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INTRODUCTION: Blunt cardiac injury (BCI), associated with high morbidity and mortality, involves multiple injuries. With no widely accepted gold standard diagnostic test and molecular biomarkers still in debate and far from application in clinical practice, exploring specific molecular biomarkers of BCI is of great significance. The clarification of molecular biomarkers can improve the diagnosis of BCI, leading to more precise care for victims in various situations. AREAS COVERED: Using the search term "Biomarker AND Blunt cardiac injury',' we carefully reviewed related papers from June 2004 to June 2024 in PubMed and CNKI. After reviewing, we included 20 papers, summarizing the biomarkers reported in previous studies, and then reviewed molecular biomarkers such as troponins, N-terminal pro-B-type natriuretic peptide (NT pro-BNP), heart-type fatty acid binding protein (h-FABP), and lactate for BCI diagnosis. Finally, valuable views on future research directions for diagnostic biomarkers of BCI were presented. EXPERT OPINION: Several advanced technologies have been introduced into clinical medicine, which have ultimately changed the research on cardiac diseases in recent years. Some biomarkers have been identified and utilized for BCI diagnosis. Herein, we summarize the latest relevant information as a reference for clinical practice and future studies.
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BACKGROUND: Urinary bladder neoplasms constitute a heterogeneous group of tumors with diverse clinical behaviors and outcomes. Understanding the correlation between clinicopathological characteristics and the prognostic significance of molecular biomarkers in bladder cancer is vital for personalized treatment strategies and improved patient outcomes. OBJECTIVE: This prospective observational study aimed to comprehensively investigate the clinicopathological correlations and prognostic significance of molecular biomarkers in urinary bladder neoplasms. METHODS: A cohort of 174 patients diagnosed with urinary bladder neoplasm participated in this study. Clinicopathological data, including demographic information, medical history, imaging findings, and histopathological reports, were collected from the patient records. Tissue samples obtained from transurethral resection or biopsy were subjected to molecular biomarker analysis using immunohistochemistry (IHC), fluorescence in situ hybridization (FISH), and molecular profiling techniques. Longitudinal follow-up assessments were conducted to monitor disease progression, recurrence, and overall survival. RESULT: Out of 174 patients diagnosed with bladder neoplasms, the mean age of the patients was 62.4 years (±8.7), indicating that the study cohort primarily comprised elderly individuals. The majority of patients were male (126, 72.4%), reflecting the higher prevalence of bladder cancer among men compared to women. Preliminary analysis revealed significant associations between clinicopathological parameters, molecular biomarker expression profiles, and clinical outcomes in patients with urinary bladder neoplasms. Elevated expression levels of specific biomarkers such as tumor protein p53 (p53), Ki-67, and estimated glomerular filtration rate (EGFR) were observed in advanced tumor stages (p < 0.001) and higher histological grades (p < 0.05), indicating their potential prognostic significance. Furthermore, genetic alterations detected using molecular profiling techniques, including chromosomal gains and losses, were significantly correlated with aggressive disease phenotypes and increased recurrence risk (p < 0.01). Longitudinal follow-up data demonstrated that patients with elevated biomarker expression levels or genetic alterations had poorer treatment responses and shorter overall survival durations than those with lower biomarker expression levels. CONCLUSION: This study highlights the importance of integrating clinicopathological parameters and molecular biomarker data for the risk stratification, treatment selection, and prognostic assessment of urinary bladder neoplasms.
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Background: Molecular biomarkers are reshaping patient stratification and treatment decisions, yet their precise use and best implementation remain uncertain. Intratumor heterogeneity (ITH), an area of increasing research interest with prognostic value across various conditions, lacks defined clinical relevance in certain non-small cell lung cancer (NSCLC) subtypes. Exploring the relationship between ITH and tumor mutational burden (TMB) is crucial, as their interplay might reveal distinct patient subgroups. This study evaluates how the ITH-TMB dynamic affects prognosis across the two main histological subtypes of NSCLC, squamous cell and adenocarcinoma, with a specific focus on early-stage cases to address their highly unmet clinical needs. Methods: We stratify a cohort of 741 early-stage NSCLC patients from The Cancer Genome Atlas (TCGA) based on ITH and TMB and evaluate differences in clinical outcomes. Additionally, we compare driver mutations and the tumor microenvironment (TME) between high and low ITH groups. Results: In lung squamous cell carcinoma (LUSC), high ITH predicts an extended progression-free survival (PFS) (median: 21 vs. 14 months, P=0.01), while in lung adenocarcinoma (LUAD), high ITH predicts a reduced PFS (median: 15 vs. 20 months, P=0.04). This relationship is driven by the low TMB subset of patients. Additionally, we found that CD8 T cells were enriched in better-performing subgroups, regardless of histologic subtype or ITH status. Conclusions: There are significant differences in clinical outcomes, driver mutations, and the TME between high and low ITH groups among early-stage NSCLC patients. These differences may have treatment implications, necessitating further validation in other NSCLC datasets.
