Neutrophilic Myeloid-Derived Suppressor Cells and Severity in SARS-CoV-2 Infection.

BACKGROUND: While we strive to live with SARS-CoV-2, defining the immune response that leads to recovery rather than severe disease remains highly important. COVID-19 has been associated with inflammation and a profoundly suppressed immune response. OBJECTIVE: To study myeloid-derived suppressor cells (MDSCs), which are potent immunosuppressive cells, in SARS-CoV-2 infection. RESULTS: Patients with severe and critical COVID-19 showed higher frequencies of neutrophilic (PMN)-MDSCs than patients with moderate illness and control individuals (P = .005). Severe disease in individuals older and younger than 60 years was associated with distinct PMN-MDSC frequencies, being predominantly higher in patients of 60 years of age and younger (P = .004). However, both age groups showed comparable inflammatory markers. In our analysis for the prediction of poor outcome during hospitalization, MDSCs were not associated with increased risk of death. Still, patients older than 60 years of age (odds ratio [OR] = 5.625; P = .02) with preexisting medical conditions (OR = 2.818; P = .003) showed more severe disease and worse outcome. Among the immunological parameters, increased C-reactive protein (OR = 1.015; P = .04) and lymphopenia (OR = 5.958; P = .04) strongly identified patients with poor prognosis. CONCLUSION: PMN-MDSCs are associated with disease severity in COVID-19; however, MDSC levels do not predict increased risk of death during hospitalization.

Biomarkers for Hepatocellular Carcinoma: From Origin to Clinical Diagnosis.

The incidence of hepatocellular carcinoma (HCC) and HCC-related deaths has increased over the last few decades. There are several risk factors of HCC such as viral hepatitis (B, C), cirrhosis, tobacco and alcohol use, aflatoxin-contaminated food, pesticides, diabetes, obesity, nonalcoholic fatty liver disease (NAFLD), and metabolic and genetic diseases. Diagnosis of HCC is based on different methods such as imaging ultrasonography (US), multiphasic enhanced computed tomography (CT), magnetic resonance imaging (MRI), and several diagnostic biomarkers. In this review, we examine the epidemiology of HCC worldwide and in Egypt as well as risk factors associated with the development of HCC and, finally, provide the updated diagnostic biomarkers for the diagnosis of HCC, particularly in the early stages of HCC. Several biomarkers are considered to diagnose HCC, including downregulated or upregulated protein markers secreted during HCC development, circulating nucleic acids or cells, metabolites, and the promising, recently identified biomarkers based on quantitative proteomics through the isobaric tags for relative and absolute quantitation (iTRAQ). In addition, a diagnostic model used to improve the sensitivity of combined biomarkers for the diagnosis of early HCC is discussed.

A combination of α-fetoprotein, midkine, thioredoxin and a metabolite for predicting hepatocellular carcinoma.

INTRODUCTION AND OBJECTIVES: The heterogenous nature of hepatocellular carcinoma (HCC) motivated this attempt at developing and validating a model based on combined biomarkers for improving early HCC detection. PATIENTS/MATERIALS AND METHODS: This study examined 196 patients for an estimation study (104 patients with HCC, 52 with liver cirrhosis and 40 with liver fibrosis) and 122 patients for the validation study (80 patients with HCC, 42 with liver cirrhosis). All patients were positive for hepatitis C virus. Four markers were measured: Midkine and thioredoxin using ELISA, 1-methyladenosine and 1-methylguanosine using a gas chromatography-mass spectrometry (GC-MS). The results were compared with alpha-fetoprotein (AFP). The performance of the model was estimated in BCLC, CLIP and Okuda staging systems of HCC. RESULTS: The model yielded high performance with an area under ROC (AUC) of 0.94 for predicting HCC in patients with liver cirrhosis, compared with AUC of 0.69 for AFP. This model had AUCs of 0.93, 0.94 and 0.94 in patients who had only one single nodule, absent macrovascular invasion and tumor size <2cm, respectively, compared with AUCs of 0.71, 0.6 and 0.59 for AFP. The model produced AUCs of 0.91 for BCLC (0-A), 0.92 for CLIP (0-1) and 0.94 for Okuda (stage I) compared with AUCs of 0.56, 0.58 and 0.64 for AFP. No significant difference was found between AUC in the estimation and the validation groups. CONCLUSION: This model may enhance early-stage HCC detection and help to overcome insufficient sensitivity of AFP.

An Easy and Useful Noninvasive Score Based on α-1-acid Glycoprotein and C-Reactive Protein for Diagnosis of Patients with Hepatocellular Carcinoma Associated with Hepatitis C Virus Infection.

This study aimed to evaluate the diagnostic value of α-1-acid glycoprotein (AGP) and C-reactive protein (CRP) and develop a predictive score to improve the diagnosis of hepatocellular carcinoma (HCC). AGP and CRP were measured in serum of 53 HCC patients and 20 liver cirrhosis (LC) patients, in addition to 15 healthy individuals. Area under receiver-operating characteristic curves (AUCs) was used to create a predictive score comprising AGP, CRP, alpha fetoprotein, and albumin. The diagnostic performances of score was determined and compared with AFP alone for the diagnosis of HCC. The combination of AGP, albumin, CRP, and AFP had AUC 0.92 and sensitivity 85% which was higher than AFP alone. The odds ratio of having HCC was 8.4 for AGP, 5.8 for CRP, 12.5 for AFP and 6.5 for albumin. Our score predicted HCC with an OR of 50.6 for HCC. The AUC of score in HCC with single tumor, absent vascular invasion and CLIP score (0-1) were 0.9, 0.9, 0.82, respectively, compared with 0.71, 0.71, 0.68, respectively, for AFP. In conclusion, a non-invasive and simple score based on AGP, CRP, AFP, and albumin could improve the accuracy of HCC diagnosis.