Prognostic Marker Of Disease Progression Research Articles

Unveiling Functional Biomarkers in Schizophrenia: Insights from Region of Interest Analysis Using Machine Learning.

Schizophrenia is a complex and disabling mental disorder that represents one of the most important challenges for neuroimaging research. There were many attempts to understand these basic mechanisms behind the disorder, yet we know very little. By employing machine learning techniques with age-matched samples from the auditory oddball task using multi-site functional magnetic resonance imaging (fMRI) data, this study aims to address these challenges. The study employed a three-stage model to gain a better understanding of the neurobiology underlying schizophrenia and techniques that could be applied for diagnosis. At first, we constructed four-level hierarchical sets from each fMRI volume of 34 schizophrenia patients (SZ) and healthy controls (HC) individually in terms of hemisphere, gyrus, lobes, and Brodmann areas. Second, we employed statistical methods, namely, t-tests and Pearson's correlation, to assess the group differences in cortical activation. Finally, we assessed the predictive power of the brain regions for machine learning algorithms using K-nearest Neighbor (KNN), Naive Bayes, Decision Tree (DT), Random Forest (RF), Support Vector Machines (SVMs), and Extreme Learning Machine (ELM). Our investigation depicts promising results, obtaining an accuracy of up to 84% when applying Pearson's correlation-selected features at lobes and Brodmann region level (81% for Gyrus), as well as Hemispheres involving different stages. Thus, the results of our study were consistent with previous studies that have revealed some functional abnormalities in several brain regions. We also discovered the involvement of other brain regions which were never sufficiently studied in previous literature, such as the posterior lobe (posterior cerebellum), Pyramis, and Brodmann Area 34. We present a unique and comprehensive approach to investigating the neurological basis of schizophrenia in this study. By bridging the gap between neuroimaging and computable analysis, we aim to improve diagnostic accuracy in patients with schizophrenia and identify potential prognostic markers for disease progression.

A prognostic impact of interleukin 32 (IL-32) as an immune marker in patients with bladder cancer

Background. Urinary bladder cancer is a prevalent global health concern. IL-32 is a cytokine that promotes inflammation and has been shown in multiple studies to suppress the development of cancer cells and trigger cell death in different types of cancer cells. Materials and methods. Expression of 32 interleukins was determined using an immunohistochemistry technique, which uses analysis of the exact concentrations and locations of specific compounds in tissues. This is done by using antibodies (antibodies) that react with the target protein (in this case IL-32), then identifying the sites where the active protein is located. The study included 114 diagnosed bladder cancer samples and 10 healthy controls. Results. By analyzing the expression of IL-32 using IHC technology on both bladder tissue from cancer patients and healthy bladder tissue that was considered a control, the results of evaluating IL-32 levels in bladder tissue from cancer patients showed a high level. Conclusion. High levels of IL-32 indicate disease progression or a poor outcome, while low levels can indicate an improvement or a good outcome. This is consistent with the fundamental aim of this study: the possibility of using IL-32 as a diagnostic or prognostic marker for disease progression and outcome prediction in cancer patients.

Diagnostic and Prognostic Markers for Pancreatitis and Pancreatic Ductal Adenocarcinoma.

Diagnostic markers are desperately needed for the early detection of pancreatic ductal adenocarcinoma (PDA). We describe sets of markers expressed in temporal order in mouse models during pancreatitis, PDA initiation and progression. Cell type specificity and the differential expression of PDA markers were identified by screening single cell (sc) RNAseq from tumor samples of a mouse model for PDA (KIC) at early and late stages of PDA progression compared to that of a normal pancreas. Candidate genes were identified from three sources: (1) an unsupervised screening of the genes preferentially expressed in mouse PDA tumors; (2) signaling pathways that drive PDA, including the Ras pathway, calcium signaling, and known cancer genes, or genes encoding proteins that were identified by differential mass spectrometry (MS) of mouse tumors and conditioned media from human cancer cell lines; and (3) genes whose expression is associated with poor or better prognoses (PAAD, oncolnc.org). The developmental progression of PDA was detected in the temporal order of gene expression in the cancer cells of the KIC mice. The earliest diagnostic markers were expressed in epithelial cancer cells in early-stage, but not late-stage, PDA tumors. Other early markers were expressed in the epithelium of both early- and late-state PDA tumors. Markers that were expressed somewhat later were first elevated in the epithelial cancer cells of the late-stage tumors, then in both epithelial and mesenchymal cells, or only in mesenchymal cells. Stromal markers were differentially expressed in early- and/or late-stage PDA neoplasia in fibroblast and hematopoietic cells (lymphocytes and/or macrophages) or broadly expressed in cancer and many stromal cell types. Pancreatitis is a risk factor for PDA in humans. Mouse models of pancreatitis, including caerulein treatment and the acinar-specific homozygous deletion of differentiation transcription factors (dTFs), were screened for the early expression of all PDA markers identified in the KIC neoplasia. Prognostic markers associated with a more rapid decline were identified and showed differential and cell-type-specific expression in PDA, predominately in late-stage epithelial and/or mesenchymal cancer cells. Select markers were validated by immunohistochemistry in mouse and human samples of a normal pancreas and those with early- and late-stage PDA. In total, we present 2165 individual diagnostic and prognostic markers for disease progression to be tested in humans from pancreatitis to late-stage PDA.

