Prognosis and clinical significance of Piezo2 in tumor: a meta-analysis and database validation.

OBJECTIVE: The objective of this study is to assess the correlation between Piezo2 and tumors through a comprehensive meta-analysis and database validation. METHODS: Case-control studies investigating the association between Piezo2 and tumors were obtained from various databases, including China National Knowledge Infrastructure (CNKI), SinoMed, Embase, Web of Science, The Cochrane Library, and PubMed. The search was performed from the inception of each database up until May 2023. Two researchers independently screened the literature, extracted data, and assessed the quality of the included studies. Metaanalysis of the included literature was conducted using Stata 12.0 software. Additionally, the Gene Expression Profiling Interactive Analysis (GEPIA) database predicted a correlation between Piezo2 expression and prognostic value in tumor patients. RESULTS: A total of three studies, involving a combined sample size of 392 participants, were included in the meta-analysis. The findings revealed that the expression level of Piezo2 in tumor patients was not significantly associated with age, gender, or tumor size. However, it was found to be positively correlated with lymphatic invasion (OR = 7.89, 95%CI: 3.96-15.73) and negatively correlated with invasion depth (OR = 0.17, 95%CI: 0.06-0.47), TNM stage (OR = 0.48, 95%CI: 0.27-0.87), and histological grade (OR = 0.40, 95%CI: 0.21-0.77). Confirming these findings, the GEPIA database indicated that high expression of Piezo2 was associated with poor prognosis of disease-free survival in patients with colon adenocarcinoma (HR = 1.6, P = 0.049) and gastric cancer (HR = 1.6, P = 0.017). CONCLUSION: Piezo2 may be associated with poor prognosis and clinicopathological parameters in tumor patients.

Construction of a Cuproptosis-Related Gene Signature for Predicting Prognosis in Gastric Cancer.

This study aimed to develop and validate a cuproptosis-related gene signature for the prognosis of gastric cancer. The data in TCGA GC TPM format from UCSC were extracted for analysis, and GC samples were randomly divided into training and validation groups. Pearson correlation analysis was used to obtain cuproptosis-related genes co-expressed with 19 Cuproptosis genes. Univariate Cox and Lasso regression analyses were used to obtain cuproptosis-related prognostic genes. Multivariate Cox regression analysis was used to construct the final prognostic risk model. The risk score curve, Kaplan-Meier survival curves, and ROC curve were used to evaluate the predictive ability of Cox risk model. Finally, the functional annotation of the risk model was obtained through enrichment analysis. Then, a six-gene signature was identified in the training cohort and verified among all cohorts using Cox regression analyses and Kaplan-Meier plots, demonstrating its independent prognostic significance for gastric cancer. In addition, ROC analysis confirmed the significant predictive potential of this signature for the prognosis of gastric cancer. Functional enrichment analysis was mainly related to cell-matrix function. Therefore, a new cuproptosis-related six-gene signature (ACLY, FGD6, SERPINE1, SPATA13, RANGAP1, and ADGRE5) was constructed for the prognosis of gastric cancer, allowing for tailored prediction of outcome and the formulation of novel therapeutics for gastric cancer patients.

Prognostic significance of N6-methyladenosine-modified related chemotransferase METTL3 in gastric carcinoma: Evidence from meta-analysis.