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Neurological involvement has been widely reported in SARS-CoV-2 infection. However, viral identification in the cerebrospinal fluid (CSF) is rarely found. The aim of this study is to evaluate the accuracy of virological and immunological biomarkers in CSF for the diagnosis of neuroCOVID-19. We analyzed 69 CSF samples from patients with neurological manifestations: 14 with suspected/confirmed COVID-19, with 5 additional serial CSF samples (group A), and as a control, 50 non-COVID-19 cases (group B-26 with other neuroinflammatory diseases; group C-24 with non-inflammatory diseases). Real-time reverse-transcription polymerase chain reaction (real-time RT-PCR) was used to determine SARS-CoV-2, and specific IgG, IgM, neopterin, and protein 10 induced by gamma interferon (CXCL-10) were evaluated in the CSF samples. No samples were amplified for SARS-CoV-2 by real-time RT-PCR. The sensitivity levels of anti-SARS-CoV-2 IgG and IgM were 50% and 14.28%, respectively, with 100% specificity for both tests. CXCL-10 showed high sensitivity (95.83%) and specificity (95.83%) for detection of neuroinflammation. Serial CSF analysis showed an association between the neuroinflammatory biomarkers and outcome (death and hospital discharge) in two cases (meningoencephalitis and rhombencephalitis). The detection of SARS-CoV-2 RNA and specific immunoglobulins in the CSF can be used for neuroCOVID-19 confirmation. Additionally, CXCL-10 in the CSF may contribute to the diagnosis and monitoring of neuroCOVID-19.
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Anticuerpos Antivirales , Biomarcadores , COVID-19 , Quimiocina CXCL10 , Inmunoglobulina G , Inmunoglobulina M , SARS-CoV-2 , Humanos , COVID-19/diagnóstico , COVID-19/líquido cefalorraquídeo , COVID-19/virología , SARS-CoV-2/aislamiento & purificación , SARS-CoV-2/genética , Masculino , Persona de Mediana Edad , Femenino , Inmunoglobulina G/líquido cefalorraquídeo , Inmunoglobulina G/sangre , Adulto , Inmunoglobulina M/líquido cefalorraquídeo , Inmunoglobulina M/sangre , Anciano , Biomarcadores/líquido cefalorraquídeo , Quimiocina CXCL10/líquido cefalorraquídeo , Anticuerpos Antivirales/líquido cefalorraquídeo , Anticuerpos Antivirales/sangre , Sensibilidad y Especificidad , Neopterin/líquido cefalorraquídeo , Anciano de 80 o más Años , Enfermedades del Sistema Nervioso/diagnóstico , Enfermedades del Sistema Nervioso/virología , Enfermedades del Sistema Nervioso/líquido cefalorraquídeo , Adulto JovenRESUMEN
Skin cancer is the most common cancer type in the USA, with over five million annually treated cases and one in five Americans predicted to develop the disease by the age of 70. Skin cancer can be classified as melanoma or non-melanoma (NMSC), the latter including basal cell carcinoma (BCC) and cutaneous squamous cell carcinoma (SCC). Development of BCC and SCC is impacted by environmental, behavioral, and genetic risk factors and the incidence is on the rise, with the associated number of deaths surpassing those caused by melanoma, according to recent reports. Substantial morbidity is related to both BCC and SCC, including disfigurement, loss of function, and chronic pain, driving high treatment costs, and representing a heavy financial burden to patients and healthcare systems worldwide. Clinical presentations of BCC and SCC can be diverse, sometimes carrying considerable phenotypic similarities to benign lesions, and underscoring the need for the development of disease-specific biomarkers. Skin biomarker profiling plays an important role in deeper disease understanding, as well as in guiding clinical diagnosis and patient management, prompting the use of both invasive and non-invasive tools to evaluate specific biomarkers. In this work, we review the known and emerging biomarkers of BCC and SCC, with a focus on molecular and histologic biomarkers relevant for aspects of patient management, including prevention/risk assessments, tumor diagnosis, and therapy selection.
