Enhanced Proteomic Coverage in Tissue Microenvironment by Immune Cell Subtype Library-Assisted DIA-MS.

Immune cells that infiltrate the tumor microenvironment (TME) play crucial roles in shaping cancer development and influencing clinical outcomes and therapeutic responses. However, obtaining a comprehensive proteomic snapshot of tumor-infiltrating immunity in clinical specimens is often hindered by small sample amounts and a low proportion of immune infiltrating cells in the TME. To enable in-depth and highly sensitive profiling of microscale tissues, we established an immune cell-enriched library-assisted strategy for data-independent acquisition mass spectrometry (DIA-MS). Firstly, six immune cell subtype-specific spectral libraries were established from sorted cluster of differentiation markers, CD8+, CD4+ T lymphocytes, B lymphocytes, natural killer cells, dendritic cells, and macrophages in murine mesenteric lymph nodes (MLNs), covering 7815 protein groups with surface markers and immune cell-enriched proteins. The feasibility of microscale immune proteomic profiling was demonstrated on 1 µg tissue protein from the tumor of murine colorectal cancer (CRC) models using single-shot DIA; the immune cell-enriched library increased coverage to quantify 7419 proteins compared to directDIA analysis (6978 proteins). The enhancement enabled the mapping of 841 immune function-related proteins and exclusive identification of many low-abundance immune proteins, such as CD1D1, and CD244, demonstrating high sensitivity for immune landscape profiling. This approach was used to characterize the MLNs in CRC models, aiming to elucidate the mechanism underlying their involvement in cancer development within the TME. Even with a low percentage of immune cell infiltration (0.25-3%) in the tumor, our results illuminate downregulation in the adaptive immune signaling pathways (such as C-type lectin receptor signaling, and chemokine signaling), T cell receptor signaling, and Th1/Th2/Th17 cell differentiation, suggesting an immunosuppressive status in MLNs of CRC model. The DIA approach using the immune cell-enriched libraries showcased deep coverage and high sensitivity that can facilitate illumination of the immune proteomic landscape for microscale samples.

Cerebrospinal Fluid Proteome Map Reveals Molecular Signatures of Reversible Cerebral Vasoconstriction Syndrome.

Reversible cerebral vasoconstriction syndrome (RCVS) is a complex neurovascular disorder characterized by repetitive thunderclap headaches and reversible cerebral vasoconstriction. The pathophysiological mechanism of this mysterious syndrome remains underexplored and there is no clinically available molecular biomarker. To provide insight into the pathogenesis of RCVS, this study reported the first landscape of dysregulated proteome of cerebrospinal fluid (CSF) in patients with RCVS (n = 21) compared to the age- and sex-matched controls (n  = 20) using data-independent acquisition mass spectrometry. Protein-protein interaction and functional enrichment analysis were employed to construct functional protein networks using the RCVS proteome. An RCVS-CSF proteome library resource of 1054 proteins was established, which illuminated large groups of upregulated proteins enriched in the brain and blood-brain barrier (BBB). Personalized RCVS-CSF proteomic profiles from 17 RCVS patients and 20 controls reveal proteomic changes involving the complement system, adhesion molecules, and extracellular matrix, which may contribute to the disruption of BBB and dysregulation of neurovascular units. Moreover, an additional validation cohort validated a panel of biomarker candidates and a two-protein signature predicted by machine learning model to discriminate RCVS patients from controls with an area under the curve of 0.997. This study reveals the first RCVS proteome and a potential pathogenetic mechanism of BBB and neurovascular unit dysfunction. It also nominates potential biomarker candidates that are mechanistically plausible for RCVS, which may offer potential diagnostic and therapeutic opportunities beyond the clinical manifestations.

A Rapid One-Pot Workflow for Sensitive Microscale Phosphoproteomics.

Compared to advancements in single-cell proteomics, phosphoproteomics sensitivity has lagged behind due to low abundance, complex sample preparation, and substantial sample input requirements. We present a simple and rapid one-pot phosphoproteomics workflow (SOP-Phos) integrated with data-independent acquisition mass spectrometry (DIA-MS) for microscale phosphoproteomic analysis. SOP-Phos adapts sodium deoxycholate based one-step lysis, reduction/alkylation, direct trypsinization, and phosphopeptide enrichment by TiO2 beads in a single-tube format. By reducing surface adsorptive losses via utilizing n-dodecyl ß-d-maltoside precoated tubes and shortening the digestion time, SOP-Phos is completed within 3-4 h with a 1.4-fold higher identification coverage. SOP-Phos coupled with DIA demonstrated >90% specificity, enhanced sensitivity, lower missing values (<1%), and improved reproducibility (8%-10% CV). With a sample size-comparable spectral library, SOP-Phos-DIA identified 33,787 ± 670 to 22,070 ± 861 phosphopeptides from 5 to 0.5 µg cell lysate and 30,433 ± 284 to 6,548 ± 21 phosphopeptides from 50,000 to 2,500 cells. Such sensitivity enabled mapping key lung cancer signaling sites, such as EGFR autophosphorylation sites Y1197/Y1172 and drug targets. The feasibility of SOP-Phos-DIA was demonstrated on EGFR-TKI sensitive and resistant cells, revealing the interplay of multipathway Hippo-EGFR-ERBB signaling cascades underlying the mechanistic insight into EGFR-TKI resistance. Overall, SOP-Phos-DIA is an efficient and robust protocol that can be easily adapted in the community for microscale phosphoproteomic analysis.

