The timeline for the development and discovery of biomarkers for early cancer diagnosis reveals a complex and ongoing process (Figure ). It involves many years of research, clinical trials, and validation studies. In 1948, the existence of cell free DNA was first observed. Cell free DNAs are derived from necrotic and apoptotic cells, commonly released by all cell types. Further, numerous subsequent studies confirmed that the tumor-specific pattern of alterations, such as chromosomal abnormality, somatic mutations, resistance mutation, aberrant methylation and copy number variations could be found in cfDNA, which can serve as potential target for diagnosis of cancer through non-invasive approach. The pursuit for noninvasive biomarkers appropriate for early cancer detection started in the 1970s and 1980s when certain so-called "cancer antigens" were discovered by introducing human cancer tissues into lab animals and testing the animal serum for antibodies against the human antigens in the extract. The first clinically applicable cancer biomarker identified this way in 1965 was cancer embryonic antigen (CEA) in colon cancer tissue , and by the end of the 1970s, potential serum tests had been developed for a variety of cancers. Additional biomarkers developed in the 1980s included prostate-specific antigen (PSA), alpha-fetoprotein (AFP), cancer antigens 19-9 (CA19-9), 72-4 (CA72.4), 125 (CA125), and 15-3 (CA 15-3). The development of monoclonal antibodies and immunoassays later on revolutionized biomarker research. This allowed for the detection of specific proteins associated with cancer. CEA became a widely used biomarker for monitoring cancer progression and treatment response. Advances in molecular biology and genetics led to the identification of genetic markers associated with inherited cancer syndromes. The discovery of BRCA1 and BRCA2 mutations in the 1990s marked a significant milestone in hereditary breast and ovarian cancer risk assessment. Genomic technologies like DNA microarrays and high-throughput sequencing that have emerged in the late 1990s to early 2000s, enabled the analysis of gene expression patterns in cancer cells. This period also saw the development of proteomics, which focused on identifying cancer-related proteins and peptides. The Human Genome Project and The Cancer Genome Atlas (TCGA) project provided valuable insights into the genetic mutations and alterations associated with various cancers. Liquid biopsy techniques began to gain attention for their potential to detect circulating tumor DNA (ctDNA) and other biomarkers in blood samples, providing safe, accurate, non-invasive, and dynamic tracking of disease progression. Further, advances in single-cell sequencing allowed for a deeper understanding of tumor heterogeneity and the identification of rare cancer cells. Immune-related biomarkers, such as PD-L1 expression, gained prominence with the advent of immunotherapy for cancer treatment. 82, 83 The development of artificial intelligence and machine learning algorithms accelerated the analysis of vast datasets for biomarker discovery. Ongoing research continues to focus on identifying novel early cancer biomarkers, especially those associated with rare cancers or those with poor prognosis. Efforts are made to develop minimally invasive or non-invasive methods for biomarker detection, such as through blood, urine, or breath tests. Multi-marker panels and composite biomarkers are being explored to improve diagnostic accuracy and reduce false positives. Figure . A concise timeline of key milestones and developments of biomarkers for early cancer diagnosis Biomarkers must undergo rigorous validation and testing before receiving regulatory approval for clinical use. The timeline for regulatory approval and clinical adoption can vary, and biomarkers typically go through phases of clinical trials to demonstrate their clinical utility and safety. Development and adoption of cancer biomarkers vary by cancer type and the availability of technologies and funding for research. Advancements in molecular biology, genomics, and data analysis methods continue to shape the landscape of cancer biomarker discovery.