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Accurate prediction and grading of gliomas play a crucial role in evaluating brain tumor progression, assessing overall prognosis, and treatment planning. In addition to neuroimaging techniques, identifying molecular biomarkers that can guide the diagnosis, prognosis and prediction of the response to therapy has aroused the interest of researchers in their use together with machine learning and deep learning models. Most of the research in this field has been model-centric, meaning it has been based on finding better performing algorithms. However, in practice, improving data quality can result in a better model. This study investigates a data-centric machine learning approach to determine their potential benefits in predicting glioma grades. We report six performance metrics to provide a complete picture of model performance. Experimental results indicate that standardization and oversizing the minority class increase the prediction performance of four popular machine learning models and two classifier ensembles applied on a low-imbalanced data set consisting of clinical factors and molecular biomarkers. The experiments also show that the two classifier ensembles significantly outperform three of the four standard prediction models. Furthermore, we conduct a comprehensive descriptive analysis of the glioma data set to identify relevant statistical characteristics and discover the most informative attributes using four feature ranking algorithms.
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Neoplasias Encefálicas , Glioma , Aprendizaje Automático , Clasificación del Tumor , Glioma/genética , Glioma/patología , Humanos , Neoplasias Encefálicas/genética , Neoplasias Encefálicas/patología , Biomarcadores de Tumor/genética , Pronóstico , AlgoritmosRESUMEN
Alzheimer's Disease (AD) is a challenging neurodegenerative condition, with overwhelming implications for affected individuals and healthcare systems worldwide. Animal models have played a crucial role in studying AD pathogenesis and testing therapeutic interventions. Remarkably, studies on the genetic factors affecting AD risk, such as APOE and TREM2, have provided valuable insights into disease mechanisms. Early diagnosis has emerged as a crucial factor in effective AD management, as demonstrated by clinical studies emphasizing the benefits of initiating treatment at early stages. Novel diagnostic technologies, including RNA sequencing of microglia, offer promising avenues for early detection and monitoring of AD progression. Therapeutic strategies remain to evolve, with a focus on targeting amyloid beta (Aß) and tau pathology. Advances in animal models, such as APP-KI mice, and the advancement of anti-Aß drugs signify progress towards more effective treatments. Therapeutically, the focus has shifted towards intricate approaches targeting multiple pathological pathways simultaneously. Strategies aimed at reducing Aß plaque accumulation, inhibiting tau hyperphosphorylation, and modulating neuroinflammation are actively being explored, both in preclinical models and clinical trials. While challenges continue in developing validated animal models and translating preclinical findings to clinical success, the continuing efforts in understanding AD at molecular, cellular, and clinical levels offer hope for improved management and eventual prevention of this devastating disease.
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Enfermedad de Alzheimer , Modelos Animales de Enfermedad , Diagnóstico Precoz , Enfermedad de Alzheimer/genética , Enfermedad de Alzheimer/diagnóstico , Enfermedad de Alzheimer/metabolismo , Animales , Humanos , Péptidos beta-Amiloides/metabolismo , RatonesRESUMEN
AIM: To identify new biomarkers to detect untreated and treated periodontitis in gingival crevicular fluid (GCF) using sequential window acquisition of all theoretical mass spectra (SWATH-MS). MATERIALS AND METHODS: GCF samples were collected from 44 periodontally healthy subjects and 40 with periodontitis (Stages III-IV). In the latter, 25 improved clinically 2 months after treatment. Samples were analysed using SWATH-MS, and proteins were identified by the UniProt human-specific database. The diagnostic capability of the proteins was determined with generalized additive models to distinguish the three clinical conditions. RESULTS: In the untreated periodontitis vs. periodontal health modelling, five proteins showed excellent or good bias-corrected (bc)-sensitivity/bc-specificity values of >80%. These were GAPDH, ZG16B, carbonic anhydrase 1, plasma protease inhibitor C1 and haemoglobin subunit beta. GAPDH with MMP-9, MMP-8, zinc-α-2-glycoprotein and neutrophil gelatinase-associated lipocalin and ZG16B with cornulin provided increased bc-sensitivity/bc-specificity of >95%. For distinguishing treated periodontitis vs. periodontal health, most of these proteins and their combinations revealed a predictive ability similar to previous modelling. No model obtained relevant results to differentiate between periodontitis conditions. CONCLUSIONS: New single and dual GCF protein biomarkers showed outstanding results in discriminating untreated and treated periodontitis from periodontal health. Periodontitis conditions were indistinguishable. Future research must validate these findings.
