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Frontiers in Immunology 2023Hepatitis B virus-related acute-on-chronic liver failure (HBV-ACLF) has significant morbidity and mortality and is associated with the induction of cytokines/chemokines,...
BACKGROUND
Hepatitis B virus-related acute-on-chronic liver failure (HBV-ACLF) has significant morbidity and mortality and is associated with the induction of cytokines/chemokines, which might contribute to the pathogenesis of liver injury. This study aimed to explore the cytokine/chemokine profiles of patients with HBV-ACLF and develop a composite clinical prognostic model.
METHODS
We prospectively collected blood samples and the clinical data of 107 patients with HBV-ACLF admitted to the Beijing Ditan Hospital. The concentrations of 40-plex cytokines/chemokines were measured in 86 survivors and 21 non-survivors using the Luminex assay. Discrimination between the cytokine/chemokine profiles in different prognosis groups was analyzed using the multivariate statistical techniques of principal component analysis (PCA) and partial least squares discriminant analysis (PLS-DA). An immune-clinical prognostic model was obtained using multivariate logistic regression analysis.
RESULTS
The PCA and PLS-DA indicated that cytokine/chemokine profiling could clearly distinguish patients with different prognoses. A total of 14 cytokines, namely, IL-1β, IL-6, IL-8, IL-10, TNF-α, IFN-γ, CXCL1, CXCL2, CXCL9, CXCL13, CX3CL1, GM-SCF, CCL21, and CCL23, were significantly correlated with disease prognosis. Multivariate analysis identified CXCL2, IL-8, total bilirubin, and age as independent risk factors that constituted the immune-clinical prognostic model, which showed the strongest predictive value of 0.938 compared with those of the Chronic Liver Failure Consortium (CLIF-C) ACLF (0.785), Model for End-Stage Liver Disease (MELD) (0.669), and MELD-Na (0.723) scores ( < 0.05 for all).
CONCLUSION
The serum cytokine/chemokine profiles correlated with the 90-day prognosis of patients with HBV-ACLF. The proposed composite immune-clinical prognostic model resulted in more accurate prognostic estimates than those of the CLIF-C ACLF, MELD, and MELD-Na scores.
Topics: Humans; Hepatitis B virus; Acute-On-Chronic Liver Failure; Cytokines; End Stage Liver Disease; Interleukin-8; Severity of Illness Index; Prognosis
PubMed: 37180134
DOI: 10.3389/fimmu.2023.1133656 -
Ugeskrift For Laeger May 2021This review covers congenital hair shaft anomalies, which are conditions affecting hair shaft morphology. Sometimes suspected with the naked eye, often in need of... (Review)
Review
This review covers congenital hair shaft anomalies, which are conditions affecting hair shaft morphology. Sometimes suspected with the naked eye, often in need of microscopic examination to properly diagnose, these conditions could lead to the discovery of a complex genetic syndrome. Further knowledge is needed in order to establish a diagnosis, approach treatment alternatives and shed light on prognoses, which benefits patients. Our aim is to provide an updated summary of pathogenesis, clinical findings, treatment options and prognosis as well as psychosocial impact.
Topics: Hair; Hair Diseases; Humans; Microscopy; Prognosis
PubMed: 34060455
DOI: No ID Found -
Aging Oct 2023The purpose of the study was to investigate the role of exosome and lipid metabolism-related genes (EALMRGs) mRNA levels in the diagnosis and prognosis of Pancreatic...
OBJECTIVE
The purpose of the study was to investigate the role of exosome and lipid metabolism-related genes (EALMRGs) mRNA levels in the diagnosis and prognosis of Pancreatic Adenocarcinoma (PAAD).
METHODS
The mRNA expression pattern of PAAD and pan-cancers with prognostic data were obtained from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) database. EALMRGs were acquired from GeneCards and MSigDB database after merging and deduplication. Prognostic EALMRGs were screened through univariate COX regression analysis, and a prognostic model was constructed based on these genes by least absolute shrinkage and selection operator (LASSO) regression. The prognostic value of EALMRGs was then validated in pan-cancer data. The time characteristics ROC curve analysis was performed to evaluate the effectiveness of the prognostic genes.
