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Type I interferons (IFN-I) exert pleiotropic biological effects during viral infections, balancing virus control versus immune-mediated pathologies, and have been successfully employed for the treatment of viral diseases. Humans express 12 IFN-alpha (α) subtypes, which activate downstream signaling cascades and result in distinct patterns of immune responses and differential antiviral responses. Inborn errors in IFN-I immunity and the presence of anti-IFN autoantibodies account for very severe courses of COVID-19; therefore, early administration of IFN-I may be protective against life-threatening disease. Here we comprehensively analyzed the antiviral activity of all IFNα subtypes against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) to identify the underlying immune signatures and explore their therapeutic potential. Prophylaxis of primary human airway epithelial cells (hAEC) with different IFNα subtypes during SARS-CoV-2 infection uncovered distinct functional classes with high, intermediate, and low antiviral IFNs. In particular, IFNα5 showed superior antiviral activity against SARS-CoV-2 infection in vitro and in SARS-CoV-2-infected mice in vivo. Dose dependency studies further displayed additive effects upon coadministration with the broad antiviral drug remdesivir in cell culture. Transcriptomic analysis of IFN-treated hAEC revealed different transcriptional signatures, uncovering distinct, intersecting, and prototypical genes of individual IFNα subtypes. Global proteomic analyses systematically assessed the abundance of specific antiviral key effector molecules which are involved in IFN-I signaling pathways, negative regulation of viral processes, and immune effector processes for the potent antiviral IFNα5. Taken together, our data provide a systemic, multimodular definition of antiviral host responses mediated by defined IFN-I. This knowledge will support the development of novel therapeutic approaches against SARS-CoV-2.
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Tratamiento Farmacológico de COVID-19 , Interferón-alfa/farmacología , SARS-CoV-2/efectos de los fármacos , Transcriptoma , Replicación Viral/efectos de los fármacos , Animales , COVID-19/inmunología , COVID-19/virología , Chlorocebus aethiops , Clonación Molecular , Modelos Animales de Enfermedad , Escherichia coli/genética , Escherichia coli/metabolismo , Perfilación de la Expresión Génica , Regulación de la Expresión Génica , Vectores Genéticos/química , Vectores Genéticos/metabolismo , Humanos , Interferón-alfa/genética , Interferón-alfa/inmunología , Ratones , Isoformas de Proteínas/clasificación , Isoformas de Proteínas/genética , Isoformas de Proteínas/inmunología , Isoformas de Proteínas/farmacología , Proteínas Recombinantes/clasificación , Proteínas Recombinantes/genética , Proteínas Recombinantes/inmunología , Proteínas Recombinantes/farmacología , SARS-CoV-2/genética , SARS-CoV-2/inmunología , Transducción de Señal , Células VeroRESUMEN
Oligodendrocytes are generated via a two-step mechanism from pluripotent neural stem cells (NSCs): after differentiation of NSCs to oligodendrocyte precursor/NG2 cells (OPCs), they further develop into mature oligodendrocytes. The first step of this differentiation process is only incompletely understood. In this study, we utilized the neurosphere assay to investigate NSC to OPC differentiation in a time course-dependent manner by mass spectrometry-based (phospho-) proteomics. We identify doublecortin-like kinase 1 (Dclk1) as one of the most prominently regulated proteins in both datasets, and show that it undergoes a gradual transition between its short/long isoform during NSC to OPC differentiation. This is regulated by phosphorylation of its SP-rich region, resulting in inhibition of proteolytic Dclk1 long cleavage, and therefore Dclk1 short generation. Through interactome analyses of different Dclk1 isoforms by proximity biotinylation, we characterize their individual putative interaction partners and substrates. All data are available via ProteomeXchange with identifier PXD040652.
