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.

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.

Comparison of Breast Fine-Needle Aspiration Cytology and Tissue Sampling for High-Throughput Proteomic Analysis and Cancer Biomarker Detection.

INTRODUCTION: Fine-needle aspiration cytology (FNAC) specimens are widely utilized for the diagnosis and molecular testing of various cancers. We performed a comparative proteomic analysis of three different sample types, including breast FNAC, core needle biopsy (CNB), and surgical resection tissues. Our goal was to evaluate the suitability of FNAC for in-depth proteomic analysis and for identifying potential therapeutic biomarkers in breast cancer. METHODS: High-throughput proteomic analysis was conducted on matched FNAC, CNB, and surgical resection tissue samples obtained from breast cancer patients. The protein identification, including currently established or promising therapeutic targets, was compared among the three different sample types. Gene Ontology (GO) enrichment analysis was also performed on all matched samples. RESULTS: Compared to tissue samples, FNAC testing revealed a comparable number of proteins (7,179 in FNAC; 7,196 in CNB; and 7,190 in resection samples). Around 85% of proteins were mutually identified in all sample types. FNAC, along with CNB, showed a positive correlation between the number of enrolled tumor cells and identified proteins. In the GO analysis, the FNAC samples demonstrated a higher number of genes for each pathway and GO terms than tissue samples. CCND1, CDK6, HER2, and IGF1R were found in higher quantities in the FNAC compared to tissue samples, while TUBB2A was only detected in the former. CONCLUSION: FNAC is suitable for high-throughput proteomic analysis, in addition to an emerging source that could be used to identify and quantify novel cancer biomarkers.

The N-terminal cysteine is a dual sensor of oxygen and oxidative stress.

Cellular homeostasis requires the sensing of and adaptation to intracellular oxygen (O2) and reactive oxygen species (ROS). The Arg/N-degron pathway targets proteins that bear destabilizing N-terminal residues for degradation by the proteasome or via autophagy. Under normoxic conditions, the N-terminal Cys (Nt-Cys) residues of specific substrates can be oxidized by dioxygenases such as plant cysteine oxidases and cysteamine (2-aminoethanethiol) dioxygenases and arginylated by ATE1 R-transferases to generate Arg-CysO2(H) (R-CO2). Proteins bearing the R-CO2 N-degron are targeted via Lys48 (K48)-linked ubiquitylation by UBR1/UBR2 N-recognins for proteasomal degradation. During acute hypoxia, such proteins are partially stabilized, owing to decreased Nt-Cys oxidation. Here, we show that if hypoxia is prolonged, the Nt-Cys of regulatory proteins can be chemically oxidized by ROS to generate Arg-CysO3(H) (R-CO3), a lysosomal N-degron. The resulting R-CO3 is bound by KCMF1, a N-recognin that induces K63-linked ubiquitylation, followed by K27-linked ubiquitylation by the noncanonical N-recognin UBR4. Autophagic targeting of Cys/N-degron substrates is mediated by the autophagic N-recognin p62/SQTSM-1/Sequestosome-1 through recognition of K27/K63-linked ubiquitin (Ub) chains. This Cys/N-degron-dependent reprogramming in the proteolytic flux is important for cellular homeostasis under both chronic hypoxia and oxidative stress. A small-compound ligand of p62 is cytoprotective under oxidative stress through its ability to accelerate proteolytic flux of K27/K63-ubiquitylated Cys/N-degron substrates. Our results suggest that the Nt-Cys of conditional Cys/N-degron substrates acts as an acceptor of O2 to maintain both O2 and ROS homeostasis and modulates half-lives of substrates through either the proteasome or lysosome by reprogramming of their Ub codes.

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.

Multisample Mass Spectrometry-Based Approach for Discovering Injury Markers in Chronic Kidney Disease.

