PCSK9 stimulates Syk, PKCδ, and NF-κB, leading to atherosclerosis progression independently of LDL receptor.

Proprotein convertase subtilisin/kexin type-9 (PCSK9) binds to and degrades low-density lipoprotein (LDL) receptor, leading to increase of LDL cholesterol in blood. Its blockers have emerged as promising therapeutics for cardiovascular diseases. Here we show that PCSK9 itself directly induces inflammation and aggravates atherosclerosis independently of the LDL receptor. PCSK9 exacerbates atherosclerosis in LDL receptor knockout mice. Adenylyl cyclase-associated protein 1 (CAP1) is the main binding partner of PCSK9 and indispensable for the inflammatory action of PCSK9, including induction of cytokines, Toll like receptor 4, and scavenger receptors, enhancing the uptake of oxidized LDL. We find spleen tyrosine kinase (Syk) and protein kinase C delta (PKCδ) to be the key mediators of inflammation after PCSK9-CAP1 binding. In human peripheral blood mononuclear cells, serum PCSK9 levels are positively correlated with Syk, PKCδ, and p65 phosphorylation. The CAP1-fragment crystallizable region (CAP1-Fc) mitigates PCSK9-mediated inflammatory signal transduction more than the PCSK9 blocking antibody evolocumab does.

Protein Signatures of Parathyroid Adenoma according to Tumor Volume and Functionality.

Background: Parathyroid adenoma (PA) is a common endocrine disease linked to multiple complications, but the pathophysiology of the disease remains incompletely understood. The study aimed to identify the key regulator proteins and pathways of PA according to functionality and volume through quantitative proteomic analyses. Methods: We conducted a retrospective study of 15 formalin-fixed, paraffin-embedded PA samples from tertiary hospitals in South Korea. Proteins were extracted, digested, and the resulting peptides were analyzed using liquid chromatography-tandem mass spectrometry. Pearson correlation analysis was employed to identify proteins significantly correlated with clinical variables. Canonical pathways and transcription factors were analyzed using Ingenuity Pathway Analysis. Results: The median age of the participants was 52 years, and 60.0% were female. Among the 8,153 protein groups analyzed, 496 showed significant positive correlations with adenoma volume, while 431 proteins were significantly correlated with parathyroid hormone (PTH) levels. The proteins SLC12A9, LGALS3, and CARM1 were positively correlated with adenoma volume, while HSP90AB2P, HLA-DRA, and SCD5 showed negative correlations. DCPS, IRF2BPL, and FAM98A were the main proteins that exhibited positive correlations with PTH levels, and SLITRK4, LAP3, and AP4E1 had negative correlations. Canonical pathway analysis demonstrated that the RAN and sirtuin signaling pathways were positively correlated with both PTH levels and adenoma volume, while epithelial adherence junction pathways had negative correlations. Conclusion: Our study identified pivotal proteins and pathways associated with PA, offering potential therapeutic targets. These findings accentuate the importance of proteomics in understanding disease pathophysiology and the need for further research.

Glutamyl-prolyl-tRNA synthetase (EPRS1) drives tubulointerstitial nephritis-induced fibrosis by enhancing T cell proliferation and activity.