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Células-Madre Neurales , Células Precursoras de Oligodendrocitos , Diferenciación Celular , Quinasas Similares a Doblecortina , Oligodendroglía , Fosforilación , Proteínas Serina-Treonina Quinasas , ProteómicaRESUMEN
BACKGROUND: Stem cell apheresis in the context of autologous stem cell transplantation requires an accurate cluster of differentiantion 34 (CD34+) count determined by flow cytometry as the current gold standard. Since flow cytometry is a personnel and time-intensive diagnostic tool, automated stem cell enumeration may provide a promising alternative. Hence, this study aimed to compare automated hematopoietic progenitor enumeration carried out on a Sysmex XN-20 module compared with conventional flow cytometric measurements. METHODS: One hundred forty-three blood samples from 41 patients were included in this study. Correlation between the two methods was calculated over all samples, depending on leukocyte count and diagnosis. RESULTS: Overall, we found a high degree of correlation (r = 0.884). Furthermore, correlation was not impaired by elevated leukocyte counts (>10 000/µL, r = 0.860 vs <10 000/µL, r = 0.849; >20 000/µL, r = 0.843 vs <20 000/µL, r = 0.875). However, correlation was significantly impaired in patients with multiple myeloma (multiple myeloma r = 0.840 vs nonmyeloma r = 0.934). SUMMARY: Stem cell measurement carried out on the Sysmex XN-20 module provides a significant correlation with flow cytometry and might be implemented in clinical practice. In clinical decision-making, there was discrepancy of under 15% of cases. In multiple myeloma patients, XN-20 should be used with caution.
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Antígenos CD34 , Citometría de Flujo , Células Madre Hematopoyéticas , Adulto , Femenino , Humanos , Masculino , Antígenos CD34/análisis , Antígenos CD34/sangre , Recuento de Células Sanguíneas/métodos , Recuento de Células Sanguíneas/instrumentación , Citometría de Flujo/métodos , Células Madre Hematopoyéticas/citología , Recuento de Leucocitos/métodos , Mieloma Múltiple/sangre , Mieloma Múltiple/diagnósticoRESUMEN
Diagnosing urothelial cancer (UCa) via invasive cystoscopy is painful, specifically in men, and can cause infection and bleeding. Because the UCa risk is higher for male patients, urinary non-invasive UCa biomarkers are highly desired to stratify men for invasive cystoscopy. We previously identified multiple DNA methylation sites in urine samples that detect UCa with a high sensitivity and specificity in men. Here, we identified the most relevant markers by employing multiple statistical approaches and machine learning (random forest, boosted trees, LASSO) using a dataset of 251 male UCa patients and 111 controls. Three CpG sites located in ALOX5, TRPS1 and an intergenic region on chromosome 16 have been concordantly selected by all approaches, and their combination in a single decision matrix for clinical use was tested based on their respective thresholds of the individual CpGs. The combination of ALOX5 and TRPS1 yielded the best overall sensitivity (61%) at a pre-set specificity of 95%. This combination exceeded both the diagnostic performance of the most sensitive bioinformatic approach and that of the best single CpG. In summary, we showed that overlap analysis of multiple statistical approaches identifies the most reliable biomarkers for UCa in a male collective. The results may assist in stratifying men for cystoscopy.
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Líquidos Corporales , Dedos/anomalías , Enfermedades del Cabello , Síndrome de Langer-Giedion , Neoplasias , Nariz/anomalías , Masculino , Humanos , Biomarcadores de Tumor/genética , Metilación de ADN , Aprendizaje Automático , ADN de Neoplasias , Proteínas RepresorasRESUMEN
This article describes some use case studies and self-assessments of FAIR status of de.NBI services to illustrate the challenges and requirements for the definition of the needs of adhering to the FAIR (findable, accessible, interoperable and reusable) data principles in a large distributed bioinformatics infrastructure. We address the challenge of heterogeneity of wet lab technologies, data, metadata, software, computational workflows and the levels of implementation and monitoring of FAIR principles within the different bioinformatics sub-disciplines joint in de.NBI. On the one hand, this broad service landscape and the excellent network of experts are a strong basis for the development of useful research data management plans. On the other hand, the large number of tools and techniques maintained by distributed teams renders FAIR compliance challenging.
