ObjectiveTo summarize the clinical application and future application prospects of organoid model in pancreatic cancer. MethodThe domestic and foreign literature related on the application of organoid model in pancreatic cancer was reviewed. ResultsIn recent years, the organoid model of pancreatic cancer was constructed mainly using patient-derived tissues, fine-needle aspiration samples, and human pluripotent stem cells. The biomarkers of pancreatic cancer were screened according to the histological and structural heterogeneities of the primary tumor retained in organoid model, such as microRNA, glypican-1, annexin A6 and protein biomarkers cytokeratin 7 and 20, cell tumor antigen p53, Claudin-4, carbohydrate antigen 19-9, etc.in the extracellular vesicles. The results of organoid model could maintain the original tumor characteristics and the higher correlation between the organoid model drug sensitivity data and the clinical results of pancreatic cancer patients suggested that, the drug sensitivity data of organoid model could be used to avoid ineffective chemotherapy, so as to improve the treatment response rate and reduce the toxicity of chemical drug treatment, and reasonably select individualized treatment plans for pancreatic cancer patients in future. ConclusionsOrganoid model has many research in screening biomarkers of pancreatic cancer, individualized drug screening, and drug sensitivity test. It can simulate the complex pathophysiological characteristics of pancreatic cancer in vitro, and retain the physiological characteristics and gene phenotype of original tumor cells. It is expected to become a new platform for selecting biomarkers of pancreatic cancer, testing drug sensitivity, and formulating individualized treatment methods for pancreatic cancer, which might further accelerate the research progress of pancreatic cancer.
Breast cancer is a malignant tumor with the highest morbidity and mortality in female in recent years, and it is a complex disease that affects human health. Studies have shown that dynamic network biomarkers (DNB) can effectively identify critical states at which complex diseases such as breast cancer change from a normal state to a disease state. However, the traditional DNB method requires data from multiple samples in the same disease state, which is usually unachievable in clinical diagnosis. This paper quantitatively analyzes the time series data of MCF-7 breast cancer cells and finds the DNB module of a single sample in the time series based on landscape DNB (L-DNB) method. Then, a comprehensive index is constructed to detect its early warning signals to determine the critical state of breast cancer cell differentiation. The results of this study may be of great significance for the prevention and early diagnosis of breast cancer. It is expected that this paper can provide references for the related research of breast cancer.
Although great progress has been achieved in the techniques and materials of cardiopulmonary bypass (CPB), cardiac surgery under CPB is still one of the surgeries with the highest complication rate. The systemic inflammatory response is an important cause of complications, mainly characterized by activation of innate immune cells and platelets, and up-regulation of inflammatory cytokines. After activation, a variety of molecules on the membrane surface are up-regulated or down-regulated, which can amplify tissue inflammatory damage by releasing cytoplasmic protease and reactive oxygen species, and activate multiple inflammatory signaling pathways in the cell, ultimately leading to organ dysfunction. Therefore, the expression of these cell membrane activation markers is not only a marker of cell activation, but also plays an important role in the process of vital organ injury after surgery. Identification of these specific activation markers is of great significance to elucidate the mechanisms related to organ injury and to find new prevention and treatment methods. This article will review the relationship between these activated biomarkers in the innate immune cells and vital organ injuries under CPB.