Toxin- and drug-induced tubulointerstitial nephritis (TIN), characterized by interstitial infiltration of immune cells, frequently necessitates dialysis for patients due to irreversible fibrosis. However, agents modulating interstitial immune cells are lacking. Here, we addressed whether the housekeeping enzyme glutamyl-prolyl-transfer RNA synthetase 1 (EPRS1), responsible for attaching glutamic acid and proline to transfer RNA, modulates immune cell activity during TIN and whether its pharmacological inhibition abrogates fibrotic transformation. The immunological feature following TIN induction by means of an adenine-mixed diet was infiltration of EPRS1high T cells, particularly proliferating T and γδ T cells. The proliferation capacity of both CD4+ and CD8+ T cells, along with interleukin-17 production of γδ T cells, was higher in the kidneys of TIN-induced Eprs1+/+ mice than in the kidneys of TIN-induced Eprs1+/- mice. This discrepancy contributed to the fibrotic amelioration observed in kidneys of Eprs1+/- mice. TIN-induced fibrosis was also reduced in Rag1-/- mice adoptively transferred with Eprs1+/- T cells compared to the Rag1-/- mice transferred with Eprs1+/+ T cells. The use of an EPRS1-targeting small molecule inhibitor (bersiporocin) under clinical trials to evaluate its therapeutic potential against idiopathic pulmonary fibrosis alleviated immunofibrotic aggravation in TIN. EPRS1 expression was also observed in human kidney tissues and blood-derived T cells, and high expression was associated with worse patient outcomes. Thus, EPRS1 may emerge as a therapeutic target in toxin- and drug-induced TIN, modulating the proliferation and activity of infiltrated T cells.

Identification of VWA5A as a novel biomarker for inhibiting metastasis in breast cancer by machine-learning based protein prioritization.

Distant metastasis is the leading cause of death in breast cancer (BC). The timing of distant metastasis differs according to subtypes of BCs and there is a need for identification of biomarkers for the prediction of early and late metastasis. To identify biomarker candidates whose abundance level can discriminate metastasis types, we performed a high-throughput proteomics assay using tissue samples from BCs with no metastasis, late metastasis, and early metastasis, processed data with machine learning-based feature selection, and found that low VWA5A could be responsible for shorter duration of metastasis-free interval. Low expression of VWA5A gene in METABRIC cohort was associated with poor survival in BCs, especially in hormone receptor (HR)-positive BCs. In-vitro experiments confirmed tumor suppressive effect of VWA5A on BCs in HR+ and triple-negative BC cell lines. We found that expression of VWA5A can be assessed by immunohistochemistry (IHC) on archival tissue samples. Decreasing nuclear expression of VWA5A was significantly associated with advanced T stage and lymphatic invasion in consecutive BCs of all subtypes. We discovered lower expression of VWA5A as the potential biomarker for metastasis-prone BCs, and our results support the clinical utility of VWA5A IHC, as an adjunctive tools for prognostication of BCs.

Integrative Multi-omics Analysis Reveals Different Metabolic Phenotypes Based on Molecular Characteristics in Thyroid Cancer.

PURPOSE: Thyroid cancer metabolic characteristics vary depending on the molecular subtype determined by mutational status. We aimed to investigate the molecular subtype-specific metabolic characteristics of thyroid cancers. EXPERIMENTAL DESIGN: An integrative multi-omics analysis was conducted, incorporating transcriptomics, metabolomics, and proteomics data obtained from human tissues representing distinct molecular characteristics of thyroid cancers: BRAF-like (papillary thyroid cancer with BRAFV600E mutation; PTC-B), RAS-like (follicular thyroid cancer with RAS mutation; FTC-R), and ATC-like (anaplastic thyroid cancer with BRAFV600E or RAS mutation; ATC-B or ATC-R). To validate our findings, we employed tissue microarray of human thyroid cancer tissues and performed in vitro analyses of cancer cell phenotypes and metabolomic assays after inducing genetic knockdown. RESULTS: Metabolic properties differed between differentiated thyroid cancers of PTC-B and FTC-R, but were similar in dedifferentiated thyroid cancers of ATC-B/R, regardless of their mutational status. Tricarboxylic acid (TCA) intermediates and branched-chain amino acids (BCAA) were enriched with the activation of TCA cycle only in FTC-R, whereas one-carbon metabolism and pyrimidine metabolism increased in both PTC-B and FTC-R and to a great extent in ATC-B/R. However, the protein expression levels of the BCAA transporter (SLC7A5) and a key enzyme in one-carbon metabolism (SHMT2) increased in all thyroid cancers and were particularly high in ATC-B/R. Knockdown of SLC7A5 or SHMT2 inhibited the migration and proliferation of thyroid cancer cell lines differently, depending on the mutational status. CONCLUSIONS: These findings define the metabolic properties of each molecular subtype of thyroid cancers and identify metabolic vulnerabilities, providing a rationale for therapies targeting its altered metabolic pathways in advanced thyroid cancer.

