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Inoviem has developed a sensitive and accurate proteomic methodology for the proteomic profiling of human individuals in the context of translational evaluation of biomarkers and clinical development of new drug candidates. The methodology works with both human frozen whole blood and any other matrixes including plasma/sera, urine, sputum etc.
The workflow of MS-based proteomics experiments includes the following steps: experimental design, sampling, tissue/cell preparation, protein extraction, separation, MS analysis, protein identification, statistical analysis of data, validation of identification, quantification, and data analysis. The experimental design is detailed in a table, which is submitted for approval.
This methodology has the great potential of analyzing frozen whole blood for biomarkers discovery by extracting hemoglobin. Haemoglobin indeed poses a significant challenge in whole blood proteomic analysis due to its high abundance and potential to interfere with the detection of other proteins. Inoviem developed a label free, non-chromatography-based methodology to extract the haemoglobin and to elute the proteins bound to albumin.
Iron ions (Fe2+) are replaced by Mn2+ and Mg2+ with gradually increasing saline forces. This will precipitate free hemoglobin and induce hemagglutination.
Stepwise change in ionic forces from neutral to acid between with pH interval 4 to 6.
Separation as well as isolation of hydrophobic and hydrophilic proteins using proprietary three phases gradient. Each phase is analyzed thereafter in triplicate.
Filtration on SDS-PAGE gradient gel, isolation of proteins and proceed to proteomics.
Each fractioned phase is sequenced via label-free quantitative proteomics (LC-MS/MS) and the proteins are analyzed both quantitatively and qualitatively.
This method identifies an average of 710 proteins per blood sample, outperforming other depletion and fractionation methods available on the market, which typically rely on labelling and conjugation chemistry approaches.
Label free proteomics analysis reveals many proteins that can be easily sorted and ranked by Inoviem’s InOpera database, able to discriminate between frequent and specific proteins within the dataset. This opens the possibility to perform pathway enrichment analysis aiming to the identification of modulated pathways related to disease features (e.g. progression rate, stage) or to treatment response (e.g. response/non-response related pathways) leading to the identification of potential biomarkers candidates.
Each fractioned blood sample undergoes to label-free quantification in order to get an exhaustive proteomic signature of each patient.
Analyses are based on two steps:
These types of analyses can reveal modulated proteins based on patient’s group therefore revealing potential biomarkers candidates. With this methodology we can get the following types of biomarkers:
