Circulating miR-10b, soluble urokinase-type plasminogen activator receptor, and plasminogen activator inhibitor-1 as predictors of non-small cell lung cancer progression and treatment response

BACKGROUND

Despite advances in lung cancer treatment, most lung cancers are diagnosed at an advanced stage. Expression of microRNA10b (miR-10b) and fibrinolytic activity, as reflected by soluble urokinase-type plasminogen activator receptor (suPAR) and plasminogen activator inhibitor 1 (PAI-1), are promising biomarker candidates.

OBJECTIVE

To assess the expression of miR-10b, and serum levels of suPAR and PAI-1 in advanced stage non-small cell lung cancer (NSCLC) patients, and their correlation with progression, treatment response and prognosis.

METHODS

The present prospective cohort and survival study was conducted at Dharmais National Cancer Hospital and included advanced stage NSCLC patients diagnosed between March 2015 and September 2016. Expression of miR-10b was quantified using qRT-PCR. Levels of suPAR and PAI-1 were assayed using ELISA. Treatment response was evaluated using the RECIST 1.1 criteria. Patients were followed up until death or at least 1 year after treatment.

RESULTS

Among the 40 patients enrolled, 25 completed at least four cycles of chemotherapy and 15 patients died during treatment. Absolute miR-10b expression ⩾ 592,145 copies/μL or miR-10b fold change ⩾ 0.066 were protective for progressive disease and poor treatment response, whereas suPAR levels ⩾ 4,237 pg/mL was a risk factor for progressive disease and poor response. PAI-1 levels > 4.6 ng/mL was a protective factor for poor response. Multivariate analysis revealed suPAR as an independent risk factor for progression (ORa⁢d⁢j, 13.265; 95% confidence intervals (CI), 2.26577.701; P= 0.006) and poor response (ORa⁢d⁢j, 15.609; 95% CI, 2.221-109.704; P= 0.006), whereas PAI-1 was an independent protective factor of poor response (ORa⁢d⁢j, 0.127; 95% CI, 0.019-0.843; P= 0.033).

CONCLUSIONS

Since miR-10b cannot be used as an independent risk factor for NSCLC progression and treatment response, we developed a model to predict progression using suPAR levels and treatment response using suPAR and PAI-1 levels. Further studies are needed to validate this model.

The Role of Plasminogen Activator Inhibitor 1 in Predicting Sepsis-Associated Liver Dysfunction: An Observational Study

Sepsis-associated liver dysfunction (SALD) is associated with a poor prognosis and increased mortality in the intensive care unit. Bilirubin is one of the components of Sequential Organ Failure Assessment used in Sepsis-3 criteria. Hyperbilirubinemia is a late and non-specific symptom of liver dysfunction. This study aimed to identify plasma biomarkers that could be used for an early diagnosis of SALD. This prospective, observational study was conducted on a group of 79 patients with sepsis and septic shock treated in the ICU. Plasma biomarkers-prothrombin time, INR, antithrombin III, bilirubin, aspartate transaminase (AST), alanine transaminase, alkaline phosphatase, gamma glutamyl transferase, albumin, endothelin-1, hepcidin, plasminogen activator inhibitor-1 (PAI-1), thrombin-antithrombin complex, and interferon-gamma inducible protein (10 kDa) were analysed. Plasma samples were obtained within 24 h after having developed sepsis/septic shock. Enrolled patients were followed for 14 days for developing SALD and 28 days for overall survival. A total of 24 patients (30.4%) developed SALD. PAI-1 with a cut-off value of 48.7 ng/mL was shown to be a predictor of SALD (AUC = 0.671, sensitivity 87.3%, and specificity 50.0%) and of 28-day survival in patients with sepsis/septic shock (p = 0.001). Measuring PAI-1 serum levels at the onset of sepsis and septic shock may be useful in predicting the development of SALD. This should be verified in multicenter prospective clinical trials.

