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

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.

Automated summary

Tumor tissue processing methodologies combined with data-independent acquisition mass spectrometry (DIA-MS) can accurately analyze the proteome of multiple tumor samples, providing new insights into cancer classification, tumor biology, biomarkers, treatment response, and drug targets. However, these technologies have not yet been widely implemented in routine cancer clinical practice.