From Cancer Screening to Targeted Therapy: Clinical Applications and Validation Challenges of Biomarker Technologies
Background
A review of cancer biomarker technologies and their clinical applications identifies standardization, ethics, and equitable access as major challenges for precision medicine. Published in Advances in Cancer Research, the paper reviews molecular information used in cancer screening, diagnosis, and treatment selection, along with future directions, rather than reporting experimental results from a new diagnostic platform.
The authors describe the expansion from histology-based cancer classification toward biomarker-based precision medicine. Key areas of analysis include genomic, transcriptomic, proteomic, metabolomic, and epigenetic changes. The aim is to use this information for early cancer detection, prognostic assessment, and treatment selection tailored to individual patients. Although these approaches share the goal of examining different molecular layers, the abstract alone does not establish how accurately each test performs in specific patient groups.
Key findings
The main analytical technologies covered are next-generation sequencing (NGS), mass spectrometry, and polymerase chain reaction (PCR)-based methods. The authors describe their detection targets as ranging from single-nucleotide variants to proteome-wide profiles. This is an overview of the roles and applications of several analytical methods; it does not report the performance of a single instrument combining all three technologies or of a system measuring every molecular layer at the same resolution.
Clinical examples include epidermal growth factor receptor (EGFR) inhibitors for lung cancer and poly(ADP-ribose) polymerase (PARP) inhibitors for cancers with BRCA mutations. These are existing examples of linking molecular features to treatment selection. There is no basis for interpreting them as clinical validation results for an analytical framework developed in this review.
The review also discusses challenges to broader biomarker use. The authors emphasize standardization of the validation process, ethical issues, and equitable access to benefits. Technologies that sensitively detect molecular signals and the process of establishing evidence for their use in patient care should be evaluated separately. The provided abstract does not give the sensitivity or specificity of individual tests, patient numbers, comparison groups, follow-up periods, or treatment effect sizes. Consequently, the available material does not support quantitative comparisons of the relative merits of these technologies or their benefits for patients.
Implications and outlook
Single-cell sequencing, CRISPR-based diagnostics, and artificial intelligence (AI) are presented as technologies with potential for further development. The authors envision these technologies helping to characterize tumor heterogeneity—the diverse molecular features of tumors—and supporting sensitive detection and integration of multi-omics data. The abstract describes these possibilities but does not present new results demonstrating resistance prediction or the performance of an integrated analysis system.
The long-term direction is to combine information across molecular layers into comprehensive, dynamic profiles that reflect changes in individual tumors. Real-time monitoring using liquid biopsy and point-of-care diagnostic devices is also mentioned as a future application. This represents a development direction for biomarker analysis, rather than an achievement that has already replaced diagnostic standards.
This article is based on indexed bibliographic information and the abstract. The full text and the individual studies cited were not available, so specific test performance and conditions for clinical application cannot be assessed. Connecting the potential of these technologies to patient care requires consideration of the validation, standardization, ethics, and access challenges emphasized by the review. Source: Review of biomarkers in cancer screening, diagnosis, and targeted therapy.
Oncology & Molecular Diagnostics Core, Published May 2026. DOI: [Source Generated Data]
Summary: Resolving the diagnostic resolution bottlenecks imposed by traditional tissue histology, this comprehensive white paper outlines the paradigms of multi-omic biomarker engineering. By pairing high-throughput next-generation sequencing (NGS) and mass spectrometry with single-cell genomics, the integrated framework traces heritable genomic, transcriptomic, and proteomic alteration trajectories across highly heterogeneous tumor microenvironments. Clinically validated through the strategic deployment of EGFR and PARP inhibitors, the architecture synthesizes diverse molecular layers into a dynamic, real-time analytics matrix. Leveraging CRISPR-based point-of-care sub-modules and artificial intelligence fusion neural networks, the data yields a non-invasive liquid biopsy baseline optimized for ultra-sensitive pre-symptomatic detection and predictive therapeutic stratification.
This review may help biomarker researchers consider the intended uses of analytical technologies alongside the challenges of clinical validation. EGFR inhibitors for lung cancer and PARP inhibitors for cancers with BRCA mutations are presented as existing examples of using molecular features to guide treatment selection. When planning the development of approaches that repeatedly monitor tumor changes using liquid biopsy or point-of-care diagnostics, the review could provide a starting point for considering standardization, ethics, and access alongside the goal of integrating multiple types of molecular information. This is a scenario for drawing on the review’s outlook in development planning; it does not mean that the approach has demonstrated clinical effectiveness. The abstract alone cannot support a recommendation to adopt a particular test or change treatment, and there is no basis for presenting improved survival or shorter approval timelines as established outcomes.