Biomarker Reproducibility Challenge: A Review of Non-Nucleotide Biomarker Discovery Protocols from Body Fluids in Breast Cancer Diagnosis.

Breast 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.

Investigation of Plasma-Derived Lipidome Profiles in Experimental Cerebral Malaria in a Mouse Model Study.

Cerebral malaria (CM), a fatal complication of Plasmodium infection that affects children, especially under the age of five, in sub-Saharan Africa and adults in South-East Asia, results from incompletely understood pathogenetic mechanisms. Increased release of circulating miRNA, proteins, lipids and extracellular vesicles has been found in CM patients and experimental mouse models. We compared lipid profiles derived from the plasma of CBA mice infected with Plasmodium berghei ANKA (PbA), which causes CM, to those from Plasmodium yoelii (Py), which does not. We previously showed that platelet-free plasma (18k fractions enriched from plasma) contains a high number of extracellular vesicles (EVs). Here, we found that this fraction produced at the time of CM differed dramatically from those of non-CM mice, despite identical levels of parasitaemia. Using high-resolution liquid chromatography-mass spectrometry (LCMS), we identified over 300 lipid species within 12 lipid classes. We identified 45 and 75 lipid species, mostly including glycerolipids and phospholipids, with significantly altered concentrations in PbA-infected mice compared to Py-infected and uninfected mice, respectively. Total lysophosphatidylethanolamine (LPE) levels were significantly lower in PbA infection compared to Py infection and controls. These results suggest that experimental CM could be characterised by specific changes in the lipid composition of the 18k fraction containing circulating EVs and can be considered an appropriate model to study the role of lipids in the pathophysiology of CM.