Purification and characterization of different proteasome species from mammalian cells.

Proteasomes are heterogeneous in forms and functions, but how the equilibrium among the 20S, 26S, and 30S proteasomes is achieved and altered is elusive. Here, we present a protocol for purifying and characterizing proteasome species. We describe steps for generating stable cell lines; affinity purifying the proteasome species; and characterizing them through native PAGE, activity assay, size-exclusion chromatography, and mass spectrometry. These standardized methods may contribute to biochemical studies of cellular proteasomes under both physiological and pathological conditions. For complete details on the use and execution of this protocol, please refer to Choi et al. (2023).1.

Proteome and immune responses of extracellular vesicles derived from macrophages infected with the periodontal pathogen Tannerella forsythia.

Periodontitis is a chronic inflammatory disease caused by periodontal pathogens in subgingival plaque and is associated with systemic inflammatory diseases. Extracellular vesicles (EVs) released from host cells and pathogens carry a variety of biological molecules and are of interest for their role in disease progression and as diagnostic markers. In the present study, we analysed the proteome and inflammatory response of EVs derived from macrophages infected with Tannerella forsythia, a periodontal pathogen. The EVs isolated from the cell conditioned medium of T. forsythia-infected macrophages were divided into two distinct vesicles, macrophage-derived EVs and T. forsythia-derived OMVs, by size exclusion chromatography combined with density gradient ultracentrifugation. Proteome analysis showed that in T. forsythia infection, macrophage-derived EVs were enriched with pro-inflammatory cytokines and inflammatory mediators associated with periodontitis progression. T. forsythia-derived OMVs harboured several known virulence factors, including BspA, sialidase, GroEL and various bacterial lipoproteins. T. forsythia-derived OMVs induced pro-inflammatory responses via TLR2 activation. In addition, we demonstrated that T. forsythia actively released OMVs when T. forsythia encountered macrophage-derived soluble molecules. Taken together, our results provide insight into the characterisation of EVs derived from cells infected with a periodontal pathogen.

In-depth proteome analysis of brain tissue from Ewsr1 knockout mouse by multiplexed isobaric tandem mass tag labeling.

EWS RNA binding protein 1 (EWSR1) is a multifunctional protein whose epigenetic signatures contribute to the pathogenesis of various human diseases, such as neurodegenerative disorders, skin development, and tumorigenic processes. However, the specific cellular functions and physiological characteristics of EWSR1 remain unclear. In this study, we used quantitative mass spectrometry-based proteomics with tandem mass tag labeling to investigate the global proteome changes in brain tissue in Ewsr1 knockout and wild-type mice. From 9115 identified proteins, we selected 118 differentially expressed proteins, which is common to three quantitative data processing strategies including only protein level normalizations and spectrum-protein level normalization. Bioinformatics analysis of these common differentially expressed proteins revealed that proteins up-regulated in Ewsr1 knockout mouse are mostly related to the positive regulation of bone remodeling and inflammatory response. The down-regulated proteins were associated with the regulation of neurotransmitter levels or amino acid metabolic processes. Collectively, these findings provide insight into the physiological function and pathogenesis of EWSR1 on protein level. Better understanding of EWSR1 and its protein interactions will advance the field of clinical research into neuronal disorders. The mass spectrometry proteomics data have been deposited to the ProteomeXchange Consortium via the PRIDE partner repository with the dataset identifier PXD026994.

Machine Learning-Based Proteomics Reveals Ferroptosis in COPD Patient-Derived Airway Epithelial Cells Upon Smoking Exposure.