Aging, Cellular Senescence, and Alzheimer's Disease

Aging is the greatest risk factor for late-onset Alzheimer's disease (LOAD), which accounts for >95% of Alzheimer's disease (AD) cases. The mechanism underlying the aging-related susceptibility to LOAD is unknown. Cellular senescence, a state of permanent cell growth arrest, is believed to contribute importantly to aging and aging-related diseases, including AD. Senescent astrocytes, microglia, endothelial cells, and neurons have been detected in the brain of AD patients and AD animal models. Removing senescent cells genetically or pharmacologically ameliorates β-amyloid (Aβ) peptide and tau-protein-induced neuropathologies, and improves memory in AD model mice, suggesting a pivotal role of cellular senescence in AD pathophysiology. Nonetheless, although accumulated evidence supports the role of cellular senescence in aging and AD, the mechanisms that promote cell senescence and how senescent cells contribute to AD neuropathophysiology remain largely unknown. This review summarizes recent advances in this field. We believe that the removal of senescent cells represents a promising approach toward the effective treatment of aging-related diseases, such as AD.

PAI-1 in Diabetes: Pathophysiology and Role as a Therapeutic Target

Hypofibrinolysis is a key abnormality in diabetes and contributes to the adverse vascular outcome in this population. Plasminogen activator inhibitor (PAI)-1 is an important regulator of the fibrinolytic process and levels of this antifibrinolytic protein are elevated in diabetes and insulin resistant states. This review describes both the physiological and pathological role of PAI-1 in health and disease, focusing on the mechanism of action as well as protein abnormalities in vascular disease with special focus on diabetes. Attempts at inhibiting protein function, using different techniques, are also discussed including direct and indirect interference with production as well as inhibition of protein function. Developing PAI-1 inhibitors represents an alternative approach to managing hypofibrinolysis by targeting the pathological abnormality rather than current practice that relies on profound inhibition of the cellular and/or acellular arms of coagulation, and which can be associated with increased bleeding events. The review offers up-to-date knowledge on the mechanisms of action of PAI-1 together with the role of altering protein function to improve hypofirbinolysis. Developing PAI-1 inhibitors may form for the basis of future new class of antithrombotic agents that reduce vascular complications in diabetes.

The Central Role of Fibrinolytic Response in COVID-19-A Hematologist's Perspective

The novel coronavirus disease (COVID-19) has many characteristics common to those in two other coronavirus acute respiratory diseases, severe acute respiratory syndrome (SARS) and Middle East respiratory syndrome (MERS). They are all highly contagious and have severe pulmonary complications. Clinically, patients with COVID-19 run a rapidly progressive course of an acute respiratory tract infection with fever, sore throat, cough, headache and fatigue, complicated by severe pneumonia often leading to acute respiratory distress syndrome (ARDS). The infection also involves other organs throughout the body. In all three viral illnesses, the fibrinolytic system plays an active role in each phase of the pathogenesis. During transmission, the renin-aldosterone-angiotensin-system (RAAS) is involved with the spike protein of SARS-CoV-2, attaching to its natural receptor angiotensin-converting enzyme 2 (ACE 2) in host cells. Both tissue plasminogen activator (tPA) and plasminogen activator inhibitor 1 (PAI-1) are closely linked to the RAAS. In lesions in the lung, kidney and other organs, the two plasminogen activators urokinase-type plasminogen activator (uPA) and tissue plasminogen activator (tPA), along with their inhibitor, plasminogen activator 1 (PAI-1), are involved. The altered fibrinolytic balance enables the development of a hypercoagulable state. In this article, evidence for the central role of fibrinolysis is reviewed, and the possible drug targets at multiple sites in the fibrinolytic pathways are discussed.

Serpins in Hemostasis as Therapeutic Targets for Bleeding or Thrombotic Disorders

Bleeding and thrombotic disorders result from imbalances in coagulation or fibrinolysis, respectively. Inhibitors from the serine protease inhibitor (serpin) family have a key role in regulating these physiological events, and thus stand out as potential therapeutic targets for modulating fibrin clot formation or dismantling. Here, we review the diversity of serpin-targeting strategies in the area of hemostasis, and detail the suggested use of modified serpins and serpin inhibitors (ranging from small-molecule drugs to antibodies) to treat or prevent bleeding or thrombosis.

