Analytical Techniques as Indicators of Biomarkers in Proteomics Cancer Diagnosis.

Background: Cancer is a complex disease marked by changes in the levels and functions of key cellular proteins, including oncogenes and tumor suppressors. Proteomics technology enables the identification of crucial protein targets and signaling pathways involved in cancer cell proliferation and metastasis. Various proteomics techniques have been employed to investigate the molecular mechanisms of cancer, aiding in the confirmation and characterization of heritable disorders.

Method: A comprehensive literature search was conducted using PubMed, ScienceDirect, and Google Scholar with search terms like "Cancer and proteomics" and "Mass spectrometry in oncology," utilizing Boolean operators for refinement. Selection criteria included peer-reviewed articles in English on MS-based biomarker detection, tumor-specific proteins, and drug resistance markers, excluding non-peer-reviewed works and pre-2000 publications unless foundational. Extracted data focused on MS methodologies, biomarker sensitivity, and clinical applications, particularly advances in detecting low-abundance biomarkers and monitoring treatment response. Methodological quality was assessed using PRISMA, evaluating study design, sample size, reproducibility, and statistical analysis. Ethical approval was not required, but adherence to systematic review guidelines and proper citation were ensured.

Result: In this review, we highlighted the advanced analytical technique for cancer diagnosis and management of cancer, and described the objective of novel cancer biomarkers. Mass spectrometry (MS) is transforming cancer diagnostics and personalized medicine by enabling precise biomarker detection and monitoring. Unlike traditional antibody-based methods, MS provides high-throughput, quantitative analysis of tumor-specific proteins in clinical samples like blood and tissue. Advanced MS techniques improve sensitivity, allowing for the identification of low-abundance biomarkers and tumor-associated proteoforms, including post-translational modifications and drug resistance markers. In research, MS-based proteomics supports multi-center biomarker validation studies with standardized protocols, enhancing reproducibility. The integration of proteomic data with genomic and transcriptomic datasets through proteogenomics is refining precision oncology strategies. These advancements are bridging the gap between research and clinical application, making MS a critical tool for early cancer detection, prognosis, and therapy selection.

Conclusion: Advancements in technology and analytical techniques have helped to produce more accurate and sensitive cancer-specific biomarkers. These methods are advancing rapidly, and developing high-throughput platforms has yielded great results. However, The substantial variation in protein concentrations makes cancer protein profiling extremely complicated. This shows that more technical developments are required in the future to improve proteome broad screening of cancer cells.