This review discusses the current testing methodologies for COVID-19 diagnosis and explores next-generation sequencing (NGS) technology for the detection of SARS-CoV-2 and monitoring phylogenetic evolution in the current COVID-19 pandemic. The review addresses the development, fundamentals, assay quality control and bioinformatics processing of the NGS data. This article provides a comprehensive review of the obstacles and opportunities facing the application of NGS technologies for the diagnosis, surveillance, and study of SARS-CoV-2 and other infectious diseases. Further, we have contemplated the opportunities and challenges inherent in the adoption of NGS technology as a diagnostic test with real-world examples of its utility in the fight against COVID-19.

Emerging infectious diseases (EIDs) pose an increasingly significant global burden, driven by urbanization, population explosion, global travel, changes in human behavior, and inadequate public health systems. The recent SARS-CoV-2 pandemic highlights the urgent need for innovative and robust technologies to effectively monitor newly emerging pathogens. Rapid identification, epidemiological surveillance, and transmission mitigation are crucial challenges for ensuring public health safety. Genomics has emerged as a pivotal tool in public health during pandemics, enabling the diagnosis, management, and prediction of infections, as well as the analysis and identification of cross-species interactions and the categorization of infectious agents. Recent advancements in high-throughput DNA sequencing tools have facilitated rapid and precise identification and characterization of emerging pathogens. This review article provides insights into the latest advances in various genomic techniques for pathogen detection and tracking and their applications in global outbreak surveillance. We assess methods that leverage pathogen sequences and explore the role of genomic analysis in understanding the epidemiology of newly emerged infectious diseases. Additionally, we address technical challenges and limitations, ethical and legal considerations, and highlight opportunities for integrating genomics with other surveillance approaches. By delving into the prospects and obstacles of genomics, we can gain valuable insights into its role in mitigating the threats posed by emerging pathogens and improving global preparedness in the face of future outbreaks.

Colorectal cancer (CRC) is a high burden disease with several genes involved in tumor progression. The aim of the present study was to identify, generate and clinically validate a novel gene signature to improve prediction of overall survival (OS) to effectively manage colorectal cancer. We explored The Cancer Genome Atlas (TCGA), COAD and READ datasets (597 samples) from The Protein Atlas (TPA) database to extract a total of 595 candidate genes. In parallel, we identified 29 genes with perturbations in > 6 cancers which are also affected in CRC. These genes were entered in cBioportal to generate a 17 gene panel with highest perturbations. For clinical validation, this gene panel was tested on the FFPE tissues of colorectal cancer patients (88 patients) using Nanostring analysis. Using multivariate analysis, a high prognostic score (composite 4 gene signature—DPP7/2, YWHAB, MCM4 and FBXO46) was found to be a significant predictor of poor prognosis in CRC patients (HR: 3.42, 95% CI: 1.71–7.94, p < 0.001 *) along with stage (HR: 4.56, 95% CI: 1.35–19.15, p = 0.01 *). The Kaplan-Meier analysis also segregated patients on the basis of prognostic score (log-rank test, p = 0.001 *). The external validation using GEO dataset (GSE38832, 122 patients) corroborated the prognostic score (HR: 2.7, 95% CI: 1.99–3.73, p < 0.001 *). Additionally, higher score was able to differentiate stage II and III patients (130 patients) on the basis of OS (HR: 2.5, 95% CI: 1.78–3.63, p < 0.001 *). Overall, our results identify a novel 4 gene prognostic signature that has clinical utility in colorectal cancer.

