Large-scale Profiling Research Articles

Development and application of a LC-HRMS method for simultaneous determination of ten illicit antifungal drugs in herbal bacteriostatic products.

The widespread use of sub-therapeutic antibiotics may lead to treatment failures, increased resistance to antibiotics, and even the encouragement of the formation of superbugs. Fraudulent herbal medicines that actually contain unlabeled active ingredients are a global problem. Therefore, streamlined and accurate analytical techniques that can identify and quantify a variety of antimicrobials in suspected illegal products are required. In the present work, we developed a sensitive, robust, and accurate method that involves multi-step extraction, EMR-lipid-based pass-through cleanup, and UHPLC-Q/HRMS with an orbital ion trap instrument analysis for the simultaneous detection of ten illicit antifungal drugs (flucytosine, fluconazole, ketoconazole, naftifine hydrochloride, griseofulvin, bifonazole, econazole nitrate, elubiol, clotrimazole, and miconazole nitrate) in herbal disinfection products. This validated method was then applied to 210 authentic samples, resulting in 25% of the samples being positive for the drugs. The results suggested the need to strengthen controls in this field to detect illicit antifungal drugs in herbal bacteriostatic products, which represents a potential health risk for the consumer. On a global scale, more and more frequent routine monitoring is being carried out in this area. This study provides valuable insights into large-scale complex sample chemical profiling, and the method developed appears to be promising and applicable for high-throughput routine multiple antibiotic analysis in a complex sample matrix.

Large-scale single-nuclei profiling identifies role for ATRNL1 in atrial fibrillation

Atrial fibrillation (AF) is the most common sustained arrhythmia in humans, yet the molecular basis of AF remains incompletely understood. To determine the cell type-specific transcriptional changes underlying AF, we perform single-nucleus RNA-seq (snRNA-seq) on left atrial (LA) samples from patients with AF and controls. From more than 175,000 nuclei we find that only cardiomyocytes (CMs) and macrophages (MΦs) have a significant number of differentially expressed genes in patients with AF. Attractin Like 1 (ATRNL1) was overexpressed in CMs among patients with AF and localized to the intercalated disks. Further, in both knockdown and overexpression experiments we identify a potent role for ATRNL1 in cell stress response, and in the modulation of the cardiac action potential. Finally, we detect an unexpected expression pattern for a leading AF candidate gene, KCNN3. In sum, we uncover a role for ATRNL1 which may serve as potential therapeutic target for this common arrhythmia.

Lasy-Seq: A High-Throughput 3' RNA-Seq Method for Large-Scale Transcriptome Profiling in Rice.

Lasy-Seq (low-cost and easy RNA-seq) is a high-throughput library preparation method for 3' RNA-seq. Usage of oligo(dT) primers with unique index sequences allows simultaneous reverse transcription (RT) reaction and sample indexing. Therefore, each post-RT step, which was performed on a sample-by-sample basis in a conventional method, can be performed on a large number of samples together in a single tube. With the Lasy-Seq, the sequencing-ready library pool can be prepared from a few to several hundred samples in a few days.

Identification of small molecule agonists of fetal hemoglobin expression for the treatment of sickle cell disease.

Induction of fetal hemoglobin (HbF) has been shown to be a viable therapeutic approach to treating sickle cell disease and potentially other β-hemoglobinopathies. To identify targets and target-modulating small molecules that enhance HbF expression, we engineered a human umbilical-derived erythroid progenitor reporter cell line (HUDEP2_HBG1_HiBiT) by genetically tagging a HiBiT peptide to the carboxyl (C)-terminus of the endogenous HBG1 gene locus, which codes for γ-globin protein, a component of HbF. Employing this reporter cell line, we performed a chemogenomic screen of approximately 5000 compounds annotated with known targets or mechanisms that have achieved clinical stage or approval by the US Food and Drug Administration (FDA). Among them, 10 compounds were confirmed for their ability to induce HbF in the HUDEP2 cell line. These include several known HbF inducers, such as pomalidomide, lenalidomide, decitabine, idoxuridine, and azacytidine, which validate the translational nature of this screening platform. We identified avadomide, autophinib, triciribine, and R574 as novel HbF inducers from these screens. We orthogonally confirmed HbF induction activities of the top hits in both parental HUDEP2 cells as well as in human primary CD34+ hematopoietic stem and progenitor cells (HSPCs). Further, we demonstrated that pomalidomide and avadomide, but not idoxuridine, induced HbF expression through downregulation of several transcriptional repressors such as BCL11A, ZBTB7A, and IKZF1. These studies demonstrate a robust phenotypic screening workflow that can be applied to large-scale small molecule profiling campaigns for the discovery of targets and pathways, as well as novel therapeutics for sickle cell disease and other β-hemoglobinopathies.

