Screening and Identification of Neutrophil Extracellular Trap-related Diagnostic Biomarkers for Pediatric Sepsis by Machine Learning.

Neutrophil extracellular trap (NET) is released by neutrophils to trap invading pathogens and can lead to dysregulation of immune responses and disease pathogenesis. However, systematic evaluation of NET-related genes (NETRGs) for the diagnosis of pediatric sepsis is still lacking. Three datasets were taken from the Gene Expression Omnibus (GEO) database: GSE13904, GSE26378, and GSE26440.

Predictive Value of a Diagnostic Five-Gene Biomarker for Pediatric Sepsis.

Background: Pediatric sepsis has a very high morbidity and mortality rate. The purpose of this study was to evaluate diagnostic biomarkers and immune cell infiltration in pediatric sepsis.

Methods: Three datasets (GSE13904, GSE26378, and GSE26440) were downloaded from the gene expression omnibus (GEO) database.

Increased PAFAH1B3 was associated with poor prognosis and T-cell exhaustion microenvironment in hepatocellular carcinoma.

The link between T-cell exhaustion (TEX) and PAFAH1B3 in hepatocellular carcinoma (HCC) remains unknown, even though both of them are related to overall survival. PAFAH1B3 expression was investigated in TCGA and ICGC data, and 50 paired clinical tissue section samples were used for qRT-PCR and immunohistochemistry (IHC) confirmation. The Immunocell Abundance Identifier (ImmuCellAI) was used to precisely calculate the abundance of TEX, and its accuracy was verified by single-cell RNA-seq and labeling of CD8 + T cells in clinical tissue sections.

Lysosome-Related Diagnostic Biomarkers for Pediatric Sepsis Integrated by Machine Learning.

Background: There is currently no biomarker that can reliably identify sepsis, despite recent scientific advancements. We systematically evaluated the value of lysosomal genes for the diagnosis of pediatric sepsis.

Methods: Three datasets (GSE13904, GSE26378, and GSE26440) were obtained from the gene expression omnibus (GEO) database.

Prognostic clinical phenotypes associated with tumor stemness in the immune microenvironment of T-cell exhaustion for hepatocellular carcinoma.

T-cell exhaustion (TEX) and high heterogeneity of cancer stem cells (CSCs) are associated with progression, metastasis, and treatment resistance in hepatocellular carcinoma (HCC). Here, we aim to characterize TEX-stemness-related genes (TEXSRGs) and screen for HCC patients who are more sensitive to immunotherapy. The immune cell abundance identifier (ImmuCellAI) was utilized to precisely evaluate the abundance of TEX and screen TEX-related genes.

Telomere-related prognostic biomarkers for survival assessments in pancreatic cancer.

Human telomeres are linked to genetic instability and a higher risk of developing cancer. Therefore, to improve the dismal prognosis of pancreatic cancer patients, a thorough investigation of the association between telomere-related genes and pancreatic cancer is required. Combat from the R package "SVA" was performed to correct the batch effects between the TCGA-PAAD and GTEx datasets.

Prognostic Lysosome-Related Biomarkers for Predicting Drug Candidates in Hepatocellular Carcinoma: An Insilco Analysis.

Background: Lysosomes play an important role in enhancing tumorigenesis and chemoresistance in hepatocellular carcinoma (HCC). Therefore, a detailed analysis of the role of lysosome-related genes could improve the poor prognosis of HCC patients.

Methods: Lysosome-associated genes were downloaded from the GO and Genome Enrichment Analysis (GSEA) databases.

Identification and validation of a novel four-gene diagnostic model for neonatal early-onset sepsis with bacterial infection.

Unlabelled: Neonatal early-onset sepsis (EOS) has unfortunately been the third leading cause of neonatal death worldwide. The current study is aimed at discovering reliable biomarkers for the diagnosis of neonatal EOS through transcriptomic analysis of publicly available datasets. Whole blood mRNA expression profiling of neonatal EOS patients in the GSE25504 dataset was downloaded and analyzed.

A novel stemness-hypoxia-related signature for prognostic stratification and immunotherapy response in hepatocellular carcinoma.

Background: The specific differentiation potential, unlimited proliferation, and self-renewal capacity of cancer stem cells (CSCs) are closely related to the occurrence, recurrence, and drug resistance of hepatocellular carcinoma (HCC), as well as hypoxia. Therefore, an in-depth analysis of the relationship between HCC stemness, oxygenation status, and the effectiveness of immunotherapy is necessary to improve the poor prognosis of HCC patients.

Methods: The weighted gene co-expression network analysis (WGCNA) was utilized to find hypoxia-related genes, and the stemness index (mRNAsi) was evaluated using the one-class logistic regression (OCLR) technique.

Regulatory T-cells-related signature for identifying a prognostic subtype of hepatocellular carcinoma with an exhausted tumor microenvironment.

Regulatory T-Cells (Tregs) are important in the progression of hepatocellular cancer (HCC). The goal of this work was to look into Tregs-related genes and develop a Tregs-related prognostic model. We used the weighted gene co-expression network analysis (WGCNA) to look for Tregs-related genes in the TCGA, ICGC, and GSE14520 cohorts and then used the non-negative matrix factorization (NMF) algorithm to find Tregs-related subpopulations.

