Stroke is one of the major causes of death and disability, including ischemic stroke, which accounts for 85 -87 % of cases. Currently, there are few treatment options available for minimizing tissue death following a stroke. Emerging data suggest that biomarkers may help improve current clinical outcome of stroke. As such, there is a pressing need to understand the pathophysiology and to explore effective biomarkers following an ischemic brain event. The pathophysiology of ischemic stroke is complex, and majorly involves excitotoxicity, oxidative stress, inflammation, blood-brain barrier dysfunction, apoptosis, etc. Several of the biomarkers are related to these pathophysiologic mechanisms and they may have applications in stroke prediction, diagnosis, assessment, prognosis or treatment. In this review, we summarized the pathophysiology of ischemic stroke and some related biomarkers are examined.

Clinical archives of patient material near-exclusively consist of formalin-fixed and paraffin-embedded (FFPE) blocks. The ability to precisely characterise mutational signatures from FFPE-derived DNA has tremendous translational potential. However, sequencing of DNA derived from FFPE material is known to be riddled with artefacts. Here we derive genome-wide mutational signatures caused by formalin fixation. We show that the FFPE-signature is highly similar to signature 30 (the signature of Base Excision Repair deficiency due to NTHL1 mutations), and chemical repair of DNA lesions leads to a signature highly similar to signature 1 (clock-like signature due to spontaneous deamination of methylcytosine). We demonstrate that using uncorrected mutational catalogues of FFPE samples leads to major mis-assignment of signature activities. To correct for this, we introduce FFPEsig, a computational algorithm to rectify the formalin-induced artefacts in the mutational catalogue. We demonstrate that FFPEsig enables accurate mutational signature analysis both in simulated and whole-genome sequenced FFPE cancer samples. FFPEsig thus provides an opportunity to unlock additional clinical potential of archival patient tissues.

A tumour grows when the total division (birth) rate of its cells exceeds their total mortality (death) rate. The capability for uncontrolled growth within the host tissue is acquired via the accumulation of driver mutations which enable the tumour to progress through various hallmarks of cancer. We present a mathematical model of the penultimate stage in such a progression. We assume the tumour has reached the limit of its present growth potential due to cell competition that either results in total birth rate reduction or death rate increase. The tumour can then progress to the final stage by either seeding a metastasis or acquiring a driver mutation. We influence the ensuing evolutionary dynamics by cytotoxic (increasing death rate) or cytostatic (decreasing birth rate) therapy while keeping the effect of the therapy on net growth reduction constant. Comparing the treatments head to head we derive conditions for choosing optimal therapy. We quantify how the choice and the related gain of optimal therapy depends on driver mutation, metastasis, intrinsic cell birth and death rates, and the details of cell competition. We show that detailed understanding of the cell population dynamics could be exploited in choosing the right mode of treatment with substantial therapy gains.

Background: Formalin fixation and paraffin embedding (FFPE) of patient material remains standard practice in clinical pathology labs around the world. Clinical archives of patient material near-exclusively consist of FFPE blocks. The ability to perform high quality genome sequencing on FFPE-derived DNA would accelerate a broad spectrum of medical research. However, formalin is a recognised mutagen and sequencing of DNA derived from FFPE material is known to be riddled with artefactual mutations. Results: Here we derive genome-wide mutational signatures caused by formalin fixation, and provide a computational method to correct mutational profiles for these formalin-induced artefacts. We show that the FFPE-signature is dominated by C>T transitions caused by cytosine deamination, and has very high similarity to COSMIC signature SBS30 (base excision repair deficiency due to inactivation mutations in NTHL1). Further, we demonstrate that chemical repair of formalin-induced DNA lesions, a process that is routinely performed as part of sequencing library preparation, leads to a signature highly similar to COSMIC signature SBS1 (spontaneous deamination of methylated cytosine). Next, we design FFPEsig, a computational method to remove the formalin-induced artefacts from mutational counts. We prove the efficacy of this method by generating synthetic FFPE samples using 2,780 cancer genomes from the Pan-Cancer Analysis of Whole Genome (PCAWG) project, and via analysis of FFPE-derived genome sequencing data from colorectal cancers. Conclusions: Formalin fixation leaves a predictable mutational footprint across the genome. The application of our FFPEsig software corrects the mutational profile for the influence of formalin, enabling robust mutational signature analysis in FFPE-derived patient material.