Cardiovascular autonomic failure in hereditary transthyretin amyloidosis and TTR carriers is an early and progressive disease marker.

The cardiomyopathic and neuropathic phenotype of hereditary transthyretin amyloidosis are well recognized. Cardiovascular autonomic dysfunction is less systematically and objectively assessed. Autonomic and clinical features, quantitative cardiovascular autonomic function, and potential autonomic prognostic markers of disease progression were recorded in a cohort of individuals with hereditary transthyretin amyloidosis and in asymptomatic carriers of TTR variants at disease onset (T0) and at the time of the first quantitative autonomic assessment (T1). The severity of peripheral neuropathy and its progression was stratified with the polyneuropathy disability score. A total of 124 individuals were included (111 with a confirmed diagnosis of hereditary transthyretin amyloidosis, and 13 asymptomatic carriers of TTR variants). Symptoms of autonomic dysfunction were reported by 27% individuals at T0. Disease duration was 4.5 ± 4.0years [mean ± standard deviation (SD)] at autonomic testing (T1). Symptoms of autonomic dysfunction were reported by 78% individuals at T1. Cardiovascular autonomic failure was detected by functional testing in 75% individuals and in 64% of TTR carriers. Progression rate from polyneuropathy disability stages I/II to III/IV seemed to be shorter for individuals with autonomic symptoms at onset [2.33 ± 0.56 versus 4.00 ± 0.69years (mean ± SD)]. Cardiovascular autonomic dysfunction occurs early and frequently in individuals with hereditary transthyretin amyloidosis within 4.5years from disease onset. Cardiovascular autonomic failure can be subclinical in individuals and asymptomatic carriers, and only detected with autonomic function testing, which should be considered a potential biomarker for early diagnosis and disease progression.

Anemia as a Prognostic Marker for Disease Progression in HIV Infection

Anemia, a prevalent hematologic manifestation in individuals living with Human Immunodeficiency Virus (HIV) infection, has garnered considerable attention as a prognostic indicator for disease progression and adverse clinical outcomes. This abstract presents a comprehensive review elucidating the intricate relationship between anemia and the progression of HIV infection, incorporating epidemiological trends, underlying pathophysiological mechanisms, clinical implications, and prognostic significance. Despite advances in antiretroviral therapy (ART), anemia remains a frequent complication in HIVinfected individuals, posing substantial challenges to patient management. This paper aims to provide a nuanced understanding of anemia's role as a prognostic marker, surpassing its conventional characterization as a hematologic abnormality in the context of HIV infection. Anemia's role as a predictive marker for adverse clinical outcomes in HIV patients is explored, encompassing increased mortality rates, heightened risk of opportunistic infections, accelerated disease progression, and compromised quality of life. The review delves into its prognostic significance, shaping therapeutic decisions and prognostic assessments. This paper encapsulates the criticality of anemia as a prognostic marker for disease progression in HIV infection. Understanding its epidemiology, pathophysiological mechanisms, clinical implications, and prognostic significance is pivotal for informed clinical decision-making, prognostic assessments, and optimizing care paradigms in HIV management. Keywords: Anemia, Prognostic Marker, Disease Progression and HIV

