Abstract
Background: Cancer metastasis remains the primary cause of cancer-related mortality, driven by complex molecular alterations. Traditional proteomic studies often focus on protein abundance, overlooking the vast diversity of proteoforms arising from genetic variations, alternative splicing, and post-translational modifications (PTMs). Understanding this proteoform diversity is critical for unraveling the intricate mechanisms of metastasis and identifying novel therapeutic targets. Methods: This study employed a multi-modal proteomic approach, combining high-resolution liquid chromatography-mass spectrometry (LC-MS/MS) with top-down and middle-down strategies, to characterize proteoform landscapes in matched primary tumor and metastatic lesion samples from breast and prostate cancer patients. Bioinformatics workflows were developed to identify and quantify proteoforms, including splice variants and PTMs. Selected metastasis-associated proteoforms were then functionally validated using in vitro assays for cell migration, invasion, and proliferation, and further explored in patient-derived xenograft models. Results: We identified thousands of distinct proteoforms, with significant differences observed between primary tumors and metastatic sites. A subset of proteoforms, particularly those involving phosphorylation and glycosylation, exhibited substantial enrichment in metastatic samples. Functional studies revealed that specific proteoforms of established metastasis-related proteins, such as MTA1 and Akt, significantly modulated cellular invasiveness and metastatic potential. We also identified novel proteoforms whose manipulation impacted key hallmarks of metastasis. Conclusions: This comprehensive characterization highlights the critical role of proteoform diversity in cancer metastasis. Our findings underscore the potential of proteoform-centric approaches to uncover new mechanistic insights, identify precise biomarkers, and develop targeted therapies that address the specific molecular alterations driving metastatic progression. This work represents a significant step towards a deeper understanding of the metastatic cascade at an unprecedented molecular resolution.