BACKGROUND: Proteomics and genomics studies have contributed to understanding the pathogenesis of chronic obstructive pulmonary disease (COPD), but previous studies have limitations. Here, using a machine learning (ML) algorithm, we attempted to identify pathways in cultured bronchial epithelial cells of COPD patients that were significantly affected when the cells were exposed to a cigarette smoke extract (CSE). METHODS: Small airway epithelial cells were collected from patients with COPD and those without COPD who underwent bronchoscopy. After expansion through primary cell culture, the cells were treated with or without CSEs, and the proteomics of the cells were analyzed by mass spectrometry. ML-based feature selection was used to determine the most distinctive patterns in the proteomes of COPD and non-COPD cells after exposure to smoke extract. Publicly available single-cell RNA sequencing data from patients with COPD (GSE136831) were used to analyze and validate our findings. RESULTS: Five patients with COPD and five without COPD were enrolled, and 7,953 proteins were detected. Ferroptosis was enriched in both COPD and non-COPD epithelial cells after their exposure to smoke extract. However, the ML-based analysis identified ferroptosis as the most dramatically different response between COPD and non-COPD epithelial cells, adjusted P value = 4.172 × 10-6, showing that epithelial cells from COPD patients are particularly vulnerable to the effects of smoke. Single-cell RNA sequencing data showed that in cells from COPD patients, ferroptosis is enriched in basal, goblet, and club cells in COPD but not in other cell types. CONCLUSION: Our ML-based feature selection from proteomic data reveals ferroptosis to be the most distinctive feature of cultured COPD epithelial cells compared to non-COPD epithelial cells upon exposure to smoke extract.

ECPAS/Ecm29-mediated 26S proteasome disassembly is an adaptive response to glucose starvation.

The 26S proteasome comprises 20S catalytic and 19S regulatory complexes. Approximately half of the proteasomes in cells exist as free 20S complexes; however, our mechanistic understanding of what determines the ratio of 26S to 20S species remains incomplete. Here, we show that glucose starvation uncouples 26S holoenzymes into 20S and 19S subcomplexes. Subcomplex affinity purification and quantitative mass spectrometry reveal that Ecm29 proteasome adaptor and scaffold (ECPAS) mediates this structural remodeling. The loss of ECPAS abrogates 26S dissociation, reducing degradation of 20S proteasome substrates, including puromycylated polypeptides. In silico modeling suggests that ECPAS conformational changes commence the disassembly process. ECPAS is also essential for endoplasmic reticulum stress response and cell survival during glucose starvation. In vivo xenograft model analysis reveals elevated 20S proteasome levels in glucose-deprived tumors. Our results demonstrate that the 20S-19S disassembly is a mechanism adapting global proteolysis to physiological needs and countering proteotoxic stress.

Discovery of Novel Digital Biomarkers for Type 2 Diabetic Nephropathy Classification via Integration of Urinary Proteomics and Pathology.

Background: The heterogeneous phenotype of diabetic nephropathy (DN) from type 2 diabetes complicates appropriate treatment approaches and outcome prediction. Kidney histology helps diagnose DN and predict its outcomes, and an artificial intelligence (AI)-based approach will maximize clinical utility of histopathological evaluation. Herein, we addressed whether AI-based integration of urine proteomics and image features improves DN classification and its outcome prediction, altogether augmenting and advancing pathology practice. Methods: We studied whole slide images (WSIs) of periodic acid-Schiff-stained kidney biopsies from 56 DN patients with associated urinary proteomics data. We identified urinary proteins differentially expressed in patients who developed end-stage kidney disease (ESKD) within two years of biopsy. Extending our previously published human-AI-loop pipeline, six renal sub-compartments were computationally segmented from each WSI. Hand-engineered image features for glomeruli and tubules, and urinary protein measurements, were used as inputs to deep-learning frameworks to predict ESKD outcome. Differential expression was correlated with digital image features using the Spearman rank sum coefficient. Results: A total of 45 urinary proteins were differentially detected in progressors, which was most predictive of ESKD (AUC=0.95), while tubular and glomerular features were less predictive (AUC=0.71 and AUC=0.63, respectively). Accordingly, a correlation map between canonical cell-type proteins, such as epidermal growth factor and secreted phosphoprotein 1, and AI-based image features was obtained, which supports previous pathobiological results. Conclusions: Computational method-based integration of urinary and image biomarkers may improve the pathophysiological understanding of DN progression as well as carry clinical implications in histopathological evaluation.

