Koenig, R. | Search bioRxiv

bioRxiv2019

Modelling TERT regulation across 19 different cancer types based on the MIPRIP 2.0 gene regulatory network approach

BackgroundReactivation of the telomerase reverse transcriptase gene TERT is a central feature for the unlimited proliferation potential of the majority of cancers but the underlying regulatory processes are only partly understood.\n\nResultsWe assembled regulator binding information from different sources to construct a generic human and mouse regulatory network. Advancing our \"Mixed Integer linear Programming based Regulatory Interaction Predictor\" (MIPRIP) approach, we identified the most common and cancer-type specific regulators of TERT across 19 different human cancers. The results were validated by using the well-known TERT regulation by the ETS1 transcription factor in a subset of melanomas with mutations in the TERT promoter.\n\nConclusionOur improved MIPRIP2 R-package and the associated generic regulatory networks are freely available at https://github.com/network-modeling/MIPRIP. MIPRIP 2.0 identified both common as well as tumor type specific regulators of TERT. The software can be easily applied to transcriptome datasets to predict gene regulation for any gene and disease/condition under investigation.

bioinformatics↗

bioRxiv2018

Use of IFNγ/IL10 ratio for stratification of hydrocortisone therapy in patients with septic shock

BackgroundLarge clinical trials testing hydrocortisone therapy in septic shock have produced conflicting results. Subgroups may however benefit depending on their individual immune response.\n\nMethodsWe performed an exploratory analysis of the CORTICUS trial database employing machine learning to a panel of 137 variables collected from 83 patients (60 survivors, 23 non-survivors) including demographic and clinical measures, organ failure scores, leukocyte counts and circulating cytokine levels. The identified biomarker was validated against data collected from patients enrolled into a cohort of the Hellenic Sepsis Study Group (HSSG) (n=162) and two data sets of two other clinical trials. Ex vivo studies were performed on this biomarker to assess a possible mechanistic role.\n\nResultsA low serum IFN{gamma}/IL10 ratio predicted increased survival in the hydrocortisone group whereas a high ratio predicted better survival in the placebo group. Using this ratio for a decision rule, we found significant improvement in survival in the groups of patients being in compliance with the prediction rule (discovery set: OR=3.03 [95% Cl: 1.05-8.75], P=0.031, validation set: OR=2.01 [95% CI: 1.04-3.88], P=0.026). Applying the rule to two further, smaller datasets showed the same tendency. Mechanistic studies revealed that IFN{gamma}/IL10 was negatively associated with pathogen load in spiked human blood. An in silico analysis of published IFN{gamma} and IL10 values in bacteremic and non-bacteremic SIRS patients supported this association between the ratio and pathogen burden.\n\nConclusionIf confirmed prospectively, the IFN{gamma}/IL10 ratio could be used as a rapidly available theranostic for use of hydrocortisone therapy in septic shock.

immunology↗