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Biomarker candidates for tumours identified from deep-profiled plasma stem predominantly from the low abundant area

ABSTRACT: The plasma proteome has the potential to enable a holistic analysis of the health state of an individual. However, plasma biomarker discovery is difficult due to its high dynamic range and variability. Here, we present a novel automated analytical approach for deep plasma profiling and applied it to a 180-sample cohort of human plasma from lung, breast, colorectal, pancreatic, and prostate cancer. Using a controlled quantitative experiment, we demonstrate a 257% increase in protein identification and a 263% increase in significantly differentially abundant proteins over neat plasma. In the cohort, we identified 2732 proteins. Using machine learning, we discovered biomarker candidates such as STAT3 in colorectal cancer and developed models that classify the disease state. For pancreatic cancer, a separation by stage was achieved. Importantly, biomarker candidates came predominantly from the low abundance region, demonstrating the necessity to deeply profile because they would have been missed by shallow profiling.

INSTRUMENT(S): Orbitrap Exploris 480

ORGANISM(S): Escherichia Coli (ncbitaxon:562) Saccharomyces Cerevisiae (ncbitaxon:4932) Homo Sapiens (ncbitaxon:9606)

SUBMITTER: Lukas Reiter

PROVIDER: MSV000088180 | MassIVE | Fri Oct 01 14:14:00 BST 2021

REPOSITORIES: MassIVE

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