Proteomic profiling of protein expression changes after 3 months-exercise in ESRD patients on hemodialysis.

The prevalence of chronic kidney disease (CKD) is steadily increasing, and it is a global health burden. Exercise has been suggested to improve physical activity and the quality of life in patients with CKD, eventually reducing mortality. This study investigated the change in physical performance after exercise in dialysis-dependent patients with CKD and analyzed differentially expressed proteins before and after the exercise. Plasma samples were collected at enrollment and after 3 months of exercise. Liquid chromatography with tandem mass spectrometry analysis and data-independent acquisition results were analyzed to determine the significantly regulated proteins. A total of 37 patients on dialysis were recruited, and 16 were randomized to exercise for 3 months. The hand grip strength and the walking speed significantly improved in the exercise group. Proteome analysis revealed 60 significantly expressed proteins after 3 months of exercise. In the protein functional analysis, the significantly expressed proteins were involved in the immune response. Also, some of the key significantly expressed proteins [(M Matrix metallopeptidase 9 (MMP-9), Activin A Receptor Type 1B (ACVR1B), Fetuin B (FETUB)] were validated via an enzyme-linked immunosorbent assay. Our results showed that exercise in dialysis-dependent patients with CKD could improve their physical performance. These results indicated that this beneficial effect of exercise in these populations could be associated with immune response.

In-depth proteomic signature of parathyroid carcinoma.

OBJECTIVE: Diagnosing parathyroid carcinoma (PC) is complicated and controversial that early diagnosis and intervention are often difficult. Therefore, we aimed to elucidate the protein signatures of PC through quantitative proteomic analyses to aid in the early and accurate diagnosis of PC. DESIGN: We conducted a retrospective cohort study. METHODS: We performed liquid chromatography with tandem mass spectrometry using formalin-fixed paraffin-embedded samples. For the analyses, 23 PC and 15 parathyroid adenoma (PA) tissues were collected from 6 tertiary hospitals in South Korea. RESULTS: The mean age of the patients was 52 years, and 63% were women. Proteomic expression profiling revealed 304 differentially expressed proteins (DEPs) with a cut-off of P < .05 and fold change >1.5. Among DEPs, we identified a set of 5 proteins that can discriminate PC from PA: carbonic anhydrase 4 (CA4), alpha/beta hydrolase domain-containing protein 14B (ABHD14B), laminin subunit beta-2 (LAMB2), CD44 antigen (CD44), and alpha-1-acid glycoprotein 1 (ORM1) that exhibited the highest area under the curve of 0.991 in neural network model. The nuclear percentage of CA4 and LAMB2 in immunohistochemistry was significantly lower in PC tissue than in the PA (CA4: 2.77 ± 1.96%, 26.2 ± 3.45%, P < .001; LAMB2: 6.86 ± 3.46%, 38.54 ± 4.13%, P < .001). The most enriched canonical pathways in PC included glycoprotein-6 signaling and mammalian target of rapamycin (mTOR). CONCLUSIONS: We identified key proteins differentially expressed between PC and PA using proteomic analyses of parathyroid neoplasms. These findings may help to diagnose PC accurately and elucidate potential therapeutic targets.

Dual viscosity mixture vehicle for intratympanic steroid treatment modifies the ROS and inflammation related proteomes.

