety of clinical characteristics, its correlation with the level of immune infiltration and poor prognosis, so CENPM can be used as a useful prognosis for patients' markers and HCC.

Identification of a protein signature for predicting overall survival of hepatocellular carcinoma: a study based on data mining.

BACKGROUND: Hepatocellular carcinoma (HCC), is the fifth most common cancer in the world and the second most common cause of cancer-related deaths. Over 500,000 new HCC cases are diagnosed each year. Combining advanced genomic analysis with proteomic characterization not only has great potential in the discovery of useful biomarkers but also drives the development of new diagnostic methods. METHODS: This study obtained proteomic data from Clinical Proteomic Tumor Analysis Consortium (CPTAC) and validated in The Cancer Proteome Atlas (TCPA) and TCGA dataset to identify HCC biomarkers and the dysfunctional of proteogenomics. RESULTS: The CPTAC database contained data for 159 patients diagnosed with Hepatitis-B related HCC and 422 differentially expressed proteins (112 upregulated and 310 downregulated proteins). Restricting our analysis to the intersection in survival-related proteins between CPTAC and TCPA database revealed four coverage survival-related proteins including PCNA, MSH6, CDK1, and ASNS. CONCLUSION: This study established a novel protein signature for HCC prognosis prediction using data retrieved from online databases. However, the signatures need to be verified using independent cohorts and functional experiments.

A Metabolic Gene Signature to Predict Overall Survival in Head and Neck Squamous Cell Carcinoma.

BACKGROUND: Head and neck squamous cell carcinoma (HNSCC) is a common malignancy that emanates from the lips, mouth, paranasal sinuses, oropharynx, larynx, nasopharynx, and from other pharyngeal cancers. The availability of high-throughput expression data has made it possible to use global gene expression data to analyze the relationship between metabolic-related gene expression and clinical outcomes in HNSCC patients. METHOD: In this study, we used RNA sequencing (RNA-seq) data from the cancer genome atlas (TCGA), with validation in the GEO dataset to profile the metabolic microenvironment and define potential biomarkers for metabolic therapy. RESULTS: We extracted data for 529 patients and 327 metabolic genes (198 upregulated and 129 downregulated genes) in the TCGA database. Carbonic anhydrase 9 (CA9) and CA6 had the largest logFCs in the upregulated and downregulated genes, respectively. Our Cox regression model data showed 51 prognostic-related genes with lysocardiolipin acyltransferase 1 (LCLAT1) and choline dehydrogenase (CHDH) being associated with the highest risk (HR = 1.144, 95% CI = 1.044 ~ 1.251) and the lowest risk (HR = 0.580, 95% CI = 0.400 ~ 0.839) in HNSCC, respectively. We next used the ROC curve to evaluate whether the differentially expressed metabolic-related genes could serve as early predictors of HNSCC. The findings showed an AUC of 0.745 and 0.618 in the TCGA and GEO analysis, respectively. Besides, the ability for the genes to predict clinicopathological HNSCC status was analyzed and the data showed that the AUC for age, gender, grade, stage, T, M, and N was 0.520, 0.495, 0.568, 0.606, 0.577, 0.476, and 0.673, respectively, in the TCGA dataset. On the other hand, the AUC for age, gender, stage, T, M, N, smoking, and HPV16-pos was 0.599, 0.531, 0.622, 0.606, 0.616, 0.550, 0.614, 0.519, and 0.397, respectively, in the GEO dataset. CONCLUSION: Taken together, our study unearths a novel metabolic gene signature for the prediction of HNSCC prognosis based on the TCGA dataset. Our signature might point out the metabolic microenvironment disorders and provides potential treatment targets and prognostic biomarkers.

The relationship between obstructive sleep apnea hypopnea syndrome and gastroesophageal reflux disease: a meta-analysis.

BACKGROUND: Obstructive sleep apnea hypopnea syndrome (OSAHS) means apnea and hypopnea caused by partial or complete obstruction of upper airway collapse during sleep. Gastroesophageal reflux disease (GERD) is believed to be associated with various manifestations in the otorhinolaryngology and has been found to be an additional risk factor for OSAHS. AIM: A meta-analysis was performed to identify the association between obstructive sleep apnea hypopnea syndrome and gastroesophageal reflux disease. METHODS: To identify eligible original articles, we searched a series of computerized databases, including Medline via PubMed, EMBASE, Web of Science, and CNKI with a systematic searching strategy. The characteristics of each article and pooled odds ratios (ORs) with corresponding confidence intervals (CIs) were calculated and subgroup analysis was performed to analyze the source of heterogeneity. RESULTS: A total of 2699 patients from seven articles were included in the meta-analysis. We identified a significant relationship between obstructive sleep apnea syndrome and gastroesophageal reflux disease, with a pooled OR of 1.75 (95% CI 1.18-2.59, P < 0.05). The pooled data was calculated under the random-effects model as a significant moderate heterogeneity was found among the meta-analysis. CONCLUSIONS: The meta-analysis showed that there was a significant correlation between obstructive sleep apnea hypopnea syndrome and gastroesophageal reflux disease.

