Development of a Routine Serological Test Index Panel for the Surveillance of Gastric Cancer Risk in a High-Risk Population.

OBJECTIVE: This study aims to develop a predictive model for the detection of gastric cancer risk utilizing non-invasive parameters and to assess the model's effectiveness in risk stratification for gastric cancer (GC). METHODS: A case-control study was conducted among inpatients with various gastric diseases. These individuals were categorized into two groups: the gastric cancer group (138 cases) and the chronic non-atrophic gastritis (CNAG) group (319 cases). We employed a comprehensive panel of hematological, biochemical, and coagulation parameters derived from routine blood tests. Random Forest and Logistic regression analysis was used for feature selection and model building. Statistical analyses were performed using R version 4.2.3. RESULTS: Logistic regression analysis was employed to establish risk prediction models for GC, incorporating variables such as D-dimer, carcinoembryonic antigen (CEA), carbohydrate antigen 724 (CA724), and hemoglobin (HGB). A visual nomogram was generated as the final prediction model. The area under the receiver operating characteristic curve (AUC) for the training and test sets were 0.8093 [95% confidence interval (CI), 0.7541-0.8644], and 0.8076 [95% CI 0.7237-0.8915], respectively. Furthermore, we have developed an HTML file, featuring the Logistic equation, which enables real-time assessment of GC risk scores. CONCLUSION: The performance of this predictive model demonstrates its adequacy, making it a valuable and cost-effective noninvasive tool for identifying early gastric cancer (EGC) in patients. Consequently, this model may facilitate the implementation of targeted preventive and intervention strategies in clinical practice.

Comprehensive analysis of aberrantly expressed circRNAs, mRNAs and lncRNAs in patients with nasopharyngeal carcinoma.

BACKGROUND: The location of nasopharyngeal cancer is hidden, so it is difficult to diagnose at an early stage. In this study, we aimed to investigate the expression profiles of circRNAs, mRNAs and IncRNAs and to provide some basis for further studies. METHODS: Expression profiles of circRNAs, mRNAs, and lncRNAs were analyzed using microarray techniques. The differentially expressed ncRNA was calculated by bioinformatics. RESULTS: A total of 3048 circRNAs, 2179 lncRNAs, and 2015 mRNAs were detected to be significantly differentially expressed in NPC. The most upregulated circRNAs, lncRNAs, and mRNAs were hsa-circ-0067562, NONHSAT232922.1, and HOXB13, respectively. And, the most downregulated circRNAs, lncRNAs, and mRNAs were hsa_circ_0078837, lnc-TTC8-4:3, and LTF, respectively. The number of upregulated DE lncRNAs was more than twice than those downregulated. Our data showed that 80.44% of pairs of lncRNAs and cis-mRNAs demonstrated positive correlations. For lncRNAs and trans-mRNAs pairs, 53.7% of pairs showed positive correlation. LncRNA-mediated cis regulation is a prevalent regulatory mode in the development of nasopharyngeal carcinoma. CR1, LRMP and SORBS2 are predicted to be mediated not only by cis-acting lncRNA modes of action, but also by trans-acting lncRNA mechanisms. Additionally, we constructed a diagnostic prediction model with a high sensitivity and specificity. CONCLUSION: Our study characterized the landscape of circRNAs, mRNAs and lncRNAs in NPC tissue and provided novel insights into the molecular mechanisms of NPC.

An aberrant DNA methylation signature for predicting the prognosis of head and neck squamous cell carcinoma.

Head and neck squamous cell carcinoma (HNSCC) is a common malignancy worldwide with a poor prognosis. DNA methylation is an epigenetic modification that plays a critical role in the etiology and pathogenesis of HNSCC. The current study aimed to develop a predictive methylation signature based on bioinformatics analysis to improve the prognosis and optimize therapeutic outcome in HNSCC. Clinical information and methylation sequencing data of patients with HNSCC were downloaded from The Cancer Genome Atlas database. The R package was used to identify differentially methylated genes (DMGs) between HNSCC and adjacent normal tissues. We identified 22 DMGs associated with 246 differentially methylated sites. Patients with HNSCC were classified into training and test groups. Cox regression analysis was used to build a risk score formula based on the five methylation sites (cg26428455, cg13754259, cg17421709, cg19229344, and cg11668749) in the training group. The Kaplan-Meier survival curves showed that the overall survival (OS) rates were significantly different between the high- and low-risk groups sorted by the signature in the training group (median: 1.38 vs. 1.57 years, log-rank test, p < 0.001). The predictive power was then validated in the test group (median: 1.34 vs. 1.75 years, log-rank test, p < 0.001). The area under the receiver operating characteristic curve (area under the curve) based on the signature for predicting the 5-year survival rates, was 0.7 in the training and 0.73 in test groups, respectively. The results of multivariate Cox regression analysis showed that the riskscore (RS) signature based on the five methylation sites was an independent prognostic tool for OS prediction in patients. In addition, a predictive nomogram model that incorporated the RS signature and patient clinical information was developed. The innovative methylation signature-based model developed in our study represents a robust prognostic tool for guiding clinical therapy and predicting the OS in patients with HNSCC.