Until recently, the most standard treatment for sensorineural or sudden hearing loss, which is caused by inner ear damage or deterioration, has been systemic oral steroid administration. In recent, intratympanic steroid injections such as dexamethasone have been used for the treatment of sudden hearing loss as well. It is injected into the tympanic cavity through its membrane and is expected to diffuse over the round window located between the tympanic cavity and the inner ear. However, in clinical situations, the delivery time of steroids to the inner ear is shorter than 24 h, which does not allow for a sufficient therapeutic effect. Therefore, we applied a previously invented dual viscosity mixture vehicle (DVV) for intratympanic dexamethasone to a guinea pig model, which could reduce the side effects of systemic steroid administration with sufficient dwelling time for the treatment of hearing loss, and we investigated the physiological changes with a global proteomic approach. In this study, we extracted perilymph in three different conditions from guinea pigs treated with dexamethasone-embedded DVV, dexamethasone mixed in saline, and control groups to compare proteomic changes using tandem mass spectrometry analysis. After liquid chromatography coupled tandem mass spectrometry (LC-MS/MS) analysis, we first identified 46 differentially expressed proteins (DEPs) that were statistically significant after one-way ANOVA multiple-sample test. We also performed pairwise comparisons among each group to identify DEPs closely related to the treatment response of dexamethasone-embedded DVV. Gene ontology enrichment analysis showed that these DEPs were mostly related to inflammation, immune, actin remodeling, and antioxidant-related processes. As a result, the proteome changes in the DVV-treated groups revealed that most upregulated proteins activate the cell proliferation process, and downregulated proteins inhibit apoptosis and inflammatory reactions. Moreover, the reactive oxygen process was also regulated by DEPs after DVV treatment.

Proteomic Discovery of Plasma Protein Biomarkers and Development of Models Predicting Prognosis of High-Grade Serous Ovarian Carcinoma.

Ovarian cancer is one of the most lethal female cancers. For accurate prognosis prediction, this study aimed to investigate novel, blood-based prognostic biomarkers for high-grade serous ovarian carcinoma (HGSOC) using mass spectrometry-based proteomics methods. We conducted label-free liquid chromatography-tandem mass spectrometry using frozen plasma samples obtained from patients with newly diagnosed HGSOC (n = 20). Based on progression-free survival (PFS), the samples were divided into two groups: good (PFS ≥18 months) and poor prognosis groups (PFS <18 months). Proteomic profiles were compared between the two groups. Referring to proteomics data that we previously obtained using frozen cancer tissues from chemotherapy-naïve patients with HGSOC, overlapping protein biomarkers were selected as candidate biomarkers. Biomarkers were validated using an independent set of HGSOC plasma samples (n = 202) via enzyme-linked immunosorbent assay (ELISA). To construct models predicting the 18-month PFS rate, we performed stepwise selection based on the area under the receiver operating characteristic curve (AUC) with 5-fold cross-validation. Analysis of differentially expressed proteins in plasma samples revealed that 35 and 61 proteins were upregulated in the good and poor prognosis groups, respectively. Through hierarchical clustering and bioinformatic analyses, GSN, VCAN, SND1, SIGLEC14, CD163, and PRMT1 were selected as candidate biomarkers and were subjected to ELISA. In multivariate analysis, plasma GSN was identified as an independent poor prognostic biomarker for PFS (adjusted hazard ratio, 1.556; 95% confidence interval, 1.073-2.256; p = 0.020). By combining clinical factors and ELISA results, we constructed several models to predict the 18-month PFS rate. A model consisting of four predictors (FIGO stage, residual tumor after surgery, and plasma levels of GSN and VCAN) showed the best predictive performance (mean validated AUC, 0.779). The newly developed model was converted to a nomogram for clinical use. Our study results provided insights into protein biomarkers, which might offer clues for developing therapeutic targets.

Intratympanic steroid treatment can reduce ROS and immune response in human perilymph investigated by in-depth proteome analysis.