Lung cancer is one of the leading causes of death worldwide. Cell death pathways such as autophagy, apoptosis, and necrosis can provide useful clinical and immunological insights that can assist in the design of personalized therapeutics. In this study, variations in the expression of genes involved in cell death pathways and resulting infiltration of immune cells were explored in lung adenocarcinoma (The Cancer Genome Atlas: TCGA, lung adenocarcinoma (LUAD), 510 patients). Firstly, genes involved in autophagy (n = 34 genes), apoptosis (n = 66 genes), and necrosis (n = 32 genes) were analyzed to assess the prognostic significance in lung cancer. The significant genes were used to develop the cell death index (CDI) of 21 genes which clustered patients based on high risk (high CDI) and low risk (low CDI). The survival analysis using the Kaplan–Meier curve differentiated patients based on overall survival (40.4 months vs. 76.2 months), progression-free survival (26.2 months vs. 48.6 months), and disease-free survival (62.2 months vs. 158.2 months) (Log-rank test, p < 0.01). Cox proportional hazard model significantly associated patients in high CDI group with a higher risk of mortality (Hazard Ratio: H.R 1.75, 95% CI: 1.28–2.45, p < 0.001). Differential gene expression analysis using principal component analysis (PCA) identified genes with the highest fold change forming distinct clusters. To analyze the immune parameters in two risk groups, cytokines expression (n = 265 genes) analysis revealed the highest association of IL-15RA and IL 15 (> 1.5-fold, p < 0.01) with the high-risk group. The microenvironment cell-population (MCP)-counter algorithm identified the higher infiltration of CD8+ T cells, macrophages, and lower infiltration of neutrophils with the high-risk group. Interestingly, this group also showed a higher expression of immune checkpoint molecules CD-274 (PD-L1), CTLA-4, and T cell exhaustion genes (HAVCR2, TIGIT, LAG3, PDCD1, CXCL13, and LYN) (p < 0.01). Furthermore, functional enrichment analysis identified significant perturbations in immune pathways in the higher risk group. This study highlights the presence of an immunocompromised microenvironment indicated by the higher infiltration of cytotoxic T cells along with the presence of checkpoint molecules and T cell exhaustion genes. These patients at higher risk might be more suitable to benefit from PD-L1 blockade or other checkpoint blockade immunotherapies.

Women are at a significantly higher risk of developing osteoarthritis (OA) compared to males. The pathogenesis of osteoarthritis (OA) in women is poorly understood. Extracellular vesicles (EVs) have been shown to play an essential role in numerous signaling processes during the pathogenesis of age-related diseases via paracrine signaling. Molecular profiling of the synovial fluid-derived EVs cargo in women may help in the discovery of novel biomarkers and therapeutics for the treatment of OA in women. Previously, we reported that synovial fluid-derived EV miRNA cargo differs in a sex-specific manner. This study aims to characterize synovial fluid-derived EV protein cargo in OA patients. Our data showed sex-specific EVs protein content in OA. We found haptoglobin, orosomucoid, and ceruloplasmin significantly up-regulated, whereas apolipoprotein down-regulated in female OA EVs. In males, we discovered β-2-glycoprotein, and complement component 5 proteins significantly up-regulated and Spt-Ada-Gcn5 acetyltransferase (SAGA)-associated factor 29 down-regulated in male OA EVs. Database for Annotation, Visualization, and Integrated Discovery (DAVID) and QuickGO analysis revealed OA-specific protein involvement in several biological, molecular, and cellular pathways, specifically in inflammatory processes. In conclusion, synovial fluid EV protein content is altered in a sex-specific manner with OA, explaining the increased prevalence and severity of OA in women.

Non-small cell lung cancer (NSCLC) is a major subtype of lung cancer that accounts for almost 85% of lung cancer cases worldwide. Although recent advances in chemotherapy, radiotherapy, and immunotherapy have helped in the clinical management of these patients, the survival rate in advanced stages remains dismal. Furthermore, there is a critical lack of accurate prognostic and stratification markers for emerging immunotherapies. To harness immune response modalities for therapeutic benefits, a detailed understanding of the immune cells in the complex tumor microenvironment (TME) is required. Among the diverse immune cells, natural killer (NK cells) and dendritic cells (DCs) have generated tremendous interest in the scientific community. NK cells play a critical role in tumor immunosurveillance by directly killing malignant cells. DCs link innate and adaptive immune systems by cross-presenting the antigens to T cells. The presence of an immunosuppressive milieu in tumors can lead to inactivation and poor functioning of NK cells and DCs, which results in an adverse outcome for many cancer patients, including those with NSCLC. Recently, clinical intervention using modified NK cells and DCs have shown encouraging response in advanced NSCLC patients. Herein, we will discuss prognostic and predictive aspects of NK cells and DC cells with an emphasis on NSCLC. Additionally, the discussion will extend to potential strategies that seek to enhance the anti-tumor functionality of NK cells and DCs.