Urinary proteomics studies have primarily focused on identifying markers of chronic kidney disease (CKD) progression. Here, we aimed to determine urinary markers of CKD renal parenchymal injury through proteomics analysis in animal kidney tissues and cells and in the urine of patients with CKD. Label-free quantitative proteomics analysis based on liquid chromatography-tandem mass spectrometry was performed on urine samples obtained from 6 normal controls and 9, 11, and 10 patients with CKD stages 1, 3, and 5, respectively, and on kidney tissue samples from a rat CKD model by 5/6 nephrectomy. Tandem mass tag-based quantitative proteomics analysis was performed for glomerular endothelial cells (GECs) and proximal tubular epithelial cells (PTECs) before and after inducing 24-h hypoxia injury. Upon hierarchical clustering, out of 858 differentially expressed proteins (DEPs) in the urine of CKD patients, the levels of 416 decreased and 403 increased sequentially according to the disease stage, respectively. Among 2965 DEPs across 5/6 nephrectomized and sham-operated rat kidney tissues, 86 DEPs showed same expression patterns in the urine and kidney tissue. After cross-validation with two external animal proteome data sets, 38 DEPs were organized; only ten DEPs, including serotransferrin, gelsolin, poly ADP-ribose polymerase 1, neuroblast differentiation-associated protein AHNAK, microtubule-associated protein 4, galectin-1, protein S, thymosin beta-4, myristoylated alanine-rich C-kinase substrate, and vimentin, were finalized by screening human GECs and PTECs data. Among these ten potential candidates for universal CKD marker, validation analyses for protein S and galectin-1 were conducted. Galectin-1 was observed to have a significant inverse correlation with renal function as well as higher expression in glomerulus with chronic injury than protein S. This constitutes the first multisample proteomics study for identifying key renal-expressed proteins associated with CKD progression. The discovered proteins represent potential markers of chronic renal cell and tissue damage and candidate contributors to CKD pathophysiology.

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.

Aggresomal sequestration and STUB1-mediated ubiquitylation during mammalian proteaphagy of inhibited proteasomes.

The 26S proteasome, a self-compartmentalized protease complex, plays a crucial role in protein quality control. Multiple levels of regulatory systems modulate proteasomal activity for substrate hydrolysis. However, the destruction mechanism of mammalian proteasomes is poorly understood. We found that inhibited proteasomes are sequestered into the insoluble aggresome via HDAC6- and dynein-mediated transport. These proteasomes colocalized with the autophagic receptor SQSTM1 and cleared through selective macroautophagy, linking aggresomal segregation to autophagic degradation. This proteaphagic pathway was counterbalanced with the recovery of proteasomal activity and was critical for reducing cellular proteasomal stress. Changes in associated proteins and polyubiquitylation on inhibited 26S proteasomes participated in the targeting mechanism to the aggresome and autophagosome. The STUB1 E3 Ub ligase specifically ubiquitylated purified human proteasomes in vitro, mainly via Lys63-linked chains. Genetic and chemical inhibition of STUB1 activity significantly impaired proteasome processing and reduced resistance to proteasomal stress. These data demonstrate that aggresomal sequestration is the crucial upstream event for proteasome quality control and overall protein homeostasis in mammals.

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.

Altered secretome by diesel exhaust particles and lipopolysaccharide in primary human nasal epithelium.

BACKGROUND: Airway epithelial cells can actively participate in the defense against environmental pathogens to elicit local or systemic inflammation. Diesel exhaust particles (DEP), a main component of urban air pollution with particulate matter, are associated with the occurrence of acute and chronic upper airway inflammatory diseases. OBJECTIVES: We sought to investigate the effect of DEP alone or in combination with lipopolysaccharide on the secretome in the primary human nasal epithelium (PHNE) and to find potential biomarkers to relate DEP exposure to upper airway inflammatory diseases. METHODS: PHNE was cultured at an air-liquid interface to create a differentiated in vivo-like model. Secreted proteins (secretome) on the bottom media of the PHNE were analyzed by mass spectrometry-based label-free quantitative proteomics and ELISA. RESULTS: Considerably more differentially expressed secreted proteins were identified in response to DEP plus lipopolysaccharide than to DEP alone. Some canonical pathways related to inflammation and cancer such as the p53, ß-catenin, and extracellular signal-regulated kinase 1/2 pathways were involved. Among differentially expressed secreted proteins, leukemia inhibitory factor was also detected at a high level in the middle ear effusions of otitis media patients, and the leukemia inhibitory factor level was significantly correlated with daily mean mass concentrations of atmospheric particulate matter averaged over 8 days before sample collection. CONCLUSIONS: Apical stimulation with DEP and lipopolysaccharide can significantly alter the basal secretome in PHNE, and this alteration can be reflected by surrounding inflammation with effusion of fluids in vivo such as middle ear effusions in otitis media patients.

