Quantifiable peptide library bridges the gap for proteomics based biomarker discovery and validation on breast cancer.

Mass spectrometry (MS) based proteomics is widely used for biomarker discovery. However, often, most biomarker candidates from discovery are discarded during the validation processes. Such discrepancies between biomarker discovery and validation are caused by several factors, mainly due to the differences in analytical methodology and experimental conditions. Here, we generated a peptide library which allows discovery of biomarkers in the equal settings as the validation process, thereby making the transition from discovery to validation more robust and efficient. The peptide library initiated with a list of 3393 proteins detectable in the blood from public databases. For each protein, surrogate peptides favorable for detection in mass spectrometry was selected and synthesized. A total of 4683 synthesized peptides were spiked into neat serum and plasma samples to check their quantifiability in a 10 min liquid chromatography-MS/MS run time. This led to the PepQuant library, which is composed of 852 quantifiable peptides that cover 452 human blood proteins. Using the PepQuant library, we discovered 30 candidate biomarkers for breast cancer. Among the 30 candidates, nine biomarkers, FN1, VWF, PRG4, MMP9, CLU, PRDX6, PPBP, APOC1, and CHL1 were validated. By combining the quantification values of these markers, we generated a machine learning model predicting breast cancer, showing an average area under the curve of 0.9105 for the receiver operating characteristic curve.

Differential responses of B vitamins in black soybean seeds.

This study was aimed to determine the contents and the association of B vitamins from seeds of 10 black and one yellow soybean (Glycine max (L.) Merr.) varieties with either green or yellow cotyledon. Thiamine, flavin adenine dinucleotide (FAD), riboflavin and total riboflavin were found highest in 'Chengjakong', while flavin mononucleotide (FMN) was greatest in 'Mirang'. Nicotinic acid and total vitamin B3 were highest in 'Shingi' as a yellow soybean variety but pantothenic acid and pyridoxine contents were greatest in 'Tawon' and 'Mirang', respectively. These content variations of B vitamins directly reflected the wide segregation of soybean varieties on the principal component analysis (PCA) scores plot, indicating that these 4 soybean varieties appeared to be least associated with other soybean varieties based on the different responses of B vitamins. The results of cluster and correlation analyses presented that the cotyledon colour of soybean seed contributed to a variation of B vitamin contents. Overall, the results suggest that a wide range of B vitamin contents would be affected by genotypic factors alongside the difference of cotyledon colour.