Objective To investigate the impact and mechanisms of periostin (POSTN), Krebs von den Lungen-6 (KL-6), pulmonary surfactant protein A (SP-A), and pulmonary surfactant protein D (SP-D) on the diagnosis and disease assessment of idiopathic pulmonary fibrosis (IPF), and conduct a comparative analysis. Methods From October 2022 to October 2023, a total of 55 patients diagnosed with IPF and treated at the Third Affiliated Hospital of Anhui Medical University were enrolled as an IPF group. Additionally, 30 patients with bacterial pneumonia and 30 healthy individuals undergoing concurrent health examinations during the same period were selected as a pneumonia control group and a healthy control group, respectively. All participants underwent enzyme-linked immunosorbent assay to measure serum levels of POSTN, KL-6, SP-A, and SP-D, along with pulmonary function tests. The IPF patients also underwent high-resolution computed tomography (HRCT) and echocardiography to quantify HRCT scores and pulmonary artery systolic pressure (PASP). Receiver operating characteristic (ROC) curves were plotted to analyze the significance of serum POSTN, KL-6, SP-A, and SP-D levels in IPF diagnosis. Pearson and Spearman correlation tests were used to analyze the relationships between these biomarkers and pulmonary function, PASP, and HRCT scores. Results Serum concentrations of POSTN, KL-6, SP-A, and SP-D were significantly elevated in the IPF group compared with the pneumonia group and the healthy controls (P<0.05), while serum levels of SP-A and SP-D were notably higher in the pneumonia group compared with the healthy control group (P<0.05). Within the IPF group, serum POSTN levels were negatively correlated with forced expiratory volume in the first second as a percentage of predicted value (FEV1%pred) and diffusion capacity of the lung for carbon monoxide as a percentage of predicted value (DLCO%pred) (P<0.05); KL-6 and SP-D levels were also negatively correlated with FEV1%pred, forced vital capacity as a percentage of predicted value (FVC%pred), and DLCO%pred (P<0.05); and the concentration of SP-A was negatively correlated with DLCO%pred and positively correlated with PASP (P<0.05). Additionally, serum levels of POSTN, KL-6, and SP-A in the IPF group showed significant positive associations with HRCT scores (P<0.01). Conclusions POSTN is a valuable serum biomarker for IPF, exhibiting the highest sensitivity and specificity among the four serum markers, with diagnostic performance superior to KL-6, SP-A, and SP-D. POSTN, KL-6, SP-A, and SP-D can all be used for the diagnosis and assessment of IPF.
Objective To explore the change of serum levels of neutrophil gelatinase-associated lipocalin (NGAL), tissue inhibitor of metalloproteinases-2 (TIMP-2), and insulin-like growth factor-binding protein 7 (IGFBP-7) in the early stage of multiple trauma, and their predictive efficacy for acute kidney injury (AKI). Methods The multiple trauma patients admitted between February 2020 and July 2021 were prospectively selected, and they were divided into AKI group and non-AKI group according to whether they developed AKI within 72 h after injury. The serum levels of NGAL, TIMP-2, and IGFBP-7 measured at admission and 12, 24, and 48 h after injury, the Acute Pathophysiology and Chronic Health Evaluation Ⅱ(APACHE Ⅱ) score, intensive care unit duration, rate of renal replacement therapy, and 28-day mortality rate were compared between the two groups. Results A total of 51 patients were included, including 20 in the AKI group and 31 in the non-AKI group. The APACHE Ⅱ at admission (20.60±3.57 vs. 11.61±3.44), intensive care unit duration [(16.75±2.71) vs. (11.13±3.41) d], rate of renal replacement therapy (35.0% vs. 0.0%), and 28-day mortality rate (25.0% vs. 3.2%) in the AKI group were higher than those in the non-AKI group (P<0.05). The serum levels of NGAL and IGFBP-7 at admission and 12, 24, and 48 h after injury in the AKI group were all higher than those in the non-AKI group (P<0.05). For the prediction of AKI, the areas under receiver operating characteristic curves and 95% confidence intervals of serum NGAL, TIMP-2 and IGFBP-7 12 h after injury were 0.98 (0.96, 1.00), 0.92 (0.83, 1.00), and 0.87 (0.78, 0.97), respectively. Conclusion Serum NGAL, TIMP-2, and IGFBP-7 have high predictive efficacy for AKI secondary to multiple trauma, and continuous monitoring of serum NGAL can be used for early prediction of AKI secondary to multiple trauma.
ObjectiveTo evaluate the monitoring value of brain injury biomarkers in the patients during extracorporeal membrane oxygenation (ECMO). MethodsWe searched PubMed, EMbase, the Cochrane Library, CNKI, and CBM from inception of each database to May 2015 to identify randomized controlled trials, or case-control trials, or cohort trials of brain injury biomarkers predict brain injury during ECMO. Data were extracted independently by two reviewers. Meta-analysis was conducted using STATA 12.0 software. ResultsFour retrospective trials were included. The results showed that compared with patients without brain injury, the patients with brain injury had a higher level of S100B protein (P < 0.05). The incidence of major neurological events was higher for high neuron-specific enolase level patients than mild-to-moderate neuron-specific enolase level patients (85% vs. 29%, P=0.01). The incidence of brain injury was higher for normal glial fibrillary acidic protein level than patients with glial fibrillary acidic protein > 0.436 ng/ml (OR=11.5, 95%CI 1.3-98.3). ConclusionsBrain injury biomarkers may be used as an indicator for earlier diagnosis of brain injury in patients during ECMO.