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AIMS/HYPOTHESIS: Metabolic risk factors and plasma biomarkers for diabetes have previously been shown to change prior to a clinical diabetes diagnosis. However, these markers only cover a small subset of molecular biomarkers linked to the disease. In this study, we aimed to profile a more comprehensive set of molecular biomarkers and explore their temporal association with incident diabetes. METHODS: We performed a targeted analysis of 54 proteins and 171 metabolites and lipoprotein particles measured in three sequential samples spanning up to 11 years of follow-up in 324 individuals with incident diabetes and 359 individuals without diabetes in the Danish Blood Donor Study (DBDS) matched for sex and birth year distribution. We used linear mixed-effects models to identify temporal changes before a diabetes diagnosis, either for any incident diabetes diagnosis or for type 1 and type 2 diabetes mellitus diagnoses specifically. We further performed linear and non-linear feature selection, adding 28 polygenic risk scores to the biomarker pool. We tested the time-to-event prediction gain of the biomarkers with the highest variable importance, compared with selected clinical covariates and plasma glucose. RESULTS: We identified two proteins and 16 metabolites and lipoprotein particles whose levels changed temporally before diabetes diagnosis and for which the estimated marginal means were significant after FDR adjustment. Sixteen of these have not previously been described. Additionally, 75 biomarkers were consistently higher or lower in the years before a diabetes diagnosis. We identified a single temporal biomarker for type 1 diabetes, IL-17A/F, a cytokine that is associated with multiple other autoimmune diseases. Inclusion of 12 biomarkers improved the 10-year prediction of a diabetes diagnosis (i.e. the area under the receiver operating curve increased from 0.79 to 0.84), compared with clinical information and plasma glucose alone. CONCLUSIONS/INTERPRETATION: Systemic molecular changes manifest in plasma several years before a diabetes diagnosis. A particular subset of biomarkers shows distinct, time-dependent patterns, offering potential as predictive markers for diabetes onset. Notably, these biomarkers show shared and distinct patterns between type 1 diabetes and type 2 diabetes. After independent replication, our findings may be used to develop new clinical prediction models.
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Breast cancer is a heterogeneous disease with various morphologies and molecular features, and it is the second leading cause of cancer death in women in developed countries. According to the literature, we currently lack both prognostic biomarkers and therapeutic targets. The most important prognostic factors are disease stage and Nottingham grade. We conducted a retrospective analysis involving 273 patients with BC who underwent neoadjuvant therapy before proceeding to curative surgical treatment between 1 January 2014 and 31 December 2023. Pathological procedures were conducted at the Department of Pathology, Emergency County Hospital of Targu MureÈ, Romania. A statistical analysis was performed. Regarding the relationship between Nottingham grade and Ki67, grade I was associated with a Ki67 of less than 14. The relationship between tumor grade and luminal was similar (p = 0.0001): Grade I was associated with luminal A. Regarding TNM stage, it was statistically significantly correlated with TILs (p = 0.01) and RCB (p = 0.0001). Stages III and IV were associated with a high RCB and poor prognosis. Regarding the prognostic value, Nottingham grade 3 and TNM stages III and IV were correlated with low overall survival and disease-free survival, with poor prognosis, and, among the molecular variables, RCB played the most important prognostic role.