BACKGROUND: N6-methyladenosine (m6A) methylation is known as the research hotspot for tumor epimodification, and its associated methyltransferase-like3 (METTL3) is significantly differentially expressed in gastric carcinoma, but its clinical value has not been summarized. This meta-analysis aimed to evaluate the prognostic significance of METTL3 in gastric carcinoma. MATERIAL AND METHODS: Databases, including PubMed, EMBASE (Ovid platform), Science Direct, Scopus, MEDLINE, Google Scholar, Web of Science, and Cochrane Library, were used to identify relevant eligible studies. The endpoints included overall survival, progression-free survival, recurrence-free survival, post-progression survival, and disease-free survival. Hazard ratios (HR) with 95% confidence intervals (CI) were used to correlate METTL3 expression with prognosis. Subgroup and sensitivity analyses were performed. RESULTS: Seven eligible studies involving 3034 gastric carcinoma patients were recruited for this meta-analysis. The analysis showed that high METTL3 expression was associated with significantly poorer overall survival (HR = 2.37, 95% CI 1.66-3.39, P < 0.01) and unfavorable disease-free survival (HR = 2.58, 95% CI 1.97-3.38, P < 0.01), as did unfavorable progression-free survival (HR = 1.48, 95% CI 1.19-1.84, P < 0.01)/recurrence-free survival (HR = 2.62, 95% CI 1.93-5.62, P < 0.01)/post-progression survival (HR = 1.53, 95% CI 1.22-1.91, P < 0.01). Subgroup analysis found that high METTL3 expression was associated with worse overall survival in patients with Chinese (HR = 2.21, 95% CI 1.48-3.29, P < 0.01), in studies with sample source from formalin-fixed, paraffin-embedded tissues (HR = 2.66, 95% CI 1.79-3.94, P < 0.01), and the reported directly from articles group (HR = 2.42, 95% CI 1.66-3.53, P < 0.01). The subgroup analysis that was performed based on sample size, detected method, and follow-up showed the same results. CONCLUSIONS: High expression of METTL3 predicts poor prognosis in gastric carcinoma, indicating promise for METTL3 as a prognostic biomarker.Systematic review registration: https://www.crd.york.ac.uk/prospero, ID = CRD42023408519.

Mammalian STE20­like kinase 1 regulates pancreatic cancer cell survival and migration through Mfn2­mediated mitophagy.

Mammalian STE20-like kinase 1 (MST1) plays an important role in pancreatic cancer progression, but its downstream targets are still unknown. In the present study, our results indicated that MST1 expression was significantly downregulated in pancreatic cancer cell lines (PANC­1, BxPC­3 and HPAC) compared with that in the normal ductal epithelial cell line (hTERT­HPNE). Moreover, MST1 overexpression in PANC­1 cells led to increased apoptosis as determined by MTT and TUNEL assays and inhibited cellular migration. Mechanistically, upregulation of MST1 expression caused mitochondrial dysfunction, decreased ATP production, and activation of the mitochondrial­dependent apoptotic pathway via inhibition of mitofusin 2 (Mfn2)­mediated mitophagy, which ultimately resulted in increased cellular apoptosis and decreased cellular migration. Collectively, the present study demonstrated that MST1 may regulate pancreatic cancer PANC­1 cell survival, invasion and migration through Mfn2­mediated mitophagy, laying the foundation for the exploration of novel therapeutic targets for pancreatic cancer.

The rs2839698 Single Nucleotide Polymorphism of lncRNA H19 is Associated with Post-Operative Prognosis in T3 Gastric Adenocarcinoma.

BACKGROUND: It has been widely demonstrated that long non-coding RNA H19 (lncRNA H19) plays an important role in the progression of various human cancers. However, the associations of common genetic variations with recurrence and survival in gastric adenocarcinoma in this lncRNA remain largely unknown. METHODS: The rs2839698 single nucleotide polymorphism (SNP) of H19 was genotyped in tissue samples from 441 patients with T3 gastric adenocarcinoma who had surgical operations between 2004 to 2009, and the relationships between the different genotypes and recurrence and survival after surgery alone (n = 156) or surgery plus chemotherapy (n = 285) were assessed using 3 different statistical-methods. RESULTS: Based on the final day of investigation (November 2014), the GA genotype was significantly associated with recurrence and survival in patients treated with surgery alone, but not in patients treated with surgery plus chemotherapy. In patients treated with surgery alone, individuals with the GA genotype had significantly lower risks of recurrence and death [adjusted hazard ratio (HR) 0.57, 95% CI 0.37 - 0.88; adjusted HR: 0.58, 95% CI 0.38 - 0.88] than the GG genotype (p = 0.010 and p = 0.010), respectively. More importantly, patients treated with surgery alone who carried the GA genotype achieved significantly longer median disease-free survival time and overall survival than carriers of the GG genotype (45 vs. 26 months, p = 0.010; 44 vs. 23 months, p = 0.013). CONCLUSIONS: The rs2839698 SNP of H19 may have potential as a novel prognostic factor for survival in T3 gastric adenocarcinoma after surgery alone; these finding have special relevance to patients who are not suitable for postoperative chemotherapy.