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Manejo de Datos/métodos , Metadatos , Redes Neurales de la Computación , Proteómica/métodos , Programas Informáticos , Genoma Humano , Secuenciación de Nucleótidos de Alto Rendimiento , Humanos , Cooperación Internacional , Fenotipo , Plantas/genética , Proteoma , Autoevaluación (Psicología) , Flujo de TrabajoRESUMEN
Neuromelanin is a black-brownish pigment, present in so-called neuromelanin granules (NMGs) in the cell bodies of dopaminergic neurons in the substantia nigra (SN) pars compacta. These neurons are lost in neurodegenerative diseases, such as Parkinson's disease and dementia with Lewy bodies. Although it is known that lipids, proteins, and environmental toxins accumulate in NMGs, the function of NMGs has not yet been finally clarified as well as their origin and the synthesis of neuromelanin. We, therefore, isolated NMGs and surrounding SN tissue from control patients by laser microdissection and analyzed the proteomic profile by tandem mass spectrometry. With our improved workflow, we were able to (1) strengthen the regularly reported link between NMGs and lysosomes, (2) detect tyrosine hydroxylase to be highly abundant in NMGs, which may be related to neuromelanin synthesis and (3) indicate a yet undescribed link between stress granules (SGs) and NMGs. Based on our findings, we cautiously hypothesize, that SGs may be the origin of NMGs or form in close proximity to them, potentially due to the oxidative stress caused by neuromelanin-bound metals.
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Proteómica , Tirosina 3-Monooxigenasa , Humanos , Lisosomas/metabolismo , Melaninas/metabolismo , Proteómica/métodos , Gránulos de Estrés , Sustancia Negra/metabolismo , Tirosina 3-Monooxigenasa/metabolismoRESUMEN
Chronic obstructive pulmonary disease (COPD) is a major risk factor for the development of lung adenocarcinoma (AC). AC often develops on underlying COPD; thus, the differentiation of both entities by biomarker is challenging. Although survival of AC patients strongly depends on early diagnosis, a biomarker panel for AC detection and differentiation from COPD is still missing. Plasma samples from 176 patients with AC with or without underlying COPD, COPD patients, and hospital controls were analyzed using mass-spectrometry-based proteomics. We performed univariate statistics and additionally evaluated machine learning algorithms regarding the differentiation of AC vs. COPD and AC with COPD vs. COPD. Univariate statistics revealed significantly regulated proteins that were significantly regulated between the patient groups. Furthermore, random forest classification yielded the best performance for differentiation of AC vs. COPD (area under the curve (AUC) 0.935) and AC with COPD vs. COPD (AUC 0.916). The most influential proteins were identified by permutation feature importance and compared to those identified by univariate testing. We demonstrate the great potential of machine learning for differentiation of highly similar disease entities and present a panel of biomarker candidates that should be considered for the development of a future biomarker panel.
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Adenocarcinoma del Pulmón , Neoplasias Pulmonares , Enfermedad Pulmonar Obstructiva Crónica , Biomarcadores , Humanos , Neoplasias Pulmonares/diagnóstico , Neoplasias Pulmonares/patología , Proteómica , Enfermedad Pulmonar Obstructiva Crónica/patologíaRESUMEN
Desmin mutations cause familial and sporadic cardiomyopathies. In addition to perturbing the contractile apparatus, both desmin deficiency and mutated desmin negatively impact mitochondria. Impaired myocardial metabolism secondary to mitochondrial defects could conceivably exacerbate cardiac contractile dysfunction. We performed metabolic myocardial phenotyping in left ventricular cardiac muscle tissue in desmin knock-out mice. Our analyses revealed decreased mitochondrial number, ultrastructural mitochondrial defects, and impaired mitochondria-related metabolic pathways including fatty acid transport, activation, and catabolism. Glucose transporter 1 and hexokinase-1 expression and hexokinase activity were increased. While mitochondrial creatine kinase expression was reduced, fetal creatine kinase expression was increased. Proteomic analysis revealed reduced expression of proteins involved in electron transport mainly of complexes I and II, oxidative phosphorylation, citrate cycle, beta-oxidation including auxiliary pathways, amino acid catabolism, and redox reactions and oxidative stress. Thus, desmin deficiency elicits a secondary cardiac mitochondriopathy with severely impaired oxidative phosphorylation and fatty and amino acid metabolism. Increased glucose utilization and fetal creatine kinase upregulation likely portray attempts to maintain myocardial energy supply. It may be prudent to avoid medications worsening mitochondrial function and other metabolic stressors. Therapeutic interventions for mitochondriopathies might also improve the metabolic condition in desmin deficient hearts.