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Chronic obstructive pulmonary disease (COPD) plays a significant role in global morbidity and mortality rates, typified by progressive airflow restriction and lingering respiratory symptoms. Recent explorations in molecular biology have illuminated the complex mechanisms underpinning COPD pathogenesis, providing critical insights into disease progression, exacerbations, and potential therapeutic interventions. This review delivers a thorough examination of the latest progress in molecular research related to COPD, involving fundamental molecular pathways, biomarkers, therapeutic targets, and cutting-edge technologies. Key areas of focus include the roles of inflammation, oxidative stress, and protease-antiprotease imbalances, alongside genetic and epigenetic factors contributing to COPD susceptibility and heterogeneity. Additionally, advancements in omics technologies-such as genomics, transcriptomics, proteomics, and metabolomics-offer new avenues for comprehensive molecular profiling, aiding in the discovery of novel biomarkers and therapeutic targets. Comprehending the molecular foundation of COPD carries substantial potential for the creation of tailored treatment strategies and the enhancement of patient outcomes. By integrating molecular insights into clinical practice, there is a promising pathway towards personalized medicine approaches that can improve the diagnosis, treatment, and overall management of COPD, ultimately reducing its global burden.
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Biomarcadores , Enfermedad Pulmonar Obstructiva Crónica , Enfermedad Pulmonar Obstructiva Crónica/metabolismo , Enfermedad Pulmonar Obstructiva Crónica/diagnóstico , Enfermedad Pulmonar Obstructiva Crónica/genética , Humanos , Biomarcadores/metabolismo , Estrés Oxidativo , Proteómica/métodos , Genómica/métodos , Metabolómica/métodos , Epigénesis GenéticaRESUMEN
BACKGROUND: Wilms tumor (WT) is the most common pediatric embryonal tumor. Improving patient outcomes requires advances in understanding and targeting the multiple genes and cellular control pathways, but its pathogenesis is currently not well-researched. We aimed to identify the potential molecular biological mechanism of WT and develop new prognostic markers and molecular targets by comparing gene expression profiles of Wilms tumors and fetal normal kidneys. METHODS: Differential gene expression analysis was performed on Wilms tumor transcriptomic data from the GEO and TARGET databases. For biological functional analysis, Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment were utilized. Out of 24 hub genes identified, nine were found to be prognostic-related through univariate Cox regression analysis. These nine genes underwent LASSO regression analysis to enhance the predictive capability of the model. The key hub genes were validated in the GSE73209 datasets, and cell function experiments were conducted to identify the genes' functions in WiT-49 cells. RESULTS: The enrichment analysis revealed that DEGs were significantly involved in the regulation of angiogenesis and regulation of cell differentiation. 24 DEGs were identified through PPI networks and the MCODE algorithm, and 9 of 24 genes were related to WT patients' prognosis. EMCN and CCNA1 were identified as key hub genes, and related to the progression of WT. Functionally, over-expression of EMCN and CCNA1 knockdown inhibited cell viability, proliferation, migration, and invasion of Wilms tumor cells. CONCLUSIONS: EMCN and CCNA1 were identified as key prognostic markers in Wilms tumor, suggesting their potential as therapeutic targets. Differential gene expression and enrichment analyses indicate significant roles in angiogenesis and cell differentiation.
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Biomarcadores de Tumor , Biología Computacional , Perfilación de la Expresión Génica , Regulación Neoplásica de la Expresión Génica , Neoplasias Renales , Tumor de Wilms , Tumor de Wilms/genética , Tumor de Wilms/patología , Humanos , Biología Computacional/métodos , Neoplasias Renales/genética , Neoplasias Renales/patología , Biomarcadores de Tumor/genética , Pronóstico , Redes Reguladoras de Genes , Transcriptoma , Proliferación Celular/genética , Mapas de Interacción de Proteínas/genética , Ontología de Genes , Línea Celular TumoralRESUMEN
Limited research exists regarding the effects of resistance exercise (RE) combined with whole body vibration (WBV), blood flow restriction (BFR), or both on the neuropsychological performance of working memory (WM) in late-middle-aged and older adults and regarding the physiological mechanisms underlying this effect. This study thus explored the acute molecular and neurophysiological mechanisms underlying WM performance following RE combined with WBV, BFR, or both. Sixty-six participants were randomly assigned into a WBV, BFR, or WBV + BFR group. Before and after the participants engaged in a single bout of isometric RE combined with WBV, BFR, or both, this study gathered data on several neurocognitive measures of WM performance, namely, accuracy rate (AR), reaction time (RT), and brain event-related potential (specifically P3 latency and amplitude), and data on biochemical indices, such as the levels of insulin-like growth factor-1 (IGF-1), norepinephrine (NE), and brain-derived neurotrophic factor (BDNF). Although none of the RE modalities significantly affected RTs and P3 latencies, ARs and P3 amplitudes significantly improved in the WBV and WBV + BFR groups. The WBV + BFR group exhibited greater improvements than the WBV group did. Following acute RE combined with WBV, BFR, or both, IGF-1 and NE levels significantly increased in all groups, whereas BDNF levels did not change. Crucially, only the changes in NE levels were significantly correlated with improvements in ARs in the WBV + BFR and WBV groups. The findings suggest that combining acute RE with WBV, BFR, or both could distinctively mitigate neurocognitive decline in late-middle-aged and older adults.