Large-scale proteomic profiling reveals characteristic HIV-specific druggable protein signatures associated with incident heart failure

Abstract Background Compared with the general population, persons with HIV suffer from an augmented risk of both systolic and diastolic heart failure despite effective antiretroviral therapy [1]. While inflammatory and coagulation markers are thought to be involved in this increased risk, other contributing mechanisms, such as pro-inflammatory protein networks, remain to be elucidated. Purpose To identify novel protein predictors of incident heart failure events in the longitudinal Veterans Aging Cohort Study Biomarker Cohort of United States Veterans with HIV (PLWH; n = 1525) and without HIV (PWoH; n = 853) and to assess the functional relatedness of these proteins in PLWH. Methods We characterized the plasma proteome of PLWH and PWoH using an aptamer-based platform and assessed univariable associations with incident heart failure. Druggable proteins were identified using the Therapeutic Target Database [2]. We built a protein interaction network querying significant proteins (q-value <0.05) using Cytoscape for the Retrieval of Interacting Genes/Proteins (STRING) database [3]. To focus on densely connected core proteins, we used the mcl clustering method and identified a subnetwork of approximately 77 proteins. Over-representation analysis was performed for the core network by identifying enriched gene sets using Gene Ontology biological processes and WikiPathways. Final results are filtered based on a false discovery rate (FDR) threshold of 0.05. Results Of 4926 plasma proteins, 441 proteins in all PLWH and 706 in those with well-controlled HIV (viral load <200 copies/mL) were significantly associated with incident heart failure, compared with only 142 among PWoH (Figure 1A). Of the top 50 proteins most significantly associated with heart failure, 21 were druggable in PLWH and 14 in PWoH; only 5 druggable markers were shared, while 16 were unique to HIV (Table 1). Pleiotrophin, a pro-angiogenic, pro-inflammatory cytokine that induces tumor necrosis factor- (TNF) α, interleukin- (IL) 1β, and IL-6 expression and has been implicated in cardiomyocyte apoptosis [4,5], had the highest hazard ratio (HR) for incident heart failure (HR = 4.7; p = 1.6E-20; q = 1.7E-18) in PLWH. The most significant enriched protein pathway included 36 genes involved in chemotaxis (FDR = 1.3E-30); 3 of the 21 druggable targets (pleiotrophin, ephrin-A5, and ephrin type-A receptor 2) were represented in this pathway (Figure 1B). Ephrin signaling pathways, which are involved in cell adhesion, differentiation, and proliferation [6], have not previously been implicated in heart failure, nor in HIV. Subnetwork analysis of druggable proteins demonstrated that ephrin-signaling, IL-15, and TNF pathways were functionally interconnected (Figure 1C). Conclusions Our findings indicate that there may be unique pro-inflammatory pathways characteristic of HIV-associated cardiomyopathy that merit further study as dedicated pharmacologic targets and/or risk markers in this population.

Daily glycome and transcriptome profiling reveals polysaccharide structures and correlated glycosyltransferases critical for cotton fiber growth.

