Clinical applications of mass spectrometry‐based proteomics in cancer: Where are we?

Abstract

Tumor tissue processing methodologies in combination with data‐independent acquisition mass spectrometry (DIA‐MS) have emerged that can comprehensively analyze the proteome of multiple tumor samples accurately and reproducibly. Increasing recognition and adoption of these technologies has resulted in a tranche of studies providing novel insights into cancer classification systems, functional tumor biology, cancer biomarkers, treatment response and drug targets. Despite this, with some limited exceptions, MS‐based proteomics has not yet been implemented in routine cancer clinical practice. Here, we summarize the use of DIA‐MS in studies that may pave the way for future clinical cancer applications, and highlight the role of alternative MS technologies and multi‐omic strategies. We discuss limitations and challenges of studies in this field to date and propose steps for integrating proteomic data into the cancer clinic.

Proteomic Characterization of Acute Myeloid Leukemia for Precision Medicine

“…Similarly, protein expression may not correlate with their extent of activation. Protein phosphorylation is closer to protein function and can be used to infer the activities of kinases, which are enzymes that participate in the regulation of essentially all biological processes in normal and cancer cells ( 118 ). Therefore, proteomics and phosphoproteomics approaches—alone or integrated with genomics and transcriptomics—provide new mechanistic insights into disease pathogenesis from which to identify drug targets and biomarkers of drug response, to be used as input of predictive models, and to rationalize drug combinations that synergistically induce AML cell death.…”

Nanoparticles overcome adaptive immune resistance and enhance immunotherapy via targeting tumor microenvironment in lung cancer

“…Lung cancer patients have an increased risk from COVID-19 infection and exhibit poor outcomes [ (Oldani et al, 2022), (Aramini et al, 2022)]. In addition, genomics, transcriptomics, proteomics, lipidomics and metabolomics are important to be used to determine the mechanisms of disease development and carcinogenesis [ (Zhou et al, 2019;Zhang et al, 2020b;Boys et al, 2022)]. The role of multi-omics has been described in lung cancer early detection and therapy [ (Abbasian et al, 2022), (Ling et al, 2022)].…”

Metabolomics in oncology

“…One of the advantages of using MS for metabolomics in cancer is its high sensitivity and specificity, which allows for the detection of very small amounts of a wide range of metabolites 153 . MS analysis has been used to study a variety of cancer types, and also in identification of different biomarkers in cancer 154 . For example, Han et al, recently showed four lipid‐based biomarkers that may be used for early diagnosis in lung cancer 155 .…”

“… 153 MS analysis has been used to study a variety of cancer types, and also in identification of different biomarkers in cancer. 154 For example, Han et al, recently showed four lipid‐based biomarkers that may be used for early diagnosis in lung cancer. 155 MS can be coupled with other analytical techniques.…”