Simple SummaryVarious studies and techniques have been designed to discover biofluid-derived biomarkers for non-invasive early detection and prognosis of cancers. Despite the importance of non-invasive biomarker discovery in cancer diagnosis and management, the reported markers are often inconsistent and irreproducible across different studies and cohorts. In this article, we reviewed the ongoing trend of non-nucleotide biomarkers, including lipidomics, proteomics and metabolomics, derived from body fluids, with a focus on breast cancer, and reviewed the inconstancies in the biomarker discovery pipelines across pre-analytical, analytical, and post-analytical phases, covering the diversity of approaches from sample processing to predictive modelling and validation.AbstractBreast cancer has now become the most commonly diagnosed cancer, accounting for one in eight cancer diagnoses worldwide. Non-invasive diagnostic biomarkers and associated tests are superlative candidates to complement or improve current approaches for screening, early diagnosis, or prognosis of breast cancer. Biomarkers detected from body fluids such as blood (serum/plasma), urine, saliva, nipple aspiration fluid, and tears can detect breast cancer at its early stages in a minimally invasive way. The advancements in high-throughput molecular profiling (omics) technologies have opened an unprecedented opportunity for unbiased biomarker detection. However, the irreproducibility of biomarkers and discrepancies of reported markers have remained a major roadblock to clinical implementation, demanding the investigation of contributing factors and the development of standardised biomarker discovery pipelines. A typical biomarker discovery workflow includes pre-analytical, analytical, and post-analytical phases, from sample collection to model development. Variations introduced during these steps impact the data quality and the reproducibility of the findings. Here, we present a comprehensive review of methodological variations in biomarker discovery studies in breast cancer, with a focus on non-nucleotide biomarkers (i.e., proteins, lipids, and metabolites), highlighting the pre-analytical to post-analytical variables, which may affect the accurate identification of biomarkers from body fluids.