Cotton fiber is the most valuable naturally available material for the textile industry and the fiber length and strength are key determinants of its quality. Dynamic changes in the pectin, xyloglucan, xylan, and cellulose polysaccharide epitope content during fiber growth contribute to complex remodeling of fiber cell wall (CW) and quality. Detailed knowledge about polysaccharide compositional and structural alteration in the fiber during fiber elongation and strengthening is important to understand the molecular dynamics of fiber development and improve its quality. Here, large-scale glycome profiling coupled with fiber phenotype and transcriptome profiling was conducted on fiber collected daily covering the most critical window of fiber development. The profiling studies with high temporal resolution allowed us to identify specific polysaccharide epitopes associated with distinct fiber phenotypes that might contribute to fiber quality. This study revealed the critical role of highly branched RG-I pectin epitopes such as β-1,4-linked-galactans, β-1,6-linked-galactans, and arabinogalactans, in addition to earlier reported homogalacturonans and xyloglucans in the formation of cotton fiber middle lamella and contributing to fiber plasticity and elongation. We also propose the essential role of heteroxylans (Xyl-MeGlcA and Xyl-3Ar), as a guiding factor for secondary CW cellulose microfibril arrangement, thus contributing to fiber strength. Correlation analysis of profiles of polysaccharide epitopes from glycome data and expression profiles of glycosyltransferase-encoding genes from transcriptome data identified several key putative glycosyltransferases that are potentially involved in synthesizing the critical polysaccharide epitopes. The findings of this study provide a foundation to identify molecular factors that dictate important fiber traits.

Retinal Proteome Profiling of Inherited Retinal Degeneration Across Three Different Mouse Models Suggests Common Drug Targets in Retinitis Pigmentosa

Inherited retinal degenerations (IRDs) are a leading cause of blindness among the population of young people in the developed world. Approximately half of IRDs initially manifest as gradual loss of night vision and visual fields, characteristic of retinitis pigmentosa (RP). Due to challenges in genetic testing, and the large heterogeneity of mutations underlying RP, targeted gene therapies are an impractical largescale solution in the foreseeable future. For this reason, identifying key pathophysiological pathways in IRDs that could be targets for mutation-agnostic and disease-modifying therapies (DMTs) is warranted. In this study, we investigated the retinal proteome of three distinct IRD mouse models, in comparison to sex- and age-matched wild-type mice. Specifically, we used the Pde6βRd10 (rd10) and RhoP23H/WT (P23H) mouse models of autosomal recessive and autosomal dominant RP, respectively, as well as the Rpe65-/- mouse model of Leber's congenital amaurosis type 2 (LCA2). The mice were housed at two distinct institutions and analyzed using LC-MS in three separate facilities/instruments following data-dependent and data-independent acquisition modes. This cross-institutional and multi-methodological approach signifies the reliability and reproducibility of the results. The large-scale profiling of the retinal proteome, coupled with invivo electroretinography recordings, provided us with a reliable basis for comparing the disease phenotypes and severity. Despite evident inflammation, cellular stress, and downscaled phototransduction observed consistently across all three models, the underlying pathologies of RP and LCA2 displayed many differences, sharing only four general KEGG pathways. The opposite is true for the two RP models in which we identify remarkable convergence in proteomic phenotype even though the mechanism of primary rod death in rd10 and P23H mice is different. Our data highlights the cAMP and cGMP second-messenger signaling pathways as potential targets for therapeutic intervention. The proteomic data is curated and made publicly available, facilitating the discovery of universal therapeutic targets for RP.

An initial game-theoretic assessment of enhanced tissue preparation and imaging protocols for improved deep learning inference of spatial transcriptomics from tissue morphology.