Identification of a Cancer Stem Cells Signature of Head and Neck Squamous Cell Carcinoma.

Background: Head and neck squamous cell carcinoma (HNSCC) ranks as the sixth most widespread and deadly cancer. In recent times, it has been determined that undifferentiated cell populations with stem cell-like properties in HNSCC are major factors influencing recurrence and progression. Method: In this study, we determine key genes related to stemness by merging WGCNA with HNSCC mRNAsi based on the online database. Results: We first download the mRNA expression-based stemness index (mRNAsi) data and contrast the expression levels of mRNAsi in cancers and control samples; we found significantly elevated mRNAsi expressions in HNSCC tissues (p = 0.002). Moreover, the brown module showed a relatively high negative correlation with mRNAsi (cor = -0.8). Thus, we selected the brown module as the interesting module and used it for following analysis. We screened 20 key genes (PDGFRB, PLPP4, CALU, ADAMTS14, COL5A3, KCNE4, LOXL1, CLEC11A, PODN,BGN, AEBP1, COL1A2, LAMA4, LOXL2, LRRC15, THY1, SPON2, COL1A1, NID2, and AC134312.5) including and as to decide the neighbor genes biological interaction network of these 20 stemness-related genes in HNSCC. The top 10 frequent alterations were PIK3CA, FGF3, FGF19, FGF4, DVL3, P3H2, GNB4, COL22A1, COL14A1, and PLOD2. Conclusion: This study showed the critical role of stemness-related genes in HNSCC. However, more related studies are needed to confirm these results.

Bioinformatics Study Revealed Significance of Exosome Transcriptome in Hepatocellular Carcinoma Diagnosis.

Background: Hepatocellular carcinoma (HCC) is one of the fifty most common cancers globally, having a high mortality rate being the second most common cause of cancer-related deaths. However, little attention has been paid to the involvement of exosomes and ceRNA in HCC. Method: The study aimed to explore exosome data from exoRBase database and a free online database to estimate possible binding miRNA from mRNA, lncRNA, and circRNA and discover useful exosome biomarkers for HCC therapy. Results: The results indicated that a total of 159 mRNAs, 60 lncRNAs, and 13 circRNAs were differentially expressed, with HIST2H3C exhibiting the highest log2FC change, CTD-2031P19 exhibiting the most relevant lncRNA, and CTD-2031P19 exhibiting the most relevant lncRNA. MARCH8, SH3PXD2A, has-circ-0014088, hsa-miR-186-5p, and hsa-miR-613 were identified as hub biomarkers used by Cytoscape. According to the KEGG pathway analysis results, the differentially expressed proteins were primarily enriched in the MAPK signaling network, central carbon metabolism in cancer, the glucagon signaling pathway, glutamatergic synapse, and spliceosome. Furthermore, immunohistochemical images from the Human Protein Atlas (HPA) online tool were used to directly evaluate the protein expression of SMARCA5, CDC42, and UBC between normal and cancer tissues, and the results showed that these three gene expressions were significantly higher in tumor tissues. Conclusion: This study discovered atypical signature exosomes for HCC prognostic prediction based on an online database. The signals could mimic exosome microenvironmental disorders providing potential biomarkers for exosome treatment.

Pyroptosis-Related Signature and Tumor Microenvironment Infiltration Characterization in Head and Neck Squamous Cell Carcinoma.

Background: Head and neck squamous cell carcinoma (HNSCC) is the sixth most widespread and deadly cancer. Until now, very few studies have systematically evaluated the role of pyroptosis-related genes (PRGs) and lncRNAs in HNSCC patients. Methods: We integrated the genomic data to comprehensively assess the role of pyroptosis with the tumor microenvironment cell-infiltrating characteristics in HNSCC. In addition, we also constructed a set of the scoring system to calculate the pyroptosis dysfunction in each patient. Results: The analysis of the CNV alteration frequency displayed that CNV changes were common in 33 PRGs, and the frequency of copy number gain and loss was similar. CASP8 demonstrated the highest mutation frequency. Considering the individual heterogeneity, a scoring system to quantify the pyroptosis pattern in each patient was constructed based on these phenotypic-related genes, which we named as the PyroptosisScore. The results indicated that the low PyroptosisScore group experienced increased extensive TMB than the high group, with the most significant mutated genes being TP53 and TTN. Finally, we tried to find some useful pyroptosis-related lncRNAs, and 14 differentially expressed lncRNAs were selected as independent prognosis factors of HNSCC patients based on the multivariate Cox analysis. Conclusion: This work suggests the pyroptosis features and the potential mechanisms of the tumor microenvironment. The exploration may assist in identifying novel biomarkers and help patients predict prognosis, clinical diagnosis, and management.