MicroRNAs as biomarkers of multiple sclerosis progression

Multiple sclerosis (MS) is an autoimmune inflammatory neurodegenerative disease of the central nervous system. The disease is characterized by a heterogeneous clinical course, which is reflected in the fact that there are various types, such as relapsing-remitting MS (RRMS), primary and secondary progressive MS (PPMS and SPMS, respectively). Currently, there is an active search for MS biomarkers capable of predicting and assessing disease progression with high sensitivity and specificity, which would be of great benefit in determining treatment tactics and evaluating their efficacy. MicroRNAs (miRNAs) are short (21–25 nucleotides) non-coding RNA molecules that are primarily involved in post-transcriptional regulation of gene expression. miRNAs play an essential role in tissue development, homeostasis, immune system regulation, and immune cell maturation; they are also involved in the pathophysiology of MS. In addition, high hopes are pinned on miRNAs as disease biomarkers, mainly due to their stability and ability to be released from cells into the extracellular space and circulate there for a long time. The review considers published data on miRNAs in different types of MS. In the future, changes in their levels may be used to create a panel of prognostic markers for disease progression. Studies of miRNAs levels in both circulating fluids (plasma, serum, cerebrospinal fluid) and brain tissue of MS patients were reviewed. Based on the aggregated data from the studies reviewed, it can be confirmed that the accumulated data are quite sufficient to recognize that regulatory miRNAs molecules are involved in the pathophysiological mechanisms of MS progression. However, there is still a long way to go to establish a panel of circulating miRNAs that predict the rate of progression of MS.

Study of mucocutaneous manifestations in HIV-infected patients and its relation to cd4 count and stage of HIV disease

: HIV patients frequently have mucocutaneous manifestations, which could be the first sign of the infection and can also be prognostic markers for disease progression. This study was done to note the different mucocutaneous manifestations occurring in the people living with HIV/AIDS.: One hundred ensuent HIV seropositive patients who attended the opd were included in the study.: The bulk of the study participants were illiterate, had a mean age of 32, and a male to female ratio of 2:1. The patients' number of manifestations ranged from 01 to 05. The most typical illnesses observed in this investigation were dermatophyte infections followed by oral candidiasis. The most frequent non-infectious symptoms observed in this investigation were SD and PPE. The most prevalent STI was herpes genitalis. Inversely correlated with CD4 level were the type, number, and severity of mucocutaneous symptoms. The number of manifestations and CD4 count were found to be inversely correlated. The majority of PLHAs (55%) exhibited several manifestations. The majority of the manifestations are unusual, persistent, recurrent, and resistant to the therapy. Young patients presenting with extensive SD, PPE, OC, scrofuloderma, and HZ should encourage the clinician to investigate the patient's sero-reactivity status

Common pathogenetic mechanisms in affective disorders and multiple sclerosis: role of interleukin imbalance in the progression of comorbid pathology

Relevance. Among many comorbid pathologies, it is of considerable interest to study and compare the pathogenetic mechanisms of neurological and mental disorders that combine the clinical manifestations of multiple sclerosis (MS) and affective disorders. The high MS prevalence, economic and social significance of the disease, heterogeneity of clinical symptoms, an unfavorable progressive course, as well as the frequent combination of this pathology with various forms of hypothymic disorders determine the relevance of studying the common pathogenetic mechanisms for the development of this comorbid pathology, which is necessary for the development of effective and safe preventive medical activities. The purpose of the review is to determine the common immunopathological mechanisms of affective disorders and multiple sclerosis, to analyze the role of cytokine status imbalance in the mutual increase in the severity of clinical symptoms in comorbid pathology, and to identify prognostic markers of disease progression. Materials and methods. On the basis of electronic Russian and foreign databases for the period 2017–2022, a theoretical analysis of the pathophysiological mechanisms of autoimmune CNS damage in MS and affective disorders was carried out. In order to search for literary sources, the following resources were used: https://elibrary.ru/, https://www.ncbi.nlm.nih.gov/pubmed/, https://cyberleninka.ru/. 10 Russian and 25 foreign sources were cited. Results. The mechanisms of development of mental affective disorders and multiple sclerosis have common pathogenetic features and are characterized by a violation of pro-inflammatory cytokine reactions and autoimmune nature of changes in the structures of the central nervous system (CNS). The similarity of immunological disorders underlying the pathogenesis of various forms of multiple sclerosis and affective disorders is of undoubted interest in terms of developing common approaches to the prevention and treatment of detectable interleukin status imbalance in neurological and mental diseases. Conclusion. Identification of mutually reinforcing changes in interleukin status and determination of the features of the course of immune imbalance in multiple sclerosis and hypothymic disorders in various pathologies of the mental sphere are necessary for a deeper understanding of neuroimmune interactions.