The application of deep learning to spatial transcriptomics (ST) can reveal relationships between gene expression and tissue architecture. Prior work has demonstrated that inferring gene expression from tissue histomorphology can discern these spatial molecular markers to enable population scale studies, reducing the fiscal barriers associated with large-scale spatial profiling. However, while most improvements in algorithmic performance have focused on improving model architectures, little is known about how the quality of tissue preparation and imaging can affect deep learning model training for spatial inference from morphology and its potential for widespread clinical adoption. Prior studies for ST inference from histology typically utilize manually stained frozen sections with imaging on non-clinical grade scanners. Training such models on ST cohorts is also costly. We hypothesize that adopting tissue processing and imaging practices that mirror standards for clinical implementation (permanent sections, automated tissue staining, and clinical grade scanning) can significantly improve model performance. An enhanced specimen processing and imaging protocol was developed for deep learning-based ST inference from morphology. This protocol featured the Visium CytAssist assay to permit automated hematoxylin and eosin staining (e.g. Leica Bond), 40×-resolution imaging, and joining of multiple patients' tissue sections per capture area prior to ST profiling. Using a cohort of 13 pathologic T Stage-III stage colorectal cancer patients, we compared the performance of models trained on slide prepared using enhanced versus traditional (i.e. manual staining and low-resolution imaging) protocols. Leveraging Inceptionv3 neural networks, we predicted gene expression across serial, histologically-matched tissue sections using whole slide images (WSI) from both protocols. The data Shapley was used to quantify and compare marginal performance gains on a patient-by-patient basis attributed to using the enhanced protocol versus the actual costs of spatial profiling. Findings indicate that training and validating on WSI acquired through the enhanced protocol as opposed to the traditional method resulted in improved performance at lower fiscal cost. In the realm of ST, the enhancement of deep learning architectures frequently captures the spotlight; however, the significance of specimen processing and imaging is often understated. This research, informed through a game-theoretic lens, underscores the substantial impact that specimen preparation/imaging can have on spatial transcriptomic inference from morphology. It is essential to integrate such optimized processing protocols to facilitate the identification of prognostic markers at a larger scale.

1036P Large-scale cellular profiling of 1283 cancer patients reveals a NK cell-mediated immunosuppressive tumor microenvironment in immunotherapy resistance

1036P Large-scale cellular profiling of 1283 cancer patients reveals a NK cell-mediated immunosuppressive tumor microenvironment in immunotherapy resistance

PSXIII-11 Large-scale profiling of non-conventional peptides in several tissues of Yak (Bos mutus) by peptidogenomic pipeline

PSXIII-11 Large-scale profiling of non-conventional peptides in several tissues of Yak (<i>Bos mutus</i>) by peptidogenomic pipeline

When do I ask for a DNA methylation array for primary brain tumor diagnosis?

Despite remarkable advances in molecular characterization, the diagnosis of brain tumors remains challenging, particularly in cases with ambiguous histology or contradictory molecular features. In this context, DNA methylation profiling plays an important role in improving diagnostic and prognostic accuracy. This review aims to provide diagnostic guidance regarding when DNA methylation arrays represent a useful tool for the diagnosis of primary brain tumors. Large-scale profiling has revealed that DNA methylation profiles of brain tumors are highly reproducible and stable. Therefore, DNA methylation profiling has been successfully used to classify brain tumors and identify new entities. This approach seems to be particularly promising for heterogeneous groups of tumors, such as IDH-wildtype gliomas, and glioneuronal and embryonal tumors, which include a variety of entities that are still under characterization. As underlined in the fifth edition of the WHO classification of central nervous system tumors, the diagnosis of brain tumors requires the integration of histological, molecular, clinical, and radiological features. Although advanced imaging and histological examination remain the standard diagnostic tools, DNA methylation analysis can significantly improve diagnostic accuracy, with a substantial impact on patient management.

Large-scale CSF proteome profiling identifies biomarkers for accurate diagnosis of Frontotemporal Dementia.

Diagnosis of Frontotemporal dementia (FTD) and the specific underlying neuropathologies (frontotemporal lobar degeneration; FTLD- Tau and FTLD-TDP) is challenging, and thus fluid biomarkers are needed to improve diagnostic accuracy. We used proximity extension assays to analyze 665 proteins in cerebrospinal fluid (CSF) samples from a multicenter cohort including patients with FTD (n = 189), Alzheimer's Disease dementia (AD; n = 232), and cognitively unimpaired individuals (n = 196). In a subset, FTLD neuropathology was determined based on phenotype or genotype (FTLD-Tau = 87 and FTLD-TDP = 68). Forty three proteins were differentially regulated in FTD compared to controls and AD, reflecting axon development, regulation of synapse assembly, and cell-cell adhesion mediator activity pathways. Classification analysis identified a 14- and 13-CSF protein panel that discriminated FTD from controls (AUC: 0.96) or AD (AUC: 0.91). Custom multiplex panels confirmed the highly accurate discrimination between FTD and controls (AUCs > 0.96) or AD (AUCs > 0.88) in three validation cohorts, including one with autopsy confirmation (AUCs > 0.90). Six proteins were differentially regulated between FTLD-TDP and FTLD-Tau, but no reproducible classification model could be generated (AUC: 0.80). Overall, this study introduces novel FTD-specific biomarker panels with potential use in diagnostic setting.