RESULTS
We identified 5 hub genes (ABCB1, CAP1, EGFR, PPARG, SNCA) according to high and low-risk groups of prognoses. The risk formula was verified in three other cohort of pancreatic cancer patients and was explored in pan-cancer data. Additionally, T cell and dendritic cell infiltration was significantly increased in low-risk group. The expression of the 5 hub genes was also identified in single-cell sequencing data of pancreatic cancer with pivotal pathways. Additionally, functional enrichment analysis based on pancreatic cancer data in pancreatic cancer showed that protein serine/threonine kinase activity, focal adhesion, actin binding, cell-substrate junction, organic acid transport, and regulation of transporter activity were significant related to the expression of genes in EALMRGs.
CONCLUSIONS
Our risk formula shows potential prognostic value in multiple cancers and manifest pivotal alterations in immune infiltration and biological pathway in pancreatic cancer.
Topics: Humans; Adenocarcinoma; Pancreatic Neoplasms; Lipid Metabolism; Exosomes; Prognosis; RNA, Messenger
PubMed: 37857015
DOI: 10.18632/aging.205130 -
Orphanet Journal of Rare Diseases Apr 2022Gorham-Stout syndrome (GSS) is a rare disorder with various presentations and unpredictable prognoses. Previous understandings of GSS mainly focused on progressive bone...
BACKGROUND
Gorham-Stout syndrome (GSS) is a rare disorder with various presentations and unpredictable prognoses. Previous understandings of GSS mainly focused on progressive bone destruction, while we identified a group of GSS patients with serous effusion as the first symptom. This study aimed to investigate the clinical characteristics of patients with GSS having serous effusion as the first symptom.
METHODS
Patients diagnosed with GSS were identified through the Peking Union Medical College Hospital Medical Record System. The demographic, clinical, laboratory, and imaging data were collected. Patients who first presented with serous effusion were recruited into the serous group, while those with bone destruction were recruited into the bone group.
RESULTS
Of the 23 patients with GSS enrolled, 13 were in the bone group and 10 in the serous group. The median disease duration was shorter and exercise tolerance was lower in the serous group. Despite less frequent bone pain in the serous group, the frequency of bone involvement was similar to that in the bone group. Patients in the serous group had higher rates of bilateral pleural effusion and multiple serous effusion. However, serous effusion also developed with disease progression in the bone group. Of the 17 patients treated with bisphosphonates, 14 reached bone-stable state. However, 5 out of 10 patients with serous effusion still had refractory effusions after bisphosphonates treatment. Three patients received sirolimus treatment, with an improvement in serous effusion. Seventeen patients were followed up; three patients died, two in the bone group and one in the serous group.
CONCLUSIONS
This study discovered that GSS could first be presented with serous effusion. We believe that this may be a new phenotype of the disease. Sirolimus might help in controlling serous effusion and improving prognosis.
Topics: Diphosphonates; Humans; Osteolysis, Essential; Prognosis; Serositis; Sirolimus
PubMed: 35379268
DOI: 10.1186/s13023-022-02307-8 -
Frontiers in Immunology 2023During tumor growth, tumor cells interact with their tumor microenvironment (TME) resulting in the development of heterogeneous tumors that promote tumor occurrence and...
BACKGROUND
During tumor growth, tumor cells interact with their tumor microenvironment (TME) resulting in the development of heterogeneous tumors that promote tumor occurrence and progression. Recently, there has been extensive attention on TME as a possible therapeutic target for cancers. However, an accurate TME-related prediction model is urgently needed to aid in the assessment of patients' prognoses and therapeutic value, and to assist in clinical decision-making. As such, this study aimed to develop and validate a new prognostic model based on TME-associated genes for BC patients.
METHODS
Transcriptome data and clinical information for BC patients were extracted from The Cancer Genome Atlas (TCGA) database. Gene Expression Omnibus (GEO) and IMvigor210 databases, along with the MSigDB, were utilized to identify genes associated with TMEs (TMRGs). A consensus clustering approach was used to identify molecular clusters associated with TMEs. LASSO Cox regression analysis was conducted to establish a prognostic TMRG-related signature, with verifications being successfully conducted internally and externally. Gene ontology (GO), KEGG, and single-sample gene set enrichment analyses (ssGSEA) were performed to investigate the underlying mechanisms. The potential response to ICB therapy was estimated using the Tumor Immune Dysfunction and Exclusion (TIDE) algorithm and Immunophenoscore (IPS). Additionally, it was found that the expression level of certain genes in the model was significantly correlated with objective responses to anti-PD-1 or anti-PD-L1 treatment in the IMvigor210, GSE111636, GSE176307, or Truce01 (registration number NCT04730219) cohorts. Finally, real-time PCR validation was performed on 10 paired tissue samples, and cytological experiments were also conducted on BC cell lines.