Utility of laboratory and immune biomarkers in predicting disease progression and mortality among patients with moderate to severe COVID-19 disease at a Philippine tertiary hospital.

This study was performed to determine the clinical biomarkers and cytokines that may be associated with disease progression and in-hospital mortality in a cohort of hospitalized patients with RT-PCR confirmed moderate to severe COVID-19 infection from October 2020 to September 2021, during the first wave of COVID-19 pandemic before the advent of vaccination. Clinical profile was obtained from the medical records. Laboratory parameters (complete blood count [CBC], albumin, LDH, CRP, ferritin, D-dimer, and procalcitonin) and serum concentrations of cytokines (IL-1β, IL-2, IL-4, IL-6, IL-8, IL-10, IL-18, IFN-γ, IP-10, TNF-α) were measured on Days 0-3, 4-10, 11-14 and beyond Day 14 from the onset of illness. Regression analysis was done to determine the association of the clinical laboratory biomarkers and cytokines with the primary outcomes of disease progression and mortality. ROC curves were generated to determine the predictive performance of the cytokines. We included 400 hospitalized patients with COVID-19 infection, 69% had severe to critical COVID-19 on admission. Disease progression occurred in 139 (35%) patients, while 18% of the total cohort died (73 out of 400). High D-dimer >1 µg/mL (RR 3.5 95%CI 1.83-6.69), elevated LDH >359.5 U/L (RR 1.85 95%CI 1.05-3.25), lymphopenia (RR 1.91 95%CI 1.14-3.19), and hypoalbuminemia (RR 2.67, 95%CI 1.05-6.78) were significantly associated with disease progression. High D-dimer (RR 3.95, 95%CI 1.62-9.61) and high LDH (RR 5.43, 95%CI 2.39-12.37) were also significantly associated with increased risk of in-hospital mortality. Nonsurvivors had significantly higher IP-10 levels at 0 to 3, 4 to 10, and 11 to 14 days from illness onset (p<0.01), IL-6 levels at 0 to 3 days of illness (p=0.03) and IL-18 levels at days 11-14 of illness (p<0.001) compared to survivors. IP-10 had the best predictive performance for disease progression at days 0-3 (AUC 0.81, 95%CI: 0.68-0.95), followed by IL-6 at 11-14 days of illness (AUC 0.67, 95%CI: 0.61-0.73). IP-10 predicted mortality at 11-14 days of illness (AUC 0.77, 95%CI: 0.70-0.84), and IL-6 beyond 14 days of illness (AUC 0.75, 95%CI: 0.68-0.82). Elevated D-dimer, elevated LDH, lymphopenia and hypoalbuminemia are prognostic markers of disease progression. High IP-10 and IL-6 within the 14 days of illness herald disease progression. Additionally, elevated D-dimer and LDH, high IP-10, IL-6 and IL-18 were also associated with mortality. Timely utilization of these biomarkers can guide clinical monitoring and management decisions for COVID-19 patients in the Philippines.

A Single-Center Experience on the Treatment Outcomes of Patients with COVID-19-Pleural Disorders: Lessons for the Future.

Pleural disorders in novel coronavirus disease 2019 (COVID-19), responsible for the deaths of more than 6.7 million people worldwide, are relatively uncommon and underappreciated findings. The severity of the pleural disease in these patients correlates with the treatment outcome and overall prognosis. We aim to review our experience with treatment modalities and prognosis in 45 patients with COVID-19, who were treated at our Clinic between April 2020 and October 2021. We conducted a retrospective, single-center, cross-sectional study. Demographic data, the type of thoracosurgical intervention(s), and treatment outcome for 45 patients included in this study were recorded for every patient. We analyzed the type and number of treatment modalities according to the pleural disorder, and the outcome of the treatment. Pneumothorax was the most common COVID-19-related pleural disorder, followed by the pleural effusion. Tube thoracostomy was the mainstay of treatment, performed in 84.4% of patients with unilateral pleural complications. In total, 20% of our patients were on mechanical ventilation, and all of them had a fatal outcome. We found statistical significance in comparison to the percentage of fatal outcomes between patients treated with and without mechanical ventilation (p=0.000). COVID-19-related pleural disorders are prognostic markers of disease progression. Mechanically ventilated patients who require tube thoracostomy have an unfavorable prognosis.