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Cardiomiopatías , Desmina , Hexoquinasa , Aminoácidos/metabolismo , Animales , Cardiomiopatías/genética , Cardiomiopatías/metabolismo , Citratos/metabolismo , Forma Mitocondrial de la Creatina-Quinasa/metabolismo , Desmina/genética , Desmina/metabolismo , Ácidos Grasos/metabolismo , Glucosa/metabolismo , Transportador de Glucosa de Tipo 1/metabolismo , Hexoquinasa/genética , Hexoquinasa/metabolismo , Ratones , Ratones Noqueados , Miocardio/metabolismo , Fosforilación Oxidativa , ProteómicaRESUMEN
We evaluated the quantification strategies label-free (LF), stable isotope labeling by amino acids in cell culture (SILAC), and tandem mass tags (TMT) and their performance in quantification of proteins and phosphosites (p-sites) to identify the most powerful approach for monitoring cellular signaling. We analyzed the epidermal growth factor receptor (EGFR) signaling network, which plays an essential role in colorectal cancer, and studied its dynamics within 24 h upon treatment with the EGFR-blocking antibody cetuximab, representing the first cellular adaption toward therapy. LF achieved superior coverage but was outperformed by label-based approaches regarding technical variability, especially for quantification of p-sites. TMT showed the lowest coverage and most missing values. We found that its performance considerably decreases when experimental replicates are distributed over several TMT plexes. SILAC showed the highest precision and outstanding performance for quantification of p-sites, rendering it the method of choice for analyzing cellular signaling in cell culture models. On the protein level, we observed only little regulation upon cetuximab treatment, whereas a great fraction of p-sites was significantly regulated. These dynamics represented an initial downregulation of the MAPK pathway, which was partially rescued as early as 24 h after treatment. We identified upregulation and signaling via ERBB3 as well as calcium and cAMP signaling as possible mechanisms bypassing the blockage of EGFR.
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Neoplasias Colorrectales , Proteómica , Línea Celular , Neoplasias Colorrectales/tratamiento farmacológico , Receptores ErbB/genética , Humanos , Marcaje IsotópicoRESUMEN
Histopathological differentiation between severe urocystitis with reactive urothelial atypia and carcinoma in situ (CIS) can be difficult, particularly after a treatment that deliberately induces an inflammatory reaction, such as intravesical instillation of Bacillus Calmette-Guèrin. However, precise grading in bladder cancer is critical for therapeutic decision making and thus requires reliable immunohistochemical biomarkers. Herein, an exemplary potential biomarker in bladder cancer was identified by the novel approach of Fourier transform infrared imaging for label-free tissue annotation of tissue thin sections. Identified regions of interest are collected by laser microdissection to provide homogeneous samples for liquid chromatography-tandem mass spectrometry-based proteomic analysis. This approach afforded label-free spatial classification with a high accuracy and without interobserver variability, along with the molecular resolution of the proteomic analysis. Cystitis and invasive high-grade urothelial carcinoma samples were analyzed. Three candidate biomarkers were identified and verified by immunohistochemistry in a small cohort, including low-grade urothelial carcinoma samples. The best-performing candidate AHNAK2 was further evaluated in a much larger independent verification cohort that also included CIS samples. Reactive urothelial atypia and CIS were distinguishable on the basis of the expression of this newly identified and verified immunohistochemical biomarker, with a sensitivity of 97% and a specificity of 69%. AHNAK2 can differentiate between reactive urothelial atypia in the setting of an acute or chronic cystitis and nonmuscle invasive-type CIS.