Single-cell genomic profiling of acute myeloid leukemia for clinical use: A pilot study.

Although bulk high-throughput genomic profiling studies have led to a significant increase in the understanding of cancer biology, there is increasing awareness that bulk profiling approaches do not completely elucidate tumor heterogeneity. Single-cell genomic profiling enables the distinction of tumor heterogeneity, and may improve clinical diagnosis through the identification and characterization of putative subclonal populations. In the present study, the challenges associated with a single-cell genomics profiling workflow for clinical diagnostics were investigated. Single-cell RNA-sequencing (RNA-seq) was performed on 20 cells from an acute myeloid leukemia bone marrow sample. Putative blasts were identified based on their gene expression profiles and principal component analysis was performed to identify outlier cells. Variant calling was performed on the single-cell RNA-seq data. The present pilot study demonstrates a proof of concept for clinical single-cell genomic profiling. The recognized limitations include significant stochastic RNA loss and the relatively low throughput of the current proposed platform. Although the results of the present study are promising, further technological advances and protocol optimization are necessary for single-cell genomic profiling to be clinically viable.

Coverage analysis in a targeted amplicon-based next-generation sequencing panel for myeloid neoplasms.

AIMS: PCR amplicon-based next-generation sequencing (NGS) panels are increasingly used for clinical diagnostic assays. Amplification bias is a well-known limitation of PCR amplicon-based approaches. We sought to characterise lower-performance amplicons in an off-the-shelf NGS panel (TruSight Myeloid Sequencing Panel) for myeloid neoplasms and attempted to patch the low read depth for one of the affected genes, CEBPA. METHODS: We performed targeted NGS of 158 acute myeloid leukaemia samples and analysed the amplicon read depths across 568 amplicons to identify lower-performance amplicons. We also correlated the amplicon read depths with the template GC content. Finally, we attempted to patch the low read depth for CEBPA using a parallel library preparation (Nextera XT) workflow. RESULTS: We identified 16 lower-performance amplicons affecting nine genes, including CEBPA. There was a slight negative correlation between the amplicon read depths and template GC content. Addition of the separate CEBPA library generated a minimum read depth per base across the CEBPA gene ranging from 268x to 758x across eight samples. CONCLUSIONS: The identification of lower-performance amplicons will be informative to laboratories intending to use this panel. We have also demonstrated proof-of-concept that different libraries (TruSight Myeloid and Nextera XT) can be combined and sequenced on the same flow cell to generate additional reads for CEBPA.

A machine learning approach for the identification of key markers involved in brain development from single-cell transcriptomic data.

BACKGROUND: The ability to sequence the transcriptomes of single cells using single-cell RNA-seq sequencing technologies presents a shift in the scientific paradigm where scientists, now, are able to concurrently investigate the complex biology of a heterogeneous population of cells, one at a time. However, till date, there has not been a suitable computational methodology for the analysis of such intricate deluge of data, in particular techniques which will aid the identification of the unique transcriptomic profiles difference between the different cellular subtypes. In this paper, we describe the novel methodology for the analysis of single-cell RNA-seq data, obtained from neocortical cells and neural progenitor cells, using machine learning algorithms (Support Vector machine (SVM) and Random Forest (RF)). RESULTS: Thirty-eight key transcripts were identified, using the SVM-based recursive feature elimination (SVM-RFE) method of feature selection, to best differentiate developing neocortical cells from neural progenitor cells in the SVM and RF classifiers built. Also, these genes possessed a higher discriminative power (enhanced prediction accuracy) as compared commonly used statistical techniques or geneset-based approaches. Further downstream network reconstruction analysis was carried out to unravel hidden general regulatory networks where novel interactions could be further validated in web-lab experimentation and be useful candidates to be targeted for the treatment of neuronal developmental diseases. CONCLUSION: This novel approach reported for is able to identify transcripts, with reported neuronal involvement, which optimally differentiate neocortical cells and neural progenitor cells. It is believed to be extensible and applicable to other single-cell RNA-seq expression profiles like that of the study of the cancer progression and treatment within a highly heterogeneous tumour.