Data Independent Acquisition Mass Spectrometry Enhanced Personalized Glycosylation Profiling of Haptoglobin in Hepatocellular Carcinoma.

Aberrant glycosylation has gained significant interest for biomarker discovery. However, low detectability, complex glycan structures, and heterogeneity present challenges in glycoprotein assay development. Using haptoglobin (Hp) as a model, we developed an integrated platform combining functionalized magnetic nanoparticles and zwitterionic hydrophilic interaction liquid chromatography (ZIC-HILIC) for highly specific glycopeptide enrichment, followed by a data-independent acquisition (DIA) strategy to establish a deep cancer-specific Hp-glycosylation profile in hepatitis B virus (HBV, n = 5) and hepatocellular carcinoma (HCC, n = 5) patients. The DIA strategy established one of the deepest Hp-glycosylation landscapes (1029 glycopeptides, 130 glycans) across serum samples, including 54 glycopeptides exclusively detected in HCC patients. Additionally, single-shot DIA searches against a DIA-based spectral library outperformed the DDA approach by 2-3-fold glycopeptide coverage across patients. Among the four N-glycan sites on Hp (N-184, N-207, N-211, N-241), the total glycan type distribution revealed significantly enhanced detection of combined fucosylated-sialylated glycans, which were the most dominant glycoforms identified in HCC patients. Quantitation analysis revealed 48 glycopeptides significantly enriched in HCC (p < 0.05), including a hybrid monosialylated triantennary glycopeptide on the N-184 site with nearly none-to-all elevation to differentiate HCC from the HBV group (HCC/HBV ratio: 2462 ± 766, p < 0.05). In summary, DIA-MS presents an unbiased and comprehensive alternative for targeted glycoproteomics to guide discovery and validation of glyco-biomarkers.

Lessons learned: establishing a CLIA-equivalent laboratory for targeted mass spectrometry assays - navigating the transition from research to clinical practice.

Mass spectrometry (MS) assays offer exceptional capabilities in high multiplexity, specificity, and throughput. As proteomics technologies continue advancements to identify new disease biomarkers, transition of these innovations from research settings to clinical applications becomes imperative. To meet the rigorous regulatory standards of clinical laboratories, development of a clinical protein MS assay necessitates adherence to stringent criteria. To illustrate the process, this project focused on using thyroglobulin (Tg) as a biomarker and an immuno-multiple reaction monitoring (iMRM) MS-based assay as a model for establishing a Clinical Laboratory Improvement Amendments (CLIA) compliant laboratory within the Centers of Genomic and Precision Medicine, National Taiwan University. The chosen example also illustrates the clinical utility of MS assays to complement conventional immunoassay-based methods, particularly in cases where the presence of autoantibodies in 10-30% of patients hinders accuracy. The laboratory design entails a comprehensive coordination in spatial layout, workflow organization, equipment selection, ventilation systems, plumbing, electrical infrastructure, documentation procedures, and communication protocols. Practical aspects of the transformation process, including preparing laboratory facilities, testing environments, instrument validation, assay development and validation, quality management, sample testing, and personnel competency, are discussed. Finally, concordant results in proficiency testing demonstrate the harmonization with the University of Washington Medical Center and the quality assurance of the CLIA-equivalent Tg-iMRM MS assay established in Taiwan. The realization of this model protein MS assay in Taiwan highlights the feasibility of international joint development and provides a detailed reference map to expedite the implementation of more MS-based protein assays in clinical laboratories for patient care.

Heart rate variability biofeedback enhances cognitive, motor, psychological, and autonomic functions in post-stroke rehabilitation.