Baseline Cerebrospinal Fluid α-Synuclein in Parkinson's Disease Is Associated with Disease Progression and Cognitive Decline.

Biomarkers are increasingly recognized as tools in the diagnosis and prognosis of neurodegenerative diseases. No fluid biomarker for Parkinson’s disease (PD) has been established to date, but α-synuclein, a major component of Lewy bodies in PD and dementia with Lewy bodies (DLB), has become a promising candidate. Here, we investigated CSF α-synuclein in patients with PD (n = 28), PDD (n = 8), and DLB (n = 5), applying an electrochemiluminescence immunoassay. Median values were non-significantly (p = 0.430) higher in patients with PDD and DLB (287 pg/mL) than in PD (236 pg/mL). A group of n = 36 primarily non-demented patients with PD and PDD was clinically followed for up to two years. A higher baseline α-synuclein was associated with increases in Hoehn and Yahr classifications (p = 0.019) and Beck Depression Inventory scores (p < 0.001) as well as worse performance in Trail Making Test A (p = 0.017), Trail Making Test B (p = 0.043), and the Boston Naming Test (p = 0.002) at follow-up. Surprisingly, higher levels were associated with a better performance in semantic verbal fluency tests (p = 0.046). In summary, CSF α-synuclein may be a potential prognostic marker for disease progression, affective symptoms, and executive cognitive function in PD. Larger-scaled studies have to validate these findings and the discordant results for single cognitive tests in this exploratory investigation.

Candidate diagnostic and prognostic markers for pancreatitis and pancreatic ductal adenocarcinoma

Diagnostic markers are desperately needed for early detection of pancreatic ductal adenocarcinoma (PDA). We describe sets of markers expressed in temporal order in mouse models during pancreatitis, PDA initiation and progression. Cell type specificity of PDA marker expression was analyzed by interrogating quantitative dot plots of single cell (sc) RNAseq for 3021 candidate genes in tumor samples from a mouse model for PDA (KIC) at early and late stages of PDA progression compared to normal pancreas. Protein markers were identified by differential mass spectrometry (MS) of mouse tumors and conditioned media from human cancer cell lines. Additional candidate genes were identified from signaling pathways that drive PDA, including the Ras pathway, calcium signaling, and known cancer genes. Developmental progression of cancer was revealed in seven classes of PDA markers expressed in cancer cells and stroma. The earliest diagnostic markers (47 genes) were specifically expressed in epithelial cancer cells in early, but not late, PDA tumors. Other markers were first elevated in epithelial cancer cells of late stage tumors (288 genes), or in both epithelial and mesenchymal cells (740 genes), or only in mesenchymal cells (216 genes). Stromal markers were differentially expressed in early‐ and/or late‐PDA neoplasia (594 genes). Pancreatitis is a risk factor for PDA in humans. Mouse models of pancreatitis, including caerulein treatment and acinar‐specific homozygous deletion of differentiation transcription factors (dTFs), were screened for early expression of all PDA markers identified in KIC neoplasia. Select diagnostic markers were validated by immunohistochemistry in mouse and human samples of normal pancreas, early‑ and late‐stage PDA. Prognostic markers from TCGA were identified that showed differential and cell type‐specific expression in PDA. Here we present diagnostic and prognostic markers for disease progression from pancreatitis to late‐stage PDA.

Bioactive Lipids as Chronic Myeloid Leukemia's Potential Biomarkers for Disease Progression and Response to Tyrosine Kinase Inhibitors.