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Factor Neurotrófico Derivado del Encéfalo , Factor I del Crecimiento Similar a la Insulina , Memoria a Corto Plazo , Tiempo de Reacción , Entrenamiento de Fuerza , Vibración , Humanos , Entrenamiento de Fuerza/métodos , Masculino , Femenino , Persona de Mediana Edad , Vibración/uso terapéutico , Anciano , Factor Neurotrófico Derivado del Encéfalo/sangre , Memoria a Corto Plazo/fisiología , Factor I del Crecimiento Similar a la Insulina/metabolismo , Cognición/fisiología , Norepinefrina/sangre , Flujo Sanguíneo Regional/fisiología , Encéfalo/fisiologíaRESUMEN
Understanding the interplay among organophosphorus flame retardants (OPFRs), microplastics, and freshwater organisms is crucial for unravelling the dynamics within freshwater environments and foreseeing the potential impacts of organic pollutants and plastic contamination. For that purpose, the present research assessed the exposure impact of 10 mg L-1 flame-retardant aluminium diethylphosphinate (ALPI), 10 µg mg-1liver microplastics polyurethane (PU), and the combination of ALPI and PU on the freshwater planarian Girardia tigrina. The exposure to both ALPI and PU revealed a sequential effect, i.e., a decrease in locomotor activity, while oxidative stress biomarkers (total glutathione, catalase, glutathione S-transferase, lipid peroxidation) and metabolic responses (cholinesterase activity, electron transport system, and lactate dehydrogenase) remained unaffected. Despite this fact, it was possible to observe that the range of physiological responses in exposed organisms varied, in particular in the cases of the electron transport system, cholinesterase activity, glutathione S-transferase, catalase, and levels of total glutathione and proteins, showing that the energetic costs for detoxification and antioxidant capacity might be causing a lesser amount of energy allocated for the planarian activity. By examining the physiological, behavioural, and ecological responses of planarians to these pollutants, insights can be gained into broader ecosystem-level effects and inform strategies for mitigating environmental risks associated with OPFRs and microplastic pollution in freshwater environments.
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Colorectal cancer (CRC) is the third most frequently found cancer in the world, and it is frequently discovered when it is already far along in its development. About 20% of cases of CRC are metastatic and incurable. There is more and more evidence that colorectal cancer stem cells (CCSCs), which are in charge of tumor growth, recurrence, and resistance to treatment, are what make CRC so different. Because we know more about stem cell biology, we quickly learned about the molecular processes and possible cross-talk between signaling pathways that affect the balance of cells in the gut and cancer. Wnt, Notch, TGF-ß, and Hedgehog are examples of signaling pathway members whose genes may change to produce CCSCs. These genes control self-renewal and pluripotency in SCs and then decide the function and phenotype of CCSCs. However, in terms of their ability to create tumors and susceptibility to chemotherapeutic drugs, CSCs differ from normal stem cells and the bulk of tumor cells. This may be the reason for the higher rate of cancer recurrence in patients who underwent both surgery and chemotherapy treatment. Scientists have found that a group of uncontrolled miRNAs related to CCSCs affect stemness properties. These miRNAs control CCSC functions like changing the expression of cell cycle genes, metastasis, and drug resistance mechanisms. CCSC-related miRNAs mostly control signal pathways that are known to be important for CCSC biology. The biomarkers (CD markers and miRNA) for CCSCs and their diagnostic roles are the main topics of this review study.