RESULTS
In BC patients, 133 genes differentially expressed that were associated with prognosis in TME. Consensus clustering analysis revealed three distinct clinicopathological characteristics and survival outcomes. A novel prognostic model based on nine TMRGs (including C3orf62, DPYSL2, GZMA, SERPINB3, RHCG, PTPRR, STMN3, TMPRSS4, COMP) was identified, and a TMEscore for OS prediction was constructed, with its reliable predictive performance in BC patients being validated. MultiCox analysis showed that the risk score was an independent prognostic factor. A nomogram was developed to facilitate the clinical viability of TMEscore. Based on GO and KEGG enrichment analyses, biological processes related to ECM and collagen binding were significantly enriched among high-risk individuals. In addition, the low-risk group, characterized by a higher number of infiltrating CD8+ T cells and a lower burden of tumor mutations, demonstrated a longer survival time. Our study also found that TMEscore correlated with drug susceptibility, immune cell infiltration, and the prediction of immunotherapy efficacy. Lastly, we identified SERPINB3 as significantly promoting BC cells migration and invasion through differential expression validation and phenotypic experiments.
CONCLUSION
Our study developed a prognostic model based on nine TMRGs that accurately and stably predicted survival, guiding individual treatment for patients with BC, and providing new therapeutic strategies for the disease.
Topics: Humans; Tumor Microenvironment; Urinary Bladder Neoplasms; Prognosis; Nomograms; Immunotherapy
PubMed: 37965307
DOI: 10.3389/fimmu.2023.1213947 -
Journal of Biomedical Informatics Oct 2022Electronic Health Records (EHRs) aggregate diverse information at the patient level, holding a trajectory representative of the evolution of the patient health status...
BACKGROUND
Electronic Health Records (EHRs) aggregate diverse information at the patient level, holding a trajectory representative of the evolution of the patient health status throughout time. Although this information provides context and can be leveraged by physicians to monitor patient health and make more accurate prognoses/diagnoses, patient records can contain information from very long time spans, which combined with the rapid generation rate of medical data makes clinical decision making more complex. Patient trajectory modelling can assist by exploring existing information in a scalable manner, and can contribute in augmenting health care quality by fostering preventive medicine practices (e.g. earlier disease diagnosis).
METHODS
We propose a solution to model patient trajectories that combines different types of information (e.g. clinical text, standard codes) and considers the temporal aspect of clinical data. This solution leverages two different architectures: one supporting flexible sets of input features, to convert patient admissions into dense representations; and a second exploring extracted admission representations in a recurrent-based architecture, where patient trajectories are processed in sub-sequences using a sliding window mechanism.
RESULTS
The developed solution was evaluated on two different clinical outcomes, unexpected patient readmission and disease progression, using the publicly available Medical Information Mart for Intensive Care (MIMIC)-III clinical database. The results obtained demonstrate the potential of the first architecture to model readmission and diagnoses prediction using single patient admissions. While information from clinical text did not show the discriminative power observed in other existing works, this may be explained by the need to fine-tune the clinicalBERT model. Finally, we demonstrate the potential of the sequence-based architecture using a sliding window mechanism to represent the input data, attaining comparable performances to other existing solutions.
CONCLUSION
Herein, we explored DL-based techniques to model patient trajectories and propose two flexible architectures that explore patient admissions on an individual and sequence basis. The combination of clinical text with other types of information led to positive results, which can be further improved by including a fine-tuned version of clinicalBERT in the architectures. The proposed solution can be publicly accessed at https://github.com/bioinformatics-ua/PatientTM.
Topics: Disease Progression; Electronic Health Records; Humans; Patient Readmission; Physicians; Prognosis
PubMed: 36150641
DOI: 10.1016/j.jbi.2022.104195 -
Therapeutic Advances in Respiratory... 2023The central role of inflammatory progression in the development of Coronavirus disease 2019 (COVID-19), especially in severe cases, is indisputable. However, the role of... (Meta-Analysis)
Meta-Analysis
BACKGROUND
The central role of inflammatory progression in the development of Coronavirus disease 2019 (COVID-19), especially in severe cases, is indisputable. However, the role of some novel inflammatory biomarkers in the prognosis of COVID-19 remains controversial.
