Biology subjects

Boor, P.

Publications and source records attributed to Boor, P..

21 records · Page 2Linked to original sources

bioRxiv2020

Cell-type apoptosis in lung during SARS-CoV-2 infection

The SARS-CoV-2 pandemic has inspired renewed interest in understanding the fundamental pathology of acute respiratory distress syndrome (ARDS) following infection because fatal COVID-19 cases are commonly linked to respiratory failure due to ARDS. The pathologic alteration known as diffuse alveolar damage in endothelial and epithelial cells is a critical feature of acute lung injury in ARDS. However, the pathogenesis of ARDS following SRAS-CoV-2 infection remains largely unknown. In the present study, we examined apoptosis in post-mortem lung sections from COVID-19 patients and lung tissues from a non-human primate model of SARS-CoV-2 infection, in a cell-type manner, including type 1 and 2 alveolar cells and vascular endothelial cells (ECs), macrophages, and T cells. Multiple-target immunofluorescence (IF) assays and western blotting suggest both intrinsic and extrinsic apoptotic pathways are activated during SARS-CoV-2 infection. Furthermore, we observed that SARS-CoV-2 fails to induce apoptosis in human bronchial epithelial cells (i.e., BEAS2B cells) and primary human umbilical vein endothelial cells (HUVECs), which are refractory to SARS-CoV-2 infection. However, infection of co-cultured Vero cells and HUVECs or Vero cells and BEAS2B cells with SARS-CoV-2 induced apoptosis in both Vero cells and HUVECs/BEAS2B cells, but did not alter the permissiveness of HUVECs or BEAS2B cells to the virus. Post-exposure treatment of the co-culture of Vero cells and HUVECs with an EPAC1-specific activator ameliorated apoptosis in HUVECs. These findings may help to delineate a novel insight into the pathogenesis of ARDS following SARS-CoV-2 infection.

pathology↗

bioRxiv2019

Deep learning detects virus presence in cancer histology

Oncogenic viruses like human papilloma virus (HPV) or Epstein Barr virus (EBV) are a major cause of human cancer. Viral oncogenesis has a direct impact on treatment decisions because virus-associated tumors can demand a lower intensity of chemotherapy and radiation or can be more susceptible to immune check-point inhibition. However, molecular tests for HPV and EBV are not ubiquitously available.\n\nWe hypothesized that the histopathological features of virus-driven and non-virus driven cancers are sufficiently different to be detectable by artificial intelligence (AI) through deep learning-based analysis of images from routine hematoxylin and eosin (HE) stained slides. We show that deep transfer learning can predict presence of HPV in head and neck cancer with a patient-level 3-fold cross validated area-under-the-curve (AUC) of 0.89 [0.82; 0.94]. The same workflow was used for Epstein-Barr virus (EBV) driven gastric cancer achieving a cross-validated AUC of 0.80 [0.70; 0.92] and a similar performance in external validation sets. Reverse-engineering our deep neural networks, we show that the key morphological features can be made understandable to humans.\n\nThis workflow could enable a fast and low-cost method to identify virus-induced cancer in clinical trials or clinical routine. At the same time, our approach for feature visualization allows pathologists to look into the black box of deep learning, enabling them to check the plausibility of computer-based image classification.

cancer biology↗

bioRxiv2017

Genetic regulatory effects modified by immune activation contribute to autoimmune disease associations

The immune system plays a major role in human health and disease, and understanding genetic causes of interindividual variability of immune responses is vital. We isolated monocytes from 134 genotyped individuals, stimulated the cells with three defined microbe-associated molecular patterns (LPS, MDP, and ppp-dsRNA), and profiled the transcriptome at three time points. After mapping expression quantitative trait loci (eQTL), we identified 417 response eQTLs (reQTLs) with differing effect between the conditions. We characterized the dynamics of genetic regulation on early and late immune response, and observed an enrichment of reQTLs in distal cis-regulatory elements. Response eQTLs are also enriched for recent positive selection with an evolutionary trend towards enhanced immune response. Finally, we uncover novel reQTL effects in multiple GWAS loci, and show a stronger enrichment of response than constant eQTLs in GWAS signals of several autoimmune diseases. This demonstrates the importance of infectious stimuli modifying genetic predisposition to disease.

genetics↗