Endoplasmic Reticulum Stress-Related Signature for Predicting Prognosis and Immune Features in Hepatocellular Carcinoma.

Hepatocellular carcinoma (HCC) with cancer cells under endoplasmic reticulum (ER) stress has a poor prognosis. This study is aimed at discovering credible biomarkers for predicting the prognosis of HCC based on ER stress-related genes (ERSRGs). We constructed a novel four-ERSRG prognostic risk model, including PON1, AGR2, SSR2, and TMCC1, through a series of bioinformatic approaches, which can accurately predict survival outcomes in HCC patients.

Identification of HM13 as a prognostic indicator and a predictive biomarker for immunotherapy in hepatocellular carcinoma.

Background: Histocompatibility minor 13 (HM13) is a signal sequence stubbed intramembrane cleavage catalytic protein that is essential for cell signaling, intracellular communication, and cancer. However, the expression of HM13 and its prognostic value, association with tumor-infiltrating immune cells (TIICs) in the microenvironment, and potential to predict immunotherapeutic response in HCC are unknown.

Methods: The HM13 expression, clinicopathology analysis, and its influence on survival were analyzed in multiple public databases and further verified in collected HCC and normal tissues by qRT-PCR and immunohistochemistry staining assay (IHC).

A novel Cuproptosis-related LncRNA signature to predict prognosis in hepatocellular carcinoma.

Increased intracellular toxicity due to an imbalance in copper homeostasis caused by copper ion accumulation could regulate the rate of cancer cell growth and proliferation. The goal of this study was to create a novel Cuproptosis-related lncRNA signature that may be utilized to predict survival and immunotherapy in HCC patients. Cuproptosis-associated lncRNAs and differentially expressed lncRNAs between HCC tumor tissue and normal tissue were discovered first.

Platelet-Related Molecular Subtype to Predict Prognosis in Hepatocellular Carcinoma.

Purpose: Complex crosstalk between tumor cells and platelets is closely related to the development, relapse, and drug resistance of hepatocellular carcinoma (HCC). Therefore, an intensive analysis of the relationship between platelet-related genes and the effectiveness of immunotherapy is necessary for improving the poor prognosis of HCC patients.

Methods: Genes associated with platelets in the GeneCards database were collected and were used to identify molecular subtypes using a non-negative matrix decomposition algorithm (NMF) and constructed a platelet-related genes-based prognostic stratification model by the LASSO-Cox regression and stepwise Cox regression analysis.

A novel tumor doubling time-related immune gene signature for prognosis prediction in hepatocellular carcinoma.

Background: Hepatocellular carcinoma (HCC) has become a global health issue of wide concern due to its high prevalence and poor therapeutic efficacy. Both tumor doubling time (TDT) and immune status are closely related to the prognosis of HCC patients. However, the association between TDT-related genes (TDTRGs) and immune-related genes (IRGs) and the value of their combination in predicting the prognosis of HCC patients remains unclear.

A Novel Five-Gene Signature for Prognosis Prediction in Hepatocellular Carcinoma.

Hepatocellular carcinoma (HCC) has been a global health issue and attracted wide attention due to its high incidence and poor outcomes. In this study, our purpose was to explore an effective prognostic marker for HCC. Five cohort profile datasets from GEO (GSE25097, GSE36376, GSE62232, GSE76427 and GSE101685) were integrated with TCGA-LIHC and GTEx dataset to identify differentially expressed genes (DEGs) between normal and cancer tissues in HCC patients, then 5 upregulated differentially expressed genes and 32 downregulated DEGs were identified as common DEGs in total.

Prognostic Significance of Pregnancy Zone Protein and Its Correlation with Immune Infiltrates in Hepatocellular Carcinoma.

Aim: Human pregnancy zone protein (PZP) is a pregnancy-related protein which is increased dramatically during pregnancy. However, the expression of PZP and its prognostic value, association with tumor-infiltrating immune cells (TIICs) in microenvironment and potential biological process in HCC were unclear.

Methods: The PZP expression, clinicopathology analysis and its influence on survival were analyzed by GEPIA and HPA.

Expression and Prognostic Significance of BANF1 in Triple-Negative Breast Cancer.

Aim: To investigate the expression of barrier-to-autointegration factor 1 (BANF1) and its prognostic significance in triple-negative breast cancer (TNBC).

Methods: BANF1 immunohistochemical detection was performed in 60 TNBC specimens and 30 normal control tissues. Real-time PCR was performed to assess the expression of BANF1 gene in TNBC tissues and their correlations with proliferation and metastasis.

TPX2 siRNA regulates growth and invasion of esophageal cancer cells.

Purpose: Observe how specific small RNA interference (siRNA) aimed at TPX2 gene suppresses TPX2 gene expression in esophageal cancer EC9706 cells and the effect on esophageal cancer cell growth and invasion ability.

Methods: Transfect TPX2 siRNA into EC9706 cells via lipofectamin 2000. The experiments were divided into three groups, a negative control, a blank control and an siRNA interference group (24h, 48h, 72h, 96h).