Chronic myelogenous leukemia (CML) is a myeloproliferative neoplasm that expresses the Philadelphia chromosome and constitutively activated Bcr-Abl tyrosine kinase in hematopoietic progenitor cells. Bcr-Abl tyrosine-kinase inhibitors (TKI) do not definitively cure all CML patients. The efficacy of TKI is reduced in CML patients in the blastic phase—the most severe phase of the disease—and resistance to this drug has emerged. There is limited knowledge on the underlying mechanisms of disease progression and resistance to TKI beyond BCR-ABL1, as well as on the impact of TKI treatment and disease progression on the metabolome of CML patients. The present study reports the metabolomic profiles of CML patients at different phases of the disease treated with TKI. The plasma metabolites from CML patients were analyzed using liquid chromatography, mass spectrometry, and bioinformatics. Distinct metabolic patterns were identified for CML patients at different phases of the disease and for those who were resistant to TKI. The lipid metabolism in CML patients at advanced phases and TKI-resistant patients is reprogrammed, as detected by analysis of metabolomic data. CML patients who were responsive and resistant to TKI therapy exhibited distinct enriched pathways. In addition, ceramide levels were higher and sphingomyelin levels were lower in resistant patients compared with control and CML groups. Taken together, the results here reported established metabolic profiles of CML patients who progressed to advanced phases of the disease and failed to respond to TKI therapy as well as patients in remission. In the future, an expanded study on CML metabolomics may provide new potential prognostic markers for disease progression and response to therapy.

Characterization of Cellular and Acellular Analytes from Pre-Cystectomy Liquid Biopsies in Patients Newly Diagnosed with Primary Bladder Cancer.

Simple SummaryThe standard of care for patients diagnosed with localized bladder cancer (BCa) is cystectomy. However, emerging evidence shows that the patients receiving surgical intervention often experience a return of their cancer. Examining patient blood samples for rare events, such as circulating tumor cells (CTCs) and large extracellular vesicles (LEVs), may reveal biomarkers indicative of the presence of cancer and provide an insight into disease progression. Through computational methodologies, each event in the blood was characterized to determine its rarity within the sample and then compared to events found in normal donors. We demonstrate that a wide range of CTCs and LEVs are found in significantly higher proportions among BCa patients compared to normal donors. This result suggests that the blood liquid biopsy is a proficient analyte for detecting BCa to ultimately guide clinical decisions to improve patient treatment outcomes.Urinary bladder cancer (BCa) is the 10th most frequent cancer in the world, most commonly found among the elderly population, and becomes highly lethal once cells have spread from the primary tumor to surrounding tissues and distant organs. Cystectomy, alone or with other treatments, is used to treat most BCa patients, as it offers the best chance of cure. However, even with curative intent, 29% of patients experience relapse of the cancer, 50% of which occur within the first year of surgery. This study aims to use the liquid biopsy to noninvasively detect disease and discover prognostic markers for disease progression. Using the third generation high-definition single cell assay (HDSCA3.0), 50 bladder cancer patient samples and 50 normal donor (ND) samples were analyzed for circulating rare events in the peripheral blood (PB), including circulating tumor cells (CTCs) and large extracellular vesicles (LEVs). Here, we show that (i) CTCs and LEVs are detected in the PB of BCa patients prior to cystectomy, (ii) there is a high heterogeneity of CTCs, and (iii) liquid biopsy analytes correlate with clinical data elements. We observed a significant difference in the incidence of rare cells and LEVs between BCa and ND samples (median of 74.61 cells/mL and 30.91 LEVs/mL vs. 34.46 cells/mL and 3.34 LEVs/mL, respectively). Furthermore, using classification models for the liquid biopsy data, we achieved a sensitivity of 78% and specificity of 92% for the identification of BCa patient samples. Taken together, these data support the clinical utility of the liquid biopsy in detecting BCa, as well as the potential for predicting cancer recurrence and survival post-cystectomy to better inform treatment decisions in BCa care.

Secretogranin II impairs tumor growth and angiogenesis by promoting degradation of hypoxia‐inducible factor‐1α in colorectal cancer

