With therapeutic advances in multiple myeloma, high-sensitivity disease monitoring has become crucial when the disease burden falls below the detection limit of conventional assays. While bone marrow (BM)-based minimal residual disease assessment is the gold standard, its invasiveness restricts the feasibility for frequent longitudinal monitoring. Bottom-up proteomics offers a non-invasive and highly sensitive alternative by detecting patient-specific clonotypic peptides in peripheral blood, but most approaches require BM RNA or full-length antibody sequencing to identify the clonotypic peptides. Hence, we developed the MyeloTrak assay, a sequencing-independent approach that identifies clonotypic peptides from plasma by leveraging intrinsic biological signatures of M-proteins. Monoclonal antibody-spiked samples and a patient cohort were utilized to validate the selection of clonotypic peptides benchmarked against known antibody and BM RNA sequences. Clonotypic peptides were enriched approximately 1,000-fold from a polyclonal background, enabling confident identification in 23 patients across diverse M-protein levels and isotypes. Selected clonotypic peptides remained detectable (idotp ≥ 0.9) at concentrations of 1–4 mg/L in serial dilution experiments using monoclonal antibody-spiked samples. Longitudinal tracking in 19 patients showed generally concordant trends with conventional assays, although four patients exhibited discordant trajectories. MyeloTrak supports the feasibility of identifying patient-specific clonotypic peptides directly from plasma by leveraging the inherent biological signatures of M-proteins. Because its discovery workflow does not require BM RNA or full-length immunoglobulin sequencing, it significantly reduces the complexity of blood-based residual M-protein monitoring.
Immune checkpoint inhibitors (ICIs) have revolutionized cancer management; nevertheless, a large number of patients fail to respond to treatment. Despite extensive research efforts, there is a lack of accurate non-invasive biomarkers for prognosis and treatment outcome prediction. In this systematic review, we aim to record and evaluate studies investigating blood-circulating protein biomarkers and their association with ICIs outcomes. A literature search of PubMed and the Cochrane Library (on December 18, 2025) for studies investigating plasma biomarkers in ICI-treated cohorts at baseline was performed. Results were synthesized across cancer types and proteomic technologies, based on a vote-counting approach. The QUIPS (Quality In Prognosis Studies) tool was used to assess the risk of bias. A total of 49 studies meeting the eligibility criteria were included in the analysis. The majority of these studies focused on lung cancer (n = 21) and melanoma (n = 13) and used Olink (n = 23) and mass spectrometry (n = 15) platforms. Synthesis of the results revealed that high pre-treatment systemic levels of IL-6, CXCL8, ANGPT2, CRP, CCL3, CSF1, CXCL10, TNFSF14, and SAA1/2 were associated with poorer outcomes in ICI treated patients, while elevated levels of soluble T-cell ligands (ICOSLG, TNFSF10, and FASLG) and CXCL5 were reproducibly correlated with improved treatment outcomes. To conclude, despite limitations linked to the heterogeneity of proteomic platforms and variability in outcome reporting across studies, consistent patterns emerged: markers of systemic inflammation were associated with poor response, while proteins involved in T-cell activation and signaling were linked to better outcomes.
Salivary proline-rich proteins (sPRPs) are major proteins in saliva. However, their physiological function and dysregulation in disease, particularly beyond the local oral environment, remain largely unknown. We investigated the potential functions of sPRPs and their potential as biomarkers in chronic kidney disease (CKD) using mouse and human models. In mice, we used a unilateral nephrectomy model combined with a high-phosphate diet and FGF23-deficient mice. Single-cell RNA sequencing was used to identify sPRP-expressing cell-types in mouse and human salivary glands. The potential of sPRPs as CKD biomarkers was evaluated using saliva and serum from 1,023 human subjects. Association of serum sPRPs, eGFR, and ePTFp with the serum proteome were examined using Olink and SomaScan proteomic platforms. We found that sPRP expression is upregulated by a high-phosphate diet in a mouse CKD model and is positively regulated by FGF23. Human studies revealed that sPRPs are present not only in saliva but also in serum. Furthermore, serum, but not salivary, sPRP levels correlated with canonical CKD biomarkers, eGFR and ePTFp. Importantly, analysis of the human serum proteome revealed common and distinct CKD-related molecular signatures captured by eGFR and ePTFp, with serum sPRPs representing predominantly common features. Comparison of these serum sPRP-associated proteomic signatures with a comprehensive panel of serum biomarkers across 59 non-CKD human diseases found that 65.64
Protein C is a critical regulator of haemostasis, exerting anticoagulant, anti-inflammatory and cytoprotective effects through tightly coordinated interactions within the coagulation system. Protein C activity is dependent not only on circulating concentration, but also on its structure and functional interactions with other proteins. The plasma concentration, structure and functional activity of Protein C is known to change with age, but changes in protein-protein interactions (PPIs) of Protein C with age have not been investigated. Co-immunoprecipitation (coIP) was performed on plasma samples pooled in age groups spanning from neonates to adults using an anti-Protein C antibody. Eluates were subjected to LC-MS/MS, enriched and depleted proteins identified, and multivariate analysis, pair-wise comparisons, and functional enrichment analysis was performed. The Protein C co-precipitating proteome was found to change across development, with the most pronounced differences in the enrichment of Protein C seen in the youngest cohorts, the largest number of Protein C interaction partners identified in the 11–16 year-old group and the smallest number identified in the 6–10 year-old group. Protein C appears to associate with age-specific haemostatic, platelet, complement, and immune-related protein networks, suggesting that the surrounding protein context of Protein C differs across age. However, pathway analysis identified significant cross-over of pathways in which Protein C and interactors are involved in across age ranges, despite different proteins being identified as participating in these pathways. The findings of this study highlight global differences in the haemostatic system across normal development, and the complex and shifting role of the plasma proteome with age. Data are available via ProteomeXchange with identifier PXD077907.