Diabetes increases the mortality of patients with COVID-19: a meta-analysis.

AIMS: Nowadays, the ongoing pandemic of COVID-19 caused by the novel coronavirus Syndrome-Coronavirus-2 (SARS-CoV-2) is an emerging, rapidly evolving situation. Complications such as hypertension, diabetes, COPD, cardiovascular disease, and cerebrovascular disease are major risk factors for patients with COVID-19. METHODS: No meta-analysis has explored if or not diabetes related to mortality of patients with COVID-19. Therefore, this meta-analysis first aims to explore the possible clinical mortality between diabetes and COVID-19, analyze if diabetes patients infected with SARS-CoV-2 are exposed to the worst clinical prognostic risk, and to evaluate the reliability of the evidence. RESULTS: Our results showed a close relationship between diabetes and mortality of COVID-19, with a pooled OR of 1.75 (95% CI 1.31-2.36; P = 0.0002). The pooled data were calculated with the fixed effects model (FEM) as no heterogeneity appeared in the studies. Sensitivity analysis showed that after omitting any single study or converting a random effect model to FEM, the main results still held. CONCLUSIONS: Our meta-analysis showed that diabetes increases the mortality of patients with COVID-19. These results indicated the disturbance of blood glucose in the COVID-19 patients. More importantly, this meta-analysis grades the reliability of evidence for further basic and clinical research into the diabetes dysfunction in COVID-19 patients.

Alternative splicing events implicated in carcinogenesis and prognosis of thyroid gland cancer.

Alternative splicing (AS), a critical post-transcriptional regulatory mechanism, expands gene expression patterns, thereby leading to increased protein diversity. Indeed, more than 95% of human genes undergo alternative splicing events (ASEs). In this study, we drew an all-around AS profile of thyroid cancer cells based on RNA-seq data. In total, there were 45,150 AS in 10,446 thyroid cancer cell genes derived from 506 patients, suggesting that ASEs is a common process in TC. Moreover, 1819 AS signatures were found to be significantly associated with the overall survival (OS) of TC patients. Kaplan-Meier survival analyses suggested that seven types of ASEs were associated with poor prognosis of TC (P < 0.05). Among them, exon skipping (ES) was the most common, with alternate promoter (AP) and alternate terminator (AT) coming second and third, respectively. Our results indicated that acceptor sites (AA) (AUC: 0.937), alternate donor sites (AD) (AUC: 0.965), AT (AUC: 0.964), ES (AUC: 0.999), mutually exclusive exons (ME) (AUC: 0.999), and retained intron (RI) (AUC: 0.837) exhibited an AUC greater than 0.6. In addition, age and risk score (All) were risk factors for TC patients. We also evaluated whether TC-ASEs are regulated by various splicing factors (SFs). We found that the expression of 90 SFs was associated with 469 ASEs and OS of TC patients. Our findings provide an insight into the role of spliceosomes in TC, which may offer novel perspectives in tumor research.

Development and Validation of a Pyroptosis-Related Long Non-coding RNA Signature for Hepatocellular Carcinoma.

Background: Hepatocellular carcinoma (HCC) is a highly aggressive malignant disease, and numerous studies have demonstrated that an inflammatory environment can induce normal cells to transform into cancerous. Methods: We integrated genomic data to comprehensively assess the association between pyroptosis and tumor microenvironment (TME) cell-infiltrating characteristics in HCC, as well as the potential molecular function and clinical significance of lncRNA. Results: The analysis of CNV alteration frequency displayed that CNV changes were common in 33 PRGs, and most were focused on copy number amplification. As a result of lasso regression analysis, nine differentially expressed lncRNAs (AL031985.3, NRAV, OSMR-AS1, AC073611.1, MKLN1-AS, AL137186.2, AL049840.4, MIR4435-2HG, and AL118511.1) were selected as independent prognosis factors of HCC patients. Patients at high risk have poorer survival than those in the low-risk group in training and testing cohorts. A low-risk score was significantly associated with an IC50 of chemotherapeutics such as bortezomib (p < 0.001), but a high-risk score was significantly linked to docetaxel (p < 0.001), implying that signature served as a prospective predictor for chemosensitivity. Conclusion: This work suggests pyroptosis-related lncRNAs features and their potential mechanisms on tumor microenvironment. The exploration may assist in identifying novel biomarkers and assist patients in predicting their prognosis, clinical diagnosis, and management.