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Biomarcadores de Tumor , Neoplasias Colorrectales , Células Madre Neoplásicas , Transducción de Señal , Humanos , Células Madre Neoplásicas/metabolismo , Células Madre Neoplásicas/patología , Neoplasias Colorrectales/patología , Neoplasias Colorrectales/genética , Neoplasias Colorrectales/metabolismo , Biomarcadores de Tumor/metabolismo , Biomarcadores de Tumor/genética , MicroARNs/genética , Regulación Neoplásica de la Expresión GénicaRESUMEN
Extracellular vesicles (EVs) are tools for intercellular communication, mediating molecular transport processes. Emerging studies have revealed that EVs are significantly involved in immune processes, including sepsis. Sepsis, a dysregulated immune response to infection, triggers systemic inflammation and multi-organ dysfunction, posing a life-threatening condition. Although extensive research has been conducted on animals, the complex inflammatory mechanisms that cause sepsis-induced organ failure in humans are still not fully understood. Recent studies have focused on secreted exosomes, which are small extracellular vesicles from various body cells, and have shed light on their involvement in the pathophysiology of sepsis. During sepsis, exosomes undergo changes in content, concentration, and function, which significantly affect the metabolism of endothelia, cardiovascular functions, and coagulation. Investigating the role of exosome content in the pathogenesis of sepsis shows promise for understanding the molecular basis of human sepsis. This review explores the contributions of activated immune cells and diverse body cells' secreted exosomes to vital organ dysfunction in sepsis, providing insights into potential molecular biomarkers for predicting organ failure in septic shock.
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Biomarcadores , Exosomas , Insuficiencia Multiorgánica , Sepsis , Humanos , Exosomas/metabolismo , Sepsis/metabolismo , Insuficiencia Multiorgánica/metabolismo , Insuficiencia Multiorgánica/inmunología , Insuficiencia Multiorgánica/etiología , AnimalesRESUMEN
Pancreatic ductal adenocarcinoma (PDAC) is one of the most aggressive neoplasia, characterized by early metastasis, low diagnostic rates at early stages, resistance to drugs, and poor prognosis. There is an urgent need to better characterize this disease in order to identify efficient diagnostic/prognostic biomarkers. Since microRNAs (miRNAs) contribute to oncogenesis and metastasis formation in PDAC, they are considered potential candidates for fulfilling this task. In this work, the levels of two miRNA subsets (involved in chemoresistance or with oncogenic/tumor suppressing functions) were investigated in a panel of PDAC cell lines and liquid biopsies of a small cohort of patients. We used RT-qPCR and droplet digital PCR (ddPCR) to measure the amounts of cellular- and vesicle-associated, and circulating miRNAs. We found that both PDAC cell lines, also after gemcitabine treatment, and patients showed low amounts of cellular-and vesicle-associated miR-155-5p, compared to controls. Interestingly, we did not find any differences when we analyzed circulating miR-155-5p. Furthermore, vesicle-related miR-27a-3p increased in cancer patients compared to the controls, while circulating let-7a-5p, miR-221-3p, miR-23b-3p and miR-193a-3p presented as dysregulated in patients compared to healthy individuals. Our results highlight the potential clinical significance of these analyzed miRNAs as non-invasive diagnostic molecular tools to characterize PDAC.
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Alzheimer's disease (AD) and osteoarthritis (OA) are both senile degenerative diseases. Clinical studies have found that OA patients have a significantly increased risk of AD in their later life. This study hypothesized that chronic aseptic inflammation might lead to AD in KOA patients. However, current research has not yet clarified the potential mechanism between AD and KOA. Therefore, this study intends to use KOA transcriptional profiling and single-cell sequencing analysis technology to explore the molecular mechanism of KOA affecting AD development, and screen potential molecular biomarkers and drugs for the prediction, diagnosis, and prognosis of AD in KOA patients. It was found that the higher the expression of TXNIP, MMP3, and MMP13, the higher the risk coefficient of AD was. In addition, the AUC of TXNIP, MMP3, and MMP13 were all greater than 0.70, which had good diagnostic significance for AD. Finally, through the virtual screening of core proteins in FDA drugs and molecular dynamics simulation, it was found that compound Cobicistat could be targeted to TXNIP, Itc could be targeted to MMP3, and Isavuconazonium could be targeted to MMP13. To sum up, TXNIP, MMP3, and MMP13 are prospective molecular markers in KOA with AD, which could be used to predict, diagnose, and prognosis.
