Screening and validation of novel serum panel of microRNA in stratification of prostate cancer

Background

Owing to the heterogeneous nature of prostate cancer (PCa) and errors in the characterization of the disease, researchers have been trying to unveil molecular biomarkers like microRNA (miRNA) as diagnostic markers. The purpose of our study is to demonstrate the precision of a panel of miRNAs as biomarkers with diagnostic potential for risk stratification.

Materials and methods

The present study demonstrates the comparative expression profiles of miRNA-141,-1290,-100, and -335 in both tissue and serum, including Benign Prostate Hyperplasia (BPH) and PCa, with healthy volunteers. Firstly, we demonstrate the expression of all miRNAs in the discovery cohort, including metastasis and benign tissue, and later validate their non-invasive diagnostic potential in BPH and PCa with healthy volunteers. MiRNA was isolated from tissue and serum to be quantified by RT-PCR and analyzed for biomarker potential by receiver operating characteristic (ROC) curve analysis, followed by targetome analysis of each miRNA.

Results

Among the non-invasive miRNA assessed, it was seen that miRNA 141 (P = 0.0003) and miRNA 1290 (P < 0.0001) are oncogenic with significantly higher expression, while miRNA 100 (P = 0.0002) and miRNA 335 are tumor suppressor, in PCa as compared to controls. While for BPH, miRNA 141 (P = 0.003) and miRNA 335 (P = 0.0002) were found to be significantly oncogenic and tumor suppressors, respectively. The analysis of the ROC curve of panel miRNAs (miRNA-141,-1290, and -100) portrayed a significant area under the curve with greater sensitivity and specificity. Moreover, in-silico prediction of their respective targetomes represents their extensive involvement in PCa progression and various other cascades that aid in PCa networks.

Conclusions

To the best of our knowledge, we are going to report for the first time this panel of miRNA that can be used to accurately and efficiently diagnose BPH and PCa patients from healthy males.

Safety and efficacy of tenecteplase in patients with wake-up stroke assessed by non-contrast CT (TWIST): a multicentre, open-label, randomised controlled trial

BACKGROUND

Current evidence supports the use of intravenous thrombolysis with alteplase in patients with wake-up stroke selected with MRI or perfusion imaging and is recommended in clinical guidelines. However, access to advanced imaging techniques is often scarce. We aimed to determine whether thrombolytic treatment with intravenous tenecteplase given within 4·5 h of awakening improves functional outcome in patients with ischaemic wake-up stroke selected using non-contrast CT.

METHODS

TWIST was an investigator-initiated, multicentre, open-label, randomised controlled trial with blinded endpoint assessment, conducted at 77 hospitals in ten countries. We included patients aged 18 years or older with acute ischaemic stroke symptoms upon awakening, limb weakness, a National Institutes of Health Stroke Scale (NIHSS) score of 3 or higher or aphasia, a non-contrast CT examination of the head, and the ability to receive tenecteplase within 4·5 h of awakening. Patients were randomly assigned (1:1) to either a single intravenous bolus of tenecteplase 0·25 mg per kg of bodyweight (maximum 25 mg) or control (no thrombolysis) using a central, web-based, computer-generated randomisation schedule. Trained research personnel, who conducted telephone interviews at 90 days (follow-up), were masked to treatment allocation. Clinical assessments were performed on day 1 (at baseline) and day 7 of hospital admission (or at discharge, whichever occurred first). The primary outcome was functional outcome assessed by the modified Rankin Scale (mRS) at 90 days and analysed using ordinal logistic regression in the intention-to-treat population. This trial is registered with EudraCT (2014-000096-80), ClinicalTrials.gov (NCT03181360), and ISRCTN (10601890).

FINDINGS

From June 12, 2017, to Sept 30, 2021, 578 of the required 600 patients were enrolled (288 randomly assigned to the tenecteplase group and 290 to the control group [intention-to-treat population]). The median age of participants was 73·7 years (IQR 65·9-81·1). 332 (57%) of 578 participants were male and 246 (43%) were female. Treatment with tenecteplase was not associated with better functional outcome, according to mRS score at 90 days (adjusted OR 1·18, 95% CI 0·88-1·58; p=0·27). Mortality at 90 days did not significantly differ between treatment groups (28 [10%] patients in the tenecteplase group and 23 [8%] in the control group; adjusted HR 1·29, 95% CI 0·74-2·26; p=0·37). Symptomatic intracranial haemorrhage occurred in six (2%) patients in the tenecteplase group versus three (1%) in the control group (adjusted OR 2·17, 95% CI 0·53-8·87; p=0·28), whereas any intracranial haemorrhage occurred in 33 (11%) versus 30 (10%) patients (adjusted OR 1·14, 0·67-1·94; p=0·64).

INTERPRETATION

In patients with wake-up stroke selected with non-contrast CT, treatment with tenecteplase was not associated with better functional outcome at 90 days. The number of symptomatic haemorrhages and any intracranial haemorrhages in both treatment groups was similar to findings from previous trials of wake-up stroke patients selected using advanced imaging. Current evidence does not support treatment with tenecteplase in patients selected with non-contrast CT.

FUNDING

Norwegian Clinical Research Therapy in the Specialist Health Services Programme, the Swiss Heart Foundation, the British Heart Foundation, and the Norwegian National Association for Public Health.

A Fokker-Planck Framework for Parameter Estimation and Sensitivity Analysis in Colon Cancer

A new stochastic framework for parameter estimation and uncertainty quantification in colon cancer-induced immune response is presented. The dynamics of colon cancer is given by a stochastic process that captures the inherent randomness in the system. The stochastic framework is based on the Fokker-Planck equation that represents the evolution of the probability density function corresponding to the stochastic process. An optimization problem is formulated that takes input individual patient data with randomness present, and is solved to obtain the unknown parameters corresponding to the individual tumor characteristics. Furthermore, sensitivity analysis of the optimal parameter set is performed to determine the parameters that need to be controlled, thus, providing information of the type of drugs that can be used for treatment.