Intratympanic (IT) steroid treatment is one of the most widely used and effective treatments for inner ear disorders such as sudden sensorineural hearing loss (SNHL). However, a clear mechanism of IT steroids in inner ear recovery has not yet been revealed. Therefore, we investigated proteome changes in extracted human perilymph after steroid treatment. In this study, we applied a tandem mass spectrometry (MS/MS)-based proteomics approach to discover global proteome changes by comparing human perilymph after steroid treatment with non-treated perilymph group. Using liquid chromatography-MS/MS analysis, we selected 156 differentially expressed proteins (DEPs) that were statistically significant according to Student's t-test. Functional annotation analysis showed that upregulated proteins after steroid treatment are related to apoptosis signaling, as well as reactive oxygen species (ROS) and immune responses. The protein-protein interaction (PPI) clusters the proteins associated with these processes and attempts to observe signaling circuitry, which mediates cellular response after IT steroid treatments. Moreover, we also considered the interactome analysis of DEPs and observed that those with high interaction scores were categorized as having equivalent molecular functions (MFs). Collectively, we suggest that DEPs and interacting proteins in human perilymph after steroid treatment would inhibit the apoptotic and adaptive immune processes that may lead to anti-inflammatory effects.

Quantitative proteomics identifies TUBB6 as a biomarker of muscle-invasion and poor prognosis in bladder cancer.

Muscle-invasive urothelial carcinoma (MIUC) of the bladder shows highly aggressive tumor behavior, which has prompted the quest for robust biomarkers predicting invasion. To discover such biomarkers, we first employed high-throughput proteomic method and analyzed tissue biopsy cohorts from patients with bladder urothelial carcinoma (BUC), stratifying them according to their pT stage. Candidate biomarkers were selected through bioinformatic analysis, followed by validation. The latter comprised 2D and 3D invasion and migration assays, also a selection of external public datasets to evaluate mRNA expression and an in-house patient-derived tissue microarray (TMA) cohort to evaluate protein expression with immunohistochemistry (IHC). Our multilayered platform-based analysis identified tubulin beta 6 class V (TUBB6) as a promising prognostic biomarker predicting MIUC of the bladder. The in vitro 2D and 3D migration and invasion assays consistently showed that inhibition of TUBB6 mRNA significantly reduced cell migration and invasion ability in two BUC cell lines with aggressive phenotype (TUBB6 migration, P = .0509 and P < .0001; invasion, P = .0002 and P = .0044; TGFBI migration, P = .0214 and P = .0026; invasion, P < .0001 and P = .0001; T24 and J82, respectively). Validation through multiple public datasets, including The Cancer Genome Atlas (TCGA) and selected GSE (Genomic Spatial Event) databases, confirmed TUBB6 as a potential biomarker predicting MIUC. Further protein-based validation with our TMA cohort revealed concordant results, highlighting the clinical implication of TUBB6 expression in BUC patients (overall survival: P < .001). We propose TUBB6 as a novel IHC biomarker to predict invasion and poor prognosis, also select the optimal treatment in BUC patients.

The proteomic landscape shows oncologic relevance in cystitis glandularis.

BACKGROUND: The relationship between cystitis glandularis (CG) and bladder malignancy remains unclear. METHODS: We identified the oncologic significance of CG at the molecular level using liquid chromatography-tandem mass spectrometry-based proteomic analysis of 10 CG, 12 urothelial carcinoma (UC), and nine normal urothelium (NU) specimens. Differentially expressed proteins (DEPs) were identified based on an analysis of variance false discovery rate < 0.05, and their functional enrichment was analyzed using a network model, Gene Set Enrichment Analysis, and Gene Ontology annotation. RESULTS: We identified 9,890 proteins across all samples and 1,139 DEPs among the three entities. A substantial number of DEPs overlapped in CG/NU, distinct from UC. Interestingly, we found that a subset of DEP clusters (n = 53, 5%) was differentially expressed in NU but similarly between CG and UC. This "UC-like signature" was enriched for reactive oxygen species (ROS) and energy metabolism, growth and DNA repair, transport, motility, epithelial-mesenchymal transition, and cell survival. Using the top 10 shortlisted DEPs, including SOD2, PRKCD, CYCS, and HCLS1, we identified functional elements related to ROS metabolism, development, and transport using network analysis. The abundance of these four molecules in UC/CG than in NU was consistent with the oncologic functions in CG. CONCLUSIONS: Using a proteomic approach, we identified a predominantly non-neoplastic landscape of CG, which was closer to NU than to UC. We also confirmed a small subset of common DEPs in UC and CG, suggesting that altered ROS metabolism might imply potential cancerous risks in CG.