Targeting PAI-1 in Cardiovascular Disease: Structural Insights Into PAI-1 Functionality and Inhibition

Plasminogen activator inhibitor-1 (PAI-1), a member of the serine protease inhibitor (serpin) superfamily with antiprotease activity, is the main physiological inhibitor of tissue-type (tPA) and urokinase-type (uPA) plasminogen activators (PAs). Apart from being crucially involved in fibrinolysis and wound healing, PAI-1 plays a pivotal role in various acute and chronic pathophysiological processes, including cardiovascular disease, tissue fibrosis, cancer, and age-related diseases. In the prospect of treating the broad range of PAI-1-related pathologies, many efforts have been devoted to developing PAI-1 inhibitors. The use of these inhibitors, including low molecular weight molecules, peptides, antibodies, and antibody fragments, in various animal disease models has provided ample evidence of their beneficial effect in vivo and moved forward some of these inhibitors in clinical trials. However, none of these inhibitors is currently approved for therapeutic use in humans, mainly due to selectivity and toxicity issues. Furthermore, the conformational plasticity of PAI-1, which is unique among serpins, poses a real challenge in the identification and development of PAI-1 inhibitors. This review will provide an overview of the structural insights into PAI-1 functionality and modulation thereof and will highlight diverse approaches to inhibit PAI-1 activity.

Peritoneal effluent MMP-2 and PAI-1 in encapsulating peritoneal sclerosis

BACKGROUND

Recently, the use of effluent matrix metalloproteinase 2 (MMP-2) and plasminogen activator inhibitor 1 (PAI-1) as potential biomarkers of peritoneal fibrosis has been demonstrated during longitudinal follow-up of incident peritoneal dialysis (PD) patients. This study focuses on effluent MMP-2 and PAI-1 as early diagnostic markers in the preceding years of patients who develop encapsulating peritoneal sclerosis (EPS).

STUDY DESIGN

Diagnostic test study.

SETTINGS & PARTICIPANTS

PD patients who developed EPS were compared with controls using a 1:3 case-control design with a minimum PD duration of 57 months.

INDEX TESTS

Dialysate appearance rates of MMP-2 and PAI-1.

REFERENCE TEST

EPS cases identified by 2 experienced nephrologists and a radiologist based on predefined criteria.

RESULTS

11 patients developed EPS within our center. The time course of MMP-2 appearance rates, studied by means of a linear repeated-measures model 4 years prior to the diagnosis of EPS, showed no difference between long-term controls and patients with EPS. In contrast, higher PAI-1 appearance rates were found in patients with EPS compared with controls (P=0.01). At a lag time of 1 year prior to EPS diagnosis, time-specific receiver operating characteristic curve analyses indicated a discriminative ability for PAI-1 appearance rate of 0.77 (95% CI, 0.63-0.91). A discriminative capacity was absent for those of MMP-2.

LIMITATIONS

Low event rate of EPS prevented independent validation in this single-center study.

CONCLUSIONS

Elevated levels of PAI-1 appearance rates are present in patients who develop EPS, pointing to progressive peritoneal fibrosis and sclerosis. The PAI-1 appearance rate has fair discriminative capacity from 3 years prior to EPS diagnosis. Therefore, effluent PAI-1 may aid in monitoring peritoneal fibrosis and serve as a biomarker for EPS.

Targeted therapies in cancer - challenges and chances offered by newly developed techniques for protein analysis in clinical tissues

In recent years, new anticancer therapies have accompanied the classical approaches of surgery and radio- and chemotherapy. These new forms of treatment aim to inhibit specific molecular targets namely altered or deregulated proteins, which offer the possibility of individualized therapies.The specificity and efficiency of these new approaches, however, bring about a number of challenges. First of all, it is essential to specifically identify and quantify protein targets in tumor tissues for the reasonable use of such targeted therapies. Additionally, it has become even more obvious in recent years that the presence of a target protein is not always sufficient to predict the outcome of targeted therapies. The deregulation of downstream signaling molecules might also play an important role in the success of such therapeutic approaches. For these reasons, the analysis of tumor-specific protein expression profiles prior to therapy has been suggested as the most effective way to predict possible therapeutic results. To further elucidate signaling networks underlying cancer development and to identify new targets, it is necessary to implement tools that allow the rapid, precise, inexpensive and simultaneous analysis of many network components while requiring only a small amount of clinical material.Reverse phase protein microarray (RPPA) is a promising technology that meets these requirements while enabling the quantitative measurement of proteins. Together with recently developed protocols for the extraction of proteins from formalin-fixed, paraffin-embedded (FFPE) tissues, RPPA may provide the means to quantify therapeutic targets and diagnostic markers in the near future and reliably screen for new protein targets.With the possibility to quantitatively analyze DNA, RNA and protein from a single FFPE tissue sample, the methods are available for integrated patient profiling at all levels of gene expression, thus allowing optimal patient stratification for individualized therapies.