A recent review published on Jun. 9 examines how changes in protein post-translational modifications (PTMs) can drive cancer development and influence treatment response. The study, conducted by researchers from the National Clinical Research Center for Geriatrics, State Key Laboratory of Biotherapy at West China Hospital, Sichuan University, and the Department of Experimental Radiation Oncology at The University of Texas MD Anderson Cancer Center, outlines current evidence linking dysregulated PTM systems to cancer biomarkers and therapeutic targets.
The authors said that while mutations in DNA or RNA have long been considered central to cancer biology, these genetic layers do not fully explain why tumors with similar profiles can behave differently. They emphasized that proteins serve as the working machinery of cells and that PTMs rapidly alter protein activity, stability, location, and interactions. In cancer cells, these modifications are frequently rewired—reshaping signaling pathways, metabolism, chromatin organization, immune escape mechanisms, and drug resistance.
According to the review titled "Protein modification systems as cancer biomarkers and therapeutic targets," two major layers of PTM dysregulation are highlighted. First is the direct impact individual PTMs have on tumor initiation and progression: phosphorylation amplifies signaling; acetylation and methylation reshape chromatin; ubiquitination controls protein stability; SUMOylation affects various cellular processes; glycosylation influences membrane signaling and immune recognition. Emerging modifications such as lactylation or palmitoylation further expand this regulatory network. Second is the concept of PTM crosstalk—where different modifications cooperate or compete on a single protein or pathway—resulting in complex network-level changes that stabilize malignant behavior or support immune checkpoint activity involving PD-1/PD-L1.
The authors said their central message is that “cancer should be viewed not only as a disease of altered genes, but also as a disease of altered protein regulation.” They added that analyzing PTMs provides a dynamic view of tumor cell state, which complements genomic information—and may offer improved association with treatment response in some contexts.
Clinically, the implications are broad: PTM-based biomarkers could improve early detection methods, molecular subtyping strategies, prognosis assessments, and therapy prediction when combined with proteomics techniques or machine learning approaches. Examples discussed include glycosylated alpha-fetoprotein (AFP), phosphorylated ERK kinase (ERK), and exosomal PD-L1 levels among others. Therapeutic strategies already targeting these pathways include kinase inhibitors and epigenetic therapies such as histone deacetylase inhibitors.