Dual Oxidase 2 (DUOX2) as a Proteomic Biomarker for Predicting Treatment Response to Chemoradiation Therapy for Locally Advanced Rectal Cancer: Using High-Throughput Proteomic Analysis and Machine Learning Algorithm.

High-throughput mass-spectrometry-based quantitative proteomic analysis was performed using formalin-fixed, paraffin-embedded (FFPE) biopsy samples obtained before treatment from 13 patients with locally advanced rectal cancer (LARC), who were treated with concurrent chemoradiation therapy (CCRT) followed by surgery. Patients were divided into complete responder (CR) and non-complete responder (nCR) groups. Immunohistochemical (IHC) staining of 79 independent FFPE tissue samples was performed to validate the predictive ability of proteomic biomarker candidates. A total of 3637 proteins were identified, and the expression of 498 proteins was confirmed at significantly different levels (differentially expressed proteins-DEPs) between two groups. In Gene Ontology enrichment analyses, DEPs enriched in biological processes in the CR group included proteins linked to cytoskeletal organization, immune response processes, and vesicle-associated protein transport processes, whereas DEPs in the nCR group were associated with biosynthesis, transcription, and translation processes. Dual oxidase 2 (DUOX2) was selected as the most predictive biomarker in machine learning algorithm analysis. Further IHC validation ultimately confirmed DUOX2 as a potential biomarker for predicting the response of nCR to CCRT. In conclusion, this study suggests that the treatment response to RT may be affected by the pre-treatment tumor microenvironment. DUOX2 is a potential biomarker for the early prediction of nCR after CCRT.

One-Week Dynamic Changes in Cardiac Proteomes After Cardiac Radioablation in Experimental Rat Model.

Background: Recently, stereotactic ablative radiotherapy (SABR) has been adopted to non-invasively treat catheter ablation-refractory ventricular tachycardia (VT). VT episodes have been dramatically reduced after SABR, within weeks; however the underlying mechanisms of these clinical effects and potential mediators of early anti-arrhythmic effect remain unclear. Methods: In this study, cardiac tissue was harvested from non-irradiated control (0 Gy), conventional irradiated control (2 Gy), and radioablative test (25 Gy) rat groups after 3 and 7 days of irradiation. The samples were proteomically analyzed to identify the differentially expressed proteins (DEP) between different groups. Validation experiments were performed similar to validation in profiling where Data independent acquisition and parallel reaction monitoring methods were used. Data are available via ProteomeXchange with identifier PXD030878. Results: Functional enrichment analysis of 25 Gy sample showed that among the downregulated proteins, "intracellular signal transduction" and "cell to cell adhesion" proteins were significantly affected at day 3 while "Ras protein signal transduction," "GTPase regulation," and "actin filament-based process" proteins were majorly affected at day 7. GO analysis demonstrated that most of the upregulated proteins belonged to the classes "cellular stress response," "endomembranal organization," or "endoplasmic reticulum stress response" at day 3. At day 7, 42 proteins, mainly associated with response to drug, organic substance, or radiation, were specifically upregulated in 25 Gy. DEP analysis of cardiac conduction showed Ryr2 and Cav1 upregulation and Cacna2d2, Gja3, Scnb2, and Kcnn3 downregulation in the 25 Gy group compared to 0 Gy. In validation experiments, four proteins (Gsta1, Myot, Ephx1, and Capg) were repeatedly detected with 25 Gy-specific patterns at day 7. Conclusions: 25 Gy single fractional irradiation induces considerable cardiac proteome changes within the first 7 days, distinct from 2 Gy. Several candidate proteins displayed 25 Gy-specific changes and were related to oxidative stress-induced innate response or cardiac remodeling processes. Future studies should explore the specific role of these proteins upon cardiac radioablation.