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BACKGROUND: Brain tumors are one of the leading causes of epilepsy, and brain tumor-related epilepsy (BTRE) is recognized as the major cause of intractable epilepsy, resulting in huge treatment cost and burden to patients, their families, and society. Although optimal treatment regimens are available, the majority of patients with BTRE show poor resolution of symptoms. BTRE has a very complex and multifactorial etiology, which includes several influencing factors such as genetic and molecular biomarkers. Advances in multi-omics technologies have enabled to elucidate the pathophysiological mechanisms and related biomarkers of BTRE. Here, we reviewed multi-omics technology-based research studies on BTRE published in the last few decades and discussed the present status, development, opportunities, challenges, and prospects in treating BTRE. METHODS: First, we provided a general review of epilepsy, BTRE, and multi-omics techniques. Next, we described the specific multi-omics (including genomics, transcriptomics, epigenomics, proteomics, and metabolomics) techniques and related molecular biomarkers for BTRE. We then presented the associated pathogenetic mechanisms of BTRE. Finally, we discussed the development and application of novel omics techniques for diagnosing and treating BTRE. RESULTS: Genomics studies have shown that the BRAF gene plays a role in BTRE development. Furthermore, the BRAF V600E variant was found to induce epileptogenesis in the neuronal cell lineage and tumorigenesis in the glial cell lineage. Several genomics studies have linked IDH variants with glioma-related epilepsy, and the overproduction of D2HG is considered to play a role in neuronal excitation that leads to seizure occurrence. The high expression level of Forkhead Box O4 (FOXO4) was associated with a reduced risk of epilepsy occurrence. In transcriptomics studies, VLGR1 was noted as a biomarker of epileptic onset in patients. Several miRNAs such as miR-128 and miRNA-196b participate in BTRE development. miR-128 might be negatively associated with the possibility of tumor-related epilepsy development. The lncRNA UBE2R2-AS1 inhibits the growth and invasion of glioma cells and promotes apoptosis. Quantitative proteomics has been used to determine dynamic changes of protein acetylation in epileptic and non-epileptic gliomas. In another proteomics study, a high expression of AQP-4 was detected in the brain of GBM patients with seizures. By using quantitative RT-PCR and immunohistochemistry assay, a study revealed that patients with astrocytomas and oligoastrocytomas showed high BCL2A1 expression and poor seizure control. By performing immunohistochemistry, several studies have reported the relationship between D2HG overproduction and seizure occurrence. Ki-67 overexpression in WHO grade II gliomas was found to be associated with poor postoperative seizure control. According to metabolomics research, the PI3K/AKT/mTOR pathway is associated with the development of glioma-related epileptogenesis. Another metabolomics study found that SV2A, P-gb, and CAD65/67 have the potential to function as biomarkers for BTRE. CONCLUSIONS: Based on the synthesized information, this review provided new research perspectives and insights into the early diagnosis, etiological factors, and personalized treatment of BTRE.
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Neoplasias Encefálicas , Epilepsia , Glioma , MicroARNs , Humanos , Multiómica , Fosfatidilinositol 3-Quinasas , Proteínas Proto-Oncogénicas B-raf , Epilepsia/genética , Epilepsia/complicaciones , Neoplasias Encefálicas/complicaciones , Neoplasias Encefálicas/genética , Glioma/complicaciones , Glioma/genética , Convulsiones/etiología , BiomarcadoresRESUMEN
Atopic dermatitis (AD) is a complex and heterogeneous skin disease for which achieving complete clinical clearance for most patients has proven challenging through single cytokine inhibition. Current studies integrate biomarkers and evaluate their role in AD, aiming to advance our understanding of the diverse molecular profiles implicated. Although traditionally characterized as a TH2-driven disease, extensive research has recently revealed the involvement of TH1, TH17, and TH22 immune pathways as well as the interplay of pivotal immune molecules, such as OX40, OX40 ligand (OX40L), thymic stromal lymphopoietin, and IL-33. This review explores the mechanistic effects of treatments for AD, focusing on mAbs and Janus kinase inhibitors. It describes how these treatments modulate immune pathways and examines their impact on key inflammatory and barrier biomarkers.