Review Untangles Cancer's Growing Web of Biomarkers

A review published in Current Cell Science pulls together the science behind BRCA1, PSA, KRAS, and other biomarkers now used to detect cancer earlier and track how well treatment is working. The review, “Role of Cancer Biomarkers Trend in Cancer Diagnosis and Therapeutics: A Review,” was authored by Anukrati Agnihotri, Najish Parveen, Hasmatullah, and Md Nematullah.

Cancer remains one of the leading causes of death worldwide, and part of what makes it so difficult to manage is its diversity—more than 100 distinct types can arise depending on which tissue or organ is affected. The review takes stock of one of the most important tools researchers and clinicians rely on to make sense of that complexity: cancer biomarkers.

The review organizes biomarkers along several lines. They can be grouped by molecular type, such as proteins (including enzymes and receptors), nucleic acids like microRNAs, antibodies, and peptides. They can also be grouped by the cancer they are associated with—for example, BRCA1 for breast and ovarian cancer, KRAS for colorectal cancer, CA125 for ovarian cancer, AFP and PIVKA-II for liver cancer, and PSA for prostate cancer. A third way to categorize biomarkers is by detection method, including liquid biopsy, imaging, or biosensor-based platforms such as aptasensors and immunosensors. Together, these categories give researchers and clinicians a structured framework for thinking about how biomarkers support diagnosis, prognosis, and monitoring of treatment response.

Some of the biomarkers covered will be recognizable outside specialist circles. BRCA1, widely known for its link to inherited breast and ovarian cancer risk, is one example the authors highlight. PSA is described as a commonly used screening tool for prostate cancer. KRAS is discussed as a prognostic marker in colorectal cancer, while HER2 overexpression is tied to both gastric and breast cancers. Each marker plays a different role in the patient journey, from estimating risk before disease develops to guiding treatment decisions after diagnosis.

The review also covers the laboratory methods behind biomarker discovery, including high-throughput sequencing, proteomic techniques such as mass spectrometry, LC-MS/MS, and MALDI-MS, and gene expression arrays, which let researchers compare samples and pinpoint molecules that differ between healthy and cancerous tissue. Biosensors are described as a particularly active area of development, classified as immunosensors, aptasensors, enzymatic biosensors, or nucleic acid biosensors depending on the biological component used to recognize their target. 

The review’s contribution is synthesis: organizing a fast-moving, fragmented field into a single picture of how biomarkers are classified, discovered, and applied across cancer types and detection technologies.