Post-stroke patients often experience psychological distress and autonomic nervous system (ANS) dysregulation, impacting their well-being. This study evaluated the effectiveness of heart rate variability (HRV) biofeedback on cognitive, motor, psychological, and ANS functions in sixty-two ischemic stroke patients (43 males, mean age = 60.1) at a Medical Center in southern Taiwan. To prevent interaction, we allocated patients to the HRV biofeedback or control (usual care) group based on their assigned rehabilitation days, with 31 patients in each group. Assessments conducted at baseline, three, and six months included the Montreal Cognitive Assessment (MoCA), Fugl-Meyer Assessment for Upper Extremities (FMA-UE), Perceived Stress Scale, Hospital Anxiety and Depression Scales (HADS), and HRV indices. Mixed-effect models were used to analyze Group by Time interactions. The results revealed significant interactions across all functions. At 3 months, significant improvements in the HRV biofeedback group were observed only in MoCA, FMA-UE, and HADS-depression scores compared to the control group. By 6 months, all measured outcomes demonstrated significant improvements in the biofeedback group relative to the control group. These results suggest that HRV biofeedback may be an effective complementary intervention in post-stroke rehabilitation, warranting further validation.

Extending the Coverage of Lys-C/Trypsin-Based Bottom-up Proteomics by Cysteine S-Aminoethylation.

To improve the coverage in bottom-up proteomics, S-aminoethylation of cysteine residues (AE-Cys) was carried out with 2-bromoethylamine, followed by cleavage with lysyl endopeptidase (Lys-C) or Lys-C/trypsin. A model study with bovine serum albumin showed that the C-terminal side of AE-Cys was successfully cleaved by Lys-C. The frequency of side reactions at amino acids other than Cys was less than that in the case of carbamidomethylation of Cys with iodoacetamide. Proteomic analysis of A549 cell extracts in the data-dependent acquisition mode after AE-Cys modification afforded a greater number of identified protein groups, especially membrane proteins. In addition, label-free quantification of proteins in mouse nonsmall cell lung cancer (NSCLC) tissue in the data-independent acquisition mode after AE-Cys modification showed improved NSCLC pathway coverage and greater reproducibility. Furthermore, the AE-Cys method could identify an epidermal growth factor receptor peptide containing the T790 M mutation site, a well-established lung-cancer-related mutation site that has evaded conventional bottom-up methods. Finally, AE-Cys was found to fully mimic Lys in terms of collision-induced dissociation fragmentation, ion mobility separation, and cleavage by Lys-C/trypsin, except for sulfoxide formation during sample preparation.

Increasing DNA damage sensitivity through corylin-mediated inhibition of homologous recombination.

BACKGROUND: DNA repair allows the survival of cancer cells. Therefore, the development of DNA repair inhibitors is a critical need for sensitizing cancers to chemoradiation. Sae2CtIP has specific functions in initiating DNA end resection, as well as coordinating cell cycle checkpoints, and it also greatly interacts with the DDR at different levels. RESULTS: In this study, we demonstrated that corylin, a potential sensitizer, causes deficiencies in DNA repair and DNA damage checkpoints in yeast cells. More specifically, corylin increases DNA damage sensitivity through the Sae2-dependent pathway and impairs the activation of Mec1-Ddc2, Rad53-p and γ-H2A. In breast cancer cells, corylin increases apoptosis and reduces proliferation following Dox treatment by inhibiting CtIP. Xenograft assays showed that treatment with corylin combined with Dox significantly reduced tumor growth in vivo. CONCLUSIONS: Our findings herein delineate the mechanisms of action of corylin in regulating DNA repair and indicate that corylin has potential long-term clinical utility as a DDR inhibitor.

Proteomic profiling of tumor microenvironment and prognosis risk prediction in stage I lung adenocarcinoma.

OBJECTIVES: With the increasing popularity of CT screening, more cases of early-stage lung cancer are being diagnosed. However, 24.5% of stage I non-small-cell lung cancer (NSCLC) patients still experience treatment failure post-surgery. Biomarkers to predict lung cancer patients at high risk of recurrence are needed. MATERIALS AND METHODS: We collected protein mass spectrometry data from the Taiwan Lung Cancer Moonshot Project and performed bioinformatics analysis on proteins with differential expressions between tumor and adjacent normal tissues in 74 stage I lung adenocarcinoma (LUAD) cases, aiming to explore the tumor microenvironment related prognostic biomarkers. Findings were further validated in 6 external cohorts. RESULTS: The analysis of differentially expressed proteins revealed that the most enriched categories of diseases and biological functions were cellular movement, immune cell trafficking, and cancer. Utilizing proteomic profiling of the tumor microenvironment, we identified five prognostic biomarkers (ADAM10, MIF, TEK, THBS2, MAOA). We then developed a risk score model, which independently predicted recurrence-free survival and overall survival in stage I LUAD. Patients with high risk scores experienced worse recurrence-free survival (adjusted hazard ratio = 8.28, p < 0.001) and overall survival (adjusted hazard ratio = 6.88, p = 0.013). Findings had been also validated in the external cohorts. CONCLUSION: The risk score model derived from proteomic profiling of tumor microenvironment can be used to predict recurrence risk and prognosis of stage I LUAD.