Comparison of three automatic chemiluminescent immunoassays for monitoring dynamic profile of SARS-CoV-2 IgG and IgM.

BACKGROUND: Seldom performance evaluation and diagnosis comparison studies were reported for different chemiluminescent immunoassay (CLIA) kits approved under an emergency approval program for SARS-CoV-2 infection. METHODS: A total of 100 and 105 serum separately from non-infected populations and COVID-19 patients were detected with SARS-CoV-2 IgM and IgG kits. The characteristics including precision, functional sensitivity, linearity, and accuracy were evaluated for Axceed, iFlash, and Maglumi CLIA kits. RESULTS: Maglumi and iFlash had the best analytical sensitivity for IgM and IgG, respectively. Axceed kits had a linearity response in the detected concentration. The clinical sensitivity of Axceed, iFlash, and Maglumi was 68.0%, 64.9%, and 63.9% with a specificity of 99.0%, 96.0%, and 100% for IgM, 85.6%, 97.9%, and 94.8% with a specificity of 97.0% for IgG. ROC analysis indicated all kits had a diagnostic power greater than 0.9. Notably, either IgM or IgG kits obtained a poor agreement (Kappa value from 0.397 to 0.713) with others. Among 38 recovered patients, 94.7% had an effective immune response, and both seropositive IgM and IgG accounted for the biggest proportion (medium, 42 days onset), then followed by the single seropositive IgG (medium, 50 days onset) in Ab profile. CONCLUSION: The performance of CLIA kits satisfied the diagnosis of SARS-CoV-2 infection. Both positive of IgG and IgM contributes to improve the specificity, and a positive one will enhance the sensitivity.

Analytical performance evaluation of five RT-PCR kits for severe acute respiratory syndrome coronavirus 2.

BACKGROUND: We aimed to evaluate the analytical performance of five commercial RT-PCR kits (Genekey, Daan, BioGerm, Liferiver, and Yaneng) commonly used in China, since such comparison data are lacking. METHODS: A total of 20 COVID-19 confirmed patients and 30 negative nasopharyngeal swab specimens were analyzed by five kits. The detection ability of five RT-PCR kits was evaluated with 5 concentration gradients diluted by a single positive sample. The limit of detection was evaluated by N gene fragment solid standard. Two positive clinical specimens were used to evaluate the repeatability and imprecision. Finally, we used six human coronaviruses plasmid and four respiratory pathogens plasmid to check for cross-reactivity. RESULTS: The positive detection rate was 100% for Genekey, Daan, and BioGerm,and 90% for Liferiver and Yaneng in 20 clinical SARS-CoV-2 infection. The coincidence rate of five kits in 10 negative samples was 100%. The detection rate of target genes for Daan, BioGerm, Liferiver, and Yaneng was 100% from Level 1 to Level 3. In Level 4, only Daan detection rate was 100%. In Level 5, five kits presented poor positive rate. The limit of detection declared by each manufacturer was verified. The repeatability for target genes was less than 5% and so did the total imprecision. There is no cross-reactivity of five kits with six human coronaviruses and four respiratory pathogens for ORF1ab and N gene. CONCLUSIONS: Five RT-PCR kits assessed in this study showed acceptable analytical performance characteristics and are useful tools for the routine diagnosis of SARS-CoV-2.

Consistency evaluation of Liferiver, Yaneng, Darui, and the Cobas 4800 test for high-risk human papillomavirus screening.

BACKGROUND: In recent years, several high-risk human papillomavirus (HR-HPV) tests have been developed. The assay capabilities need to be systematically reviewed. Here, we compared the clinical sample performance of three novel HR-HPV assays (Liferiver, Yaneng, and Darui) based on different platforms with the widely adopted cobas4800 test. METHODS: A total of 346 cervical swabs from women who were screened for cervical cancer were analyzed for the presence of 14 HR-HPV genotypes. The distinction between the four assays was investigated by the genotyping and direct sequencing. RESULTS: The positive rates of the four assays ranged from 61.56% to 64.16%. The overall concordance was 88.15%. The Yaneng assays displayed the best sensitivity (100%) and specificity (98.43%). The sensitivity (98.17%) and specificity (98.43%) of the Darui assay were superior to those of the cobas4800 test (97.72% and 93.70%, respectively). The Liferiver assay displayed comparable sensitivity with the cobas4800 test (95.89% and 97.72%, respectively). The specificity of the cobas4800 was lower than that of the Liferiver assay (93.70% vs. 97.64%). CONCLUSIONS: The three novel HR-HPV assays displayed good agreement with the cobas4800 test. The analytical performance of all four fulfilled the requirements of sensitivity and specificity for HR-HPV detection.

Performance evaluation of the XPEN60 CRP&SAA, a novel automated hematology analyzer, in detecting complete blood count, C-reactive protein, and serum amyloid A.