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Biomarcadores de Tumor/metabolismo , Proteínas del Citoesqueleto/metabolismo , Proteínas de Neoplasias/metabolismo , Proteómica , Neoplasias de la Vejiga Urinaria , Urotelio , Femenino , Humanos , Inmunohistoquímica , Masculino , Espectroscopía Infrarroja por Transformada de Fourier , Neoplasias de la Vejiga Urinaria/diagnóstico por imagen , Neoplasias de la Vejiga Urinaria/metabolismo , Urotelio/diagnóstico por imagen , Urotelio/metabolismoRESUMEN
INTRODUCTION: Acute myeloid leukemia (AML) is, if untreated, a fatal hematologic neoplasia. Failure of the first induction chemotherapy is a hallmark for a poor prognosis. Early recognition of therapy failure is crucial for planning further therapies. Therefore, international guidelines recommend a bone marrow biopsy around day 14 after the beginning of induction therapy. Hypocellular bone marrow on day 14 is still gold standard for therapy assessment and further therapy strategy. Despite this, non-invasive ways for the evaluation of induction therapy were looked for in the past years. METHODS: We collected peripheral blood cell counts and routine laboratory values of patients treated with "7â¯+â¯3" induction therapy. Ratios of absolute cell counts of monocytes and neutrophils (MNR) were calculated daily, and the values were compared in patients with failure of the first induction therapy and patients with therapy response. RESULTS: 54 patients were included, 12 of which had failure of first induction therapy. The MNR following therapy was highly correlated with the bone marrow results. With the right cut-off, the MNR provides a valid and reliable tool for identification of patients with failure of first induction therapy with a sensitivity of 83.3% and a specificity of 87.8% on day 18. CONCLUSIONS: We propose a novel and non-invasive method for detection of failure of first induction therapy in patients with de novo AML and "7â¯+â¯3" induction therapy. The MNR is free of cost since the required cell counts are performed routinely for each patient undergoing intensive chemotherapy.
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Leucemia Mieloide Aguda/sangre , Recuento de Leucocitos , Monocitos , Neutrófilos , Protocolos de Quimioterapia Combinada Antineoplásica/efectos adversos , Protocolos de Quimioterapia Combinada Antineoplásica/uso terapéutico , Biomarcadores , Femenino , Humanos , Quimioterapia de Inducción , Leucemia Mieloide Aguda/diagnóstico , Leucemia Mieloide Aguda/tratamiento farmacológico , Masculino , Pronóstico , Curva ROC , Estudios Retrospectivos , Insuficiencia del TratamientoRESUMEN
In proteomics, liquid chromatography-tandem mass spectrometry (LC-MS/MS) is established for identifying peptides and proteins. Duplicated spectra, that is, multiple spectra of the same peptide, occur both in single MS/MS runs and in large spectral libraries. Clustering tandem mass spectra is used to find consensus spectra, with manifold applications. First, it speeds up database searches, as performed for instance by Mascot. Second, it helps to identify novel peptides across species. Third, it is used for quality control to detect wrongly annotated spectra. We compare different clustering algorithms based on the cosine distance between spectra. CAST, MS-Cluster, and PRIDE Cluster are popular algorithms to cluster tandem mass spectra. We add well-known algorithms for large data sets, hierarchical clustering, DBSCAN, and connected components of a graph, as well as the new method N-Cluster. All algorithms are evaluated on real data with varied parameter settings. Cluster results are compared with each other and with peptide annotations based on validation measures such as purity. Quality control, regarding the detection of wrongly (un)annotated spectra, is discussed for exemplary resulting clusters. N-Cluster proves to be highly competitive. All clustering results benefit from the so-called DISMS2 filter that integrates additional information, for example, on precursor mass.
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Algoritmos , Análisis por Conglomerados , Espectrometría de Masas en Tándem/métodos , Control de CalidadRESUMEN
Many challenges in proteomics result from the high-throughput nature of the experiments. This paper first presents pre-analytical problems, which still occur, although the call for standardization in omics has been ongoing for many years. This article also discusses aspects that affect bioinformatic analysis based on three sets of reference data measured with different orbitrap instruments. Despite continuous advances in mass spectrometer technology as well as analysis software, data-set-wise quality control is still necessary, and decoy-based estimation, although challenged by modern instruments, should be utilized. We draw attention to the fact that numerous young researchers perceive proteomics as a mature, readily applicable technology. However, it is important to emphasize that the maximum potential of the technology can only be realized by an educated handling of its limitations.
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Proteomic studies using mass spectrometry (MS)-based quantification are a main approach to the discovery of new biomarkers. However, a number of analytical conditions in front and during MS data acquisition can affect the accuracy of the obtained outcome. Therefore, comprehensive quality assessment of the acquired data plays a central role in quantitative proteomics, though, due to the immense complexity of MS data, it is often neglected. Here, we address practically the quality assessment of quantitative MS data, describing key steps for the evaluation, including the levels of raw data, identification and quantification. With this, four independent datasets from cerebrospinal fluid, an important biofluid for neurodegenerative disease biomarker studies, were assessed, demonstrating that sample processing-based differences are already reflected at all three levels but with varying impacts on the quality of the quantitative data. Specifically, we provide guidance to critically interpret the quality of MS data for quantitative proteomics. Moreover, we provide the free and open source quality control tool MaCProQC, enabling systematic, rapid and uncomplicated data comparison of raw data, identification and feature detection levels through defined quality metrics and a step-by-step quality control workflow.
