Analytical evaluation of the automated genotyping system (GenPlex) compared to a traditional real-time PCR assay for the detection of high-risk human papillomaviruses.

The detection of high-risk human papillomaviruses (HPVs) is crucial for early screening and preventing cervical cancer. However, the substantial workload in high-level hospitals or the limited resources in primary-level hospitals hinder widespread testing. To address this issue, we explored a sample-to-answer genotyping system and assessed its performance by comparing it with the traditional real-time polymerase chain reaction (PCR) method conducted manually. Samples randomly selected from those undergoing routine real-time PCR detection were re-analyzed using the fully automatic GenPlex® system. This system identifies 24 types of HPV through a combination of ordinary PCR and microarray-based reverse hybridization. Inconsistent results were confirmed by repeated testing with both methods, and the κ concordance test was employed to evaluate differences between the two methods. A total of 365 samples were randomly selected from 7259 women. According to real-time PCR results, 76 were high-risk HPV negative, and 289 were positive. The GenPlex® system achieved a κ value greater than 0.9 (ranging from 0.920 to 1.000, p < 0.0001) for 14 types of high-risk HPV, except HPV 51 (κ = 0.697, p < 0.0001). However, the inconsistent results in high-risk HPV 51 were revealed to be false positive in real-time PCR by other method. When counting by samples without discriminating the high-risk HPV type, the results of both methods were entirely consistent (κ = 1.000, p < 0.0001). Notably, the GenPlex® system identified more positive cases, with 73 having an HPV type not covered by real-time PCR, and 20 potentially due to low DNA concentration undetectable by the latter. Compared with the routinely used real-time PCR assay, the GenPlex® system demonstrated high consistency. Importantly, the system's advantages in automatic operation and a sealed lab-on-chip format respectively reduce manual work and prevent aerosol pollution. For widespread use of GenPlex® system, formal clinical validation following international criteria should be warranted.

The level of macrophage migration inhibitory factor is negatively correlated with the efficacy of PD-1 blockade immunotherapy combined with chemotherapy as a neoadjuvant therapy for esophageal squamous cell carcinoma.

PURPOSE: This study aimed to screen biomarkers to predict the efficacy of programmed cell death 1 (PD-1) blockade immunotherapy combined with chemotherapy as neoadjuvant therapy for esophageal squamous cell carcinoma (ESCC). METHODS: In the first stage of the study, the baseline concentrations of 40 tumor-related chemokines in the serum samples of 50 patients were measured to screen for possible biomarkers. We investigated whether the baseline concentration of the selected chemokine was related to the therapeutic outcomes and tumor microenvironment states of patients treated with the therapy. In the second stage, the reliability of the selected biomarkers was retested in 34 patients. RESULTS: The baseline concentration of macrophage migration inhibitory factor (MIF) was negatively correlated with disease-free survival (DFS) and overall survival (OS) in patients treated with the therapy. In addition, a low baseline expression level of MIF is related to a better tumor microenvironment for the treatment of ESCC. A secondary finding was that effective treatment decreased the serum concentration of MIF. CONCLUSION: Baseline MIF levels were negatively correlated with neoadjuvant therapy efficacy. Thus, MIF may serve as a predictive biomarker for this therapy. The accuracy of the prediction could be improved if the serum concentration of MIF is measured again after the patient received several weeks of treatment.

Integrated bioinformatics analysis and experimental validation reveal ISG20 as a novel prognostic indicator expressed on M2 macrophage in glioma.

BACKGROUND: Glioma is the most common malignant primary brain tumor and is characterized by a poor prognosis and limited therapeutic options. ISG20 expression is induced by interferons or double-stranded RNA and is associated with poor prognosis in several malignant tumors. Nevertheless, the expression of ISG20 in gliomas, its impact on patient prognosis, and its role in the tumor immune microenvironment have not been fully elucidated. METHODS: Using bioinformatics, we comprehensively illustrated the potential function of ISG20, its predictive value in stratifying clinical prognosis, and its association with immunological characteristics in gliomas. We also confirmed the expression pattern of ISG20 in glioma patient samples by immunohistochemistry and immunofluorescence staining. RESULTS: ISG20 mRNA expression was higher in glioma tissues than in normal tissues. Data-driven results showed that a high level of ISG20 expression predicted an unfavorable clinical outcome in glioma patients, and revealed that ISG20 was possibly expressed on tumor-associated macrophages and was significantly associated with immune regulatory processes, as evidenced by its positive correlation with the infiltration of regulatory immune cells (e.g., M2 macrophages and regulatory T cells), expression of immune checkpoint molecules, and effectiveness of immune checkpoint blockade therapy. Furthermore, immunohistochemistry staining confirmed the enhanced expression of ISG20 in glioma tissues with a higher WHO grade, and immunofluorescence assay verified its cellular localization on M2 macrophages. CONCLUSIONS: ISG20 is expressed on M2 macrophages, and can serve as a novel indicator for predicting the malignant phenotype and clinical prognosis in glioma patients.