CaV α2δ Autoimmune Encephalitis: A Novel Antibody and its Characteristics.

OBJECTIVE: Discovery of a novel antibody would enable diagnosis and early treatment of autoimmune encephalitis. The aim was to discover a novel antibody targeting a synaptic receptor and characterize the pathogenic mechanism. METHOD: We screened for unknown antibodies in serum and cerebrospinal fluid samples from autoimmune encephalitis patients. Samples with reactivity to rat brain sections and no reactivity to conventional antibody tests underwent further processing for antibody discovery, using immunoprecipitation to primary neuronal cells, mass-spectrometry analysis, an antigen-binding assay on an antigen-overexpressing cell line, and an electrophysiological assay with cultured hippocampal neurons. RESULTS: Two patients had a novel antibody against CaV α2δ (voltage-gated calcium channel alpha-2/delta subunit). The patient samples stained neuropils of the hippocampus, basal ganglia, and cortex in rat brain sections and bound to a CaV α2δ-overexpressing cell line. Knockdown of CaV α2δ expression in cultured neurons turned off the immunoreactivity of the antibody from the patients to the neurons. The patients were associated with preceding meningitis or neuroendocrine carcinoma and responded to immunotherapy. In cultured neurons, the antibody reduced neurotransmitter release from presynaptic nerve terminals by interfering with tight coupling of calcium channels and exocytosis. INTERPRETATION: Here, we discovered a novel autoimmune encephalitis associated with anti-CaV α2δ antibody. Further analysis of the antibody in autoimmune encephalitis might promote early diagnosis and treatment. ANN NEUROL 2021;89:740-752.

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.

Discovery of Proteins Responsible for Resistance to Three Chemotherapy Drugs in Breast Cancer Cells Using Proteomics and Bioinformatics Analysis.

Chemoresistance is a daunting obstacle to the effective treatment of breast cancer patients receiving chemotherapy. Although the mechanism of chemotherapy drug resistance has been explored broadly, the precise mechanism at the proteome level remains unclear. Especially, comparative studies between widely used anticancer drugs in breast cancer are very limited. In this study, we employed proteomics and bioinformatics approaches on chemoresistant breast cancer cell lines to understand the underlying resistance mechanisms that resulted from doxorubicin (DR), paclitaxel (PR), and tamoxifen (TAR). In total, 10,385 proteins were identified and quantified from three TMT 6-plex and one TMT 10-plex experiments. Bioinformatics analysis showed that Notch signaling, immune response, and protein re-localization processes were uniquely associated with DR, PR, and TAR resistance, respectively. In addition, proteomic signatures related to drug resistance were identified as potential targets of many FDA-approved drugs. Furthermore, we identified potential prognostic proteins with significant effects on overall survival. Representatively, PLXNB2 expression was associated with a highly significant increase in risk, and downregulation of ACOX3 was correlated with a worse overall survival rate. Consequently, our study provides new insights into the proteomic aspects of the distinct mechanisms underlying chemoresistance in breast cancer.

In-depth proteome of perilymph in guinea pig model.

The vast majority of sensorineural hearing loss is caused by impairment of the inner ear cells. Proteomic analysis of perilymph may therefore improve our understanding of inner ear diseases and hearing loss. However, the investigation of the human perilymph proteome was limited due to technical difficulties in perilymph sampling. The guinea pig (Cavia porcellus) is frequently used as an experimental model in preclinical hearing research. In this study, we analyzed samples of perilymph collected from 12 guinea pigs to overcome limited experimental information regarding its proteome. We identified a total of 1413 proteins, establishing a greatly expanded proteome of the previously inferred guinea pig perilymph. This provides a comprehensive proteomic resource for the research community, which will facilitate future molecular-phenotypic studies using the guinea pig as an experimental model of relevance to human inner ear biology.

Longitudinal proteomic profiling provides insights into host response and proteome dynamics in COVID-19 progression.

