Systematic Review on the Application of Molecular Biology Techniques in Early Detection and Targeted Therapy of Human Diseases

Abstract

Background: The integration of molecular biology techniques into clinical medicine represents a paradigm shift towards precision healthcare. While these methods hold immense promise for the early detection of disease and the guidance of targeted therapies, the evidence remains fragmented across various specialties and technological platforms, necessitating a consolidated, critical appraisal. Objective This systematic review aimed to evaluate the role of molecular biology methods in improving diagnostic accuracy and therapeutic strategies for human diseases, focusing on their application in early detection and targeted therapy. Methods A systematic review was conducted following PRISMA guidelines. Comprehensive searches of PubMed, Scopus, Web of Science, and the Cochrane Library were performed for studies published between 2014 and 2023. Inclusion criteria encompassed primary studies (randomized controlled trials, cohort studies, diagnostic accuracy studies) evaluating molecular techniques for early detection or therapy guidance in human diseases. Two independent reviewers performed study selection, data extraction, and risk-of-bias assessment using standardized tools. Results Eight studies were included in the qualitative synthesis. The findings demonstrate that molecular techniques, such as circulating tumor DNA analysis and next-generation sequencing, can detect cancer recurrence with a lead time of several months before clinical relapse and significantly improve patient outcomes when used to guide targeted therapies. For instance, molecular stratification for PD-L1 expression in non-small cell lung cancer and for homologous recombination deficiency in ovarian cancer was associated with significantly improved survival (Hazard Ratios of 0.69 and 0.33, respectively). Conclusion Molecular biology techniques provide a substantial advantage for early disease detection and personalized treatment selection, directly translating to improved clinical outcomes. However, evidence heterogeneity and potential publication bias highlight the need for standardized, large-scale prospective studies to confirm efficacy across diverse populations and healthcare settings, and to establish cost-effectiveness.