Site-specific N-glycoproteomic analysis reveals up-regulated fucosylation in seminal plasma of asthenozoospermia.

N-linked glycoproteins are rich in seminal plasma, playing essential roles in supporting sperm function and fertilization process. The alteration of seminal plasma glycans and its correspond glycoproteins may lead to sperm dysfunction and even infertility. In present study, an integrative analysis of glycoproteomic and proteomic was performed to investigate the changes of site-specific glycans and glycoptoteins in seminal plasma of asthenozoospermia. By large scale profiling and quantifying 5,018 intact N-glycopeptides in seminal plasma, we identified 92 intact N-glycopeptides from 34 glycoproteins changed in asthenozoospermia. Especially, fucosylated glycans containing lewis x, lewis y and core fucosylation were significantly up-regulated in asthenozoospermia compared to healthy donors. The up-regulation of fucosylated glycans in seminal plasma may interfere sperm surface compositions and regulation of immune response, which subsequently disrupts sperm function. Three differentiated expression of seminal vesicle-specific glycoproteins (fibronectin, seminogelin-2, and glycodelin) were also detected with fucosylation alteration in seminal plasma of asthenozoospermia. The interpretation of the altered site-specific glycan structures provides data for the diagnosis and etiology analysis of male infertility, as well as providing new insights into the potential therapeutic targets for male infertility.

Sall4 regulates downstream patterning genes during limb regeneration

Many salamanders can completely regenerate a fully functional limb. Limb regeneration is a carefully coordinated process involving several defined stages. One key event during the regeneration process is the patterning of the blastema to inform cells of what they must differentiate into. Although it is known that many genes involved in the initial development of the limb are re-used during regeneration, the exact molecular circuitry involved in this process is not fully understood. Several large-scale transcriptional profiling studies of axolotl limb regeneration have identified many transcription factors that are up-regulated after limb amputation. Sall4 is a transcription factor that has been identified to play essential roles in maintaining cells in an undifferentiated state during development and also plays a unique role in limb development. Inactivation of Sall4 during limb bud development results in defects in anterior-posterior patterning of the limb. Sall4 has been found to be up-regulated during limb regeneration in both Xenopus and salamanders, but to date it function has been untested. We confirmed that Sall4 is up-regulated during limb regeneration in the axolotl using qRT-PCR and identified that it is present in the skin cells and also in cells within the blastema. Using CRISPR technology we microinjected gRNAs specific for Sall4 complexed with cas9 protein into the blastema to specifically knockout Sall4 in blastema cells only. This resulted in limb regenerate defects, including missing digits, fusion of digit elements, and defects in the radius and ulna. This suggests that during regeneration Sall4 may play a similar role in regulating the specification of anterior-proximal skeletal elements.

High-fidelity, large-scale targeted profiling of microsatellites.

Microsatellites are highly mutable sequences that can serve as markers for relationships among individuals or cells within a population. The accuracy and resolution of reconstructing these relationships depends on the fidelity of microsatellite profiling and the number of microsatellites profiled. However, current methods for targeted profiling of microsatellites incur significant "stutter" artifacts that interfere with accurate genotyping, and sequencing costs preclude whole-genome microsatellite profiling of a large number of samples. We developed a novel method for accurate and cost-effective targeted profiling of a panel of more than 150,000 microsatellites per sample, along with a computational tool for designing large-scale microsatellite panels. Our method addresses the greatest challenge for microsatellite profiling-"stutter" artifacts-with a low-temperature hybridization capture that significantly reduces these artifacts. We also developed a computational tool for accurate genotyping of the resulting microsatellite sequencing data that uses an ensemble approach integrating three microsatellite genotyping tools, which we optimize by analysis of de novo microsatellite mutations in human trios. Altogether, our suite of experimental and computational tools enables high-fidelity, large-scale profiling of microsatellites, which may find utility in diverse applications such as lineage tracing, population genetics, ecology, and forensics.

