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.

Next-generation sequencing (NGS) has revolutionized personalized oncology care by providing exceptional insights into the complex genomic landscape. NGS offers comprehensive cancer profiling, which enables clinicians and researchers to better understand the molecular basis of cancer and to tailor treatment strategies accordingly. Targeted therapies based on genomic alterations identified through NGS have shown promise in improving patient outcomes across various cancer types, circumventing resistance mechanisms and enhancing treatment efficacy. Moreover, NGS facilitates the identification of predictive biomarkers and prognostic indicators, aiding in patient stratification and personalized treatment approaches. By uncovering driver mutations and actionable alterations, NGS empowers clinicians to make informed decisions regarding treatment selection and patient management. However, the full potential of NGS in personalized oncology can only be realized through bioinformatics analyses. Bioinformatics plays a crucial role in processing raw sequencing data, identifying clinically relevant variants, and interpreting complex genomic landscapes. This comprehensive review investigates the diverse NGS techniques, including whole-genome sequencing (WGS), whole-exome sequencing (WES), and single-cell RNA sequencing (sc-RNA-Seq), elucidating their roles in understanding the complex genomic/transcriptomic landscape of cancer. Furthermore, the review explores the integration of NGS data with bioinformatics tools to facilitate personalized oncology approaches, from understanding tumor heterogeneity to identifying driver mutations and predicting therapeutic responses. Challenges and future directions in NGS-based cancer research are also discussed, underscoring the transformative impact of these technologies on cancer diagnosis, management, and treatment strategies.

Copy number alterations (CNAs) are significant in tumor initiation and progression. Identifying these aberrations is crucial for targeted therapies and personalized cancer diagnostics. Next-generation sequencing (NGS) methods present advantages in scalability and cost-effectiveness, surpassing limitations associated with reference assemblies and probe capacities in traditional laboratory approaches. This retrospective study evaluated CNAs in 50 FFPE tumor samples (breast cancer, ovarian carcinoma, pancreatic cancer, melanoma, and prostate carcinoma) using Illumina’s TruSight Oncology 500 (TSO500) and the Affymetrix Oncoscan Molecular Inversion Probe (OS-MIP) (ThermoFisher Scientific, Waltham, MA, USA). NGS analysis with the NxClinical 6.2 software demonstrated a high sensitivity and specificity (100%) for CNA detection, with a complete concordance rate as compared to the OS-MIP. All 54 known CNAs were identified by NGS, with gains being the most prevalent (63%). Notable CNAs were observed in MYC (18%), TP53 (12%), BRAF (8%), PIK3CA, EGFR, and FGFR1 (6%) genes. The diagnostic parameters exhibited high accuracy, including a positive predictive value, negative predictive value, and overall diagnostic accuracy. This study underscores NxClinical as a reliable software for identifying clinically relevant gene alterations using NGS TSO500, offering valuable insights for personalized cancer treatment strategies based on CNA analysis.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the causative agent of coronavirus disease (COVID-19), induced a global pandemic with a diverse array of clinical manifestations. While the acute phase of the pandemic may be waning, the intricacies of COVID-19′s impact on neurological health remain a crucial area of investigation. Early recognition of the spectrum of COVID-19 symptoms, ranging from mild fever and cough to life-threatening respiratory distress and multi-organ failure, underscored the significance of neurological complications, including anosmia, seizures, stroke, disorientation, encephalopathy, and paralysis. Notably, patients requiring intensive care unit (ICU) admission due to neurological challenges or due to them exhibiting neurological abnormalities in the ICU have shown increased mortality rates. COVID-19 can lead to a range of neurological complications such as anosmia, stroke, paralysis, cranial nerve deficits, encephalopathy, delirium, meningitis, seizures, etc., in affected patients. This review elucidates the burgeoning landscape of neurological sequelae associated with SARS-CoV-2 infection and explores the underlying neurobiological mechanisms driving these diverse manifestations. A meticulous examination of potential neuroinvasion routes by SARS-CoV-2 underscores the intricate interplay between the virus and the nervous system. Moreover, we dissect the diverse neurological manifestations emphasizing the necessity of a multifaceted approach to understanding the disease’s neurological footprint. In addition to elucidating the pathophysiological underpinnings, this review surveys current therapeutic modalities and delineates prospective avenues for neuro-COVID research. By integrating epidemiological, clinical, and diagnostic parameters, we endeavor to foster a comprehensive analysis of the nexus between COVID-19 and neurological health, thereby laying the groundwork for targeted therapeutic interventions and long-term management strategies.

Circulating tumor cells (CTCs) are shed from the primary tumor into the bloodstream and represent dynamic molecular biomarkers for monitoring the progression of cancer. While profiling tumor tissues with over expression of cell surface markers, such as PD-L1 or HER2, is standard in guiding therapy, tissue samples are often inaccessible and inadequate, especially post-surgery or in cases of recurrence. Emerging clinical evidence indicates that CTC counts and biomarker surface expression can predict prognosis and therapeutic resistance more accurately than imaging or tissue-based approaches. Recent advancements in the CTC detection methods, based on physical properties or surface markers (e.g., EpCAM), coupled with next-generation sequencing (NGS) have enabled the isolation of these rare cells and their molecular characterization. Consequently, CTCs provide a real-time alternative, enabling repeated, longitudinal assessment of tumor phenotype and therapeutic response. This review emphasizes the translational potential of surface protein biomarkers on CTCs for profiling, namely PD-L1, HER2, and EGFR, as a clinically actionable approach to stratify patients, guide immunotherapy decisions, and monitor minimal residual disease (MRD), especially when longitudinal tissue biopsies are not feasible.

A glioma is a solid brain tumor which originates in the brain or brain stem area. The diagnosis of gliomas based on standard-of-care (SOC) techniques includes karyotyping, fluorescence in situ hybridization (FISH), and chromosomal microarray (CMA), for detecting the pathogenic variants and chromosomal abnormalities. But these techniques do not reveal the complete picture of genetic complexity, thus requiring an alternative technology for better characterization of these tumors. The present study aimed to evaluate the clinical performance and feasibility of using optical genome mapping (OGM) for chromosomal characterization of gliomas. Herein, we evaluated 10 cases of gliomas that were previously characterized by CMA. OGM analysis showed concordance with the results of CMA in identifying the characterized Structural Variants (SVs) in these cases. More notably, it also revealed additional clinically relevant aberrations, demonstrating a higher resolution and sensitivity. These clinically relevant SVs included cryptic translocation, and SVs which are beyond the detection capabilities of CMA. Our analysis highlights the unique capability of OGM to detect all classes of SVs within a single assay, thereby unveiling clinically significant data with a shorter turnaround time. Adopting this diagnostic tool as a standard of care for solid tumors like gliomas shows potential for improving therapeutic management, potentially leading to more personalized and timely interventions for patients.