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Enfermedades Neurodegenerativas , Espectrometría de Masas en Tándem , Humanos , Espectrometría de Masas en Tándem/métodos , Proteoma/análisis , Proteómica/métodos , Biomarcadores/análisis , Control de CalidadRESUMEN
In bottom-up proteomics, proteins are enzymatically digested into peptides before measurement with mass spectrometry. The relationship between proteins and their corresponding peptides can be represented by bipartite graphs. We conduct a comprehensive analysis of bipartite graphs using quantified peptides from measured data sets as well as theoretical peptides from an in silico digestion of the corresponding complete taxonomic protein sequence databases. The aim of this study is to characterize and structure the different types of graphs that occur and to compare them between data sets. We observed a large influence of the accepted minimum peptide length during in silico digestion. When changing from theoretical peptides to measured ones, the graph structures are subject to two opposite effects. On the one hand, the graphs based on measured peptides are on average smaller and less complex compared to graphs using theoretical peptides. On the other hand, the proportion of protein nodes without unique peptides, which are a complicated case for protein inference and quantification, is considerably larger for measured data. Additionally, the proportion of graphs containing at least one protein node without unique peptides rises when going from database to quantitative level. The fraction of shared peptides and proteins without unique peptides as well as the complexity and size of the graphs highly depends on the data set and organism. Large differences between the structures of bipartite peptide-protein graphs have been observed between database and quantitative level as well as between analyzed species. In the analyzed measured data sets, the proportion of protein nodes without unique peptides ranged from 6.4% to 55.0%. This highlights the need for novel methods that can quantify proteins without unique peptides. The knowledge about the structure of the bipartite peptide-protein graphs gained in this study will be useful for the development of such algorithms.
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Péptidos , Proteínas , Proteínas/química , Péptidos/química , Bases de Datos de Proteínas , Proteómica/métodos , Espectrometría de Masas/métodosRESUMEN
Neuromelanin granules (NMGs) are organelle-like structures present in the human substantia nigra pars compacta. In addition to neuromelanin, NMGs contain proteins, lipids and metals. As NMG-containing dopaminergic neurons are preferentially lost in Parkinson's disease and dementia with Lewy bodies (DLB), it is assumed that NMGs may play a role in neurodegenerative processes. Until now, this role is not completely understood and needs further investigation. We therefore set up an exploratory proteomic study to identify differences in the proteomic profile of NMGs from DLB patients (n = 5) compared to healthy controls (CTRL, n = 5). We applied a laser microdissection and mass-spectrometry-based approach, in which we used targeted mass spectrometric experiments for validation. In NMG-surrounding (SNSurr.) tissue of DLB patients, we found evidence for ongoing oxidative damage and an impairment of protein degradation. As a potentially disease-related mechanism, we found α-synuclein and protein S100A9 to be enriched in NMGs of DLB cases, while the abundance of several ribosomal proteins was significantly decreased. As S100A9 is known to be able to enhance the formation of toxic α-synuclein fibrils, this finding points towards an involvement of NMGs in pathogenesis, however the exact role of NMGs as either neuroprotective or neurotoxic needs to be further investigated. Nevertheless, our study provides evidence for an impairment of protein degradation, ongoing oxidative damage and accumulation of potentially neurotoxic protein aggregates to be central mechanisms of neurodegeneration in DLB.
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Enfermedad por Cuerpos de Lewy , Proteoma , Humanos , alfa-Sinucleína , ProteómicaRESUMEN
Mass spectrometry is frequently used in quantitative proteomics to detect differentially regulated proteins. A very important but unfortunately oftentimes neglected part in detecting differential proteins is the statistical analysis. Data from proteomics experiments are usually high-dimensional and hence require profound statistical methods. It is especially important to already correctly design a proteomic experiment before it is conducted in the laboratory. Only this can ensure that the statistical analysis is capable of detecting truly differential proteins afterward. This chapter thus covers aspects of both statistical planning as well as the actual analysis of quantitative proteomic experiments.