In managing patients with coronavirus disease 2019 (COVID-19), early identification of those at high risk and real-time monitoring of disease progression to severe COVID-19 is a major challenge. We aimed to identify potential early prognostic protein markers and to expand understanding of proteome dynamics during clinical progression of the disease. We performed in-depth proteome profiling on 137 sera, longitudinally collected from 25 patients with COVID-19 (non-severe patients, n = 13; patients who progressed to severe COVID-19, n = 12). We identified 11 potential biomarkers, including the novel markers IGLV3-19 and BNC2, as early potential prognostic indicators of severe COVID-19. These potential biomarkers are mainly involved in biological processes associated with humoral immune response, interferon signalling, acute phase response, lipid metabolism, and platelet degranulation. We further revealed that the longitudinal changes of 40 proteins persistently increased or decreased as the disease progressed to severe COVID-19. These 40 potential biomarkers could effectively reflect the clinical progression of the disease. Our findings provide some new insights into host response to SARS-CoV-2 infection, which are valuable for understanding of COVID-19 disease progression. This study also identified potential biomarkers that could be further validated, which may support better predicting and monitoring progression to severe COVID-19.

Quantitative Proteomics Reveals Knockdown of CD44 Promotes Proliferation and Migration in Claudin-Low MDA-MB-231 and Hs 578T Breast Cancer Cell Lines.

CD44 is a transmembrane glycoprotein that can regulate the oncogenic process. This is known to be a marker of the claudin-low subtype of breast cancer, as well as a cancer stem cell marker. However, its functional regulatory roles are poorly understood in claudin-low breast cancer. To gain comprehensive insight into the function of CD44, we performed an in-depth tandem mass tag-based proteomic analysis of two claudin-low breast cancer cell lines (MDA-MB-231 and Hs 578T) transfected with CD44 siRNA. As a result, we observed that 2736 proteins were upregulated and 2172 proteins were downregulated in CD44-knockdown MDA-MB-231 cells. For Hs 578T CD44-knockdown cells, 412 proteins were upregulated and 443 were downregulated. Gene ontology and network analyses demonstrated that the suppression of this marker mediates significant functional alterations related to oncogenic cellular processes, including proliferation, metabolism, adhesion, and gene expression regulation. A functional study confirmed that CD44 knockdown inhibited proliferation by regulating the expression of genes related to cell cycle, translation, and transcription. Moreover, this promoted the expression of multiple cell adhesion-associated proteins and attenuated cancer cell migration. Finally, our proteomic study defines the landscape of the CD44-regulated proteome of claudin-low breast cancer cells, revealing changes that mediate cell proliferation and migration. Our proteomics data set has been deposited to the ProteomeXchange Consortium via the PRIDE repository with the data set identifier PXD015171.

Parallel Reaction Monitoring-Mass Spectrometry (PRM-MS)-Based Targeted Proteomic Surrogates for Intrinsic Subtypes in Breast Cancer: Comparative Analysis with Immunohistochemical Phenotypes.

Advances in targeted medications have improved the survival rate of breast cancer patients with molecular marker-positive tumors. To date, immunohistochemistry (IHC) has remained as the standard method for quantifying the markers including HER2, ER, and PR. Nevertheless, IHC-based grading is subjective, because the results depend on trained individuals' eye rather than numerical quantities. Thus, alternative methods that can account for quantitative levels of markers are gaining popularity, including targeted proteomics by mass spectrometry (MS). However, technical limitations have impeded the application of MS-based protein quantification to pathological FFPE slides that contain low amounts of cross-linked proteins. To challenge this, we developed a parallel reaction monitoring-mass spectrometry (PRM-MS) method to measure the expression levels of breast cancer markers. After developing the method using cell lines, we performed PRM-MS using 51 individuals' FFPE samples. As a result, we obtained numerical measures of targets, quantifying 13 peptides of 4 markers in a single analysis per sample. The results correlated well with the IHC readings of experienced pathologists. Moreover, the results distinguished a gray zone in HER2 classification, which IHC alone failed to do. This proof-of-concept study demonstrates the application of targeted proteomics in pathologic slides, further supporting the applicability of MS-based approaches in precision medicine.

Combined the SMAC mimetic and BCL2 inhibitor sensitizes neoadjuvant chemotherapy by targeting necrosome complexes in tyrosine aminoacyl-tRNA synthase-positive breast cancer.