OBJECTIVE
To assess the effect of some novel inflammatory biomarkers in the occurrence and prognosis of COVID-19.
METHODS
We systematically retrieved the studies related to COVID-19 and the inflammatory biomarkers of interest. The data of each biomarker in different groups were extracted, then were categorized and pooled. The standardized mean difference was chosen as an effect size measure to compare the difference between groups.
RESULTS
A total of 90 studies with 12,059 participants were included in this study. We found higher levels of endocan, PTX3, suPAR, sRAGE, galectin-3, and monocyte distribution width (MDW) in the COVID-19 positive groups compared to the COVID-19 negative groups. No significant differences for suPAR and galectin-3 were detected between the severe group and mild/moderate group of COVID-19. In addition, the deaths usually had higher levels of PTX3, sCD14-ST, suPAR, and MDW at admission compared to the survivors. Furthermore, patients with higher levels of endocan, galectin-3, sCD14-ST, suPAR, and MDW usually developed poorer comprehensive clinical prognoses.
CONCLUSIONS
In summary, this meta-analysis provides the most up-to-date and comprehensive evidence for the role of the mentioned novel inflammatory biomarkers in the prognosis of COVID-19, especially in evaluating death and other poor prognoses, with most biomarkers showing a better discriminatory ability.
Topics: Humans; Receptors, Urokinase Plasminogen Activator; Galectin 3; Lipopolysaccharide Receptors; COVID-19; Biomarkers; Prognosis
PubMed: 37727063
DOI: 10.1177/17534666231199679 -
Annals of Medicine Dec 2023Epstein-Barr virus (EBV)-associated hemophagocytic lymphohistiocytosis (EBV-HLH) is a common subtype of HLH with heterogeneous clinical presentations from self-limited...
BACKGROUND
Epstein-Barr virus (EBV)-associated hemophagocytic lymphohistiocytosis (EBV-HLH) is a common subtype of HLH with heterogeneous clinical presentations from self-limited to death, of which adults are worse than children.
OBJECTIVE
To establish predictors of mortality risk in adult EBV-HLH patients for timely and appropriate treatment.
METHODS
Patients with confirmed EBV-HLH admitted to Beijing Friendship Hospital from January 2015 to December 2019 were enrolled and statistical analysis of their laboratory test results was performed.
RESULTS
Among 246 adult patients with EBV-HLH, the deceased were older ( < 0.05), with fewer blood cells ( < 0.05), poorer renal function ( < 0.01), higher levels of procalcitonin (PCT) ( < 0.01), as well as soluble interleukin-2 receptor (sCD25) ( < 0.01). The overall median survival time of patients was 135 days, 87 days for patients without transplantation and 294 days with transplantation ( < 0.001). A combined index of sCD25, PCT, and estimated glomerular filtration rate (eGFR) was obtained to predict prognosis, named the Improved HLH index (IH index), and patients were divided into three groups meeting IH- (i.e. sCD25 ≤ 18,000 pg/mL, PCT ≤ 1.8 ng/mL, eGFR ≥ 90 mL/min/1.73m), IH1+ (i.e. only sCD25 > 18,000 pg/mL or only eGFR < 90 mL/min/1.73m), and IH2+ (i.e. the rest), respectively. In patients with the HScore ≥ 169 or meeting HLH-04, those meeting IH2+ had significantly worse prognoses than those who met IH1+ or IH- ( < 0.001). In the group meeting IH + or IH2+, patients who received allo-HSCT had better prognoses than those who did not ( < 0.05), but there was still a significant difference in prognosis among the three groups in transplanted patients ( < 0.001).
CONCLUSION
The IH index can early identify adult patients with a poor prognosis of EBV-HLH, initiating timely and appropriate treatment.KEY MESSAGESA combined index of sCD25, PCT, and eGFR was obtained to predict prognosis, named the Improved Hemophagocytic Lymphohistiocytosis index (IH index).IH index can early identify adult patients with a poor prognosis of EBV-HLH, initiating timely and appropriate treatment.
Topics: Child; Humans; Adult; Lymphohistiocytosis, Hemophagocytic; Herpesvirus 4, Human; Epstein-Barr Virus Infections; Retrospective Studies; Prognosis
PubMed: 36533966
DOI: 10.1080/07853890.2022.2149850 -
Frontiers in Immunology 2023Lipid metabolic reprogramming is gaining attention as a hallmark of cancers. Recent mounting evidence indicates that the malignant behavior of breast cancer (BC) is...