Distant metastasis is a major cause of death in patients with colorectal cancer (CRC) but the management of advanced and metastatic CRC still remains problematic due to the distinct molecular alterations during tumor progression. Tumor angiogenesis is a key step in tumor growth, invasion and metastasis. However, the signaling pathways involved in angiogenesis are poorly understood. The results of the present study showed that secretogranin II (SCG2) was significantly downregulated in malignant CRC tissues, and higher expression of SCG2 was correlated with longer disease‐free survival and overall survival of CRC patients. The results of an animal study showed that ectopic expression of SCG2 significantly inhibited CRC tumor growth by disrupting angiogenesis. Furthermore, the inhibition of expression of vascular endothelial growth factor (VEGF) by SCG2 and rescue of VEGF effectively blocked SCG2‐induced inhibition of angiogenesis. Investigations into the underlying mechanism suggested that SCG2 promoted degradation of hypoxia‐inducible factor (HIF)‐1α by interacting with the von Hippel–Lindau tumor suppressor in CRC cells. Blocking of degradation of HIF‐1α effectively attenuated the SCG2‐mediated decrease in expression of VEGF in CRC cells. Collectively, these results demonstrated that treatment with SCG2 effectively inhibited CRC tumor growth by disrupting the activities of HIF‐1α/VEGF, thereby clarifying the anti‐tumor and anti‐angiogenesis roles of SCG2 in CRC, while providing a novel therapeutic target and a potential prognostic marker of disease progression.

Detection of p53 Protein in Leukemic Cells by Flow Cytometry.

Although the alterations of TP53 gene are rare in malignant hematological disorders, these genetic alterations have strong correlations with unfavorable prognostic factors and are found in relapse acute lymphoid leukemia (ALL), relapse acute myeloid leukemia (AML), blastic crisis of chronic myeloid leukemia (CML) and evolution from chronic lymphoid leukemia to Richter's syndrome (CLL/SR). Most methods currently used to study TP53 gene employ molecular biology techniques such as single strand conformation polymorphism (PCR-SSCP) and direct DNA sequencing. Both techniques detect TP53 gene mutation but not p53 protein expression and are time-consuming and difficult to apply in the clinical setting. In the last years, p53 protein expression has emerged as a potential prognostic marker, which can be used to study TP53 gene alterations in malignant diseases. The aim of this work was to validate flow cytometry (FC) technique to detect p53 expression in different types of leukemias and analyze the relationship between p53 expression and status of disease. We studied p53 protein expression in 223 blood and bone marrow samples: 72 patients with CML, 54 in chronic phase (CML-CP), 7 in accelerated phase (CML-AP) and 11 in blastic crisis (CML-BC); 64 patients with CLL (34 at diagnosis and 9 with Richter's syndrome), 44 patients with ALL (36 at diagnosis and 8 in relapse) and 43 AML (27 de novo, 7 in relapse and 9 secondary AML). p53 protein expression was observed in 63 out of 223 patient's samples: 14/64 CLL (21.9%), 13/44 ALL (29.5%), 19/43 AML (44.2%) and 17/72 LMC (23.6%). The highest levels were detected in the advanced phases of CLL, ALL and CML. In addition, in AML cases, high levels of p53 expression were detected in secondary and relapse disease and also in de novo AML cases. Our results demonstrated that p53 expression levels are strongly associated with advanced disease. Based on these results flow cytometry can be a reliable approach to study p53 protein expression in leukemic patients. Further studies are needed to ascertain the role of p53 expression as a prognostic marker of disease progression.

Change in N-terminal pro-B-type natriuretic peptide at 1 year predicts mortality in wild-type transthyretin amyloid cardiomyopathy

ObjectivesWild-type transthyretin amyloid cardiomyopathy (wtATTR-CM) is a progressive and fatal condition. Although prognosis can be determined at the time of diagnosis according to National Amyloidosis Centre (NAC) transthyretin amyloidosis (ATTR)...

Neuropsychiatric symptoms in early stage of Alzheimer's and non-Alzheimer's dementia, and the risk of progression to severe dementia.

