Theranostic Potential of EFNB2 for Cetuximab Resistance in Head and Neck Cancer.

Only 13% of head and neck cancer (HNC) patients respond to cetuximab therapy despite its target (EGFR) is expressed in about 80-90% of HNC patients. However, this problem remained unresolved till date despite of numerous efforts. Thus, the current study aimed to establish hub genes involved in cetuximab resistance via series of bioinformatics approach. The GSE21483 dataset was analysed for differentially expressed genes (DEGs) using GEO2R and enrichment analysis was carried out using DAVID. STRING 11.5 and Cytoscape 3.7.2 were used for protein-protein interactions and hub genes respectively. The significant hub genes (p < 0.05) were validated using ULCAN and Human protein atlas. Validated genes were further queried for tumor infiltration using TIMER2.0. Out of total 307 DEGs, 38 hub genes were identified of which IL1A, EFNB2, SPRR1A, ROBO1 and SOCS3 were the significant hub genes associated with both mRNA expression and overall survival. IL1A, ROBO1, and SOCS3 were found to be downregulated whereas EFNB2 and SPRR1A were found to be upregulated in our study. However, using UALCAN, we found that high expression of IL1A, EFNB2, SOCS3 negatively affects overall survival whereas high expression of SPRR1A and ROBO1 positively affects overall survival. Protein level for EFNB2 and SPRR1A expression was significant in tumor HNC tissue as compared to normal HNC tissue. EFNB2 was found to be a key regulator of CTX resistance among HNC patients. Targeting EFNB2 and associated PPI circuits might improve the response rate to CTX. Thus, EFNB2 has potential to be theranostic marker for CTX resistance. Supplementary Information: The online version contains supplementary material available at 10.1007/s12070-023-03739-9.

Tissue plasminogen activator receptor ANXA2 and its complementary regulator anti-inflammatory ANXA1 as prognostic indicators of inflammatory response in COVID-19 pathogenesis.

COVID-19 patients demonstrating hyperactive immunologic response appear to have a severe illness with a poor prognosis. This study hypothesizes that the pro-inflammatory Annexin A2 (ANXA2) has role in COVID-19 pathogenesis. In thisobservational study, serum levels of ANXA2 along with interleukin 1 beta (IL1ß), IL6, tumour necrosis factor-alpha (TNFα), and anti-inflammatory ANXA1 were determined by sandwich ELISA in 20 each control, mild, moderate, and severe COVID-19 subjects.The ANXA2 levels (130 ng/mL, p < 0.001) were significantly elevated in severe COVID-19 subjects, compared to mild, moderate and controls. Similarly, all the other pro-inflammatory biomarkers levels were also significantly correlated with disease severity (p < 0.0001). However, ANXA1 showed significantly negative correlation with disease severity (p < 0.0001). Furthermore, the pro-inflammatory ANXA2 showed utility in mortality prediction with 86% sensitivity and specificity, and 57% positive predictive value at a serum threshold of 94 ng/mL. Overall,ANXA2 and ANXA1 along with IL1ß, IL6, TNFα, would be beneficial biomarkers in assessing the COVID-19 severity and mortality prediction.

Integrated molecular-network analysis reveals infertility-associated key genes and transcription factors in the non-obstructive azoospermia.

BACKGROUND: Male infertility is a multifactorial reproductive health problem with complex causes. Non-obstructive azoospermia (NOA) is characterized by failure of spermatogenesis, leading to the absence of spermatozoa in ejaculates. The molecular mechanism underlying the NOA is still not well understood. OBJECTIVES: This study aims to identify the key genes involved in male infertility that could be a potential biomarker in the diagnosis and prognosis of azoospermia. STUDY DESIGN: The microarray expression profiles dataset GSE45885 and GSE45887 were downloaded from the NCBI's Gene Expression Omnibus (GEO) database and analyzed for male infertility-associated differentially expressed genes (DEGs) using the GEO2R tool. The common DEGs between the two datasets were combined and their protein-protein interaction (PPI) network was constructed using Cytoscape to reveal the hub genes by topology and module analysis. In addition, transcription factors (TFs) and protein kinases regulating the hub genes were identified using the X2K tool. Then, the expression of the hub genes was validated by analyzing the GSE190752 microarray dataset. Further, the PPI network was screened for biological roles and enriched pathways using DAVID software. RESULTS: About 256 DEGs associated with NOA were identified and constructed the PPI network to find the infertility-associated proteins. The biological processes linked with these proteins were spermatogenesis, cell differentiation, flagellated sperm motility, and spermatid development. The topology and module analysis of the infertility-associated protein network identified the hub genes TEX38, FAM71F, PRR30, FAM166A, LYZL6, TPPP2, ARMC12, SPACA4, and FAM205A, which were found to be upregulated in the non-obstructive azoospermia. In addition, a total of 23 transcription factors and 3 protein kinases that are regulating these key hub genes were identified. Further these hub genes expression was validated using the microarray data and found that their expression was increased in the testicular biopsies obtained from NOA subjects, compared to healthy individuals. CONCLUSION: The identified key genes and its associated transcription factors are known to regulate the infertility-related processes in the non-obstructive azoospermia. Also, the clinical sample-based microarray data validation for the expression of these key hub genes indicates their potentiality to develop them as diagnostic or prognostic biomarkers for NOA.

Exploring breast cancer exosomes for novel biomarkers of potential diagnostic and prognostic importance.

The comprehensive bioinformatics analysis of breast cancer exosomes revealed that HSP90AA1, CCT2, and ENO1 were novel hub genes in the giant protein-protein interaction network of 110 exosomal proteins. Exosomes and their cargo such as discrete proteins, nucleic acids, and lipids are having potential role in the pathophysiology of breast cancer (BC). This study showed that the identified hub genes were particularly abundant in GO and KEGG pathways relevant to the positive regulation of telomerase. In addition, these hub genes were found to be considerably overexpressed in breast adenocarcinoma patients compared to healthy controls, and further, this overexpression is linked to the poor prognosis in BC patients. Furthermore, the ROC analysis revealed that CCT2 gene has strong diagnostic and prognostic value for BC. Additionally, this in silico analysis found that the anticancer agents and HSP90 inhibitors such as ganetespib, retaspimycin, and tanespimycin would have considerable potential in the treatment of BC. Overall, this study findings imply that HSP90AA1, a molecular chaperon and CCT2, a chaperonin would serve as diagnostic and prognostic biomarkers, respectively, for BC. However, these findings need to be further confirmed by laboratory and clinical studies for validating their potential applications. Supplementary Information: The online version contains supplementary material available at 10.1007/s13205-022-03422-w.