Metaiodobenzylguanidine (MIBG) is an analog of norepinephrine that accumulates in sympathetic nerve endings soon after intravenous administration. The degree of accumulation reflects the uptake, storage and release of transmitters by noradrenergic neurons. Myocardial imaging with 123I labeled MIBG (123I-MIBG) can be used to estimate the extent of local myocardial sympathetic nerve damage, which has been widely used in the diagnosis and treatment of various heart diseases. In recent years, numerous studies have been carried out on the application of 123I-MIBG in the diagnosis of degenerative diseases of the nervous system (such as Parkinson's disease and dementia of Lewy body), and have made some achievements. The purpose of this review is to summarize the current clinical application of 123I-MIBG myocardial imaging in the diagnosis of dementia with Lewy bodies, the problems in imaging technology and the possible research directions in the future, so as to provide valuable reference information for clinicians to reasonably and accurately apply this technology in the early diagnosis and discrimination of dementia.
ObjectiveTo analyze the current development of researches on biomarkers for predicting the efficacy of immunotherapy in non-small cell lung cancer and to provide reference for subsequent studies. MethodsStudies on biomarkers for predicting the efficacy of immunotherapy for non-small cell lung cancer indexed in the Web of Science Core Collection from 2017 to 2021 were searched by computer. The annual distribution, journals, authors, countries, institutions, and keywords of studies were visualized and analyzed by CiteSpace. ResultsA total of 426 studies were collected, including 298 articles and 128 reviews. The average number of published studies was about 85, and increased year by year. PD-L1 expression, tumor mutational burden, tumor microenvironment and liquid biopsy were hot keywords in this field. ConclusionIn the future, combination of biomarkers in the liquid biopsy and tumor microenvironment with radiomics analysis will be the research hotspot and frontier in this field for more accurate assessment with tumor-related signatures such as lymphocytic immune status and characteristics of tumor lesions in non-small cell lung cancer patients.
The human gut microbiota regulates many host pathophysiological processes including metabolic, inflammatory, immune and cellular responses. In recent years, the incidence and mortality of lung cancer have increased rapidly, which is one of the biggest challenges in the field of cancer treatment today, especially in non-small cell lung cancer. Animal models and clinical studies have found that the gut microbiota of non-small cell lung cancer patients is significantly changed compared with the healthy people. The gut microbiota and metabolites can not only play a pro-cancer or tumor suppressor role by regulating immune, inflammatory responses and so on, but also be related with radiotherapy and chemotherapy of non-small cell lung cancer and the resistance of immunotherapy. Therefore, gut microbiota and related metabolites can be both potential markers for early diagnosis and prognosis in patients with non-small cell lung cancer and novel therapeutic targets for targeted drugs. This study will review the latest research progress of effect of gut microbiota on non-small cell lung cancer, and provide a new diagnosis and treatment ideas for non-small cell lung cancer.
ObjectiveTo analyze the effects of alcohol consumption on oral flora of middle-aged and elderly men from the core area of southwestern China, and explore the relationship between excessive-alcohol-consumption-related flora and alcohol-related cancer.MethodsFrom March to June 2018, saliva samples of target subjects were collected for 16S ribosomal RNA gene sequencing, and a questionnaire survey which took drinking history of each participant as the target variable was conducted. According to the amount of alcohol consumed, the subjects were divided into non-drinking group, moderate-drinking group, and excessive-drinking group. The microbial analysis of α diversity, analysis of group difference of oral flora abundance, bacterial function prediction, and receiver operating characteristic (ROC) curve model prediction were carried out.ResultsA total of 59 subjects were included. There were 23 cases (39.0%) in the non-drinking group, 23 cases (39.0%) in the moderate-drinking group, and 13 cases (22.0%) in the excessive-drinking group. The average age was (61.90±8.85) years. Excessive drinking increased the abundance of oral flora (P<0.05), and could change the abundance of specific genus such as Peptostreptococcus and TM7［G-6］ (P<0.05) and regulate cancer-related pathways (P<0.05). ROC analysis found that a panel of three genus oral bacteria such as TM7［G-6］ might effectively distinguish the non-drinking group from the excessive-drinking group (area under curve=0.915).ConclusionsGenus of Peptostreptococcus and TM7_［G-6］ are the potential oral flora biomarkers for the excessive-drinking of target subjects. Some excessive drinking-related flora are closely related to oral cancer.