Neuropsychiatric symptoms (NPSs) in early dementia have been suggested to predict a higher risk of dementia progression. However, the literature is not yet clear whether the risk is similar across Alzheimer's dementia (AD) and non-Alzheimer's dementia (non-AD), as well as across different NPSs. This study examined the association between NPSs in early dementia and the risk of progression to severe dementia, specifically in AD and non-AD, as well as across various NPSs. This cohort study included 7,594 participants who were ≥65years and had early dementia (global Clinical Dementia Rating [CDR] = 1). Participants completed Neuropsychiatric-Inventory-Questionnaire at baseline and were followed-up almost annually for progression to severe dementia (global CDR = 3) (median follow-up = 3.5years; interquartile range = 2.1-5.9years). Cox regression was used to examine progression risk, stratified by AD and non-AD. The presence of NPSs was associated with risk of progression to severe dementia, but primarily in AD (HR 1.4, 95% confidence interval [CI]: 1.1-1.6) and not in non-AD (HR 0.9, 95% CI: 0.5-1.5). When comparing across various NPSs, seven NPSs in AD were associated with disease progression, and they were depression, anxiety, apathy, delusions, hallucinations, irritability and motor disturbance (HR 1.2-1.6). In contrast, only hallucinations and delusions were associated with disease progression in non-AD (HR 1.7-1.9). NPSs in early dementia-especially among individuals with AD-can be useful prognostic markers of disease progression. They may inform discussion on advanced care planning and prompt clinical review to incorporate evidence-based interventions that may address disease progression.

Developing and validating COVID-19 adverse outcome risk prediction models from a bi-national European cohort of 5594 patients

Patients with severe COVID-19 have overwhelmed healthcare systems worldwide. We hypothesized that machine learning (ML) models could be used to predict risks at different stages of management and thereby provide insights into drivers and prognostic markers of disease progression and death. From a cohort of approx. 2.6 million citizens in Denmark, SARS-CoV-2 PCR tests were performed on subjects suspected for COVID-19 disease; 3944 cases had at least one positive test and were subjected to further analysis. SARS-CoV-2 positive cases from the United Kingdom Biobank was used for external validation. The ML models predicted the risk of death (Receiver Operation Characteristics—Area Under the Curve, ROC-AUC) of 0.906 at diagnosis, 0.818, at hospital admission and 0.721 at Intensive Care Unit (ICU) admission. Similar metrics were achieved for predicted risks of hospital and ICU admission and use of mechanical ventilation. Common risk factors, included age, body mass index and hypertension, although the top risk features shifted towards markers of shock and organ dysfunction in ICU patients. The external validation indicated fair predictive performance for mortality prediction, but suboptimal performance for predicting ICU admission. ML may be used to identify drivers of progression to more severe disease and for prognostication patients in patients with COVID-19. We provide access to an online risk calculator based on these findings.

Prognostic Prediction Based on Dynamic Contrast-Enhanced MRI and Dynamic Susceptibility Contrast-Enhanced MRI Parameters from Non-Enhancing, T2-High-Signal-Intensity Lesions in Patients with Glioblastoma.

ObjectiveFew attempts have been made to investigate the prognostic value of dynamic contrast-enhanced (DCE) MRI or dynamic susceptibility contrast (DSC) MRI of non-enhancing, T2-high-signal-intensity (T2-HSI) lesions of glioblastoma multiforme (GBM) in newly diagnosed patients. This study aimed to investigate the prognostic values of DCE MRI and DSC MRI parameters from non-enhancing, T2-HSI lesions of GBM.Materials and MethodsA total of 76 patients with GBM who underwent preoperative DCE MRI and DSC MRI and standard treatment were retrospectively included. Six months after surgery, the patients were categorized into early progression (n = 15) and non-early progression (n = 61) groups. We extracted and analyzed the permeability and perfusion parameters of both modalities for the non-enhancing, T2-HSI lesions of the tumors. The optimal percentiles of the respective parameters obtained from cumulative histograms were determined using receiver operating characteristic (ROC) curve and univariable Cox regression analyses. The results were compared using multivariable Cox proportional hazards regression analysis of progression-free survival.ResultsThe 95th percentile value (PV) of Ktrans, mean Ktrans, and median Ve were significant predictors of early progression as identified by the ROC curve analysis (area under the ROC curve [AUC] = 0.704, p = 0.005; AUC = 0.684, p = 0.021; and AUC = 0.670, p = 0.0325, respectively). Univariable Cox regression analysis of the above three parametric values showed that the 95th PV of Ktrans and the mean Ktrans were significant predictors of early progression (hazard ratio [HR] = 1.06, p = 0.009; HR = 1.25, p = 0.017, respectively). Multivariable Cox regression analysis, which also incorporated clinical parameters, revealed that the 95th PV of Ktrans was the sole significant independent predictor of early progression (HR = 1.062, p < 0.009).ConclusionThe 95th PV of Ktrans from the non-enhancing, T2-HSI lesions of GBM is a potential prognostic marker for disease progression.