BACKGROUND: Chemotherapy is the standard treatment for breast cancer; however, the response to chemotherapy is disappointingly low. Here, we investigated the alternative therapeutic efficacy of novel combination treatment with necroptosis-inducing small molecules to overcome chemotherapeutic resistance in tyrosine aminoacyl-tRNA synthetase (YARS)-positive breast cancer. METHODS: Pre-chemotherapeutic needle biopsy of 143 invasive ductal carcinomas undergoing the same chemotherapeutic regimen was subjected to proteomic analysis. Four different machine learning algorithms were employed to determine signature protein combinations. Immunoreactive markers were selected using three common candidate proteins from the machine-learning algorithms and verified by immunohistochemistry using 123 cases of independent needle biopsy FFPE samples. The regulation of chemotherapeutic response and necroptotic cell death was assessed using lentiviral YARS overexpression and depletion 3D spheroid formation assay, viability assays, LDH release assay, flow cytometry analysis, and transmission electron microscopy. The ROS-induced metabolic dysregulation and phosphorylation of necrosome complex by YARS were assessed using oxygen consumption rate analysis, flow cytometry analysis, and 3D cell viability assay. The therapeutic roles of SMAC mimetics (LCL161) and a pan-BCL2 inhibitor (ABT-263) were determined by 3D cell viability assay and flow cytometry analysis. Additional biologic process and protein-protein interaction pathway analysis were performed using Gene Ontology annotation and Cytoscape databases. RESULTS: YARS was selected as a potential biomarker by proteomics-based machine-learning algorithms and was exclusively associated with good response to chemotherapy by subsequent immunohistochemical validation. In 3D spheroid models of breast cancer cell lines, YARS overexpression significantly improved chemotherapy response via phosphorylation of the necrosome complex. YARS-induced necroptosis sequentially mediated mitochondrial dysfunction through the overproduction of ROS in breast cancer cell lines. Combination treatment with necroptosis-inducing small molecules, including a SMAC mimetic (LCL161) and a pan-BCL2 inhibitor (ABT-263), showed therapeutic efficacy in YARS-overexpressing breast cancer cells. CONCLUSIONS: Our results indicate that, before chemotherapy, an initial screening of YARS protein expression should be performed, and YARS-positive breast cancer patients might consider the combined treatment with LCL161 and ABT-263; this could be a novel stepwise clinical approach to apply new targeted therapy in breast cancer patients in the future.

Identification of TUBB2A by quantitative proteomic analysis as a novel biomarker for the prediction of distant metastatic breast cancer.

BACKGROUND: Metastasis of breast cancer to distal organs is fatal. However, few studies have identified biomarkers that are associated with distant metastatic breast cancer. Furthermore, the inability of current biomarkers, such as HER2, ER, and PR, to differentiate between distant and nondistant metastatic breast cancers accurately has necessitated the development of novel biomarker candidates. METHODS: An integrated proteomics approach that combined filter-aided sample preparation, tandem mass tag labeling (TMT), high pH fractionation, and high-resolution MS was applied to acquire in-depth proteomic data from FFPE distant metastatic breast cancer tissues. A bioinformatics analysis was performed with regard to gene ontology and signaling pathways using differentially expressed proteins (DEPs) to examine the molecular characteristics of distant metastatic breast cancer. In addition, real-time polymerase chain reaction (RT-PCR) and invasion/migration assays were performed to validate the differential regulation and function of our protein targets. RESULTS: A total of 9441 and 8746 proteins were identified from the pooled and individual sample sets, respectively. Based on our criteria, TUBB2A was selected as a novel biomarker candidate. The metastatic activities of TUBB2A were subsequently validated. In our bioinformatics analysis using DEPs, we characterized the overall molecular features of distant metastasis and measured differences in the molecular functions of distant metastatic breast cancer between breast cancer subtypes. CONCLUSIONS: Our report is the first study to examine the distant metastatic breast cancer proteome using FFPE tissues. The depth of our dataset allowed us to discover a novel biomarker candidate and a proteomic characteristics of distant metastatic breast cancer. Distinct molecular features of various breast cancer subtypes were also established. Our proteomic data constitute a valuable resource for research on distant metastatic breast cancer.