INTRODUCTION
Lipid metabolic reprogramming is gaining attention as a hallmark of cancers. Recent mounting evidence indicates that the malignant behavior of breast cancer (BC) is closely related to lipid metabolism. Here, we focus on the estrogen receptor-positive (ER+) subtype, the most common subgroup of BC, to explore immunometabolism landscapes and prognostic significance according to lipid metabolism-related genes (LMRGs).
METHODS
Samples from The Cancer Genome Atlas (TCGA) database were used as training cohort, and samples from the Molecular Taxonomy of Breast Cancer International Consortium (METABRIC), Gene Expression Omnibus (GEO) datasets and our cohort were applied for external validation. The survival-related LMRG molecular pattern and signature were constructed by unsupervised consensus clustering and least absolute shrinkage and selection operator (LASSO) analysis. A lipid metabolism-related clinicopathologic nomogram was established. Gene enrichment and pathway analysis were performed to explore the underlying mechanism. Immune landscapes, immunotherapy and chemotherapy response were further explored. Moreover, the relationship between gene expression and clinicopathological features was assessed by immunohistochemistry.
RESULTS
Two LMRG molecular patterns were identified and associated with distinct prognoses and immune cell infiltration. Next, a prognostic signature based on nine survival-related LMRGs was established and validated. The signature was confirmed to be an independent prognostic factor and an optimal nomogram incorporating age and T stage (AUC of 5-year overall survival: 0.778). Pathway enrichment analysis revealed differences in immune activities, lipid biosynthesis and drug metabolism by comparing groups with low- and high-risk scores. Further exploration verified different immune microenvironment profiles, immune checkpoint expression, and sensitivity to immunotherapy and chemotherapy between the two groups. Finally, arachidonate 15-lipoxygenase (ALOX15) was selected as the most prominent differentially expressed gene between the two groups. Its expression was positively related to larger tumor size, more advanced tumor stage and vascular invasion in our cohort (n = 149).
DISCUSSION
This is the first lipid metabolism-based signature with value for prognosis prediction and immunotherapy or chemotherapy guidance for ER+ BC.
Topics: Humans; Female; Breast Neoplasms; Lipid Metabolism; Prognosis; Nomograms; Lipids; Tumor Microenvironment
PubMed: 37469520
DOI: 10.3389/fimmu.2023.1199465 -
Frontiers in Immunology 2023Patients with pancreatic duct adenocarcinoma (PDAC) have varied prognoses that depend on numerous variables. However, additional research is required to uncover the...
BACKGROUND
Patients with pancreatic duct adenocarcinoma (PDAC) have varied prognoses that depend on numerous variables. However, additional research is required to uncover the latent impact of ubiquitination-related genes (URGs) on determining PDAC patients' prognoses.
METHODS
The URGs clusters were discovered via consensus clustering, and the prognostic differentially expressed genes (DEGs) across clusters were utilized to develop a signature using a least absolute shrinkage and selection operator (LASSO) regression analysis of data from TCGA-PAAD. Verification analyses were conducted across TCGA-PAAD, GSE57495 and ICGC-PACA-AU to show the robustness of the signature. RT-qPCR was used to verify the expression of risk genes. Lastly, we formulated a nomogram to improve the clinical efficacy of our predictive tool.
RESULTS
The URGs signature, comprised of three genes, was developed and was shown to be highly correlated with the prognoses of PAAD patients. The nomogram was established by combining the URGs signature with clinicopathological characteristics. We discovered that the URGs signature was remarkably superior than other individual predictors (age, grade, T stage, et al). Also, the immune microenvironment analysis indicated that ESTIMATEscore, ImmuneScores, and StromalScores were elevated in the low-risk group. The immune cells that infiltrated the tissues were different between the two groups, as did the expression of immune-related genes.
CONCLUSION
The URGs signature could act as the biomarker of prognosis and selecting appropriate therapeutic drugs for PDAC patients.
Topics: Humans; Prognosis; Carcinoma, Pancreatic Ductal; Ubiquitination; Pancreatic Neoplasms; Pancreatic Ducts; Tumor Microenvironment
PubMed: 37359528
DOI: 10.3389/fimmu.2023.1171811