The maintenance of oocytes in the mammalian ovary involves extreme protein longevity

Women are born with all of their oocytes. The oocyte proteome must be maintained with minimal damage throughout the woman’s reproductive life, and hence for decades. Here we report that oocyte and ovarian proteostasis involves extreme protein longevity. Mouse ovaries had more extremely long-lived proteins than other tissues, including brain. These long-lived proteins had diverse functions, including in mitochondria, the cytoskeleton, chromatin and proteostasis. The stable proteins resided not only in oocytes but also in long-lived ovarian somatic cells. Our data suggest that mammals increase protein longevity and enhance proteostasis by chaperones and cellular antioxidants to maintain the female germline for long periods. Indeed, protein aggregation in oocytes did not increase with age and proteasome activity did not decay. However, increasing protein longevity cannot fully block female germline senescence. Large-scale proteome profiling of ~8,890 proteins revealed a decline in many long-lived proteins of the proteostasis network in the aging ovary, accompanied by massive proteome remodeling, which eventually leads to female fertility decline.

Integrated Platform for Large-Scale Quantitative Profiling of Phosphotyrosine Signaling Complexes Based on Cofractionation/Mass Spectrometry and Complex-Centric Algorithm.

The scarcity and dynamic nature of phosphotyrosine (pTyr)-modified proteins pose a challenge for researching protein complexes with pTyr modification, which are assembled through multiple protein-protein interactions. We developed an integrated complex-centric platform for large-scale quantitative profiling of pTyr signaling complexes based on cofractionation/mass spectrometry (CoFrac-MS) and a complex-centric algorithm. We initially constructed a trifunctional probe based on pTyr superbinder (SH2-S) for specifically binding and isolation of intact pTyr protein complexes. Then, the CoFrac-MS strategy was employed for the identification of pTyr protein complexes by integrating ion exchange chromatography in conjunction with data independent acquisition mass spectrometry. Furthermore, we developed a novel complex-centric algorithm for quantifying protein complexes based on the protein complex elution curve. Utilizing this algorithm, we effectively quantified 216 putative protein complexes. We further screened 21 regulated pTyr protein complexes related to the epidermal growth factor signal. Our study engenders a comprehensive framework for the intricate examination of pTyr protein complexes and presents, for the foremost occasion, a quantitative landscape delineating the composition of pTyr protein complexes in HeLa cells.

Glyco-signatures in patients with advanced lung cancer during anti-PD-1/PD-L1 immunotherapy.

Immune checkpoint inhibitors (ICIs) targeting programmed cell death 1/programmed cell death ligand-1 (PD-1/PD-L1) have significantly prolonged the survival of advanced/metastatic patients with lung cancer. However, only a small proportion of patients can benefit from ICIs, and clinical management of the treatment process remains challenging. Glycosylation has added a new dimension to advance our understanding of tumor immunity and immunotherapy. To systematically characterize anti-PD-1/PD-L1 immunotherapy-related changes in serum glycoproteins, a series of serum samples from 12 patients with metastatic lung squamous cell carcinoma (SCC) and lung adenocarcinoma (ADC), collected before and during ICIs treatment, are firstly analyzed with mass-spectrometry-based label-free quantification method. Second, a stratification analysis is performed among anti-PD-1/PD-L1 responders and non-responders, with serum levels of glycopeptides correlated with treatment response. In addition, in an independent validation cohort, a large-scale site-specific profiling strategy based on chemical labeling is employed to confirm the unusual characteristics of IgG N-glycosylation associated with anti-PD-1/PD-L1 treatment. Unbiased label-free quantitative glycoproteomics reveals serum levels' alterations related to anti-PD-1/PD-L1 treatment in 27 out of 337 quantified glycopeptides. The intact glycopeptide EEQFN 177STYR (H3N4) corresponding to IgG4 is significantly increased during anti-PD-1/PD-L1 treatment (FC=2.65, P=0.0083) and has the highest increase in anti-PD-1/PD-L1 responders (FC=5.84, P=0.0190). Quantitative glycoproteomics based on protein purification and chemical labeling confirms this observation. Furthermore, obvious associations between the two intact glycopeptides (EEQFN 177STYR (H3N4) of IgG4, EEQYN 227STFR (H3N4F1) of IgG3) and response to treatment are observed, which may play a guiding role in cancer immunotherapy. Our findings could benefit future clinical disease management.