Cytokine expression profile of dengue patients at different phases of illness.

BACKGROUND: Dengue is an important medical problem, with symptoms ranging from mild dengue fever to severe forms of the disease, where vascular leakage leads to hypovolemic shock. Cytokines have been implicated to play a role in the progression of severe dengue disease; however, their profile in dengue patients and the synergy that leads to continued plasma leakage is not clearly understood. Herein, we investigated the cytokine kinetics and profiles of dengue patients at different phases of illness to further understand the role of cytokines in dengue disease. METHODS AND FINDINGS: Circulating levels of 29 different types of cytokines were assessed by bead-based ELISA method in dengue patients at the 3 different phases of illness. The association between significant changes in the levels of cytokines and clinical parameters were analyzed. At the febrile phase, IP-10 was significant in dengue patients with and without warning signs. However, MIP-1ß was found to be significant in only patients with warning signs at this phase. IP-10 was also significant in both with and without warning signs patients during defervescence. At this phase, MIP-1ß and G-CSF were significant in patients without warning signs, whereas MCP-1 was noted to be elevated significantly in patients with warning signs. Significant correlations between the levels of VEGF, RANTES, IL-7, IL-12, PDGF and IL-5 with platelets; VEGF with lymphocytes and neutrophils; G-CSF and IP-10 with atypical lymphocytes and various other cytokines with the liver enzymes were observed in this study. CONCLUSIONS: The cytokine profile patterns discovered between the different phases of illness indicate an essential role in dengue pathogenesis and with further studies may serve as predictive markers for progression to dengue with warning signs.

Dendritic cell mediated delivery of plasmid DNA encoding LAMP/HIV-1 Gag fusion immunogen enhances T cell epitope responses in HLA DR4 transgenic mice.

This report describes the identification and bioinformatics analysis of HLA-DR4-restricted HIV-1 Gag epitope peptides, and the application of dendritic cell mediated immunization of DNA plasmid constructs. BALB/c (H-2d) and HLA-DR4 (DRA1*0101, DRB1*0401) transgenic mice were immunized with immature dendritic cells transfected by a recombinant DNA plasmid encoding the lysosome-associated membrane protein-1/HIV-1 Gag (pLAMP/gag) chimera antigen. Three immunization protocols were compared: 1) primary subcutaneous immunization with 1x10(5) immature dendritic cells transfected by electroporation with the pLAMP/gag DNA plasmid, and a second subcutaneous immunization with the naked pLAMP/gag DNA plasmid; 2) primary immunization as above, and a second subcutaneous immunization with a pool of overlapping peptides spanning the HIV-1 Gag sequence; and 3) immunization twice by subcutaneous injection of the pLAMP/gag DNA plasmid. Primary immunization with pLAMP/gag-transfected dendritic cells elicited the greatest number of peptide specific T-cell responses, as measured by ex vivo IFN-gamma ELISpot assay, both in BALB/c and HLA-DR4 transgenic mice. The pLAMP/gag-transfected dendritic cells prime and naked DNA boost immunization protocol also resulted in an increased apparent avidity of peptide in the ELISpot assay. Strikingly, 20 of 25 peptide-specific T-cell responses in the HLA-DR4 transgenic mice contained sequences that corresponded, entirely or partially to 18 of the 19 human HLA-DR4 epitopes listed in the HIV molecular immunology database. Selection of the most conserved epitope peptides as vaccine targets was facilitated by analysis of their representation and variability in all reported sequences. These data provide a model system that demonstrates a) the superiority of immunization with dendritic cells transfected with LAMP/gag plasmid DNA, as compared to naked DNA, b) the value of HLA transgenic mice as a model system for the identification and evaluation of epitope-based vaccine strategies, and c) the application of variability analysis across reported sequences in public databases for selection of historically conserved HIV epitopes as vaccine targets.