Circular RNAs (circRNAs) are a newly validated type of noncoding RNAs recently found to be deregulated in several human cancers. More accurate and specific noninvasive biomarkers are strongly needed for better diagnosis and prognosis of hepatocellular carcinoma (HCC). We performed a bioinformatics analysis to retrieve a novel panel of circRNAs potentially relevant to HCC. We examined their expression in the sera of 68 patients with HCC, 60 patients with chronic hepatitis C, and 36 healthy controls using quantitative polymerase chain reaction. We examined the performance characteristics of the selected circRNA biomarker panel in comparison with alpha‐fetoprotein (AFP). In addition, we performed a survival analysis to correlate between their expression levels and patient survival. The circRNAs hsa_circ _00224 and hsa_circ _00520 showed a strong biomarker potential with relatively high sensitivities and specificities compared with AFP. The combined panel including the three circRNAs showed superior performance characteristics relative to those of AFP. The median follow‐up period was 26 months. hsa_circ_00520 expression has been shown to be associated with relapse‐free survival (P < 0.005). circRNAs hsa_circ_00156, hsa_circ_000224, and hsa_circ_000520 are novel potential biomarkers of high sensitivity and specificity, which could potentially be used in the diagnosis of HCC.

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(1) Background: The coronavirus (COVID-19) pandemic is still a major global health problem, despite the development of several vaccines and diagnostic assays. Moreover, the broad symptoms, from none to severe pneumonia, and the various responses to vaccines and the assays, make infection control challenging. Therefore, there is an urgent need to develop non-invasive biomarkers to quickly determine the infection severity. Circulating RNAs have been proven to be potential biomarkers for a variety of diseases, including infectious ones. This study aimed to develop a genetic network related to cytokines, with clinical validation for early infection severity prediction. (2) Methods: Extensive analyses of in silico data have established a novel IL11RA molecular network (IL11RNA mRNA, LncRNAs RP11-773H22.4 and hsa-miR-4257). We used different databases to confirm its validity. The differential expression within the retrieved network was clinically validated using quantitative RT-PCR, along with routine assessment diagnostic markers (CRP, LDH, D-dimmer, procalcitonin, Ferritin), in100 infected subjects (mild and severe cases) and 100 healthy volunteers. (3) Results: IL11RNA mRNA and LncRNA RP11-773H22.4, and the IL11RA protein, were significantly upregulated, and there was concomitant downregulation of hsa-miR-4257, in infected patients, compared to the healthy controls, in concordance with the infection severity. (4) Conclusion: The in-silico data and clinical validation led to the identification of a potential RNA/protein signature network for novel predictive biomarkers, which is in agreement with ferritin and procalcitonin for determination of COVID-19 severity.

Human papillomavirus (HPV-16) E6 proteins inhibit apoptosis in both p53-dependent and p53-independent manners. So it was relevant to assess the impact of such infection on head and neck cancers and its relation to the inhibitors of apoptosis (IAPs). CIAP2 is one of these IAPs that is postulated to upregulated by E6 proteins of HPV-16 by amplification of the locus bearing it in many tissues. In this study, we aimed to search for the amplification of the locus bearing CIAP-2 and its relation to HPV-16 in head and neck cancer that may have prognostic and therapeutic impacts on these patients. Total 30 patients diagnosed as head and neck cancer (2 tissue samples were taken from each patient: from the tumor and from the safety margin). All samples were subjected to qualitative polymerase chain reaction analysis for HPV-16 and qualitative and semiquantitative reverse transcription polymerase chain reaction of CIAP-2. There was a significant association between HPV-16 and CIAP2 positivity and head and neck tumors (P=0.01). CIAP-2 expression in malignant tissues was highly associated with HPV-16 infection with 73.9% sensitivity and absolute specificity.

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