Abstract 2999: Evaluation of microRNA expression in metastatic and non-metastatic salivary gland mucoepidermoid carcinoma

Abstract Salivary gland tumors are a heterogeneous group of lesions, being mucoepidermoid carcinoma (MEC) the malignant neoplasm with the highest incidence, occurring mainly in the parotid gland. Characterization of its histological grade (high, intermediate, and low) is important for determining patient prognosis. Metastasis is more common high-grade tumors and can occur at regional lymph nodes or distant sites. Although the mechanisms underlying the metastatic process are largely unknown, large-scale microRNA expression profiling studies of human cancers have demonstrated that dysregulation of miRNA is frequently associated with many cancer types. The aim of this study is to validate the use of microRNA expression for the discrimination of the metastatic potential of MEC samples. Using Real Time RT-PCR (qPCR) we have analyzed the expression of 384 miRNAs and controls in 4 non-metastatic MECs, 3 MECs with lymph node metastasis, 3 MECs with distant metastasis, and 2 non-neoplastic human salivary gland samples. Comparing the expression among these groups we identified 45 differentially expressed miRNAs that may be related with the metastatic potential of these tumors. To validate the microRNA expression associated with the metastatic potential, we selected 7 out of the 45 differentially expressed microRNAs and 7 MEC samples from the different groups of samples. Considering the 7 microRNAs evaluated, we validated that the expression of miR-191 was increased in non-neoplastic samples when compared to MECs with lymph node metastasis and the expression of miR-494 was increased in non-neoplastic samples when compared to MECs with distant metastasis, suggesting that loss of these microRNAs might be involved in the development of metastasis in mucoepidermoid carcinoma. The determination of a miRNA expression profile could provide a better understanding of the molecular basis of MEC and facilitate the determination of diagnosis and prognosis of patients. Citation Format: Maria E. Trevizani, Katia K. Oliveira, Fabio A. Marchi, Daniela Bizinelli, Fernanda V. Mariano, Cibele P. Nagano, Felipe A. Costa, Clovis A. Pinto, Luiz P. Kowalski, Silvia V. Lourenço, Cláudia M. Coutinho-Camillo. Evaluation of microRNA expression in metastatic and non-metastatic salivary gland mucoepidermoid carcinoma [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 2999.

Large-Scale Proteome Profiling Identifies Biomarkers Associated with Suspected Neurosyphilis Diagnosis.

Neurosyphilis (NS) is a central nervous system (CNS) infection caused by Treponema pallidum (T. pallidum). NS can occur at any stage of syphilis and manifests as a broad spectrum of clinical symptoms. Often referred to as "the great imitator," NS can be easily overlooked or misdiagnosed due to the absence of standard diagnostic tests, potentially leading to severe and irreversible organ dysfunction. In this study, proteomic and machine learning model techniques are used to characterize 223 cerebrospinal fluid (CSF) samples to identify diagnostic markers of NS and provide insights into the underlying mechanisms of the associated inflammatory responses. Three biomarkers (SEMA7A, SERPINA3, and ITIH4) are validated as contributors to NS diagnosis through multicenter verification of an additional 115 CSF samples. We anticipate that the identified biomarkers will become effective tools for assisting in diagnosis of NS. Our insights into NS pathogenesis in brain tissue may inform therapeutic strategies and drug discoveries for NS patients.