BACKGROUND: The XPEN60 CRP&SAA (hereafter XPEN60) is a new automated hematology analyzer that can rapidly detect C-reactive protein (CRP), serum amyloid A (SAA), and blood cell counts (CBC), including the 5-part differential of white blood cells (5-DIFF). The aim of this study was to evaluate the analytical performance of XPEN60. METHODS: The analytical performance of XPEN60 was evaluated on the basis of several parameters, including the limit of blank (LoB), limit of detection (LoD), limit of quantitation (LoQ), precision, accuracy, carryover, linearity, clinical reportable range (CRR), and interference test. In addition, method comparisons between CBC and 5-DIFF, CRP, and SAA were performed on several systems. RESULTS: Total imprecision and accuracy for all parameters fell within acceptable criteria, and excellent measurements were observed in the dilution linearity (coefficient of determination, R2  > .99). LoBs and LoDs (0 and 0.21 mg/L for CRP, 1.1 and 2.27 mg/L for SAA) satisfy the manufacturer's statement. LoQs were 0.61 and 3.62 mg/L for CRP and SAA, respectively. No significant carryover or interference tests (<10%) were observed in this study. The comparison analysis demonstrated strong agreement between XPEN60 results and those of Sysmex-XN1000 (XN1000), except for basophils (Bas) and eosinophils (Eos). The data correlated well with E601 and Mindray CRP-M100 for CRP. CONCLUSION: XPEN60 was demonstrated satisfactory analytical performance, which made it well-suited for use in clinical laboratories, emergency departments, and community hospitals.

Development of a novel prognostic signature for predicting the overall survival of bladder cancer patients.

BACKGROUND: Bladder cancer is one of the most common malignancies. So far, no effective biomarker for bladder cancer prognosis has been identified. Aberrant DNA methylation is frequently observed in the bladder cancer and holds considerable promise as a biomarker for predicting the overall survival (OS) of patients. MATERIALS AND METHODS: We downloaded the DNA methylation and transcriptome data for bladder cancer from The Cancer Genome Atlas (TCGA), a public database, screened hypo-methylated and up-regulated genes, similarly, hyper-methylation with low expression genes, then retrieved the relevant methylation sites. Cox regression analysis was used to identify a nine-methylation site signature of a training group. Predictive ability was validated in a test group by receiver operating characteristic (ROC) analysis. RESULTS: We identified nine bladder cancer-specific methylation sites as potential prognostic biomarkers and established a risk score system based on the methylation site signature to evaluate the OS. The performance of the signature was accurate, with area under curve was 0.73 in the training group and 0.71 in the test group. Taking clinical features into consideration, we constructed a nomogram consisting of the nine-methylation site signature and patients' clinical variables, and found that the signature was an independent risk factor. CONCLUSIONS: Overall, the significant nine methylation sites could be novel prediction biomarkers, which could aid in treatment and also predict the overall survival likelihoods of bladder cancer patients.

LINC00958 and HOXC13-AS as key candidate biomarkers in head and neck squamous cell carcinoma by integrated bioinformatics analysis.

BACKGROUND: Head and neck squamous cell carcinoma (HNSCC) is a malignant tumor with a strong tendency for metastasis and recurrence. Finding effective biomarkers for the early diagnosis of HNSCC is critical for the early treatment and prognosis of patients. METHODS: RNA sequencing data including long non-coding RNAs (lncRNAs), messenger RNA (mRNAs) and microRNAs (miRNAs) of 141 HNSCC and 44 adjacent normal tissues were obtained from the TCGA. Differentially expressed genes were analyzed using the R package DESeq. GO terms and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were conducted. A competing endogenous RNAs (ceRNA) network was constructed. The most differentially expressed genes in the main ceRNA network were chosen for nasopharyngeal carcinoma (NPC) cell lines and NPEC2 Bmi-1 cell line verification. A receiver operating characteristic (ROC) curve was constructed for 141 specimens of HNSCC tissues from 44 control samples. RESULTS: In our study, 79 HNSCC-associated abnormally expressed lncRNAs , 86 abnormally expressed miRNAs and 324 abnormally expressed mRNAs were identified. The public microarray results showed that LINC00958 and HOXC13-AS expression levels were upregulated in HNSCC tissues compared with the adjacent normal tissues in this study (p < 0.0001). LINC00958 and HOXC13-AS expression levels in NPC cell lines were higher than those in the NPEC2 Bmi-1 cell line (p < 0.05). The results showed that the area under the ROC curve (AUC) of LINC00958 reached up to 0.906 at a cutoff value of 7.96, with a sensitivity and specificity of 80.85% and 90.91%, respectively. The AUC of HOXC13-AS reached up to 0.898 at a cutoff value of 0.695, with sensitivity and specificity values of 86.23% and 83.78%, respectively. CONCLUSION: The current study indicates that LINC00958 and HOXC13-AS are new candidate diagnostic biomarkers for HNSCC patients.