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Espectrometría de Masas/estadística & datos numéricos , Proteínas/análisis , Proteoma , Proteómica/estadística & datos numéricos , Proyectos de Investigación/estadística & datos numéricos , Animales , Interpretación Estadística de Datos , Humanos , Modelos EstadísticosRESUMEN
Summary: Because of the steadily increasing and already manually unmanageable total number of biomarker-related articles in biomedical research, there is a need for intelligent systems that extract all relevant information from biomedical texts and provide it as structured information to researchers in a user-friendly way. To address this, BIONDA was implemented as a free text mining-based online database for molecular biomarkers including genes, proteins and miRNAs and for all kinds of diseases. The contained structured information on published biomarkers is extracted automatically from Europe PMC publication abstracts and high-quality sources like UniProt and Disease Ontology. This allows frequent content updates. Availability and implementation: BIONDA is freely accessible via a user-friendly web application at http://bionda.mpc.ruhr-uni-bochum.de. The current BIONDA code is available at GitHub via https://github.com/mpc-bioinformatics/bionda. Supplementary information: Supplementary data are available at Bioinformatics Advances online.
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Prostate cancer (PCa) is the most common cancer and the third most frequent cause of male cancer death in Germany. MicroRNAs (miRNA) appear to be involved in the development and progression of PCa. A diagnostic differentiation from benign prostate hyperplasia (BPH) is often only possible through transrectal punch biopsy. This procedure is described as painful and carries risks. It was investigated whether urinary miRNAs can be used as biomarkers to differentiate the prostate diseases above. Therefore urine samples from urological patients with BPH (25) or PCa (28) were analysed using Next-Generation Sequencing to detect the expression profile of total and exosomal miRNA/piRNA. 79 miRNAs and 5 piwi-interacting RNAs (piRNAs) were significantly differentially expressed (adjusted p-value < 0.05 and log2-Fc > 1 or < -1). Of these, 6 miRNAs and 2 piRNAs could be statistically validated (AUC on test cohort > = 0.7). In addition, machine-learning algorithms were used to identify a panel of 22 additional miRNAs, whose interaction makes it possible to differentiate the groups as well. There are promising individual candidates for potential use as biomarkers in prostate cancer. The innovative approach of applying machine learning methods to this kind of data could lead to further small RNAs coming into scientific focus, which have so far been neglected.
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MicroARNs/metabolismo , Próstata/metabolismo , Enfermedades de la Próstata/diagnóstico , Neoplasias de la Próstata/diagnóstico , Adulto , Anciano , Anciano de 80 o más Años , Biomarcadores/metabolismo , Biomarcadores de Tumor/genética , Biomarcadores de Tumor/metabolismo , Biopsia , Diagnóstico Diferencial , Secuenciación de Nucleótidos de Alto Rendimiento , Humanos , Masculino , MicroARNs/genética , Persona de Mediana Edad , Próstata/patología , Enfermedades de la Próstata/genética , Enfermedades de la Próstata/metabolismo , Enfermedades de la Próstata/patología , Neoplasias de la Próstata/genética , Neoplasias de la Próstata/metabolismo , Neoplasias de la Próstata/patologíaRESUMEN
Therapeutic strategies for patients with locally advanced rectal cancer (LARC) who are achieving a pathological complete response (pCR) after neoadjuvant radio-chemotherapy (neoCRT) are being increasingly investigated. Recent trials challenge the current standard therapy of total mesorectal excision (TME). For some patients, the treatment strategy of "watch-and-wait" seems a preferable procedure. The key factor in determining individual treatment strategies following neoCRT is the precise evaluation of the tumor response. Contrast-enhanced computer tomography (ceCT) has proven its ability to discriminate benign and malign lesions in multiple cancers. In this study, we retrospectively analyzed the ceCT based density of LARC in 30 patients, undergoing neoCRT followed by TME. We compared the tumors´ pre- and post-neoCRT density and correlated the results to the amount of residual vital tumor cells in the resected tissue. Overall, the density decreased after neoCRT, with the highest decrease in patients achieving pCR. Densitometry demonstrated a specificity of 88% and sensitivity of 68% in predicting pCR. Thus, we claim that ceCT based densitometry is a useful tool in identifying patients with LARC who may benefit from a "watch-and-wait" strategy and suggest further prospective studies.