Epigenetic and Immune-Cell Infiltration Changes in the Tumor Microenvironment in Hepatocellular Carcinoma.

Background: Epigenetics regulate gene expression without altering the DNA sequence. Epigenetics targeted chemotherapeutic approach can be used to overcome treatment resistance and low response rate in HCC. However, a comprehensive review of genomic data was carried out to determine the role of epigenesis in the tumor microenvironment (TME), immune cell-infiltration characteristics in HCC is still insufficient. Methods: The association between epigenetic-related genes (ERGs), inflammatory response-related genes (IRRGs) and CRISPR genes was determined by merging genomic and CRISPR data. Further, characteristics of immune-cell infiltration in the tumor microenvironment was evaluated. Results: Nine differentially expressed genes (ANP32B, ASF1A, BCORL1, BMI1, BUB1, CBX2, CBX3, CDK1, and CDK5) were shown to be independent prognostic factors based on lasso regression in the TCGA-LIHC and ICGC databases. In addition, the results showed significant differences in expression of PDCD-1 (PD-1) and CTLA4 between the high- and low-epigenetic score groups. The CTRP and PRISM-derived drug response data yielded four CTRP-derived compounds (SB-743921, GSK461364, gemcitabine, and paclitaxel) and two PRISM-derived compounds (dolastatin-10 and LY2606368). Patients with high ERGs benefited more from immune checkpoint inhibitor (ICI) therapy than patients with low ERGs. In addition, the high ERGs subgroup had a higher T cell exclusion score, while the low ERGs subgroup had a higher T cell dysfunction. However, there was no difference in microsatellite instability (MSI) score among the two subgroups. Further, genome-wide CRISPR-based loss-of function screening derived from DepMap was conducted to determine key genes leading to HCC development and progression. In total, 640 genes were identified to be essential for survival in HCC cell lines. The protein-protein interaction (PPI) network demonstrated that IRRGs PSEN1 was linked to most ERGs and CRISPR genes such as CDK1, TOP2A, CBX2 and CBX3. Conclusion: Epigenetic alterations of cancer-related genes in the tumor microenvironment play a major role in carcinogenesis. This study showed that epigenetic-related novel biomarkers could be useful in predicting prognosis, clinical diagnosis, and management in HCC.

Single sample scoring of hepatocellular carcinoma: A study based on data mining.

Hepatocellular carcinoma (HCC) is a high mortality malignancy and the second leading cause of cancer-related deaths. Because the immune system plays a dual role by assisting the host barrier and tumor progression, there are complex interactions with considerable prognostic significance. Herein, we performed single-sample gene set enrichment (ssGSEA) to explore the tumor microenvironment (TME) and quantify the tumor-infiltrating immune cell (TIIC) subgroups of immune responses based on the HCC cohort of The Cancer Genome Atlas (TCGA) database. We evaluate molecular subpopulations, survival, function, and expression differential associations, as well as reveal potential targets, and biomarkers for immunotherapy. We combined the TME score and the 29 immune cell types in the low, medium, and high immunity groups. The stromal score, immune score, and ESTIMATE score were positively correlated with immune activity but negatively correlated with the tumor purity. There were 23 human leukocyte antigen (HLA)-related genes that were significantly different. However, KIAA1429 was not significant among the different immunity groups. Besides, programmed death-ligand 1 (PD-L1) and cytotoxic T-lymphocyte-associated antigen 4 (CTLA-4) expression increased with the increase of immune activity. This may provide valuable information for HCC immunotherapy. We also found that there was no significant difference in naïve B cells, macrophages M1, activated mast cells, resting natural killer (NK) cells, and T cells gamma delta among the different immunity groups. The Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis revealed that the differential proteins were mainly enriched in alpha-linolenic acid (ALA) metabolism, cytokine-cytokine receptor interaction, glycosaminoglycan biosynthesis-heparan sulfate/heparin, glycosphingolipid biosynthesis-ganglio series and proteasome. Our findings provide a deeper understanding of the immune scene, uncovering remarkable immune infiltration patterns of various subtypes of HCC using ssGSEA. This study advances the understanding of immune response and provides a basis for research to enhance immunotherapy.